Position Coding Research Articles

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.

Serial memory: Putting chains and position codes in context.

From the beginning of research on serial memory, chaining theories and position coding theories have been pitted against each other. The central question is whether items are associated with each other or with a set of position codes that are independent of the items. Around the turn of this century, the debate focused on serial recall tasks and patterns of error data that chaining models could not accommodate. Consequently, theories based on other ideas flourished and position coding models became prominent. We present an analysis of a retrieved context model that integrates chains and position codes. Under some parameter values, it produces classic chains. Under most parameter values, it produces context representations that contain information sufficient to specify the position codes in position coding theories. We suggest three ways to extract position codes from context representations and show the codes they produce are mathematically equivalent to the codes in position coding models. The extracted position codes can be substituted for the position codes in position coding models and run through their machinery to mimic their predictions exactly. We suggest that chains, position codes, and retrieved contexts may reflect different strategies for extracting desired information from a common set of memory representations, and we emphasize the value of considering item-dependent context representations that are made from fading traces of past items encoded or retrieved. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

TIMED SIGNAL CONSTRUCTIONS AS A TOOL FOR INCREASING THE NUMBER OF CODEWORDS BY IMPLEMENTING THEIR CONSTANT LENGTH

It is indicated that due to changes in the restrictions on the duration of the basic element, which is the basis for the construction of the signal structure, an increase in the channel capacity was obtained by reducing the energy distance between the signal structures. In this case, the information parameter in these structures is not the parameters of the current or voltage, but the time. The work uses timer signal structures, which are synthesized, as well as positional signals from segments not less than the Nyquist element, but not multiples of it. It is this principle of formation that significantly increases the number of synthesized code structures in comparison with positional coding. It is noted that the information content of any event is determined by the number of its states, and the entropy and the probability of the occurrence of a particular event are interrelated values. In addition, timer signaling constructs allow synthesizing ensembles with a large information content in comparison with positional coding. Keywords: basic element, Nyquist element, information parameter, entropy, probability of occurrence, information segment, message, timer signal structure.

S1379 Celiac Disease on the Rise in the U.S. Military Population: Epidemiology and Impact on Operational Readiness

Introduction: Celiac disease (CD) is an increasingly common disease that affects approximately 1% of the global population and 1-2% of Americans. Recent population based data suggests an increase in the prevalence over the last several decades. Given this is a diagnosis that can preclude induction to the military and deployment to austere environments, we conducted a study to better define the epidemiology of celiac disease in the US military population Methods: Data were collected from the Defense Medical Surveillance System (DMSS) with a surveillance period of January 1, 2000, through December 31, 2017. The population included active component military service members of the US Army, Navy, Air Force, and Marine Corps who served during the period. An individual was counted as a case if they had at least 1 outpatient encounter with a qualifying International Classification of Diseases (ICD), Ninth and Tenth Revision code in any diagnostic position. Diagnoses from all military treatment facility clinics and gastroenterology (GI) specialty clinics only were included in this analysis to increase the specificity a celiac disease diagnosis. Results: A total of 3138 cases (888 within GI clinics) of CD were identified over the surveillance period. The annual incidence rates increased from 3.0 (1.5 within GI clinics) per 100,000 person-years in 2000 to 21.4 (6.5 within GI clinics) per 100,000 person-years in 2017. The prevalence rate increasing from 7.0 per 100,000 service members (3.3 within GI clinics) in 2000 to 87.9 per 100,000 service members (24.7 within GI clinics) in 2017. Prevalence was highest in women (181.8 vs 70.0 per 100,000 service members), age 46 and above (315.5 vs average of 121.1 per 100,000 service members) and white-non Hispanic (112.4 vs average of 57.1 per 100,000 service members). Conclusion: In a retrospective review of the DMSS over 18 years, the incidence and prevalence of CD within the US military is increasing; this may impact operational readiness and health and wellness of our military members. The incidence and prevalence varies with gender, age, and ethnicity. There is a need for further studies examining the military specific aspects of care for members with CD.

