bluuebunny/crossref_metadata_2025 huggingface dataset:
Unveiling Originated Stages of Medication Errors: An Automated Pipeline Approach
Authors: Zhou Sicheng  , Kang Hong  , Yao Bin  , Gong Yang
Published: February 2025

Medication error has been a severe patient safety event in the United States. Medication error reports collected by Patient Safety Organizations provide an opportunity to analyze and learn from previous cases. However, the current process of analyzing the reports is labor-intensive and time-consuming. To improve the efficiency, we used automated text classification techniques to develop a pipeline for medication error report pre-analysis. The pipeline was proven functional in two tasks, i.e., identifying the non-preventable adverse drug events from medication error reports, and identifying the error originated stages during the medication distribution process. The proposed pipeline holds promise in helping clinicians understand the nature of medication error in an error report, and locate the potential root causes of the error, which could further facilitate to reduce medication errors in healthcare settings.
Exploring Health Information Technology Events from FDA MAUDE Database
Authors: Yao Bin  , Kang Hong  , Wang Ju  , Zhou Sicheng  , Gong Yang
Published: February 2025

To facilitate preventing patient safety events, researchers have been using the Federal Drug Administration (FDA) Manufacturer and User Device Experience (MAUDE) database as a publicly accessible data source for retrieving reports of medical devices including Health Information Technology (HIT) devices. A combined search strategy built with keywords in several fields such as Generic Name, Brand Name and Manufacturer is commonly used to extract reports of specific classifications of devices in the MAUDE. However, another structured field, Classification Product Code, is rarely visited. To improve the secondary usage of the MAUDE database in retrieval of HIT events, we extracted HIT reports from a nine-year MAUDE dataset by combining keywords filter and expert review, and explored Classification Product Codes. The distributions and relationships between Product Codes and keywords in Generic Name/Manufacturer in HIT reports were visualized to provide a view of the landscape. This study presents a new perspective for improving the search strategy of HIT events in MAUDEwhich would facilitate the understanding of HIT events for improving patient safety.
The Dimensions of Care: Big Data Analysis in Health Information Systems
Authors: Santamaría García José Ma  , Jiménez Rodríguez Ma Lourdes  , Gómez González Jorge Luis  , Batalla Marta Fernández  , González Aguña Alexandra  , Herrero Jaén Sara  , Cercas Duque Adriana  , Ramírez Sánchez Sylvia Claudine  , Melguizo Herrera Estela  , Condor Camara Daniel Flavio
Published: February 2025

The axioms of care postulate energy and time as underlying entities that allow us to study the dimensions of the person as care: the sorge. Logic allows to formalize the deductive study of sorge knowledge in order to determine what are the dimensions of care. These dimensions will be the guiding framework in the analysis of big data contained in health information systems.
Design and Implementation of a Robotic Software for the Assessment of Pain in Children
Authors: Nieto Franco Florentino
Published: February 2025

Pain in child population is presented as a vital process which produces a variation in capacities and needs of care. That pain has an impact on the child's develpoment and therefore on his self-care agency acquisition. That is why the care provided to people with these characteristics are presented as a priority for the nursing professional. From a disciplinary framework, the nursing professional appears as a figue with knowledge for the development of new technological tools (such as robotics) to treat pain in children. In this way, a robotic system that incorporates a program for the assessment of pain in children has been designed using deductive methodology and guided by Software Requirements Specification ANSI/IEEE 830. Finally, this robotic system was implemented according to the construction phases of an Expert System.
Forecasting Informatics Competencies for Nurses in the Future of Connected Health
Authors: Murphy Judy  , Honey Michelle  , Newbold Susan  , Weber Patrick  , Wu Ying (Helen)
Published: February 2025

This presentation will be in a workshop format with a panel of presenters representing four countries. All speakers are authors and will address various aspects from the content of the book published as a result of the NI 2016 Post Conference in Switzerland, Forecasting Informatics Competencies for Nurses in the Future of Connected Health [1], before inviting the audience to discuss and share their views. The discussion will be focused on defining the informatics competencies for nurses in practice and the requirements for informatics training in nursing programs around the world.
Developing Nursing Informatics Competencies for Future Nursing Leaders: An Overview of an Internship and Learning Plan
Authors: Strudwick Gillian  , Hubert Sheldon  , Gehrs Margaret
Published: February 2025

This poster will provide an overview of an internship and learning plan designed to support the development of relevant competencies for future nursing leaders. The internship activities were determined based on a learning plan to support the development of knowledge and skill from two informatics competency frameworks, and occurred over a period of six months. The intern engaged in a variety of projects, activities, and self-directed learning, which will be described in the poster.
Dataware for Improvement of Clinical Practice Quality in Phthisiology
Authors: Lugovkina Tatyana  , Gorshkov Sergey  , Tulkova Tatyana  , Svalov Evgeniy
Published: February 2025

