User Management Research Articles

Assessment of Factors Influencing Healthcare Provider’s Acceptance of Electronic Health Record in Jordanian Hospitals

Acceptance of electronic health record systems is considered an essential factor for effective implementation among healthcare providers. In an attempt to understand healthcare providers’ perceptions of electronic health record systems implementation and evaluate the factors influencing healthcare providers’ acceptance of electronic health record systems, the current research examines the effects of individual (user) context factors and organisational context factors using the technology acceptance model. A quantitative cross-sectional survey design was used, in which 319 healthcare providers from five public hospitals participated in the present study. Data were collected using a self-administered questionnaire, which was based on the technology acceptance model. Jordanian healthcare providers demonstrated positive perceptions of the usefulness and ease of use of the electronic health record systems and subsequently accepted the technology. The results indicated that they had a significant effect on the perceived usefulness and perceived ease of use of the electronic health record, which in turn was related to positive attitudes towards the electronic health record systems as well as the intention to use them. User attributes, organisational competency, management support and training and education are essential variables in predicting healthcare providers’ acceptance towards electronic health records. These findings should be considered by healthcare organisations’ administration to introduce an effective system to other healthcare organisations.

Enabling scalable and adaptive machine learning training via serverless computing on public cloud

In today’s production machine learning (ML) systems, models are continuously trained, improved, and deployed. ML design and training are becoming a continuous workflow of various tasks that have dynamic resource demands. Serverless computing is an emerging cloud paradigm that provides transparent resource management and scaling for users and has the potential to revolutionize the routine of ML design and training. However, hosting modern ML workflows on existing serverless platforms has non-trivial challenges due to their intrinsic design limitations such as stateless nature, limited communication support across function instances, and limited function execution duration. These limitations result in a lack of an overarching view and adaptation mechanism for training dynamics, and an amplification of existing problems in ML workflows.To address the above challenges, we propose SMLT, an automated, scalable and adaptive serverless framework on public cloud to enable efficient and user-centric ML design and training. SMLT employs an automated and adaptive scheduling mechanism to dynamically optimize the deployment and resource scaling for ML tasks during training. SMLT further enables user-centric ML workflow execution by supporting user-specified training deadline and budget limit. In addition, by providing an end-to-end design, SMLT solves the intrinsic problems in public cloud serverless platforms such as the communication overhead, limited function execution duration, need for repeated initialization, and also provides explicit fault tolerance for ML training. SMLT is open-sourced and compatible with all major ML frameworks. Our experimental evaluation with large, sophisticated modern ML models demonstrates that SMLT outperforms the state-of-the-art VM-based systems and existing public cloud serverless ML training frameworks in both training speed (up to 8×) and monetary cost (up to 3×).

SensorHUB – a Novel, Open-source Software Stack for Enhanced Accessibility and Secure Interoperability in IoT Project Management

Abstract. The Internet of Things (IoT) seeks to achieve seamless device connectivity and data sharing, thereby enhancing automation, efficiency, and insights in various fields of application. By delivering real-time data, IoT is essential for systems that aim to model and map the physical world to digital formats, such as digital twins or metaverses. In the recent years, there has been a surge in high-quality commercial IoT products available to various sectors. However, these solutions often come with high costs and proprietary interfaces, which hinder seamless interoperability. For users seeking cost-effective and flexible solutions, open-source software and international standards present viable alternatives. Nonetheless, despite technological progress, the adoption of open and standardized IoT software solutions is still predominantly seen among technology-affine groups or within research and development initiatives. We propose the sensorHUB, a novel IoT stack, which builds upon the Open Geospatial Consortium’s (OGC) data standard SensorThings API and enhances existing solutions towards more accessible, production-oriented solutions for diverse application domains and user groups. Key features include the provision of a new, state-of-the-art graphical user interface for managing data flows and the access to related software modules, and a secure and flexible user and access management.

Discussion On Safety Management Of Urban Gas Non-Resident Users

with the rapid development of urbanization, the number of non-residential users of gas consumption continues to increase, and the corresponding security wind direction and problems are increasing. By combing the gas safety management process of non-residential users in large-scale urban gas enterprises, embedding the whole life cycle management process, improving the quality of gas safety management of non-residential users, eliminating some potential safety hazards and reducing the accident development rate, at the same time for other enterprises in the same industry to provide reference.

