Atomic clocks provide frequency reference signals for communication, aerospace, satellite navigation and other systems. The redundant configuration of atomic clocks is necessary for ensuring the continuity and stability of the system. A radio frequency (RF) switch is usually used as a switching device in the switching system of the host atomic clock and the backup atomic clock. When the atomic clock fails, the switching between the host and the backup clock can be carried out quickly. Aiming at the fast switching requirements of atomic clock RF signals, this paper proposes a new series-shunt Positive Intrinsic Negative (PIN) switch design. In this paper, the evaluation of the RF switches is conducted by using the metrics of switching speed, insertion loss, isolation, return loss at on state and return loss at off state. Experimental result shows that the new PIN switch has better and more comprehensive performance metrics than the electromechanical switch, FET switch and conventional PIN switch. In particular, the switching speed is 53 ns faster than the conventional series-shunt PIN switch. An atomic clock is an oscillator and an auxiliary circuit which can produce high accuracy and stability standard frequency signals such as a 10 MHz sine signal . The steAtomic clocks are used in many fields, such as electronic countermeasures, navigation, aviation, wireless communications, global positioning systems, power grid systems and so on ,4. The wAs shown in In order to meet the requirements of the smooth switching of the RF signal by atomic clocks, this paper analyzes the technical performance metrics of different RF switches. By comparing their switching speed, insertion loss, isolation, return loss and other technical performance metrics, this paper proposes a new PIN series-shunt switch as the switch device for the switching system of atomic clock redundant configurations. Compared with the electromechanical switch, the FET switch and the conventional PIN switch, the new PIN switch has better performance and is more suitable for the switching system of atomic clocks. This paper consists of five parts. The first part mainly describes the research object and research background of this paper. The second part explains the basic working principle of common RF switches, and analyzes their technical metrics to select the suitable RF switch for the smooth switching of atomic clocks. The third part focuses on the solid-state switch, then describes the working principle of PIN diodes. A new PIN series-shunt switch is designed by comparing and analyzing the advantages and disadvantages of the conventional PIN switch. The fourth part designs and builds an experimental platform to verify the effectiveness of the proposed PIN switch design. The final part summarizes the main work and contributions of this paper.To evaluate the performance of a RF switch, the commonly used technical performance metrics include insertion loss, isolation, return loss and switching speed . InsertiIn a redundant atomic clock configuration, the selected RF switch should take into account the switching speed, insertion loss, isolation and other technical metrics. When the host atomic clock and the backup atomic clock are switched, a phase jump of their reference frequency signal is caused. The phase jump of the reference frequency signal will further deteriorate the system performance. For example, for a navigation positioning system with high precision requirements, an error on the order of nanoseconds may cause measurement errors of several tens of meters. Therefore, in order to ensure the continuity and stability of the reference frequency signals of the host clock and the backup clock before and after switching, the switching speed should be considered as a primary indicator.Different RF switches have different mechanical and electrical structures, so their switching speed, isolation, insertion loss, return loss and other technical metrics are also different . At presCompared with the electromechanical switch, the solid-state switch is completely based on semiconductor characteristics. It has the characteristics of fast switching speed, long lifetime, and high reliability ,29,30,31In practical engineering applications, the ON time of different RF switches is often different from the OFF time. In this paper, the switching speed is specially referred to the ON time. For example, the switching speeds of Agilent 8765B electromechanical switch and Mini-Circuits ZMSW-1211 solid-state switch are measured as shown in As shown above, the switching speed of the solid state switch is much better than that of the electromechanical switch, so the solid-state switch should be the best choice for the switching system of an atomic clock redundant configuration. Compared with other solid-state switches, the FET switch and the PIN switch have the advantages of faster response speed, and their circuit structures are simple ,32. CompJust as shown in The PIN diode is based on common PN diodes. Unlike conventional PN diodes, The PIN diode adds a thin layer of low-doped intrinsic material between the positive pole and the negative pole. The I-layer can reduce the interstage capacitance of the diode and increase the breakdown voltage .When the PIN diode is forward biased, the PIN diode is turned ‘ON’ and the diode presents a low resistance state . It can The PIN switch circuit has three basic structural forms in design, which are the series type, the shunt type, and the series-shunt type. Each of the three switches has its own advantages and disadvantages. Then, the three circuit structures will be theoretically analyzed and measured.Equation (1) is the calculation formula for the insertion loss of the series SPST switch. For multi-throw switches, the insertion loss will increase due to the impedance mismatch caused by the capacitance of the PIN diode in the branch:Equation (2) is the calculation formula for the isolation of the series SPST switch. It shows that the switch isolation is determined by the diode reverse bias capacitance.Equation (3) is the calculation formula for the insertion loss of the shut SPST switch. Compared with the Equation (1), it clearly shows that the insertion loss of the shunt PIN switch is less than the insertion loss of the series PIN switch for the same kind of PIN diode:Equation (4) is the calculation formula for the isolation of the shunt SPST switch. Compared with the Equation (2), it is obvious that with the same kind of PIN diodes, the isolation of the shunt PIN switch is less than the isolation of the series PIN switch.In order to combine the advantages of the series PIN switch with the shunt PIN switch, more serial-shunt PIN switches are used in the design. The two bias ports respectively control the on and off of D1 and D2. When Bias1 is high level and Bias2 is low level, D1 is forward biased and D2 is reverse biased. The switch is in the on state. When Bias1 is Low level as well as Bias2 is high level, D1 is forward biased and D2 is reverse biased. The switch is in the off state. The circuit schematic of the series-shunt PIN switch is shown in We measured the transmission of 10MHz RF signals for three switches under 50 Ohm load. The specific measurement data is shown in As shown in We added a Π-type matching network composed of L1, C2 and C3 to the input. The matching network is often used to select the band in the transceiver switching circuit of the wireless communication system. The improved series-shunt PIN switch designed is used in the redundant switching system of atomic clocks, so the designed working frequency band is 5 MHz–100 MHz.For the atomic clock redundant configuration, a host atomic clock and a backup atomic clock are usually required. Therefore, a Single-pole Double-throw (SPDT) switch can be used to accomplish such switching tasks. Designing a SPDT switch requires simply adding an input port based on the proposed switch. Second thing to notice, there may be interference between the two input signals. So when designing the layout of PCB, the position of the two input ports should be kept as far as possible. This can effectively reduce signal interference and improve the isolation of the switch.In order to verify the effectiveness of the new PIN switch design scheme proposed in this paper, we designed and built a test platform. The experimental equipment used includes a PRS10 rubidium atomic clock, a SDG1062X signal generator, a Tektronix DPO 2022B digital oscilloscope, a DEVISER NA7632A vector network analyzer and a detector.As shown in As shown in When the switch is turned on, S is measured as the return loss at on state. When the switch is turned off, S is measured as the return loss at off state. The formula is as follows:We measured the insertion loss, isolation, return loss, and switching speed of the improved series-shunt PIN switch and compared it with three conventional PIN switches.The experimental results are as follows:As Shown in According to This paper presents a RF switch used in a redundant configuration of 10 MHz atomic clocks. Firstly, we analyzed from theoretical and experimental perspectives the performance of the electromechanical switch, the FET switch and the PIN switch. Consequently, we verified that PIN switches are more suitable for the switching system which is used in a redundant atomic clock configuration. Then based on the principle of PIN diodes, we compared the three conventional connection modes of PIN switches. Through theoretical and experimental verification, the process proves that the series-shunt switch has the best performance. On this basis, we design an improved series-shunt PIN switch. The experimental results show that compared with the conventional series-shunt PIN switches, the improved series-shunt PIN switch can significantly improve the key technical metrics of performance such as isolation, return loss and switching speed, so it is the most suitable RF switch for a redundant configuration of atomic clocks.


Images of Bruno Catalano’s sculptures of incomplete bodies give rise to aremarkable depth confusion in which the background is partly pushed to thefront. We argue that this confusion is related to what happens in the Kanizsasquare, although the effect in the images of Catalano’s sculpture appears to bedriven by knowledge-based processing. Whenlooking at two-dimensional images of these statues , somethiThe induced illusory depth order in the Catalano statues, although less stable, isrelated to what happens in the well-known Kanizsa square , 1979, wIn Catalano’s statues, the background is partly pushed to the front due to an apparentknowledge-driven completion of the body fragments. The strength of the effect depends onthe recognizability of the fragments. To illustrate this aspect further, consider A crucial difference between the above effect and the Kanizsa square is that while thealternative depth order in the Kanizsa square appears to be triggered predominantly bybottom-up processing, the depth order as seen in the example in All in all, the ambiguity when observing the incomplete statues of Bruno Catalanosuggests that the body fragments temporarily trigger knowledge-based completions andwith that cause the aesthetically pleasant depth confusions.


