Information Handling Research Articles

An integrated outranking technique with spherical fuzzy rough numbers for the treatment of cadmium-contaminated water problem in China

The Chinese economy is one of the largest and most dynamic economies in the world. Over the past few decades, China has experienced rapid economic growth from agrarian to industrial powerhouse fueled by manufacturing, exports, and services. However, this rapid growth has also brought about challenges, including environmental issues like water contamination. The indulgence of cadmium metal in regular used water can cause serious health issues, including kidney damage and cancer. Many strategies have been implemented for treatment of water contamination. The main focus of this research is to introduce a novel methodology for treatment of cadmium contaminated water problem in China. This study seeks to demonstrate the multi-criteria group decision-making ability based on the outranking relations within the confines of a contemporary, well-organized and extremely flexible model of spherical fuzzy rough numbers. Spherical fuzzy rough numbers, amalgamation of rough numbers with traditional spherical fuzzy numbers, make the use of membership, non-membership and neutral membership degrees along with the manipulation of the subjectivity and reliance on objective uncertainties. The combination of spherical fuzzy rough numbers with an outranking multi-criteria group decision making technique, Elimination and Choice Expressing Reality, integrates spherical fuzzy logic to handle uncertainty and imprecision in multi-criteria decision-making. This approach captures degrees of uncertainty and hesitancy with spherical fuzzy numbers, improving the handling of imprecise information. The working mechanism involves generation of outranking relations among alternatives by comparing predominant and subdominant options, calculating score degrees, concordance and discordance sets, and incorporating subjective spherical fuzzy rough criteria weights. Unlike traditional methods that use crisp or conventional fuzzy numbers, this technique provides a more reliable and flexible evaluation by integrating rough set theory for better handling of imprecision and uncertainty. Finally, an outranking graph is drawn that points from the supreme option to inferior one. The legitimacy of the proposed technique is, then, testified by making its comparison with other existing techniques.

Neurorights, Neurotechnologies and Personal Data: Review of the Challenges of Mental Autonomy

Objective: to present the results of a systematic review of research on the impact of neurotechnology on legal concepts and regulatory frameworks, addressing ethical and social issues related to the protection of individual rights, privacy and mental autonomy.Methods: The systematic literature review was based on the methodology proposed by a renowned British scholar, a professor emerita of computer science at Keele University Barbara Kitchenham, chosen for its flexibility and effectiveness in obtaining results for publication. Thorough searches were carried out with the search terms “neurotechnology”, “personal data”, “mental privacy”, “neuro-rights”, “neurotechnological interventions”, and “neurotechnological discrimination” on both English and Spanish sites, using search engines like Google Scholar and Redib as well as databases including Scielo, Dialnet, Redalyc, Lilacs, Scopus, Medline, and Pubmed. The focus of this research is bibliometric data and its design is non-experimental with a cross-sectional and descriptive, using content analysis based on PRISMA model.Results: the study emphasizes the need to establish clear ethical principles to protect individual rights and promote responsible use of neurotechnologies; a number of problems of mental autonomy were identified, such as improper handling of information, lack of legal security guarantees, violation of rights and freedoms in the medical sphere. The author shows the need to adapt the existing regulatory legal framework to address the ethical and social problems arising from the new neurotechnologies. It is noted that a broad study of neurotechnology issues will contribute to the protection of human rights.Scientific novelty: an expanded understanding of the five neurorights within the Universal Declaration of Human Rights is proposed; neurorights are viewed as a new category of rights aimed at protecting mental integrity against the misuse of neurotechnologies. The author justifies the adoption of such technocratic principles as personal identity, free will, mental privacy, equal access and protection against bias.Practical significance: the obtained results are relevant for understanding modern legal concepts related to neurorights and for adapting the existing normative legal acts to solve ethical and social problems arising from the emergence of new technologies, protection of human neurorights and liability for their violation. The study of these issues is key for provision of further responsible development and use of neurotechnologies.

