Incoming Information Flow Research Articles

PECULIARITIES OF INFORMATION AND ANALYTICAL SUPPORT IN DECISION-MAKING WITHIN GOVERNMENT BODIES

The modern world is increasingly entering the era of an information society, where the role of information becomes ever more significant. Information is accumulating rapidly and in large volumes, so quickly that people struggle to process and thoroughly comprehend the incoming information flow, leading to an overall reduction in usable information. In order to process relevant data effectively in the context of professional or other activities today, it is no longer sufficient to rely solely on traditional administrative experience to make informed management decisions. It is essential to incorporate scientific knowledge, comprehensive awareness, analytical and forecasting skills, as well as socio-political responsibilities, with an appropriate recognition of these processes. This is particularly relevant for public administration bodies—both central and regional levels of executive state power—and increasingly for local government authorities, which are gaining more authority as part of the decentralization process. In Ukraine, in particular, the ideology and framework for interaction between the state and society are changing, with an increased use of decentralization mechanisms that delegate specific functions and powers from state bodies (to varying degrees) to the level of territorial communities and even to civil society. The purpose of this article is to define the peculiarities of information and analytical support in the decision-making process within government bodies. The article systematizes approaches to information and analytical support in public administration. It identifies the subjects and objects of the information and analytical support system in state management processes and specifies the goals of such support. It justifies the need to highlight the key elements of the information and analytical support system for public administration. The article also outlines the principles guiding information and analytical activities conducted by government and local authorities. Levels of information and analytical work are established, taking into account the temporal dimension. Furthermore, the article identifies issues with information and analytical support in government bodies in Ukraine and suggests ways to address these challenges.

VARIABLE ASSESSMENT OF THE TRANSPORT AND LOGISTICS SCHEME FOR THE DISTRIBUTION OF GOODS TO THE TRADE NETWORK

The distribution of goods to the trade network is a complex process that requires a careful approach to determining the hierarchical structure of the interaction of participants in the logistics chain and planning their activities. An essential element of this process is choosing the configuration of the transport and logistics scheme, which ensures efficient and timely delivery of goods to the trade network. In this study, we propose to carry out a variable assessment of the efficiency of the distribution of goods according to basic schemes on the ground of taking into account a set of factors, such as the distance of transportation, volume of cargo, delivery terms, specific costs for transportation and storage of freight, the impact of changes in the speed of movement and the time of cargo operations. It makes it possible to present the choice of a rational transport and logistics scheme in the form of an optimisation process to make it more flexible and adaptable to the changing conditions that characterise the current distribution of goods. The article aims to establish a rational structure for determining the efficiency of the delivery of goods to the trade network based on evaluating a sensible version of the transport and logistics scheme, which ensures the conditions for implementing technological operations in time. The methodological basis for establishing a rational version of the transport and logistics scheme is a developed structural model of the influence of input parameters on the total costs and timeliness of delivery of a batch of goods to the trade network. Such a research model describes the functional relationship between incoming information flows about the volumes of orders for the delivery of goods, the nature of changes in the parameters of cars in motion and under loading-unloading, information about the structure of the available car fleet, and the characteristics of the communication network and the controlling influences represented by the choice of a rational total of trunk and delivery routes. Designating a logical sequence of communication between these flows enables determining the value of the components of the efficiency criterion of the transport and logistics delivery system. We established that the transport and logistics scheme of delivery is the basis for the development of transportation routes and the organisation of the functioning of warehouse distribution complexes. The developed structure for evaluating the efficiency of the delivery of goods to the trade network allows for determining the core conditions of activity of the logistics chain participants and specifying a set of technical, operational, and economic indicators of their work. Accounting for the time parameters of the transport and logistics chain enables taking into account the influence of fluctuations in the high-speed mode of movement and idle time at loading and unloading points. The developed models for estimating the time parameters of cargo delivery facilitate efficient planning of the transportation routes and determine the rational time for delivery of each consignment. All local models work in a complex with the general structure of evaluating the efficiency of goods delivery and ensuring a more efficient and transparent management of logistics processes. Their use allows logistics companies to reduce delivery costs, improve the quality of customer service, and increase the competitiveness of the trading network in the market. Keywords: delivery, product, trade network, delivery chain, logistics system.