Deep learning is the crucial technology in intelligent question answering research tasks. Nowadays, extensive studies on question answering have been conducted by adopting the methods of deep learning. The challenge is that it not only requires an effective semantic understanding model to generate a textual representation but also needs the consideration of semantic interaction between questions and answers simultaneously. In this paper, we propose a stacked Bidirectional Long Short-Term Memory (BiLSTM) neural network based on the coattention mechanism to extract the interaction between questions and answers, combining cosine similarity and Euclidean distance to score the question and answer sentences. Experiments are tested and evaluated on publicly available Text REtrieval Conference (TREC) 8-13 dataset and Wiki-QA dataset. Experimental results confirm that the proposed model is efficient and particularly it achieves a higher mean average precision (MAR) of 0.7613 and mean reciprocal rank (MRR) of 0.8401 on the TREC dataset. Deep learning forms a more abstract high-level representation attribute feature by combining low-level features to discover the distributed feature representations of data. It provides an effective method for NLP research. In recent years, intelligent question answering in the NLP field has emerged as a prominent discipline research hotspot in both academia and industry, which has been widely used by many influential question answering systems. Answer selection plays a vital role in question answering task, and it mainly encodes QA pair and inputs them into the model to extract the key information and get the corresponding representation . Thus, tIn the past few years, most question answering studies –4 were bWith the significant innovation of deep learning, deep neural networks are able to availably map the meaning of a single word in a sentence to a continuous representation of the entire sentence, and the meaning of the sentence representation obtained is more complete. Because deep learning reduces the need for manual feature engineering and adapting to new tasks, it has become an important research method for various tasks of NLP in the last several years, and a large number of researchers take advantage of its end-to-end model for sentence semantic analysis to implement question answering tasks. Feng et al.  and WangIn this paper, we construct a deep learning architecture for question answering, where questions and answers are limited to a single sentence. The cores of our architecture are two distributed sentence models working in parallel, based on a stacked BiLSTM neural network. We map questions and answers to the corresponding distribution vectors and finally calculate the semantic similarity between them. BiLSTM neural networks have been widely used in recent years to deal with NLP issues –11. ZhanA stacked BiLSTM neural network is resorted to attain the vector representation of the input sentence, which can effectively capture the semantics of the sentence.Our model combines coattention mechanism and attention mechanism to encode sentences to obtain the interaction and influence between the QA pair.The cosine similarity and the Euclidean distance are reconciled to calculate the degree of matching between two vectors. This method is able to take the distance and angle relationship between vectors into consideration.The main contributions of this paper are summarized as follows:The rest of this paper is organized as follows. Research in question answering has been greatly boosted by the Text REtrieval Conference series since 1999. Recently, a number of related works –15 have Previously, traditional research approaches concentrated on syntactic matching between the questions and answers. Punyakanok et al.  was the In the recent work of question answering, the mainstream is based on deep learning methods. Yih et al.  and WangF1 point is 1.61%. Inspired by the related work in Bahdanau et al. . The basic LSTM cell architecture is shown in σ is the logistic sigmoid function, xt indicates t-th word vector of the sentence and ht indicates the hidden state, W terms and b terms, respectively, represent weight matrices  and bias vectors  for the three gates.LSTM networks architecture was originally developed by Hochreiter and Schmidhuber . More fox= from the opposite direction to a forward hidden sequence yt is formed by the concatenation of the final forward and backward outputs, y= is the output sequence of the first hidden layer.To overcome the shortcoming of single LSTM cell that can only capture previous context but not utilize the future context, Schuster and Paliwal  inventedyt from the lower layer becomes the input of the upper layer. The stacked BiLSTM structure is illustrated in Some previous works represented that by stacking multiple BiLSTM in neural networks, the performance of classification or regression can be further improved –32. MoreQ= and A= to represent question sequences and answer sequences, respectively, where n and m indicate the length of the questions and answers, and qt and at indicate the t-th words of the questions and answers. We run a stacked BiLSTM over the questions and answers to obtain their hidden state matrixes HQ and HA, and the mathematics is as follows:d is the dimension of the hidden state.Defining Here, we implement a coattention mechanism to encode question according to the answer sequences, as shown in L, which includes affinity scores corresponding to all pairs of question and answer words. It can be described as follows:We first perform matrix multiplication to calculate the affinity matrix Softmax function is applied to standardize vector elements, and it is effective in dealing with multiclassification and probability distribution problems. Hence, the column- and row-based softmax functions are utilized to generate attention weights for the hidden states of question and answer separately in the following equation:CQ and CA. Here, CQ and CA are the results of the interaction between the question and the answer vector:In order to obtain the attention vector of the question in light of each word of answers, we concatenate attention weights and affinity matrix to compute new context vectors CtQ indicates t-th attention context vector of the question, and the max pooling is taken to convert the input into a fixed-length vector output Oq. Then, the softmax weights of all context vectors  can be learned autonomously according to Oq via the attention mechanism, and the weighted context vector Oa of the answer is used as the final representation:To reduce the information loss of stacked BiLSTM, a soft attention flow layer can be used for linking and integrating information from the question and answer words , 13. In Wam and Wqm represent the attention matrices of CtA and Oq, respectively. wms denotes the attention weight vector. The final representation Oa of answer is determined by the attention weight Saq(t) for answer context vector of the t-th word. It is normalized by the softmax function, which is proportional to CtA. Higher values for Saq(t) indicate higher correlation between CtA and the question, and the question vector will get more attention.Here, In this work, we resort a method to reconcile cosine similarity and Euclidean distance to evaluate the degree of matching between the questions and answers. Cosine similarity represents the angle between two vectors, and the Euclidean distance represents the distance between two points in Euclidean space. We hope that the distance between the question and the answer semantic vector to be close enough and the angle is small enough, to maximize the similarity calculation between question and answer pair sentence vectors. The schematic diagram of cosine similarity and Euclidean distance is shown in Oq, Oa) is the final match result:A vector representation of the question and answer is obtained from the hidden layer of the model. The cosine similarity and Euclidean distance calculation details are as below. Score(11)ScoreM is the constant margin, a+ and a− denote the positive answer and the negative answer, respectively. λ and θ represent regularization parameters and neural networks parameters separately.During training, the positive and the negative samples can be input simultaneously by using the hinge loss function. We define the hinge loss function as the training goal as below:L/∂θ and update the parameter θ to achieve the minimization of the objective function [Lmin.In the process of training, we utilize the backpropagation algorithm to calculate the gradient ∂function . FinallyIn this section, we will introduce the detailed information of the experimental implementation, including TREC-QA (8-13) dataset and Wiki-QA dataset, model evaluation indicators, and selection of training parameters, and then, we will carefully analyze the experimental results on different datasets to prove that our proposed model has good accuracy and robustness.In this part, we mainly introduce two public datasets, TREC-QA (8-13) dataset and Wiki-QA dataset, and we also introduce the source, data characteristics, and the number of Q&A pairs of these two datasets in detail.http://nlp.stanford.edu/mengqiu/data/qg-emnlp07-data.tgz) to evaluate our model, which was created by Wang et al. [The experiment is operated on the Text REtrieval Conference 8-13 QA datasets  is an open domain Q&A dataset provided by the Microsoft team in 2015. The questions in Wiki-QA are mainly focused on the question of classification, number, and personal information. They are collected and organized by real data of users. The candidate answer statement comes from the topmost text paragraph returned by the Wikipedia input page. As shown in Wiki-QA  scripts to calculate these metrics:Nq represents the number of all queries and nai represents the number of all relevant correct answers for query i. Pi(r) represents the average accuracy of the i-th query with recall ratio r. rankk represents the position of the k-th correct candidate answer in the entire answer sequence after confidence ranking of the candidate answers for the query. ranki represents the position in which the first correct candidate answer for query i is located in the set of candidate answers.Following the previous works of Wang et al.  on this In this paper, different experimental factors are set to test and evaluate our proposed method, and then our method is compared with other most advanced methods under the same dataset. The neural network model is implemented with TensorFlow library. In the course of training, we continuously observe the performance on the test set and select the highest MAP and MRR score parameters for final evaluation. Our implementation is as follows:(1) Word Embedding. Pretrained GloVe (https://github.com/stanfordnlp/GloVe) [K = 5.p/GloVe)  is used (2) Parameter Initialization. During training, we set the minimum batch size to 40 and refer to the Adam [M is fixed to 0.2 and the regularization parameter λ is set to 1e − 5. Furthermore, we experimented with single-layer BiLSTM, stacked BiLSTM, and stacked BiLSTM with coattention. Each layer of LSTM has a memory size of 200.the Adam  experime(3) Optimization Algorithm. Adam algorithm [lgorithm  is resorIn order to verify the validity and accuracy of the algorithm model of the fusion stacked BiLSTM network and the coattention mechanism in the intelligent question answering, we tested