The Influence of Leadership Style and Work Environment on Motivation and Its Impact on Employee Performance

The goals to be attained in the research study are to: establish management design, workplace, staff member inspiration plus efficiency; examine the impact of management design plus office straight and also indirectly on staff member inspiration; assess the impact of management design as well as workplace straight along with indirectly on worker efficiency; assess the impact of inspiration on team member efficiency; as well as assessing the impact of management design along with office on staff member efficiency via inspiration. The research study technique made use of is detailed as well as confirmation techniques utilizing main coupled with additional information. The populace in this research study were staff members of the One Stop Integrated Services along with Investment Service (PMPTSP) West Tanjung Jabung Regency Jambi Province, completing 52 individuals. The tasting technique makes use of the demography technique or filled up sample. The evaluation approach utilizes the Path Analysis technique and also theory screening makes use of the F examination plus t examination. Information handling makes use of SPSS V. 22 software program. The research study outcomes program: Leadership design and also office remain in great problem, staff member inspiration as well as efficiency remain in really high problem. Management design and also office have a straight plus indirect result on inspiration. At the same time plus partly, management design and also work environment have a substantial impact on inspiration; Leadership design as well as office have a straight as well as indirect result on staff member efficiency. At the same time together with partly management design plus work environment, have a substantial impact on staff member efficiency; Motivation has a considerable impact on worker efficiency; Leadership style and work environment through motivation have a direct and indirect effect on employee performance.

Implicit Cultural Information Transmission and English Translation Strategies

Implicit cultural information plays a crucial role in the translation process, as it is often conveyed through cultural symbols, metaphors, and social contexts that do not directly appear on the surface of the text, posing challenges in translation. This paper starts with the definition and characteristics of implicit cultural information, analyzing its manifestations in translation and its relation to cultural differences and linguistic structures, focusing on the translation challenges posed by cultural symbols and metaphors. By studying domestication, foreignization, contextual reconstruction, and flexible adaptation strategies, this paper proposes translation strategies that adapt to different cultures and contexts to ensure the effective transmission of implicit cultural information, thereby enhancing the accuracy and efficiency of cross-cultural communication. The aim is to provide a theoretical basis and methodological guidance for translation practice, optimize the handling of implicit cultural information in English translation, and promote the in-depth dissemination of cultural connotations.

APPLICATION OF MACHINE LEARNING TECHNIQUES TO INCREASE THE LEVEL OF ACCURACY OF OPTICAL CHARACTER RECOGNITION RESULTS

One of the most pervasive processes of modernity is undoubtedly digitalization, which has encompassed all key spheres of human life. The development of information technology has contributed to large-scale changes not only in the everyday aspect of life, but also more globally, automating complex business processes in the field of entrepreneurship, economics, and healthcare. The transition to digital data and documentation has provided greater accessibility to necessary information and has also enhanced the efficiency of its analysis and processing. Due to this fact, optical character recognition (OCR) technology has gained significant importance, enabling the identification and extraction of textual data from images. OCR systems play a pivotal role in the digital transformation of society as they eliminate the need for manual handling of textual information in images and are applicable in automating the majority of business processes associated with paper-based data processing, such as gathering statistical data from paper forms, reflecting paper documents in electronic document management systems, converting textual information into audio files, and so on. This paper is dedicated to describing optical character recognition technology, as well as providing an overview of machine learning techniques that are actively used in the context of its modern implementation, in order to enhance the quality of the obtained results. In addition, the paper presents the principles of operation of the described approaches, their capabilities, as well as some limitations that may be encountered when using them in various scenarios.

