Information To Users Research Articles

Anomaly Detection in Time Series Data

This paper presents a novel unsupervised approach for anomaly detection in marine diesel engines using a Transformer Neural Network based autoencoder (TAE) and residual analysis with Sequential Probability Ratio Test (SPRT) and Sum of Squares of Normalized Residuals (SSNR). This approach adeptly captures temporal dependencies within normal time-series data without the necessity for labeled failure data. To assess the performance of the proposed methodology, a dataset containing faulty data is generated under the same operational profile as the normal training data. The model undergoes training using normal data, after which the faulty data is reconstructed utilizing the trained model. Subsequently, SPRT and SSNR are used to analyze the residuals from the observed and reconstructed faulty data. Significant deviations surpassing a predefined threshold are identified as anomalous behavior. Additionally, this study explores various architectures of Transformer neural networks and other types of neural networks to conduct a comprehensive comparative analysis of the performance of the proposed approach. Insights and recommendations derived from the performance analysis are also presented, offering valuable information for potential users to leverage. The experimental results demonstrate that the proposed approach can accurately and efficiently detect anomalies in marine diesel engines. Therefore, this approach can be considered as a promising solution for early anomaly detection, leading to timely maintenance and repair, and preventing costly downtime. Also, avoid accidents with probability severe consequences.

Information or Noise? Examining the Effect of Discretionary Disclosure of Accounting Estimates on Financial Analyst Forecasts

Whether discretionary disclosure of accounting estimates increases or decreases the decision usefulness of financial information is a fundamental issue in accounting and finance. Our paper speaks to this issue by examining the effect of discretionary disclosure of accounting estimates on the forecasting behaviour of financial analysts, who are sophisticated users of financial information and play a crucial role as an information intermediary in the capital markets. We find that discretionary disclosure of accounting estimates (made in the 10‐K management discussion and analysis and financial statement footnotes) reduces analyst forecast errors and analysts’ tendency to round their annual earnings forecasts. These effects are more pronounced when analysts issue forecasts for companies with high accounting reporting complexity. Overall, the results suggest that discretionary disclosure of accounting estimates reduces information costs by providing relevant information for analysts’ forecasting decisions.

Clinicians' use of Health Information Exchange technologies for medication reconciliation in the U.S. Department of Veterans Affairs: a qualitative analysis.

Medication reconciliation is essential for optimizing medication use. In part to promote effective medication reconciliation, the Department of Veterans Affairs (VA) invested substantial resources in health information exchange (HIE) technologies. The objectives of this qualitative study were to characterize VA clinicians' use of HIE tools for medication reconciliation in their clinical practice and to identify facilitators and barriers. We recruited inpatient and outpatient prescribers (physicians, nurse practitioners, physician assistants) and pharmacists at four geographically distinct VA medical centers for observations and interviews. Participants were observed as they interacted with HIE or medication reconciliation tools during routine work. Participants were interviewed about clinical decision-making pertaining to medication reconciliation and use of HIE tools, and about barriers and facilitators to use of the tools. Qualitative data were analyzed via inductive and deductive approaches using a priori codes. A total of 63 clinicians participated. Over half (58%) were female, and the mean duration of VA clinical experience was 7 (range 0-32) years. Underlying motivators for clinicians seeking data external to their VA medical center were having new patients, current patients receiving care from an external institution, and clinicians' concerns about possible medication discrepancies among institutions. Facilitators for using HIE software were clinicians' familiarity with the HIE software, clinicians' belief that medication information would be available within HIE, and their confidence in the ability to find HIE medication-related data of interest quickly. Six overarching barriers to HIE software use for medication coordination included visual clutter and information overload within the HIE display; challenges with HIE interface navigation; lack of integration between HIE and other electronic health record interfaces, necessitating multiple logins and application switching; concerns with the dependability of HIE medication information; unfamiliarity with HIE tools; and a lack of HIE data from non-VA facilities. This study is believed to be the first to qualitatively characterize clinicians' HIE use with respect to medication reconciliation. Results inform recommendations to optimize HIE use for medication management activities. We expect that healthcare organizations and software vendors will be able to apply the findings to develop more effective and usable HIE information displays.