and verified the TREC-QA (8-13) dataset and Wiki-QA dataset, respectively, and the experimental results were analyzed and summarized.We conducted a comparative experiment on single-layer BiLSTM, stacked BiLSTM, and stacked BiLSTM with coattention on the TREC-QA (8-13) dataset. Different from the traditional work of Yih et al.  and Yu eWe found that our experimental results of the coattention mechanism were significantly better than most of the above results , 8, 38. The experimental index of stacked BiLSTM is better than single-layer BiLSTM when compared line 11 and line 12 with line 13 and line 14, respectively. Furthermore, Wang and Nyberg  resortedThe best MAP 0.7613) and MRR (0.8401) are obtained by incorporating the coattention mechanism into a stacked BiLSTM neural networks and combining cosine similarity and Euclidean distance to calculate the matching degree between two vectors. Our experimental result outperforms the state-of-the-art baselines of Tan et al. [3 and MRRFirstly, we conducted comparative experiments in the model training process, selected the question and answer statement from the test set of TREC-QA (8-13) randomly, trained the model with/without coattention mechanism, and obtained the corresponding semantic vector representation through different models. The specific content verified that the presence or absence of a coattention mechanism had an impact on the analytical representation of the semantics of the statement. The comparison results are shown in In Secondly, we verified the epoch sensitivity of the above several models under different iteration periods. We performed an epoch-number sensitivity analysis on our proposed model, which varied from 5 to 35. We presented an optimized deep model by using stacked BiLSTM, coattention mechanism, attention mechanism, and a combined similarity metric, and our experimental results are shown in line 11 to line 15 of We did further comparison experiments on the Wiki-QA dataset. Validation of the model on the Wiki-QA dataset makes the proposed approach more convincing. The parameter initialization and preset aspects of the model on the Wiki-QA dataset are basically consistent with the settings of the TREC dataset, where the batch size of the dataset is 30. Because it is also the order of information retrieval and candidate answer rankings, according to the official evaluation data, the evaluation metrics are selected as MAP and MRR.We also validated the various models of the design under different epochs on the Wiki-QA dataset, as shown in The experimental results of each model under the Wiki-QA dataset are shown in In the field of intelligent question answering, these data results confirm that the model has some excellent performance in the statement semantic capture representation of questions and answers and can better represent semantic features.In this paper, we proposed a stacked BiLSTM neural network based on the coattention mechanism for question answering. Stacked BiLSTM is used to sentence semantic understanding and modeling; coattention mechanism and attention mechanism are utilized to obtain the codependent representation of questions and answers; the combination of cosine similarity and Euclidean distance is used to calculate the similarity between the question and the answer. As reported in


Visual attention is often predictive for future actions in humans. In manipulation tasks, the eyes tend to fixate an object of interest even before the reach-to-grasp is initiated. Some recent studies have proposed to exploit this anticipatory gaze behavior to improve the control of dexterous upper limb prostheses. This requires a detailed understanding of visuomotor coordination to determine in which temporal window gaze may provide helpful information. In this paper, we verify and quantify the gaze and motor behavior of 14 transradial amputees who were asked to grasp and manipulate common household objects with their missing limb. For comparison, we also include data from 30 able-bodied subjects who executed the same protocol with their right arm. The dataset contains gaze, first person video, angular velocities of the head, and electromyography and accelerometry of the forearm. To analyze the large amount of video, we developed a procedure based on recent deep learning methods to automatically detect and segment all objects of interest. This allowed us to accurately determine the pixel distances between the gaze point, the target object, and the limb in each individual frame. Our analysis shows a clear coordination between the eyes and the limb in the reach-to-grasp phase, confirming that both intact and amputated subjects precede the grasp with their eyes by more than 500 ms. Furthermore, we note that the gaze behavior of amputees was remarkably similar to that of the able-bodied control group, despite their inability to physically manipulate the objects. Humans interact continuously with objects in activities of daily living (ADLs). Vision and gaze play an important role during these interactions, not only to guide the activity itself but also in the initial planning phase. Gaze is thus said to be anticipatory and can be used to understand an individual's intentions even before they manifest themselves in the motor domain. Several studies have attempted to explore this proactivity to help disabled people, such as in a robot assistant scenario  electrodes. Contrary to prior work, asking amputees to perform “movements without movement”  to record the gaze behavior, first person video, and angular velocities of the head. These glasses sample gaze and gaze-related information at 100 Hz, while the video is recorded with a 1920 px × 1080 px resolution at 25. On their forearm, they had 12 Delsys Trigno electrodes  arranged in an array of eight equidistant electrodes at the height of the radiohumeral joint and four more electrodes in a second array 45 mm more distally. These electrodes record sEMG at 1926 Hz and contain an integrated three axes accelerometer that is sampled at 148 Hz. A picture showing the setup is shown in The experiment consisted of repeatedly grasping or manipulating household items placed on a table in front of the subject. The pairing of grasps and objects was specifically chosen based (1) on the likelihood of their co-occurrence in ADLs and (2) to attain as much as possible a many-to-many relationship between grasps and objects. In the first part of the experiment, subjects just had to perform a “static” grasp on the object without any manipulation, hold it for a few seconds and then return to a rest posture when instructed. The amputated subjects were asked to attempt to execute the action as naturally as possible “as if their missing limb were still there,” rather than just imagining it, to elicit activation of the remaining muscles in their residual limb. Each of the grasps in Given the scope of the present paper, we only use sEMG from the second and seventh electrode, which were placed approximately on the extensor and flexor digitorum superficialis. Besides having relatively high activations, these electrodes also indicate roughly whether the hand was opening or closing. To aid visualization, both channels were rectified with a moving root mean square with a window-length of 29 ms   grasping the object, (2) displacing it, or finally (3) releasing it. This behavior can clearly be seen for both intact as well as amputated subjects in the example in Finally, One of the aims of this work was to understand if a transradial amputation has introduced important changes in the visuomotor behavior of amputees. During the reach-to-grasp phase, the overall behavior of intact and amputated subjects is comparable. Even if the coordination timeline between eyes, head, and limb is similar, there are some minor discrepancies between the two groups. The main observed difference concerns the delayed activation of the forearm muscles during the reaching phase for amputated subjects, which was found to be statistically significant. Similarly, during the lifting tasks we noted slower pitch movements of the head. It is likely that some subjects interpreted the instruction to perform the grasp with their missing limb by activating their phantom limb. Such movements executed with the phantom limb are known to be slower than those executed with the intact hand  modality to verify whether we can realize an effective improvement in recognizing grasp intentions during the reaching phase.The datasets generated for this study are available on request to the corresponding author.The studies involving human participants were reviewed and approved by Ethics Commission of the canton of Valais in Switzerland and by the Ethics Commission of the Province of Padova in Italy. The patients/participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.The consortium contributed the initial conception of the study. VG and AG contributed conception and design of the study. MC, GS, MA, and the consortium collected the dataset. VG devised and implemented the automated segmentation under the supervision of AG. VG collected the segmentation dataset. VG performed the visuomotor analyses under the supervision of AG. VG wrote the first draft of the manuscript. AG rewrote sections of the manuscript. All authors contributed to manuscript revision, read, and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


In this paper, the effect of time synchronization error on protection algorithms are studied for the usage of the LAN-based collaborative protection. In order to derive the effect of time synchronization, this paper proposes a substation model which is constructed with IEEE 1588 Precision Time Protocol (PTP) supported intelligent electronic devices. The proposed model is used as an example of a target platform to study the effect of time synchronization error with two typical substation protection algorithms, i.e., current differential-based substation protection and distance protection algorithms. From the analyzed and the simulated results, it was well observed that time synchronization error is a significant error-causing factor for both protection algorithms, resulting in erroneous detection of faults and erroneous estimation of fault distances, respectively. The results of research performed in this paper are expected to provide a good guide for constructing the future LAN-based digital power substation with precise time synchronization. Future LAN-based digital substation is expected to provide collaborative protections with the utilization of wider range of time synchronized data acquired from the LAN-based distributed sensing environment. Therefore, the provision of precise time synchronization is a very important issue for the stable and reliable operation of the substation ,2,3,4,5.However, the implementation of the precise time synchronization is generally considered as a difficult task since it requires optimization of synchronizing parameters in connection with protective algorithmic details. Moreover, the proper handling of the fault causing factors in the LAN-based environment, such as failure of time synchronizing device, packet loss in heavy network, external security attack including GPS disturbance, etc., must be considered in the design and operation of the precise time synchronization.The standard and profiles, IEEE 1588 Precision Time Protocol (PTP)  and IEC For the optimized realization of time synchronization, domain