Position Coding Research Articles

A Spatio-Temporal Attention Mechanism Based Approach for Remaining Useful Life Prediction of Turbofan Engine.

The time-series data generated by turbofan engines has a great degree of complexity and dynamics. At present, recurrent neural networks are commonly used to model and forecast the remaining useful life (RUL). The relationship of the sample data is not taken into account, and there are issues such as gradient explosion. In view of this, a spatio-temporal attention model is proposed, which comprehensively relates to the temporal association of data features and the hidden state of data features in space. At the same time, position coding is performed on the temporal relationship, avoiding the use of recurrent neural networks. Experimental results show that by combining the two dimensions, the predictive performance of the model is significantly improved. Compared with different methods on the four data sets of the commercial modular aerospace propulsion system simulation (C-MAPSS), the stability and prediction accuracy of the spatio-temporal attention model are better than that of alternative methods.

Generating accurate 3D gaze vectors using synchronized eye tracking and motion capture.

Assessing gaze behavior during real-world tasks is difficult; dynamic bodies moving through dynamic worlds make gaze analysis difficult. Current approaches involve laborious coding of pupil positions. In settings where motion capture and mobile eye tracking are used concurrently in naturalistic tasks, it is critical that data collection be simple, efficient, and systematic. One solution is to combine eye tracking with motion capture to generate 3D gaze vectors. When combined with tracked or known object locations, 3D gaze vector generation can be automated. Here we use combined eye and motion capture and explore how linear regression models generate accurate 3D gaze vectors. We compare spatial accuracy of models derived from four short calibration routines across three pupil data inputs: the efficacy of calibration routines was assessed, a validation task requiring short fixations on task-relevant locations, and a naturalistic object interaction task to bridge the gap between laboratory and "in the wild" studies. Further, we generated and compared models using spherical and Cartesian coordinate systems and monocular (left or right) or binocular data. All calibration routines performed similarly, with the best performance (i.e., sub-centimeter errors) coming from the naturalistic task trials when the participant is looking at an object in front of them. We found that spherical coordinate systems generate the most accurate gaze vectors with no differences in accuracy when using monocular or binocular data. Overall, we recommend 1-min calibration routines using binocular pupil data combined with a spherical world coordinate system to produce the highest-quality gaze vectors.

Position coding as a means of increasing the range of optical communications links

Subject of study. We present research on the range of atmospheric optical communications links as a function of atmospheric conditions, the types of laser beam modulation used, and the type of interference-resistant coding used. Aim. We develop an approach for increasing the range of free-space optical communications links by improving resistance to atmospheric turbulence. Methods. We show that the modulation technique and channel coding must be compatible if optimum results are to be achieved. Pulse position modulation and interference-resistant position coding are one example of such a compatible combination; a holographic code in which a sequence of pulses representing a 1D linear hologram of a single pulse replaces a single pulse in the desired position is one example of an interference-resistant code. In this case, position modulation is still being used, but in the form of multiple pulse position modulation. A holographic code takes advantage of the fact that holograms are divisible, and a fragment of the hologram can be used for recovery of transmitted data (as well as data hidden by noise). The recovery capacity of the holographic code depends on the hologram length—the number of slots per symbol interval. Main results. We show that holographic coding provides higher interference resistance and a lower probability of detector error and provides the same benefit as an increase in transmitter power. Practical significance. The benefit from holographic coding may be used to either increase the communications range or increase the communications channel reliability. Position coding has the advantages that the redundant information required for interference-resistant encoding is created within the symbol interval, does not affect the symbol repetition frequency, and has no effect on the data transmission rate.

