bluuebunny/crossref_metadata_2025 huggingface dataset:
Contextual Constraints for the Design of Patient-Centered Health IT Tools
Authors: Gonzales Michael J.  , O'Connor Maria Francesca  , Riek Laurel D.
Published: February 2025

Technologists are constantly working to improve clinical practice by developing new health information technology (Health IT) tools, yet may not always consider the context of how these tools may be used. Patient preferences can vary widely as a result of demographics, health conditions, physical limitations, and personal inclinations, with healthcare providers having to adapt clinical encounters to better suit patient needs. Health IT tools, too, need to be agile across different healthcare contexts, with each stakeholder's specific needs in mind. In this paper, we discuss the challenges and limitations associated with the design and automation of contextually sensitive devices in the healthcare environment. We target the various contexts in which health information is presented in patient-provider encounters, and discuss contextual constraints that may apply to the aforementioned situations. In addition, we present a number of suggestions for informational constraints and the design of informational tools in these settings so that patient and provider informational needs can be better met in clinical communication contexts.
Development of Support System Solutions for Capability Transition
Authors: Downey Kevin  , Mo John P.T.
Published: February 2025

The Australian Defence Force and industry are undergoing significant changes in the way they work together in capability enhancement programs. In order to manage major asset acquisition to transition new capability into the front line of Royal Air Force Fighter Groups whilst maintaining and supporting its current obligations, this paper looks at the steady state support solution and argues that in order to interchange from one support solution to a new architecture there must be a period of transition which may need its own short term business model and operational service. Preliminary study of several existing support solutions reveals the generic elements that need to be parameterised and traced throguh the trajectory. Research is continuing with detailing these parameters and validating through actual practical application of the proposed methdoology in this paper.
Closed Contour Shape Descriptors with High Compression Properties Based on the Discrete Hartley Transform
Authors: Marti-Puig Pere  , Reig-Bolaño Ramon  , Danes Jaume
Published: February 2025

The quantitative analysis of shapes is required in some research fields, such as taxonomy, agronomy, ecology, medicine, among others. The quantification of an object shape, or a biological entity shape as extension, is usually performed on its closed contour data. Normally, the closed contours are automatically extracted from digital images. In these fields, the most used contour descriptors are the Elliptical Fourier Descriptors (EFD). In this paper we propose a new contour descriptor based on the Discrete Hartley Transform (DHT) that uses only half of the coefficients required by EFD to obtain a contour approximation with similar error measure. The proposed closed contour descriptors provide an excellent capability of contour information compression being suitable to be applied as input parameters of any shape classifier. The proposed parameterization can represent all kinds of closed curves and also it has the advantage that both the parameterization and the reconstructed shape from a reduced amount of them can be computed very efficiently by the fast Discrete Hartley Transform (DHT) algorithm.
A Combination of Knowledge and Argumentation Based System for Supporting Injection Mould Design
Authors: Cabanillas David  , Bonada Francesc  , Ventura Raquel  , Toni Francesca  , Evripidou Valentinos  , Carstens Lucas  , Rebolledo Liceth
Published: February 2025

Designing plastic parts requires knowledge about the plastic injection process. Many efforts have been made to improve simulations of the process during the design phase. This paper presents the use of different Artificial Intelligence techniques to develop a decision support system for plastic parts designers. Our approach is based on computational argumentation (ARG) and case-based reasoning (CBR) to offer both a recommendation about the design and the reasoning process followed in order to select the best solution. Given the geometry of the part, type of material, mould material and defects to be avoided, the system combines a knowledge-based system (KBS) based on past design/decision experiences and designers' social debates for providing a set of recommendations, enabling to update the knowledge database by reusing and adapting solutions from previous designs.
Robot Visions, Robot Vision
Authors: Kragic Danica
Published: February 2025

The current trend in computer vision is development of data-driven approaches where the use of large amounts of data tries to compensate for the complexity of the world captured by cameras. Are these approaches also viable solutions in robotics? Apart from ‘seeing’, a robot is capable of acting, thus purposively change what and how it sees the world around it. There is a need for an interplay between processes such as attention, segmentation, object detection, recognition and categorization in order to interact with the environment. In addition, the parameterization of these is inevitably guided by the task or the goal a robot is supposed to achieve. In this talk, I will present the current state of the art in the area of robot vision and discuss open problems in the area. I will also show how visual input can be integrated with proprioception, tactile and force-torque feedback in order to plan, guide and assess robot's action and interaction with the environment.
Probabilistic Inference in BN2T Models by Weighted Model Counting
Authors: Vomlel Jiří  , Tichavský Petr
Published: February 2025

