With the development of the express delivery industry, how to increase the recycling rate of waste cartons has become a problem that needs to be solved. Recycling enterprises began to provide the new recycling mode, door-to-door recycling services, to residents with waste cartons. In this article, we constructed a site selection model for a carton recycling site with the aim of maximizing total profits. Considering the residents’ recycling willingness and the government subsidy earned through the contribution to carbon emission reduction, this model achieves the task of site selection and unit price fixation for carton recycling. We used the particle swarm optimization (PSO) algorithm to solve the model and compared it with the genetic algorithm (GA) for validity testing. PSO algorithm was also used to carry out sensitivity analysis in this model. The proposed model and the results of the sensitivity analysis can be used for decision-making in recycling enterprises as well as for further research on waste recycling and reverse logistics. The model validity analysis and sensitivity analysis are then conducted based on a case study to discuss the influence of relevant parameters in the recycling process, so as to provide reference and suggestions for the decision-making of recycling enterprises. In a research sense, reasonable recycling site selection and carton pricing for recycling enterprises can fill the gap in the development of reverse logistics in the new waste recycling mode.This study is completed from the perspective of a recycling enterprise. The carton recycling site location model includes a single-layer reverse logistics network. See In the carton recycling process, the enterprise needs to set up a carton recycling site in a certain residential area, and post the unit carton recycling price to residents in the area on the official website. Each resident has a psychological expectation about the unit carton recycling price. Only when the recycling unit price offered by the enterprise is higher than his expectation will he participate in the recycling. The enterprise provides door-to-door pickup service from the site to residence for each resident. After serving all the residents, the enterprise takes all the collected cartons to a suburban paper mill and resells them to the mill at the resale price offered by the mill.The enterprise’s carton recycling cost consists of the cost of recycling cartons from residents and the transportation cost of providing door-to-door services. Since the paper mill is usually far away from the city center, its distance is hardly affected by the location of the recycling site in the urban residential area. Therefore, the transportation cost of sending cartons from the site to the paper mill can be considered as fixed and is not included in the model. The income of carton recycling comes mainly from the resale of cartons to the paper mill. On this basis, considering the contribution of recycled cartons to carbon emission reduction, the subsidies offered by the government influenced by the total weight of recycling cartons are set as additional income for the enterprise. In the end, the enterprise’s profit is equal to its income minus its costs.In order to help the enterprise to maximize the total profit including the carbon emission reduction subsidies, the location of the carton recycling site and unit carton recycling price considering residents’ willingness need to be studied through decision making. In summary, the carton recycling site location model is constructed on the basis of comprehensively considering the interests of residents, the recycling enterprise and their contribution to carbon emission reduction.In order to better reveal the core of the problem and improve the generality of the model proposed in this article, this study is based on the following assumptions.1. The proposed carton recycling site location model can be used as the basis for future path optimization, but this model does not consider path optimization. The enterprise provides door-to-door pickup service from site to residence.2. The transportation cost between the site and the paper mill is not considered.3. The quality of cartons of each resident in the area and his psychological expectation about the unit carton recycling price is known, and cartons are assumed to be identical. Residents who have the recycling willingness will hand over all their cartons. At the same time, due to the characteristics of price transparency of the new recycling mode, the unit carton recycling price offered by the enterprise is uniformly consistent for all residents.4. For environmental reasons, the enterprise uses electric cars, which consume no fuel and produce no carbon emissions. The transportation cost by distance is known, which is irrelevant to loads. The unit resale price offered by the paper mill is also known, and the carbon emission subsidy based on the total weight of recycling cartons is certain, too.5. The distance between the site and the resident is assumed to be Euclidean distance, regardless of the fixed cost and capacity limitation of the vehicle for recycling and the influence of the street on the distance.6. We assume that the location of the site in the region is arbitrary, and only one is selected, regardless of the opening cost of the site.The model parameters are defined as follows.Set of all the nodes in the reverse logistics network, Set of all the residents in the reverse logistics network, The unit carton recycling price offered by the enterprise (CNY/Kg).The psychologically expected unit carton recycling price of resident The unit carton resale price offered by the paper mill (CNY/Kg).The distance from resident The weight of the cartons owned by the resident The unit transportation price per kilometer (CNY/Km).The carbon emission reduction subsidy coefficient (CNY/Kg).The decision variable, It can be seen from the problem description that the ultimate goal of the recycling enterprise is to maximize net profit. Therefore, the objective function of the model includes the cost and profit of carton recycling, which is detailed as follows.(1) The cost of recycling cartons from residents.This cost is equal to the sum product of the unit carton recycling price offered by the enterprise and the weight of the carton owned by the residents, and only when residents are willing to sell them. It can be expressed mathematically as:(2) The transportation cost.The transportation cost is equal to the sum product of the round trip distance from the site to the residence and the unit transportation price per kilometer, and only when residents are willing to sell them. It can be expressed mathematically as:(3) Income from reselling.This is the main source of income for the enterprise. Similar to (4) Carbon emission reduction subsidies.λ based on the total weight of recycling cartons  The constraint is mainly the price constraint; we require the unit carton recycling price to be a positive number. It can be expressed mathematically as:(2) Since the enterprise’s main income comes from the resale of cartons, the unit carton recycling price must be less than the unit carton resale price. It can be expressed mathematically as:(3) As mentioned above, residents are willing to participate in carton recycling only when the unit carton resale price offered by the enterprise is higher than their psychological expectation. Therefore, the value of variable PSO is inspired by the study of bird foraging behavior. Its basic idea is to find the optimal solution through the cooperation and information sharing between individuals in the swarm. Each particle separately searches for the optimal solution in the search space, then records and shares the individual optimal value. All particles in a swarm adjust their speed and position based on the current individual optimal value they find and the current global optimal value shared by the whole swarm .There are many applications of PSO in the logistics field. In view of the above carton recycling site location model, combined with previous application experience, we applied PSO algorithm to solve the model.The basic principles of PSO  are as fIn the feasible solution space of a D-dimension, there is a particle population P, in which there are Each particle has a velocity and a position, and the initial particle is randomly generated as follows:In the formula, In the formula, Based on the principle of PSO, we now design the specific steps of using PSO in the carton recycling site location model.Step 1: read the x and y coordinates of residents in the data file, as well as the weight Step 2: set parameter values in the PSO algorithm, including the maximum number of iterations Step 3: determine the particles encoding. In this research, the x and y coordinate location of the recycling site and the unit carton recycling price are decision variables. Then Step 4: calculate the Euclidean distance from the site to each resident, then the fitness of each particle Step 5: set the position of particle Step 6: the iteration begins, each particle in the population updates its position and velocity according to Step 7: after the iteration, the global optimal solution in the last generation is output as the result of algorithm calculation.The Solomon benchmark is a widely recognized dataset that is commonly used to study issues related to vehicle routing problems (VRP). In this section, a Solomon benchmark example set with adjusted parameters  is used The comparison of examples used in our calculation are shown in Such comparison may be related to the coding methods of the solutions and the characteristics of the two algorithms. Firstly, from the perspective of the coding method, when using PSO to solve the recycling site location problem, only three digits are needed, and the calculation results of Matlab are automatically accurate to four decimal places. GA coding generally adopts binary coding, and uses a long array composed of only 0 and 1 to express the solution of the site location problem , which iThe most important feature of this model is that the number of residents it serves depends on the unit carton recycling price. When we validate the model, we compare it to a model that serves all residents, which implies the unit carton recycling price is set as the highest to meet all residents expectations. We assume that the unit transportation cost is 0.2 CNY/Km, and the carbon emission reduction subsidy coefficient is still temporarily set to zero.After verifying the effectiveness of PSO and the validity of our proposed model, we will complete the analysis and discussion of the proposed carton recycling site location model, that is, sensitivity analysis. Among them, the large-scale calculation example RC207 will be used as the sensitivity analysis, specific data of RC207 example are in the First, we explore the influence of the unit carton resale price and the unit price of transportation per kilometer on the unit carton recycling price and the final total profit of the enterprise, without considering the carbon emission reduction subsidy briefly. According to the actual unit carton recycling price in China, it generally fluctuates between 2 and 3 CNY/Kg, so the unit carton recycling price is set to fluctuate within the range. In addition, we consider a 50% fluctuation in the unit transportation cost. The specific calculation results are shown in The plateaus in the curve of the unit carton recycling price comparison reflect the precise calculation of the proposed model and algorithm for the maximum benefits of the enterprise. To specifically explain this point of view, through the observation of the example data, we can find that the psychologically expected value of unit carton recycling price of some residents only accounts for a small portion, and the marginal benefit of the enterprise to rise the unit price to serve these residents may be less than the transportation cost, which is the reason for the plateaus in the curve. With the rise of the unit carton resale price, when it reaches a certain value, the curve may enter a new plateau. In addition, due to the large number of residents in the RC207 example, the total profit curve remains steadily growing even though there are many plateaus and sharp increases in the unit carton recycling price curve. That is to say, although the site selection and pricing strategy of an enterprise are very sensitive to the influence of other factors, the huge number of services determines that its total profit will not be greatly affected.We choose a scenario where the unit transportation price per kilometer is 0.2 CNY/Km, and discuss the influence of the carbon emission reduction subsidy coefficient on the overall profit and