Ways Of Processing Information Research Articles

Raison d'être for the judicial process

Several Spanish authors have conceptualised the judicial process as a forced and inevitable temporal evolution that must precede the resolution of the controversy and that depends on slowness —as the antithesis of immediacy—. According to this doctrine, this process aims to avoid an immediate judicial response. In this paper, I will examine why the judicial process has been defined in this way; the reasons why speed is not desirable in the judicial function. To this end, I draw on the findings of cognitive psychology and, more specifically, on a set of theories that support the existence of two ways of processing information —two ways of knowing, believing, thinking, reasoning, and acting—: one fast and one slow; these are the dual processing theories. As a result of this confrontation, I propose a rationale, a purpose, and a definition for the judicial process, which are based on the idea that the presence of a time interval is necessary for the right to judicial impartiality and the right of defence to —materially— exist.

THE EFFECTIVENESS OF EDUPEARL BO EFEKTIVITAS ALAT PERMAINAN EDUKATIF EDUPEARL BOARD TERHADAP PERKEMBANGAN KOGNITIF USIA 5-6 TAHUN

Cognitive development is closely related to an individual's knowledge and their way of processing information regarding situations, actions, and things observed in their surroundings. This research aims to evaluate the effectiveness of the EduPearl Board as an educational play tool on the cognitive abilities of children at TK Istiqomah in Kota Cilegon. The research method utilized was qualitative, employing data collection techniques through observation and documentation. The research participants consisted of 17 children aged 5-6 years old at TK Istiqomah in Kota Cilegon. The research findings indicate that the EduPearl Board game is effective in enhancing the cognitive abilities of 5-6-year-old children, with all children receiving an assessment of 'very good'. Consequently, the conclusion drawn is that the EduPearl Board game is capable of improving the cognitive development of 5-6- year-old children, as evidenced by the highly positive assessments obtained from the research.

Айтрекинговое исследование восприятия художественной народной росписи на примере гжели и хохломы

Introduction. Folk art is the basis of spiritual and moral education. Given that folk art is entering our lives in a new way, the chosen topic is relevant. Theoretical analysis. Gzhel and Khokhloma have accompanied the development of artistic taste over the centuries. It is known about the influence of art on the psycho-emotional state of a person, an indicator of which is oculomotor activity. Eye movements can be used as indicators of the perceptual process. Empirical analysis. The characteristic values of blinking, fixations and saccades were revealed during the perception of images of Gzhel and Khokhloma, taking into account the preference for one or another folk art. It has been established that those who prefer Gzhel use a contemplative strategy of observation, while those who choose Khokhloma use a research one. Also, when considering blue-white images, persons who have chosen Gzhel use a rational way of perception, and when perceiving gold images, they use an emotional one. Participants who preferred Khokhloma showed an inverse ratio of perception methods. Conclusion. When considering folk art, different ways of processing information are actualized among people who prefer Gzhel and Khokhloma. The identified features of oculomotor activity will make it possible to use these types of folk art in art therapy when conducting additional research.

Forming cognitive culture of bachelor students during foreign language learning

Introduction. Modern information-based society puts forward the issues of obtaining, mastering, processing and understanding knowledge as a product of intellectual activity. Involvement in various types of information activities forms cognitive culture, and the up-to-date strategy of foreign language education is associated with disclosing the intellectual-forming potential of teaching, educating and helping students develop through the means of the studied language. The study aims to identify the pedagogical conditions which, through foreign language education, form cognitive culture as a key component of the intellectual personal culture of future teachers. Materials and methods. Methodologically, the study was based on the concepts of cognizant mental principle and activity, of the intellectualization of professional education, and of developed personal and intellectual culture, as well as on individual, environmental, personal-activity, communicative-cognitive, and technological approaches to developing rational and cognitive thinking and developing mental labor culture. Research methods: analysis of psychological, pedagogical and methodological literature on the research topic; qualitative and quantitative analysis of the empirical material, methodological data interpretation. Research results. The study revealed theoretical and empirical grounds for pedagogical conditions and for technological and diagnostic tools which form cognitive culture of bachelor students learning a foreign language. The former are related to the manifestation, development and regulation of intellectual skills (mental activity, intellectual search personality qualities, information behavior, criticality and logical thinking), of cognitive style (individual ways of processing information, rationality and reflexivity, flexible cognitive control), and of mental experience (intellectual maturity, ability to positively transfer knowledge, skills and competences). Conclusions. In university students, cognitive and metacognitive abilities for further inclusion in the authentic socio-cultural and professional context of life are developed through modeling, contextual, and socially oriented educational technologies that possess the characteristics of problem-based learning.