Exact inference in Bayesian networks with nodes having a large parent set is not tractable using standard techniques as are the junction tree method or the variable elimination. However, in many applications, the conditional probability tables of these nodes have certain local structure than can be exploited to make the exact inference tractable. In this paper we combine the CP tensor decomposition of probability tables with probabilistic inference using weighted model counting. The motivation for this combination is to exploit not only the local structure of some conditional probability tables but also other structural information potentialy present in the Baysian network, like determinism or context specific independence. We illustrate the proposed combination on BN2T networks – two-layered Bayesian networks with conditional probability tables representing noisy threshold models.
A Case Study on Legal Case Annotation
Authors: Wyner Adam  , Peters Wim  , Katz Daniel
Published: February 2025

The paper reports the outcomes of a study with law school students to annotate a corpus of legal cases for a variety of annotation types, e.g. citation indices, legal facts, rationale, judgement, cause of action, and others. An online tool is used by a group of annotators that results in an annotated corpus. Differences amongst the annotations are curated, producing a gold standard corpus of annotated texts. The annotations can be extracted with semantic searches of complex queries. There would be many such uses for the development and analysis of such a corpus for both legal education and legal research.
Self-Reported Differences in Personality, Emotion Control, and Presence Between Pre-Military and Non-Military Groups in a Pilot Study Using the Stress Resilience in Virtual Environments (STRIVE) System
Authors: John Bruce S.  , Oliva Laura Serra  , Buckwalter J. Galen  , Kwok David  , Rizzo Albert “Skip”
Published: February 2025

Mental health disorders are the signature wounds of war resulting from extended U.S. Military conflicts in the Middle East [1]. In an effort to abate the number of Service Members that develop mental health disorders in these conflicts, USC-ICT has created the Stress Resilience in Virtual Environments (STRIVE) project, a set of highly realistic virtual reality combat scenarios and resilience-building sessions designed for pre-deployed military personnel. This short-paper looks at self-reported differences in personality, emotion control, and presence between two different groups, pre-military and non-military, of pilot subjects that tested a prototype of the first four modules of STRIVE.
Evaluation of a Mobile Augmented Reality Application for Image Guidance of Neurosurgical Interventions
Authors: Kramers Matthew  , Armstrong Ryan  , Bakhshmand Saeed M.  , Fenster Aaron  , de Ribaupierre Sandrine  , Eagleson Roy
Published: February 2025

Image guidance can provide surgeons with valuable contextual information during a medical intervention. Often, image guidance systems require considerable infrastructure, setup-time, and operator experience to be utilized. Certain procedures performed at bedside are susceptible to navigational errors that can lead to complications. We present an application for mobile devices that can provide image guidance using augmented reality to assist in performing neurosurgical tasks. A methodology is outlined that evaluates this mode of visualization from the standpoint of perceptual localization, depth estimation, and pointing performance, in scenarios derived from a neurosurgical targeting task. By measuring user variability and speed we can report objective metrics of performance for our augmented reality guidance system.
Application of Learning Record Stores and Other Forms of Electronic Competency Records in Modeling Competency Degradation
Authors: Bergeron Bryan
Published: February 2025

In the context of cognitive competencies, we are defined by our memories. As such, experiential data in various forms of Electronic Competency Records (ECRs), including the Learning Record Store (LRS), can be used as the basis for an Intelligent Tutoring System (ITS), scheduling medical recertification preparation and other forms of educational intervention. However, the experiential data infrastructure provided by an ECR is necessary but insufficient for realizing the full potential of competency tracking and prediction technology. To this end, we are exploring competency degradation models based on time and interference, using retrospective data from our ECR-based work in ITS.
Tourniquet Master Training for Junctional and Inguinal Hemorrhage Control (TMT)
Authors: Weyhrauch Peter W.  , Niehaus James  , Metzger Max  , Laufer Shlomi  , Kwan Calvin  , Pugh Carla
Published: February 2025

Junctional and inguinal bleeding is a significant and challenging problem on the battlefield. Inventors have developed new types of tourniquets, including the Abdominal Aortic Tourniquet™ (AAT) and the Combat Ready Clamp™ (CRoC) to address these abdominal and pelvic injuries. While these hemorrhage control technologies have been developed, validated, and approved for use, training systems that teach and refresh skills related to these technologies have not been developed. These training systems are vital because these skills can be difficult to train and are infrequently used. To address these needs, a sensor-enabled manikin was designed. Using the sensor data, the different phases of applying the tourniquet were captured and key performance was measured.
From Generic Pathways to ICT-supported Horizontally Integrated Care: The SmartCare Approach and Convergence with Future Internet Assembly
Authors: Urošević Vladimir  , Mitić Marko
Published: February 2025