A Study of digital literacy among the marginalizes in Thailand: Issues, challenges for implementation and the way forward

The concerns about digital literacy in Thailand especially relevant to fake news, disinformation, and misinformation keep increasing and creating a multifaceted challenges to various sectors of Thai society i.e. financial, commercial, politics, society, and health-related. Among the areas identified include digital contents creation, dissemination, and social media enabling various information with complex challenges such as the proliferation of fake news, disinformation, and misinformation affected more kinds of negative effects currently. This study employs mixed-research method quantitative (survey questionnaire) and qualitative (Focus group discussion, observation, interview) data collection and analysis. A total of 315 samples and key informants were involved as well as grouped under 5 categories: marginal youths, elderly, community leaders, teachers, also government workers focusing on digital literacy knowledge and skills relevant to fake news. It also highlights the relevant contexts i.e. regulatory frameworks and mechanisms driven by key agencies in Thailand. Two main results were revealed that reflected the objectives of the study accordingly: The first objective is (1) overview of digital literacy and how to achieve it. The findings summarized from survey questionnaire include 1.1) even regulations exist found inadequate enforcement and low public awareness call for more effective and collaborative communication from all partners starting from the government agencies; 1.2) urgent need for public awareness communication campaigns emphasizing all the marginalized groups. Youths expressed in the interviews about their contribution to help reduce all kinds of fake news; 1.3) support more friendly ICT context provision such as availability, affordability, accessibility, usability, and useful information. The second objective is (2) mechanism for digital skills empowerment. The feedback from key informants include: 2.1) strengthening digital literacy skills among all marginalized groups to be a smart citizen then can help protecting themselves, their families and their communities; 2.2) all agencies from policy to local i.e. community leaders, educational institutions, private sectors, social media companies, civil society, and others must synergized more contributions; 2.3) educational institutions must design digital literacy academy with digital new-skills for the marginalizes, ensuring them for their safety and future job demands; 2.4) private sectors should support and co-designing digital products and services that address all current needs; 2.5) local government, and all partners should take an active collaboration and enforcement. The study concluded with implications and suggestions for future research in line with SDGs.

Development and validation of an instrument to evaluate the perspective of using the electronic health record in a hospital setting

BackgroundEvaluating healthcare information systems, such as the Electronic Health Records (EHR), is both challenging and essential, especially in resource-limited countries. This study aims to psychometrically develop and validate an instrument (questionnaire) to assess the factors influencing the successful adoption of the EHR system by healthcare professionals in Moroccan university hospitals.MethodsThe questionnaire validation process occurred in two main stages. Initially, data collected from a pilot sample of 164 participants underwent analysis using exploratory factor analysis (EFA) to evaluate the validity and reliability of the retained factor structure. Subsequently, the validity of the overall measurement model was confirmed using confirmatory factor analysis (CFA) in a sample of 368 healthcare professionals.ResultsThe structure of the modified HOT-fit model, comprising seven constructs (System Quality, Information Quality, Information technology Service Quality, User Satisfaction, Organization, Environment, and Clinical Performance), was confirmed through confirmatory factor analysis. Absolute, incremental, and parsimonious fit indices all indicated an appropriate level of acceptability, affirming the robustness of the measurement model. Additionally, the instrument demonstrated adequate reliability and convergent validity, with composite reliability values ranging from 0.75 to 0.89 and average variance extracted (AVE) values ranging from 0.51 to 0.63. Furthermore, the square roots of AVE values exceeded the correlations between different pairs of constructs, and the heterotrait-monotrait ratio of correlations (HTMT) was below 0.85, confirming suitable discriminant validity.ConclusionsThe resulting instrument, due to its rigorous development and validation process, can serve as a reliable and valid tool for assessing the success of information technologies in similar contexts.

Exploring Instructors' Experiences with Learning Management Systems: A Technological Perspective on User Satisfaction in Distance Learning

The rapid growth of educational technology in higher education has led to the widespread use of Learning Management Systems (LMS) in distance learning. However, limited research has focused on measuring instructors' satisfaction with these systems, despite its critical role in course engagement and enhancing student interaction with course content. This study proposes a comprehensive framework for evaluating instructors' satisfaction with LMS usage. Thus; We adopted DeLone and McLean's Information System Success Model to empirically assess the relationships between Information Quality (INQ), System Quality (SYQ), Service Quality (SQ), Perceived Usefulness (PU), User Loyalty (UL), and User Satisfaction (US). The results indicate that SQ has a greater effect on the US than SYQ, PU, and INQ. Moreover, the results show that the US has a significant direct influence on UL. The study focuses on higher education instructors and employs a questionnaire-based survey for data collection. Based on the results, it is recommended that LMS design should consider the needs of both instructors and students, incorporating the latest technological advancements. Neglecting instructors' satisfaction in LMS development could negatively influence the outcomes of distance learning courses.