pricing strategy of the enterprise. See Since the sensitivity analysis considers all scenarios with varying parameter combinations, we found that even the PSO algorithm, which is highly stable in the validity test, will repeatedly calculate two results under some scenarios with parameter combinations. See These results have some implications for our proposed model and algorithm. At the model level, the two results show that although enterprises set different carton unit recycling price, the final total profits are almost identical, which confirms a point: if the number of residents is large enough, small fluctuations in unit carton recycling price considering the psychological expectations of a small number of residents will not affect the enterprise’s overall total profit. At the algorithm level, although the total profit of the two results are similar, the solution with low profit may still be suboptimal. In this case, the solution with the higher profit should be chosen. this also tells us that the PSO algorithm needs to be strengthened.From the sensitivity analysis, we can know that a higher unit carton resale price and a lower unit transportation price can promote the enterprise to raise the unit carton recycling price and collect more cartons, thus achieving the two goals of contributing to carbon emission reduction and profit maximization. In addition, we came to several important conclusions:1. The carton pricing strategy is sensitive to cost variables, and higher carbon emission reduction subsidy may encourage the enterprise to raise the unit recycling price and collect more cartons.2. Although the enterprise’s pricing strategy is affected by other factors, the total profit remains stable in the end because the number of residents is large enough. The different pricing strategies made by considering the psychological expectations of a small number of residents towards the carton recycling unit price will not affect the enterprise’s overall total profit.3. It can be concluded from the two points above that the overall decision of an enterprise is influenced by many aspects. Therefore, it has important reference significance to set location selection and pricing as decision variables simultaneously. Compared with first pricing and then site selection or first site selection and then pricing, our approach in theory has more comprehensive consideration and can help to find better solutions.4. The deviation of the PSO algorithm in the sensitivity analysis on the one hand confirms the second conclusion above, and on the other hand shows that the classical PSO algorithm adopted in this paper still has instability in large-scale site selection research. The latest improved PSO algorithm can be used or combined with the algorithm based on evolutionary strategy in future site selection research.5. While we utilized a calculation example in the sensitivity analysis, its application to real-world data in the future can further unlock its practical value.Overall, this model offers valuable insights for recycling enterprises. Operating costs for such enterprises comprise multiple components, which at times can be mutually challenging. Our study integrates site selection and carton pricing strategies to encourage enterprises to approach cost-related issues from a comprehensive standpoint. Moreover, the matter of carton pricing and subsidies involves a complex interplay between enterprises, government entities, and residents. Although this paper did not delve deeply into the intricacies of this game, relying instead on simplified assumptions, future research can explore the dynamics of this game within reverse logistics in greater detail. By effectively combining this aspect with logistics optimization, a more comprehensive theoretical framework can be established.Waste cartons recycling is a huge benefit to the economy and the environment. The development of the Internet has given birth to new carton recycling mode. Considering the characteristics of this new carton recycling mode and the in-applicability of the previous location research models for it, we reconstruct the carton recycling site location model from the perspective of recycling enterprises. In the model, the unit carton recycling price and site selection are both decision variables, residents’ willingness to recycle considering their psychological expectations regarding the unit carton recycling price and the subsidy income of carbon emission reduction are fully considered. The following are the specific conclusions of our study.Firstly, we have involved the application of PSO algorithm to the solution of the model. In the algorithm validity test, the performance of PSO is more stable than that of GA, and better solutions can be found. Secondly, we validate the model by comparing it to a model that serves all residents, which shows the significant increase in total profit when setting location selection and pricing as decision variables simultaneously. Finally, we did a sensitivity analysis which shows that although the pricing strategy of an enterprise is sensitive, the total profit can remain stable rather than change dramatically after undergoing a fluctuation in pricing strategy. This is because the number of residents is large enough.Firstly, our research innovatively combines location selection and carton pricing decisions together for collaborative optimization, which can avoid the sub-optimal solution when the two decisions are optimized separately. Secondly, the model proposed by us has high universality and can incorporate other decisions such as inventory optimization or route optimization for more systematic and comprehensive optimization in the future.The carton recycling site selection model proposed in our study fills the gap in the development of reverse logistics in the new waste recycling mode and lays a good foundation for the exploration of site selection in the field of waste recycling. At the same time it provides a great reference value for decision-making in recycling enterprises: although enterprises have very mature research and use experience on site location selection and pricing decision-making in reality, these two decision-making tasks sometimes belong to two different departments, which may lead to the generation of sub-optimal solutions, and thus increase the operating costs of enterprises. In our proposed model, the idea of collaborative optimization between the two can provide new thinking for the operation of enterprises.Future studies can make some improvements in these ways: leaving the number of sites unfixed to solve a multi-site location problem considering site opening costs, combining path optimization and site location together to build a site location route optimization model.10.7717/peerj-cs.1519/supp-1Supplemental Information 1Click here for additional data file.10.7717/peerj-cs.1519/supp-2Supplemental Information 2Click here for additional data file.10.7717/peerj-cs.1519/supp-3Supplemental Information 3Click here for additional data file.10.7717/peerj-cs.1519/supp-4Supplemental Information 4Click here for additional data file.10.7717/peerj-cs.1519/supp-5Supplemental Information 5Click here for additional data file.10.7717/peerj-cs.1519/supp-6Supplemental Information 6Click here for additional data file.10.7717/peerj-cs.1519/supp-7Supplemental Information 7Click here for additional data file.10.7717/peerj-cs.1519/supp-8Supplemental Information 8Click here for additional data file.


Assessing stressful life events in large-scale epidemiologic studies is challenged by the need to measure potential stressful events in a reasonably comprehensible manner balanced with burden on participants and research staff. The aim of this paper was to create a short form of the Crisis in Family Systems-Revised (CRISYS-R) plus 17 acculturation items, a measure that captures contemporary life stressors across 11 domains. Latent class analysis (LCA) was used to segment the sample of 884 women from the PRogramming of Intergenerational Stress Mechanisms (PRISM) study experiencing different patterns of exposure to stressful events and identify items from each domain that best discriminate between individuals with different patterns of stressful-event exposures (high vs. low stress exposure). The results from the LCA, in conjunction with the expert opinions provided by the original developers of the CRISYS, yielded a 24-item item short form (CRISYS-SF) with at least one question from each of the original domains. Scores on the 24-item CRISYS-SF had high correlations with scores on the 80-item CRISYS.The online version contains supplementary material available at 10.1007/s12144-021-02335-w. Stress can be conceptualized and measured in different ways depending upon the research goals   and expert consensus, while maintaining the breadth of domains covered by the foundational, 80-item CRISYS measure as well as the acculturation items. Specifically, the goal of LCA is to find the mixture that optimally differentiates between subgroups of people, whereby the homogeneity of experiences within class and the heterogeneity of experiences across classes are maximized. Based on this understanding of the independence of life stressors and the occurrence of qualitatively distinct constellations of stressful events, the purpose of this paper is to create a short form of the 80-item CRISYS (CRISYS-SF) using LCA. Previous work on developing a short form for the Facebook Addiction Test demonstrated the utility of using LCA as a model-based criterion for investigating sources of variance in multifaceted constructs that are usually summed to a single score  study is an ongoing prospective pregnancy cohort that recruited women from prenatal clinics in New York City and Boston beginning in 2011. At the time of this analysis, 1091 pregnant women had been enrolled; we excluded 207 women that did not complete the CRISYS, resulting in an analytic sample of 884 women. The 63-item CRISYS-R, as well as the additional 17 acculturation items, was completed during pregnancy in a face-to-face interview (96.5%) or by telephone (3.5%) in their preferred language ; if a woman completed the CRISYS during more than one pregnancy, only the first response was considered. The sample is socioeconomically and demographically diverse with approximately 20%, 40% and 30% of women self-reporting White/non-Hispanic, Black/Black-Hispanic, and Hispanic/non-Black race/ethnicity, respectively (Table k classes) was based on empirical fit indices/tests and the overall utility of the model in distinguishing between items that differentiate between high and low stress individuals within domain. In accordance with insights from Tein et al.  especially when there are a large number of indicators relative to the total sample size . The original aim was to retain the two items from each domain with the greatest discrimination values. After the initial evaluation of the model-based approach, items were added or removed based on expert consensus as well as consideration of the discrimination values for items that were not in the top two of their respective domains. Reliability of the CRISYS-SF was evaluated using α  were invited to be authors on the manuscript so that they would contribute to the background, the expert validation of retained/dropped items and the interpretation of the results. Co-Author Reyes was involved in the development of the acculturation items and has years of personal experience administering the questionnaire to participants. Co-Author Wright was among the first scientists to incorporate the CRISYS in her longitudinal studies of stress and co-chaired an NHLBI expert panel on measurement that recommended the CRISYS to measure stress in studies of asthma.The enumeration process based on the BIC, LMR, VLMRT, BLRT, and class proportions resulted in the selection of a two-class model being chosen as having the best fit relative to the one- and three-class model. Table Did you have trouble with social service agencies? was not retained because the expert panel believed, based on experience administering the measure that there was confusion among participants of which agencies this entailed. Did your income decrease by a lot? and Did you go without food because you didn't have the money to pay for it? were added despite not having the highest within-domain discrimination values as there was consensus that direct questions related to income changes and food insecurity would be relevant for future health disparities research. Did anyone in your family go to jail? was dropped because Did anyone in your family get arrested? was retained and the expert panel believed there was ambiguity between jail and prison, being arrested was more direct, and retaining both of these