bluuebunny/crossref_metadata_2025 huggingface dataset:
Co-Creation of an Innovative Vocational Training Platform to Improve Autonomy in the Context of Alzheimer's Disease
Authors: Billis Antonis  , Mantziari Despoina  , Zilidou Vasiliki  , Bamidis Panagiotis D.
Published: February 2025

Support of autonomy, at the onset and while Alzheimer's Disease progresses, is of utmost importance for both older adults and their caregivers. AD-Autonomy project aims at co-creating an innovative training platform with and for elderly people and their caregivers. Main aim of the project is to increase the competencies of older adults and their caregivers to cope with the disease effects, by leveraging existing ICT tools and applications, while transferring their applicability in real life contexts and activities. Initial anecdotal feedback is collected through a co-creation session, where all above themes were discussed and analyzed between seniors, family caregivers and professionals.
Advantages of Modular Hybrid Network Communication on Clinical Wards
Authors: Jähne-Raden Nico  , Gütschleg Henrike  , Wolf Marie Cathrine  , Wolf Klaus-Hendrik
Published: February 2025

The ever-increasing flood of information, especially in the medical-clinical field, inter alia due to the increase of data-intensive mobile/wearable devices, is one of the biggest challenges of medical informatics. In this work different possibilities of the integration of wearable devices on the example of the development of a fall prevention system are presented and classified. We started with a commercial off-the-shelf one-on-one system (Shimmer/Arduino) using a Bluetooth connection, integrated via nurse call system as Human-Machine-Interface. During the evaluation of the system we mentioned several new requirements and optimization possibilities. Thus, we adjusted the hardware-software-system; the near-field communication was realized by IEEE802.15.4, we replaced commercial off-the-shelf devices with highly-specialized open hardware in-house developments and we transferred the nurse call integration by setting up our own network and integrating this into an existing (wireless) local area network. With this development, the energy-efficient, simple and intuitive mechanisms of proximity communication via IEEE802.15.4 can be combined with the benefits broadband functionalities, e.g. of Wi-Fi, with both worlds benefits and the compensation of some disadvantages.
Understanding Episodes of Physical Activity at Work Using Fitbit® Data
Authors: Van Kasteren Yasmin  , Maeder Anthony  , Perimal-Lewis Lua
Published: February 2025

For office workers as much as much as 77% of time at work is spent in sedentary behaviour, increasing the risk of cardio vascular disease, cancer, weight gain, obesity and musculoskeletal pain. Given the amount of time spent at work, increasing opportunities for moderate to vigorous physical activity for office workers can not only reduce risk of disease but also actively contribute to better brain function and reduced anxiety at work. In this research we adopt an ecological approach to understanding opportunities for physical activity at work. Using 1373 Fitbit data points from two collocated office workers with identical job descriptions, we demonstrate that episodes of movement in the office are of very short or short duration. Results were less clear for sedentary behaviour because of the potential for spurious step counts and the fact that accelerometers cannot distinguish between sitting and standing. The paper shows the limitations and potential of data from Fitbit devices as a means of understanding the opportunities and constraints of the organisational and physical environment for physical activity at work for office workers.
The Impact of M-Health on the Self-Management of Diabetes: A Preliminary Study
Authors: Chang Hsiao-Yun  , Chang Huai-Lu  , Chen An-Chi  , Yen Chiao-Hsuan
Published: February 2025

Apart from drug control, diabetes management should pay more attention to how lifestyle and daily routine affect blood sugar. This study aimed to explore the impact of m-health programme using a minimal psychological intervention on diabetes patients' knowledge, behavioural, and psychological health. A pretest-posttest single-group pre-experimental study was undertaken with 30 individuals to recruit patients with diabetes. A total of 22 participants completed the 10-week online programme. The pretest-posttest results demonstrated the differences in health behaviour, including foot care, diet control, and exercise. The adoption of m-health that changed and improved patient's self-care; however, the acceptance of using m-health remains a challenge for public dissemination.
Quro: Facilitating User Symptom Check Using a Personalised Chatbot-Oriented Dialogue System
Authors: Ghosh Shameek  , Bhatia Sammi  , Bhatia Abhi
Published: February 2025