DS-DETR: A Model for Tomato Leaf Disease Segmentation and Damage Evaluation

Early blight and late blight are important factors restricting tomato yield. However, it is still a challenge to accurately and objectively detect and segment crop diseases in order to evaluate disease damage. In this paper, the Disease Segmentation Detection Transformer (DS-DETR) is proposed to segment leaf disease spots efficiently based on several improvements to DETR. Additionally, a damage assessment is carried out by the area ratio of the segmented leaves to the disease spots. First, an unsupervised pre-training method was introduced into DETR with the Plant Disease Classification Dataset (PDCD) to solve the problem of the long training epochs and slow convergence speed of DETR. This method can train the Transformer structures in advance to obtain leaf disease features. Loading the pre-training model weight in DS-DETR can speed up the convergence speed of the model. Then, Spatially Modulated Co-Attention (SMCA) was used to assign Gaussian-like spatial weights to the query box of DS-DETR. The different positions in the image are trained using the query boxes with different weights to improve the accuracy of the model. Finally, an improved relative position code was added to the Transformer structure of DS-DETR. Relative position coding promotes the capture of the sequence order of input tokens by the Transformer. The spatial location feature is strengthened by establishing the location relationship between different instances. Based on these improvements, the DS-DETR model was tested on the Tomato leaf Disease Segmentation Dataset (TDSD) constructed by us. The experimental results show that the DS-DETR proposed by us achieved 0.6823 for APmask, which improved by 12.87%, 8.25%, 3.67%, 1.95%, 10.27%, and 9.52% compared with the state-of-the-art: Mask RCNN, BlendMask, CondInst, SOLOv2, ISTR, and DETR, respectively. In addition, the disease grading accuracy reached 0.9640 according to the segmentation results given by our proposed model.

Natural switches in behaviour rapidly modulate hippocampal coding

Throughout their daily lives, animals and humans often switch between different behaviours. However, neuroscience research typically studies the brain while the animal is performing one behavioural task at a time, and little is known about how brain circuits represent switches between different behaviours. Here we tested this question using an ethological setting: two bats flew together in a long 135 m tunnel, and switched between navigation when flying alone (solo) and collision avoidance as they flew past each other (cross-over). Bats increased their echolocation click rate before each cross-over, indicating attention to the other bat1–9. Hippocampal CA1 neurons represented the bat’s own position when flying alone (place coding10–14). Notably, during cross-overs, neurons switched rapidly to jointly represent the interbat distance by self-position. This neuronal switch was very fast—as fast as 100 ms—which could be revealed owing to the very rapid natural behavioural switch. The neuronal switch correlated with the attention signal, as indexed by echolocation. Interestingly, the different place fields of the same neuron often exhibited very different tuning to interbat distance, creating a complex non-separable coding of position by distance. Theoretical analysis showed that this complex representation yields more efficient coding. Overall, our results suggest that during dynamic natural behaviour, hippocampal neurons can rapidly switch their core computation to represent the relevant behavioural variables, supporting behavioural flexibility.

Weighted forward looking adaptive coding

Huffman coding is known to be optimal under certain constraints, yet its dynamic version, which constantly alters the Huffman tree as a function of the already processed characters, may be even more efficient in practice. A new forward looking variant of Huffman compression has been proposed recently, that provably always performs better than static Huffman coding by at least m−1 bits, where m denotes the size of the alphabet, and has a better worst case size than the standard dynamic Huffman coding. This paper introduces a new generic coding method, extending the known static and dynamic variants and including them as special cases. In fact, the generalization is applicable to all statistical methods, including arithmetic coding. This leads then to the formalization of a new double-pass coding method that is adaptive in the sense that it uses changing statistics depending on the current position within the processed file, yet it behaves like static coding, as it assumes the knowledge of the distribution in the entire file; this is contrary to online variants that rely only on the text seen so far and adapt the model dynamically. We call the new method positional coding, and its compression performance, using global statistics, is provably always at least as good as that of the best dynamic variants known to date. Moreover, we present empirical results that show improvements by positional coding and its extensions over static and dynamic Huffman and arithmetic coding, even when the encoded file includes the model description.

Raeding with the fingres: Towards a universal model of letter position coding

Letter position coding in word recognition has been widely investigated in the visual modality (e.g., labotarory is confusable with laboratory), but not as much in the tactile modality using braille, leading to an incomplete understanding of whether this process is modality-dependent. Unlike sighted readers, braille readers do not show a transposed-letter similarity effect with nonadjacent transpositions (e.g., labotarory = labodanory; Perea et al., 2012). While this latter finding was taken to suggest that the flexibility in letter position coding was due to visual factors (e.g., perceptual uncertainty in the location of visual objects (letters)), it is necessary to test whether transposed-letter effects occur with adjacent letters to reach firm conclusions. Indeed, in the auditory modality (i.e., another serial modality), a transposed-phoneme effect occurs for adjacent but not for nonadjacent transpositions. In a lexical decision task, we examined whether pseudowords created by transposing two adjacent letters of a word (e.g., laboartory) are more confusable with their base word (laboratory) than pseudowords created by replacing those letters (laboestory) in braille. Results showed that transposed-letter pseudowords produced more errors and slower responses than the orthographic controls. Thus, these findings suggest that the mechanism of serial order, while universal, can be shaped by the sensory modality at play.

