Information To Users Research Articles

INVESTORS' INTEREST IN THE REGULATORY EFFECT OF CASH FLOWS ON EXTREME CORPORATE SOCIAL RESPONSIBILITY

Today, information users are interested in disclosing non-financial information regarding activities carried out within the scope of corporate social responsibility (CSR). In this context, the reflection of CSR activities, which can increase company reputation and stakeholder interest, on financial performance is important. The research aims to determine the relationship of cash flows with firm value at optimal and extreme CSR levels. The research uses data on companies with ESG scores in Turkey to determine the impact of CSR activities on firm value. The research applies panel data analysis to determine the impact of optimal and extreme CSR activities on firm value. The research points out that optimal CSR levels have a negative effect on firm value, while extreme CSR levels have a positive and significant effect. Additionally, the results reveal that cash flows positively moderate the relationship between extreme CSR levels and firm value. The research findings support that cash flows positively moderate the relationship between firm value and CSR at extreme levels. The research emphasizes the mediating role of cash flows by distinguishing between extreme and optimal CSR activities, in line with the literature on the relationship between CSR levels and firm value.

Secure beamforming design for MISO URLLC networks in IoT applications

This paper investigates joint beamforming and artificial noise (AN) design for secure multiple-input single-output (MISO) ultra-reliable and low latency communication (URLLC) networks in Internet of Things (IoT) applications. In considered system, a base station (BS) transmits confidential information for individual IoT users using the short-packet communication technique under the wiretap of eavesdroppers. To enhance physical layer security, the BS injects additional dedicated AN symbols to degrade the information retrieval ability at eavesdroppers. In this paper, we aim to joint design the transmit beamforming and AN symbol to maximize the minimum URLLC secrecy rate of IoT user subject to the power budget of the BS. The optimization design problem is highly nonconvex due to coupled variables in the URLLC secrecy rate and channel dispersion expressions, and thus it is mathematically challenging to solve this problem directly. To overcome this issue, we first introduce various convex inner approximations to convexify the nonconvex terms, and then we develop an efficient iterative algorithm based on the sequential convex programming approach. Extensive numerical simulation results are conducted to investigate the URLLC secrecy rate region. In conclusion, the two new URLLC parameters, i.e., the transmit packet blocklength and block error probability, will cause the considerable degradation on the URLLC secrecy rate region when comparing to that of the traditional beamforming design based on the Shannon capacity.

Data Lake, Data Warehouse, Datamart, and Feature Store: Their Contributions to the Complete Data Reuse Pipeline.

The growing adoption and use of health information technology has generated a wealth of clinical data in electronic format, offering opportunities for data reuse beyond direct patient care. However, as data are distributed across multiple software, it becomes challenging to cross-reference information between sources due to differences in formats, vocabularies, and technologies and the absence of common identifiers among software. To address these challenges, hospitals have adopted data warehouses to consolidate and standardize these data for research. Additionally, as a complement or alternative, data lakes store both source data and metadata in a detailed and unprocessed format, empowering exploration, manipulation, and adaptation of the data to meet specific analytical needs. Subsequently, datamarts are used to further refine data into usable information tailored to specific research questions. However, for efficient analysis, a feature store is essential to pivot and denormalize the data, simplifying queries. In conclusion, while data warehouses are crucial, data lakes, datamarts, and feature stores play essential and complementary roles in facilitating data reuse for research and analysis in health care.

