Intelligent Components Research Articles

Identification and Ranking of Business Intelligence Components Using the Fuzzy TOPSIS Technique

Objective: The primary objective of this research is to identify and prioritize the components of business intelligence within subsidiaries of the National Bank by employing the fuzzy TOPSIS technique. This endeavor aims to establish a foundation for presenting a scientific approach to enhance business intelligence capabilities. Methodology: This study adopts a mixed-methods approach, initially gathering qualitative data through semi-structured interviews with senior managers from the bank's subsidiaries, followed by quantitative data collection using questionnaires. The fuzzy TOPSIS method was employed to handle the inherent ambiguity and uncertainty in the data, with linguistic variables used to represent the acceptability of each business intelligence component. Findings: Final model was including the dimensions of technical factors (components of information tools, characteristics of information and data, and analysis), business factors (components of stakeholders, economic and financial factors, and customer orientation), and intangible factors (including components of human capital and organizational capital) and 27 indicators. Subsequently, the identified components were ranked using the fuzzy TOPSIS technique, ultimately selecting "information confidentiality", "data reliability", and "high profit margin" as the most important indicators. Conclusion: It can be concluded that the dimensions of innovation in online advertising and its implications in digital marketing are interpretable, and legal supports for innovation in online advertising through the enforcement of laws, enactment and amendment of specific laws and regulations for digital marketing, removal of legal barriers to investment, revenue generation, and clarification of legal ambiguities and definitions in digital marketing are effective.

ULOGA EMOCIONALNE INTELIGENCIJE U ODNOSIMA SA KORISNICIMA U DIGITALNOM OKRUŽENJU

The positive relationship between emotional intelligence and business success has been proven. Employees in all organizational units have different personal characteristics that they incorporate to the organization itself internally or express them externally in relations with users. However, new technological changes have brought new challenges that are reflected in all business segments, especially in those related to relations with users. In addition, technologies based on artificial intelligence represent an unexplored area and it is not known how they affect the emotional and rational side of the relationship with users. Therefore, this paper investigates the role of components of emotional intelligence (EI) such as: self-awareness, self-discipline, motivation, understanding and sociability, in relationship with users in the digital environment. The main goal is to explore and find out the role and importance of emotional intelligence in the function of supporting users, which would enable differentiation of the organization in the competitive market.

Is artificial intelligence really influencing the marketing strategies and consumer behaviour?

Purpose: the main aim of this research is to measure the influence of different components of artificial intelligence and marketing strategies pursued by the consumers. The research is to identify the impact of different components artificial intelligence on consumer behaviour. The sales forecasting method is found with this much successful through the technology and innovations of artificial intelligence in the marketing domain. Design / Methodology: the comprehensive framework for evaluating the quality of website design was subsequently accompanied by the collection of data through a web-based survey. The researcher is able to obtain 452 responses which can be used for the main study research and used confirmatory factor analysis and linear multiple regression analysis. Findings: it is found from the study that the artificial intelligence and its generated suggestions in the marketing Arena is found very much useful for both marketers as well as the consumers. As far as the marketers are concerned the artificial intelligence is very much useful for them to exactly measure and also to get a projective figure of their business turnover in volume. The sales forecasting method is found with this much successful through the technology and innovations of artificial intelligence in the marketing domain. Practical Implications: this empirical study paved the way to identify and implement several marketing implications useful for the marketers as well as the consumers in different demographic background. It is suggested that the marketers should get a complete data in the form of profiling the consumers, demographic background and their purchase details and technological knowledge so that they can generate appropriate artificial intelligence solutions to attract the consumers and motivate them to make their next purchase within the short span of time. Originality/Value: the artificial intelligence can also optimize the advertisement campaigns, preserving profile of consumers, quick communication to the consumers, clarity in the marketing approach and to take independent autonomous marketing decisions with respect to consumer behaviour

Компоненты эмоционального интеллекта, влияющие на социально-психологическую адаптацию студенческой молодежи в иноязычной среде

Компоненты эмоционального интеллекта, влияющие на социально-психологическую адаптацию студенческой молодежи в иноязычной среде