Brain Expression of CPB2 and Effects of Cpb2 Deficiency in Mouse Models of Behavior.

Procarboxypeptidase B2 (proCPB2 or TAFI) is a zymogen that after activation cleaves C-terminal basic residues from peptides or proteins with many identified targets. A splice variant of CPB2 has been found in the brain lacking essential residues for its carboxypeptidase function. The aim was to determine CPB2 expression in the brain and effects of CPB2 deficiency (Cpb2 -/-) on behavior. Behavioral effects were tested by comparing Cpb2 -/- mice in short-term (open field and elevated zero maze tests) and long-term (Phenotyper) observations with wild-type (WT) controls. Long-term observation compared day 1 (acclimatizing to novel environment) to day 4 (fully acclimatized) with the inactive (day) and active (night) periods analyzed separately. Brain expression of CPB2 mRNA and protein was interrogated in publicly available databases. Long-term observation demonstrated differences between WT and Cpb2 -/- mice in several parameters. For example, Cpb2 -/- mice moved more frequently on both days 1 and 4, especially in the normally inactive periods. Cpb2 -/- mice spent more time on the shelter and less time in it. Differences were more pronounced on day 4 after the mice had fully acclimatized. In short-term observations, no differences were observed between Cpb2 -/- mice and WT mice. Brain expression of CBP2 was not detectable in the human protein atlas. Databases of single-cell RNAseq did not show expression of CPB2 mRNA in either human or mouse brain. Continuous observation of home-cage behavior suggests that Cpb2 -/- mice are more active than WT mice, show different day-night activity levels, and might have a different way of processing information.

Semantic information processing for interoperability in the Industrial Internet of Things

With the advent of the Internet of Everything (IoE), the concept of fully interconnected systems has become a reality, and the need for seamless communication and interoperability among different industrial systems has become more pressing than ever before. To address the challenges posed by massive data traffic, we demonstrate the potentials of semantic information processing in industrial manufacturing processes and then propose a brief framework of semantic processing and communication system for industrial network. In particular, the scheme is featured with task-orientation and collaborative processing. To illustrate its applicability, we provide examples of time series and images, as typical industrial data sources, for practical tasks, such as lifecycle estimation and surface defect detection. Simulation results show that semantic information processing achieves a more efficient way of information processing and exchanging, compared to conventional methods, which is crucial for handling the demands of future interconnected industrial networks.

МОДЕЛИРОВАНИЕ СИСТЕМЫ ОЧИСТКИ СТОЧНЫХ ВОД ЖИВОТНОВОДЧЕСКИХ ФЕРМ НА ОСНОВЕ СЕТЕЙ ПЕТРИ

The development of animal husbandry on an industrial basis causes a sharp increase in the amount of highly polluted wastewater, the purification and disinfection of which is one of the most important tasks when deciding on their use in agriculture as fertilizer or discharge into reservoirs or irrigation fields. The effectiveness of such systems is achieved with the help of new ways of processing information and mathematical characteristics of technology processes. Based on the study of the main methods of creating discrete chemical and technological systems (CTS), the expediency of using the design of Petri nets (SP) to simulate the process of wastewater treatment of livestock farms (OSWF) was developed. To characterize the system, we use N–schemes, which are based on the mathematical system of the joint venture, which can form a network structure both in analytical form for automating work during analysis, and in graphical form to create visibility of the created model. Analyzing technological and chemical processes, it is important to take into account the formality condition of N–circuits, which assumes that the circuits do not take the properties of simulated systems in time, since the timing of the transition is taken to be zero. We took into account these conditions and proposed updated Petri nets that are focused on the analysis and simulation of discrete CTS, by changing the time delay of labels on transitions and positions, as well as by enabling transitions that are in priority. We have created a model in the form of a modified updated Petri net (SME). With the help of SCADA TRACE MODE technologies, we have developed a whole software package for the control system in the process of OSWF. This system can perform dispatching monitoring of the main parts of the control apparatus, as well as stop and analyze and monitor its condition, this is feasible both in general and within the framework of forecasting the occurrence of emergency situations.