Algebraic Recognition Approach in IoT Ecosystem

The solution to the problem of identifying objects in the IoT ecosystem of the Aral region is analyzed. The problem of constructing a correct algorithm with linear closure operators of a model for calculating estimates for identifying objects in the IoT ecosystem of the Aral region is considered. An algorithm operator is developed, which is considered correct for the problem Z, is the sum of q operators of the assessment calculation model, and is described by a set of numerical parameters 3·n·m·q, where n is the number of specified features, m is the number of reference objects, and q is the set of recognized objects. Within the framework of the algebraic approach, several variants of linear combinations of recognition operators are constructed, the use of which gives the correct answer on the control material, and this is proven in the form of theorems. The constructed correct recognition algorithms, which are the easiest to use, where there is no optimization procedure, make it possible to quickly solve the issue of identifying incoming information flows in the IoT ecosystem of the Aral region.

Functions of Stereotypes in Mass Culture in the Context of Critical Multiculturalism

This article offers a project-based English lesson with university students, which is aimed at studying the way that stereotypes function in mass culture. Critical multiculturalism is currently gaining more and more attention among researchers. Its rise is reflected in English language study books, which stands in stark contrast with the inexhaustible popularity of stereotypes in popular culture. Meanwhile, it is noteworthy that stereotypes are viewed not only as clichéd images of ethnic and socio-cultural groups, but they also participate in categorizing the flow of incoming information and thus act as an essential tool of cognition. During the preparation for the project-based lesson, students studied and analysed the functioning of stereotypes in various samples of popular culture, including commercials and memes, and then presented the results of their research in class. With the help of the teacher, the students identified the following functions of stereotypes in popular culture: cognitive, persuasive, integrative, reflexive, entertaining (including sarcastic), therapeutic, and the function of compression. Further research may continue this list and describe the hierarchical relations between the functions.

Task-related modulation of facial expression processing: An FPVS-EEG study.

In the current study, we examined the role of task-related top-down mechanisms in the recognition of facial expressions. An expression of increasing intensity was displayed at a frequency of 1.5 Hz among the neutral faces of the same model that was displayed at a frequency of 12 Hz (i.e., 12 frames per second, with the expression occurring every eight frames). Twenty-two participants were asked either to recognize the emotion at the expression-specific frequency (1.5 Hz) or to perform an orthogonal task in separate blocks, while a scalp electroencephalogram (EEG) was recorded. A significant 1.5 Hz response emerged with the increase in expressive intensity over the medial occipital, right and left occipitotemporal, and centro-frontal regions. In these three regions, the magnitude of this response was greater when participants were involved in expression recognition, especially when the intensity of expression was low and ambiguous. Time-domain analysis revealed that engagement in the explicit recognition of facial expression caused a modulation of the response even before the onset of the expression over centro-frontal regions. The response was then amplified over the medial occipital and right and left occipitotemporal regions. Overall, the procedure developed in the present study allowed us to document different stages of the voluntary recognition of facial expressions, from detection to recognition, through the implementation of task-related top-down mechanisms that modulated the incoming information flow. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Application of Multilevel Models in Classification and Regression Problems

There is a constant need to create methods for improving the quality indicators of information processing. In most practical cases, the ranges of target variables and predictors are formed under the influence of external and internal factors. Phenomena such as concept drift cause the model to lose its completeness and accuracy over time. The purpose of the work is to improve the processing data samples quality based on multi-level models for classification and regression problems. A two-level data processing architecture is proposed. At the lower level, the analysis of incoming information flows and sequences takes place, and the classification or regression tasks are solved. At the upper level, the samples are divided into segments, the current data properties in the subsamples are determined, and the most suitable lower-level models are assigned according to the achieved qualitative indicators. A formal description of the two-level architecture is given. In order to improve the quality indicators for classification and regression solving problems, a data sample preliminary processing is carried out, the model’s qualitative indicators are calculated, and classifiers with the best results are determined. The proposed solution makes it possible to implement constantly learning data processing systems. It is aimed at reducing the time spent on retraining models in case of data properties transformation. Experimental studies were carried out on several datasets. Numerical experiments have shown that the proposed solution makes it possible to improve the quality processing indicators. The model can be considered as an improvement of ensemble methods for processing information flows. Training a single classifier, rather than a group of complex classification models, makes it possible to reduce computational costs.