A hot point of phthisiology in Russia during the last decade is the rising morbidity of tuberculosis associated with the drug resistant Micobacteria tuberculosis. The causes of MBT resistance are often related with human factor. Reducing the errors rate in complex Clinical Decision-making in phthisiology requires adequate software support and treatment monitoring. The methodology for structuring of the diagnosis characteristics at the moments of Clinical Decisions in phthisiology is represented. The Quality models and real Clinical Situations have the digital codes. The ontological modeling of the real Clinical Situations is used for analysis, construction the inference rules and improvement of Clinical Decisions and treatment results.
GIS Platform for Management of Diagnostic Examinations
Authors: Zarakovitis Dimitrios  , Tsoromokos Dimitrios  , Tsaloukidis Nikolaos  , Lazakidou Athina
Published: February 2025

Greece is one of the European countries with the largest number of CT and MRI scans. Geographic Information Systems (GIS) are a useful tool for efficient cost reduction in the health sector. ArcGIS software is used to create interpretable maps. Data represents the number of imaging examinations per type and population size. All available data is acquired in 2012–2015. By using special symbols, pop up windows emerge. The windows contain a large number of data. The results are filtered and uploaded to a digital control panel. This central information system combined with the digital maps form a digital platform for estimating the exact number of diagnostic examinations. The survey confirms that the General Hospital of Tripolis performed 27.000 CT examinations in 2012–2015, corresponding to approximately 57% of the population of Tripolis. The approximate percentage of CT scans of the Hospital Unit of Pyrgos was found 55%. The implementation of this platform confirms the large number of diagnostic examinations in most areas of Peloponnese.
Evaluation of a Laboratory e-Learning Course in Health Informatics
Authors: Zogas Spyros  , Birbas Konstantinos  , Chondrocoukis Gregory  , Mantas John
Published: February 2025

The current paper presents the students' evaluation of a laboratory e-learning course in Health Informatics. After attending the e-learning course, students assessed the e-learning course through an anonymous questionnaire. The study results present the positive attitude of the students towards the e-learning course in Health Informatics. The current e-learning course is easy to use, and it is preferred on the same extent as the hybrid one (e-learning and in-class learning combination). The majority of the participants believed that the e-learning method is at least the same or more efficient compared to the traditional learning approach. Based on the study findings, it seems that this e-learning course could offer important advantages on the learning process as long as it helps students learn in a more effective manner than traditional learning.
Data Collectors' Design Preferences for Mobile Electronic Data Capturing Forms
Authors: Mugisha Alice  , Krumsvik Ole Andreas  , Tylleskar Thorkild  , Babic Ankica
Published: February 2025

Data collectors collect health data using Mobile Electronic Data Collection Forms (MEDCFs) particularly in hard to reach areas. However, the usability and user acceptance of these forms by the data collectors are seldom considered, and yet these have an implication on the quality of the data collected and on the health decisions thereof. In this study we aimed at collecting the design preferences the data collectors felt would improve their data collection experience. For that purpose, a mid-fidelity prototype was used to accomplish six tasks and a semi-structured usability questionnaire was given. Forty eight data collectors from Uganda participated in the study between December 2017 and January 2018, indicating their preferences after interacting with the prototype. The results included a detailed feedback regarding the presentation of the forms content, form navigation, error handling, data input, and visualization of progress status. Involvement of users and other stakeholders in the design of MEDCFs using the User Centred Design (UCD) will presumably enhance usability of the data collection forms.
Mobile Learning in Nursing: Tales from the Profession
Authors: Mather Carey  , Cummings Elizabeth  , Gale Fred
Published: February 2025

During the last five years, research about mobile learning conducted with nurses, nurse supervisors and undergraduate students has provided insight into the complexity of this emerging issue, which has the potential to positively impact the workflow of nursing care and improve patient outcomes. Survey and focus group studies including confirmation of beliefs of nurses and nurse supervisors and interviews with representatives from nursing profession organisations were undertaken. Nursing student perspectives about mobile learning were also explored through an online survey. This paper draws on participant narratives from this research revealing ‘tales from the profession’, to demonstrate the complexity of installing mobile technology for learning at point of care for the benefit of healthcare professionals and their patients. This research demonstrates the urgency for introducing governance to provide guidance regarding safe and appropriate use of mobile learning at point of care. Teaching digital professionalism early in undergraduate nursing curricula and promotion of modelling digitally professional behaviour by nurses within healthcare environments is also imperative.
Recommendations for Enhancing the Implementation and Utility of Shared Digital Health Records in Rural Australian Communities
Authors: Almond H.  , Cummings E.  , Turner P.
Published: February 2025