specific protection features must be jointly considered to provide collaborative and advanced protection functions for future LAN-based digital substations. The joint consideration reflecting domain specific protection details is a difficult task to achieve since it requires comprehensive studies on substation protections in relation with time synchronization. The difficulty causes the lack of joint consideration in previous research and leads to the restrictive focuses on the performance of time synchronization itself.In this paper, two typical protection algorithms, i.e., a current differential-based substation protection algorithm  and a diA substation model which was constructed with IEEE 1588 PTP supported intelligent electronic devices (IEDs), is proposed in order to study the effect of time synchronization error. Computer simulations and analytic derivation were also performed for the validation of the effect of time synchronization error in the distributed sensing environment.The current differential-based substation protection algorithm  was simuThe effect of time synchronization error on the distance protection algorithm was analyzed and simulated with two source-based power system for the line-to-line fault case. From the analytic derivation of formula for per unit distance error, it is shown that time synchronization error appears inside the argument of tangent function in both real and imaginary parts of a relay estimating impedance. The validation of the analytical results is shown from the results of simulations. The simulation results also showed a significant amount of a per unit distance error was caused by time synchronization error.In this section, a time synchronizing IED-based substation model is proposed. The proposed substation model is considered as a basic and simplified structure to realize a collaborative protection in the future IEC 61850-based smart substation. The substation model will be used as an example of a target platform to study the effect of time synchronization error in typical substation protection algorithms in The basic structure of the proposed time synchronizing substation model consists of collaborative IEDs connected to the wired/wireless LAN-based network as shown in For the purpose of adaptive configuration of time synchronization, the two network-based protocols, i.e., IEC 61850 communication networks and systems for power systems  and IEEEThe time synchronization structure of the proposed substation model is designed with a master-slave based time synchronization protocol which is supported with hardware timestamping structure . This stReliability of digital substation cannot be achieved without providing the functions of time synchronization error detection and recovery. Master clock failure detection is a typical example of the collaborative operation of IEDs. The master clock failure detection is based on sharing of time correction data among the collaborative IEDs. The shared data are processed for the application of thresholding logic. As an example of detecting the master’s abnormal PTP time offset, the time windowed PTP time offset sequences are compared and thresholded with the data collected from distributed slave IEDs. As suggested in the IEC 61850-9-3 communication protocol, the TLV  message is a good choice to utilize for the sharing of PTP data .In the proposed substation model, a recovery management IED is suggested to share the TLV messages for the adaptive configuration of time synchronization during the PTP master failure. The core PTP parameters including backup run-time, clock accuracy class, synchronization period, etc., must be set adaptively reflecting the time synchronization error effects to the performance of protection algorithms. Therefore, the failure detection and recovery must be designed to realize flexible and adaptive profiles of substation protection reflecting the domain specific protections and algorithms.However, the optimized failure detection and recovery is very difficult to achieve because it requires a comprehensive study on the performance of substation protection and the effects of time synchronization error. In In this section, based on the substation model proposed in Functional blocks required for the design of current differential-based collaborative protection system are shown in The current differential-based main fault detection block detects a fault in the substation. The protection algorithm applies thresholding logic to the differential current value which is obtained from Kirchhoff’s Current Law (KCL)-based summation of the measurement data. Normalization of the measurement data should be performed before obtaining the differential current value since the measurement data includes primary and secondary current values of a transformer.The correction and compensation block produces the uncorrupted measurement data. Initialization process corrects the parameters used by the sensing units to obtain unbiased V/I (voltage and current) information. Compensation of nonlinearity was performed to prevent the distortion of measurement data caused by the saturation effect of an instrumental transformer.The PTP based measurement alignment block provides the synchronized measurement data from the distributed sensing units. A master-slave based time synchronization protocol guarantees precisely synchronized operation of the sensing units. The asynchronized measurement timing of each sensing unit is compensated by applying signal processing technique such as extra/interpolation of the measurement values.By analyzing the status of substation including load variation and transient of a fault, the protection algorithm operates adaptively. According to the status of substation, the parameters used by the protection algorithm and PTP structure are adaptively configured.In In this subsection, the effect of time synchronization error in measurement data on a digital distance protection algorithm for line-to-line fault case was analyzed. Time synchronization error was applied to B-phase of V/I signal under AB fault case. The operation of digital distance protection was based on the measurement and evaluation of the short-circuit impedance by using the phasors of discrete voltage and current signal . For eacUnder AB fault situation, the currents of A and B-phases, The phasor of the fundamental frequency of The phasors of the signals can be expressed as Equations (6)–(8), as well:From The second multiplication term of Equation (9) can be simplified by using Euler’s formula and trigonometric function:The real and imaginary parts of Equation (10) can be divided as Equation (11):Equation (11) shows time synchronization error in a distance relaying algorithm under AB fault case appears inside the argument of tangent function in both real and imaginary parts of a relay estimating impedance In this subsection, the effect of time synchronization error between phases in the distance protection algorithm was analyzed. In the future distributed sensing-based substation, traditional fixed measurement format will be changed into the freed and unconstrained measurement format for applying various protecting and monitoring approaches. The analytical result obtained from in the subsection is expected to provide basic information for constructing the future distributed sensing-based substation.Reflection of domain specific protection details for the designing of an advanced time synchronizing system in power substation is generally a difficult task since it requires comprehensive exploitation of inter-relationships among the many and various protection components in the substation. The effect of time synchronization error on protection algorithms in power system has not been much studied in previous research. However, the effect of time synchronization error in substation protection studied in this paper is compared with representative studies by Bi  and ZhanIn the following, the performance degradation caused by time synchronization error of two typical protection algorithms in power system are simulated. Current differential-based substation-area backup protection (SBP) algorithm  is simulSubstation-area Backup Protection (SBP)  is an alx-zone and Simplified diagram of a 154-kV substation is shown in Suppose that a transmission line fault occurs at fault 1 and SBP tries to find the fault component. SBP will start up due to zone A1 being in operating (fault) state. If SBP firstly tries to remove L2 from zone A1, the remaining zone (A2+L1) is still in operating state. Furthermore, after L1 is removed, remaining zone A2 immediately turns to restraining (fault released) state. Thus, it is determined that the fault lies at L1 . With fuTime synchronization error in SBP causes unaligned phasors which come from asynchronized sampled values among measuring points. This affects calculating In the simulation, it is assumed that time synchronization error occurs at the only one measuring point among 14 points in each simulation. The range of synchronization error is from 50 to 450 μs and for each error case 14 simulations are performed to consider all the case of time synchronization error in single measuring point.The performance of SBP algorithm is represented as the percentage of maloperation which was defined as 2 fault conditions, i.e., SBP fails to detect a fault or to find the location of a fault. The result of performance of SBP algorithm for the case of Fault 2 is shown in Higher load usage is more vulnerable to time synchronization error than lower load usage as shown in To validate the analytical result of the effect of time synchronization error in an algorithm for digital distance protection, two source-based power systems have been modeled which are shown in Comparison of the distance relay estimating resistance and the resistance obtained from the analytically derived formula is shown in Comparison of the distance relay estimating reactance and the reactance obtained from analytically derived formula is shown in To investigate the effect of time synchronization error in the operation of the distance protection algorithm, AB-fault simulations with varying time synchronization error on B-phase signal were performed for the mho type distance protection relay. In this paper, the effects of time synchronization error are analytically derived and simulated to show the occurrences of erroneous fault detection. The time synchronizing IED-based substation model is proposed to study time synchronization error effects with the two typical substation protection algorithms. A significant amount of maloperation ratio, which reaches to near 10%, is shown as a result of time synchronization error bound to 250 μs for the case of the current differential-based protection algorithm. A significant amount of a per unit distance error is also observed which ranges from 0.06% to 92.72% when the time synchronization error varies from 1 sample to 10 samples for the case of the distance protection algorithm. The importance of accurate and fault tolerate time synchronization, which are considered as essential for the realization of collaborative protection for future LAN-based digital power substations, is well illustrated through the results of this research. Also, the results of the analysis can be considered as important references in designing the reliable time synchronization reflecting the performance degradation of collaborative protections.