Securing Anomaly Detection for Process-Based Time Series

Widespread innovation from artificial intelligence and machine learning (AI/ML) tools presents a lucrative opportunity for the nuclear industry to improve state-of-the-art analyses (e.g. condition monitoring, remote operation, etc.) due to increased data visibility. In recent years, the risk posed by collaborative data exchange has received increased attention due, in part, to a potential adversary’s ability to reverse-engineer intercepted data using domain knowledge and AI/ML tools. While the efficacy of typical encryption has been proven during passive communication and data storage, collaborative exchange typically requires decryption for extended analyses by a third-party, which poses an intrinsic risk due to these trustworthiness concerns. The directed infusion of data (DIOD) 1 1 A.Al Rashdan and H.Abdel-Khalik, Deceptive Infusion of Data, Non-Provisional Patent, Application No. 63/227,389, September 2022. paradigm presented in this paper discusses a novel data masking technique that relies on preserving the usable information of proprietary data while concealing its identity via reduced-order modeling. In contrast to existing state-of-the-art data masking methods, DIOD does not impose limiting assumptions, computational overheads, or induced uncertainties, thereby allowing for secure and flexible data-level security that does not alter the inferential content of the data. This paper focuses on the application of DIOD to a process-based simulation wherein a leaking reservoir with a controlled inlet pump is simulated under various experimental conditions with the goal of producing masked data that preserve the information given by anomalies. These experiments included the injection of statistically significant anomalies, subtle anomalies that occurred over an extended period, and the addition of several independent anomalous states. Each experiment showed that a classifier will identify the same anomalies whether it analyzes the original or masked data. An additional experiment also tested the case of corrupted labeling information wherein labels were arbitrarily randomized, and the loss in labeling accuracy was about the same for both datasets. Each of these experiments show that data obfuscated by DIOD may be utilized in the place of real data for a variety of condition monitoring scenarios with no loss in performance.

Climate change beliefs and behaviours: Data collected from 30-year-old offspring and their parents in the Avon Longitudinal Study of Parents and Children (ALSPAC)

Climate change is causing a suite of environmental and social issues. Understanding patterns of climate change beliefs and behaviours, and the factors which shape these attitudes and actions, is therefore essential. This data note describes the novel data collection of climate belief and behaviour questions embedded within the Avon Longitudinal Study of Parents and Children (ALSPAC), a longitudinal population-based birth cohort in southwest England. Two generations of ALSPAC participants completed the questionnaires containing these climate questions: the Generation-1 (G1) offspring (n=4,341), Generation-0 (G0) mothers (n=4,793), and the G0 mother’s partners (n=2,111). The questions asked about: belief in climate change; concern over climate change; whether climate change is caused by human activity; whether individual behaviours can impact climate change; the impacts of climate change in the participants’ local area; and whether participants were engaging in any of 17 pro-environmental behaviours (e.g., recycling more, reducing meat/dairy consumption) for climate change and/or other reasons. The majority of participants believed the climate was definitely changing (~80%), were somewhat or very concerned about climate change (~90%) and attributed most or all of climate change to human activity (~75%), with only small differences between the generations. On average, participants reported engaging in between 5 and 6 actions because of concerns regarding climate change (5.8 in G0 mothers; 5.2 in G1 offspring and G0 partners). Associations with sociodemographic factors (e.g., age, sex, ethnicity and socioeconomic background) were relatively weak, but positive relationships between highest level of education and greater climate change belief, concern and behaviours were evident. Increased climate belief and concern also predicted engaging in more pro-environmental actions. Responses to these climate questions were more similar within-families. This data note provides important information for future users of these data, as well as discussing some of the key strengths, limitations and considerations for data users.

Debt Accounting System Analysis in Accounting Information Systems

The Debt Information System and Accounting Information System support and collaborate with each other to ensure that the company's financial information is well managed, regulatory compliance is maintained, and the right business decisions can be taken. This research uses a literature study method with the data used is secondary data. The research results show that the Debt Accounting System and the Accounting Information System are interrelated in processing and producing financial reports, especially in this case company debt. This is also supported by the sophistication of information technology, user capabilities, user participation, and top management support.