Early is left and up: Saccadic responses reveal horizontal and vertical spatial associations of serial order in working memory

Maintaining serial order in working memory is crucial for cognition. Recent theories propose that serial information is achieved by positional coding of items on a spatial frame of reference. In line with this, an early-left and late-right spatial-positional association of response code (SPoARC) effect has been established. Various theoretical accounts have been put forward to explain the SPoARC effect (the mental whiteboard hypothesis, conceptual metaphor theory, polarity correspondence, or the indirect spatial-numerical association effect). Crucially, while all these accounts predict a left-to-right orientation of the SPoARC effect, they make different predictions regarding the direction of a possible vertical SPoARC effect. In this study, we therefore investigated SPoARC effects along the horizontal and vertical spatial dimension by means of saccadic responses. We replicated the left-to-right horizontal SPoARC effect and established for the first time an up-to-down vertical SPoARC effect. The direction of the vertical SPoARC effect was in contrast to that predicted by metaphor theory, polarity correspondence, or by the indirect spatial-numerical association effect. Rather, our results support the mental whiteboard-hypothesis, according to which positions can be flexibly coded on an internal space depending on the task demands. We also found that the strengths of the horizontal and vertical SPoARC effects were correlated, showing that some people are more prone than others to use spatial references for position coding. Our results therefore suggest that context templates used for position marking are not necessarily spatial in nature but depend on individual strategy preferences.

Which Factors Modulate Letter Position Coding in Pre-literate Children?

One of the central landmarks of learning to read is the emergence of orthographic processing (i.e., the encoding of letter identity and letter order): it constitutes the necessary link between the low-level stages of visual processing and the higher-level processing of words. Regarding the processing of letter position, many experiments have shown worse performance in various tasks for the transposed-letter pair judge-JUDGE than for the orthographic control jupte-JUDGE. Importantly, 4-y.o. pre-literate children also show letter transposition effects in a same-different task: TZ-ZT is more error-prone than TZ-PH. Here, we examined whether this effect with pre-literate children is related to the cognitive and linguistic skills required to learn to read. Specifically, we examined the relation of the transposed-letter in a same-different task with the scores of these children in phonological, alphabetic and metalinguistic awareness, linguistic skills, and basic cognitive processes. To that end, we used a standardized battery to assess the abilities related with early reading acquisition. Results showed that the size of the transposed-letter effect in pre-literate children was strongly associated with the sub-test on basic cognitive processes (i.e., memory and perception) but not with the other sub-tests. Importantly, identifying children who may need a pre-literacy intervention is crucial to minimize eventual reading difficulties. We discuss how this marker can be used as a tool to anticipate reading difficulties in beginning readers.

THE DATA DIAGNOSTIC METHOD OF IN THE SYSTEM OF RESIDUE CLASSES

The subject of the article is the development of a method for diagnosing data that are presented in the system of residual classes (SRC). The purpose of the article is to develop a method for fast diagnostics of data in the SRC when entering the minimum information redundancy. Tasks: to analyze and identify possible shortcomings of existing methods for diagnosing data in the SRC, to explore possible ways to eliminate the identified shortcomings, to develop a method for prompt diagnosis of data in SRC. Research methods: methods of analysis and synthesis of computer systems, number theory, coding theory in SRC. The following results were obtained. It is shown that the main disadvantage of the existing methods is the significant time of data diagnostics when it is necessary to introduce significant information redundancy into the non-positional code structure (NCS). The method considered in the article makes it possible to increase the efficiency of the diagnostic procedure when introducing minimal information redundancy into the NCS. The data diagnostics time, in comparison with the known methods, is reduced primarily due to the elimination of the procedure for converting numbers from the NCS to the positional code, as well as the elimination of the positional operation of comparing numbers. Secondly, the data diagnostics time is reduced by reducing the number of SRC bases in which errors can occur. Third, the data diagnostics time is reduced due to the presentation of the set of values of the alternative set of numbers in a tabular form and the possibility of sampling them in one machine cycle. The amount of additionally introduced information redundancy is reduced due to the effective use of the internal information redundancy that exists in the SRC. An example of using the proposed method for diagnosing data in SRC is given. Conclusions. Thus, the proposed method makes it possible to reduce the time for diagnosing data errors that are presented in the SRC, which increases the efficiency of diagnostics with the introduction of minimal information redundancy.

Improved Transformer Net for Hyperspectral Image Classification

In recent years, deep learning has been successfully applied to hyperspectral image classification (HSI) problems, with several convolutional neural network (CNN) based models achieving an appealing classification performance. However, due to the multi-band nature and the data redundancy of the hyperspectral data, the CNN model underperforms in such a continuous data domain. Thus, in this article, we propose an end-to-end transformer model entitled SAT Net that is appropriate for HSI classification and relies on the self-attention mechanism. The proposed model uses the spectral attention mechanism and the self-attention mechanism to extract the spectral–spatial features of the HSI image, respectively. Initially, the original HSI data are remapped into multiple vectors containing a series of planar 2D patches after passing through the spectral attention module. On each vector, we perform linear transformation compression to obtain the sequence vector length. During this process, we add the position–coding vector and the learnable–embedding vector to manage capturing the continuous spectrum relationship in the HSI at a long distance. Then, we employ several multiple multi-head self-attention modules to extract the image features and complete the proposed network with a residual network structure to solve the gradient dispersion and over-fitting problems. Finally, we employ a multilayer perceptron for the HSI classification. We evaluate SAT Net on three publicly available hyperspectral datasets and challenge our classification performance against five current classification methods employing several metrics, i.e., overall and average classification accuracy and Kappa coefficient. Our trials demonstrate that SAT Net attains a competitive classification highlighting that a Self-Attention Transformer network and is appealing for HSI classification.