Small and pervasive devices have been increasingly used to identify and track objects automatically. Consequently, several low-cost localization schemes have been proposed in the literature based on angle of arrival (AoA), time difference of arrival (TDoA), received signal strength indicator (RSSI) or their combinations. In this paper, we propose a three-dimensional empirical AoA localization (TDEAL) technique for battery-powered devices. The proposed technique processes the AoA measurements at fixed reader nodes to estimate the locations of the tags. The proposed technique provides localization accuracy that mitigates non-linear empirical errors in AoA measurements. We utilize two omni-directional antenna arrays at each fixed reader node to estimate the location vector. With multiple location estimations from different fixed reader nodes, each estimated location is assigned a weight that is inversely proportional to the AoA phase-difference error. Furthermore, the actual AoA parabolic formula of the location is approximated to a cone to simplify the location calculation process. The proposed localization technique has a low hardware cost, low computational requirements, and precise location estimates. Based on the performance evaluation, significant location accuracy is achieved by TDEAL; where, for instance, an average error margin of less than 13 cm is achieved using 10 readers in an area of Non-satellite based localization is a fundamental basis for a multitude of Internet of Things (IoT) smart environment applications. Since IoT device fabric comprises low power and small footprint devices  tags, Zigbee nodes, Bluetooth tags, etc.), such devices, with their typical long lifetime, are ideal for indoor radio frequency (RF) based localization. In literature, several techniques have been proposed aiming at low infrastructure cost, high accuracy, and low computational complexity. Such techniques can broadly be categorized into range- and range-free based localization.In range-based techniques, time difference of arrival (TDoA), time of arrival (ToA), angle of arrival (AoA), and received signal strength indicator (RSSI) are dominant ,4,5,6,7.By contrast, range-free techniques are mainly based on fingerprint matching ,14,15,16In this paper, three-dimensional empirical AoA localization (TDEAL) is proposed. The TDEAL technique localizes a sender (hereafter referred to as a tag) in 3D space with respect to a fixed reference point (hereafter referred to as a reader). The scheme utilizes the robustness of AoA and the careful placement of readers at well-known and specified locations. The readers with antenna arrays are placed on the sidewalls of the localization area so that radio signals from the target are in the LOS of the readers. The collected AoAs from all readers are reported to a central database to apply the proposed method in localizing the target device at that given time. No modification on the tag is needed; however, two-antenna arrays are added to each reader to measure AoA.The contributions of this work are:The proposed TDEAL technique utilizes realistic  non-linear AoA in the calculation of the tag location.The proposed technique employs a weighted-sum that is inversely proportional to AoA phase-difference error to achieve higher location accuracy. The weight assignment in TDEAL promotes location estimations with low AoA error. The estimation of the tag’s location is approximated to cone equations (based on the linear slope of the cone) instead of hyperbola quadratic equations. This simplifies the calculation without sacrificing the accuracy of the estimated location.The rest of the paper is organized as follows. In Several node localization schemes have been proposed in the literature. The primal aim was to provide an estimate of the two or three-dimensional location in reference to an absolute reference point. In , Mao et For TDoA, researchers attempt to determine the location of an object based on the signal’s ToA from different sources. Subtracting the ToA of the signals will eliminate the need for determining the time at which the signal was generated thus eliminating the need for accurate clock synchronization at the objects to be localized. However, the clock synchronization issue will remain a critical part of the objects performing the localization process. In , the resFor RSSI, much work had been done on estimating the tag’s location and distance based on RSSI measurements. In general, to determine the location of an object based on the received signal strength, you mainly need two pieces of information: the transmitter′s location, and the signal strength at the transmitter. In , the resIn AoA-based schemes, clock synchronization among multiple nodes is not needed. Amundson et al.  proposedN readers to determine the 3D relative positions of K IoT devices tags. Let N readers and K tags. The positions of the readers are pre-determined and placed at the sidewalls of the area at which the tags are to be localized. This is to ensure clear LOS paths or LOS paths that are not blocked by metallic materials. If the readers are placed at lower elevation, higher number of readers will be needed to guarantee LOS with the tags. All readers in our technique have the same elevation , and consequently, the elevation of the tags is never higher than the readers’ elevation. An example of this model is illustrated in We employ Each tag uses an omni-directional antenna to broadcast its signals, while a reader receives the signals from the tags with vertical and horizontal antenna arrays. Each array consists of two antennas for AoA measurement. A reader with two antenna arrays is depicted in x-y plane is the horizontal plane, and z is the height . The location of any given reader The readers are assumed to be placed at a known location in the common orthogonal coordinate system (x-y plane) or the vertical . The phase difference 1d and 2d are the distances between the tag and the first and second antenna in the array, respectively. In To estimate the angle of arrival of the tag’s signal, an antenna array composed of two individual antenna elements are used. The two antenna elements are separated by a distance of To adapt the above relation between the tag location and the horizontal angle to a 3D space, for every measured In this section, the three-dimensional empirical AoA localization (TDEAL) is presented. The solution based on one reader is first introduced. The effect of the error in AoA is then illustrated, followed by tag location estimation two readers. The weighted average of the estimated location of a given tag is defined to mitigate location estimates based on high AoA errors. Finally, TDEAL location estimation algorithm is given to summarize the technique steps.In our location estimation algorithm, we reduce the complexity of the hyperbola equations by using a cone formed by the asymptotes of that hyperbola. This is justifiable as the distance between the target tag z-axis. Similarly, for the horizontal antenna array in which the antennas are placed alongside the x-axis to measure Note that x, y, z space ), then the two equations formed by the phase difference measurements As illustrated in Similarly, as Note that the two cone equations represented in The phase error plays a significant role in the accuracy of the estimated target location. In AoA detectors, the accuracy of the estimated tag location depends on the location itself; hence, the non-linearity in phase error . To consBy introducing the errorThe resultant two solution volumes in  in x-y location on the grid and its height dictate the phase difference To illustrate the relation between the measured angle from vertical and horizontal antenna arrays on the error in the phase difference, an example of the actual vertical angle ), In y-coordinates are closer to the reader’s y-coordinates , x-coordinates are closer to the reader’s x-coordinates  which is mapped to a constant error aroundIn In summary, Within the localization area, refer to  unless:x,y-coordinates of the reader  of the readers is set to (a) same height of 3 m in evaluation scenario 1, (b) different heights that are uniformly distributed from 2.55 to 3.45 m in evaluation scenario 2.In the following, we evaluate TDEAL with two scenarios. The Scenario 1 : the localization error between the actual tag location and the estimated tag location by TDEAL technique is reported. The empirical phase error of AD8302 at 900 MHz in Equation (4) is applied by all readers to calculate AoA. The localization error of a tag that is detected by the two readers The reported results in The first observation is the error dependency on the tag’s height. The lower the tag’s height, the higher the accuracy For the same number of localizing readers, the localization accuracy gets higher as the elevation of the tags gets lower (closer to the floor). (2)A dramatic increase in the mean location error is observed when the tag is at the same elevation of the localizing readers due to the high error in The second observation describes the error dependency on the number of readers. From The third observation in Scenario 2 (readers at different heights): In this scenario, we evaluate the localization accuracy when the readers are not at the same height from the floor. To maintain the applicability of the TDEAL algorithm, the lowest reader is placed at a height above the maximum height of the tag. This is justifiable as in indoor environments the tags are usually are attached to humans or mobile objects with known maximum possible height.In this scenario, the reader The readers above the average readers’ height , have lower average phase difference errors, especially vertical phase difference error  which yields vectors instead of hyperbola intersection trajectories. TDEAL is designed so that two non-collinear readers measure the vertical and horizontal AoA angles from a given tag and report them to a central database. Then the tags’ locations are estimated from all combinations of any two readers while accounting for the inherited angle error in such a location estimate. Angle- and distance-dependent weights are assigned by the proposed technique to hinder high error-location estimates.The simulation of TDEAL based on the polynomial approximation of the empirical phase error profile validates the effectiveness of the proposed TDEAL under realistic assumptions. It is shown that the TDEAL technique is capable of accurately estimating the location of tags (at different heights) in a relatively large localization area. For instance, with 10 readers TDEAL was able to achieve an average error of less than 13 cm with a tag height of 1.5 m. The integration between TDEAL and range-free localization or inertial navigation systems is a future direction to improve localization accuracy under the constraint of a low number of readers.In the future, we are planning to extend this work to evaluate TDEAL under NLOS conditions. We also look forward to implementing TDEAL for tracking applications in which subsequent location estimation  can be applied for the targeted indoor applications. The potential optimizing of the readers’ location as a function of the empirical error profile is also part of our future plans.


