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ABSTRACT This paper addresses the challenge of improving the effectiveness and innovativeness of online teaching in higher education. It presents a blended learning course designed for faculty development and discusses the findings of surveying the opinions of participants. The course integrates synchronous sessions with digital learning tools and platforms to equip educators with essential skills for online teaching. A mixed‐methods design has been applied for evaluating the educational activity, incorporating both qualitative and quantitative data collection. The course had a completion rate of 91.13%. The opinions of 72 higher education members have been surveyed, and the findings revealed that the blended learning course enhanced instructors' ability to design and deliver online content that is both pedagogically sound and engaging. The necessity for such learning activities is strongly emphasised. The paper concludes by discussing the implications for future course design and faculty development programs in higher education. [ABSTRACT FROM AUTHOR]

Blockchain technology has been used with great effect in farm-to-fork traceability projects. However, this technology has a steep learning curve when it comes to its user interface. To minimize this difficulty, we created a solution based on a Large Language Model (LLM) conversational agent. Our implementation, starting with an existing knowledge base that is prepared and processed with an embedding model to be stored in a vector database, follows a Retrieval-Augmented Generation (RAG) approach. Other non-textual media like images and videos are aggregated with the embeddings to enrich the user experience. User queries are combined with a proximity search in the vector database and feed into an LLM that considers the conversation history with the user in its replies. Given the asynchronous nature of these models, we implemented a similarly asynchronous scheme using Server-Sent Events that deliver the models' replies to a UI that supports multimodal media types such as images and videos by providing the visualization of these resources. The end solution allows users to interact with advanced technologies using a natural language interface; this in turn empowers food traceability projects to overcome their natural difficulty in engaging early adopters. [ABSTRACT FROM AUTHOR]

Blockchain technology has been used with great effect in farm-to-fork traceability projects. However, this technology has a steep learning curve when it comes to its user interface. To minimize this difficulty, we created a solution based on a Large Language Model (LLM) conversational agent. Our implementation, starting with an existing knowledge base that is prepared and processed with an embedding model to be stored in a vector database, follows a Retrieval-Augmented Generation (RAG) approach. Other non-textual media like images and videos are aggregated with the embeddings to enrich the user experience. User queries are combined with a proximity search in the vector database and feed into an LLM that considers the conversation history with the user in its replies. Given the asynchronous nature of these models, we implemented a similarly asynchronous scheme using Server-Sent Events that deliver the models’ replies to a UI that supports multimodal media types such as images and videos by providing the visualization of these resources. The end solution allows users to interact with advanced technologies using a natural language interface; this in turn empowers food traceability projects to overcome their natural difficulty in engaging early adopters.

Background Scientific workflow systems are increasingly popular for expressing and executing complex data analysis pipelines over large datasets, as they offer reproducibility, dependability, and scalability of analyses by automatic parallelization on large compute clusters. However, implementing workflows is difficult due to the involvement of many black-box tools and the deep infrastructure stack necessary for their execution. Simultaneously, user-supporting tools are rare, and the number of available examples is much lower than in classical programming languages. Results To address these challenges, we investigate the efficiency of large language models (LLMs), specifically ChatGPT, to support users when dealing with scientific workflows. We performed 3 user studies in 2 scientific domains to evaluate ChatGPT for comprehending, adapting, and extending workflows. Our results indicate that LLMs efficiently interpret workflows but achieve lower performance for exchanging components or purposeful workflow extensions. We characterize their limitations in these challenging scenarios and suggest future research directions. Conclusions Our results show a high accuracy for comprehending and explaining scientific workflows while achieving a reduced performance for modifying and extending workflow descriptions. These findings clearly illustrate the need for further research in this area. [ABSTRACT FROM AUTHOR]