items would have been redundant—Was anyone in your family pulled over or questioned by the police? was then added as this was felt to be a stressor, particularly to certain racial/ethnic groups regardless of whether this resulted in an arrest. Did a family member die? was added by the expert panel because this event is included on the majority of life event measures. Did your regular childcare arrangements change in any way? was added because this was deemed an important topic unrelated to any of the retained items. Were you a victim of a crime while you were in your home? was dropped because more specific questions related to neighborhood violence and emotional/physical abuse had already been retained. The modifications in conjunction with the LCA resulted in a 24-item CRISYS-SF, which included at least one item from each of the original 11 domains.Table SSFactors including questionnaire length contribute to respondent burden and can contribute to reduced response rate, incomplete data, and consequent reduced data quality in epidemiologic studies . Although groups of individuals may experience several life stressors captured within a particular CRISYS domain, items within a domain are best thought of as capturing qualitatively distinct stressors rather than constituting a scale. The distinction between a typical group of scales, which would be analyzed with common continuous latent trait methods , and the CRISYS domains is typified by the theoretical independence of the stressors. Life stressors, unlike items in a depression or anxiety inventory, are not captured by an underlying continuous latent variable , which has associated assumptions like local independence and monotonicity, whereby items are independent of one another given the individual’s score on the latent variable and the probability of endorsing an item increases as a function of the underlying latent trait and is related to the item parameters Reckase, . These iThe optimal latent class solution was obtained by segmenting the original sample into two subgroups . Following enumeration, items were considered for inclusion in the CRISYS-SF based on their LCA discrimination values . The results from the LCA, in conjunction with the expert opinions provided by the authors of this paper, yielded a 24-item item short form with acceptable reliability. The total scores for the CRISYS-SF had a Spearman correlation with the total scores of the CRISYS equal to 0.89. This provided evidence of the robustness of the CRISYS-SF, which included only 30% of the original items in the CRISYS. Furthermore, each of the domains was represented by at least one item, which extends the breadth and integrity of the CRISYS to the CRISYS-SF. As noted before, the construction of this short form or any life stressor inventory is particularly challenging because stressful life events do not beget fulfillment of item-level assumptions related to continuous underlying latent variable modeling. This study involved to the use of LCA as a method for pruning the CIRSYS, but researchers will likely find different latent class solutions with subsequent latent class models using the final CRISYS-SF items. Therefore, researchers interested in in using the CRISYS-SF to investigate relationships between stressful life events and health outcomes are encouraged to explore differences in using cumulative risks represented by sum scores as predictors versus latent class regression.act together to have an impact on health. This paper demonstrates the type of statistical approach necessary to have a valid, reliable and reproducible way to capture SDoH information that relates directly to biological mechanisms affecting health while, at the same time, highlighting opportunities for intervention. The CRISYS-SF offers promise as a way to screen for SDoH in a clinical setting, identify resources for individual areas of stress, and refer individuals for targeted intervention. Further, the CRISYS-SF can be used to investigate statistical relationships between SDoH and adverse health conditions over time, and the impact of interventions.Development of a valid and reliable abbreviated survey to assess stressful life events has other implications. The evidence of a relationship between stress and health has led to a relatively recent awakening of interest among health care professionals and health care financing entities. A growing consensus is gaining traction for health care providers to systematically identify and then intervene in sources of stress  to improve health or prevent disease. A recent position paper of the US Preventive Services Task Force calls for “valid and reliable screening tools” for use in primary care and evidence that “screening…lead[s] to reduced morbidity, mortality or both from relevant health conditions Supplementary file2 (DOCX 138 KB)Below is the link to the electronic supplementary material.


In vitro study showed that CH was released in a sustained-release manner for 2 weeks. The concentration of CH in the retina, choroid/retinal pigment epithelium, sclera, iris, and aqueous humor was determined by high-performance liquid chromatography. Transscleral administration was able to deliver CH to the posterior segment  rather than the anterior segment , while eyedrops delivered CH only to the anterior segment. Transscleral administration could deliver CH to aqueous humor at half the concentration versus treatment with eyedrops and reduced intraocular pressure (IOP) at 1 day after implantation; however, the IOP-lowering effect was not sustained thereafter. In conclusion, transscleral drug delivery may be a useful method for the reduction of IOP. Notably, the aqueous concentration must be equal to that delivered by the eyedrops, and this approach might be preferable for drug delivery to the posterior segment of the eye.The objectives of this study were to develop a sustained-release device for carteolol hydrochloride (CH) and investigate any potential difference in the intraocular distribution of this agent between the transscleral administration of the device and treatment with eyedrops. The device was formulated with photocurable resin, poly (ethyleneglycol) dimethacrylate, to fit within the curve of the rabbit eyeball.  The choice of route depends on convenience and compliance, as well as the pharmacokinetic and pharmacodynamic profiles of drugs. We previously developed a transscleral drug delivery device composed of photopolymerized poly (ethyleneglycol) dimethacrylate (PEGDM) . The devin vivo .Dr Nobuhiro Nagai was supported by Data will be made available on request.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.The authors have no conflict of interest to declare.


Vision-simulated imagery―the process of generating images that mimic the human visual system―is a valuable tool with a wide spectrum of possible applications, including visual acuity measurements, personalized planning of corrective lenses and surgeries, vision-correcting displays, vision-related hardware development, and extended reality discomfort reduction. A critical property of human vision is that it is imperfect because of the highly influential wavefront aberrations that vary from person to person. This study provides an overview of the existing computational image generation techniques that properly simulate human vision in the presence of wavefront aberrations. These algorithms typically apply ray tracing with a detailed description of the simulated eye or utilize the point-spread function of the eye to perform convolution on the input image. Based on the description of the vision simulation techniques, several of their characteristic features have been evaluated and some potential application areas and research directions have been outlined. Vision is one of the main mechanisms used to perceive the world. By capturing the light reflected from the surrounding objects, the brain can gather a wide range of information and support a variety of tasks in everyday lives.The organs that enable vision are the brain and human eye. The human eye acts as an optical system and is responsible for collecting incoming light rays. It is a slightly ovoid organ comprising the cornea and crystalline lens as its main refractive components. The incoming light rays pass through these elements and focus on the back of the eye (the retina), where millions of light-sensitive photoreceptors (the rods and cones) are activated to sense this light. The information thus collected is then forwarded to the brain, which performs various postprocessing tasks to correct the optical limitations of the eye, generating a final image as output, referred to as vision.The performance of the human eye is heavily affected by a variety of factors despite its robust optical design . OpticalAn important and highly unfortunate aspect of visual aberrations is that they affect every living person; this is because the eye’s inherent complexity causes some aberrations even in otherwise healthy vision . In addiThe problem of simulating the performance of an optical system is not new in the field of computer graphics. A prominent component of plausible visual simulations is the proper use of the depth-of-field (DOF), for which researchers have developed a large set of different rendering algorithms . Most exRay tracing for image synthesis has a long history in computer graphics. It is a technique that utilizes the rays recursively bouncing around in the scene to collect color information through the intersection of these rays with objects and light sources. A large number of ray-tracing approaches have been proposed to address the computational complexity of the problem in an efficient manner. These methods are mainly categorized as forward ray tracing  and backward ray tracing . However, there also exist hybrid algorithms that combine the advantages of these two approaches. Covering the details of these algorithms is beyond the scope of this survey. The reader is referred to ref.  for a moSeveral studies have utilized ray tracing for human vision simulations. Table The first method for simulating human vision via ray tracing was introduced by Mostafawy et al. . Their iRegarding the description of the eye, the approach of Mostafawy et al.  is builtIn the approach proposed by Mostafawy et al. , the imaDias et al.  circumveThe final simulation is then obtained by projecting the resulting spherical image onto the image plane using an orthographic projection matrix. Alternatively, Fink and Micol  demonstrThe distributed ray-tracing algorithm described above randomly samples the anterior lens during the construction of ray bundles. Such an approach can potentially lead to a large number of rays being blocked by the pupil, as shown in Fig. To overcome this issue, Wu et al.  proposedThe gist of their solution is to sample the entrance pupil directly during the ray-generation step, which guarantees that no sample is blocked by the physical pupil. This is called a camera subpath. Rays are also initiated from the light sources of the scene in the light subpath. The algorithm then attempts to connect the various hits along these two subpaths. If an unblocked connection can be made, the starting location of the ray on the entrance pupil is traced through the eye model to find the corresponding image-space projection. Such a sampling strategy can also be combined with distributed ray tracing, as shown in Fig. Chromatic aberration results from the wavelength-dependent refraction index of the optical elements of the eye, leading to a different focus distance per wavelength of light. Cholewiak et al.  studied A different yet more physically correct approach of simulating chromatic aberration is to assign a different wavelength to each ray and compute the wavelength-dependent refraction index of the simulated optical elements during ray tracing. This approach was adopted in the algorithm of Steinert et al. , which wThe distributed ray-tracing approach described thus far ignores the wave-related effects. Although the effect of diffraction is generally small with large pupil diameters, the severity of its impact increases as the pupil size decreases. Therefore, not considering these effects can significantly reduce the quality of the simulation.To simulate diffraction, the Heisenberg uncertainty ray bending (HURB) method  was emplAll the ray-tracing algorithms described above model the eye using a complex system of spherical or aspherical elements. Although such a description has several benefits (such as the ability to support a wide range of eye conditions and chromatic aberration), it also contributes to lengthy computation times; this makes the process of simulating simple eye aberrations unnecessarily complex.To overcome these issues, Wang and Xiao  