Experimental insights on sound characteristics and psychoacoustic parameters on axial fan performance in heat pump systems

This study focuses on the computational fluid dynamics (CFD) simulations and experimental measurements of the sound power level of an axial fan used in heat pump systems. Calculations and experiments were systematically conducted for three different fan-evaporator distances. CFD results, including kinetic energy and velocity vector values, were obtained and compared with experimental sound power results. The relationships obtained were thoroughly examined in terms of their impact on psychoacoustic parameters. This study was conducted to contribute to the understanding of fan performance and sound characteristics in heat pump systems. The results provide crucial information for users aiming to reduce air-source noise and determine optimized fan-evaporator distances for acoustic comfort.

E-Waste Management Practices Through the Eyes of Responsible Departments at Malaysian Public Universities

Electronic and electrical waste (E-waste) has been identified as the fastest-growing waste stream in the world. In Malaysia, forecasts indicate that it will soon reach 24.5 million units of e-waste by the year 2025. Today, higher learning institutions also contribute to the rapidly growing threat of e-waste. Besides mobile phones, the usage of Information and Communication Technology (ICT) equipment at universities keeps increasing and contributes to the increased quantity of e-waste, while the handling and disposal methods of e-waste still need to be improved. The purpose of this paper is to examine the current e-waste management system as well as to investigate the critical challenges constraining e-waste management at public universities in Malaysia. By using a qualitative approach, a number of interview sessions have been conducted with the responsible departments at six established public universities in Malaysia. It has been found that currently only e-waste generated from used electric and electronic equipment (EEE) which have been declared as university assets are being managed by the responsible departments at the six universities. All six universities are using the standard process of handling their e-waste since every single process needs to comply with the requirements of the Ministry of Finance (MOF). This remains the main constraint to flexibility or improvement of the current system. The universities are also facing some challenges, among others, lack of awareness and knowledge on how to properly handle e-waste among university citizens, no clear sustainable policy at the university, lack of facilities within the university compound to support the proper practice of e-waste disposal as well as lack of education and related training provided to the campus citizens. This paper also provides some recommendations for the improvement of e-waste management towards sustainability and offers an agenda for future research.

Standardized research on multifunctional beacon multi-sensor data acquisition and transmission

Abstract This paper discusses the research on the standardization of data acquisition and transmission for multifunctional beacon systems. The multifunctional beacon system integrates various types of sensing devices and can provide real-time, comprehensive and accurate marine environment and navigation information for ships and shore-based users. However, the system currently faces challenges such as non-uniform data formats and communication protocols, low hardware standardization and integration, and data and network security risks. In order to solve these problems, this paper puts forward the solution of “standard terminal for data acquisition and transmission”, which achieves the compatibility of equipment interface, unified data format, and reliable information security. It lays the foundation for the standardization of multi-purpose beacon system. Through modular design and standardized packaging, the performance, reliability and efficiency of the hardware of multi-purpose beacons are improved, the development and maintenance costs are reduced, and the flexibility of the system is enhanced. The “Standard Terminal for Data Acquisition and Transmission” is applied to the multi-purpose beacon system, and interfaces and integrates with the existing “Operation Management System for Navigation Guarantee” to realize a unified platform for multi-purpose beacons. This research helps to promote the formulation of multi-purpose beacon data format and communication protocol standards at the national or industrial level, provides important reference for the formulation of international standards, and is of great significance in promoting the standardized development and application promotion of multi-purpose beacon technology.

The Evolution Of International Financial Reporting Standards (IFRS) And Its Impact On Global Business Practices

The International Financial Reporting Standards (IFRS) have undergone significant evolution over the years, shaping the financial reporting on a global scale. The journey of IFRS began with the establishment of the International Accounting Standards Committee (IASC) in 1973, which laid the foundation for international accounting harmonization. Over time, the IASC transformed into the International Accounting Standards Board (IASB), which took on the responsibility of developing and issuing IFRS. The adoption of IFRS has become increasingly widespread, with many countries around the world either adopting the standards outright or converging their national standards with IFRS. One of the primary objectives of IFRS is to enhance the comparability, transparency, and reliability of financial reporting across borders. By providing a common set of accounting principles, IFRS facilitates better communication and understanding among stakeholders, including investors, creditors, regulators and other users of financial information. This standardization promotes efficiency in capital markets and encourages cross-border or cross-nation investment and business activities. IFRS is characterized by its principles-based approach, which emphasizes substance over form and allows for greater flexibility in financial reporting. Unlike rules-based standards, which prescribe specific treatments for various transactions, principles-based standards provide a framework for judgment, allowing preparers to alter their financial statements to reflect the economic reality of their transactions. The impact of IFRS extends beyond financial reporting to areas such as taxation, auditing, and regulatory compliance. While the adoption of IFRS has brought many benefits, it has also presented challenges for companies and regulators alike. The evolution of IFRS has had a profound impact on global business practices, promoting greater transparency, comparability, and efficiency in financial reporting. Through an examination of the evolution of IFRS, this research contributes to a deeper understanding of its profound influence on global business practices