For organizations, the error-free, consistent, and transparent management of business processes is crucial. Process management relates to the proper handling of data, achievable through enterprise resource planning (ERP) software. This software enables all departments, structured around a central database, to work together. From an organizational perspective, one of the most critical factors for the success of ERP software is its users. Users often require support when using ERP software for various reasons, such as lack of training, experience, or technical issues. Providing this support, whether internally or from external sources, incurs a cost. This study seeks to determine whether a structure can be developed where users can resolve their support requests independently. To achieve this goal, we propose a model for an intelligent user support system with an AI-based process engine for ERP users. Using this model, unstructured user support requests, created in natural language, are transformed into structured forms using natural language processing techniques and then classified using multi-class machine learning algorithms. The process relevant to the identified class is executed to generate a solution for the user's problem. In this study, 1,000 samples of text written in natural language across 10 different categories, based on real data, were used in the learning process. The data were analyzed using machine learning algorithms (K-Nearest Neighbors, Naive Bayes, C4.5, Support Vector Machine, Random Forest, Sequential Minimal Optimization, LibSVM) and deep learning algorithms (Long Short-Term Memory). The best classification was achieved with Sequential Minimal Optimization (SMO) using TF-IDF weighting. The developed chat and process robot helped convert requests or problems into structured forms and provided solutions. In addition to solving the problem through chat or process, technologies such as augmented reality and virtual reality were used. [ABSTRACT FROM AUTHOR]

In the rapidly evolving landscape of modern technology, the convergence of diverse technological advancements is reshaping how ERP systems function and perform. This transformation aims to bolster the utilization of ERP systems, ultimately leading to improved organizational performance. Despite these developments, limited insights are available regarding the factors that both foster ERP system usage and impede organizational performance. Consequently, the present study strives to gain a deeper comprehension of the determinants influencing ERP system utilization, consequently contributing to organizational advancement. Specifically, the study seeks to explore how ERP system usage acts as a mediator within the framework of internal and external factors, individual characteristics, ERP-specific elements, and overall organizational performance. To achieve this objective, survey questionnaires were administered to employees within Saudi Arabian companies, utilizing the convenience sampling technique. The subsequent analysis was conducted using Structural Equation Modelling (SEM) through Amos-16. The study's outcomes highlight the significance of User Support, Top Management Support, IT Expert/Consultant Support, Computer self-efficacy, and Communication Effectiveness in driving increased ERP system utilization, thereby fostering organizational performance enhancement. The outcomes of this study enrich the existing knowledge base by deepening researchers' comprehension of the various elements that impact both ERP utilization and overall firm performance. Furthermore, the study's findings provide valuable insights for industry practitioners, enabling them to strategically incorporate these factors to optimize ERP usage and consequently enhance firm performance. Notably, the examination of these interrelationships among variables, particularly within the context of Saudi Arabian organizations, remains a relatively underexplored area within the current body of research, based on the researchers' available information.

In the rapidly evolving landscape of modern technology, the convergence of diverse technological advancements is reshaping how ERP systems function and perform. This transformation aims to bolster the utilization of ERP systems, ultimately leading to improved organizational performance. Despite these developments, limited insights are available regarding the factors that both foster ERP system usage and impede organizational performance. Consequently, the present study strives to gain a deeper comprehension of the determinants influencing ERP system utilization, consequently contributing to organizational advancement. Specifically, the study seeks to explore how ERP system usage acts as a mediator within the framework of internal and external factors, individual characteristics, ERP-specific elements, and overall organizational performance. To achieve this objective, survey questionnaires were administered to employees within Saudi Arabian companies, utilizing the convenience sampling technique. The subsequent analysis was conducted using Structural Equation Modelling (SEM) through Amos-16. The study's outcomes highlight the significance of User Support, Top Management Support, IT Expert/Consultant Support, Computer Self Efficacy, and Communication Effectiveness in driving increased ERP system utilization, thereby fostering organizational performance enhancement. The outcomes of this study enrich the existing knowledge base by deepening researchers' comprehension of the various elements that impact both ERP utilization and overall firm performance. Furthermore, the study's findings provide valuable insights for industry practitioners, enabling them to strategically incorporate these factors to optimize ERP usage and consequently enhance firm performance. Notably, the examination of these interrelationships among variables, particularly within the context of Saudi Arabian organizations, remains a relatively underexplored area within the current body of research, based on the researchers' available information. [ABSTRACT FROM AUTHOR]

The newest NERSC supercomputer Cori is a Cray XC40 system consisting of 2,388 Intel Xeon Haswell nodes and 9,688 Intel Xeon-Phi “Knights Landing” (KNL) nodes. Compared to the Xeon-based clusters NERSC users are familiar with, optimal performance on Cori requires consideration of KNL mode settings; process, thread, and memory affinity; fine-grain parallelization; vectorization; and use of the high-bandwidth MCDRAM memory. This paper describes our efforts preparing NERSC users for KNL through the NERSC Exascale Science Application Program, Web documentation, and user training. We discuss how we configured the Cori system for usability and productivity, addressing programming concerns, batch system configurations, and default KNL cluster and memory modes. System usage data, job completion analysis, programming and running jobs issues, and a few successful user stories on KNL are presented.

