Automatic Information Processing Research Articles

Memory and automatic processing of valuable information in younger and older adults.

People often engage in the selective remembering of valuable or important information, whether strategic and/or automatic. We examined potential age-related differences in the automatic processing of value during encoding on later remembering by presenting participants with words paired with point values (range: 1-10 twice or 1-20) to remember for a later test. On the first three lists, participants were told that they would receive the points associated with each word if they recalled it on the test (their goal was to maximize their score). On the last three lists, we told participants that all words were worth the same number of points if recalled on the tests, thus making the point value paired with each word meaningless. Results revealed that selective memory may be impaired in older adults using procedures with larger value ranges. Additionally, we demonstrated that the automatic effects of value may have a greater effect on younger adults relative to older adults, but there may be instances where older adults also exhibit these automatic effects. Finally, strategic and automatic processes may not be related within each learner, suggesting that these processes may rely on different cognitive mechanisms. This indicates that these processes could be underpinned by distinct cognitive mechanisms: strategic processes might engage higher-level cognitive operations like imagery, while automatic processes appear to be more perceptually driven.

A Deep Neural Network-Based Intelligent Forecasting Approach for Multi-Dimensional Economic Indexes in Smart Cities

Intelligent forecasting of economic indexes has been an important demand for sustainable management of smart cities. Existing methods for this purpose were mostly established upon the basis of economic mechanism. Econometric models are the most general technical means in this area. However, in era of digital economy, increasing amount of big data has brought great change to traditional production. It is becoming more difficult for conventional technological forecasting methods to deal with multi-dimensional economic indexes. To deal with such challenge, this paper introduces the artificial intelligence algorithms to implement automatic information processing, and proposes a deep neural network-based intelligent forecasting method for multi-dimensional economic indexes in smart cities. Specifically, a deep neural network with three-layer structure is developed as the backbone methodology. For empirical analysis, the real-world data from “Chengdu–Chongqing Economic Circle” in China from 2012 to 2022 are selected as the main simulation scenario. Four major indexes are selected as the main research object: gross product (GDP), per capita GDP, GDP growth rate and the proportion of tertiary industry in GDP. The experimental results show that the proposal can well deal with such forecasting problem from a data-driven perspective, with a proper forecasting effect on historical data.

Research on Ai Technology of Intelligent Information Visualization Based on Rtos System Service

In order to improve the visual interaction ability of intelligent information, an intelligent information visualization artificial intelligence technology based on RTOS system service is proposed in this paper. Based on embedded integrated control, this paper constructs the system design scheme, client and host system of intelligent information visualization artificial intelligence RTOS service system. The information monitoring module, artificial intelligence programmable logic control module, artificial intelligence processing module and human-computer interaction module of intelligent information visualization artificial intelligence RTOS service system are established to realize the label identification and identification in the process of intelligent information visualization artificial intelligence RTOS service system based on unified resource locator sipur, The communication system model of intelligent information visualization artificial intelligence RTOS service system under the transmission mode of multimedia communication channel is established to realize the automatic information processing of intelligent information visualization RTOS system. The test results show that the design has good stability, strong intelligent information visualization and interaction ability, low memory and time cost.

Study on the Automatic Information Processing Strategy in L2 Reading

Reading is currently a prominent topic in L2 acquisition research, serving as an indicator of L2 learners’ overall language proficiency. However, there are still many challenges in reading for L2 learners. For example, there still exist some linguistic and non-linguistic problems, such as insufficient language ability, lack of cultural background knowledge, low reading efficiency, and poor reading habits. Effectively improving the information processing skills of L2 learners in reading posts a major challenge for researchers. This paper explores the effective strategies for L2 learners to obtain the ability of automatic reading information processing through the scale survey. It is found in the study that:1) L2 learners believe that they can reach the level of automatic reading processing through the automatic information processing strategy; 2) The automatic information processing strategy can be applied in L2 reading to effectively improve the level of L2 automatic processing. Various strategies, such as improving language proficiency, increasing cultural background knowledge, utilizing metacognitive strategies, and employing socio-emotional strategies, both linguistic and non-linguistic, have been identified to effectively improve the automatic information processing ability of L2 learners. This study has important theoretical and practical value for improving the reading ability of L2 learners.