used a sIn contrast to the previous case, there are situations where the main concern is quality and not the cost of ray tracing. While the aspheric surfaces and multiple refractive zones in the previous techniques can be used to simulate a wide range of eye conditions, the model is not detailed enough to accurately capture every nuance of a real human eye.To construct a model that can simulate arbitrary conditions, the use of the circle polynomials of Zernike  was propThe main disadvantage of this approach is the cost of calculating intersection points. The iterative nature of the Newton–Raphson method and the complexity of evaluating surface points, both play an important role in this problem. The use of polygon meshes was proposed by Wei et al.  to increThe stochastic nature of distributed ray tracing introduces noise into the resulting simulations. The impact of noise can be reduced by increasing the number of rays traced per pixel; however, this approach causes an inordinate increase in computation times. Denoising  is anothTo overcome this issue, Vu et al.  proposedIn addition to ray tracing, another main method for visual aberration simulations is via postprocessing filters that operate on prerendered images. Performance often being a key factor, these approaches are usually employed in rasterization-based systems. Rasterization works by taking a set of input primitives  and determining the list of image pixels that each primitive covers. Per-object transformations and camera projections are handled by transforming the vertices of the input primitives using 4 × 4 transformation matrices. A pinhole camera model is often assumed, with physical camera-based effects simulated via postprocessing. Correct depth ordering is usually resolved using a per-pixel depth buffer, which outputs a depth map, and is often utilized by image-space filters. For a more elaborate explanation of rasterization-based image synthesis, the reader is referred to ref. .Many algorithms operate in the image space to produce vision-simulated images. Table One of the earliest image-space approaches simulating visual aberrations was based on convolution with the PSF of the eye, which is the diffraction pattern of an ideal point source. Given the PSF, the eye can be treated as a black box, and vision can be simulated as the superposition of every object point modulated by the PSF of the optical system. This process is illustrated in Fig. Therefore, devising a method for the computation of the PSF is necessary. Even with the goal of simulating vision using convolution, ray tracing can still be used to obtain the PSF. Paraxial ray tracing with a measured corneal topography map was used by Camp et al.  to obtaiAlthough the approach by Camp et al. was an important milestone for convolution-based vision simulation, it has several limitations. Specifically, the simplified eye model removes the inherent aberrations of the eye, which is further exacerbated by the inability of the paraxial approach to correctly simulate wavefront aberrations and diffractions. Greivenkamp et al.  demonstrThe two convolution-based approaches described above focus on 2D images. Although the ability to simulate a single object plane holds tremendous value, extending the approach to cover the entire focal region could provide a more holistic image of the individual’s vision. Furthermore, such an extension could also facilitate the simulation of 3D scenes and open the door for creating fully immersive simulations.Motivated by these reasons, Barsky  introducSimilar to previous works, Barsky used ray tracing to compute the OSPSFs. However, instead of utilizing the eye model directly, Barsky proposed using wavefront aberrations of the eye to calculate perturbed ray directions. In their work, aberration functions are obtained using a Shack-Hartmann wavefront sensor, allowing vision to be simulated without measuring the physical properties of the eye.Given a set of OSPSFs, vision is simulated by partitioning the input rendering into distinct depth regions and then convolving each slice with the OSPSF corresponding to its central depth value. This approach has a disadvantage—if an object spans several different depth regions, the convolution process may include discarded pixel values along the borders of the depth regions. Barsky referred to this phenomenon as a discretization artifact. To eliminate these artifacts, edge detection can be employed for object identification . By inclIf the wavefront aberrations of an optical system are known, the PSF can also be computed using diffraction theory. To this end, Watson  used theMore recently, Csoba and Kunkli  proposedAll the image-space methods described above used the convolution theorem (convolution in the frequency domain) to produce the final images. Although such an approach works well with 2D inputs or depth-based partitioning, it fails to accurately represent the spatially varying nature of the PSF. Furthermore, processing multiple slices is prohibitively expensive in interactive environments.To overcome these limitations, Csoba and Kunkli  utilizedTo produce a dense PSF, their approach builds on Barsky’s concept . The PSFAs described in the subsection on chromatic aberration (Vision simulation using ray tracing), chromatic aberration stems from the wavelength-dependent refractive index of the eye. As a result, the PSF of the eye also depends on the wavelength of light. An example of a set of chromatic PSFs is shown in Fig. The chromatic PSF can be computed in multiple ways. In the case of ray-traced PSFs, the same strategies described in the Vision simulation using ray tracing section, can be employed. The situation is somewhat more complicated with diffraction theory, in which the wavelength-dependent aberration coefficients need to be obtained to compute the corresponding PSFs. Watson  and CholAlternatively, if the eye structure is available, aberration coefficients can also be obtained using ray tracing and least-squares coefficient fitting, the applicability of which was demonstrated by Csoba and Kunkli . Their aA common limitation of the image-space convolution methods described above is that they ignore the angle of incidence during the PSF calculation and consider the aberrations (and the corresponding PSFs) to be uniform across the entire visual region. This approach is often referred to as the isoplanatic assumption , 53. WhiTo overcome this issue, Rodríguez Celaya et al.  used theThe algorithm of Rodríguez Celaya et al. was later extended by Gonzalez Utrera  to suppoSimilar to ray tracing, the computation time for convolution-based approaches can be reduced by confining the simulation to certain types of aberrations. Such approaches typically employ a simplified kernel that only approximates the true PSF and displays some favorable properties that enable a more efficient convolution.Rokita  proposedOne of the main issues with the repeated-filtering approach is the poor mapping to modern GPUs. This is because current GPUs are severely affected by the speed of memory transactions, and repeated filtering requires a significant number of passes to produce a result for highly defocused images. Consequently, most modern algorithms employ larger kernels that involve only a small number of render passes.Barbero and Portilla  approximAlthough a single-pass filtering approach has significant benefits over several considerably small passes, the requirement for a large number of samples still poses some limitations on the extent of possible blurring at a reasonable speed. In computer graphics, this problem is typically solved by using separable kernels –56, whicOne of the most well-known separable kernels is the Gaussian kernel, which was used by Tang and Xiao  as a subThe approach of Tang and Xiao utilizes a small neural network to calculate the radii of the blur ellipse for each input pixel, which they refer to as the blur distribution function (BDF). They employ a schematic eye model to build a custom training dataset via ray tracing. The neural network uses the focal length, pupil size, object distance, and angles of incidence as input, and thus, their algorithm naturally supports off-axis aberrations.One of the biggest drawbacks of Gaussian kernels is their significant deviation from the true PSF. To overcome this issue, the use of complex phasors has been proposed as a separable filtering approach  for DOF Complex phasors can also be used for vision simulation, as demonstrated by Csoba and Kunkli . Their aImage-based vision simulation algorithms are typically implemented as a postprocessing filter for input images that were originally rendered using pinhole camera models. This approach results in a one-to-one mapping between object space and image space, which fails to properly account for the partially covered object points that are invisible on the pinhole image. The problem is visualized in Fig. This issue is typically solved by using layered inputs , 58 to pA different approach for simulating distributed effects is to place virtual viewpoints on the pupil and render the scene from each viewpoint using rasterization. This technique, often referred to as the accumulation-buffering method, was introduced by Haeberli and Akeley . A schemTo simulate vision using accumulation buffering, Kakimoto et al.  proposedIn previous sections, the working principles of the most common approaches for simulating aberrant human vision were described. In this section, several of the most important properties, which can guide the selection of the correct approach for a given problem, are discussed and compared. An overview of these properties is provided in Table One of the key differentiators between ray-tracing and image-space approaches is the required input data. Most image-space approaches rely on PSFs, which are comparatively simple to acquire using a wavefront aberrometer, as demonstrated in several recent studies. Furthermore, wavefront aberrations are typically described using the well-understood and standardized approach of Zernike coefficients , which cRay-traced vision simulation algorithms, however, require a complete eye model to support arbitrary visual aberrations. Such a description can be obtained by utilizing an existing schematic eye model, but the uses of such models are limited because they are not representative of the individual’s eye structure. It is possible to extend the schematic eye model using additional optical elements to simulate glasses; however, this approach is still not ideal if the true physical characteristics of the simulated eye are important. Taking measurements for all required eye parameters is a viable alternative and is often performed in population studies (such as in ref. ). HoweveRecently, the use of an optimization-based eye-structure estimation process was proposed by Csoba and Kunkli  as an efThe behavior of the eye with varying pupil sizes and focus distances is also of interest. While exploring the performance of the eye in one state is tremendously useful in itself, aberrations vary greatly as the pupil diameter or state of accommodation changes. We also demonstrate the effects of changing the pupil diameter and focus distance in Fig. Handling a variable pupil size is trivial for all the approaches presented in this study. First, the pupil diameter is already a part of the model when the physical eye structure is used. Second, methods that rely on the CoC include the diameter in the definition of the CoC. Finally, image-space approaches that use Zernike coefficients to calculate the PSF can use scaling formulas to obtain the corresponding Zernike coefficients .Refocusing, however, is a significantly more difficult problem. During accommodation, the shape of the crystalline lens changes drastically. As a result, even if the full physical structure of the relaxed eye is available, only the exact physical properties of the focused lens can be estimated. This issue is even more severe for algorithms that rely on wavefront aberrations because these algorithms do not possess any information about the shape of the eye’s optical elements. Consequently, the only viable approaches that we are aware of are extra aberration measurements and eye structure estimation .HOA have a significant impact on the overall quality of vision , as showThe complex origin of HOA hinders ray-tracing methods from being able to capture HOA when the full eye structure is not used. Furthermore, the deformation of the cornea requires special treatment even if a complete eye model is used, as a single aspherical element lacks the flexibility to represent the arbitrary deformations of a real cornea.The issue is less severe for image-space approaches because including HOA in the PSF is easily accomplished