The eHealth Service Desk is a key component of the eHealth system in Slovenia, which is intended for the all users of the system. The Service Desk performs three main tasks. General support for all users of eHealth solutions addresses health care professionals, administrative staff, information technology specialists, software solution providers, patients and all other users of eHealth solutions who wish to report malfunctions, need assistance or require information related to the functioning of the eHealth solutions. The electronic appointment for health care services helps patients to make an eAppointment for health care services. The zNET Connection Support offers help to health care providers in the process of joining the zNET network. Assistance can be accessed in several ways: via an online form, email, FAQs or phone. The Service Desk publishes notifications related to the eHealth solutions on its website and maintains a simple indicator that displays the status of eHealth solutions. During the last two years, several new eHealth solutions have been added to the Service Desk portfolio. The use has been growing rapidly in recent years, namely in 2021 we recorded a more than sevenfold increase compared to 2020. The paper analyses the operation of the eHealth Service Desk through the dynamics and content of the requests handled or services provided. The Service Desk is an important component for the successful use of eHealth solutions in Slovenia, which was particularly evident during the COVID-19 epidemic. [ABSTRACT FROM AUTHOR]

The research aims to create a smart user Support Assistant LAVA - a solution providing context sensitive and user experience aware support to a user of a software product. The solution is based on machine learning and search in a two-level distributed knowledge store. LAVA model focuses on providing user on a mouse click with a content relevant to a current context. LAVA uses context transferred from the supported product to instantly show a FAQ list of items used and/or positively rated by other users in the same context. Full-text search and a topic hierarchy are provided as well to cover as many of cases as possible given the content available currently in the Knowledge base. Main design ideas of the LAVA model are presented in the article including the calculation of ranges and creation of ranged context-sensitive FAQs, customizing the full-text search, organizing the topic hierarchy and integrating with the Service desk. The article covers as well the main considerations on how the LAVA model should be implemented in a successful solution, and a description of method to evaluate the model performance. [ABSTRACT FROM AUTHOR]

Valid models are central for credible simulation studies. If those models do not exist, they need to be developed. In fact, entire simulation studies are often aimed at developing valid models. Thereby, successive model refinement and execution of diverse simulation experiments are closely intertwined. Whereas software-based support for individual simulation experiments exists, the intricate interdependencies and the diversity of tasks that govern simulation studies have prevented a more comprehensive support. To achieve the required flexibility while adhering to the constraints that apply between individual tasks, we adopt a declarative, artifact-based workflow approach. Therefore, central products of these simulation studies are identified and specified as artifacts: the conceptual model (with a focus on formally defined requirements), the simulation model, and the experiment. Each artifact is characterized by stages the artifact moves through to reach certain milestones and which are guarded by conditions. Thereby, the relations and constraints between artifacts become explicit. This is instrumental to check and ensure the consistency between conceptual model and simulation model, to automatically execute simulation experiments to probe the specified requirements, and to develop plans to provide goal-directed guidance to the user. We demonstrate the approach by using it to repeat an existing simulation study. [ABSTRACT FROM AUTHOR]

This article introduces a prototype of a writing (and learning) assistant for verbal relative clauses of the African language Sepedi, accessible from within a dictionary or from a word processor. It is an example of how a user support tool for complicated grammatical structures in a scarcely resourced language can be compiled. We describe a dynamic light-weight tool aimed at combining user-knowledge with text production support, i.e., user-involved interactive text production of the complicated verbal relative in Sepedi. In this article, the focus is on access in a dictionary use situation. Although the tool is intended as a writing assistant to support users in text production; it also satisfies text reception and cognitive needs, but its focus is on solving text production issues related with the interaction between lexical items and complex grammatical structures in the African (Bantu) languages and for learning by users and/or training users in this interaction.