Automated conversational agents built with medical applications in mind, have the potential to reduce healthcare readmissions and improve accessibility to medical knowledge. In this work, we demonstrate the development and evaluation of an automated chatbot for triage and conditions assessment, based on user inputs in natural language. The implemented bot engages patients in conversation about symptoms experienced and provides a personalized pre-synopsis based on their symptoms and profile. Our chatbot system was able to predict user conditions correctly based on two sets of patient test cases with an average precision of 0.82. Our implementation demonstrates that a medical chatbot can help with automatic triage and pre-assessment of patients with simple symptom analysis and a conversational approach without the use of cumbersome form-based data entry.
Predicting Matching Quality of Record Linkage Algorithms on Growing Data Sets
Authors: Schuster Martin  , Tittmann Lukas  , Wolf Andreas
Published: February 2025

A record linkage algorithm tries to identify records which belong to the same individual. We analyze the matching behavior of an approach used in the E-PIX matching tool on the very limited attribute set of first name, last name, date of birth and sex. Our benchmark set contains almost 37,000 records from the Popgen biobank. We develop a model which allows us to predict the workload on clerical review for data sets growing up to a factor of 10 or even more, without the need for a data set of this size. Based on this model we show two parameter sets with comparable detection rate of true duplicates, but where only one of them scales well on growing data sets. Our model provides realistic example records for each predicted matching of an upscaled data set. Thus, it enables to identify the parameters which need to be adjusted in order to improve the quality of the matching candidates. We also show that unreviewed merging of records is prone to homonym errors on data sets with 200,000 records and the limited attribute set above, while the merged record pairs are obviously different in clerical review.
SinCRY: A Preventive Defense Tool for Detecting Vulnerabilities in Java Applications Integrating Cryptographic Modules
Authors: Fattahi Jaouhar  , Couture Mario  , Mejri Mohamed
Published: February 2025

Detecting security vulnerabilities in existing applications is a hard task. Tools to accomplish this task are not only rare but often proprietary, expensive, and not always efficient. Moreover, many of the existing tools fail to discover security vulnerabilities inside applications integrating cryptographic functionalities, since it is difficult for the inspecting software to surmount the barriers of cryptographic keys, primitives and algorithms. It is particularly tedious to cope with cryptographic protocols that may be implemented inside the inspected application. In this paper, we introduce a new tool—SinCRY—designed to inspect Java applications that implement cryptographic protocols and modules. First, we present this tool. Then, we carry out a full inspection of a legacy-like test application using this tool along with SinJAR, another static tool for inspecting Java applications through their Jar files.
Context Sampling Strategies for Generating Linked Data Graph Embeddings
Authors: Terziev Yordan  , Gruhn Volker
Published: February 2025

Linked data is a data publishing method that can be used to connect any kind of globally available data into a single multigraph. This kind of graph provides enormous opportunities for machine learning and data mining techniques to train models with large heterogenous types of data and find new relationships. Both are however strongly dependent on the engineering of high quality features and therefore requires knowledge of the domain. Recent advances in the field of representation learning has led to significant progress in automating the feature engineering process. Neural word embedding techniques from the natural language processing domain have been used to learn representations of graph nodes and subsequently applied to linked data nodes. In contrast to natural language where sentences serve as natural boundary for the context of a word, in a graph – boundaries are not clearly defined and multiple context sampling strategies exist. Applying different context sampling strategies on graph nodes result in different context sentences and subsequently different features. In this work, we explore two different context sampling strategies: predicate removal from random walks as well as breadth first search based sampling and compare them to the state of the art based on random walks. The quality of the generated features is evaluated indirectly by measuring the performance of machine learning models on a classification task across multiple data sets. Furthermore, we explore the effect of generating embeddings only for the entities that have to be classified and their neighbors, instead of generating embeddings for every node in a possibly large RDF graph. The results suggest that for classification of same typed entities the inclusion of predicates in the sampled walks for generating embeddings is of little use and can be omitted without losing classification accuracy. Results also show that the in-degree and out-degree of the entities may be useful hint for selecting the optimal sampling technique.
Developing a Cyber-Physical Autonomous and Distributed Intersection Management – A Software Engineer's Experience Report
Authors: Gries Stefan  , Meyer Ole  , Ollesch Julius  , Wessling Florian  , Hesenius Marc  , Gruhn Volker
Published: February 2025