using Zernike coefficients. However, the same cannot be said about the various approximation approaches , as the kernels that they employ are specifically chosen to approximate low-order aberrations .Another crucial aspect of aberrations is their wavelength-dependent nature. As demonstrated by Cholewiak et al. , chromatAs described in chromatic aberration subsection (in vision simulation section using ray tracing), simulating chromatic aberration is trivial with ray tracing if a full eye model is employed. The ray-tracing process can be extended by introducing a wavelength dimension and sampling, to correctly model the full spectrum. However, even without the full-eye model, it is possible to acquire correct simulations using the simplified ray-tracing approach of Wang and Xiao , which aRegarding image-space approaches, simulating chromatic aberration is equivalent to using a wavelength-dependent PSF kernel. The main problem is the calculation of the necessary Zernike coefficients, which can be solved by using a conversion formula—as demonstrated by Watson . HoweverMany existing aberration simulation techniques focus on the central area of the visual field and only attempt to simulate on-axis aberrations of the eye. Such an approach is often referred to as isoplanatic approximation, and the way it works is described by Barsky —when theWhen using physically accurate ray tracing and a complete eye model, the simulation of off-axis vision is a natural result of the rendering approach. Furthermore, the outputs are accurate as well, provided the correct retina shape is used. However, it is impossible to correctly simulate peripheral vision using a simplified ray-tracing model.To simulate off-axis aberrations using PSF-based convolution, first the off-axis PSFs must be obtained and subsequently, the corresponding aberration descriptions. Similar to refocusing, these aberrations vary heavily from person to person and depend greatly on the physical properties of the eye. Thus, the only way of obtaining these coefficients is through measurements and eye structure estimation. However, even if the off-axis aberrations are known, very few PSF-based algorithms are constructed with these considerations. Among the algorithms described in this paper, per-pixel interpolation of the PSF grid is the only approach that is capable of handling the spatially varying off-axis PSF.Finally, vision simulation algorithms that are based on PSF approximation can more easily support off-axis vision because such approaches only need to obtain the per-pixel CoC. To this end, the BDF-based approach of Tang and Xiao  can be uAnother critical aspect of these algorithms is their overall performance. Vision simulation is typically employed as part of a larger system with a specific end goal, and throughput is often a key aspect of these applications. In particular, interactive eye disease simulation, vergence-accommodation conflict reduction, vision testing, aberration-correcting displays, and machine-learning data generators are all applications in which the total computation time of the vision simulation step is a serious limiting factor.The cost of producing a single image depends significantly on the complexity of the scene owing to the nature of ray tracing. Although more recent algorithms are empowered with massive computational capabilities of the GPUs , 17, theImage-space algorithms, however, typically display much better performance characteristics. The main factors that contribute to the ray-tracing cost are the large number of per-pixel rays and the complexity of tracing a single ray through the optical system, which are hidden costs in the pre-computation part of convolution. Therefore, convolution-based approaches tend to be substantially faster than ray tracing. Furthermore, they also have the potential to achieve interactive, or even real-time performance provided GPU-based acceleration is available, as demonstrated by multiple recent approaches , 44, 45,Finally, the possible limitations of vision simulation algorithms are discussed with regard to the types of supported input scenes. Owing to the continued efforts of computer graphics and ophthalmology researchers, ray-tracing and convolution-based vision simulation algorithms are now readily available for both 2D and 3D input scenes. The main factor to consider is the performance impact of the input type, as described in the previous section.The handling of partial occlusions, however, is of particular interest. As the name of the phenomenon suggests, partial occlusion is only relevant to 3D scenes and materializes when a blurry foreground object partially covers the background, as described in partial occlusion subsection. Handling partial occlusion is trivial in using ray tracing because the resulting image is constructed by sampling the full pupil; therefore, with a sufficiently large number of samples, all the relevant parts of the scene contribute to the final value of each pixel.However, image-space approaches typically struggle with partial occlusion because the pinhole camera model that is traditionally used to render the input only considers rays that pass through the center of the pupil. As described in the partial occlusion subsection, a commonly employed solution to this issue is the use of layered input images to supply the necessary information about the missing background pixels. However, the disadvantage of this approach is the increased cost of rendering and processing extra layers of the input.As mentioned in the introduction, vision simulation algorithms have numerous potential applications –6. In thOne of the earliest uses of visual aberration simulations was the calculation of visual acuity metrics. Such methods utilize computer simulations to generate images corresponding to the vision of an individual. The simulation of visual aberrations is key in these works , which iDespite the existence of physical devices that carry out such tasks, as noted by Kordek et al. , computeComputer simulations of human visual aberrations can also be beneficial for studying the mechanisms of the human eye. A typical approach in these types of experiments is to construct computer models and derive metrics based on specific image characteristics, visual acuity, or aberrations, using a digital model. In addition, the results can be compared to data obtained from real-world measurements performed on the human eye, which are tremendously useful for testing the validity of hypotheses about the human eye. For example, Tabernero et al. , 71 usedMost of the existing studies are limited to analyzing only the aberration structure of the eye, whereas utilizing vision-simulated imagery can lead to important new theoretical results on the mechanisms of human vision, providing a deeper understanding of the human visual system and its deficiencies. For example, Cheng et al.  used a sAnother area where vision-simulated imagery can be highly useful is the visualization of eye diseases in virtual environments. These experiments typically utilize vision simulations to determine an individual’s ability to perform certain tasks in the presence of reduced vision. Using this approach, experts can gain a better understanding of the impact of such conditions on the everyday lives of affected individuals, and thereby facilitate the development of proper tools and devices that better support the lives of these people. To this end, synthetic , 73–77, Simulating visual aberrations of the eye can be tremendously important for invasive processes, such as intraocular lens implants  and laseAnother common form of vision correction is the use of progressive addition lenses (PALs). Corrective spectacle lenses are widely used to treat presbyopia , which is a common age-related condition. The main differentiating property of these lenses from traditional spectacle lenses is the continuous change in optical power over their surfaces, which significantly increases the complexity of designing a lens that properly treats the vision of the individual. Vision simulation methods are a quick and inexpensive way to evaluate the performance of various PAL designs in virtual environments , 85–87. Non-invasive vision-correcting devices have recently made significant progress, and vision simulation is also a crucial element for their development. Among the earliest devices to be developed, vision-correcting displays typically apply inverse blurring to the displayed imagery to compensate for the aberrations of the observer of the display –90.Image-prefiltering approaches often suffer from contrast issues and ringing artifacts. One way of addressing these problems is by utilizing multilayer displays , 92 suchLight-field displays have also been proposed as an alternative to overcome the limitations of single-image solutions, whereby a microlens array is placed on top of the display to provide a higher degree of control over the directionality of the emitted light. Vision correction can be achieved using such displays –95 by utWith recent advancements and increased accessibility of optical see-through head-mounted displays (OST-HMDs), vision correction using these devices has become a potential application area . A camerRecently, holographic near-eye display systems  have beeXR) displays are also a topic of active research and are heavily influenced by the human visual system. A typical problem with such systems is the inconvenience and fatigue experienced by the user, often because of the disparity between the displayed synthetic imagery and the eye’s natural vision. Enhancing simulated renderings with cues, such as chromatic aberration , 41 and Fatigue caused by visual disparity is not the only source of discomfort in these devices. Individuals with aberrant vision are often required to wear corrective glasses while using XR headsets, which severely degrades the overall experience of the user. Through the application of vision simulation, the presented imagery can be preprocessed with the inverse aberrations of the wearer, similar to certain vision-correcting displays. Such an enhancement of head-mounted devices eliminates the need to wear glasses, facilitating their use and further improving the convenience of users .Another common form of inconvenience associated with AR displays is user fatigue. Users are often required to rapidly switch their cognitive attention and eye accommodation between virtual and real information, which can lead to significant fatigue. Recently, Arefin  used visAnother area where vision simulation is highly useful is the training of autonomous virtual humans. To ensure that the behavior of a virtual human closely matches that of a real person, it is essential to accurately mimic all aspects of the human visual system. Because visual aberrations play significant role in vision and affect each individual, incorporating them into the simulation pipeline is necessary to achieve the desired results. Therefore, Nakada et al. , 105 utiIn this study, several approaches for simulating human vision that are affected by wavefront aberrations have been described. These methods were categorized as either based on ray tracing or image-space convolution, depending on the principal tools employed. Ray-tracing methods utilize a wide range of different physical eye models and distributed ray tracing to produce the final results; whereas, convolution-based techniques employ ray tracing or wavefront aberrations to compute the PSF of the eye, which is then used as the kernel for convolution. Based on a description of the various approaches, we also compared several important characteristics, which can serve as guidelines in selecting the correct algorithm when solving a problem that involves the simulation of human vision aberrations. Finally, we outlined several important application areas where simulation of human vision and visual aberrations play an essential role.Despite the large number of available techniques, there is still room for further research in this field. In particular, performance is a critical area where improvements are always welcome. With increased throughput, ray-tracing algorithms can become a viable alternative to convolutional approaches in real-time environments, particularly in case of more complex eye models. The significant recent advancements made in the field of dedicated ray-tracing hardware accelerators and neural network-based approaches, such as reconstruction from low sample-count renderings , could bVisual aberrations play an important role in our everyday lives, and with recent advancements in fields such as aberration-correcting devices, head-mounted displays, and XR devices, perfected vision simulation tools are essential to pave the way for future progress in these areas.