Imputation based wind speed forecasting technique during abrupt changes in short term scenario

AbstractIt is tough and complex to forecast wind speed due to its intermittent and stochastic nature as well as sudden and abrupt variations in the wind speed. Further, it is required to handle the variety of scenarios e.g. cyber‐attacks, unexpected power device malfunction, communication/sensor outages etc. that can cause the missing data.This paper proposes and employs a de‐noising autoencoder algorithm for wind speed forecasting to ensure the handling of missing data information. At the next step, the data is processed via variational mode decomposition technique to mitigate the noise and improves the model's prediction accuracy. Furthermore, the bi‐directional long‐short term memory deep learning approach is tied with convolution neural network to increase prediction accuracy and anticipating the sudden/abrupt changes in wind speed accurately. Finally, actual wind speed related data is examined to scrutinize meticulousness of projected forecast methodology particularly during sudden/abrupt changes in the wind speed. The parameter indicators of the wind speed forecasting technique exhibit the capability of improved predictions under the diversified conditions.

Abstracting It All: The Soviet Institute of Scientific Information (VINITI) and the Promise of Centralisation, 1952–1977

AbstractIn the aftermath of the Second World War, effective handling of scientific information was identified as crucial for advancement and international competitiveness. Here, we study how the Soviet Union, through the founding of The All-Union Institute for Scientific and Technical Information (VINITI), developed its own grandiose system which served researchers and engineers throughout the USSR. By studying its inception, the way it was structured, and how it relates to similar grand visions of how to organise knowledge, we provide rare insights into a partly alternative history of how scientific information was organised in the latter half of the 20th century. Based on available sources in English and Russian, we consider the ideas behind this grand initiative for acquiring international literature, as well as how it was received and presented to a foreign audience. In this effort, we put particular emphasis on the first 25 years of VINITI (1952–1977) while at the same time focusing on central ideas in its organisation such as “enrichment”, “abstracting” and “pre-printing”. A key principle emerging from our analysis is how the notion of concentration becomes a fundamental principle for its operations. Overall, the activities of VINITI can today appear as both old-fashioned, bordering on the utopian, and as visionary and modern in its abandonment of journals and traditional forms of peer review.

Securing Automated Intelligence: Challenges and Solutions in RPA and Generative AI Integration

Integrating Robotic Process Automation (RPA) and Generative AI can revolutionize business processes, enabling greater efficiency, scalability, and intelligent decision-making. However, this powerful combination also introduces various security challenges and impacts to governance that organizations must address to protect sensitive data and maintain trust in automation systems. As RPA bots increasingly interact with AI models, vulnerabilities such as unauthorized data access, malicious model manipulation, and improper handling of sensitive information become more pronounced. These risks can lead to cyberattacks, data breaches, and regulatory compliance violations. This paper examines the security challenges inherent in RPA and Generative AI integration, focusing on three key areas: data privacy, model integrity, and automation governance. We assess how improper configurations and lack of security oversight can expose these systems to exploitation. Furthermore, we explore solutions such as implementing robust encryption protocols, secure data access controls, and continuous monitoring of AI model behavior to detect anomalies. By presenting case studies and evaluating emerging best practices, we offer a framework for safeguarding RPA and AI systems, ensuring that automation remains a trusted and secure tool for organizations. The paper also discusses aligning security strategies with regulatory requirements and industry standards. This approach enables organizations to unlock the full potential of RPA and Generative AI while mitigating risks and protecting against evolving cyber threats.

Abstract B034: Understanding how family dynamics influence discussions about prostate cancer: A PEN-3 model analysis of shared risk communication within African American families