A diversity-aware recommendation system for tutoring

Diversity plays a major role when a student is looking for a tutor to better understand some concepts or an entire course. In fact, algorithms for recommending potential tutors have to take into account several aspects of diversity that may be critical to successful tutoring. The tutor must have the appropriate competencies in the subject matter. In addition, he/she must be able to convey the knowledge and skills associated with the tutoring topic. Moreover, the personality traits of the tutee and the tutor can facilitate or hinder the learning process during tutoring. This study presents the experience of ‘SOS TUTORÍA UC’, a responsive web application aimed at facilitating academic assistance among students. Special emphasis is placed on the importance of incorporating dimensions of diversity that can inform the artificial intelligence algorithms of the potential tutor recommendation system. Indeed, competence in the topic tutored is the first diversity criterion for recommending more knowledgeable potential tutors. In addition, the tutee has to choose whether to look for tutors with personalities that are “different”, “similar” or “indifferent” to his or her own preferences for academic assistance on the specific topic. To achieve this, ‘SOS TUTORÍA UC’ is integrated with the WeNet platform, which provides user management services and user recommendation algorithms. The results of the testing of the recommendation system were positive with regard to the criterion of competence, while the criterion of personality should be addressed for improvement. In order to improve the tutor-tutee matching process, participants emphasized the importance of considering the criterion of personality traits in addition to competence. They also requested additional information and parameters to facilitate tutor selection.

A novel probabilistic load shifting approach for demand side management of residential users

Demand side management is a beneficial set of techniques which leads improving consumption profile of residential users. Practice of dynamic pricing and appropriate shifting of electrical appliances at home are important tasks at that point. In this study, a novel probabilistic load shifting strategy is proposed and its beneficial effects on economic and technical parameters are demonstrated. For that purpose, a survey on energy consumption is applied for residential users and its results are used for creating a probabilistic model. 300 virtual residents are created in this way and a probabilistic simulation technique is developed. Next, the developed simulation technique is applied for creation of the monthly consumption data. Finally, it is demonstrated that electricity bills are decreased significantly when the proposed approach is applied. Besides that, peak-to-average ratio which is calculated by considering all residential users is also decreased as a result. In conclusion, when the results are compared with the ones of conventional constant tariff, time-of-use tariff with three time zones and a deterministic load shifting strategy, it is observed that the best results of economic and technical parameters in question are achieved by using the proposed probabilistic load shifting strategy together with dynamic pricing mechanism involved.

TripChain2RecDeepSurv: A novel framework to predict transit users’ lifecycle behavior status transitions for user management

Transit users’ lifecycle behavior pattern transition reflects the continuous and multi-phase changes in how frequently and regularly users utilize public transit over their lifetime. Predicting transit users’ lifecycle behavior pattern transition is vital for enhancing the efficiency and responsiveness of transportation systems. Thus, this study incorporates lifecycle analysis in predicting long-term sequential behavioral pattern transition processes to go beyond just examining user churning at a single point in time. Specifically, this study proposes the TripChain2RecDeepSurv, a novel model that pioneers the individual-level analysis of lifecycle behavior status transitions (LBST) within public transit systems. The TripChain2RecDeepSurv is composed of (1) the TripChain2Vec module for encoding transit users’ trip chains; (2) the self-attention Transformer module for exploring the latent features related to spatiotemporal patterns; (3) the recurrent deep survival analysis module for predicting LBSTs. We demonstrate TripChain2RecDeepSurv’s predictive performance for empirical analysis by employing Shenzhen Bus data. Our model achieves a 74.39% accuracy rate in churn determination and over 80% accuracy in status sequence identification on the churn path. In addition, our findings highlight the segmented nature of Kaplan-Meier curves and identify the optimal intervention time against the user churning process. Meanwhile, the proposed model provides individual-level heterogeneity analysis, which emphasizes the significance of customizing user engagement strategies, advocating for interventions that extend users’ engagement in patterns with high-frequency transit usage to curb the transition to less frequent travel usage.

Legal Liaison

The Legal Liaison system is an innovative web-based application designed to transform the landscape of legal practice and management. By incorporating essential functionalities for various stakeholders including clients, advocates, law students, junior advocates, and administrative staff, this system significantly enhances the efficiency and effectiveness of legal services. This application facilitates easy interaction and management for users by providing a centralized platform for all legal activities. It supports client engagement, advocate-client communication, case management, and administrative oversight, ensuring a streamlined workflow for legal professionals. Additionally, it promotes the professional development of emerging legal talents through structured mentorship and resource sharing. By leveraging modern technology, the Legal Liaison system aims to simplify complex legal processes, foster better collaboration, and improve resource utilization, ultimately providing a more accessible and efficient legal service environment. This holistic approach ensures that all participants in the legal ecosystem can benefit from enhanced coordination and optimized legal practices The front end of the Legal Liaison system is built using React.js, ensuring a responsive and interactive user experience. The backend employs Express.js and Node.js to create a robust and scalable server-side environment. MongoDB acts as the database, offering flexible and scalable data storage. Combined, these technologies form a seamless and efficient platform for contemporary legal practice