How Do Users Experience Traceability of AI Systems? Examining Subjective Information Processing Awareness in Automated Insulin Delivery (AID) Systems

When interacting with artificial intelligence (AI) in the medical domain, users frequently face automated information processing, which can remain opaque to them. For example, users with diabetes may interact daily with automated insulin delivery (AID). However, effective AID therapy requires traceability of automated decisions for diverse users. Grounded in research on human-automation interaction, we study Subjective Information Processing Awareness (SIPA) as a key construct to research users’ experience of explainable AI. The objective of the present research was to examine how users experience differing levels of traceability of an AI algorithm. We developed a basic AID simulation to create realistic scenarios for an experiment with N = 80, where we examined the effect of three levels of information disclosure on SIPA and performance. Attributes serving as the basis for insulin needs calculation were shown to users, who predicted the AID system’s calculation after over 60 observations. Results showed a difference in SIPA after repeated observations, associated with a general decline of SIPA ratings over time. Supporting scale validity, SIPA was strongly correlated with trust and satisfaction with explanations. The present research indicates that the effect of different levels of information disclosure may need several repetitions before it manifests. Additionally, high levels of information disclosure may lead to a miscalibration between SIPA and performance in predicting the system’s results. The results indicate that for a responsible design of XAI, system designers could utilize prediction tasks in order to calibrate experienced traceability.

Effects of User Experience in Automated Information Processing on Perceived Usefulness of Digital Contact Tracing Applications: Cross-sectional Survey Study (Preprint)

Effects of User Experience in Automated Information Processing on Perceived Usefulness of Digital Contact Tracing Applications: Cross-sectional Survey Study (Preprint)

Abnormal attentional bias in individuals with suicidal ideation during an emotional Stroop task: an event-related potential study.

There is increasing evidence that suicidal individuals exhibit an attentional bias toward negative or suicide-related stimuli, but the underlying neural mechanism remains unclear. This study aimed to investigate the neural mechanism of attentional bias toward emotional stimuli using a modified emotional Stroop task (EST) and to further explore the influencing factor of abnormal attention processing by identifying whether mental disorders or suicidal ideation contributes to attention processing disruptions. Fourteen students with suicidal ideation and mental disorders (SIMDs), sixteen students with suicidal ideation but no mental disorders (SINMDs), and fourteen sex- and age-matched healthy controls (HCs) were recruited. Moreover, 64-channel electroencephalography (EEG) data and behavioral responses were recorded simultaneously during the EST. Participants were instructed to respond to the ink color for various types of words (positive, neutral, negative, and suicide) while ignoring their meanings. Event-related potentials (ERPs) were analyzed to evaluate attention to the stimuli. Spearman correlations between clinical psychological assessment scales and ERP signatures were analyzed to determine the risk factors for suicide. The results showed that the SIMD group exhibited longer early posterior negativity (EPN) latency compared to the SINMD and HC groups, indicating that early attention processing was affected during the EST, and the automatic and rapid processing of emotional information decreased. Furthermore, P300 latency for positive words was positively correlated with current suicidal ideation in the SINMD group, suggesting that delayed responses or additional processing to positive information may lead individuals with suicidal ideation to an incorrect interpretation of external events. Generally, our findings suggest that the neural characteristics of the SIMD group differed from those of the SINMD and HC groups. EPN latency and P300 latency during the EST may be suicide-related neurophysiological indicators. These results provide neurophysiological signatures of suicidal behavior.

Negative bias in early and late cognitive processing of coronary heart disease patients with depressive symptoms: an EPR study

BackgroundThe purpose of this research was to explore the underlying mechanisms of cognitive impairments in patients with coronary heart disease (CHD) who exhibit depressive symptoms. This was accomplished by recording Event-related potentials (ERPs) during the emotional Stroop task, with a specific focus on the temporal dynamics of attentional bias towards various emotional words.MethodsWe selected 17 CHD patients with depressive symptoms and 23 CHD patients without depression using a convenience sampling method from the Affiliated Hospital of Weifang Medical University. Each participant completed an emotional Stroop color-word task, and ERPs were recorded during the task to examine cognitive processing.ResultsCHD patients with depressive symptoms exhibited generally smaller amplitudes of N1, N2, P3 and longer latency of P3 compared to CHD patients without depression. Specifically, the N1 amplitude of negative words was smaller and the P3 amplitude of negative words was larger in the CHD with depressive group compared to the CHD group. Furthermore, within the group of CHD patients with depressive symptoms, negative words elicited a smaller N1 amplitude and larger P3 amplitude compared to positive and neutral words.ConclusionsCHD patients with depressive symptoms demonstrate decreased attentional resources, leading to cognitive impairments. Notably, significant attentional bias occurs during both early and later stages of cognitive processing. This bias is primarily characterized by an enhanced automatic processing of negative information at the early stage and difficulty disengaging from such information at the later stage. These findings contribute to the existing literature on the cognitive neural mechanisms underlying depression in CHD patients.