Abstract Background: Race and family history are important risk-stratifying variables for prostate cancer prevention and control. Despite their elevated risks for developing and dying from the disease, African-Americans are less knowledgeable about their shared familial risk than the general population. African American family structures are quite diverse. However, the manner in which this diversity influences the flow of shared risk information is largely absent from the literature. This study uses the PEN-3 cultural model to investigate how family dynamics influence prostate cancer information sharing within African American families. Method: Twenty-three members of ten families with African-American men completed semi-structured interviews in 2018 - 2019. Using a non-probability sampling scheme, nuclear, blended, extended, single-parent and cohabiting families were recruited to participate. The interview guide was structured to elicit information about participant's (a) family descriptions/family dynamics, (b) health communication patterns, (c) motivations for sharing health information, (d) health communication approaches, (e) handling of withheld information, and (f) generational communication strategies. All audio-recorded interviews were conducted by three African- American investigators and transcribed verbatim by a professional transcriptionist. All verbatim transcripts were entered into MAXQDA qualitative software for analysis using the PEN-3 model dimensions. Results: Cultural Identity - Personal/Extended: Families were more supportive of sharing sensitive health information with kinship group members who are viewed as close than distant. Neighborhood: The church family was sometimes viewed as an extension of the immediate family, particularly in situations where family members are geographically dispersed. Relationships and Expectations - Perceptions: Indirect communication is acceptable for relaying general information with young people, but direct communication is preferred for older adults. Cultural Empowerment - Negative: Withholding information to protect other's emotions can sometimes result in feelings of exclusion or mistrust when those being protected discover that information was withheld. Conclusion/Discussion: These findings highlight the complexity of family dynamics in communicating shared prostate cancer risk information within African American families. The generational divide in communication preferences suggests that strategies are needed to bridge that gap. Citation Format: Levi Ross, Michael A. Preston, Linda Collins, Florida Uzoaru, Torhonda C. Lee. Understanding how family dynamics influence discussions about prostate cancer: A PEN-3 model analysis of shared risk communication within African American families [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr B034.

Mathematical Techniques for Enhancing Signal Processing in Electronics

Flag preparing is an critical portion of advanced innovation since it lets us analyze, alter, and progress information for numerous employments, from therapeutic checks to broadcast communications. With the expansion of progressed numerical strategies to information handling, electronic frameworks have gotten to be much more valuable and precise. This paper looks at a few vital numerical procedures that are utilized to move forward flag handling. It centers on calculations and hypothetical models that make flag examination and modifying way better. It is looked at how procedures like Fourier changes, wavelet changes, and measurable flag preparing can offer assistance move forward sifting, commotion diminishment, and determination. The Fourier change can break down signals into their recurrence components. This lets you are doing precise recurrence space investigation and sifting, which is exceptionally imperative for assignments that require high-frequency exactness. Wavelet changes permit for multi-resolution investigation, which makes it simpler to see at signals at diverse sizes and superior distinguish characteristics that alter or do not remain the same. Versatile sifting, expectation hypothesis, and other measurable strategies are talked approximately in terms of how they offer assistance decrease commotion and progress signals in changing settings. Utilizing these logical strategies together not as it were makes electronic frameworks work way better and be more solid, but it too opens the entryway to modern employments in ranges like machine learning and information analytics. This exposition gives an in-depth see at these numerical strategies, centering on their hypothetical establishments, how they are utilized in genuine life, and how they have changed cutting edge flag preparing. This paper looks at these strategies in awesome detail to appear how vital unused scientific thoughts are for progressing electronic flag preparing advances and making a difference to create electronic frameworks that are more brilliant and work superior.

Нейровизуализационный подход для выявления биомаркеров рабочей памяти у больных с хронической ишемией мозга

Verbal working memory (VWM) is a fundamental function responsible for temporary storage and short-term handling of verbal information. The study was aimed to determine the working memory biomarker associated with imaging of the source of infra-slow electrical activity in patients with chronic cerebral ischemia (CCI). A total of 50 patients with CCI took part in the study: 16 males and 34 females aged 50–85 years. VWM was evaluated by the Luria test. The subjects were divided into two groups matched by age with the VWM below and above the average level for the studied sample. The infra-slow, below 0.1 Hz, electrical activity, otherwise known as the DC potentials (DCPs) of the brain, was recorded with five monopolar leads: frontal, central, occipital, right and left temporal. The resting state fMRI was used to analyze brain regions with the activated BOLD (blood-oxygen-level-dependent) signal that were associated with the brain regions responsible for VWM and the DCP generation sources recorded with the non-polarizable electrodes. The differences in BOLD signal activation and infra-slow activity amplitude were found in two VWM groups. These resting-state neural networks, VWM and the neural network responsible for DCP generation, overlapped in frontal regions. There were significant differences in DCP recorded with the frontal lead in two VWM groups (р = 0.00004). In patients with CCI, infra-slow activity, recorded with the frontal lead that is generated by the neural network fragment representing an intersection of the VWM network and the part of the brain responsible for DCP generation in the frontal region, is a VWM biomarker.