Agent talks about itself: an implementation using Jason, CArtAgO and Speech Acts

Thinking to oneself is a prerogative of man when he needs to think about or repeat what he is doing or experiencing. It is a way of processing information and setting in motion a decision-making process. When this is done aloud, there is also a chance that someone else will understand the meaning or reasons for the action. Equipping an agent with the ability to reveal the reasons for its decisions is both a way to improve human interaction and a way to improve the triggering of a decision process. In this work, we propose to use the speech act to enable a coalition of agents to exhibit inner speech capabilities to explain their behavior, but also to guide and reinforce the creation of an inner model. The BDI agent paradigm, Jason, and CArtAgO are used to give agents the ability to act in a human-like manner. The BDI reasoning cycle has been extended to include inner speech. The proposed solution continues the research path that started with the definition of a cognitive model and architecture for human-robot teaming interaction and aims to integrate the believable interaction paradigm in it.

Analysis of Student Learning Styles in Differentiation Learning

This research is an attempt to describe students’ learning styles in differentiation learning. The study was conducted on all students of class X-3 at SMAN 8 Malang. Learning style is a consistent way that students have in capturing stimulus or information, how to remember, think, and solve problems. Based on the implementation of the independent curriculum, it is also necessary to map learning needs based on the learning profile of students. This mapping can be done by providing a diagnostic assessment to find out. There are various ways of information processing that students display, some are easier to process through visual information, some are auditory (sound), and others are kinesthetic (direct practice). The findings obtained from this study are that mapping different learning styles can not only improve the quality of learning in students but also help them in mastering mathematics.
 Keywords: learning style, differentiation learning

Quantum healthcare computing using precision based granular approach

Previously, doctors interpreted diseases and their outcomes according to their experience in diagnosis. However, with the rapid increase in technology and population, the task of examining the patient becomes cumbersome and sometimes human efforts produce inconsistent results. Several research is being done for healthcare in terms of improving visualization and accuracy by using machine learning models. The current research targets to explore quantum computing as a different way of processing information compared to classical computer systems such as the use of quantum bits (qubits) along with superposition and entanglement for extending the computation capabilities at an unprecedented level of thinking in the healthcare domain. Quantum computing systems provide exponential benefits in terms of high-speed processing, faster and easier diagnostic assistance, unimaginable reduction in processing throughput, and many more. An extensive comparative analysis of existing approaches has been made which benchmarks the need for quantum healthcare computing. The objective of this work is to interpret whether Quantum computers prove to be more trusted when it comes to patient diagnosis, and faster analysis leading to cost optimization. In order to accelerate patient diagnosis, different approaches have been presented. The authors have proposed a precision-based granular approach for patient diagnosis that incorporates diagnosing the disease with enhanced precision and granularity. It involves reporting symptoms by the patient, encountering by healthcare expert on multiple factors, precise examination, granular health status (understanding past and present medical history), followed by a precise intervention by understanding biomolecular simulations. The algorithm has been presented to describe the flow process for patient diagnosis modeling using quantum computing. It involves qubits initialization, pairing the values, assigning probabilistic values, cross-validation, and quantum circuit formation. Precision-based granular approach has been implemented for a scenario (consisting of medical parameters such as oxygen and heart rate level, with the functionality of diagnosing oxygen level and heart range which lies as either normal or not normal (high/low)). Precision-based granular approach deals specifically with the individual ‘biomolecular simulation by understanding variations in the individual body whereas the umbrella-based approach does not deal with specifically to individual mechanisms. Granular level of encounter is not possible in umbrella-based treatment. Python Jupyter notebook and IBM Composer tool is used for the implementation of results. Bloch sphere and computational state graph are obtained as an output for better visualization and understanding. Falcon r5.11H processor is used with the version of 1.0.24 of IBM Composer to simulate the experiment. The methodology using precision based granular approach provides timely encounter of disease along with umbrella diagnosis and precise treatment. The time is taken and frequency of qubits have been presented with promising results. The diagnosis process and optimizing cost efficiency can aid in an early detection of the disease.