Decoding of human identity by computer vision and neuronal vision

Extracting meaning from a dynamic and variable flow of incoming information is a major goal of both natural and artificial intelligence. Computer vision (CV) guided by deep learning (DL) has made significant strides in recognizing a specific identity despite highly variable attributes. This is the same challenge faced by the nervous system and partially addressed by the concept cells—neurons exhibiting selective firing in response to specific persons/places, described in the human medial temporal lobe (MTL) ⁠. Yet, access to neurons representing a particular concept is limited due to these neurons’ sparse coding. It is conceivable, however, that the information required for such decoding is present in relatively small neuronal populations. To evaluate how well neuronal populations encode identity information in natural settings, we recorded neuronal activity from multiple brain regions of nine neurosurgical epilepsy patients implanted with depth electrodes, while the subjects watched an episode of the TV series “24”. First, we devised a minimally supervised CV algorithm (with comparable performance against manually-labeled data) to detect the most prevalent characters (above 1% overall appearance) in each frame. Next, we implemented DL models that used the time-varying population neural data as inputs and decoded the visual presence of the four main characters throughout the episode. This methodology allowed us to compare “computer vision” with “neuronal vision”—footprints associated with each character present in the activity of a subset of neurons—and identify the brain regions that contributed to this decoding process. We then tested the DL models during a recognition memory task following movie viewing where subjects were asked to recognize clip segments from the presented episode. DL model activations were not only modulated by the presence of the corresponding characters but also by participants’ subjective memory of whether they had seen the clip segment, and by the associative strengths of the characters in the narrative plot. The described approach can offer novel ways to probe the representation of concepts in time-evolving dynamic behavioral tasks. Further, the results suggest that the information required to robustly decode concepts is present in the population activity of only tens of neurons even in brain regions beyond MTL.

Functions of Stereotypes in Mass Culture in the Context of Critical Multiculturalism

The article offers a project-based lesson of English with university students, which is aimed at studying the way stereotypes function in mass culture. Critical multiculturalism is currently gaining more and more attention among researchers, its rise is reflected in English language study books, which stands in stark contrast with the inexhaustible popularity of stereotypes in mass culture. Meanwhile, it is noteworthy that stereotypes are viewed not only as clichéd images of ethnic and socio-cultural groups, but they also participate in categorizing the flow of incoming information and thus act as an essential tool of cognition. During the preparation for the project-based lesson, students studied and analyzed the functioning of stereotypes in various samples of mass culture, including commercials and memes, and then presented the results of their research in class. With the help of their teacher the students managed to reveal the following functions of stereotypes in mass culture: cognitive, persuasive, integrative, reflexive, entertaining (including sarcastic), therapeutic function, and the function of compression. Further research may continue this list and describe the hierarchical relations between the functions.

Pola Komunikasi Komunitas Virtual ICB dalam Meminimalisasi Hoaks

The purpose of this study is to describe ICB's communication pattern as a virtual community in an effort to minimize hoaxes. This is caused by ICB's position as a massive virtual community that uses Facebook as its communication medium. However, Facebook as a social media is a place for networking information with a wide range, so that it also allows the emergence of hoaxes in circulating information. This research used a descriptive qualitative method with data collection through observation, in-depth interviews, and documentation. This research finds that there are two models of communication patterns used by ICB, namely: the wheel communication pattern and the all-channel communication pattern. The wheel communication pattern includes filtering of uploaded information within the group, in which each member waits for approval from the admin to join or share uploads to the group, especially with a centralized flow at one point, so that the flow of incoming information is orderly and minimizes hoaxes within the group. Meanwhile, the communication patterns of all channels allow for more flexible community meetings and activities, in which each member can interact with anyone without any restrictions.

Salience by competitive and recurrent interactions: Bridging neural spiking and computation in visual attention.