Responsive circularly polarized ultralong room temperature phosphorescence materials with easy-to-scale and chiral-sensing performance

Circularly polarized room temperature phosphorescence materials represent a state-of-the-art frontier of optical materials and exhibit promising applications in various fields. Herein, we fabricate a series of full-color circularly polarized room temperature phosphorescence materials, based on anionic cellulose derivatives and achiral luminophores. The ionic achiral substituents promote the spontaneous formation of chiral helical structure of cellulose derivatives via the electrostatic repulsion effect. There are multiple interactions between anionic cellulose derivatives and the doped luminophores, thus the chirality is transferred to luminophores and the non-radiative transition is inhibited. The resultant materials can be easily processed into large-scale film and flexible 3D objects with repeatable folding and curling properties. In addition, their phosphorescence performance shows to be excitation-dependence, time-dependence, visible-light excitation, and multi-responsiveness to humidity, temperature as well as pH value. Importantly, they recognize many enantiomers in an instrument-free visual mode, including amino acids, hydroxyl acids, organic phosphate and hydrobenzoin. These results provide insights into design of advanced optical materials which can be applied in multilevel information handling and chiral sensing.

Customized Approaches for Introducing Road Maintenance Management in I-BIM Environments

Road maintenance management aims to satisfy quality, comfort, and safety requirements for the various assets. To overcome delays and barriers in the widespread adoption of road management systems, the Building Information Modeling (BIM) approach may offer significant advantages as a convenient alternative for road maintenance management. Although existing BIM platforms are not fully equipped for this purpose, defining original modules and scripts can extend their capabilities, allowing for the handling of road condition information and maintenance management. In this context, this paper presents an operative framework designed to leverage BIM benefits for road maintenance management, particularly in terms of virtual inspection, asset condition assessment, and maintenance design. To achieve this, specific original and customized smart objects and routines were coded in I-BIM platforms, tailored to different scales, aims, and detail levels. These smart objects incorporate user-defined extended attributes related to pavement condition and maintenance planning (such as roughness, rutting, structural capacity). In particular, the authors have developed original virtual smart objects in different platforms, serving as “containers” for the survey information. These objects are adapted to display quality levels of the pavement segments in a realistic and user-friendly environment. Additionally, original routines were coded to automatically import survey data from external datasets and associate this information with the appropriate objects. This customized and extended approach, not available in commercial platforms, can effectively support maintenance operators.

A multibranch and multiscale neural network based on semantic perception for multimodal medical image fusion

Medical imaging is indispensable for accurate diagnosis and effective treatment, with modalities like MRI and CT providing diverse yet complementary information. Traditional image fusion methods, while essential in consolidating information from multiple modalities, often suffer from poor image quality and loss of crucial details due to inadequate handling of semantic information and limited feature extraction capabilities. This paper introduces a novel medical image fusion technique leveraging unsupervised image segmentation to enhance the semantic understanding of the fusion process. The proposed method, named DUSMIF, employs a multi-branch, multi-scale deep learning architecture that integrates advanced attention mechanisms to refine the feature extraction and fusion processes. An innovative approach that utilizes unsupervised image segmentation to extract semantic information is introduced, which is then integrated into the fusion process. This not only enhances the semantic relevance of the fused images but also improves the overall fusion quality. The paper proposes a sophisticated network structure that extracts and fuses features at multiple scales and across multiple branches. This structure is designed to capture a comprehensive range of image details and contextual information, significantly improving the fusion outcomes. Multiple attention mechanisms are incorporated to selectively emphasize important features and integrate them effectively across different modalities and scales. This approach ensures that the fused images maintain high quality and detail fidelity. A joint loss function combining content loss, structural similarity loss, and semantic loss is formulated. This function not only guides the network in preserving image brightness and texture but also ensures that the fused image closely resembles the source images in both content and structure. The proposed method demonstrates superior performance over existing fusion techniques in objective assessments and subjective evaluations, confirming its effectiveness in enhancing the diagnostic utility of fused medical images.