Successful service integration in policy and practice requires both technology innovation and service process innovation being pursued and implemented at the same time. The SmartCare project (partially EC-funded under CIP ICT PSP Program) aims to achieve this through development, piloting and evaluation of ICT-based services, horizontally integrating health and social care in ten pilot regions, including Kraljevo region in Serbia. The project has identified and adopted two generic highest-level common thematic pathways in joint consolidation phase – integrated support for long-term care and integrated support after hospital discharge. A common set of standard functional specifications for an open ICT platform enabling the delivery of integrated care is being defined, around the challenges of data sharing, coordination and communication in these two formalized pathways. Implementation and system integration on technology and architecture level are to be based on open standards, multivendor interoperability, and leveraging on the current evolving open specification technology foundations developed in relevant projects across the European Research Area.
Trust Information and Privacy Policies – Enablers for pHealth and Ubiquitous Health
Authors: Ruotsalainen Pekka  , Blobel Bernd
Published: February 2025

pHealth occurs in uncontrolled and unsecure environment where predefined organizational trust does not exist. To be accepted by users, pHealth requires a privacy model where privacy is a personal property, i.e., a person can perform own will and define policies which regulate how personal health information (PHI) is used. Privacy and trust are interconnected concepts. Therefore, before beginning to use pHealth services, the person needs practical and reliable information that enables her or him to determine the trustworthiness level of services.
Applying Open Source Data Visualization Tools to Standard Based Medical Data
Authors: Kopanitsa Georgy  , Taranik Maxim
Published: February 2025

Presentation of medical data in personal health records (PHRs) requires flexible platform independent tools to ensure easy access to the information. Different backgrounds of the patients, especially elder people require simple graphical presentation of the data. Data in PHRs can be collected from heterogeneous sources. Application of standard based medical data allows development of generic visualization methods. Focusing on the deployment of Open Source Tools, in this paper we applied Java Script libraries to create data presentations for standard based medical data.
Supporting Knowledge Discovery in Medicine
Authors: Girardi Dominic  , Arthofer Klaus
Published: February 2025

Our ontology-based benchmarking infrastructure for hospitals, we presented on the eHealth 2012, has meanwhile proven useful. Besides, we gathered manifold experience in supporting knowledge discovery in medicine. This also led to further functions and plans with our software. We could confirm and extent our experience by a literature review on the knowledge discovery process in medicine, visual analytics and data mining and drafted an according approach for extending our software. We validated our approach by exemplarily implementing a parallel-coordinate data visualization into our software and plan to integrate further algorithms for visual analytics and machine learning to support knowledge discovery in medicine in diverse ways. This is very promising but can also fail due to technical or organizational details.
iDispatcher: Using Business Rules to Allocate and Balance Workloads
Authors: Quinzaños José Manuel  , Cartas Alejandro  , Vidales Pablo  , Maldonado Armando
Published: February 2025

In the insurance sector, the assignment of business transactions to operational roles in the business process is a complex task that usually requires human intervention due to the lack of efficient and powerful automated decision making tools. A number of mechanisms and methods have been proposed to improve workloads' allocation in core business process in the insurance industry. This paper describes a novel solution, the iDispatcher, to efficiently assign and balance business transactions to line operators, in particular in the processes of underwriting and issuing policies. It is based on the use of a business rule engine that evaluates the intrinsic properties of a particular transaction and the specific abilities and technical skills of all available operators to find the best match. The iDispatcher benefits key business results by generating a more efficient operation based on the correct assignment of business transactions using a flexible and dynamic solution. The insurance companies will be able to make the right decision in the right moment for every incoming business request, and this represents a strategic difference in the market.
Online Information for Medical Treatment Decisions: an Evaluation Based on Simon's Theory
Authors: Cheung Wai Ling  , Burstein Frada
Published: February 2025

The emerging trend in treatment decision making for complex medical conditions is shifting to a collaborative model, where patients actively participate as decision makers. To facilitate this, online medical information must be fitting to the purpose of making sound treatment decisions. Underpinned by Herbert Simon's Nobel-winning work Administrative Behavior, we examine the treatment decision process in the context of Internet health information provision. Based on Simon's propositions, we propose a set of decision support features for evaluating Internet health information websites. We then use them to evaluate official Australian and international websites for Autism Spectrum Disorders (ASD), where the need for treatment decision support is prominent due to the diverse nature of the condition. The evaluation results indicate a general inadequacy in terms of Relevance under the Value proposition among the websites. Genuine individualized information based on patient's profile of symptoms, delivered by intelligent personalization technologies, should be further deployed to address this inadequacy. The theoretical contributions of this paper are: i) bridging online information quality model and classical decision making theory, and ii) analyzing online information provision based on Simon's bounded rationality. Whilst, the practical contributions are: i) to provide a set of decision support features as guidelines for ASD websites that ii) are extendable to other health domains and different technologies.
Evaluating the Utility of the Irish HSE's Paper Based Early Warning Score Chart: A Reflective Data Gathering Phase for the Design of the REVIEWS Framework
Authors: Creedon Fred  , O'Kane Thomas  , O'Donoghue John  , Adam Frederic  , Woodworth Simon  , O'Connor Siobhan
Published: February 2025