The neural mechanism of spatial-positional association in working memory: A fMRI study

In the last decade, research has reported that items at the beginning of a memorized sequence are responded to faster with the left hand, whereas items at the end are responded to faster with the right hand. This Spatial-Positional Associations of Response Codes effect has been extensively studied using behavioral methods. However, the neural networks underlying it remain unclear. We found using functional magnetic resonance imaging (fMRI) that the dorsal attention network was involved in spatial-positional associations, in particular a region of the right superior frontal cortex / pre-supplementary motor area (pre-SMA), within which neural activity correlated with behavioral measures of the strength of spatial-positional associations. Psychophysiological interaction (PPI) analysis revealed functional connectivity between this area and other regions of the dorsal attentional network including the SMA, and with the hippocampal-retrosplenial network. In contrast, explicit processing of serial order independent of spatial-positional associations was related to activity in the inferior parietal cortex. Our results provide new insight into positional coding theories of working memory, including the mental whiteboard hypothesis. They suggest that the behavioral effects of positional coding (congruency between hand and ordinal position within the list) are mediated through spatial and motor control maps in the dorsal attentional system.

RYANSQL: Recursively Applying Sketch-based Slot Fillings for Complex Text-to-SQL in Cross-Domain Databases

Abstract Text-to-SQL is the problem of converting a user question into an SQL query, when the question and database are given. In this article, we present a neural network approach called RYANSQL (Recursively Yielding Annotation Network for SQL) to solve complex Text-to-SQL tasks for cross-domain databases. Statement Position Code (SPC) is defined to transform a nested SQL query into a set of non-nested SELECT statements; a sketch-based slot filling approach is proposed to synthesize each SELECT statement for its corresponding SPC. Additionally, two input manipulation methods are presented to improve generation performance further. RYANSQL achieved competitive result of 58.2% accuracy on the challenging Spider benchmark. At the time of submission (April 2020), RYANSQL v2, a variant of original RYANSQL, is positioned at 3rd place among all systems and 1st place among the systems not using database content with 60.6% exact matching accuracy. The source code is available at https://github.com/kakaoenterprise/RYANSQL.

TrajMesa: A Distributed NoSQL-Based Trajectory Data Management System

With the development of positioning technology, a large number of trajectories have been generated, which are very useful for many urban applications. However, it is challenging to manage trajectory data for its spatio-temporal dynamics and high-volume properties. Existing trajectory data management frameworks suffer from efficiency or scalability problem, and only support limited trajectory query types. This paper takes the first attempt to build a holistic distributed NoSQL trajectory storage engine, named TrajMesa, based on GeoMesa, an open-source indexing toolkit for spatio-temporal data. TrajMesa can manage a prohibitively large number of trajectories, and support plenty of query types efficiently. Specifically, we first design a novel trajectory storage schema, which reduces the storage size tremendously. We then devise a novel indexing key schema for time ranges, based on which ID temporal query can be supported efficiently. To reduce the amount of retrieved trajectory data for a spatial range query, we innovatively propose a position code to indicate the spatial location of trajectories accurately. We also propose a bunch of pruning strategies for similarity query and k-NN query in the NoSQL environment. Extensive experiments are conducted using two real datasets and one synthetic dataset, verifying the powerful query efficiency and scalability of TrajMesa.

Do Grading Gray Stimuli Help to Encode Letter Position?

Numerous experiments in the past decades recurrently showed that a transposed-letter pseudoword (e.g., JUGDE) is much more wordlike than a replacement-letter control (e.g., JUPTE). Critically, there is an ongoing debate as to whether this effect arises at a perceptual level (e.g., perceptual uncertainty at assigning letter position of an array of visual objects) or at an abstract language-specific level (e.g., via a level of “open bigrams” between the letter and word levels). Here, we designed an experiment to test the limits of perceptual accounts of letter position coding. The stimuli in a lexical decision task were presented either with a homogeneous letter intensity or with a graded gray intensity, which indicated an unambiguous letter order. The pseudowords were either transposed-letter pseudowords or replaced-letter pseudowords (e.g., jugde vs. jupte). The results showed much longer response times and substantially more errors in the transposed-letter pseudowords than in the replacement-letter pseudowords, regardless of visual format. These findings favor the idea that language-specific orthographic element factors play an essential role when encoding letter position during word recognition.