Software Engineering’s Key Role in AI Content Trustworthiness

Artificial intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems. It can also be defined as the science and engineering of making intelligent machines, especially intelligent computer programs. In recent decades, there has been a discernible surge in the focus of the scientific and government sectors on reliable AI. The International Organization for Standardization, which focuses on technical, industrial, and commercial standardization, has devised several strategies to promote trust in AI systems, with an emphasis on fairness, transparency, accountability, and controllability. Therefore, this paper aims to examine the role of Software Engineering in AI Content trustworthiness. A secondary data analysis methodology was used in this work to investigate the crucial role that software engineering plays in ensuring the accuracy of AI content. The dataset was guaranteed to contain reliable and comprehensive material relevant to our inquiry because it was derived from peer-reviewed publications. To decrease potential biases and increase data consistency, a rigorous validation process was employed. The findings of the paper showed that lawful, ethical, and robust are the fundamental components of reliable Artificial Intelligence. The criteria for Reliable Artificial Intelligence include Transparency, Human agency and oversight, technical robustness and safety, privacy and data governance, diversity, non-discrimination, fairness, etc. The functions of software engineering in the credibility of AI content are Algorithm Design and Implementation, Data Quality and Preprocessing, Explainability and Interpretability, Ethical Considerations and Governance, User feedback, and Iterative Improvements among others. It is therefore essential for Software engineering to ensure the dependability of material generated by AI systems at every stage of the development lifecycle. To build and maintain reliable AI systems, engineers must address problems with data quality, model interpretability, ethical difficulties, security, and user input.

Predicting Psychological Well-Being Based on Digital Self-Efficacy and Emotional Intelligence in Students

Objective: This study aimed to investigate the prediction of psychological well-being based on digital self-efficacy and emotional intelligence among students at the Islamic Azad University, South Tehran Branch. Methods and Materials: The study type is correlational-descriptive and cross-sectional. The statistical population includes all students of the Islamic Azad University, South Tehran Branch, in the academic year 2023-2024. Sampling was conducted using the convenience method, and 200 individuals were selected based on the Morgan table, considering the possibility of statistical attrition. Data collection tools included standardized questionnaires on psychological well-being, digital self-efficacy, and emotional intelligence. Data were analyzed using Pearson correlation and multiple regression methods. Findings: Results showed that all components of digital self-efficacy and emotional intelligence have a significant relationship with psychological well-being. The highest correlation coefficient was related to the security component in digital self-efficacy (p<0.05, 0.64) and the emotional awareness component in emotional intelligence (p<0.05, 0.69). Multiple regression analysis showed that both independent variables significantly predict psychological well-being. The coefficient of determination (R²) was 0.30 for digital self-efficacy and 0.48 for emotional intelligence, indicating significant variance explained in psychological well-being by these variables. Conclusion: Based on the results of this study, increasing digital self-efficacy and emotional intelligence skills can help improve students' psychological well-being. Universities and educational institutions can help students enhance their abilities and, consequently, achieve better quality of life and mental health by designing and implementing special educational programs in this area.

THE INFLUENCE OF GAMING TECHNOLOGIES ON THE DEVELOPMENT OF EMOTIONAL INTELLIGENCE OF SCHOOLCHILDREN WHEN LEARNING A FOREIGN LANGUAGE

The article describes gaming technologies as one of the most innovative methods in developing the emotional intelligence of schoolchildren. The author underlines the importance of emotional intelligence for efficient communication and socialization of children. Special attention is paid to description of the experiment aimed at research into the effect the gaming technologies have on the development of the emotional intelligence of schoolchildren when learning a foreign language. The author presents the complex of different kinds of games which stimulate the engagement, encourage the students' speaking in a foreign language, and develop specific components of the emotional intelligence as well as its general level in particular. The results of the research prove the efficiency of the use of the gaming technologies in development of emotional intelligence of schoolchildren when learning a foreign language.

Fear-Neuro-Inspired Reinforcement Learning for Safe Autonomous Driving.