Evaluating and Enhancing Canvas Course Website: Prioritizing User‐Centered Design

ABSTRACTCanvas, a learning management system (LMS), has been widely adopted by academic institutions across North America. Despite its robust features, the user experience with Canvas varies significantly. This study examines the design of a Canvas course website, providing evidence‐based guidance for creating user‐centered LMS interfaces. The findings aim to enhance the user experience by addressing issues such as information overload, user control, and accessibility. Design principles and recommendations generated from this study are crucial for our institution‐wide adoption of Canvas, promoting a seamless and supportive learning environment.

Empowering Users with ChatGPT and Similar Large Language Models (LLMs): Everyday Information Needs, Uses, and Gratification

ABSTRACTDisruptive technologies such as ChatGPT and similar Large Language Models (LLMs) have transformed mundane everyday tasks of information users since their debut in late 2022. In this study, we leverage uses and gratifications theory to test a distinct set of motivations that drive users' satisfaction and continued use intentions of ChatGPT and similar large language models. Data were collected using a national online survey of 323 adults residing in the United States. We conducted data analysis using Partial Least Squares (PLS‐SEM) to investigate both direct and indirect impact of factors on users' gratification, thereby influencing the continued utilization of these tools for everyday information seeking. Results show four motivational factors ‐ social influence, trust, personalization, and perceived usefulness ‐ that positively influence users' satisfaction or sense of gratification, impacting their intentions to continue using these tools. This is one of the few early studies of ChatGPT and other LLMs from an information science perspective.

From Fandom to Fadeaway: Unpacking Factors Contributing to Anime Dropout

ABSTRACTThis study explores a case of anime dropout/disengagement to understand media information users. Particularly, this study identifies elements in anime (e.g., Tropes) that prevent audience from continue watching what they had started (i.e., dropout/disengagement). A content analysis of 226 posts from MyAnimeList.net, an online anime database and fan community, suggests that the major elements that motivate audience dropout are Plot/Narrative, Tropes, Artwork/Visual Style, Characters, and Mood. The expectation gap and sunk cost also contribute to disengagement. This study presents a way to enrich anime metadata through analyzing the identified elements. Additionally, this study suggests that understanding anime disengagement may contribute to the search and recommendation of anime.

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

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

Development of a T2D App for Elderly Users: Participatory Design Study via Heuristic Evaluation and Usability Testing

Diabetes management applications effectively help patients monitor blood glucose levels and adjust diet and exercise plans. However, most diabetes management apps, including the SugarShift application developed in 2023, use generalized designs that often fail to consider the unique cognitive and physiological characteristics of elderly users, thereby impacting their acceptance and usage. This paper proposes an enhancement for the SugarShift application by introducing a mode specifically designed for elderly users. This proposed enhancement aims to directly involve elderly patients so as to meet their needs better through a participatory design approach. A heuristic evaluation conducted with six experts identified 126 usability issues and 179 heuristic violations in the current version, which has led to the recommendation to develop optimization strategies tailored for elderly users. Subsequent usability testing with 28 elderly patients and six experts emphasized the importance of interface simplicity, logical operation, and interaction quality in enhancing user experience. These factors improve usability, facilitate information processing, and reduce cognitive load. Despite the overall usability of SUS scores, significant challenges still need to be addressed in information display, system feedback, and user interaction. Recommendations for future enhancements include simplifying data entry and presentation, improving readability, and providing timely feedback to enhance usability and user satisfaction, ultimately increasing user retention.