Learning with limited memory: Bayesianism vs heuristics

Bayesian analysis is considered the optimal way of processing information. However, it often leads to problems for decision-makers with constrained cognitive capacity. Modeling such constrained capacity by finite automata, we answer two questions in the context of Wald's (1947) sequential analysis, namely in what environments is optimal Bayesian analysis possible even with constraints; also, when it is not possible what simplifications in the analysis enable us to obtain a satisfactory outcome. We identify two features of the simplified analysis: information stickiness (ignoring information) and rule stickiness (ignoring small differences in the environment).

Interpretation of ambiguous trials along with reasoning strategy is related to causal judgements in zero-contingency learning.

The dual strategy model suggests that people can use either a Statistical or a Counterexample reasoning strategy, which reflects two qualitatively different ways of processing information. This model has been shown to capture individual differences in a wide array of tasks, such as contingency learning. Here, we examined whether this extends to individual differences in the interpretation of contingency information where effects are ambiguous. Previous studies, using perceptually complex stimuli, have shown that the way in which participants interpret ambiguous effects predicts causal judgements. In two studies, we attempted to replicate this effect using a small number of clearly identifiable cues. Results show that the interpretation of ambiguous effects as effect present is related to final contingency judgements. In addition, results showed that Statistical reasoners had a stronger tendency to interpret ambiguous effects as effect present than Counterexample reasoners, which mediates the difference in contingency judgements.

Clinical Practice Guidelines for Assessment and Management of Patients with Borderline Personality Disorder.

Clinical Practice Guidelines for Assessment and Management of Patients with Borderline Personality Disorder.

Digital Twins Utilizing XR-Technology as Robotic Training Tools

Digital technology has evolved towards a new way of processing information: web searches, social platforms, internet forums, and video games have substituted reading books and writing essays. Trainers and educators currently face the challenge of providing natural training and learning environments for digital-natives. In addition to physical spaces, effective training and education require virtual spaces. Digital twins enable trainees to interact with real hardware in virtual training environments. Interactive real-world elements are essential in the training of robot operators. A natural environment for the trainee supports an interesting learning experience while including enough professional substances. We present examples of how virtual environments utilizing digital twins and extended reality can be applied to enable natural and effective robotic training scenarios. Scenarios are validated using cross-platform client devices for extended reality implementations and safety training applications.

Application of the DEA Method for Evaluation of Information Usefulness Efficiency on Websites

The article presents analysis and evaluation of information usefulness efficiency for recipients with secondary and higher education using the example of information and shopping websites. Different levels of quality and information usefulness efficiency have an impact on different ways of processing information by users which, in turn, may result in different consumer behavior and their decisions. The study describes the basic methodological assumptions, the research evaluation procedure of information usefulness efficiency, and the forms of informational content and various forms of information presentation and visualization, as well as the results of data analysis from the study conducted on a group of respondents. In order to determine the factors that have the greatest impact on the perception of information usefulness on websites by users, the data obtained from the study using various methods, such as online questionnaire, usability testing and heuristic analysis, were analyzed using the DEA method, which is usually used for the analysis and evaluation of efficiency. The results of the research presented in this article can be useful in creating assumptions for methods of content presentation and visualization of various forms of content building for the needs of different user groups for information and business websites.

Knowledge-building in an environment mediated by digital technology: A case study in higher education

The advancement of technology in recent years seems to be prompting a re-ontologising of the world. Digital technology is transforming the educational spaces we inhabit, as well as our way of processing information. Although there are already numerous studies that have addressed this technological reality, only a handful have done so from a theoretical perspective. That is why we present research that seeks to reinforce the latest theoretical contributions for understanding how modern technology may be affecting the way in which knowledge is built. Based on the latest research in social constructivism, this is a qualitative study designed to contribute to the creation of a specific theoretical framework for an onlife world. An ill-structured task and a semi-structured interview were used to observe the use of the thinking skills that enable us to build knowledge and the relationship between them. The results show that the ways of building knowledge are changing, as digital technology fosters the use of higher-order thinking skills that, furthermore, operate in a chaotic, complex, and unpredictable manner. In conclusion, this study upholds the notion that the ways of building knowledge are changing, but we still need more empirical contributions to create a generally accepted theoretical construct for explaining how we build knowledge through digital technology.