This paper discusses a high-performance similarity measurement method based on known map information named the cross mean absolute difference (CMAD) method. Applying the conventional normalized cross-correlation (NCC) feature registration method requires sufficient numbers of feature points, which must also exhibit near-normal distribution. However, Light Detection and Ranging (LiDAR) ranging point cloud data scanned and collected on-site are scarce and do not fulfill near-normal distribution. Consequently, considerable localization errors occur when NCC features are registered with map features. Thus, the CMAD method was proposed to effectively improve the NCC algorithm and localization accuracy. Because uncertainties in localization sensors cause deviations in the localization processes, drivable moving regions (DMRs) were established to restrict the range of location searches, filter out unreasonable trajectories, and improve localization speed and performance. An error comparison was conducted between the localization results of the window-based, DMR–CMAD, and DMR–NCC methods, as well as those of the simultaneous localization and mapping methods. The DMR–CMAD method did not differ considerably from the window-based method in its accuracy: the root mean square error in the indoor experiment was no higher than 10 cm, and that of the outdoor experiment was 10–30 cm. Additionally, the DMR–CMAD method was the least time-consuming of the three methods, and the DMR–NCC generated more localization errors and required more localization time than the other two methods. Finally, the DMR–CMAD algorithm was employed for the successful on-site instant localization of a car. Autopilot technology was developed to substantially improve driving safety and convenience and thereby mitigate the burden of drivers. In the future, fully automated vehicles will likely constitute the main body of the smart transportation system and replace human drivers entirely; however, in its current form, this technology is more moderately implemented in advanced driver assistance systems. One mandatory function of autopilot technology is environmental perception, which prevents collision. Similarly crucial is accurate localization, particularly in urban environments where vehicles are operated on city roads; like human drivers, automated vehicles must adhere to traffic rules.The existing self-localization systems in vehicles are dependent on sensor assistance, and they are categorized into passive or active sensor systems according to the types of sensors used. Passive sensor systems are further divided into global navigation satellite systems, inertial navigation systems, and stereo visions. The accuracy of global navigation satellite systems is affected by non-line-of-sight reception and multipath interference ; when opThe existing active sensors comprise laser range finders and light detection and ranging (LiDAR) systems, the latter of which are more commonly used. Prior research on smart vehicles has predominately discussed the successful implementation of two-dimensional (2D) LiDAR and Velodyne active sensor systems. Overall, active sensors are widely favored over passive sensors because they simplify the distance estimation processes of basic distances and generate desirable localization results.Simultaneous localization and mapping (SLAM) systems simultaneously illustrate and update maps of unknown environments and locate agents. SLAM is a primary component of robot navigation systems, and has considerably evolved over the past two decades. As its name implies, SLAM systems provide both localization and mapping functions. The localization functions comprise curb-based, road mark-based, and landmark-and-building-based localization. Hata et al.  developePrevious studies have incorporated various estimation technologies to solve the problems in SLAM. Smith and Cheeseman ,15 develFor a 3D point cloud map, existing approaches, including Normal Distribution Transform (NDT) ,19,20,21Earlier, Chong et al.  proposedThe present study employed the synthetic LiDAR as its basic framework, proposed a high-robustness similarity measurement method measuring cross mean absolute difference (CMAD), and integrated the CMAD in the drivable moving regions (DMRs) for instant localization. This localization method detected moving objects more satisfactorily than did the conventional normalized cross-correlation (NCC) method. Notably, only the 3D LiDAR was employed herein, and no additional odometer or IMU data were incorporated for support. Therefore, the search method did not feature a motion model, and the vehicle travel information could not be accurately identified. Furthermore, when the window-based method was employed for localization, the estimated location would suddenly shift sideways or backwards; hence, DMRs were added to restrict unreasonable movement regions, filter inappropriate localization trajectories, and improve the speed and performance of the localization system. According to the results, although the DMR method did not markedly differ from the window-based method in its localization accuracy, it required less time to locate the vehicle than did the window-based method. Additionally, when a particle filter was used for localization, the particles were not required to be spread across the entire window region; rather, they were only required to be spread to the farthest possible drivable region, thereby shortening the convergence time and attaining instant localization. The aforementioned procedures were also employed for the LiDAR on-site scanning process. After all the features were extracted, the initial location and direction were estimated through the mean energy method, and the DMR was incorporated in the feature registration process to identify the current location and direction of the vehicle. X–Z plane of the point cloud, portrayed in In the experiment, the position of the LiDAR was not calibrated and thus diverged from the road surface, leading to the point cloud information pattern depicted in The calibrated point cloud was segmented to capture the features orthogonal to the road surface. The goal of segmentation was to obtain the inner product between the normal vectors of the segmented point cloud and those of the road point cloud. Therefore, the features perpendicular to the road must be retained. The inner product was within the range between the threshold values and represented the desired feature point. Calculating the inner product required segmenting the point cloud information of the road d, and caAfter the normal vectors of the segmented point cloud and road point cloud were calculated c,e and t2. Additionally, the grid map was incorporated to establish a map database as illustrated in x-axis, y-axis, and features information. The aforementioned procedures were also employed for the LiDAR on-site scanning process to capture the environmental features on-site, which were then registered with the feature data in the map database to identify the optimal location and direction. The 3D point cloud was transformed into a 2D grid map for extracting features and constructing a map database following its segmentation and calibration. x-axis represents the angles and the y-axis represents the distances. Therefore, each cycle of LiDAR scan yielded 360 degrees of distance–angle data. Assuming that the grid database exhibited N possible vehicle locations, indicated by the green area in N × 360 feature data. These data were then incorporated into the map database containing only location information.The environmental features were extracted from the grid map for their registration with the LiDAR data. Notably, virtual LiDAR scanning, rather than global scanning, was used to extract the features because locally scanned features are more accurate than those scanned globally. The features were scanned from within the circle with radius R (30% of the maximum scanning range), as depicted in The map and LiDAR features were registered to obtain the optimal location and heading angle of the vehicle in the follow-up localization calculation. The currently prevalent template matching technique involves conducting similarity measurement through the NCC method ,37,38.N represents the degree of the reference signal (set as 360). This process was conducted through Fourier transform in the frequency domain to reduce calculation cost. Specifically, when The reference and test signal were expressed as V represents the optimal location and heading angle selected through the poll mechanism.Applying the NCC requires a sufficient number of matching points, which must also exhibit near-normal distribution. Herein, the point cloud information scanned through the LiDAR was relatively scarce. Consequently, a large localization error would result when the NCC features were matched with those of the LiDAR and the map. To enhance the NCC algorithm, the CMAD method was applied to compare the similarities between the map and LiDAR features. The parameters involved in this process are listed as followsfeatures b, PMap rfeatures a, W reprM represents the degree of W and L points, the minimal L points was used to determine the optimal location, As  matched c. BecausR. Next, both the LiDAR and map features were calculated through the mean energy method, which involves adding the distance values of all the scanned energy points together and dividing the sum by the number of energy points. Equation (7) measures the energy of the map, where N represents the number of energy points scanned, ith degree, (8) measures the energy of the LiDAR, where M represents the number of energy points scanned, and jth degree. Thus, the energy data of the map were established and implemented in the map database.The feature extraction was performed locally. Therefore, some angles did not show any distance value because no obstacles were scanned in that angle or that the distance values exceeded the scanning radius t represents the tolerable error, which was smaller indoors and larger outdoors. Because the point cloud of the map was more comprehensive than the on-site point cloud of the LiDAR (which was relatively scarce), most of the energy values of the map were higher than those of the LiDAR. Theoretically the initial location can be obtained by globally search the best registration of the map and LiDAR features. To reduce the computation time, the mean energy method was also applied to globally search the coarse initial location and heading angle of the vehicle. The possible locations of the vehicle were selected through the aforementioned average energy values. The selection results obtained using the mean energy method are indicated in red in The mean energy method was also applied to globally search the initial location and heading angle of the vehicle. The possible locations of the vehicle were selected through the aforementioned average energy values, where w × h window was created, depicted as the purple rectangular box in After the initial location of the vehicle was identified through the mean energy method, its location in the next time point was determined through window-based localization. Unlike the mean energy method, which was applied for a global search, window-based localization involved locally searching for the possible locations of vehicle through the window search method, and required considerably less calculation time. First, the initial location as calculated through the mean energy method was set as the center. A Because the location of the vehicle was searched using only 3D LiDAR without additional odometer or IMU data, and because the system did not include any motion model, the vehicle movement information could not be identified. Therefore, DMR-based localization was also conducted to calculate the trajectories that approximated to the actual vehicle movement. Although the motion trajectories that were estimated through the window-based localization could result in sideways or backwards deviations from the normal movement status, indicated by the red circles in r was established . The entire DMR is illustrated in r. The z-axis. Finally, the features of the locations in the area were registered with the concurrent LiDAR features to isolate the current location of the vehicle on the map, which is identified by the orange point in Similar to the window-based localization, the DMR-based localization involved estimating the initial location and direction of the vehicle through the mean energy method. Using this initial location as the center, the DMR with the maximal movement distance radius R and the rotation radius Velodyne LiDAR (VLP-16) was employed to scan the surrounding environment using a laser, and establish a 3D point cloud. Notably, if the LiDAR sensor had been set up directly on the car, then it would have scanned the car itself because of the insufficient height. Therefore, the aluminum extrusion support frame attached with a cloud deck was heightened to thoroughly construct the 3D point cloud on the outlines and obstacles of the environment. The indoor environment selected for this study was the parking lot in Basement 5 of National Taipei University of Technology (NTUT). The motion trajectory detected through the window-based localization was smoothed using the EKF and compared with the trajectory identified through the SLAM method. The motion trajectory detected through the DMR-based localization was smoothed using the EKF and compared with the SLAM trajectory. The DMR–NCC trajectory was also compared with the SLAM trajectory. The outdoor environment for this study was the NTUT campus. The motion trajectory detected through the window-based localization was smoothed using the EKF and compared with the trajectory identified through the SLAM method. The motion trajectory detected through the DMR-based localization was smoothed using the EKF and compared with the trajectory identified through the SLAM method. The DMR–NCC trajectory was also compared with the SLAM trajectory. The comparison of the root mean square errors (RMSEs) and SDs of the indoor and outdoor errors are outlined in In the experiment, Velodyne LiDAR (VLP-16) was employed to scan the surrounding environment using a laser and establish a 3D point cloud. The computer platform that was used for vehicle localization was equipped with an Intel i5 CPU, 8 GB DDRIII. This study employed the map-based DMR localization method to improve upon the sudden sideways and backwards deviations in the window localization algorithm. The DMR–CMAD and window methods did not differ substantially in their localization errors according to the RMSE and SD comparison results. However, the DMR–NCC method exhibited more errors and required more localization time than did the DMR–CMAD and window methods; the DMR–CMAD method was the least time-consuming of the four employed methods. Because the features of the outdoor experiment environment were more complicated than those of the indoor environment, the feature registration accuracy was slightly lower in the outdoor experiment than in the indoor environment, and the outdoor localization errors were markedly larger than the indoor localization errors. However, the localization accuracy of the DMR–CMAD method was overall ideal, and the method was confirmed as applicable for instant localization.This study also incorporated the LiDAR to capture the environmental features on-site, which were then registered with the feature data in the map database to identify the optimal location and direction. However, if the features of future experimental sites differ from those of the map database, inaccurate localization may result. Furthermore, because Velodyne VLP-16 LiDAR was used to extract the on-site environmental characteristics, its number of point clouds was less than those of other 3D LiDAR systems. The point cloud densities in outdoor environments were relatively sparse, and the great variation of the point clouds between each frame resulted in substantial matching iteration error. Therefore, other types of sensors—GPS and IMU—can be used to reduce the problem of matching iteration error.