LIBRARY SKILLS REQUIRED BY THE PARAPROFESSIONAL STAFF IN USER SERVICES DEPARTMENT

This paper provides a review on the library skills that are required by the paraprofessional staff in user services department, explore the specific types of paraprofessional staff for user service department, and their roles. The study put together comparatively the user service information resource and service delivery responsibilities and the information utilitarian service support roles of the paraprofessional library staff and examines that, the more befitting type of paraprofessional library staff for user services are the “page”, “library aides”, and “library Services Assistant”. The types of responsibilities of user services paraprofessional staff was examined to be the middle level complementary roles in a way that relates to ‘user assistance’, and ‘library support’ in user management, information retrieval and access, shelve management, circulation desks services, reading area management and close access information services, among others. It also examined the library skills required by the user service paraprofessional library staff, who are expected to have the soft library – skills, hard library – skills, and the library information technologies use – skills, among others. The study concludes by stressing the existence of differing practices in the labelling paraprofessional library staff as “library support staff”, “library nonprofessional”, “not-certified” or “non-licenced librarians”, “post-secondary school” or “diploma certificate holders” in consistently, as well as confusion in their schedule of responsibilities. The study suggests the need for library regulatory agencies/parastatals and the libraries themselves to review the existing library staffing pattern/nomenclature and responsibilities to suit the current changing library environment, development in knowledge acquisition and certificates, changing users’ information needs and seeking behaviour and the changing trends in information services, among others.

Spesifikasi Kebutuhan Perangkat Lunak Sistem Informasi E-Survey Badan Litbang dan Diklat Kementerian Agama dengan standar ISO/IEC/IEEE 29148:2018

The digitalization of survey processes is crucial in today's era, and this research aims to design the software requirements specification for the E-Survey Information System for the Research and Training Agency of the Ministry of Religious Affairs of the Republic of Indonesia. The methodology employed follows the ISO/IEC/IEEE 29148:2018 standard in developing the System Requirements Specification (SRS) document. This comprehensive SRS outlines the purpose, scope, product overview, user characteristics, limitations, functional requirements, non-functional requirements, database design, interface, and use case diagrams. The functional requirements encompass survey management, survey question management, user management, role management, and accessing surveys. Non-functional requirements address performance and user-friendliness aspects. The result is a detailed SRS document that serves as a guideline for the development team in building an integrated and modern E-Survey application. This application will streamline and digitize the survey activities conducted by the Research and Training Agency, enabling efficient data collection, processing, and analysis. By following industry standards, the developed system aims to enhance productivity, centralize survey operations, and support informed decision-making processes related to strengthening religious moderation and harmony among religious communities in Indonesia

Aligning interoperability architectures for digital agri-food platforms

Interoperability is a critical challenge in Agri-food digitalisation, aligning with European data strategies and fostering pan-European cooperation, innovation, cost reduction, and market competition. Within the last years, the European Commission funded several projects to address interoperability in digital agriculture. We compare the projects IoF2020, ATLAS, and DEMETER which address interoperability for Agri-food systems with varying architectures and approaches, supported by the OpenDEI project. Interoperability, defined as the ability of systems to exchange and use information, encompasses multiple dimensions, including legal, organisational, semantic, and technical aspects. The analysis in this comparison focuses on the semantic and technical interoperability aspects of each project, covering architectural approaches, contextualization, marketplace functionalities, and user management and security measures.The examined projects highlight a variety of solutions, including service-oriented, data-centric, and process-oriented approaches, with the optimal choice between them remaining open, and an emphasis on the need for data consistency and plausibility. Advancements in standards and technologies, such as NGSI-LD, OGC, GAIA-X, and DSBA's implementation-driven plan, indicate a shift toward open interoperability in the broader ecosystem.

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.

A Method for Calculating the Adjustable Capacity of Feeder Load Aggregators Considering the User’s Wishes

Abstract With the deepening of China’s energy reform, large-scale renewable energy access has put forward higher requirements for the flexible adjustment ability of the power system. The research and application of mining flexible and adjustable resources on the user side to participate in the peak regulation and frequency regulation of the power grid have received extensive attention. With the gradual opening of the power market and the deepening of the reform of the power system, the feeder load aggregator has gradually become a new role in the power market, and the feeder load aggregator plays an important role in the centralized management of users, the optimization of distribution, and the realization of market-oriented transactions. However, the research on the participation of feeder loads in the auxiliary services of power grid peak regulation and frequency regulation is not perfect. In this context, this paper proposes a method for calculating the adjustable capacity of feeder load aggregators considering the wishes of users, in which the maximum voltage adjustable at the feeder and the change of the capacity of each user caused by the feeder voltage regulation are calculated by the feeder load aggregator through the power flow relationship, and finally the adjustable capacity declaration for the ancillary service market is completed.