Еквідистантність та одиничні коди

In coding theory, single codes, as the implementation of non-traditional coding methods, are focused in particular on such a practical application as the transmission of symbols (bits) in communication channels. Today, the analysis and study of unit codes is a priority and actuality in terms of evaluating their corrective properties.
 This paper analyzes the properties of three unit codes, such as unit position (marking), unit pair and unit normal codes. The comparative characteristic of these codes taking into account their correcting properties is given. It is taken into account that the corrective properties of the code are determined by the code distance, which is the minimum distance between its code points. The formulas for determining the average probability of error non-detection for the received correction codes are given. Research and proof of corrective properties of unit codes were carried out from the point of view of their equidistance. Such codes are characterized by the fact that the code distance in the equidistant code must be an even number. The analysis of the characteristics of unit codes presented in this work showed that one of the optimal among equidistant unit codes can be considered a unit position (marking) code. The formula for calculating the lower estimate of the average probability of error non-detection for any probability of error-free transmission of the symbol, which coincides with the value of the average probability of error non-detection for the McDonald's equidistant code. This also confirmed the optimality of a considered unit position (marking) code.
 With this in mind, the application area of the unit position code, as noise immunity, extends due to the possibility of encoding the states of correcting machines and addressing data in computer storage devices.

In preprints: buckling under pressure during gastrulation.

In preprints: buckling under pressure during gastrulation.

Building Space Coding Based on Beidou Grid Position Code

Building Space Coding Based on Beidou Grid Position Code

Neural Evidence for Different Types of Position Coding Strategies in Spatial Working Memory.

Sustained neural activity during the delay phase of spatial working memory tasks is compelling evidence for the neural correlate of active storage and maintenance of spatial information, however, it does not provide insight into specific mechanisms of spatial coding. This activity may reflect a range of processes, such as maintenance of a stimulus position or a prepared motor response plan. The aim of our study was to examine neural evidence for the use of different coding strategies, depending on the characteristics and demands of a spatial working memory task. Thirty-one (20 women, 23 ± 5 years) and 44 (23 women, 21 ± 2 years) participants performed a spatial working memory task while we measured their brain activity using fMRI in two separate experiments. Participants were asked to remember the position of a briefly presented target stimulus and, after a delay period, to use a joystick to indicate either the position of the remembered target or an indicated non-matching location. The task was designed so that the predictability of the response could be manipulated independently of task difficulty and memory retrieval process. We were particularly interested in contrasting conditions in which participants (i) could use prospective coding of the motor response or (ii) had to rely on retrospective sensory information. Prospective motor coding was associated with activity in somatomotor, premotor, and motor cortices and increased integration of brain activity with and within the somatomotor network. In contrast, retrospective sensory coding was associated with increased activity in parietal regions and increased functional connectivity with and within secondary visual and dorsal attentional networks. The observed differences in activation levels, dynamics of differences over trial duration, and integration of information within and between brain networks provide compelling evidence for the use of complementary spatial working memory strategies optimized to meet task demands.