EMPLOYEE PAYROLL DATA ANALYSIS USING MACHINE LEARNING

Every company is using machine learning to predict their employees' working styles and competence by estimating how long it will take them to complete a task. The effectiveness of various classification algorithms for predicting employee salary classes has been the subject of numerous recent studies. Salary prediction appears to be a challenging endeavor from the perspective of machine learning because of the low sample size, relatively high dimensionality, and presence of noise. Deeper architectures are required to address this and locate more useful features. Also, more information investigation and information handling can be commonsense to make the forecast model go past the relationship and accuracy guidelines by highlight extraction methods.

SIMFusion: A semantic information-guided modality-specific fusion network for MR Images

Multi-modal medical image fusion aims to integrate distinct imaging modalities to yield more comprehensive and precise medical images, which can benefit the subsequent image analysis tasks. However, prevailing state-of-the-art image fusion methods, despite substantial advancements, do not explicitly address the efficient handling of complementary information between modalities. Moreover, most current multi-modal medical image fusion methods encounter challenges when integrating with practical tasks, which lack the guidance of semantic information, thus hindering the generation of high-quality images for accurate identification of lesion areas. To deal with these challenges, this paper introduces a novel semantic information-guided modality-specific fusion network for multi-modal magnetic resonance (MR) images, named SIMFusion. Specifically, we propose the decomposition branch to capture common and specific features from MR images of different modalities for fusion to reduce information redundancy through correlated mutual information loss. Subsequently, we obtain their semantic characteristics via the semantic branch utilizing a pre-train segmentation network and, finally, achieve an adaptive balance between the two sets of features through a specialized fusion strategy. Extensive experiments demonstrate the superiority of SIMFusion over existing competing techniques on both BraTS2019 and ISLES2022 datasets, with 8.1% improvement in MI and 38.7% in VIFF in T2-T1ce image pairs, highlighting the potential of the proposed method as a promising solution for MR image fusion in practical applications. Our code will be released at https://github.com/Zhangxw-ustc/SIMFusion.

Web Engineering Methods in Building a Web-Based School Academic Information System

The advancement of computer technology has paved the way for the development of computer-based information systems, significantly enhancing the efficiency and speed of data processing tasks. In educational settings, particularly in secondary vocational schools, there is a pressing need to transition from traditional manual data handling methods to more sophisticated, automated systems. This study focuses on the development of an academic web application aimed at improving the data processing quality in a secondary vocational school where data is currently managed manually using paper and pen.The existing manual method of processing academic data could be more efficient, prone to errors, and susceptible to data loss. This antiquated approach hinders the school's ability to manage academic information effectively, leading to delays and inaccuracies in data reporting and access. There is a clear necessity for a system that can streamline data processing, ensure data security, and provide easy access to information.The method employed to design this academic information system is web engineering. Web engineering combines engineering principles, management practices, and systematic approaches to create high-quality web-based applications. The development process includes several critical activities: formulation, planning, analysis, engineering, page generation, and testing. The system is implemented using PHP and MySQL, which were chosen for their robustness and reliability in web application development.The development and implementation of the academic information system have demonstrated significant improvements in data processing quality. The system allows for efficient, accurate, and secure handling of academic information. It facilitates quick accessto data from any location, enhancing the practicality of data management. Testing confirmed that all system functions met the predefined requirements, ensuring that the application operates as intended. The introduction of this web-based system has effectively addressed the deficiencies of the previous manual method, providing timely and accurate reporting. This improvement has enhanced the services provided to students, teachers, and principals, leveraging modern technology to achieve greater efficiency in educational administration.KeywordsAcademic, MySQL, PHP, System Information, Web engineering