This paper presents a design science evaluation of a vital sign chart for an Aggregate-Weighted Track-and-Trigger System (AWTTS) developed by the Irish Health Service Executive (HSE). This system is known as the National Early Warning Score (NEWS), with the chart incorporated within NEWS known as the Early Warning Score (EWS) Chart. Presentations of patient vital sign data on charts provides an opportunity for healthcare professionals (HCPs) to process vital sign data and identify trends of patient deterioration. Due to the reality of working in a complex work environment processing this data can be difficult for HCPs. This research evaluates how useful experienced nurses perceive the EWS chart to be in the context of supporting them in processing vital sign data presented on the NEWS chart. This paper represents a reflective data-gathering phase for the development of a design framework for improving how vital sign data is visualised on electronic AWTTS charts. This paper also utilises the approach for Reflective Design Knowledge Synthesis (RDKS) to synthesise design knowledge inherent to the NEWS chart. The empirical findings of this study involving interviews of 8 nurses with an average of 21 years' experience demonstrate that the NEWS chart is significantly more useful than legacy vital sign charts that would have been previously used. Furthermore, the evaluation establishes which design features are perceived to be most useful for nurses when processing vital signs displayed on the NEWS chart.
Ontology-based Decision Support System Architecture for Tendering Management
Authors: Mohemad Rosmayati  , Hamdan Abdul Razak  , Ali Othman Zulaiha  , Mohamad Noor Noor Maizura
Published: February 2025

Tendering management is a large and fragmented process implemented in various industries such as construction, logistics, pharmaceutical, and commerce. Tendering process is vital for a governing body that intends to acquire any goods or services from third parties for ensuring fair and transparent competition. Current electronic tender management does not have the necessary capabilities to automatically extract unstructured information on the tender document and hence, requires the decision maker to examine the information contained on the document one by one. In addition, the isolated tendering process leads to the ineffective communication between different stakeholders such as owners/clients, consultants, and contractors/suppliers to share and reuse information especially during decision-making. The increasing inconsistent and semantic heterogeneity information for the decision-making process requires the need to represent knowledge in a uniform format that is understandable to both humans and computers. Thus, the ontology-based decision support system architecture for tendering management is proposed to support information extraction and decision-making process. A prototype of ontology-based decision support system is developed using the case study of the construction tender evaluation process.
Action Design Research: a Case Study of Business Intelligence in Non-Profit Organizations
Authors: Mackrell Dale  , McDonald Craig
Published: February 2025

The needs of non-profit organizations for accountability are no less than that of for-profit or public sector organizations, yet typically they allocate resources to front-line activities rather than organizational systems. A research and development project is being conducted that aims to develop a conceptual framework which would guide organizations in the non-profit sector in improving their decision-making and reporting performance through the adoption of business intelligence solutions. This paper uses and reflects on Action Design Research, a contemporary socio-technical approach that draws on action research and design research, as a means for framing the project's processes, products, and context. This paper contributes to the understanding of Action Design Research by reflecting on what it reveals about the case study and how related theories for ‘design and action’ such as small wins and user participation can be brought into the Action Design Research framework.
DG-GPR: A Decision-Guided Group Package Recommender With Hybrid Condorcet-Instant Runoff Voting
Authors: Mengash Hanan  , Brodsky Alexander
Published: February 2025

This paper proposes a Decision-Guided Group Package Recommender (DG-GPR) framework, which provides recommendations on dynamically defined packages of products and services. This framework is based on: (1) defining the space of alternatives; (2) eliciting the utility function for each individual decision maker; (3) estimating the group utility function; (4) using the group utility function to find an optimal recommendation alternative; (5) constructing a set of diverse recommendations which contains the optimal recommendation alternative; and (6) applying a Hybrid Condorcet-Instant Runoff Voting method from social choice theories, to refine the recommendations. A preliminary experimental study is conducted which shows that the proposed framework significantly outperforms its previous extension which in turn had previously outperformed three popular aggregation strategies.
Consumers' collaborative innovation for supporting retailers' decision making: a new immersive approach for store design
Authors: Pantano Eleonora  , Migliarese Piero
Published: February 2025

Innovating is a prerequisite for competing also for retail sector and has attracted huge interest concerning the role of technology management for successfully adopting technology-based innovations. In this competitive scenario, the design of new and attractive retail environments able to better influence consumer decision-making process plays a critical role, with emphasis on stores characterized by large size (i.e. department stores, huge anchor stores, etc.). Despite the wide deal of research in involving consumers in the design process, identifying the best practices for achieving consumers' contribution to the co-design process has proven difficult. This study extents previous knowledge on consumers' involvement in collaborative innovation by focusing on retail environments, starting from the case study of a new collaborative platform devoted the design of a new store in Italy and the experimental design based on the response of 150 potential consumers. Empirical findings suggest a set of users' motives to participate to the development of the new store, by providing insights for defining novel tools for achieving more consumers' contribution with benefits for innovation and decision-making process.
Experiences with Building Modern Communication-Driven Decision Support
Authors: Stanek Stanislaw  , Drosio Stanislaw  , Namyslo Jacek
Published: February 2025