Close(d) to you? Avoidant attachment is associated with attenuated pupil responsivity to social stimuli

Insecure attachment is thought to impair romantic relationships, presumably also contributing to mental health problems. Previous research has suggested a link to biased automatic processing of social information, potentially reflected in pupil dilation responses. To address this hypothesis, 37 adults were presented with attachment-related, emotional pictures of erotic couples, everyday couples, or interpersonal violence after assessment with the Experiences in Close Relationships Scale. Considerable variation in self-reported attachment behaviors regarding both attachment anxiety and avoidance was observed in our sample. Overall, pupil dilation was most pronounced during viewing of erotica and violence-related pictures. Relative to nature pictures as control, attachment avoidance was associated with attenuated pupillary responses to social content. However, this was not significant with erotica. For pictures of violence, this avoidant bias was also evident in reduced subjective arousal. In contrast, attachment anxiety was unrelated to differential pupil dilation. Our findings, although preliminary, suggest that previous attachment-related experiences may bias the processing of social stimuli, which in turn may be reflected in altered patterns of pupillary responses.

Integrating ocean observations across body‐size classes to deliver benthic invertebrate abundance and distribution information

AbstractInvertebrate animals living at the seafloor make up a prominent component of life globally, spanning 10 orders of magnitude in body size over 71% of Earth's surface. However, integrating information across sizes and sampling methodologies has limited our understanding of the influence of natural variation, climate change and human activity. Here, we outline maturing practices that can underpin both the feasibility and impact of establishing Benthic Invertebrate Abundance and Distribution as a Global Ocean Observing System—Essential Ocean Variable, including: (1) quantifying individual body size, (2) identifying the well‐quantified portions of sampled body‐size spectra, (3) taking advantage of (semi‐)automated information processing, (4) application of metadata standards such as Darwin Core, and (5) making data available through internationally recognized access points. These practices enable broader‐scale analysis supporting research and sustainable development, such as assessments of indicator taxa, biodiversity, biomass, and the modeling of carbon stocks and flows that are contiguous over time and space.

A Novel Business Scheduling Approach for Enterprises via Vision Sensing-Based Automatic Documental Information Extraction

Currently, the prevalence of various Internet intrusion technologies has brought much challenge to the enterprise management. For many core documents, the information leakage may lead to the loss of secrets of enterprises. Therefore, some core official documents in enterprises are in the format of papers, rather than electronic format. As a consequence, it is of significance to develop automatic information processing techniques for official documents in the format of papers, so as to improve the working efficiency of enterprises. In this paper, a novel business scheduling approach for enterprises via vision sensing-based automatic documental information extraction is proposed. For the first stage, the vision sensing-based optical character recognition (OCR) technique is utilized to extract textual information from official documents in the format of papers. For the second stage, the deep neural network is utilized to output business scheduling results on the basis of digital recognition contents from the first stage. Finally, the experimental simulation is also carried out to verify efficiency of the proposal.

Electronic Communications in Information and Analytical Activities

The goal of the work. The scientific problem is highlighted with the aim of systematizing and summarizing the known and new knowledge about electronic communications in information and analytical activities from the point of view of the present and the prospects of their use. The research methodology consists in the application of methods of description, information diagnostics, review and analysis, generalization and system approach. The scientific novelty of the work consists in the generalization and systematization of known and new knowledge about electronic communications in analytics from the point of view of the present and the prospects of their use within one study. Conclusions. The article highlights the current opinions of researchers and the author's position on the use of electronic communications in information and analytical activities, and in this connection reveals new opportunities and advantages of modern online (operational) analytics, while pointing out the existing threats and dangers associated with with digitization and automation of information processes. The works of domestic researchers were analyzed: O. Adler, I. Vinnikova, V. Glowatskyi, O. Kalita, O. Oksentiuk, P. Pucenteilo, I. Khvalchyk., L. Voloshchuk, K. Shaposhnikova and others. Their modern views on the use of electronic communications in information and analytical activities formed the basis of the presentation of the main material. It is emphasized that we have an objective process of development of electronic information technologies and it depends on our choice whether we will have competitive advantages, using them with maximum benefit. Separate information technologies, their advantages and possibilities of application in information and analytical activities are described. Based on the studied material, the logic of the information-analytical process, the author suggests the use of certain electronic communications depending on the subject of analysis and other factors. The methodology is based on the systematic use of electronic technologies in the information and analytical process. The practical use of these technologies clearly affects the speed and quality of management decision-making, which will contribute to the efficiency of any activity. Keywords: information and analytical activity, digitalization, electronic communication, electronic resources, information technologies, management decision.