PENINGKATAN KOMPETENSI PROFESIONAL GURU MELALUI SUPERVISI AKADEMIK DENGAN TEKNIK T2SM

This School Action Research aims to see the effectiveness of the academic supervision of the T2SM method in improving the professional competence of teachers at SMP Negeri 4 Depok in the 2020/2021 academic year. This research was conducted in odd semesters with 36 teachers as the object of research. Professional teachers are teachers who are able to carry out their duties in accordance with their responsibilities and professions according to their characteristics, among others; understand the task, collaborate effectively with students, parents of students, fellow teachers, and the community, able to develop themselves for the sake of improving services to students; able to direct, motivate and grow student behavior; and maintain the position code of ethics. The purpose of academic supervision is to help teachers develop skills, develop curricula, develop teacher working groups, and guide classroom action research to achieve the learning goals set for their students. The result of this research is that there is an increase in the number of teachers and the percentage of academic competence. It can be seen that 94.46% have completed learning administration, carried out classroom learning activities in accordance with the learning implementation plan, and have carried out an assessment in accordance with the assessment guidelines both on the assessment of attitudes, knowledge, and skills and have carried out item analysis. The use of the T2SM method has proven to be effective in improving the professional competence of teachers.

Dynamic historical information incorporated attention deep learning model for industrial soft sensor modeling

Due to the limitations of sampling conditions and sampling techniques in many real industrial processes, the process data under different sampling conditions subject to different sampling frequencies, which leads to irregular interval sampling characteristics of the entire process data. The dynamic historical data information reflecting the production status under irregular sampling frequency has an important influence on the performance of data feature extraction. However, the existing soft sensor modeling methods based on deep learning do not consider introducing dynamic historical information into the feature extraction process. To combat this issue, a novel attention-based dynamic stacked autoencoder networks (AD-SAE) for soft sensor modeling is proposed in this paper. First, the sliding window technology and attention mechanism based on position coding are introduced to select dynamic historical samples and calculate the contribution of different historical samples to the current sample, respectively. Then, AD-SAE combines obtained historical sample information and current sample information as the input of the network for deep feature extraction and industrial soft sensor modeling. The experimental results on the actual hydrocracking process data set show that the proposed method has better performance than traditional methods.

The human primary visual cortex (V1) encodes the perceived position of static but not moving objects

Brain activity in retinotopic cortex reflects illusory changes in stimulus position. Is this neural signature a general code for apparent position? Here we show that responses in primary visual cortex (V1) are consistent with perception of the Muller-Lyer illusion; however, we found no such signature for another striking illusion, the curveball effect. This demonstrates that V1 does not encode apparent position per se.

Knowledge Base Question Answering Based on Multi-head Attention Mechanism and Relative Position Coding

Most current knowledge base question answering models mainly use RNN and its various derivative versions such as BiLSTM to model the problem, which limits Parallel computing capabilities of the model. In response to this problem, we try to use TransformerEncoder instead of BiLSTM to model and encode the problem, and hope to improve the parallel computing efficiency of the model. At the same time, to solve the problem of insufficient relative position information obtained by using absolute position coding in TransformerEncoder, it is proposed to use relative position coding instead of absolute position coding. According to the experimental results, our model effectively reduces a certain amount of training time and has achieved certain results on the WebQuestions benchmark data set.

ЗАВАДОСТІЙКІСТЬ ОДИНИЧНОГО КОДУВАННЯ ДЛЯ ПРИСТРОЇВ КЕРУВАННЯ

The method of encoding numerical information plays a significant role in the synthesis of the control device in the process of encoding its states. This is due not only to the complexity of the combination of control devices, but also to the need to control their noise stability. In most cases, the controllability of code combinations is achieved by introducing additional (control) bits, i.e. by increasing the dimension of codes and the introduction of means of generating control bits. However, there are coding methods that have a "built-in" in the structure of codes the ability to noise stability. Such codes include one of the types of unit codes, namely the unit position (marking) code. This article considers the property of noise stability of a unit position code with an orientation to the applying the control device based on the R-automaton for coding its states. Increasing the bits of such code and a specific way of forming neighboring code combinations provide such a property as equidistance. And this, in turn, allows you to organize simple combinational schemes of nodes for detection and correction of errors such as "race" signals. Also, the functional schemes for error detection and correction units and their connection to the shift register, which is a storage part of the control device based on the R-automaton, are shown.