Gastric mucus gel is known to exhibit dramatic and unique swelling behaviors in response to the ionic composition of the hydrating solution. This swelling behavior is important in the maintenance of the mucus layer lining the stomach wall, as the layer is constantly digested by enzymes in the lumen, and must be replenished by new mucus that swells as it is secreted from the gastric wall. One hypothesis suggests that the condensed state of mucus at secretion is maintained by transient bonds with calcium that form crosslinks. These crosslinks are lost as monovalent cations from the environment displace divalent crosslinkers, leading to a dramatic change in the energy of the gel and inducing the swelling behavior. Previous modeling work has characterized the equilibrium behavior of polyelectrolyte gels that respond to calcium crosslinking. Here, we present an investigation of the dynamic swelling behavior of a polyelectrolytic gel model of mucus. In particular, we quantified the rate at which a globule of initially crosslinked gel swells when exposed to an ionic bath. The dependence of this swelling rate on several parameters was characterized. We observed that swelling rate has a non-monotone dependence on the molarity of the bath solution, with moderate concentrations of available sodium inducing the fastest swelling. Gastric mucus is a polyelectrolyte gel which serves an important biological function. It is generally accepted that the gastric mucus layer provides a protective barrier between the stomach wall and the stomach interior, shielding the wall from acid and digestive enzymes and preventing auto-digestion of the stomach epithelium. However, there are several outstanding questions regarding the maintenance of the gastric barrier. Digestive enzymes within the stomach are constantly degrading the mucus layer from the inside-out, cleaving the mucin glycoproteins and destroying the entangled network which makes up the mucus gel . This deFresh mucus is secreted from epithelial cells on the stomach wall via exocytosis of microscopic vesicles filled with densely packed mucin polymers. This dense packing of negatively charged polymers is shielded by an abundance of divalent calcium ions within the vesicle . When thnt bonds ,7,8,9,10The dynamics of swelling hydrogels have been studied for over seventy years, using theoretical frameworks of increasing sophistication . Howevern) and solvent (subscript s). The network represents the entangled mesh of polymeric proteins which give rise to the gel, while the solvent represents the interstitial hydrating fluid. Each material is allowed to move with its own distinct velocity. Dissolved ionic species are allowed to move through the solvent phase, and bind/unbind to/from the network phase.In this work, we choose to model a mucus gel using a two-phase framework. Similar frameworks have been used in a wide variety of biological contexts, including the modeling of blood clots, cellular mechanics, and bacterial biofilms ,15,16,17p is the hydrodynamic pressure. The final term in Equation (5) replaces the drag forces between the ions and the solvent. In effect, the forces from the ionic potentials are transferred to the solvent because the only forces that act on the ions of type j are that from p is determined by the incompressibility constraint in Equation (3). In Equation (5), j to the number density of water particles. This ionic contribution is valid in the limit that ions are dilute in the solvent.As is standard in a two-phase model, there are four equations for the composite material composed of network and solvent. The first two equations describe conservation of mass of the solvent and network phases, respectively:The internal stresses within each phase must be given by a constitutive law. In this work, we assume that both the solvent and network exhibit a viscous response (though the modeling framework is adaptable to account for elastic or viscoelastic constitutive laws as well). In one spatial dimension, the stress tensor for each phase reduces toj measured in units of moles per liter solvent volume, R: ideal gas constant; T: absolute temperature; and F: Faraday constant). The parameter j to the gel network, while The ionic species dissolved within the solvent phase are each subject to a Nernst–Planck type equation, modified to account for diffusion through a fluid of non-uniform volume fraction. Cations may bind to the network via mass-action type reactions, while anions may not. We are specifically interested in the behavior of the model when we have three distinct types of ions present: a monovalent cation , a divalent cation , and a monovalent anion (chloride).total volume. Because calcium is divalent, it may bind twice, and therefore exists in one of two bound states: singly bound  account for entropic, long-range electrostatic, and short-range internal energy effects. The potentials acting directly on the solvent are given byj. Equation (17) accounts for both entropic (I) and electric (II) potentials.Because the ionic species are regarded as massless, the forces on each species are in balance. Thus, the chemical potential force and the solvent drag force on each ionic species sum to zero. Since the drag force the ions exert on the solvent is the opposite of that the solvent exerts on the ions, the net effect is that the chemical potential forces appear to act on the solvent itself (as incorporated in the last term of Equation (5)). The potentials which act on dissolved ions are given byWe now return to the term arameter . HoweverFinally, terms found in .total amount of calcium, sodium, and chloride. Under the assumption that all species are spatially uniform, Equations (7) to (12) may be solved to determine the individual concentrations , and the diffusion coefficients , as well as the regime where this is a more moderate density of binding sites (referred to as “sparse binding”). Estimates for the density of cation binding sites on ne molar . Howeverne molar  suggest cus used ,20. Furtcus used  assumed To quantitatively measure the rate at which the network phase swells, we track the maximum network volume fraction , for sodium concentrations between approximately In this paper, we have presented the first investigation of the dynamic swelling behavior of the model of polyelectrolyte gels first derived in . We charFinally, we note that, for the sake of simplicity, we chose to treat the rheology of the mucus network as constant and viscous. However, it is known that mucus networks may exhibit a wide range of viscoelastic behaviors depending on the ionic milieu and other factors ,22,23, i


The study of gene flow in pedigrees is of strong interest for the development of quantitative trait loci (QTL) mapping methods in multiparental populations. We developed a Markovian framework for modeling ancestral origins along two homologous chromosomes within individuals in fixed pedigrees. A highly beneficial property of our method is that the size of state space depends linearly or quadratically on the number of pedigree founders, whereas this increases exponentially with pedigree size in alternative methods. To calculate the parameter values of the Markov process, we describe two novel recursive algorithms that differ with respect to the pedigree founders being assumed to be exchangeable or not. Our algorithms apply equally to autosomes and sex chromosomes, another desirable feature of our approach. We tested the accuracy of the algorithms by a million simulations on a pedigree. We demonstrated two applications of the recursive algorithms in multiparental populations: design a breeding scheme for maximizing the overall density of recombination breakpoints and thus the QTL mapping resolution, and incorporate pedigree information into hidden Markov models in ancestral inference from genotypic data; the conditional probabilities and the recombination breakpoint data resulting from ancestral inference can facilitate follow-up QTL mapping. The results show that the generality of the recursive algorithms can greatly increase the application range of genetic analysis such as ancestral inference in multiparental populations. FurtherThe theory of one-locus gene flow in a pedigree has been well developed. The haploid genomes of pedigree founders are designated by distinct labels, called founder genome labels (FGLs). A set of genes are identical by descent (IBD) if they carry the same FGLs. The identity state for two genes is either IBD or non-IBD. The IBD probability for two distinct genes within an individual is the inbreeding coefficient, and it is the kinship coefficient for the two genes randomly sampled from two distinct individuals. L distinct FGLs. Thus, the calculation of the two-locus ancestral inferences has been developed only for simple breeding systems including selfing, brother-sister (or sibling) mating, and parent-offspring mating  under the assumption of FGLs being exchangeable, which is applicable for the construction of Markovian framework in simple breeding schemes. Then we develop a recursive algorithm (denoted by NON-EXCH) for modeling ancestral origins to relax the exchangeability assumption. The two recursive algorithms apply to both autosomes and sex chromosomes if they exist. The results of both recursive algorithms are compared with those from extensive simulations on a classical pedigree. We first apply the two algorithms to compare different population designs (or breeding pedigrees) prior to experiments, for example, in terms of the overall density of junctions (recombination