Internationally, shared digital health records are becoming an important addition to improving contemporary healthcare provision. In 2012, Australia launched its version of a shared digital health record, My Health Record, but enrolment is slow and there remain challenges in its practical implementation. Further, people living with complex and chronic conditions in rural and remote communities often experience challenges in obtaining equitable access to contemporary healthcare provision, including eHealth services. This paper reports on research that explored the experience of and engagement with My Health Record, in a rural Australian community setting. Based on the key research findings, recommendations are presented for improving national roll out of My Health Record. The findings highlight, to understand and engage vulnerable communities and support their adoption and use of shared digital health records, there is a need to move away from traditional models of healthcare delivery toward person-centred care delivered from a digital complex adaptive systems perspective.
Verbal Probabilities: Linear or Logistic? – A Regression Analysis Approach
Authors: Ostermann Thomas  , Vogel Hannah  , Appelbaum Sebastian
Published: February 2025

Verbal probability expressions are quite intuitive and used in a variety of clinical important issues like adverse drug causality appraisal. However, there is insufficient evidence of their numerical meaning and whether they have a linear or logistic relationship with them. We aimed at contributing to answering these questions by means of a comparative regression analysis based on a sample of N=683 participants between 10 and 82 years (mean age 20.33±11.77; median: 18 years) who were asked to numerically rate a given set of sixteen verbal probability phrases on a visual analogue scale. With respect to the explained variance, we found an R2for the linear model of 0.574 while R2for the logistic model was only 0.392 indicating a superiority of linear model compared to the logistic model. Although we were able to show that ranked verbal phrases are more likely to behave in a linear that in a logistic way other regression options like the double logistic model should be taken into consideration for further research.
Data-Driven Assessment of Potentially Inappropriate Medication in the Elderly
Authors: Friedrichs Marcel  , Shoshi Alban  , Kleine Maren
Published: February 2025

Multimorbid patients taking polypharmacy represent a growing population at high risk for inappropriate prescribing. Various lists for identifying potentially inappropriate medication are spread across scientific journals and difficult to access. To address this ongoing need, a new database named PIMBase is developed which integrates these well-known lists and unifies their rating scales. The analysis of the pharmacovigilance data reveals the benefits of combining the lists. PIMBase is meant to be a web-based system and starting point for the data-driven assessment of polypharmacy to identify inappropriate medication and to improve the quality of prescribing. PIMBase is available at https://pimbase.kalis-amts.de.
What Are Inter-Professional eHealth Competencies?
Authors: Thye Johannes  , Shaw Toria  , Hüsers Jens  , Esdar Moritz  , Ball Marion  , Babitsch Birgit  , Hübner Ursula
Published: February 2025

As health IT supports processes along the entire patient trajectory and involves different types of professional groups, eHealth is inter-professional by nature. The aim of this study, therefore, is to investigate which competencies are at the intersection of the individual groups of health professionals. 718 international experts provided relevance ratings of eHealth competencies for different professional roles in an online survey. Communication and leadership proved to be important competencies across all professions, not only for executives. None or very little differences between professions were found between physicians and nurses, between IT experts at different levels and between IT experts and executives. However, there were a number of competencies rated differently when contrasting direct patient care specialists with executives. These findings should encourage organisations issuing educational recommendations to specify areas of shared competencies more extensively.
Practical Extension of Provenance to Healthcare Data Based on the W3C PROV Standard
Authors: Kock-Schoppenhauer Ann-Kristin  , Hartung Lina  , Ulrich Hannes  , Duhm-Harbeck Petra  , Ingenerf Josef
Published: February 2025

Secondary use of healthcare data is dependent on the availability of provenance data for assessing its quality, reliability or trustworthiness. Usually, instance-level data that might be communicated by HL7 interfaces entail limited metadata about involved software systems, persons or organizations bearing responsibility for those systems. This paper proposes a strategy for capturing interoperable provenance data needed by data stewards for assessing healthcare data that are reused in a research context. Aimed at a realistic level of granularity even system-level metadata will support a data steward trying to trace the origins or provenance of healthcare data that have been transferred to the research context. Those metadata are extracted from the 3LGM2-system, used for modelling hospital information systems. Based on the W3C provenance specification interrelated activities, entities and agents can be integrated and stored in RDF triple stores and therefore queried and visualized.
Samply.MDR – A Metadata Repository and Its Application in Various Research Networks
Authors: Kadioglu Dennis  , Breil Bernhard  , Knell Christian  , Lablans Martin  , Mate Sebastian  , Schlue Danijela  , Serve Hubert  , Storf Holger  , Ückert Frank  , Wagner Thomas  , Weingardt Paul  , Prokosch Hans-Ulrich
Published: February 2025