Managing Linux servers with LLM-based AI agents: An empirical evaluation with GPT4

This paper presents an empirical study on the application of Large Language Model (LLM)-based AI agents for automating server management tasks in Linux environments. We aim to evaluate the effectiveness, efficiency, and adaptability of LLM-based AI agents in handling a wide range of server management tasks, and to identify the potential benefits and challenges of employing such agents in real-world scenarios. We present an empirical study where a GPT-based AI agent autonomously executes 150 unique tasks across 9 categories, ranging from file management to editing to program compilations. The agent operates in a Dockerized Linux sandbox, interpreting task descriptions and generating appropriate commands or scripts. Our findings reveal the agent’s proficiency in executing tasks autonomously and adapting to feedback, demonstrating the potential of LLMs in simplifying complex server management for users with varying technical expertise. This study contributes to the understanding of LLM applications in server management scenarios, and paves the foundation for future research in this domain.

BIKE RENTAL SYSTEM

Abstract The Bike Rental Management System is an innovative web application designed to revolutionize the rental process of bicycles for short-term urban use. It offers a comprehensive solution that caters to both customers and administrators, ensuring a seamless experience for all users.At its core, the system boasts a user-friendly interface that simplifies the process of searching for available bikes, selecting preferred options, and completing rentals. Real-time availability information is provided, empowering customers to make informed decisions. The secure payment processing feature guarantees a safe and convenient transaction experience, instilling trust and reliability in the system.For administrators, the system includes a robust admin panel that allows for efficient management of bikes, user accounts, and rentals. This panel provides a comprehensive overview of the rental operations, enabling administrators to make informed decisions and optimize the rental process for better efficiency.The technology stack behind the system is equally impressive, utilizing Java Servlet for backend logic, JDBC for database connectivity, JavaScript for client-side interactivity, and Bootstrap for responsive design. This ensures a smooth and seamless user experience across different devices and platforms.One of the key advantages of the Bike Rental Management System is its contribution to promoting eco-friendly urban mobility. By encouraging the use of bicycles for short-distance travel, the system helps reduce traffic congestion and carbon emissions, ultimately leading to a cleaner and greener environment. Additionally, the system promotes healthier lifestyles by encouraging physical activity through cycling.In conclusion, the Bike Rental Management System is a comprehensive and innovative solution that offers a wide range of benefits for both users and the environment. Its user-friendly interface, secure payment processing, efficient admin panel, and eco-friendly initiatives make it a standout choice for urban mobility solutions. Index Terms – Bike Rental, JDBC, User Authentication, Product Management, Admin Panel, Payment Processing, Scalability, Rental Process.

Participatory Approaches in the Context of Research Into Workplace Health Promotion to Improve Physical Activity Levels and Reduce Sedentary Behavior Among Office-Based Workers: Scoping Review.

Participatory research (PR) involves engaging in cocreation with end users and relevant stakeholders throughout the research process, aiming to distribute power equitably between the end users and research team. Engagement and adherence in previous workplace health promotion (WHP) studies have been shown to be lacking. By implementing a PR approach, the insights of end users and stakeholders are sought in the co-design of feasible and acceptable intervention strategies, thereby increasing the relevance of the research. This scoping review aims to explore, identify, and map PR techniques and their impact when used in office-based WHP interventions designed to improve physical activity (PA) or reduce sedentary behavior (SB). The reporting of this scoping review followed the PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews). A systematic literature search of 5 electronic databases-Web of Science, PubMed, Scopus, Google Scholar, and OpenGrey-was conducted, searching from January 1, 1995, to February 8, 2023. In total, 2 independent reviewers first screened the retrieved articles by title and abstract, and then assessed the full texts based on the inclusion and exclusion criteria. The search strategy and eligibility criteria were developed and guided by an a priori population (office-based working adults), intervention (a PA WHP intervention that took a PR approach), comparison (no comparison required), and outcome (PA or SB) framework. Data were charted and discussed via a narrative synthesis, and a thematic analysis was conducted. The included studies were evaluated regarding the degree of end user engagement throughout the research process and power shared by the researchers, using Arnstein's ladder of citizen participation. The search retrieved 376 records, of which 8 (2.1%) met the inclusion criteria. Four key strategies were identified: (1) end user focus groups, (2) management involvement, (3) researcher facilitators, and (4) workplace champions. The degree of engagement and power shared was relatively low, with 25% (2/8) of the studies determined to be nonparticipation studies, 25% (2/8) determined to be tokenistic, and 50% (4/8) determined to provide citizen power. This review provides a foundation of evidence on the current practices when taking a PR approach, highlighting that previous office-based PA WHP studies have been largely tokenistic or nonparticipative, and identified that the end user is only engaged with in the conception and implementation of the WHP studies. However, a positive improvement in PA and reduction in SB were observed in the included studies, which were largely attributed to implementing a PR approach and including the end user in the design of the WHP intervention. Future studies should aim to collaborate with workplaces, building capacity and empowering the workforce by providing citizen control and letting the end users "own" the research for a sustainable WHP intervention. RR2-10.1136/bmjopen-2021-054402.