Morpheme Position Coding in Reading Development as Explored With a Letter Search Task.

Suffixes have been shown to be recognized as units of processing in visual word recognition and their identification has been argued to be position-specific in skilled adult readers: in lexical decision tasks suffixes are automatically identified at word endings, but not at word beginnings. The present study set out to investigate whether position-specific coding can be detected with a letter search task and whether children already code suffixes as position-specific units. A preregistered experiment was conducted in Italian in which 3rd-graders, 5th-graders, and adults had to detect a target letter that was either contained in the suffix of a pseudoword (e.g., S in flagish) or in a non-suffix control (e.g., S in flagosh). To investigate sensitivity to position, letters also had to be detected in suffixes and non-suffixes placed in reversed position, that is in the beginning of pseudowords (e.g., S in ishflag vs. oshflag). Results suggested position-specific processing differences between suffixes and non-suffixes that develop throughout reading development. However, some effects were weak and only partially compatible with the hypotheses. Therefore, a second experiment was conducted. The effects of position-specific suffix identification could not be replicated. A combined analysis additionally using a Bayesian approach indicated no processing differences between suffixes and non-suffixes in our task. We discuss potential interpretations and the possibility of letter search being unsuited to investigate morpheme processing. We connect our example of failed self-replication to the current discussion about the replication crisis in psychology and the lesson psycholinguistics can learn.

The transposed-word effect revisited: the role of syntax in word position coding

ABSTRACT Skilled readers may misinterpret “you that read wrong” for “you read that wrong”: a transposed-word effect. This relatively novel finding, which supports parallel word processing during sentence reading, is attributed to a combination of noisy bottom-up word position coding and top-down syntactic constraints. The present study focussed on the contribution of syntactic constraints in driving transposed-word effects. In a speeded grammatical decision experiment, two types of ungrammatical transposed-word sequences were compared, namely a transposition either across a syntactic phrase (“the have girls gone home”) or within a syntactic phrase (“the girls gone have home”). We found longer response times and lower accuracy rates for within-phrase transpositions than across-phrase transpositions, demonstrating a direct influence of syntactic structures on the transposed-word effect. We conclude that the assignment of words to positions in a sentence is guided by top-down syntactic constraints.

Modeling Articulatory Rehearsal in an Attention-Based Model of Working Memory

Maintenance of verbal information within human working memory occurs through two main complementary mechanisms: articulatory rehearsal and refreshing. Both are well-described in the literature but very few computational models have attempted to describe the ways they interact to maintain information. Because these interactions are difficult to apprehend without computer simulations, this paper presents a possible implementation of rehearsal within TBRS* (Time-Based Resource-Sharing Theory), a computational model operating only with refreshing and based on the TBRS verbal theory. Computer code is available at https://osf.io/taqmv/ . The implementation was tested on different benchmark findings and could replicate all main effects attributed to rehearsal, while still being accountable for the same effect as TBRS*. Four aspects of our rehearsal implementation are discussed with respect to the human behavior that is intended to be described: first, the primacy and recency effects in relation to the short-term property of rehearsal and the long-term purpose of refreshing; second, the moment at which long-term memory influences working memory performance during working memory tasks in reference to the redintegration hypothesis; third, the interplay between the two maintenance mechanisms; finally, positional coding as the appropriate representation for rehearsal.

ЕФЕКТИВНІСТЬ ОДИНИЧНОГО КОДУВАННЯ ДАНИХ

The paper analyzes the implementation properties of unit codes as alternatives to classical binary ones. The possibility of forming a logical-temporal code, which is a symbiosis of two known unit codes: a unit normal and a unit positional (marking) code, is shown. This allows you to provide accelerated principle of recording information and less energy-intensive while storing it. Analytical expressions for calculation of hardware and time expenses at concrete realization of unit data encoding on the shift register and the binary counter with the decoder are resulted. It is the lack of decryption of the generated data that requires increasing the number of connections in the schemes in times. The widespread use of FPGAs eliminates this problem with the compact placement of unit-coded devices in the FPGA chip. This makes it possible to use unit codes as an alternative to binary codes in data transmission, as well as in some types of control devices when encoding their states and in storage devices when addressing their contents. As an example, the efficiency of using unit codes for encoding the states of microprogram automata is shown, which is achieved by the low complexity of combinational circuits and the absence of the need to decode the code combinations of automaton states.