The paper aims to outline the possibility of using an integrated, computer assisted communication platform to improve crisis management processes. The authors draw on a previous paper contributed to the 2012 IFIP conference Fusing Decision Support System into the Fabric of the Context to indicate further evolution paths for crisis management support and to showcase a solution developed over the past two years, along with some of its applications.
Online Perspective-Taking as an Intervention Tool Against Cyberbullying
Authors: Van Den Broeck Evert  , Poels Karolien  , Vandebosch Heidi  , Van Royen Kathleen
Published: February 2025

This study will examine the use of an online role-playing experiment as a cyberbullying intervention tool. The study will be carried out among 14 – to 18-year old adolescents (N = 200). Respondents will be assigned a fictitious character and a role (perpetrator, victim or bystander) in a cyberbullying situation. They will be asked to identify with this character and act accordingly in an initiated mock, but realistic online bullying situation. We expect, based on role playing literature and bullying prevention programs, a positive change in the adolescents' behavioral intentions (e.g. defending a victim).
Enabling eHealth as a Pathway for Patient Engagement: a Toolkit for Medical Practice
Authors: Graffigna Guendalina  , Barello Serena  , Triberti Stefano  , Wiederhold Brenda K.  , Bosio A. Claudio  , Riva Giuseppe
Published: February 2025

Academic and managerial interest in patient engagement is rapidly earning attention and becoming a necessary tool for researchers, clinicians and policymakers worldwide to manage the increasing burden of chronic conditions. The concept of patient engagement calls for a reframe of healthcare organizations' models and approaches to care. This also requires innovations in the direction of facilitating the exchanges between the patients and the healthcare. eHealth, namely the use of new communication technologies to provide healthcare, is proved to be proposable to innovate healthcare organizations and to improve exchanges between patients and health providers. However, little attention has been still devoted to how to best design eHealth tools in order to engage patients in their care. eHealth tools have to be appropriately designed according to the specific patients' unmet needs and priorities featuring the different phases of the engagement process. Basing on the Patient Engagement model and on the Positive Technology paradigm, we suggest a toolkit of phase-specific technological resources, highlighting their specific potentialities in fostering the patient engagement process.
Positive Technology: A Free Mobile Platform for the Self-Management of Psychological Stress
Authors: Gaggioli Andrea  , Cipresso Pietro  , Serino Silvia  , Campanaro Danilo Marco  , Pallavicini Federica  , Wiederhold Brenda K.  , Riva Giuseppe
Published: February 2025

We describe the main features and preliminary evaluation of Positive Technology, a free mobile platform for the self-management of psychological stress (http://positiveapp.info/). The mobile platform features three main components: (i) guided relaxation, which provides the user with the opportunity of browsing a gallery of relaxation music and video-narrative resources for reducing stress; (ii) 3D biofeedback, which helps the user learning to control his/her responses, by visualizing variations of heart rate in an engaging 3D environment; (iii) stress tracking, by the recording of heart rate and self-reports. We evaluated the Positive Technology app in an online trial involving 32 participants, out of which 7 used the application in combination with the wrist sensor. Overall, feedback from users was satisfactory and the analysis of data collected online indicated the capability of the app for reducing perceived stress levels. A future goal is to improve the usability of the application and include more advanced stress monitoring features, based on the analysis of heart rate variability indexes.
Marketing Analysis of a Positive Technology App for the Self-Management of Psychological Stress
Authors: Wiederhold Brenda K.  , Boyd Chelsie  , Sulea Camelia  , Gaggioli Andrea  , Riva Giuseppe
Published: February 2025

The INTERSTRESS project developed a completely new concept in the treatment of psychological stress: Interreality, a concept that combines cognitive behavioral therapy with a hybrid, closed-loop empowering experience bridging real and virtual worlds. This model provides the opportunity for individual citizens to become active participants in their own health and well-being. This article contains the results of the Marketing Trial and analysis of the opinions of individual consumers/end users of the INTERSTRESS product. The specific objective of this study was to evaluate the feasibility, efficacy and user acceptance of a novel mobile-based relaxation training tool in combination with biofeedback exercises and wearable biosensors. Relaxation was aided through immersion in a mobile virtual scenario (a virtual island) featuring pre-recorded audio narratives guiding a series of relaxation exercises. During biofeedback exercises, a wearable biosensor system provided data which directly modified the virtual reality experience in real-time. Thirty-six participants evaluated the product and overall feedback from users was positive, with some variation seen based on participant gender. A larger market study is now underway to understand if there are cultural variations in acceptability of the device.
The Treatment of Hierarchical Criteria in Dominant AHP with Super Pairwise Comparison Matrix
Authors: Ohya Takao  , Kinoshita Eizo
Published: February 2025