Cross-Social-Network User Identification Based on Bidirectional GCN and MNF-UI Models

Due to the distinct functionalities of various social network platforms, users often register accounts on different platforms, posing significant challenges for unified user management. However, current multi-social-network user identification algorithms heavily rely on user attributes and cannot perform user identification across multiple social networks. To address these issues, this paper proposes two identity recognition models. The first model is a cross-social-network user identification model based on bidirectional GCN. It calculates user intimacy using the Jaccard similarity coefficient and constructs an adjacency matrix to accurately represent user relationships in the social network. It then extracts cross-social-network user information to accomplish user identification tasks. The second model is the multi-network feature user identification (MNF-UI) model, which introduces the concept of network feature vectors. It effectively maps the structural features of different social networks and performs user identification based on the common features of seed nodes in the cross-network environment. Experimental results demonstrate that the bidirectional GCN model significantly outperforms baseline algorithms in cross-social-network user identification tasks. The MNF-UI (multi-network feature user identification) model can operate in situations with two or more networks with inconsistent structures, resulting in improved identification accuracy. These two user identification algorithms provide technical and theoretical support for in-depth research on social network information integration and network security maintenance.

Bookhive: Virtual Society for Readers

In an era marked by technological advancements, the research endeavors to revolutionize the traditional paradigm of library management by introducing a comprehensive virtual society for readers enriched with digital features and user-centric functionalities. This system comprises multiple interconnected modules designed to enhance the overall library experience for both administrators and patrons. The core Library Management Module streamlines book cataloging, user management, and inventory tracking, optimizing the operational efficiency of libraries. Concurrently, the Mobile App Module extends the library’s reach beyond physical boundaries, offering a user-friendly platform for on-the-go access to resources, virtual book clubs, and personalized recommendations. The Community Engagement Module fosters a vibrant literary community by facilitating discussions, author-reader interactions, and collaborative book recommendations. The Delivery and Rare Books Module ensures accessibility by enabling users to request book deliveries and notifying them of rare book availability. Furthermore, the User Profile and Customization Module empowers patrons to personalize their library experience, from user registration to preference settings. This research is not merely a technological overhaul but a gateway to a more dynamic and inclusive library ecosystem, embracing the digital age while preserving the essence of community, engagement, and the joy of reading. With data-driven insights, personalized features, and an emphasis on community building, our Library Management System represents a forward-looking approach to redefining the role of libraries in the modern world, ensuring they remain vibrant hubs of knowledge, connection, and literary exploration.

Optimizing user and resource management in modern businesses using a domain controller in Windows Server 2019

Optimizing user and resource management in modern businesses using a domain controller in Windows Server 2019

PDHL-MARCOS method based on cumulative prospect theory for MAGDM and its application in network security evaluation

The increasingly large and complex network brings convenience to our life and production, but it also brings potential dangers. Any minor vulnerability may lead to failure of application software configuration, software maintenance, user management and system management. Eventually, our network is interrupted, and even life and production data are leaked. Therefore, establishing a scientific and effective network security evaluation model is an effective way to supervise, manage and improve network security; It is also an effective measure to reduce the loss of life and production. Therefore, we first selected six factors closely related to network security to form a complete network security evaluation index system. Then, the utility function in the traditional measurement of alternatives and ranking according to compromise solution (MARCOS) method is improved by using the value function in cumulative prospect theory (CPT), and a PDHL-MARCOS evaluation model that can reflect the decision-makers’ (DMs’) attitudes towards gains and losses is obtained in the probabilistic double hierarchy linguistic term set (PDHLTS). In addition, the relative entropy (RE) method is also used to obtain expert weights. The combination weights of attributes are obtained using the correlation coefficient and the standard deviation (CCSD) method and the weight function in CPT.