Decisions about where to move the eyes depend on neurons in frontal eye field (FEF). Movement neurons in FEF accumulate salience evidence derived from FEF visual neurons to select the location of a saccade target among distractors. How visual neurons achieve this salience representation is unknown. We present a neuro-computational model of target selection called salience by competitive and recurrent interactions (SCRI), based on the competitive interaction model of attentional selection and decision-making (Smith & Sewell, 2013). SCRI selects targets by synthesizing localization and identification information to yield a dynamically evolving representation of salience across the visual field. SCRI accounts for neural spiking of individual FEF visual neurons, explaining idiosyncratic differences in neural dynamics with specific parameters. Many visual neurons resolve the competition between search items through feedforward inhibition between signals representing different search items, some also require lateral inhibition, and many act as recurrent gates to modulate the incoming flow of information about stimulus identity. SCRI was tested further by using simulated spiking representations of visual salience as input to the gated accumulator model of FEF movement neurons (Purcell et al., 2010, 2012). Predicted saccade response times fit those observed for search arrays of different set sizes and different target-distractor similarities, and accumulator trajectories replicated movement neuron discharge rates. These findings offer new insights into visual decision-making through converging neuro-computational constraints and provide a novel computational account of the diversity of FEF visual neurons. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

ПЕРИНАТАЛЬНЫЙ ОПЫТ

Perinatal experience constitutes in and of itself a state of subjective reality, which occurs during the period of the intrauterine development of a person. Its essential elements, those, which at the later stages form the frame of human psyche and behaviour are listed below. Firstly, there is sensory information that is fully manifest during the third trimester of the fetal development in its entirety. During the perinatal period all the sensory systems of a human being without exception are being shaped and filled with incoming information; the learning process is actively functioning, attention and fetal memory are developing. Secondly, there is emotional development that can already be detected in the second trimester. Furthermore, there is the sensation of bodily wholeness, which develops after the 25th week of pregnancy and that constitutes the first mental representation of the Self ontogenetically, that is, the foundation of subjective reality that accompanies a human being throughout their life, but that is, doubtless, still very different from authentic self-awareness. Additionally, one should mention the spatio-temporal continuum of subjective reality, which is already initiating its formation starting from the eighth week of embryo development. Finally, prenatal sensations create archetypes and archetypal patterns that permeate the unconscious structures of subjective reality during its entire existence. The incoming information flows, their processing, encoding and entrenchment in memory, the emotional response to stimuli and spatio-temporal structure of subjective reality generate initially perceptive and later spatio-figurative thinking of a fetus, which occur during the oneiric state of dreamless sleep, in cases of severe sensory deprivation, partial immobilization and hypoxia of the brain.

Information and Analytical Support of Local Self-Government in the Context of Automation of Public Administration Services

Abstract. Introduction. Creating a modern information and analytical base for managerial decisions in local governments is especially relevant at the present stage of development of Ukraine Information and analytical support, based on the wide use of new information technologies, means of computer and communication technologies is an integral part of the professional functioning of the public administration system. The introduction and comprehensive use of modern information technologies in the activities of local governments provides information and analytical support for managerial decisions, provides information needs of both civil servants and other categories of citizens. Purpose. The purpose of the article is to study the organization of information and analytical support of local selfgovernment in the context of automation of public administration services. Results. The state of information and analytical activity of the local self-government institution on the example of the general department of the Bashtanka territorial community of the Mykolayiv region is investigated. An analysis of the possibilities of using the computer program “Smart Village” in the activities of communities, the widespread implementation of which will help increase the efficiency of management, planning and use of all resources of local communities. The study of the state of information and analytical activity of local self-government institutions in the current conditions has allowed to determine that in the absence of the necessary information it is difficult to make objective and timely managerial decisions. Conclusions. Information and analytical support as a direction of activity and in the context of automation of public administration services should be identified as one of the leading and provide for appropriate changes in the functions and structure of executive institutions at the local level. These changes, in turn, require an adequate interpretation of information from the environment with pre-ordering of incoming information flows, while ensuring a balanced supply of information from all sources, taking into account the functional load for the community.