We have proposed a super pairwise comparison matrix to express all pairwise comparisons in the evaluation process of the dominant AHP (analytic hierarchy process) or the multiple dominant AHP as a single pairwise comparison matrix. This paper shows the treatment of hierarchical criteria in the dominant AHP with super pairwise comparison matrix.
Modeling Facebook Posting Life-Cycle
Authors: Castro-Fonseca Joaquim  , Grilo Antonio
Published: February 2025

As Facebook becomes a quite relevant tool for companies marketing and sales it is important to analyze and understand posting activity. Propagation of relevant episodes in Facebook is quite fast and companies must not only plan, monitor and control the posting activities in their own Facebook page but also understand what is happening in their competitors Facebook. This paper presents a model and algorithm that allows the implementation of automated monitoring of Facebook posting activity, identifying normal and outliers in their activity, and hence enhancing companies' Facebook competitive intelligence. The model is validated with a data sample of 27924 public publications from the 550 companies Facebook pages.
An Extended Fuzzy-kNN Approach to Solving Class-imbalanced Problems
Authors: Xiong Zhigang  , Watada Junzo  , Xu Zhenyuan  , Wang Bo  , Tan Shing Chiang
Published: February 2025

In this paper, for solving imbalanced classification problem, more attention is placed on data points in the boundary area between two classes. The fuzzy k-nearest neighbors algorithm, which has good performance in conventional classification problems, is adapted here to solve imbalanced classification problems, where G-mean accuracy is used to evaluate our proposal method and compare it with other approaches.
Will Mail-Based Disaster Information Systems Work Well?: A Case Study in Japan
Authors: Tomoyasu Kota  , Wang Yuanyuan  , Kimura Reo  , Sumiya Kazutoshi
Published: February 2025

Japan's recent disaster response management planning efforts have focused on non-structural measures. Many local governments often disseminate evacuation information through mail-based disaster information systems. Local governments make evacuation announcements based on their best judgment, and after that, they disseminate these announcements further using e-mails. However, there are no format of mail-based disaster information systems, and it has proven difficult to disseminate the appropriate evacuation information at the right time. Further, there are no current studies focused on developing a more suitable and effective management of mail-based disaster information system. We intend to analyze problems associated with current disaster information systems?with the objective of being able to recommend improvements?by focusing on actual evacuation information dissemination processes of mail-based disaster information systems. We begin with a survey of the actual content and timing of text messages issued by local governments. In this way, we are able to identify differences between text messages and time delays in the dissemination of evacuation information by local governments. Our case study is based on a survey of the evacuation information dissemination processes used in the case of Typhoon Man-yi (2013).
Four Wheel Steering Advantageous for the Autodriver Algorithm
Authors: Marzbani Hormoz  , Ahmad Salahuddin Mohd Harithuddin  , Simic Milan  , Fard M.  , Jazar Reza N.
Published: February 2025

The autodriver algorithm was originally developed based on the dynamics of 4-Wheel-Steering (4WS) vehicles. The algorithm was transformed to be usable on 2WS vehicles which is more practical based on the existing steering systems for the vehicles on roads. The kinematic advantage of 4WS for the autodriver algorithm is presented. The steering angles required to keep the car on different roads have been calculated and compared for both steering types. One of the mentioned steering types is introduced as the superior steering arrangement for systems using the Autodriver algorithm.
Educating and Enhancing Compassion, Emotion and Reflective Professional Practice through Contemporary Digital Filmmaking
Authors: Patel Shreepali  , Toulson Rob
Published: February 2025

The use of artistic and contemporary digital filmmaking is explored as a educational tool for enhancing compassion, emotion and reflective professional practice in a healthcare environment. The case study film, The Golden Window, was produced specifically for this research and captures a unique insight into an advanced life saving technique for premature babies. The research shows that the artistic use of filmmaking and sound design brings an immersive audience experience that has caused practitioners to reflect on their professional practice in new ways, and specifically with respect to the compassion they show to patients and other staff. Furthermore, this method of filmmaking has been seen to engage new audiences and to inspire and educate the general public in a complex field of healthcare and science.
Wordling my Writing: Practices and Perceptions
Authors: Al Aamri Kamla Suleiman Salim
Published: February 2025