Ensuring safety and achieving human-level driving performance remain challenges for autonomous vehicles, especially in safety-critical situations. As a key component of artificial intelligence, reinforcement learning is promising and has shown great potential in many complex tasks; however, its lack of safety guarantees limits its real-world applicability. Hence, further advancing reinforcement learning, especially from the safety perspective, is of great importance for autonomous driving. As revealed by cognitive neuroscientists, the amygdala of the brain can elicit defensive responses against threats or hazards, which is crucial for survival in and adaptation to risky environments. Drawing inspiration from this scientific discovery, we present a fear-neuro-inspired reinforcement learning framework to realize safe autonomous driving through modeling the amygdala functionality. This new technique facilitates an agent to learn defensive behaviors and achieve safe decision making with fewer safety violations. Through experimental tests, we show that the proposed approach enables the autonomous driving agent to attain state-of-the-art performance compared to the baseline agents and perform comparably to 30 certified human drivers, across various safety-critical scenarios. The results demonstrate the feasibility and effectiveness of our framework while also shedding light on the crucial role of simulating the amygdala function in the application of reinforcement learning to safety-critical autonomous driving domains.

Emotional Intelligence as a Correlate of Restiveness among in-School Adolescents in Nigeria Universities: Counselling Implication

The spate of mental health issues and social decadence among the adolescents has necessitated this study which aimed at correlating emotional intelligence and restiveness among the in-school university adolescents in Enugu State higher institutions, Nigeria. The study formulated five research hypotheses which were tested at 0.05 level of significance using correlation co-efficient analysis of Pearson Product Moment correlation. The study adopted a correlation research design and was carried out in four universities in Enugu state. A sample of (N-120)undergraduates were selected through a Peer Nomination Scale and a purposive sample to include equal numbers of male and female, thirty students from each school. Two research instruments were administered to the selected respondents namely; the Emotional Intelligence Questionnaire (EIQ) and Restiveness Factor Description (RFD).The instruments were validated through pilot study for the reliability index and vetting for its face and content validity by experts in the field of test and measurement. Descriptive statistics of mean and percentages were employed to code the responses while Pearson Product Moment Correlation Coefficient was adopted to test the five hypotheses. The findings from the study returned negative significant correlation between all the five domains of Emotional intelligence and restiveness. The students’ responses on the five emotional intelligence domains were all at average low mean of 2.04, 2.13, 1.96, 1.99 and 1.97 respectively indicating that the restive adolescents are low on Emotional Intelligence. It was recommended that the universities should provide resources both human and materials tailored towards promoting the different components of emotional intelligence. The counselling implications were also proffered.

Smart Energy Components – Foundation of A Decentralised Energy Supply

The energy sector is facing a significant change from a centralised to a decentralised energy supply. In order to successfully implement this change, smart control of the technologies used is essential. This paper first analyses the motivation for using these intelligent energy components and then examines the main components of smart energy and the Internet of Energy in detail. The analysis focuses on the way in which these technologies can contribute to increasing efficiency, reducing costs and increasing energy security. It also identifies obstacles to the implementation of this concept, such as maintaining grid stability, increasing energy efficiency and storing energy. Finally, the current state of development is presented and the further path to a functioning decentralised energy supply is described.

Творча біографія Івана Котляревського в жанрово-крайовому контексті перших десятиліть ХХІ століття

In the article, for the first time, samples of Ukrainian artistic and biographical Kotlyarevskiana of the first decades of the 21st century are analyzed holistically in a typological and regional aspect. Biographical, cultural-historical, comparative, and psychological methods of scientific research are applied. The main object of study is the biographical literary, artistic and popular science works «The Choice of Captain Kotlyarevsky» (2020) by V. Dobryansky and «Ivan Kotlyarevsky: Between the Empire and Ukraine» (2021) by P. Kraljuk; contextual component of intelligence – biographical novels and essays of the latest writing «P. S. of Hryhoriy Skovoroda...» (2009) by M. Shtelmak, «All angels of the Triangle. Apocrypha of Grigory Skovoroda's Travels» (2012) by V. Eshkilev, «Black Apple» (2013) and «Moon, Moon» (2022) by S. Protsyuk, «Secret Agent Mykola Gogol» (2016) P. by Kraljuk, «Iron Water» (2021) by M. Layuk. They represent figures of the classics of Ukrainian literature, whose lives are connected with the Poltava region, and were created and published in the postmodern period. The intensification of scientific and literary-artistic biography (in particular, writer's) nowadays is noted, the humanitarian and civilizational importance of this process is emphasized; the academic, scientific, popular science, and artistic formats of purely literary biographies are outlined and the special spread of the biographical novel (a type of artistic biography) and creative biography (a popular historical-literary mix) is indicated; the term «creative biography» is used with a scientific and universal meaning that is remarkable for today. It has been noted that Poltava Kotlyarevskiana, as well as regional writer biographies in general, is currently actively developing; its creators – mainly writers from the western region of Ukraine – time biographical novels and historical-publicist essays to the jubilee dates of outstanding writers, rethink and often interpret freely their biographies, causing public resonance and discussions.P. Kralyuk and V. Dobryanskyi in their works dedicated to I. Kotlyarevsky subtly depict and interpret in an original way, ideologically actualize in an anti-colonial and civic-patriotic way the image and achievements of the «father» of Ukrainian literature, emphasize his psychoworld, the alleged splitting of the spirit, but integral soul, interpreted as a national cultural code that clearly resonates in the tragic present.