СИНТЕЗ ПРИСТРОЮ КЕРУВАННЯ НА БАЗІ R-АВТОМАТА ДЛЯ АСОЦІАТИВНОГО ПРОЦЕСОРА

This article discusses one of the well-known options for the synthesis of control devices with rigid logic. Such control devices provide a significant response speed compared to control devices with programmable logic, but they have a laborious process at the stages of abstract and structural synthesis of a microprogram automaton (MPA) as the basic structural model of this type of control device. Synthesis of an MPA based on a shift register as an R-automaton provides a compromise solution among the implementations of an MPA based on a parallel register as a T-automaton or a counter as a CT-automaton. This is due to the load on the memory of the MPA by reducing the complexity of the logical part of the MPA, namely its combinational scheme. The use of a specific single positional coding of the MPA states makes it possible to significantly simplify the complex process of the formation of Boolean functions corresponding to the excitation functions in the abstract synthesis of the MPA. And this, in turn, leads to a simplification of the combinational part of the MPA. At the same time, the complication of the memory part of the MPA based on the shift register leads to an increase in its bit rate without reducing the regularity of its structure. The article proposes a non-standard approach to the synthesis of a control device and develops its functional scheme. As a result, synthesis on the basis of the R - automaton of the control device structure for the associative processor confirmed the perspective of this version of MPA synthesis by simplifying the process of the corresponding abstract and structural synthesis. This is due to the simplicity of forming direct and simplified structural tables using single positional coding of MPA states. It is planned to place the developed structure of the control device in a programmable logic IC (FPGA), which will allow the placement of the entire associative processor in the FPGA. This approach will ensure the compactness of the organization and the speed of the associative processor.

Mersenne Numbers in the Bases of Systems of Residual Classes when Transmitting Data in Serial Communication Channels

In this paper, we consider the system of residual classes for data representation in communication channels. In this case, it is possible to perform parallel data processing without taking into account digit transfers. However, the most of communication channels are serial; therefore, we also consider the possibility of serial transmission of parallel data. We show that the use of the system of residual classes of Mersenne numbers as a base does not lead to decreasing the data transmission rate. We estimate the amount of information contained in the positions of the numbers of a positional code.

FVT: Finger Vein Transformer for Authentication

In recent years, deep learning-based finger vein (FV) authentication has attracted the attention of biometric researchers and achieved breakthrough results. Previously, convolutional neural networks (CNNs) were the most commonly used deep learning-based methods for FV authentication. Recently, the vision Transformer-based method has started getting attention from the research community due to its excellent performance in many computer vision tasks. In this paper, we delve into vision Transformers and propose a novel model, FV Transformer (FVT), for finger vein authentication. FVT consists of four key modules: (1) the conditional position embedding, which is capable of dynamically generating position codes according to the input FV tokens; (2) the weight-shared expanded multi-layer perceptron, which helps to extract richer and more robust token information; (3) the local information-enhanced feed-forward network, which enhances the ability of local information extraction; and (4) the expansion-less mechanism for aggregating adjacent FV tokens, which implements the pyramid structure, and hence the multi-level feature extraction capability is introduced to the Transformer architecture, which originally focuses on global information. To fully validate the performance and generalization of FVT, experiments were conducted on nine publicly available FV datasets. The effectiveness of each key module of FVT is demonstrated in the ablation experiments. And the comparative experiments show that FVT outperforms several baseline Transformer models and achieves competitive performance when compared with the state-of-the-art finger vein authentication methods.

Temporal grouping effects in verbal and musical short-term memory: Is serial order representation domain-general?

The question of the domain-general versus domain-specific nature of the serial order mechanisms involved in short-term memory is currently under debate. The present study aimed at addressing this question through the study of temporal grouping effects in short-term memory tasks with musical material, a domain which has received little interest so far. The goal was to determine whether positional coding—currently the best account of grouping effect in verbal short-term memory—represents a viable mechanism to explain grouping effects in the musical domain. In a first experiment, non-musicians performed serial reconstruction of 6-tone sequences, where half of the sequences was grouped by groups of three items and the other half presented at a regular pace. The overall data pattern suggests that temporal grouping exerts on tone sequences reconstruction the same effects as in the verbal domain, except for ordering errors which were not characterised by the typical increase of interpositions. This pattern has been replicated in two additional experiments with verbal material, using the same grouping structure as in the musical experiment. The findings support that verbal and musical short-term memory domains are characterised by similar temporal grouping effects for the recall of 6-item lists grouped by three, but it also suggests the existence of boundary condition to observe an increase in interposition errors predicted by positional theories.