Evaluation of firewall performance when ranging a filtration rule set

This article is a continuation of a number of works devoted to evaluation of probabilistic-temporal characteristics of firewalls when ranging a filtration rule set. This work considers a problem of the decrease in the information flow filtering efficiency. The problem emerged due to the use of a sequential scheme for checking the compliance of packets with the rules, as well as due to heterogeneity and variability of network traffic. The order of rules is non-optimal, and this, in the high-dimensional list, significantly influences the firewall performance and also may cause a considerable time delay and variation in values of packet service time, which is essentially important for the stable functioning of multimedia protocols. One of the ways to prevent decrease in the performance is to range a rule set according to the characteristics of the incoming information flows. In this work, the problems to be solved are: determination and analysis of an average filtering time for the traffic of main transmitting networks; and assessing the effectiveness of ranging the rules. A method for ranging a filtration rule set is proposed, and a queuing system with a complex request service discipline is built. A certain order is used to describe how requests are processed in the system. This order includes the execution of operations with incoming packets and the logical structure of filtration rule set. These are the elements of information flow processing in the firewall. Such level of detailing is not complete, but it is sufficient for creating a model. The QS characteristics are obtained with the help of simulation modelling methods in the Simulink environment of the matrix computing system MATLAB. Based on the analysis of the results obtained, we made conclusions about the possibility of increasing the firewall performance by ranging the filtration rules for those traffic scripts that are close to real ones.

Casos sobre la institución familiar moderna afectada por el entorno de los medios

El objetivo del trabajo consiste en discutir la crisis de la institución moderna de la familia, la influencia del entorno mediático en la condición social y psicológica de sus usuarios, así como en los valores familiares que se forman en los jóvenes. Al estudiar este problema, el método principal es el análisis de materiales teóricos y prácticos rusos y extranjeros que tratan el tema de las opiniones de los jóvenes que se configuran bajo la influencia del entorno de los medios de comunicación. El análisis permite conocer la incapacidad de los jóvenes para controlar sabiamente los flujos de información entrante y el efecto adverso sobre las orientaciones valorativas y la imagen de familia creada. En el artículo, se presentan los siguientes resultados principales. Se han descubierto las opiniones de los jóvenes sobre la formación de una familia y la identificación de las fuentes de información que les son preferibles. Los jóvenes han sido analizados como objeto de acción del entorno mediático. Los materiales del periódico pueden ser de ayuda para los jóvenes, los especialistas que trabajan con los jóvenes y los padres en el uso consciente de los medios de comunicación. También pueden ser fundamentales en el desarrollo de programas especializados para formar la imagen de los jóvenes de la familia y las orientaciones de valores como libres de la influencia de los medios.

The Effect of Internet Usage on Social Capital in Indonesia

The development capital consists of financial capital, physical capital, human capital, and social capital. Social capital focuses on efforts to empower social relations. The relationship between social capital and ICT, especially the internet, has become an interesting debate. In fact, several studies have been conducted with quite diverse findings. The internet is able to connect people who are far from each other, but on the other hand, it often makes people who are physically close to each other seem far apart. This study aims to examine the effect of internet use on social capital in Indonesia. The data is obtained from the fifth Indonesian Family Life Survey (IFLS-5). The study found that in general, internet users have lower social capital than non-internet users. Likewise, highly educated people have higher social capital than people with low education. Then, internet users with higher education have higher social capital when compared to internet users with lower education. This means that the use of the internet must be accompanied by the readiness of human resources (digital literacy) in accepting new technology, filtering the flow of incoming information, and educating the public about how to use the internet in healthy, safe, and wise manner.

Algorithm for processing weakly formalized information

An algorithm for processing weakly formalized information is proposed, which is based on the methods of processing and storing information that are used in living organisms. In particular, the compactness of storage and processing of heterogeneous information according to a single algorithm, the generation of new information based on the comparison of recently received and processed information in a certain way with previously received and processed information, consideration of priorities in the processing and use of information, consideration of recurring patterns in the incoming information, based on which develops a stereotype of animal behavior. This approach makes it possible to efficiently store weakly formalized information, i.e. store not all incoming information, but only the results of its special processing, And also effectively process a large volume of incoming weakly formalized information (by taking into account priorities), identify recurring patterns in the flow of incoming information, effectively generate new knowledge, (analyze stored in memory, the results of special processing of weakly formalized information).