Automated information processing systems in environmental monitoring

The article shows examples of using the algorithm for calculating emissions into the atmosphere during production activities in the process of laboratory tests for designing maximum allowable emissions and assessing the impact of possible activities on the environment. The calculation algorithm is based on the use of the ERA PC software package in the laboratory process, designed to calculate pollutants in all components of the environment. This software package allows you to make calculations for many parameters automatically, which simplifies the work of environmental designers. The use of this software package can be used in the training of specialists in the field of environmental monitoring.

The differences between cerebral dominance patterns in the speed and accuracy of information processing among university students

IntroductionThe subject of cerebral dominance has received great attention by researchers; however, there is a paucity of studies that have examined its relationship to information processing. ObjectiveThe current study aims to reveal the differences between the cerebral dominance patterns (left cerebral dominance, right cerebral dominance, integrated parallel cerebral dominance) in the speed and accuracy of information processing. MethodA sample of (182) volunteers university students, (mean age±SD, 19.92±2.76 years; range, 18–24years; 68 male, 114 females). The Human Information processing survey was applied to the participants. Each subject was exposed to two elementary cognitive tasks (Stroop task and Eriksen flanker task). Each task included two experimental conditions: first, the congruent condition that reflects the automatic processing of information; second, the incongruent condition that reflects the controlled processing of information. ResultsThe results of the study revealed that there were no differences between the patterns of cerebral dominance in the speed and accuracy of information processing. ConclusionAlthough the relationship between cerebral dominance and information processing is not significant, we need more studies to examine this relationship in other samples and in other experimental conditions.

Suicide-related construct accessibility and attention disengagement bias in suicide ideation.

Previous attempts to determine whether attention bias toward suicide-related stimuli is associated with risk for future suicide attempts have yielded mixed findings that have been difficult to replicate. Recent evidence suggests that methods used to assess attention bias toward suicide-specific stimuli have low reliability. The present study used a modified attention disengagement and construct accessibility task to examine suicide-specific disengagement biases, along with cognitive accessibility of suicide-related stimuli, among young adults with different histories of suicide ideation. Young adults (N = 125; 79% women), screened for moderate-to-high levels of anxiety or depressive symptoms completed an attention disengagement and lexical decision (cognitive accessibility) task, along with self-report measures of suicide ideation and clinical covariates. Findings using generalized linear mixed-effects modeling revealed that young adults with recent suicide ideation displayed a suicide-specific facilitated disengagement bias, compared to peers with lifetime ideation. In contrast, there was no evidence of a construct accessibility bias for suicide-specific stimuli, irrespective of suicide ideation history. These findings point to a suicide-specific disengagement bias that may depend on the recency of suicidal thoughts and suggests automatic processing of suicide-specific information. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

A Digital Twin-Based Heuristic Multi-Cooperation Scheduling Framework for Smart Manufacturing in IIoT Environment

Intertwining smart manufacturing and the Internet of Things (IoT) is known as the Industrial Internet of Things (IIoT). IIoT improves product quality and reliability and requires intelligent connection, real-time data processing, collaborative monitoring, and automatic information processing. Recently, it has been increasingly deployed; however, multi-party collaborative information processing is often required in heterogeneous IIoT. The security and efficiency requirements of each party interacting with other partners have become a significant challenge in information security. This paper proposes an automated smart manufacturing framework based on Digital Twin (DT) and Blockchain. The data used in the DT are all from the cluster generated after blockchain authentication. The processed data in the DT will only be accessed and visualized in the cloud when necessary. Therefore, all the data transmitted in the process are result reports, avoiding the frequent transmission of sensitive data. Simulation results show that the proposed authentication mode takes less time than the standard protocol. In addition, our DT framework for a smart factory deploys the PDQN DRL model, proving to have higher accuracy, stability, and reliability.