Enhancing Database Query Performance: Analysis of Indexing Techniques

The need to enhance query performance in databases within the contemporary information environment is crucial for ensuring efficient operations across various domains. This paper is dedicated to an analysis of database indexing techniques aimed at understanding their impact on query performance and efficiency. It meticulously examines various types of indexes, including B-trees, hash tables, and textual indexes, analyzing their advantages and limitations. The investigation into the influence of these techniques on query execution time reveals that performance depends on various factors such as query complexity and data volume. Special attention is given to selecting the optimal index type based on specific database needs and characteristics. The research underscores the importance of considering data volume and database structure in choosing effective indexing methods. Additionally, the advantages and disadvantages of different indexing techniques are scrutinized, taking into account their impact on query execution speed and efficiency. Of the study indicate that the correct selection and utilization of appropriate indexing strategies can significantly enhance the performance of database management systems, providing swift and efficient access to information for users. Ultimately, this work makes a significant contribution to understanding and practically applying indexing techniques to improve query performance in databases.

An Indigenous-informed scoping review study methodology: advancing the science of scoping reviews

BackgroundHistorically, Indigenous voices have been silent in health research, reflective of colonial academic institutions that privilege Western ways of knowing. However, Indigenous methodologies and methods with an emphasis on the active involvement of Indigenous peoples and centering Indigenous voices are gaining traction in health education and research. In this paper, we map each phase of our scoping review process and weave Indigenous research methodologies into Arksey and O’Malley’s (2005) framework for conducting scoping reviews.MethodsGuided by an advisory circle consisting of Indigenous Knowledge Keepers and allied scholars, we utilized both Indigenous and Western methods to conduct a scoping review. As such, a circle of Knowledge Keepers provided guidance and informed our work, while our methods of searching and scoping the literature remained consistent with PRISMA-ScR guidelines. In keeping with an Indigenous methodology, the scoping review protocol was not registered allowing for an organic development of the research process.ResultsWe built upon Arksey and O’Malley’s 5-stages and added an additional 3 steps for a combined 8-stage model to guide our research: (1) Exploration and Listening, (2) Doing the Groundwork, (3) Identifying and Refining the Research Question, (4) Identifying Relevant Studies, (5) Study Selection, (6) Mapping Data, (7) Collating, Summarizing and Synthesizing the Data, and lastly, (8) Sharing and Making Meaning. Engagement and listening, corresponding to Arksey and O’Malley (2005)’s optional “consultation stage,” was embedded throughout, but with greater intensity in stages 1 and 8.ConclusionAn Indigenous approach to conducting a scoping review includes forming a team with a wide array of experience in both Indigenous and Western methodologies, meaningful Indigenous representation, and inclusion of Indigenous perspectives to shape the analysis and presentation of findings. Engaging Indigenous peoples throughout the entire research process, listening, and including Indigenous voices and perspectives is vital in reconciliation research, producing both credible and useable information for both Indigenous communities and academia. Our Indigenous methodology for conducting a scoping review can serve as a valuable framework for summarizing Indigenous health-related research.

МОДЕЛИРОВАНИЕ НАРУШИТЕЛЯ, ИНФРАСТРУКТУРЫ И АТАК В СИСТЕМАХ ИНФОРМАЦИОННОЙ БЕЗОПАСНОСТИ

Formal models of subjects, infrastructure and attacks for information security systems are proposed. The models include descriptions of information security operators, administrators, users and violators, taking into account their knowledge, qualifications and initial conditions. A comprehensive intruder model is presented, including initial knowledge and access rights, initial location, qualifications and goals. Infrastructure models, vulnerabilities, and information collection methods are also considered, which makes it possible to more accurately predict the behavior of violators and develop effective protection strategies. The results of the study show that the proposed models significantly improve the accuracy of risk assessment and security planning, which is especially important for mission-critical information systems. The practical significance lies in the possibility of using models to develop and improve information network security systems. The results of the practical implementation of the model on real data are also presented.

How much does reclaimed wastewater cost? A comprehensive analysis for irrigation uses in the European Mediterranean context

ABSTRACT The new European Union regulation on the minimum requirements for the use of reclaimed water for irrigation entered into force in June 2023, thereby imposing concerns regarding the costs of this non-conventional resource for potential users in the context of increasing water scarcity in the Mediterranean region. This research offers a comprehensive cost assessment of reclaimed water production based on the financial information gathered from wastewater treatment plants located on the Mediterranean coast of Andalusia (Southern Spain). The results offer valuable information for policy-makers, water operators, and potential users to assess the economic viability of utilising reclaimed water as an alternative source to scarce conventional resources.