Arabic Text Detection on Traffic Panels in Natural Scenes

Identifying and acknowledging Traffic Panels (TP) and the text they display constitute significant use cases for Advanced Driver Assistance Systems (ADAS). In recent years, particularly in the context of the Arabic language, extracting textual information from TP and signs has emerged as a challenging problem in the field of computer vision. Furthermore, the significant rise in road traffic accidents within Arabic-speaking countries has resulted in substantial financial losses and loss of human lives. This is largely attributed to the limited number of diverse datasets for traffic signs and the absence of a reliable system for TP detection. Implementing warning and guidance systems for drivers on the road not only addresses this issue but also paves the way for the integration of intelligent components into future vehicles, offering decision support for transitioning to semi-automatic or fully automatic driving based on the driver’s health condition. These tasks present us with two main challenges. First, it involves developing a new Arabic dataset called the Syphax Traffic Panels dataset (STP) tailored to the diverse conditions of natural scenes gathered from “Sfax,” a city in Tunisia. This dataset aims to provide high-quality images of Arabic TP. Secondly, we suggest a deep learning method for detecting Arabic text on TP by evaluating the performance of the state-of-the-art algorithms in this context. In our study, we enhance the architecture of the most successful result achieved. The experiments conducted reveal promising results, affirming the significant contribution of our dataset to this research area, and even more encouraging results stemming from the enhancements made to the proposed method. The dataset we possess is accessible to the general public on IEEE DataPort https://dx.doi.org/10.21227/5zd9-pe55

A CROSS-SECTIONAL STUDY ON ASSOCIATION BETWEEN EMOTIONAL INTELLIGENCE AND ACADEMIC PERFORMANCE AMONG NURSING STUDENTS OF SELECTED NURSING COLLEGES IN KATHMANDU

Background: Emotional intelligence incorporates the important aspects of interpersonal and intrapersonal relationships, adaptability, moods and stress management skills, which have a profound effect on the academic performance of students. Methodology: An Analytical Cross-sectional study was carried out with main objective to find out the association between emotional intelligence and academic performance of nursing students from selected nursing colleges. Using non - probability purposive sampling method, PCL Nursing 3rd year students were selected and data was collected using standardized Assessing Emotions Scale to measure Emotional Intelligence and final examination score of the students was considered as academic performance. Collected data was processed and analyzed using SPSS version 24. Results: The findings revealed that majority of the nursing students have high emotional intelligence. There is no any statistically significant correlation between emotional intelligence and academic performance of nursing students. Regarding sub dimensions of Emotional Intelligence, there was no any statistically significant correlation between managing other’s emotion, perception of emotion and utilization of emotion with academic performance, except for managing own emotion which has statistically significant correlation with academic performance. Nursing students from different ethnicity, mother and father’s education background do not defer in EI scores except age and type of family. Conclusion: Majority of the nursing students have higher level of emotional intelligence. Emotional intelligence is not significantly correlated with academic performance. This paper suggests that emotional intelligence is not guaranteed with the highest academic grades of students and that emotional intelligence components may be incorporated into the curriculum.