Application of a multilayer perceptron with adaptive learning for the analysis of acoustic signals in the water environment

Modern studies of acoustic, magnetic, and other fields of the marine environment are conducted under conditions that are characterized by a high rate of change in the external environment and an ever-increasing amount of information received on various channels in real time. This is especially typical for studies of signals with passive reception methods, which are characterized by a low SNR. Additionally, in shallow sea areas with a significant number of signal sources and serious interference, passive methods of signal monitoring encounter difficulties in noise measurement and the problem of low accuracy. Experience from such studies involving automatic information processing reveals that classical theories are often not applicable. The most promising field of science that can efficiently address current challenges is machine learning. Machine learning offers various tools, such as neural networks, for the task of signal analysis. There are numerous variations in this field, and there are many possible solutions. However, not all solutions work well for specific tasks with various data. Hence, there is a need to enhance existing methods that can address recent challenges. A new method has been proposed, which is more efficient and provides better results in the field of underwater signal analysis. In this study, a multilayer perceptron with batch normalization and adaptive learning was proposed. These solutions surpassed the original method and demonstrated their ability to efficiently analyze data from underwater acoustic vessel sources. The accuracy of the proposed classifier reached up to 96% on a dataset containing 4 vessels with various SNR levels.

ІНФОРМАЦІЙНЕ ЗАБЕЗПЕЧЕННЯ ОБЛІКУ ФІНАНСОВИХ РЕЗУЛЬТАТІВ В ЛІСОВІЙ ГАЛУЗІ

At the article the issue of the use of automated software that facilitates prompt response and control of the legality of operations were considered. The relevance of the study of the problem of accounting and automation of financial results by domestic forestry enterprises was confirmed. Different problems to increase and improve the efficiency of accounting of the financial results of the operation of enterprises in the forest industry were defined. In practice, this provides an opportunity to use automated software, facilitates prompt response and control of the legality of operations. It was justified that the automation process carried out will contribute to increasing the efficiency of the introduction of automation and their feasibility from an economic point of view, and also prevents their influence on the final result. Performing accounting of financial results under the conditions of an automated information processing system, the entire accounting process is carried out in several stages were installed. The characteristics of these stages were provided. The proposals when, with the help of modern software, accounting functions can be fully automated and the consequences of their work can be presented in any form convenient for users were justified. The introduction of automated accounting systems is a process, the result of which is an improvement in the quality of accounting data was considered. The result of the actions taken is the improvement of the management efficiency of the forest industry. It has been proven that the automated accounting system is appropriate when using it at forestry enterprises. Thanks to the introduction of automation, the time for processing various documents that do not require large storage spaces is reduced. As a result of the conducted research, recommendations were given to enterprises of the forestry industry to switch to the accounting information processing program BAS Accounting. The advantage of the efficiency of the resulting accounting information will be the strengthening of control over the legality and economic efficiency of business operations.

Defects in automatic processing of auditory channel brain information in children with developmental dyslexia

Defects in automatic processing of auditory channel brain information in children with developmental dyslexia

Processing of information from networks of airspace surveillance radar systems

The presented paper examines the principles and methods for processing of information from airspace surveillance radar networks. Information technologies allow implementing automatic collection, processing, storage, transmission and issuance of radar information to users. In this work, the synthesis and analysis of the optimal structure of the interstage processing of signal data and radar information of primary processing in the network of airspace surveillance radar systems is carried out. The quality of information from radar networks of airspace surveillance systems affects almost all indicators of the quality of the radar systems network functioning. The stages of radar information processing in radar systems networks are analyzed. The importance of specifying the above stages for creating a complete picture of the air situation in the area of responsibility is shown. To improve the quality of information support for consumers, a network of radar systems requires information processing at all stages. At each stage of information processing, information processing quality indicators were analyzed. This made it possible to show that the staged implementation of information processing, on the one hand, simplified the optimization of processing within each processing stage, but on the other hand, it made it difficult to carry out compatible optimization of both the detection of an aerial object and the measurement of the coordinates of an aerial object. The synthesized structure of processing radar information of the network of radar systems of airspace surveillance, which in its turn made it possible to carry out interstage optimization of processing of both signal data and primary processing information. Calculations have shown that the method of information processing, in which the combination of information is carried out at the level of decision-making on the detection of airborne objects in each signal data processing channel, has some advantages in the quality of information processing of the network of radar systems compared to the one currently used. time option combination information at the stage of signal processing. At the same time, for the method of combining information at the level of decision-making about the detection of aerial objects, the flow of transmitted information to the joint processing point is significantly reduced. All this allows improving the quality of information processing in the airspace control system.