The diagnosis of resistance variable multifault location (RVMFL) in a mine ventilation system is an essential function of the mine intelligent ventilation system, which is of great significance to mine-safe production. In this paper, a supervised machine learning model based on a decision tree (DT), multilayer perceptron (MLP), and ranking support vector machine (Rank-SVM) is proposed for RVMFL diagnosis in a mine ventilation system. The feasibility of the method and the predictive performance and generalization ability of the model were verified using a tenfold cross-validation of a multifault sample set of a 10-branch T-shaped angle-joint ventilation network and a 54-branch experimental ventilation network. The reliability of the model was further verified by diagnosing the RVMFL of the experimental ventilation system. The results show that the three models, DT, MLP, and Rank-SVM, can be used for the diagnosis of RVMFL in mine ventilation systems, and the prediction performance and generalization ability of the MLP and DT models perform better than the Rank-SVM model. In the diagnosis of multifault locations of the experimental ventilation system, the diagnostic accuracy of the MLP model reached 100% and that of the DT model was 44.44%. The results confirm the MLP model outperforms the three models and can meet engineering needs. A good ventilation system can effectively reduce the possibility of accidents, such as gas or coal dust combustion and explosion, carbon monoxide poisoning, and asphyxiation, in mines5. This shows that a stable and reliable ventilation system is extremely important for ensuring the mine’s safe production. However, during the production process of a mine, sudden changes in the air volume of the ventilation system inevitably occur, such as the blockage of the roadway bubble fall, breakage and failure of dampers, and emptying of the mine silo. The essence of these phenomena, which result in sudden changes in roadway air volume, is the sudden change in the wind resistance of the roadway. In this case, these phenomena are defined as the occurrence of resistance failure in the mine ventilation system6. When a resistance fault occurs in a mine ventilation system, the air volume distribution in the ventilation system changes significantly. This most likely leads to a decrease in the air supply in the mining and digging working faces, as well as the accumulation of toxic and harmful gases in some breeze tunnels. It will cause serious safety hazards and risks to the mine7.The main function of the mine ventilation system is to provide fresh air to underground places that need wind. This dilutes and removes toxic and harmful gases, such as gas, carbon monoxide, and dust. It can also create a good working environment to ensure the occupational health of workers and the normal conduct of production activities8. Owing to the rapid development of intelligent technology, the traditional method of relying on personnel to identify resistance variable faults in ventilation systems has gradually been replaced by intelligent diagnostic methods. The intelligent diagnosis method can save considerable human and material resources. Additionally, it saves a lot of time and adapts to the demand for the rapid disposal of mine ventilation system faults. Studies have shown that artificial intelligence and machine learning algorithms, such as support vector machine (SVM), decision tree (DT), artificial neural network (ANN), random forest (RF), genetic algorithm (GA), and multilayer perceptron (MLP), are used to solve single fault diagnosis problems in mine ventilation systems14. However, owing to the specificity and complexity of underground mine conditions, it is common for mine ventilation systems to have resistance variable faults in multiple locations concurrently. Few studies have been conducted on diagnosing and identifying faults in multiple locations of mine ventilation systems.The mine ventilation network has good self-adaptability and robustness, making it suitable for the application of artificial intelligence and machine learning methods15 first proposed a machine learning–k-nearest neighbor-based (ML–KNN-based) model and method for the diagnosis of resistance variable multifault location (RVMFL) in mine ventilation systems. They solve the RVMFL diagnosis problem of mine ventilation systems as a multilabel and multi-classification problem. From the multifault location diagnosis problem, the multilabel classification problem can be transformed into multiple single-label classification problems through a conversion strategy. For example, the ventilation system RVMFL diagnosis problem can be divided into multiple single-fault location diagnosis problems, but this undoubtedly increases the computational complexity17. The multilabel classification problem can also be solved by applying multilabel classification support and adaptation algorithms, such as DT, MLP, ranking support vector machine (Rank-SVM), and AdaBoost.MH, ML–KNN22. These methods are all supervised machine learning algorithms, and Rank-SVM is an improvement of the SVM algorithm. According to the existing studies, DT, MLP, and SVM perform well in solving the problem of resistance variable single-fault location diagnosis in the mine ventilation system9. In addition, these methods represent an important value in the application of classification problems. Formally due to their good classification performance and adaptation to multi-label classification problems, the methods for intelligent diagnosis of RVMFL in ventilation systems are improved. In this paper, three important and widely used machine learning algorithms, DT, MLP, and Rank-SVM, are used to investigate the problem of diagnosing RVMFL in mine ventilation systems.Wang et al.It is well known that different algorithms exhibit different prediction accuracies, performances, and generalization capabilities. Industrial tests are frequently conducted to confirm whether these algorithms can be used in engineering practice, how well they perform in RVMFL diagnosis, and how reliable and valid each diagnosis model is. To conduct an industrial field test of a ventilation system failure in a production mine, it is necessary to open the dampers in a closed state for a long time or block the tunnel to make a real failure in the mine, particularly to create a failure in multiple locations. However, such a test is not permitted, particularly in coal mines. If the resistance variable fault industrial test is conducted in metal mines, unlike coal mines, metal mines do not experience gas disasters and natural coal fires in the mining area while collecting test sample data. It may lead the mine ventilation system to a state of failure for a long time, which significantly affects the safety production of mines. In summary, conducting industrial tests on actual resistance variable faults in mine ventilation systems is difficult and involves certain safety risks. To address the problem of creating resistance variable faults in actual mines that affects normal production, a ventilation system resistance variable fault simulation experimental system was built. The advantage of this system is that it can simulate any type of resistance variable faults and create any degree of resistance variable faults at any location, without being limited by the site's environmental conditions and without safety problems, such as industrial tests in the field.The main objectives of this study are as follows: 1) Solving the problem of accurate diagnosis of resistance variable faults occurring at multiple locations in the mine ventilation system simultaneously. (2) Analyzing and comparing the performance of different intelligent algorithms in the problem of multifault location diagnosis of resistance variable faults in ventilation systems to find more suitable algorithms and models. (3) Building an experimental system for simulating resistance variable faults in the mine ventilation system. Then, using this system to verify the reliability and validity of the proposed model through experiments, and solve the problem of being unable to conduct realistic industrial tests to confirm the reliability and validity of the algorithms in actual production mines. (4) The study results provide a theoretical basis for constructing an intelligent body on mine ventilation systems. The research flow of this paper is shown in Fig.  Solving Mine occurs resistance variable multifaults refer to cases in which the mine ventilation system in a normal production period experiences resistance variable faults in two or more different roadways simultaneously. This study considers the case of two roadways simultaneously occurring with resistance variable faults as an example and adopts a supervised learning method to address the problem of mine ventilation system RVMFL diagnosis. Figure The airflow information of all or the residual branches of the ventilation network is used as an observation feature. Based on the values monitored by the mine wind speed sensors, the monitored values are averaged statistically for time averaging, corrected for single-point wind speed values, and converted into ventilation system airflow. The observed feature data of the constructed training sample set are normalized and used as input to the classifier for learning and training, and the binary vector of fault labels corresponding to multifault locations is used as the output of the classifier to train an RVMFL diagnostic classifier for mine ventilation. Based on the changes in air velocity at monitoring points when a ventilation system in normal production has a resistance variable multifault, the trained multifault location diagnostic classifier can quickly diagnose the locations of faults.25. When a wind volume vector xi ∈ Rn, i = 1,…,l and its corresponding fault location label vector y ∈ Rl after a resistance variable multifault occur, the classification tree recursively divides the feature space so that samples with the same fault label are grouped. For each feature segmentation point, let nm multifault sample data at node m. For a candidate segmentation θ =  comprising a fault feature j and a domain value tm, segment the data into subsets The DT algorithm supports multilabel classification problems. The process of RVMFL diagnosis is equivalent to constructing a fault label classification tree, which is based on the principle of learning multifault samples and inferring simple fault decision rules from data features to predict fault location target valuesm. The Gini index is chosen as the metric function for impurity and is calculated as follows:pmk is the proportion of data labeled k at node m.The impurity function is used to calculate the number of impurities for one candidate segmentation of node The parameters that minimize impurities are as follows:The recursion of subsets 28. Given a resistance variable multifault feature set and its corresponding fault labels, it can learn to obtain a nonlinear function approximator for multifault location diagnosis. Between the input and output layers of the multifault location diagnosis MLP model, there can be l (l ≥ 1) implicit layers with the following information-processing mechanism:jth neuron in layer l, ith neuron in layer l-1, ith neuron in layer l-1, and the jth neuron in layer l, jth neuron in layer l, and g(∙) is the activation function using the hyperbolic tangent as the activation function:MLP is a supervised learning algorithm that is a feed-forward network and supports multilabel classification problem solvingη is the learning