Collaboration in medical research is becoming common, especially for collecting relevant cases across institutional boundaries. If the data, which is usually very heterogeneously formalized and structured, can be integrated, such a collaboration can facilitate research. An absolute prerequisite for this is an extensive description about the formalization and exact meaning of every data element contained in a dataset. This information is commonly known as metadata. Various research networking projects tackle this challenge with the development of concepts and IT tools. The Samply Metadata Repository (Samply.MDR) is a solution for managing and publishing such metadata in a standardized and reusable way. In this article we present the structure and features of the Samply.MDR as well as its flexible usability by giving an overview about its application in various projects.
Social Media for Medical and Health Information: Malaysian Medical Tourism Hospital
Authors: Timan Hazila  , Kama Nazri  , Yusoff Rasimah Che Mohd  , Selamat Ali
Published: February 2025

Given the rapid development of Internet, social media opened up new opportunity for medical and health communications. Numbers of previous research conducted showed that social media shape up new chances to ensure an effective distribution of information in healthcare. Looking from the perspective of medical tourism, this study aimed to identify the availability of social media link in the medical tourism hospitals websites from Malaysia and evaluate their performance on every social media platform namely Facebook, Instagram, Twitter and YouTube. A list of 70 medical tourism hospitals gathered from the websites of Malaysian Health Travel Council (MHTC) http://www.mhtc.org.my. Each URL of the hospital identified and visited. The social media link availability on the website was observed and results showed that Facebook is the most preferable social media among the hospitals which is 51.4% followed by Instagram recorded as 14.3%. The Twitter recorded as 12.9% and YouTube only 11.4% hospitals. Most hospitals only provide one link to social media directly from their website. Astonishingly, almost half of the total medical tourism hospitals in Malaysia that is 44.2% does not have link to any social media on their websites. The top ten-hospital performance in Facebook rank gain more than 15000 “like” and “follows” at their page. Therefore, it was highly recommended for the medical tourism hospitals to actively engage with the social media and promote the link on their websites so that they can lead their current and prospective patients towards various information resources for a better distribution of medical and health information.
Comparing Two Approaches for Consensus Computation in Group Decision Making Problems
Authors: Del Moral M.J.  , Tapia J.M.  , Chiclana F.  , Herrera-Viedma E.
Published: February 2025

In group decision making problems, the soft consensus calculus is an important topic. Soft consensus measures are utilized to show the different agreement degrees between decisors. Using the concept of coincidence we have two main approaches to calculating soft consensus measures: concordance among expert preferences and concordance among individual solutions. In the first, the coincidence is obtained by evaluating the similarity among the expert preferences, while in the second one the concordance is derived from the measurement of the similarity among the solutions proposed by these decisors or experts. In this paper we perform a basic comparative study of consensus calculus based on both coincidence approaches. We use the nonparametric Wilcoxon signed-ranks test to compare these approaches. We obtain significant differences between both approaches for measuring consensus.
Leveraging Distributed Unit Test Case Execution for Java for Improving the Testing Process
Authors: Fuchs Andreas  , von Hof Vincent  , Neugebauer Matthias
Published: February 2025

Software testing is a broad research field and of great relevance to practitioners. Software testing involves multiple consecutive testing phases. One of these phases is the unit-testing phase, during which individual requirements of the software component are checked. Only once software-units and -components have been tested, can the testing process continue. Trivially, if this phase requires a great amount time, the testing process is delayed and in the worst case, the rollout of the system has to be rescheduled. Focusing on the widely adopted JUnit test framework, a system was proposed to execute test cases on multiple distributed virtual machines. This paper evaluates the approach to distribute such test cases across multiple Java Virtual Machines (JVMs), leveraging container-based virtualization, by means of a prototype. The distribution achieves a significant runtime decrease. Furthermore, the effect of different distributions strategies on the overall runtime is evaluated.
Evaluating Aspect-Based Sentiment Classification on Twitter Hate Speech Using Neural Networks and Word Embedding Features
Authors: Zainuddin Nurulhuda  , Selamat Ali  , Ibrahim Roliana
Published: February 2025

In this paper, a neural network is proposed to analyse Twitter sentiment classification for the Twitter domain. The study examines and evaluates the performance of neural networks with word embedding features in Twitter sentiment classification. Four benchmark datasets were used to represent different domains. The results indicated that the proposed method significantly improves the accuracy of the neural network classifier compared to existing works in aspect-based sentiment classification, especially for the highly imbalanced dataset.
Automating Question Generation and Marking of Language Learning Exercises for isiZulu
Authors: Gilbert Nikhil  , Keet C. Maria
Published: February 2025

Increase in isiZulu language learning is hampered by the predominantly manual approach to creating and marking homework and test exercises. Extant computer-assisted language learning platforms cannot handle the intricacies of agglutination in isiZulu and related languages. We seek to address this by designing a controlled natural language-based exercise generator and marker for isiZulu. This consists of question and answer sentence templates for exercise types, reusable algorithm snippets as grammar library, a small corpus of words and sentences to be used by the system, a constrained sentence generator to combine the right type of words, and finally the exercise creation and automated marking system. The preliminary evaluation shows encouraging results.
The Identity of Dispositions
Authors: Barton Adrien  , Grenier Olivier  , Jansen Ludger  , Ethier Jean-François
Published: February 2025