Heteroclinic units acting as pacemakers: entrained dynamics for cognitive processes

Heteroclinic dynamics is a suitable framework for describing transient and reproducible dynamics such as cognitive processes in the brain. We demonstrate how heteroclinic units can act as pacemakers to entrain larger sets of units from a resting state to hierarchical heteroclinic motion that is able to describe fast oscillations modulated by slow oscillations. Such features are observed in brain dynamics. The entrainment range depends on the type of coupling, the spatial location of the pacemaker and the individual bifurcation parameters of the pacemaker and the driven units. Noise as well as a small back-coupling to the pacemaker facilitate synchronization. Units can be synchronously entrained to different temporal patterns encoding transiently excited neural populations, depending on the selected path in the heteroclinic network. Via entrainment, these temporal patterns, locally generated by the pacemakers, can be communicated to the resting units in target waves over a spatial grid. For getting entrained there is no need of fine-tuning the parameters of the resting units. Thus, entrainment provides one way of processing information over the grid, when information is encoded in the generated spatiotemporal patterns.

Algocracy in the Political System: Pro & Contra

The development of information and communication technologies leads to new technological phenomena, such as artificial intelligence, which makes it possible to increase the capacity of the human brain to process information and make decisions. Over the last twenty years, the information collection system has become more complex, its volume is growing exponentially, and new ways of processing information, such as neural networks and machine learning, are appearing. Technologies are rapidly changing and developing, and of course the public administration system takes them to improve the accuracy of forecasts and the quality of decision-making in various policy sectors. Algorithmic governance is referred to by the term algocracy. However, not all of the public administration system works with the use of machine learning algorithms remain areas where traditional decision-making methods persist. Despite the progressiveness of algorithmic governance there are still a number of problematic aspects that require ethical and legislative regulation of algorithmic governance. The purpose of this article is to analyze the essence of governance based on the use of big data algorithms and to present a classification of the advantages and risks of an automated data analysis system for public administration.

“Computer metaphor”, interhemispheral asymmetry and species (spontaneous) knowledge of Homo sapiens

The purpose of this article is to supplement the discussion in the field of research and modeling of the process of cognition first with data from neuropsychology and interhemispheric asymmetry, and second with reflections on species’ (spontaneous) knowledge of Homo sapiens. I. The data of neuropsychology and interhemispheric asymmetry signify two differently directed and complementary ways of processing information and regulating the functions inherent in the brain. One of these methods is analytical computer-like information processing, which is necessary for voluntary learning, the other method provides holistic-simultaneous, imaginative, unconscious, and involuntary processing. The duality of cognitive strategies is clearly manifested in the psychological analysis of syndromes in the case of brain lesions, as well as various conditions in healthy people (for example, in the case of bilingualism). II. Biological existence, which is the basis for all other layers of life, is provided by species-specific behavior and knowledge. Presumably species knowledge manifests itself as 1 — Constant involuntary assessment of the surrounding world and adequate reactions to changes in the world: from ordinary reactions (step aside, add a step, etc.) to the ability to react without hesitation in dangerous situations. 2 — The ability to understand connections between phenomena without scientific calculations. The entire history of mankind speaks of the existence of such an ability. People survived without science and created science along the way. 3 — Deep knowledge (often without the ability to logically explain) of what is natural and useful for us as representatives of the Homo Sapiens species, and of what is unnatural and harmful. There are reasons to assume that species knowledge is the basis that determines the common behavior of people of different eras and cultures in everything related to the continuation of the family and the cultivation of a new generation. Species knowledge merges together in the process of development with the knowledge gained during training.

Contextual Text Mining Framework for Unstructured Textual Judicial Corpora through Ontologies

Digitalization has changed the way of information processing, and new techniques of legal data processing are evolving. Text mining helps to analyze and search different court cases available in the form of digital text documents to extract case reasoning and related data. This sort of case processing helps professionals and researchers to refer the previous case with more accuracy in reduced time. The rapid development of judicial ontologies seems to deliver interesting problem solving to legal knowledge formalization. Mining context information through ontologies from corpora is a challenging and interesting field. This research paper presents a three tier contextual text mining framework through ontologies for judicial corpora. This framework comprises on the judicial corpus, text mining processing resources and ontologies for mining contextual text from corpora to make text and data mining more reliable and fast. A top-down ontology construction approach has been adopted in this paper. The judicial corpus has been selected with a sufficient dataset to process and evaluate the results. The experimental results and evaluations show significant improvements in comparison with the available techniques.