breakpoints), an important factor of QTL mapping resolution. In addition, the non-exchangeability can be illustrated under various breeding designs. Then we apply the two algorithms to incorporate pedigree information for ancestral inference from genotypic data in simulated and real collaborative cross (CC) populations, resulting in conditional probabilities that are necessary for downstream QTL mapping.a, b, c the members of a pedigree, and denote by a comes after individual bm the maternally derived genes or chromosomes, and p for the paternally derived. We denote by superscripts o, m or p) of genes or chromosomes. For the sake of brevity, a, XX chromosomes of female a, and XY chromosomes of male a, respectively.The symbols are briefly explained in a back to its two parental genes or chromosomes if the maternally derived gene or chromosome concerns the quantity, and otherwise trace the paternally derived gene or chromosome. Throughout this paper, a, rather than any other, respectively.In the derivations of recurrence relations of a quantity, we will focus on a particular ordering a and has parental origin b and has parental origin The identity coefficient rigin o2 . There aa and have parental origin b and have parental origin An expected identity junction density is defined as the expected number of the specified type of recombination breakpoints per Morgan along two homologous chromosomes. Here expectation concerns the stochasticity of gene flow from founders to descendants on a fixed pedigree. And identity indicates that only the identity patterns (not specific FGLs) on the two sides of junctions matter. In the recursive algorithm NON-EXCH, we will introduce ancestral junction densities where the specific FGLs do matter. For example, e (1232) . Here thπ of ancestral origins and a rate matrix Q. Under the assumption of exchangeability among FGLs, the initial distribution π of individual a is determined by the identity coefficient Q of individual a is determined by the five expected identity junction densities Q from the five junction densities.Following the previous framework , we modeS is true and 0 otherwise, and let In the following, we describe a recursive algorithm for calculating the identity coefficients and the expected junction densities for an individual in a given pedigree. In short, let e.g., The recurrence relations for the two- and three-gene identity coefficients are similar to the recursive algorithm of a are given bya, the second equation follows from the rules 1 and 3 for the paternally derived gene within individual a, and the last equation is obtained by reversing the ordering of two genes. The symmetries such as a.We derive the recurrence relations according to the Mendelian inheritance rules: (1) a maternally  derived autosomal gene descends from the two genes within the mother  with equal probability The boundary conditions of these recurrence relations are given according to the assignment of FGLs to the founders in a pedigree. If we assign distinct FGLs to each haploid genome of an outbred founder, all multi-gene non-IBD probabilities are 1 if any pair of genes is not from the same haploid genome, and 0 otherwise. Four-gene or higher order identity coefficients may be derived similarly, but they are not required for the derivations of junction densities.a. The implicit two-gene identity state for the map expansions is a is given by a are relatively simple, and they are given by  between two chromosomes can be formed only by duplicating the chromosome segment harboring the recombination breakpoint. For the expected junction density a are invisible.We derive the recurrence relations for The boundary conditions are given by the assignment of FGLs to the founders. The within- and between-founder identity junction densities are 0 if a single FGL is assigned to the whole haploid genome of each founder.Let a carries FGL We represent a two-gene ancestral state by π of the Markov chain can be constructed from the two-gene ancestral coefficients, and the rate matrix Q can be constructed from the expected ancestral junction densities, without assuming the exchangeability of FGLs.Similarly, the initial distribution a, we haveThe relations of the ancestral coefficients are very similar to those of the identity coefficients, and they are based on the same rules of Mendelian inheritance. For example for the one-gene ancestral coefficient The boundary conditions of the recurrence relations of the ancestral coefficients are given by the FGLs assigned to the founders in a pedigree.a with parental origin o, while the terms on the right-hand side refer to the junctions on the two homologous chromosomes of a. We have i and j.The ancestral map expansions can be expressed in terms of the expected ancestral junction densities as followsi and j, for example, i and j at the location of a crossover.The recurrence relations for the ancestral map expansions are given byThe recurrence relations for As before, the within- and between-founder ancestral junction densities are 0 if a single FGL is assigned to the whole haploid genome of each founder.https://github.com/chaozhi/RABBIT.git, and it is offered under the GNU Affero general public license, version 3 (AGPL-3.0). Example scripts for using the recursive algorithms, simulating genotypic data, and ancestral inference are included. The real CC data have been described by Ancestral inference using the two recursive algorithms is implemented in the previous developed RABBIT software, where the function magicReconstruct is extended to incorporate pedigree information. RABBIT is available at Before applying the two recursive algorithms EXCH and NON-EXCH to multiparental populations, we evaluate their accuracy by forward simulations on the classical pedigree of Native Americans  Chapman. The peds result .We confirmed that the numerical results from the algorithm NON-EXCH are reduced to those from the algorithm EXCH, by summing over possible FGLs under the given identity pattern. In addition, we confirmed the consistency between the two algorithms in the multiparental populations shown in Figure 4.e.g., sibling mating. The alternating backcross and the father-daughter backcross have been studied by We apply the recursive algorithm EXCH to multiparental populations, which have become attractive for QTL mapping in many animal and plant species. Specifically, we study the inbreeding process by calculating the IBD probability  schemes . In the e.g., aamp(11) , and hasion (t≥5).We apply the recursive algorithm NON-EXCH to study the prior FGL exchangeability for the multi-way funnel breeding schemes . We assuThe right panels of We examine the exchangeability patterns for the other multi-way funnel breeding schemes, and focus on autosomes since the FGL exchangeability does not hold in general for sex chromosomes because of the asymmetry between X and Y chromosomes. The non-exchangeability of Either one of the two recursive algorithms can be used as a prior to incorporate pedigree information for ancestral inference in multiparental populations from genotypic data, which will be illustrated as follows by simulated and real CC populations.We simulate a CC population  or the sex chromosomes (XX). We perform two analyses for each data set by applying each of the two recursive algorithms as the prior for modeling ancestral origins along two homologous chromosomes within an individual. See t in the range of The real CC population consists of 120 lines that are sampled at generation To study the effect of marker densities on ancestral inference, we analyze only the first pair of homologous autosomes and thin the full dataset by taking every second SNP markers, and repeat to obtain nested sub datasets. The data fractions or the relative marker densities are given by We have developed two novel recursive algorithms for modeling genomic ancestral origins along two homologous chromosomes in a pedigree with arbitrary but known structure. The algorithms apply to both autosomes and sex chromosomes when they exist, and allow selfing in the pedigree. The extensive simulations on a real example pedigree show that the numerical results from the two recursive algorithms are consistent with the simulated results, apart from the stochasticity of gene flow. The Markov property is assumed for the ancestral origin process along two chromosomes, and thus genetic interference is assumed to be absent. The assumption does not affect the expected junction densities calculated from the two recursive algorithms, although it does affect the distribution of inter-junction distances including the variance of junction densities.One important application of the recursive algorithms is to design a breeding scheme for accelerating the inbreeding process to obtain immortal lines and for maximizing the resolution of mapping QTL. The second important application of the two recursive algorithms is to provide an appropriate way of incorporating pedigree information for analyzing genotypic data in bi- or multiparental populations. Specifically, the two recursive algorithm can be used to calculate the process parameter values of hidden Markov models for genotypic data, that is, the prior probability distribution of ancestral origins (FGLs) at an initial site and the prior transition probability matrix describing how ancestral origins change along two homologous chromosomes within an individual. See Furthermore, we have applied the two recursive algorithms to incorporate pedigree information for genotype imputation in multiparental populations (