Public relations strategy of Tarumajaya Village in developing promotion and local potentials

Background: The role of the community in introducing, communicating, or promoting Tarumajaya Tourism Village to the wider community outside is vital. Community Information Group (KIM) Cerdas Tarumajaya has a strategic role in connecting local communities with tourism and developing the tourism potential of Tarumajaya Village and the visibility of Tarumajaya as a leading tourist destination. Purpose: This study examined how KIM Cerdas Tarumajaya as public relations implemented strategies to enhance local potential and promote Tarumajaya as a leading tourist destination, and why these strategies were used. Methods: This study used a case study approach. Results: The communication and promotion of Tarumajaya tourism village cover the campaign for Tarumajaya as a whole tourist destination and a highlight for each attraction within the village, such as Situ Cisanti, Kilometre 0 Citarum, Paesan Hill, Pakawa Pine Forest, and Tawides. Every tourism site wants to be communicated and marketed simultaneously. Furthermore, the communication and promotion do not emphasise the differences between one tourist attraction and another. However, regardless of the achievement, the social media management of Tarumajaya Tourism Village is less consistent. Conclusion: Tarumajaya Tourism Village’s communication and promotion lack concentration and consistency. Implications: The success of communication and promotion depends on tourism differentiation, communication messages, and the consistency of information handling.

The Order and Chaos in Human Relationships: Objective Grounds and the Ways of Harmonization

Purpose. This article aims to provide a philosophical analysis of disharmonious relations between people in society, to reveal the causes of existing conflicts and to find ways to reduce the manifestations of chaos in human relations. Theoretical basis of the article is socio-cultural anthropology, the principles of the unity of the historical and logical, the ascent from the abstract to the concrete, the unity of analysis and synthesis. To solve the tasks set, authors also used the principles of objectivity, systematicity, and comprehensive development. Originality. The article goes beyond one-sided views on the relationship between people in society, reveals the causes of existing conflicts from a philosophical perspective and searches for ways to reduce chaosogenic manifestations in society. It is assumed that chaos and order in human relations arise not only due to the contradictory interaction between the fundamental components of the Universe – matter and energy, but also due to a lack of understanding of the laws of information use. Therefore, without the discovery and rational use of the basic laws and principles governing the functioning of information in the Universe, it is impossible to overcome chaos in human relations. Conclusions. Given the profound impact of information on human relations, it is possible to help reduce the manifestations of chaos in human relationships. The proper handling of information, along with the rational use of matter and energy, is crucial for overcoming the current state of disharmony and creating a more favourable and orderly future for humanity. Thus, the vector of harmonisation of human relations lies in the plane of comprehensive knowledge of mass-energy and information processes occurring in the Universe, focusing not on subjective, ill-considered short-term goals, but submitting to them for consistent inclusion in these processes.

Perceptions of Realtors on Property Information Processing: Basis for a Web-Based Real Estate Property Management System

Managing real estate properties efficiently presented challenges due to the complexity of tasks involved, including tenant communication, maintenance scheduling, and financial tracking. Traditional methods often relied on manual processes, leading to inefficiencies, errors, and delays. Motivated by the need for a streamlined solution, this paper introduced a web-based real estate property management system designed to address these challenges. By employing a descriptive research design and utilizing the mixed methodology approach, the study investigates the challenges faced by realtors in managing property information. It also evaluated the current information management systems of each realtor in handling property listing, sales, leases, and rentals. The research findings revealed that 45% of respondents encounter challenges in property information management, primarily related to inefficient handling of sales information and lease agreements. While 72.7% of respondents use real estate software, shortcomings such as a lack of detailed property information and communication issues underline the need for a comprehensive web-based management system meeting various real estate management needs, as preferred by 90.9% of respondents. The results of the study will be used to propose a web-based real estate property management system for the overall efficiency of real estate operations and revolutionize how real estate assets were managed and optimized in digital age