rate of the control step in the parameter space search.The stochastic gradient descent algorithm was chosen and used to train this multifault location diagnosis perceptron network using the gradient of the loss function to update the weights w:y is the actual fault location, n is the number of samples, α > 0 is a nonnegative hyperparameter controlling the magnitude of the penalty.The average cross-entropy is used as the loss function for the RVMFL diagnosis model, whose expression in the binary case takes the following form:Starting with initial random weights, MLP minimizes the loss function by iteratively updating these weights. After calculating the loss, backpropagation propagates it from the output layer to the previous layer, updating the value of each weight parameter to reduce the loss.31. Let the Rank-SVM multifault learning system comprise m linear classifiers ωj is the weight vector corresponding to the jth class of faults and bj is the bias corresponding to the jth class of faults. For a given multifault training sample set xi, Yi), which can be expressed as follows:Rank-SVM is a ranking-based multilabel classification algorithm that uses a maximization interval strategy and introduces a kernel trick to address nonlinear classification problemsT, the classification interval of the learning system is given byEquation  represenS are scaled. Then, the optimization problem of maximizing the training set classification interval can be expressed as follows:The training sample set classification interval is considered positive, and the parameters of the linear classifier  yi and yk; there exists Let the training sample be sufficiently adequate, i.e., for all category markersEquation  can be tC is the equilibrium coefficient and By approximating the max operator with a summation operator and introducing slack variables and using Ranking Loss as the loss, the optimization problem is transformed into35. The five metrics of hamming loss, ranking loss, coverage, average accuracy, and one-error are the most commonly used and most widely applied metrics. These five metrics were selected to evaluate the RVMFL diagnosis models for mine ventilation, as shown in Table To compare and evaluate the diagnostic performance of DT, MLP, and Rank-SVM-based RVMFL diagnosis models for mine ventilation systems, the evaluation metrics were selected considering the existing literature on multilabel classification problems mentclass2pt{minimTo verify the feasibility and model reliability of the DT, MLP, and Rank-SVM-based RVMFL diagnosis method for ventilation systems, as well as to compare and analyze the diagnostic performance of these three models and find the optimal model, experiments were conducted using a 10-branch simple T-shaped angle-joint network and a 54-branch network with a multifault location diagnosis experimental system. The experimental study process is shown in Fig. e4 and a ventilation fan at branch e8. The characteristic curve of the ventilation fan is given as follows:The topology of the T-shaped angle-joint ventilation network, the wind resistance coefficient and the fan characteristic curves in literature 6 are used as references for the ventilation system RVMFL diagnosis study. Figure The branching parameters of the T-shaped angle-joint ventilation network are presented in Table 36 is used to simulate the resistance-increasing faults of the general branches, except for the inlet and outlet branches, and the resistance-decreasing faults of the dampers. Assuming that the two branches in the ventilation system fail simultaneously and that the faulted air resistance values are generated using a random method, the steps for generating the resistive multifault sample set are as follows:ei and ej have faulted simultaneously, with resistance variables Δri and Δrj, the wind resistances of the faulty branch become Keeping the topology of the ventilation network and the operating characteristics of the ventilator unchanged when any two branches of the ventilation system ei and ej failures, the ventilation network after the fault is solved once it generates new sample data Based on the wind resistance vector ei and ej where the fault occurred and the ventilation system branch air volume Construct a multifault sample data space and record the branch numbers ei and ej branches occur many times, and the number of fault variables differs with each occurrence, resulting in generating the resistance multifault samples on the ei and ej branches. Based on the above rules, other branches of the ventilation network generate multifault samples of the corresponding branches, forming the ventilation network resistance variable multifault sample set T.Repeat steps (1)–(3) so that the Based on the branch information of the ventilation network during normal production periods, the mine ventilation simulation system (MVSS)Following the above method, a total of 600 sets of resistance variable multifault samples were generated for the T-shaped angle-joint ventilation network, as shown in Table The reasonableness of the hyperparameter settings determines the predictive performance of the model's multifault location diagnosis machine learning model. In this study, the cross-validation grid search method is used to determine the hyperparameters of the model. The hyperparameter settings of the T-shaped angle-joint ventilation network multifault location diagnosis machine learning model are shown in Table A sample set containing 600 sets of multifaults was cross-validated. The results are shown in Fig. The experimental ventilation system was built using unplasticized polyvinyl chloride (UPVC) pipes with diameters of 200 mm, 160 mm, and 110 mm. The total length of the experimental system piping is 353 m. There are 14 structures in the experimental system, of which seven are completely closed, one is the inlet air branch adjustment, and the remaining six are fault-simulated adjustment valves. The system can simulate different types and amounts of faults, and it can better simulate situations in which multiple faults occur in the ventilation system. The seven closed dampers position can be carried out to simulate the descending resistance fault experiment, and the six regulating valve position can be carried out to simulate the increasing resistance fault experiment. The experimental system is shown in Fig. e1, and the model 9–19-5A 7.5KW centrifugal fan is installed on branch e65. The operating frequency of both fans is 50 Hz. The plate resistance method is used to increase the resistance of the system, and the air volume and pressure of the ventilation fan under different system conditions are tested by using a differential pressure meter and pitot tube, and the characteristic curve equation of the fan is obtained by the method of data fitting. By testing, the characteristic curves of these fans are h (q) = 3156.2 + 1323.6 q—1838.7 q2 and h (q) = 4266.8 + 4515.3 q—4406.1 q2, respectively.The topology of the experimental system is illustrated in Fig. Based on the construction method of the T-shaped angle-joint ventilation network resistance variable multifault sample set, 500 sets of experimental ventilation network multifault sample sets were generated, as shown in Table A cross-validation grid search was adopted to determine the hyperparameters of the experimental ventilation network multifault location diagnosis model, as shown in Table Cross-validation was performed on a 500-group multifault sample set, and the results of the cross-validation are shown in Fig. In the experimental system, increasing and decreasing the resistance fault simulation point improve the reliability of the multifault location diagnostic model; thus, the ventilation system experiences resistance variable multifaults. Owing to the poor predictive performance and generalization ability of the Rank-SVM model for multifault sample sets, it is not considered here; only the reliability of the MLP and DT models is considered. A fully open regulating valve preset at the simulation point of a resistance-increasing fault in the experimental ventilation system is used to create a resistance-increasing fault, and the dampers in the original system are used to create a resistance-reducing fault. A total of 9 sets of multifaults were created and tested for the remaining branch airflow in each state. After each multifault diagnosis was performed, the system was restored to the original ventilation system state to ensure consistency. A sample of the experimental ventilation system multifault example tests is shown in Table k = 2 and 100% when k = 3. The diagnostic accuracy of the MLP model is comparable to that of the ML-KNN model.The reliability of the MLP and DT models was verified using the multifault sample set in Table According to the cross-validation results, the DT, MLP, and Rank-SVM supervised machine learning methods are feasible for the multifault location diagnosis of mine ventilation systems based on air volume characteristics. The diagnostic performances of both the MLP and DT models are better than that of the Rank-SVM model, and the MLP model performs the best.In the diagnosis of the experimental ventilation system resistance variable multifault instance, the diagnostic accuracy of the MLP model is 100%, while the diagnostic accuracy of the DT model is 44.44%, further indicating that the generalization ability of the MLP model is better than that of the DT model. The high diagnostic accuracy and reliability satisfy the engineering requirements and can be used as a method of RVMFL diagnosis in engineering practice and application.The successful practice of RVMFL diagnosis of experimental ventilation systems shows that the resistance variable multifault experimental verification system for mines established in this study can serve as a verification platform for intelligent fault diagnosis of mine ventilation systems, effectively solving the problem that industrial tests cannot be conducted in the field and providing strong support for the construction of intelligent ventilation systems for mines.This study investigated the concurrent diagnosis of resistance faults occurring at multiple locations in a mine ventilation system, proposed three supervised machine learning diagnosis models for RVMFL diagnosis, and validated the reliability and effectiveness of the models and methods using a 10-branch T-shaped angle-joint ventilation network and a 54-branch experimental ventilation network. We obtained the following main conclusions:This study focused on the diagnosis of multifault locations in mine ventilation systems, and further study is needed to diagnose the magnitude of faults, i.e., the volume of faults, in ventilation systems where multifault locations occur. In this study, only the air volume was used as a single feature as an input to the model, and a higher accuracy might be obtained if factors such as the differential pressure of the structure or pressure energy of the nodes were considered. Rank-SVM has the worst diagnostic performance among the three models. The factors affecting the performance of the Rank-SVM model are the setting of the penalty factor, the selection of the kernel, and the sample size and quality. At present, the kernel selected in this paper is a linear kernel and the penalty factor set in this paper may lead to the degradation of the diagnostic performance of the model, and the subsequent research should focus on the factors affecting the performance of the model in order to find the best model setting so as to improve the diagnostic performance of the model.