Clear criteria for the identity of dispositions are still lacking, and this has been presented as one of the main challenge raised by such entities. It is of prime importance to identify or distinguish dispositions such as diseases or risks. This article first introduces conventional ways to refer to a disposition (such as “fragility”) and canonical ways (such as “disposition to break in case of a strong shock”). This raises the issue of how should exactly be defined a “disposition d to R when TR”, where R is a realization specification and TR a trigger specification. Two ontological frameworks are distinguished. The first framework, which has been largely used so far in the literature on dispositions, interprets d as a disposition which can only be triggered by instances of TR, and can only be realized by instances of R. The second, new framework introduces the notion of “minimal trigger” and “maximal realization”, and interprets TR as a parent class of a class of processes that have as part a minimal trigger, and R as a parent class of a class of processes that are parts of a maximal realization. We then discuss several criteria of identity, including the criterion according to which two dispositions are identical iff they have the same categorical basis, the same class of minimal triggers and the same class of maximal realizations. We show on several examples that the second framework avoids the disposition multiplicativism that is introduced by the first framework.
Organisations and Variable Embodiments
Authors: Ferrario Roberta  , Masolo Claudio  , Porello Daniele
Published: February 2025

How can organisations survive not only the substitution of members, but also other dramatic changes, like that of the norms regulating their activities, the goals they plan to achieve, or the system of roles that compose them? This paper is as first step towards a well-founded ontological analysis of the persistence of organisations through changes. Our analysis leverages Kit Fine's notions of rigid and variable embodiment and proposes to view the (history of the) decisions made by the members of the organisation as the criterion to re-identify the organisation through change.
On Decomposition Operations in a Theory of Multidimensional Qualitative Space
Authors: Hahmann Torsten
Published: February 2025

Mereotopological relations, such as contact, parthood and overlap, are central for representing spatial information qualitatively. While most existing mereotopological theories restrict models to entities of equal dimension (e.g., all are 2D regions), multidimensional mereotopologies are more flexible by allowing entities of different dimensions to co-exist. In many respects, they generalize traditional spatial data models based on geometric entities (points, simple lines, polylines, cells, polygon, and polyhedra) and algebraic topology that power much of the existing spatial information systems (e.g., GIS, CAD, and CAM). Geometric representations can typically be decomposed into atomic entities using set intersection and complementation operations, with non-atomic entities represented as sets of atomic ones. This paper accomplishes this for CODI, a first-order logic ontology of multidimensional mereotopology, by extending its axiomatization with the mereological closure operations intersection and difference that apply to pairs of regions regardless of their dimensions. We further prove that the extended theory satisfies important mereological principles and preserves many of the mathematical properties of set intersection and set difference.
Identity Criteria for Localities
Authors: Garbacz Pawel  , Ławrynowicz Agnieszka  , Szady Bogumił
Published: February 2025

The paper provides a tentative formulation of the diachronic identity criteria for localities based on a set of paradigmatic case studies of changes they may undergo.
Low-Resource Translation Quality Estimation for Estonian
Authors: Yankovskaya Elizaveta  , Fishel Mark
Published: February 2025

Quality estimation is an essential step in applying machine translation systems in practice, however state-of-the-art approaches require manual post-edits and other expensive resources. We introduce an approach to quality estimation that uses the attention weights of a neural machine translation system and can be applied to a translation produced by any machine translation system; a lighter version of the approach does not even require any post-edits. Our experiments with German-Estonian and English-Estonian translations show that its performance matches the state-of-the-art baseline.
A Fuzzy Learning Method to Segment Visitors of a Tourist Attraction
Authors: Nguyen Jennifer  , Armisen Albert  , Sánchez-Hernández German  , Agell Núria  , Angulo Cecilio
Published: February 2025

We propose in this paper a method which segments demographic and contextual attributes of tourists when visiting an attraction. Clustering patterns based on categorical attributes can be challenging as it is difficult to define a distance between two categorical attributes where a natural order does not exist. Our proposed measure, based on a fuzzy aggregation operator, can be easily implemented in a hierarchical agglomerative clustering algorithm. The method has been implemented in a particular tourist attraction example with 2937 visitors.
Implementing CDS Hooks Communication in an Arden-Syntax-Based Clinical Decision Support Platform
Authors: Spineth Martin  , Rappelsberger Andrea  , Adlassnig Klaus-Peter
Published: February 2025

Introduction: Arden Syntax is a Health Level Seven International standard for the development of clinical decision support (CDS) solutions. CDS Hooks is a specification for an interface to call CDS services from an electronic health record. Implementing the CDS Hooks interface into ArdenSuite, an Arden-Syntax-based CDS platform, will further enhance its interoperability with external systems.
KITE: An Analytics Platform for Multimorbidity Management
Authors: Tommasi Pierpaolo  , Pascale Alessandra  , Deparis Stéphane  , Kotoulas Spyros
Published: February 2025