This paper is aimed to explore and use Wordle: data visualization tool as a facilitating teaching tool in EFL writing class. Wordle has been employed to carry out this action research project on English as Foreign Language (EFL) writing at the Language Centre of Sultan Qaboos University. It was used to generate word cloud analyses to discuss students' writing progress, strategies and lexical acquisition. Here in this study, the researcher positively postulated that Wordle is a very effective teaching tool in the writing class and that the incorporation of this technology medium in the composition class would enhance EFL students' writing and vocabulary skills. By conducting this project, electronic compositions, multiple drafts of students' writing were obtained over a course of one semester. The writing tasks covered certain rhetorical functions instructed over two blocks: four months in the Fall academic semester of the year 2014, including Cause and Effect, Compare and Contrast, and Opinion Essay. These students were freshmen doing their English writing course on the Foundation Programme they are placed on once they were admitted to the Sultan Qaboos University. The study also discussed other potential ways to use Wordle in the classroom as a smart learning component and concluded with some classroom implications and recommendations about using Wordle software in the EFL writing class. Key words. Visualization tool, Wordle, Word cloud, composition, vocabulary acquisition
Cancer Information Seeking Behaviors and Information Needs among Korean Americans
Authors: Park Hyejin  , Park Min Sook
Published: February 2025

Linguistically and culturally isolated Korean Americans have less access to health service and cancer screening tests than all U.S population. Lack of adequate cancer information is one of the barriers to undergoing cancer screening tests. It is necessary to understand their current cancer information-seeking behaviors and information needs if we are to more effectively provide adequate cancer information. The purpose of the study was to identify cancer information seeking behaviors and information needs among Korean Americans. Data were collected from one of the biggest websites for the Korean community in the USA. A total of 273 free-texts from January to June 2013 were reviewed and analyzed for this study. The extracted terms were categorized based on the coding system. The primary reason for asking questions was inquiry followed by sharing experiences. The main topics of the postings were categorized as medical or non-medical. In relation to types of cancer, breast cancer was the greatest concern. The findings from this study can help in establishing more effective strategies to provide better cancer information among Korean Americans by assessing their current cancer information seeking trends and information needs.
Automatic Generation of Nursing Narratives from Entity-Attribute-Value Triplet for Electronic Nursing Records System
Authors: Min Yul Ha  , Park Hyeoun-Ae  , Lee Joo Yun  , Jo Soo Jung  , Jeon Eunjoo  , Byeon Namsoo  , Choi Seung Yong  , Chung Eunja
Published: February 2025

The aim of this study is to develop and evaluate a natural language generation system to populate nursing narratives using detailed clinical models. Semantic, contextual, and syntactical knowledges were extracted. A natural language generation system linking these knowledges was developed. The quality of generated nursing narratives was evaluated by the three nurse experts using a five-point rating scale. With 82 detailed clinical models, in total 66,888 nursing narratives in four different types of statement were generated. The mean scores for overall quality was 4.66, for content 4.60, for grammaticality 4.40, for writing style 4.13, and for correctness 4.60. The system developed in this study generated nursing narratives with different levels of granularity. The generated nursing narratives can improve semantic interoperability of nursing data documented in nursing records.
Improving Inpatient Fall Prevention Strategies Using Interactive Data Repository Information System
Authors: Chen Lichin  , Yu Hui-Chu  , Lee Hung-Chang  , Chung Yufang  , Shang Rung-Ji  , Liu Hsiu-Yun  , Tan Ching-Ting  , Lai Feipei
Published: February 2025

Observing the pattern changes of inpatient fall and validating the Fall Prevention Tool Kit (FPTK) are essential for developing fall prevention strategies. However, the work requires the collection, calculation, and comparison of large amount of data. The information is often scattered in diverse information systems and lack of integration, which makes the work difficult and often neglected. This study demonstrates the development of an Interactive Data Repository System (IDRS) and uses it in the analysis of the pattern changes of inpatient fall within the institute, and validates efficiency of the FPTK across time. This study collected the incident data of year 2011 and compared it with the previous analysis in 2001. The result shows that reasons for patient fall had turned from physical disability to impaired conscious or cognition. The scoring result may be too sensitive in identifying patient falls. Patients with high scores needed to reinforce in functional strength.
Identifying Barriers for Implementation of Computer Based Nursing Documentation
Authors: Vollmer Anna-Maria  , Prokosch Hans-Ulrich  , Bürkle Thomas
Published: February 2025

This study was undertaken in the planning phase for the introduction of a comprehensive computer based nursing documentation system at Erlangen University Hospital. There, we expect a wide range of difficult organizational changes, because the nurses currently neither used computer based nursing documentation nor did they follow strongly the nursing process model within paper based documentation. Thus we were eager to recognize potential pitfalls early and to identify potential barriers for digital nursing documentation. In a questionnaire study we surveyed all German university hospitals for their experience with the implementation of computer based nursing documentation implementation. We received answers from 11 of the 23 hospitals. Furthermore we performed a questionnaire study about expectations and fears among the nurses of four pilot wards of our hospital. Most respondents stated a positive attitude towards the nursing process documentation, but many respondents note technical (e.g. bad performance of the software) and organizational barriers (e.g. lack of time).
Analyzing the tradeoff between efficiency and cost of norm enforcement in stochastic environments
Authors: Fagundes Moser Silva  , Ossowski Sascha  , Meneguzzi Felipe
Published: February 2025