Running any computing center is a complex task. With the growth of scales and costs such tasks become challenges. So the top supercomputer sites, being big in everything, have always required special approaches to manage, to control, and to take care of them. At present, large HPC centers can have a variety of totally diverse systems containing up to millions of components, having thousands of users worldwide with the full range of complicated applications. Obviously, tons of data have to be managed in a concerted way to allow such an informational factory functioning. This paper shares the design principles, some implementation details and the roadmap vision regarding the Octoshell HPC center management system, which has been developed and is currently being used in the everyday practice of Moscow State University supercomputer center. This open source system manages Lomonosov and Lomonosov-2 systems with a total of over 5 PFlops peak performance complexes at present, providing multiple tools aimed to tackle most typical workflow tasks both for regular users and system administrators in a single shell. [ABSTRACT FROM AUTHOR]

This study examines user support issues concerning open-source software in computational sciences. The literature suggests that there are three main problem areas: transparency, learnability, and usability. Looking at questions asked in user communities for chemistry software projects, the author found that for software supported by feature-based documentation, problems of transparency and learnability are prominent, leading users to have difficulty reconciling disciplinary practices and values with software operations. For software supported by task-based documentation, usability problems were more prominent. The author considers the implications of this study for user support and the role that technical communication could play in developing and supporting open-source projects. [ABSTRACT FROM AUTHOR]

Background:Online user networks are important points of contact for users who seek help from their peers rather than documentation.Literature review:The appeal of online user networks coincides with and seems connected to growing user interest in topicalized and tailored content, the production of which is inconsistent with the “craftsman” model of technical communication. Studies of online user networks indicate that community members may be practicing a different kind of technical communication.Research questions:This study examines an online user network for an open-source software product and asks how we can study online user networks, with the aim of identifying important people, practices, and relationships associated with the kind of technical communication practiced in those settings.Research methodology:Social network analysis is used to visualize the structural properties of an online user network, in order to identify central figures and their relationships to others. Verbal data-analysis techniques are used to find themes in their contributions.Results/discussion:People who are central to the structure of online interaction are important figures in the distribution of the technical communication effort. They engage users in reciprocal exchanges of information and they influence user practices. They are also important as brokers who link users and developers. Broadly, their conversational exchanges are a kind of distributed technical communication.Implications for practice:We learn what the practice of technical communication looks like in an online user network. By observing the work of participants, technical communicators can understand what it means to do technical communication and make user networks a more integral part of a broader documentation strategy. We see promising ways in which technical experts (e.g., software developers) can engage with users as well. [ABSTRACT FROM AUTHOR]

Background: Earth System Grid Federation (ESGF), a well-known e-infrastructure provides open data to study the future anthropogenic climate change. Data are accessed by the research communities to produce sophisticated simulations of the earth system and to study the impact of climate change. Although these e-infrastructures provide relevant data, little is known about the User eXperience (UX) and the issues that users face during their interaction with these infrastructures. Aim: This article presents an investigation about the issues that researchers (end-users) may face while interacting with an e-Science infrastructure and consequently, it elucidates obstacles to access required data. Method: Supported by Action Research (AR) methodology, this study was carried out in the context of ESGF by analysing different types of stakeholders especially users and the help desk. Based on Grounded Theory (GT), in a deeply qualitative analysis, we examined 655 e-mail threads that were sent to ESGF help desk as there were questions asked by end-users to access the data served by the e-infrastructure. Results: The outcomes revealed that questions related to workflow in the e-infrastructure were the bottlenecks that mostly impact the UX. Based on the classification scheme of the barriers that is derived as a result, after applying GT, we classified such bottlenecks and made suggestions to improve UX in e-Science infrastructure. Conclusions: According to our knowledge, this is the first study focused on discussing UX in e-Science infrastructure as it explains the barriers that limit and delay the research process of scientists while they interact with the e-infrastructure. Henceforth, the full benefit of the data projects hosted by the e-infrastructure is not realized. If these barriers would be treated using a joint-strategy initiated by the stakeholders of an e-infrastructure, the research process for the users will be faster and they will have a better UX. [ABSTRACT FROM AUTHOR]