Enhancing Recommendation Diversity and Novelty with Bi-LSTM and Mean Shift Clustering

In the digital age, personalized recommendation systems have become crucial for information dissemination and user experience. While traditional systems focus on accuracy, they often overlook diversity, novelty, and serendipity. This study introduces an innovative recommendation system model, Time-based Outlier Aware Recommender (TOAR), designed to address the challenges of content homogenization and information bubbles in personalized recommendations. TOAR integrates Neural Matrix Factorization (NeuMF), Bidirectional Long Short-Term Memory Networks (Bi-LSTM), and Mean Shift clustering to enhance recommendation accuracy, novelty, and diversity. The model analyzes temporal dynamics of user behavior and facilitates cross-domain knowledge exchange through feature sharing and transfer learning mechanisms. By incorporating an attention mechanism and unsupervised clustering, TOAR effectively captures important time-series information and ensures recommendation diversity. Experimental results on a news recommendation dataset demonstrate TOAR’s superior performance across multiple metrics, including AUC, precision, NDCG, and novelty, compared to traditional and deep learning-based recommendation models. This research provides a foundation for developing more intelligent and personalized recommendation services that balance accuracy with content diversity.

Friend2User : A new CNN based method for user network and content embedding

Nowadays, social networks have become an integral part of modern society, significantly influencing individuals worldwide due to their extensive reach. Consequently, analyzing the data disseminated within these networks in order to identify online communities presents a major challenge for researchers in the data mining field. To address this challenge, we propose, in this paper, a novel deep user embedding framework for community extraction on social networks. Our method leverages the capability of Convolutional Neural Networks (CNNs) to produce abstract representations of users that preserve the semantic information in the data. Specifically, our approach considers both the profile content and the network structure, harnessing the power of unsupervised CNNs. The key concept underlying our proposal is that each user is represented not only by their own content but also by the content of their close friends. We employ a recursive CNN to integrate neighboring users’ content, thereby generating concise and informative user embeddings. The empirical findings obtained by our method demonstrate the effectiveness of our proposed user embeddings in efficiently detecting communities within social networks, particularly in the context of cybersecurity.

GNNRI: detecting anomalous social network users through heterogeneous information networks and user relevance exploration

GNNRI: detecting anomalous social network users through heterogeneous information networks and user relevance exploration

Optimising the review of electronic monitoring information for management of commercial fisheries

Electronic monitoring (EM) systems incorporating cameras and other devices can collect a broad range of data to support fisheries management. We reviewed the data collection capabilities of EM and considered approaches to increasing efficiency, including cost effectiveness, of EM review. EM can provide information on catch, effort, catch handling, bycatch mitigation, fishing gear and operational data, which are relevant for fisheries management including by Regional Fisheries Management Organisations (RFMOs). Methods to increase efficiency and decrease costs of EM review apply from the programme design phase, through data collection and review. At review, costs may be reduced by sampling imagery optimally to meet monitoring objectives. Considering RFMOs as users of EM-collected information, we applied EMoptim, an open-source simulation model developed in R that estimates the amount of EM review necessary to meet one or more user-specified monitoring objectives. EMoptim uses stratification to increase review efficiency and incorporates a function to explore review costs against the monitoring objectives set. We evaluated the amount of EM review needed to estimate catch with specified precision, using fishery data available from the Western and Central Pacific Fisheries Commission. Model outputs show that EM review requirements increase as catch frequency decreases, dispersion of catch events increases, and when more precise catch estimates are required. Geographical stratification reduced the amount of review required for more commonly caught species and when catch events were focused in a limited area. Optimising review rates across multiple monitoring objectives was most effective for more commonly caught species. We highlight opportunities for future use and development of this prototype modelling package.

Adaptation of Parallax Scrolling Effect Technique in LegitCheck Website Interface Development

This research focuses on developing LegitCheck's website interface by applying the Parallax Scrolling Effect technique, which is considered as a potential solution to support the startup's promotional strategy. LegitCheck, as a startup that needs an effective way to introduce its services and business concept to consumers and brands, requires a website that can serve as an attractive promotional medium as well as a comprehensive information center. The purpose of this research is to examine the effectiveness of the Parallax Scrolling Effect technique compared to a website without the effect in increasing the effectiveness of the LegitCheck website as a promotional tool. The research method used includes the design and implementation of the Parallax Scrolling Effect technique on the LegitCheck website, followed by evaluation using the A/B testing method. The results showed that the implementation of the Parallax Scrolling Effect technique provided significant benefits, including improved information accuracy, service quality, user satisfaction, and company net profit. Although there are constraints related to page loading speed, the majority of respondents prefer websites with Parallax Scrolling Effect because it provides a more interactive and engaging experience. The implication of this study is that the use of Parallax Scrolling Effect can be an effective strategy for startups such as LegitCheck to increase interaction with users, strengthen brand image, and increase the effectiveness of the website as a promotional tool, although it is necessary to pay attention to technical aspects such as page loading speed to minimize potential disruptions to the user experience.