Managing multimorbidity entails processing distributed, dynamic and heterogeneous data using diverse analytics tools. We present KITE, a Cloud-based infrastructure allowing the aggregation and processing of health data using a dynamic set of analytical components. We showcase KITE in the context of the ProACT project, aiming at advancing home-based integrated care though IoT, analytics and a behavior change framework. We validate the viability of the infrastructure through an application of Bayesian networks to give a probabilistic representation of older individuals based on a variety of factors.
Greensboro College: A Model of UDL in the Curriculum
Authors: Bodgan Georgieann  , Pass Ilari
Published: February 2025

Developed at the North Carolina State University College of Design in the 1980s, a group of architects, product designers, engineers, authors and environmental design researchers, collaborated to establish the Principles of Universal Design to guide a wide range of design disciplines including environments, products, and communications [1]. Universal Design for Learning (UDL) is a research-based set of principles intended to guide the design of learning environments that are accessible and effective for all. First articulated by CAST (Center for Applied Science and Technology) in the 1990s and now the leading framework in an international reform movement, UDL informs all of our work in educational research and development, capacity building, and professional learning. UDL is based on cognitive neuroscience and is intended to guide the development of flexible learning environments that can accommodate individual learning differences [2]. UDL asks educators to create curricula that provide: multiple means of representation, multiple means of expression and multiple means of engagement, while motivating all students to learn and succeed [3]. Greensboro College is unique in higher education in that it has committed to fully embracing UDL. Greensboro College uses UDL as a framework for successful academic and student development at a small, private, Methodist-affiliated, liberal arts college. Greensboro College has initiated its transformation to an institution that values and facilitates UDL across its curriculum. As The Mission Statement of Greensboro College points out, we as a college believe “Universal Design for Learning, at its core is a comprehensive educational framework that removes barriers to student learning and academic success. The principles of UDL recognize that variance in learning ability and style among individuals is the norm and not the exception. Therefore, curricula should be adaptable to individual learning differences rather than the other way around” [4]. Greensboro College has taken its first steps towards providing a learning environment for all students, which can be used as a model for launching a UDL initiative at a small, liberal arts, private college [5].
Regulatory Intermediaries: The Role of Interest Organizations in Supporting Web Accessibility Policy Implementation
Authors: Giannoumis G. Anthony
Published: February 2025

This article explores how interest organizations, including non-profit and commercial service providers, act as intermediaries to support the implementation of regulations for web accessibility. Web accessibility policies promote the usability of web content for persons with disabilities. Previous research on relational regulation has focused on the bidirectional relationship between regulators and private enterprises in managing compliance. However, this research has yet to examine the complex relationships that emerge when interest organizations act as intermediaries between private enterprises and regulators. Previous research demonstrates that intermediaries translate and adjust legal obligations in practice. This article demonstrates that interest organizations in the United Kingdom, United States and Norway translated and adjusted legislation and standards to demonstrate the commercial value of compliance. This article extends previous research by suggesting that interest organizations act as intermediaries to support policy implementation and manage compliance.
Housing Design for the Ageing: Struggle Toward Supporting Age-in-Place Instead of Special Housing for Seniors
Authors: Kose Satoshi
Published: February 2025

With the global trend of population ageing, efforts are in progress in many countries to cope with the problems associated with it. As one grows older, his/her capabilities gradually deteriorate. What need to be done to mitigate mismatch of dwelling design, and to enable age-in-place? A comparative study of design guidelines in Japan, UK and USA is conducted to find out challenges and opportunities we are faced with. In Japan, design guidelines for the ageing society were proposed in the early 1990s, and they have been used ever since in several contexts. Although they were not mandatory, policy-linked incentives have worked to some extent. In the UK, Lifetime Homes concept has been formulated, and it seems to have gained momentum with its adoption in the Approved Document M. In the USA, Fair Housing Amendment Act in 1988 [5] introduced requirements on wheelchair accessibility on rental sector, and Visitability concept, less stringent than liveability, is being adopted in some localities. Although wheelchair accessibility is not the same as design for the ageing, most of the issues are shared. What are the problems we still face with, revealed from the survey? First is the time lag between acquisition of the dwelling versus one's senior years, which sometimes extends to 40 years. Second, many of the dwellings are already built with lower standards than desirable, not as new construction. Third, home modification quite often lacks financial support through government policy. This presentation will give some proposals toward improvement over the situation.
Marrying Digital and Analog with Generation Z: Confronting the Moral Panic of Digital Learning in Late Modern Society
Authors: Alvi Shahid
Published: February 2025