In this paper, we present a hybrid frequency shift keying and frequency division multiplexing  approach for information embedding in dual-function radar and communication (DFRC) design to achieve an improved communication data rate. Since most of the existing works focus on merely two-bit transmission in each pulse repetition interval (PRI) using different amplitude modulation (AM)- and phased modulation (PM)-based techniques, this paper proposes a new technique that doubles the data rate by using a hybrid FSK–FDM technique. Note that the AM-based techniques are used when the communication receiver resides in the side lobe region of the radar. In contrast, the PM-based techniques perform better if the communication receiver is in the main lobe region. However, the proposed design facilitates the delivery of information bits to the communication receivers with an improved bit rate (BR) and bit error rate (BER) regardless of their locations in the radar’s main lobe or side lobe regions. That is, the proposed scheme enables information encoding according to the transmitted waveforms and frequencies using FSK modulation. Next, the modulated symbols are added together to achieve a double data rate using the FDM technique. Finally, each transmitted composite symbol contains multiple FSK-modulated symbols, resulting in an increased data rate for the communication receiver. Numerous simulation results are presented to validate the effectiveness of the proposed technique. Spectrum-sharing techniques have received substantial attention from the research community to meet the high data rate demands of the users for 5G and beyond applications ,2,3. ModNote that radar applications, nowadays, are not limited to monitoring purposes only. They are used for geophysical checking, weather monitoring and forecasting, air traffic surveillance, etc. . AlthougAccording to studies ,9,10,11,Note that radar and communication design sharing can be achieved initially in terms of time and frequency. In time-based sharing, a strobe switch allocates slots to radar and communication receivers . ContrarOn the other hand, the DFRC design uses a suitable transmitter that simultaneously facilitates both the radar and communication system in terms of hardware and frequency spectrum, where the system performance is improved by using shared knowledge. More importantly, the spectrum in the DFRC design can be shared with the wireless communication system by three well-known methods, i.e., (a) radar waveform, (b) communication waveform, and (c) multi-beam methods . As radaThe embedding of the information bits into the radar-based waveforms using time-modulated arrays is presented in , where tThe proposed design facilitates the delivery of information bits to the communication receivers with an improved bit rate (BR) and bit error rate (BER) regardless of their locations in the radar’s main lobe or side lobe regions.The proposed method offers reduced inter-symbol interference as the decoding of each composite symbol at any communication receiver is independent of other neighbouring symbols.This paper presents a new approach to embedding information in radar waveforms by a hybrid FSK–FDM technique, which enjoys the benefits of both the modulations and multiplexing techniques. Note that the AM-based techniques are used when the communication receiver resides in the side lobe region of the radar. In contrast, the PM techniques perform better in communication receivers in the main lobe region. However, the proposed design facilitates the delivery of information bits to the communication receivers with an improved bit rate (BR) and bit error rate (BER) regardless of their locations in the radar’s main lobe or side lobe regions. Initially, a lookup table containing the symbols mapped against the possible combination of two information bits is maintained. Since each symbol contains information about the orthogonal waveforms and frequencies, a composite signal is generated by adding multiple symbols using a linear adder. Eventually, the overall data rate significantly increased when adding the symbol through a linear adder in each PRI. Next, this composite signal is modulated at an intermediate frequency upon which the radar operates. Finally, the received signal at the communication receiver is passed through the bandpass filtering procedure to extract the individual symbol. Each combination of waveform and frequency is decoded using matched filtering. The main attributes of this paper are summarized as follows:The rest of the paper is organized as follows. t, and the pulse number is represented by A signal data model is developed in the following sections for the DFRC design, using FSK and FDM techniques. The DFRC transmitter, the radar receiver, and the communication receiver are all equipped with uniform linear arrays (ULAs) using  antenna  is(1)s at the receiver. The beam-forming operation is mathematically expressed by Equation .(6)gkfdkth communication receiver.The next step in this process is to apply bandpass filtering techniques to the received FDM composite signal. The bandpass filter is implemented as a digital finite impulse response (FIR) filter and configured to have a passband with the desired bandwidth. The filtered signal is then demodulated to recover the original transmitted information. A mathematical description is given in Equation  and a grMatched filtering is then applied to the signal, Equation , to idenThe overall process of match filtering and information decoding at the communication receiver is shown in T is the threshold constant of frequency separation for orthogonality.Furthermore, by performing the simple ratio test on the output of the filter in Equation , we obtaIt is important to note that multiple waveforms are selected at a time, and they change on a pulse-to-pulse basis. The data rate is given as a product of the number of bits per pulse and the PRF, i.e.,The probability that 00 is transmitted and 01 is received can be written as This paper considers a uniform linear transmit array consisting of In the following sections, we will present the simulation results with different illustrative examples for clarity and manageable acquaintance.In the 1st case, the radar target is fixed at At the communication receiver, we have In this study, we assume that the average transmit power of each transmit antenna is normalized to 1, i.e., the total transmit power is fixed to The performance of both cases explained in examples 1 and 2 of the proposed scheme remains the same, and no degradation is observed. For the case of four communication receivers as shown in example 2, there is a slight degradation in the BER compared to the single communication receiver due to interference. We compared the performance of the proposed scheme for a single communication receiver with side lobe control and waveform diversity cited in  and achiapproach  in termsAll communication receivers are assigned the same weight vectors. The lookup table is shared with all communication receivers in advance. The shape of the composite signal at the transmitted and received side is shown in The FFT analysis reveals that both the transmitted and received signals have the same frequency content. Similarly, in In this section, we discuss the concerns related to the security in communication. We calculated the SNR for all angles used for transmission. It is clear from Our objective in this section is to assess the accuracy of DoA estimation for radar operation. A target is assumed to be located in the far field region at a distance of In this subsection, we discuss the probability of target detection at different SNR levels. A single target is considered in this case, located at Mathematically, ROC can be calculated as (12)Pd=1A comparison of the proposed technique with other existing techniques in terms of BER vs. SNR are provided in A total of Implementing an FSK–FDM-based DFRC transmitter requires special attention to the SNR since it directly impacts the data rate. Based on simulation results, it is clear that the proposed scheme performs well at higher SNR values. Moreover, we have addressed jamming and the computational complexity of the system at the communication and radar receivers. The proposed system achieves a better trade-off between jamming robustness and data rate than other systems. It also has lower computational complexity, making it a cost-effective solution. Finally, it offers greater flexibility in terms of modulation format and data rate.A novel approach to a dual-function radar communication system was introduced in the paper. The proposed technique increased the data rate for the communication receiver. Moreover, it delivered information to the communication receivers with an improved BER regardless of their location in the main or side lobes of the radar beam. Next, orthogonal frequency and waveform-based combinations were used to transmit binary information to each communication user, facilitating double the PRF-based data rate with improved secrecy. Finally, diverse scenarios were considered and extensive simulations were conducted to validate the effectiveness of the proposed technique. Currently, only one waveform is considered using likelihood-based estimation for DFRC. Keeping all constraints, such as inter-symbol interference and SNR vs. BER, more than one waveform shall be considered using FDM techniques. In addition, a different scenario needs to be developed when the radar lies in the side lobe, and communications are in the main lobe. In addition, an algorithm needs to be developed to decide when ASK-based techniques should be used and which scenario will work well with PSK-based techniques.