Analisis Keberhasilan Sistem Informasi Sentuh Tanahku Badan Pertanahan Nasional Menggunakan Metode ISSM

The use and usefulness of information technology is an important issue in today's life. This can be seen as a way of using technology to support human activities in various sectors or fields, including government and user security. Of course, the use and usefulness of information technology in various agencies is very necessary to support the implementation of better government programs. The use and utilization of technology in the government environment can be carried out with the help of a research information system. Research is located at two government information agencies: Lubuk-Linggau City National Land Agency; The information system used by the National Land Agency is called Touch My Land based on Android. The implementation of an information system is said to be successful if it can be proven that the information system produces significant positive impacts or benefits for some of its users. The DeLone and McLean evaluation concept is considered a successful information system model. The research method used in this research is a quantitative method with a sample size as many as 61 people from National Land Agency. This research uses six variables and nine hypotheses. The sixth variable consists of information quality, system quality, service quality, usage intention, user satisfaction and net profit. The research results show that several research hypotheses are accepted because the t-statistic value is greater than 1.96.

Weakly Supervised Deep Embedding for Product Review Sentiment Analysis

Online reviews have become an important source of information for users before making an informed purchase decision. Early reviews of a product tend to have a high impact on the subsequent product sales. In this project, we take the initiative to study the behavior characteristics of early reviewers through their posted reviews on two real-world large e-commerce platforms, i.e., Amazon and Yelp. In specific, we divide product lifetime into three consecutive stages, namely early, majority and laggards. A user who has posted a review in the early stage is considered as an early reviewer. We quantitatively characterize early reviewers based on their rating behaviors, the helpfulness scores received from others and the correlation of their reviews with product popularity. We have found that (1) an early reviewer tends to assign a higher average rating score; and (2) an early reviewer tends to post more helpful reviews. Our analysis of product reviews also indicates that early reviewers’ ratings and their received helpfulness scores are likely to influence product popularity. By viewing review posting process as a multiplayer competition game, we propose a novel margin-based embedding model for early reviewer prediction. Extensive experiments on two different e-commerce datasets have shown that our proposed approach outperforms a number of competitive baselines. In our project we have used algorithms like Decision Tree (DT) and Multi Layer Perceptron (MLP). All are measured in terms of accuracy

A Comparison of Using Multiple Choice and Cloze Tests on Students’ Achievement in Reading Comprehension at Second Semester of English Department of FKIP Batanghari University

The purpose of the study was to find out the comparative achievement of multiple choice test and bracket test in reading comprehension in the second semester of the department of english, University of FKIP Batanghari. This study used a mixed method approach. The subject of the test would be second semester english students of FKIP Batanghari University. Data was collected through two instruments, which were a test and an interview. Based on the results of this study, the author found that students scored higher in the cloze test than in the multiple choice test. The result of the interview showed that the students preferred to answer the question in the cloze test than in the multiple choice question because they were easier to understand. These perceptions confirm the differences in student scores on the first research question. However, the result also showed that the multiple choice test is a better measure of students' reading comprehension. The students' impressions and opinions about the tests and their own performance were recorded and considered. Implications of results and recommendations further research is needed to obtain detailed and usable information to improve students' reading comprehension and achievement in the future.

Development of a Cloud-Based Building Information Modeling Design Configurator to Auto-Link Material Catalogs with Code-Compliant Designs of Residential Buildings

Configurators have recently emerged as essential tools in the construction industry to enable builders to offer a wide range of customizable designs. Due to significant challenges in information integration between construction suppliers and clients, existing configurator systems often lack crucial usability and supply chain information, presenting barriers to wider adoption among residential communities, especially in single-family residence development that requires a high degree of customization. To address this challenge in the design and construction supply chain, this study presents a lightweight cloud-based modular home configuration methodology as a robust unified platform solution to integrate parametric design options with a certified kit-of-parts library to meet local design codes. The configurator prototype developed under this framework seamlessly integrates essential design and supply chain information by leveraging (1) a generative layout design with pre-approved blueprints, (2) a knowledge-based recommender system to link the design process with certified material catalogs, and (3) a user-friendly web interface to present possible designs. The implementation of a single-family housing design adhering to the building codes in the British Columbia Province of Canada illustrates the benefits of the proposed configurator functionalities and efficient supplier data integration. Lightweight and automated, the proposed configurator has substantial potential to be scaled and adopted across different communities.