In some quarters, the implementation of digital technologies continues to be touted as the solution to educational challenges faced by contemporary post-secondary instructors and their students. In this paper, I examine the veracity of the claims made by the purveyors of “edu-tech,” particularly in relation to what we know about learning and in light of the characterization of traditional pedagogical strategies as vestigial. The arguments advanced in that context include the ideas that “digital natives” no longer can be taught effectively by “digital immigrants,” that instructors must “meet students where they live,” and that changes to pedagogy go hand in glove with an understanding of the putative characteristics of today's young learners. I argue that such claims are at best inconsistent with the evidence, that major structural issues have been ignored thereby framing debates far too narrowly, and that the political and economic consequences of neoliberalism must be taken seriously if education is to be of any value, going forward. The paper offers a third, “medium” way which highlights what we know about literacy, what technology can and cannot reasonably offer, and how “analog ways” can contribute to the intellectual and social development of post-secondary students. Finally, I advance the idea that serious evaluation and implementation of such an approach might help to eclipse the “moral panic” characterizing today's educational discourse.
Lighting Design as a Universal Design Strategy to Support Functional Visual Environments
Authors: Mathiasen Nanet  , Frandsen Anne Kathrine
Published: February 2025

The visual environment that surrounds us all makes us able to understand and interpret the world we live in. One of the most important players in that field is light. In general, it is useful for all of us to have aesthetic, appropriate and well-functioning lighting conditions. Research has shown that when it comes to visually impaired and hearing-impaired people it is of crucial importance in order to make their daily lives work and being self-reliant. Based on this research rules and regulation in a Danish context is studied to see how lighting design can support Universal Design in general and the specific users need in particular as described in the user organisations guidelines to accessibility. The regulations often focus on the quantitative aspects like light levels and the uniformity of the light. They certainly are important aspects however, they are not sufficient for users with specific needs. This point to the need for a broader approach to lighting design where the quantitative aspects meet the qualitative in order to fulfil a successful Universal Design of the visual environment. This paper present a general discussion on lighting design strategies and their impact on aesthetics and functionality of the visual environment based on classic theories on lighting design describe by Richard Kelly, William M. C. Lam and Hervé Descottes. These strategies are put in relation to the overall concept of the Universal Design principles and the guidelines outlined by The Danish Association of the Blind to support a visual stimulating environment.
A Heuristic Algorithm to Eliminate Edges for TSP
Authors: Wang Yong  , Geng Chang Xin  , Wu Yi Wen
Published: February 2025

A heuristic algorithm is provided to trim many edges for reducing the search space of traveling salesman problem (TSP). The heuristic algorithm is designed according to a probability model and the fuzzy numbers plays an important role to enhance the performance. The heuristic algorithm may lose a few edges in some optimal solutions if the parameter N is too small or F is too big in the algorithm. Since we are not sure whether all optimal solutions in the original graph are trimmed, the best and worst solutions in the preserved graphs are not proven. The experimental results demonstrate that the heuristic algorithm computes a residual graph with less than nlog2n edges for most of the TSP instances in the TSPLIB. Thus, the computation times of algorithms for TSP will be greatly reduced when these TSP instances on sparse graphs are resolved.
A Clustering-Based User Reputation Evaluation Approach for Web Service Recommendation
Authors: Su Kai  , Su Xiaoguang  , Yang Lihua  , Xiao Bin
Published: February 2025

In web service recommender systems, users are always asked to provide their observed QoS data to assist the personalized QoS prediction for other users. Most existed approaches assume that all the users will provide real data to the system, however the dishonest users may be appeared in many recommender systems. Attracted by commercial benefit, some users may intentionally provide unfair feedback inconsistent with their real experience, which will harm to the robustness of service recommender system. In this paper, we propose a clustering-based reputation evaluation approach to identify the dishonest users. Firstly, we calculate the trustworthy cluster on each service by Clustering of users' QoS feedback. Then the feedback of users will be classified according to their deviation degree from the trustworthy cluster. Finally, according to the users' statistic feedback information, we apply Beta reputation model to evaluate users' reputation dynamically. Experimental results demonstrate that this approach can accurately evaluate users' reputaion compared to other state-of-the-art approaches.
Multi-Granularity Variable Precision Soft Rough Set
Authors: Wang Xiaomin  , Cheng Weiwei  , Liu Huiyuan  , Zhang Lichao
Published: February 2025

This paper briefly introduces the basic concepts of rough sets, and then introduces some current research status of rough sets. Based on this, a multi-granularity variable precision soft rough set (MGVPSRS) is proposed and some related properties are given. Then a new reduction algorithm is proposed by using the multi-granularity variable precision soft rough set model and applied to the weather classification problem.
Modeling of Wire Isolation System Based on Finite Element and Neural Network
Authors: Zhao Heming  , Ding Mingjun  , Hu Xiaoling  , Zhang Hailiang
Published: February 2025