ЭФФЕКТИВНОСТЬ КОДИРОВАНИЯ В СИСТЕМАХ ОСТАТОЧНЫХ КЛАССОВ

In the process of transmitting signals over channels of different data transmission systems to provide high reliability and transmission performance can use various coding methods and ways of converting transmitted data. Moreover, each of the methods has its own advantages and disadvantages in comparison with others. For example, when using timer signaling structures (TSC), it is possible to provide the transmission of significantly more information in one time interval in comparison, for example, with positional coding. Also, classical positional coding is inferior in such important parameters of data transmission as information capacity and entropy. At the same time, the used language of the transmitted text information significantly affects the results of calculating these parameters, based on which the calculations are carried out or the type of text used (literary, technical, etc.). Also, the result of the calculations can be affected by the volume of the analyzed text (the influence is likely to be noticeable in particular cases, and not in general). In these conditions, the possibility of using a certain / adapted type of coding of the transmitted data in the corresponding information transmission systems becomes especially important. Conducted theoretical studies show that timer signal coding under these conditions can be successfully applied in residual class systems, in contrast to positional coding. This possibility provides a number of advantages over the classical positional coding method in terms of reliability, performance and amount of transmitted information. To fully confirm the validity of the results obtained in the course of theoretical research, it is necessary to conduct appropriate practical research, for example, with the simulation on a software model of the application of a particular transmission system with different coding principles.

What, Where, When and How of Visual Word Recognition: A Bibliometrics Review.

The neural/mental operations involved in the process of visual word recognition (VWR) are fundamental for the efficient comprehension of written/printed words during reading. The present study used CiteSpace, a visual analysis software, to identify the intellectual landscape where VWR has been reviewed in the past decade. Thus, synthesized co-citation networks were analyzed to explore and discuss the main questions raised in the VWR literature: the research fronts and the emerging trends of research on this topic. Our results showed that the main questions addressed in VWR studies during the last decade have been focused on four main aspects related to "what," "where," "when," and "how" of VWR; to be specific, the different types of representations assessed during VWR ("what"), the locations and the timing of the brain activity involved in VWR ("where" and "when"), and the interactivity among different representations during processing ("how"). Among the revised studies, letter position coding was found to be the main topic of interest, possibly reflecting the critical role of this process. Furthermore, the evidence found in these studies consistently supported that VWR implies access to phonological, semantic, and morphological representations, which interact and modulate the processing of written words, particularly during early stages. Altogether, our findings showed the evolution in VWR literature regarding the different cognitive and neural operations involved in this process, highlighting the growing interest over the last decade toward the top-down way that mental representations interact.

INCREASE OF STEALTH TRANSMISSION BASED ON TIMER SIGNALS AND LINEAR FREQUENCY MODULATION

Recently, much attention has been paid to the research of the properties and methods of forming complex noise-like signals to increase the noise immunity of radio communication systems operating in the conditions of electronic conflict. Using such signals, the tasks are resolved to improve the noise immunity and the main indicators of transmission stealth (energy, structural and information). For the task of the synthesis noise-like signals using timer signal designs in combination with the method of spreading the spectrum based on linear frequency modulation is proposed. The advisability of using timer signals is justified by their properties, which increase the noise immunity and stealth transmission. In contrast to positional codes, timer signals have more complex structure for construct signal construction. The initial parameters for constructing timer signals allow the formation of various sets of signal constructions. Such variational possibilities of constructing timer signals substantially increase the potential structural stealth of the transmission. Also based on timer signals, noise immunity coding is implemented without additional test elements. In the article A method for synthesizing noise-like signals based on linear frequency modulation and timer signal designs is proposed.

Adaptive grayscale image coding scheme based on dynamic multi-grouping absolute moment block truncation coding

Multi-Grouping Absolute Moment Block Truncation Coding (MGAMBTC) technique improve the image quality of Absolute Moment Block Truncation Coding (AMBTC) by adaptively dividing pixels in a block into groups according to block activity. This study found that the bit rate can be reduced further if there is some similarity among the blocks. Therefore, this study proposes a block prediction scheme that exploits the intra-block similarity of neighboring blocks. If a similar encoded block is found, its position code will be stored to encode the block; otherwise, it is encoded with the proposed improved MGAMBTC (iMGAMBTC). The proposed iMGAMBTC employs an entropy-based indicator generation mechanism to reduce the bit rate, and the evaluation demonstrates that the proposed scheme enhances the compression performance of AMBTC and MGAMBTC efficiently.