Digital Computer Science for Tax System in SME Taxpayers in Binjai City

Computer technology with digital power will bring better tax payment procedures and expectations of compliance levels. The digital world will encourage increasingly widespread use of artificial intelligence components to make tax-related work easier. This research falls under comparative causal studies using a survey method. The population consists of MSME operators (individual taxpayers) in the city of Binjai who have filled out and returned the questionnaire to the researchers. The sample selection was carried out using purposive sampling technique, and data was gathered from the opinions or perceptions of MSME operators (individual taxpayers) in Binjai. The primary data obtained were descriptively analyzed, and the model and the influence of tax rates and tax penalties on taxpayer compliance through tax understanding were examined using path analysis. The findings indicate a significant influence of tax rates and tax penalties on taxpayer compliance both simultaneously and partially, with tax understanding as an intervening variable not fully proving to mediate the relationship between tax rates and penalties on taxpayer compliance. The low path analysis value in this study should be considered by subsequent researchers to include other variables that may affect corporate value

Emotional intelligence as predictor of resilience toward academic stress mitigation among Public and Private Medical College students

Background: Emotional intelligence is a crucial concept in management, business, engineering, nursing and medicine. It has gained more attention than personality and Intelligence Quotient. Understanding human emotions is essential for understanding emotional intelligence. Aim: High-EQ individuals can combine intellectual and emotional skills to adapt to new situations and achieve goals. Individuals with high emotional intelligence can read interpersonal cues and manipulate others' emotions. Method: The Comparative study is conducted in Rai Medical College Sargodha from April 2021 to August 2022and population was the MBSS students. Provide more demographic and socioeconomic data on survey participants. Determine the emotional intelligence traits all respondents share. Determine the respondents' academic achievement and calculate an average. Thoroughly study how socioeconomic background affects emotional intelligence. Determine if respondents' socioeconomic profile affects academic performance. To examine and publish the relationship between emotional intelligence components and respondents' academic performance. Result: The study reveals a significant correlation between gender and emotional intelligence, with women generally having greater emotional intelligence. The majority of respondents are male, with 97.14% attending public institutions and 2.5% attending private medical colleges. Age and educational degree also impact emotional intelligence, with 54.89% of respondents aged 18-19 and 36.73% aged 20-22. Higher education levels are associated with increased emotional intelligence. Conclusion: Emotional intelligence and academic performance were positively correlated. Emotional regulation and adaptive emotions are linked, suggesting emotional intelligence may prevent ASD. The study shows that high-AR students naturally manage and use emotional information to perform better academically. This supports the COR-based theoretical claims linking AR, EI, and AP. Keywords: Emotional intelligence, Stress, Behavioral science, Public Private medical college.

The Role of Social Intelligence and Resilience in Explaining Students’ Distress Tolerance: A Study during Covid-19 Pandemic

IL RUOLO DELL’INTELLIGENZA SOCIALE E DELLA RESILIENZA NELLO SPIEGARE LA TOLLERANZA AL DISAGIO DEGLI STUDENTI: UNO STUDIO DURANTE LA PANDEMIA DI COVID-19 Abstract Understanding the factors that influence or correlate with distress tolerance is very important. Therefore, the aim of this study was to investigate the role of social intelligence and resilience in explaining college students’ distress tolerance. A descriptive correlational study was carried out on 260 male college students of Farhangian University of Birjand, Iran in 2020/21. They completed Social Intelligence Scale, Resilience Scale, and Distress Tolerance Questionnaire. The results showed that there was a direct and significant relationship between social intelligence and distress tolerance (r = 0.473; p <0.001), as well as resilience and distress tolerance (r = 0.608; p = 0.008). Also, the coefficient of determination showed that the components of social intelligence and resilience up to 65% can explain the variance of students’ distress tolerance. Psychological interventions such as promoting social intelligence and effective resilience can be used to prevent and control the college students’ distress especially during Covid-19 pandemic.

Information System for the Educational Center

The goal of the research of the qualification thesis is the development of an intelligent information system of the educational centre using the Python programming language and the Django framework, the SQLite database system, and the chatbot with artificial intelligence ChatGPT. The developed system should facilitate the interaction of different types of users with learning/training centres in order to acquire new necessary skills. As you know, from now on every day more and more educational centres are opening, which provide their services for the study of this or that ability. Due to the onset of the pandemic period, all such educational centres are transferring their classes to the online mode, and the actual need to solve this type of issue arises more and more often. In this work, an analytical review of literary sources is carried out, a comparison of known means of implementation, i.e., so-called analogue systems, is carried out; the actual functioning of this type of system is checked. In addition, a goal tree is being built, which clearly outlines the general goal, namely, the optimization of all processes of the educational centre. In addition, an equally important step is the description of requirements, which is carried out in this work using the RUP methodology for the intelligent information system of the educational centre. The category of users is also determined and a generalized model of system functioning in the environment is built. To develop the system, an analysis of possible methods and software tools for creating and deploying the system is carried out. The most optimal methods for this case are chosen, namely the method of software synthesis and the method of using ready-made solutions, because their application will provide an opportunity to develop a system from scratch using the necessary components and provide an opportunity to integrate an already ready-made system with an intelligent component. Next, a recalculation of possible options among the integration of ready-made intelligent components is carried out, and a chat system with artificial intelligence is chosen, because it will give users the opportunity to search for answers to their questions without leaving the system and facilitate the learning process for each of the users.