In order to reduce the computational difficulty by reducing the degree of freedom nonlinear system modeling wire isolator ,proposed a hybrid finite element modeling and neural network convergence. According to the method, linear structure parts of the wire isolator system use the finite element modeling and nonlinear structure parts or the parts difficult to use mechanism modeling use neural network description. Secondly, the finite element model part can be combined with the neural network model through the force and displacement boundary conditions and get a hybrid model of the whole system which has clear physical structure. Sine and broadband random excitation be predicted,tested and analyzed by the hybrid model with good results. The hybrid modeling method provides an effective way for the nonlinear dynamic system with the linear elastic structure as the main structure and the strongly nonlinear devices.
Re-Extraction of Deep Learning Features with Applications to Speaker Recognition
Authors: Li Tian-xing  , Zheng We-ijie  , Ma Tao  , Man Boqi  , Han Lv  , Jia Xiao-ning  , Shi Shan-zhi  , Zhou Lin-hua
Published: February 2025

In this work, the authors propose a method for re-extracting deep learning features. By the approach of “Separation Statistics”, one can obtain a criterion of the principle of “Intraclass Aggregation and Interclass Dispersion”, so as to realize the re-extraction of the “deep learning” features. The re-extraction algorithm is applied to speaker recognition, and the experimental results indicate that the re-extracted deep learning features can effectively improve the accuracy of the speaker recognition. The findings reveal a fact that, although one can obtain more information depend on the deep learning, not all of the “more abstract” or “more deeper” features have positive effect on the task of recognition and classification, one should focus on the most important features rather than more features.
Low-Power Appliance Recognition Using Recurrent Neural Networks
Authors: Pratama Azkario R.  , Simanjuntak Frans J.  , Lazovik Alexander  , Aiello Marco
Published: February 2025

Indoor energy consumption can be understood by breaking overall power consumption down into individual components and appliance activations. The classification of components of energy usage is known as load disaggregation or appliance recognition. Most of the previous efforts address the separation of devices with high energy demands. In many contexts though, such as an office, the devices to separate are numerous, heterogeneous, and have low consumptions. The disaggregation problem becomes then more challenging and, at the same time, crucial for understanding the user context. In fact, from the disaggregation one can deduce the number of people in an office room, their activities, and current energy needs. In this paper, we review the characteristics of office appliances load disaggregation efforts. We then illustrate a proposal for a classification model based on Recurrent Neural Network (RNN). RNN is used to infer device activation from aggregated energy consumptions. The approach shows promising results in recognizing 14 classes of 5 different devices being operated in our office, reaching 99.4% of Cohen's Kappa measure.
Application of Super-Resolution Techniques to Transmission Electron Microscopy Images
Authors: Bárcena-González G.  , Guerrero-Lebrero M.P.  , Guerrero E.  , Reyes D.F.  , Nuñez-Moraleda B.  , Rivas-Sánchez M.  , Yañez A.  , González D.  , Galindo P.L.
Published: February 2025

Super-resolution (SR) methodologies allow the construction of high resolution images from several noisy low-resolution images. This methodology can be applied to overcome the inherent resolution limitation and improve the performance in digital imaging of scanning transmission electron microscopes (STEM). Here we apply SR to column resolved images of a monocrystalline GaAs/InAs quantum dot covered by a GaAsSb capping layer. Series of 8 images with a dwell time of 1s were taken to apply SR. The improvement of the SR images has been evaluated in terms of SNR and spatial reliability by comparison of images captured with a dwell time of 8s. The results indicate that the SR technique emerges as a remarkable and powerful tool for the improvement of the quality of the STEM imaging.
Distances Between Tensor Subspaces
Authors: Itoh Hayato  , Imiya Atsushi  , Sakai Tomoya
Published: February 2025

Sampled values of volumetric data are expressed as three-way array data, which is expressed as tensors. We are required to process and analyse volumetric data without embedding into higher-dimensional vector space from the viewpoints of object oriented data analysis. Multi-way forms of volumetric data require quantitative methods for the discrimination of multi-way forms. Therefore, we define a distance metric for subspaces of multi-way data arrays using transportation between the Stiefel manifolds constructed by subspaces of multi-way data arrays.
Evaluation of Patterns for Mobile User Interface Enhancement
Authors: Pušnik Maja  , Ivanovski Dimitar  , Welzer Družovec Tatjana  , Šumak Boštjan
Published: February 2025

In the paper, we explore the topic of mobile user experience and we focus on native mobile applications. The goal of this paper is to research what mobile user experience is, identify important mobile patterns, and define processes and guidelines for the design and measurement of the mobile user experience and the identified mobile patterns. Based on the literature review, there are several elements or factors affecting the mobile user experience. We established a big advantage of native applications, which are designed for a specific platform, where there is more time to create a specific customer experience. The main findings of the paper showed that the mobile user experience differs from the desktop user experience, and that there are many mobile patterns, which may significantly improve or degrade the mobile user experience for various target groups.