Natural noise management in collaborative recommender systems over time-related information

Recommender systems are currently a suitable alternative for providing easy and appropriate access to information for users in today’s digital information-overloaded world. However, an important drawback of these systems is the inconsistent behavior of users in providing item preferences. To address this issue, several natural noise management (NNM) approaches have been proposed, which positively influence recommendation accuracy. However, a major limitation of such previous works is the disregarding of the time-related information coupled to the rating data in RSs. Based on this motivation, this paper proposes two novel methods, named SeqNNM and SeqNNM-p for NNM focused on an incremental, time-aware recommender system scenario that has not yet been considered, by performing a classification-based NNM over specific preference sequences, driven by their associated timestamps. Such methods have been evaluated by simulating a real-time scenario and using metrics such as mean absolute error, root-mean-square error, precision, recall, NDCG, number of modified ratings, and running time. The obtained experimental results show that in the used settings, it is possible to achieve better recommendation accuracy with a low intrusion degree. Furthermore, the main innovation associated with the overall contribution is the screening of natural noise management approaches to be used on specific preferences subsets, and not over the whole dataset as discussed by previous authors. These proposed approaches allow the use of natural noise management in large datasets, in which it would be very difficult to correct the entire data.

A contextual approach to estimate household activities in instrumented dwellings

Occupants and their activities are important in computer-aided systems such as energy management or energy simulation in residential buildings. Numerous studies have extensively examined detailed household activities at the population level using time-use surveys. Despite the considerable influence of contexts on occupants' activities, a limited number of studies focus on individual households due to the constraints imposed by private policies on collecting occupants' activities. This article proposes an approach to detect detailed occupants' activities (e.g., cooking, entertaining) based on measurements in specific households. Firstly, a camera-free mobile application is proposed to support the data collection process due to the restriction of cameras. Then, relevant features are determined for each activity. Finally, Bayesian networks were built to represent human-understandable relationships between determined features and related activities. An instrumented dwelling with five individuals is tested, and a 4-month dataset is used to evaluate the model quality. Results show that the model can estimate most of the studied activities (e.g., cooking, washing dishes) with a F1-score between 0.77 and 0.92. The approach is better than the statistical approach with time-use surveys in building household activity profiles, which is important in energy simulation and verification. In addition, this approach is replicable for different households, providing them with context-specific and highly useable information to enhance smart energy management systems and occupants’ energy behavior.

Cascade or updown sliding: the influence of interactive interface of short video app on information processing and user experience

Cascade or updown sliding: the influence of interactive interface of short video app on information processing and user experience

Hubungan Kualitas Informasi Terhadap Kepuasan Pengguna Layanan Rekam Medis Elektronik (RME) di Rawat Jalan RSU Queen Latifa Yogyakarta

Introduction: The application of electronic medical records is increasing in developing countries, including Indonesia. Electronic medical records are increasingly being implemented in hospitals to achieve improved service quality. The increasing number of hospital investments in information systems indicates that hospitals understand the importance of end-user and system-user satisfaction. User satisfaction is one way to determine the effectiveness and success of an information system. Research explains that information quality influences user satisfaction. Research objective: to determine the relationship between information quality and user satisfaction with electronic medical record services at outpatient hospital Queen Latifa Yogyakarta. Research Method: this research is quantitative. The population is officers who input medical record data into Sitiql (electronic medical records). The sampling technique uses accidental sampling. The sample was 81 people. The data collection technique uses a questionnaire. Data analysis uses Spearman rank. Research results: explain that the p-value is 0,596, namely that there is no relationship between the quality of information and the satisfaction of users of electronic medical record services at RSU Queen Latifa Yogyakarta. Conclusion: Information quality cannot increase user satisfaction with electronic medical record services at RSU Queen Latifa Yogyakarta.