Information Flow Networks of Chinese Stock Market Sectors

Transfer entropy measures the strength and direction of information flow between different time series. We study the information flow networks of the Chinese stock market and identify important sectors and information flow paths. This paper uses the daily closing price data of the 28 level-1 sectors from Shenyin \& Wanguo Securities ranging from 2000 to 2017 to study the information transmission between different sectors. We construct information flow networks with the sectors as the nodes and the transfer entropy between them as the corresponding edges. Then we adopt the maximum spanning arborescence (MSA) to extracting important information flows and the hierarchical structure of the networks. We find that, during the whole sample period, the \textit{composite} sector is an information source of the whole stock market, while the \textit{non-bank financial} sector is the information sink. We also find that the \textit{non-bank finance}, \textit{bank}, \textit{computer}, \textit{media}, \textit{real estate}, \textit{medical biology} and \textit{non-ferrous metals} sectors appear as high-degree root nodes in the outgoing and incoming information flow MSAs. Especially, the \textit{non-bank finance} and \textit{bank} sectors have significantly high degrees after 2008 in the outgoing information flow networks. We uncover how stock market turmoils affect the structure of the MSAs. Finally, we reveal the specificity of information source and sink sectors and make a conclusion that the root node sector as the information sink of the incoming information flow networks. Overall, our analyses show that the structure of information flow networks changes with time and the market exhibits a sector rotation phenomenon. Our work has important implications for market participants and policy makers in managing market risks and controlling the contagion of risks.

Neural Correlates of Trust During an Automated System Monitoring Task: Preliminary Results of an Effective Connectivity Study

As autonomous systems become more prevalent and their inner workings become more opaque, we increasingly rely on trust to guide our interactions with them especially in complex or rapidly evolving situations. When our expectations of what automation is capable of do not match reality, the consequences can be sub-optimal to say the least. The degree to which our trust reflects actual capability is known as trust calibration. One of the approaches to studying this is neuroergonomics. By understanding the neural mechanisms involved in human-machine trust, we can design systems which promote trust calibration and possibly measure trust in real time. Our study used the Multi Attribute Task Battery to investigate neural correlates of trust in automation. We used EEG to record brain activity of participants as they watched four algorithms of varying reliability perform the SYSMON subtask on the MATB. Subjects reported their subjective trust level after each round. We subsequently conducted an effective connectivity analysis and identified the cingulate cortex as a node, and its asymmetry ratio and incoming information flow as possible indices of trust calibration. We hope our study will inform future work involving decision-making and real-time cognitive state detection.

Directionality of information flow and echoes without chambers.

How do echo chambers operate? Why does social propagation of information become trapped within the boundaries of social groups? Previous studies of these questions have identified informational and structural factors which hinder information exchange across group boundaries; these factors constitute “chambers” in which information flows are confined and transformed into “echoes.” However, empirical evidence has indicated that these factors may not sufficiently explain the mechanism of echo chambers. Hence, the present study investigated whether the insular flow of information emerges and endures without the chambers. A randomized controlled experiment was conducted in which participants, who were classified into two political groups, exchanged randomly selected articles with the same number of ingroup and outgroup neighbors. The experiment manipulated the directionality of incoming information flow by varying the number of articles sent from ingroup neighbors across two conditions. Analyses revealed that the ingroup-slanted inflow induced ingroup-slanted outflow, suppressing transmission toward neighbors in a different social group. The biased inflow also promoted positive reactions to information exchanges and reduced negative evaluations on the exchanged information. Furthermore, the ingroup-slanted inflow increased false perceptions of ingroup majority, which is known to encourage information dissemination by a social group. The present study suggests two self-reinforcing mechanisms of ingroup-biased flows that generate echoes even without the chambers. These mechanisms may enable a small group of strategic actors to exacerbate polarization within a large population by manipulating directions of information flow.

Fight or flight? Attributing responsibility in response to mixed congruent and incongruent partisan news in selective exposure media environments

ABSTRACT In today’s media environment, the flow of incoming information can be overwhelming. Citizens are exposed to both congruent and incongruent information, following each other at a fast pace. At the same time, citizens have the freedom to compose their own daily information diet. This demanding and personalized media environment plays a decisive role in political decision-making. One crucial political evaluation is to assign credit or blame to politicians. In this setting of selective exposure and motivated reasoning, we conducted two experiments (N = 1,117) to test how forced versus selective exposure to mixed congruent-incongruent news articles and fact checkers on immigration (Study 1) or climate change (Study 2) affects citizens’ evaluations of responsibility. The key findings expand extant research that identified partisan biases in citizens’ responsibility perceptions: People select and process partisan information in a biased way to reassure partisan identities. A key democratic implication is the prevalence of citizens’ defensive motivation when assigning responsibility.