Transformation of economic model: Comparative analysis of intellectual, intelligent and smart economy in the context of digitalization

Aim. To identify the interrelationships that contribute to the effective integration and synergy of intellectual, intelligent and smart components in socio-economic formations.Objectives. To perform a semantic analysis of the process of intelligence; to describe the evolution of intellectual economy; to conceptually distinguish between intelligent, intellectual and smart economy; to identify interrelationships, similarities and differences between intellectual and digital economy through comparison.Methods. The study applied comparative-historical method, literature review, semantic and qualitative analysis.Results. The etymology of intelligence was studied, which allowed us to analyze the origin of the term and its historical dynamics. The key sources devoted to the development of intellectual economy were systematized and studied, focusing on the identification of the main stages of this process. The concepts of intelligent, intellectual and smart economy were clarified and differentiated. The key features of each concept are defined and their differences are identified. The intersection of intellectual and digital economy was considered, which contributed to a better understanding of their interaction and interrelation.Conclusions. The intelligent economy, based on the application of advanced technologies to optimize processes and decisions, emphasizes automation, predictive models, and real-time solutions. The knowledge- and intellect-intensive economy emphasizes the use of knowledge as a key resource, implying the availability of skilled human resources, intellectual property and scientific and technological capabilities. Smart economy focuses on integrating digital technologies and networked solutions into economic systems to achieve greater efficiency, sustainability and flexibility.

Особенности профессиональной самоактуализации студентов вуза – будущих учителей средней школы с учетом уровня развития невербального компонента их социального интеллекта

The work aims to identify the features of professional self-actualization of university students – future secondary school teachers in connection with the development of the non-verbal component of their social intelligence. The paper describes the process of conducting a study consisting of the theoretical and the empirical stages and oriented towards achieving the specified aim. The scientific novelty of the research lies in identifying the nonlinear nature of the relationships between the features of professional self-actualization of future teachers and the level of development of the non-verbal component of their social intelligence. As a result, the work has shown that the majority of future teachers have an average level of development of socio-perceptual abilities (the non-verbal component of social intelligence) and an average level of self-actualization. Concerning university students – future secondary school teachers, self-actualization and the level of development of the non-verbal component of their social intelligence are interrelated, but these relationships are nonlinear. Teachers with the low level of socio-perceptual abilities have less pronounced components of self-actualization, such as time orientation, values and creativity (compared with teachers with both high and medium levels of socio-perceptual abilities).

Enhancing Object Detection in Remote Sensing: A Hybrid YOLOv7 and Transformer Approach with Automatic Model Selection

In the remote sensing field, object detection holds immense value for applications such as land use classification, disaster monitoring, and infrastructure planning, where accurate and efficient identification of objects within images is essential for informed decision making. However, achieving object localization with high precision can be challenging even if minor errors exist at the pixel level, which can significantly impact the ground distance measurements. To address this critical challenge, our research introduces an innovative hybrid approach that combines the capabilities of the You Only Look Once version 7 (YOLOv7) and DEtection TRansformer (DETR) algorithms. By bridging the gap between local receptive field and global context, our approach not only enhances overall object detection accuracy, but also promotes precise object localization, a key requirement in the field of remote sensing. Furthermore, a key advantage of our approach is the introduction of an automatic selection module which serves as an intelligent decision-making component. This module optimizes the selection process between YOLOv7 and DETR, and further improves object detection accuracy. Finally, we validate the improved performance of our new hybrid approach through empirical experimentation, and thus confirm its contribution to the field of target recognition and detection in remote sensing images.