THE ROLE OF ESG BUSINESS REPORTING IN WATER MANAGEMENT

The rational use of water resources by business structures requires the development of appropriate strategies and their adherence to the chosen policy in terms of management of these objects: drawing up programs and plans, introducing environmental protection actions, displaying the economic effect and documenting all transactions, minimizing negative impacts on the environment and presentation of the positive and negative consequences of the use of natural resources in the format of ESG reporting, which discloses information about the activities of companies in the field of Environmental aspects, Social responsibility and Corporate Governance. This practice positions companies as an active participant in sustainable development and allows them to increase their own ratings, which makes it possible to have advantages in attracting investments and targeted financing, increasing one's own competitiveness due to improved trust in such companies, etc. Improving the quality of information in ESG reporting on water resources management and related processes allows stakeholders to receive complete and reliable information when making management decisions. On the basis of the study of ESG reporting of 8 corporations from Ukraine in terms of the use of water resources during the implementation of the strategy of sustainable development, positive and problematic practices of companies were identified when preparing the necessary data for reporting. During this analysis, the experience and legislative guidelines on the exploitation of water resources and the use of ecological and economic accounting of water in the countries were taken into account. In addition, approaches to applying the level of materiality in ESG reporting were analyzed when reporting in this format. The results of the study made it possible to rank the elements of water resources management of economic entities according to the rule of materiality of data in ESG reporting and to propose an algorithm for compiling ESG reporting in the part of water resources management, taking into account the level of materiality. The article substantiates the directions of providing companies with adequate information on water resources management measures and reflecting such practices in ESG reporting to meet the needs of internal and external users. The directions of further scientific research in the field of reporting on the use of water resources by various business entities are also outlined. A critical analysis of the peculiarities of ESG reporting in the area of water resources management can provide an opportunity for top managers of domestic companies to improve the quality of financial and non-financial information, which, in turn, will contribute to the improvement of the corporate governance system on the one hand, and on the other hand, improve the satisfaction of information users. requests of all stakeholders when making their own management decisions.

A Proposal for a Mobility-Control Data Transfer Mechanism Based on a Block Network Utilizing End-to-End Authentication Data

Advances in communications technology have had tremendous influence on network implementation to date, and as communication devices get smaller and technologies more intelligent, a great number of solutions are emerging that converge communications with a multitude of domains. In particular, as transportation modes assisting with mobility have developed, many studies are in the pipeline on the domain of mobility. The development of mobility services has prompted the spread of car sharing, which also highlights the need for a system that controls shared vehicles. The data of such control system can be used not only for the operational management of vehicles but also the management of users in terms of user driving analysis or monitoring safe driving. In addition, it can be utilized in a variety of other applications that analyze traffic flow based on vehicle driving data, determine required vehicle maintenance intervals, or schedule vehicle maintenance in advance. However, if forged/altered by a third party, control data might pose a lot of challenges to data utilization. This study proposes a mechanism that manages control data on a blockchain to enhance the integrity of control data created in the communications process. In this paper, we propose a mechanism for applying a blockchain to the communication process between clients and servers. In the proposed mechanism, platform operators generate and provide independent identification information and identification numbers for users. The identification information and identification numbers are used to prove that the generated blocks were created by specific users. Data generated by clients create a block with a hash including user identification information alongside the user identification number. Verification of the generated block is performed on the platform vendor’s server, validating that the user identification number in the block matches the server-side user identification information and the hash of the data within the block. Thus, even when the contents of the block are shared in a public blockchain environment, user identification information is only held by the server and clients, preventing third parties from impersonating specific users to create data blocks. Furthermore, the verification process of the data includes hashes received from other nearby vehicles, preventing data tampering by the block creator.