In multiagent systems, agents might interfere with each other as a side-effect of their activities. One approach to coordinating these agents is to restrict their activities by means of social norms whose violation results in sanctions to violating agents. We formalize a normative system within a stochastic environment and norm enforcement follows a stochastic model in which stricter enforcement entails higher cost. Within this type of system, we provide an approach to analize the tradeoff between norm enforcement efficiency and its cost considering a population of norm-aware selfish agents.
Planning with Ensembles of Classifiers
Authors: Garbajosa Alberto  , de la Rosa Tomás  , Fuentetaja Raquel
Published: February 2025

Learning search control for forward state planning has been previously addressed as a relational classification task, where predictions are used to generate action policies. In this paper, we describe a new bagging approach to learn and apply ensembles of relational decision trees to generate more robust policies for planning. Preliminary experimental results demonstrate that new policies produce on average plans of better quality.
Probabilistic Argumentation with Incomplete Information
Authors: Hunter Anthony  , Thimm Matthias
Published: February 2025

We consider augmenting abstract argumentation frame-works with probabilistic information and discuss different constraints to obtain meaningful probabilistic information. Moreover, we investigate the problem of incomplete probability assignments and propose a solution for completing these assignments by applying the principle of maximum entropy.
Estimating Trust from Agents' Interactions via Commitments
Authors: Kalia Anup K.  , Zhang Zhe  , Singh Munindar P.
Published: February 2025

How an agent trusts another naturally depends on the outcomes of their interactions. Previous approaches have treated the outcomes in a domain-specific way. We propose an approach relating trust to the domain-independent notion of commitments. We conduct an empirical study to evaluate our approach, in which subjects read emails extracted from the Enron dataset (augmented with some synthetic emails for completeness), and estimate trust between each pair of communicating participants. We propose a probabilistic model for trust based on commitment outcomes and show how to train its parameters for each subject based on the subject's trust assessments. The results are promising, though imperfect. Our main contribution is to launch a research program into computing trust based on a semantically well-founded account of agent interactions.
Influencing Social Networks: An Optimal Control Study
Authors: Bloembergen Daan  , Ranjbar-Sahraei Bijan  , Ammar Haitham Bou  , Tuyls Karl  , Weiss Gerhard
Published: February 2025

We study the evolution of cooperation in social networks, aiming in particular at ways of influencing the behavior in such networks using methods and techniques from optimal control theory. This is of importance to many scenarios where politicians or policy makers strive to push consensus on some topic that may seem suboptimal from individuals' perspectives. To this end, we employ the Continuous Action Iterated Prisoner's Dilemma (CAIPD) as model for the interactions in a social network. This model describes how neighboring nodes influence each other, and in effect determines how different strategies may spread through the network. We extend this model, incorporating a mechanism for external influence on the behavior of individual nodes. Next we prove reachability of an arbitrary network-wide agreement using the Lyapunov's Direct Method. Based on the theory of Linear-Quadratic Trackers we propose a step-wise iterative control algorithm, and show the effectiveness of the proposed controller in various Small World and Scale Free social networks.
Unsupervised semantic clustering of Twitter hashtags
Authors: Vicient Carlos  , Moreno Antonio
Published: February 2025

Social micro-blogging networks such as Twitter provide an enormous amount of information, and their automated and unsupervised analysis constitutes an exciting research challenge in Artificial Intelligence. This work presents a novel methodology, based on a semantic clustering of the set of hashtags, which permits to obtain automatically the topics associated to a given set of tweets. A case study on the field of Oncology shows how the main topics of interest are successfully discovered.
Geometrical Feature Extraction for Cuneiforms
Authors: Richardson Ariella  , Smilansky Uzy
Published: February 2025

Cuneiform writing is one of the earliest methods of writing in human history. It is based on pressing a stylus (reed) on clay tablets, resulting in wedge marks (cuneiforms) which, when combined, provide meaningful symbols. Applying modern machine learning methods to the study of ancient cuneiform tablets is a fascinating task. In the present paper we describe a method for extracting geometrical features of the wedges imprinted by the stylus that is used for writing. We introduce two independent feature extraction methods to describe the wedges. The data for this study come from precise optical scans of three tablets, originating from different historical periods. We use these tablets to demonstrate the validity of our extracted features, and to demonstrate the accuracy of classifying the different tablets.