Developing CPS means uniting multiple engineering disciplines: mechanical, electrical and software engineering. Each of them provides a set of models, guidelines and processes crucial for a projects success. Consequently, CPS development is heavily influenced by processes known in either engineering discipline. There is currently no coherent software engineering approach to develop CPS, making it very hard to align the aforementioned domain experts in a controlled and repeatable process. This paper takes a step towards filling this gap by providing the insights during the development of a CPS in the form of an experience report. Based on our findings we validated the use of the Double TwinPeaks model and contribute to the field of software engineering for CPS the Matrix of Granularity to assess the components of a CPS in terms of customizability, risk and constraints.
A Study on Forecasting the Success of Software Projects
Authors: Buharali Olcaysoy Ayşe  , Biricik Göksel  , Taysi Ziya Cihan  , Kalipsiz Oya
Published: February 2025

Projects in software engineering have very low success rate compared to other engineering areas. This rate can be increased by building a better project plan with the help of project success forecasting tools. These tools employ prediction methods, which use time, budget and scope to perform estimations and they can only be used in late phases of the project. In this study, we proposed a new approach, which is capable of forecasting the project success in the initiation or the analysis phase of the project. In order to achieve this, we utilized sponsor score, which reflects the business outcomes of a project, as a metric. We also derived several features of these projects and evaluated their applicability with different classifiers in our forecasting approach. We tested our proposed method on a dataset of software projects, which were carried out in an international telecommunication company. Our results show that the proposed model is capable of predicting project success in the early stages of the project, in means of sponsor score.
M-Learning to Support Project-Oriented Higher Education in Software Engineering
Authors: Hermann Julia  , Gruhn Volker
Published: February 2025

In this paper, we describe how mobile learning sets new impulses for teaching and learning in project-oriented higher education. In our project clavis, we support the self-directed learning, deepening and application of knowledge and skills in project phases of the master program of “Applied Computer Science and Systems Engineering” (AI-SE) at the University of Duisburg-Essen. Therefore, we want to provide practical examples and relevant learning units in a mobile multimedia toolbox. Students can come back to the small learning chunks during their master projects regardless of time and place. The development of our learning platform is an agile and iterative process model that is tailored to the needs of the target group. To ensure user-friendly implementation and to increase the acceptance, we involve members of the target group continuously throughout the development and implementation process. We raised the requirements in workshops with the participation of future users and the development team. Based on the findings we became aware of the requirements related to the content, didactic methods and technical concepts, that form the basis for the implementation. In this article, we provide a brief insight into our approach, the concept and the students' requirements for the development of the micro learning units and mobile learning platform.
Sentence-Level Sentiment Analysis Using Feature Vectors from Word Embeddings
Authors: Hayashi Toshitaka  , Fujita Hamido
Published: February 2025

Word2vec have been proven to facilitate various NLP tasks. We suppose that the vector space of word2vec can be divided into positive and negative. Hence, word2vec is applicable to Sentiment Analysis tasks. In this paper, we proposed supervised approach for Sentence-level Sentiment Analysis. We utilize pre trained Word Embeddings to extract features from Sentence. We train feature vectors and their polarities to make classification model. After training, we use the model for predicting new sentence's polarity. We compare our method against state of the arts and discuss about how to improve our method.
A Controlled Natural Language for Financial Services Compliance Checking
Authors: Azzopardi Shaun  , Colombo Christian  , Pace Gordon J.
Published: February 2025

Controlled natural languages have long been used as a surface form for formal descriptions, allowing easy transitioning between natural language specifications and implementable specifications. In this paper we motivate the use of a controlled natural language in the representation and verification of financial services regulations. The verification context is that of payment applications that come with a model of their promised behaviour and which are deployed on a payments ecosystem. The semantics of this financial services regulations controlled natural language (FSRCNL) can produce compliance checks that analyse both the promised model and/or monitor the application itself after it is deployed.
Using the AIDA Language to Formally Organize Scientific Claims
Authors: Kuhn Tobias
Published: February 2025

Scientific communication still mainly relies on natural language written in scientific papers, which makes the described knowledge very difficult to access with automatic means. We can therefore only make limited use of formal knowledge organization methods to support researchers and other interested parties with features such as automatic aggregations, fact checking, consistency checking, question answering, and powerful semantic search. Existing approaches to solve this problem by improving the scientific communication methods have either very restricted coverage, require formal logic skills on the side of the researchers, or depend on unreliable machine learning for the formalization of knowledge. Here, I propose an approach to this problem that is general, intuitive, and flexible. It is based on a unique kind of controlled natural language, called AIDA, consisting of English sentences that are atomic, independent, declarative, and absolute. Such sentences can then serve as nodes in a network of scientific claims linked to publications, researchers, and domain elements. I present here some small studies on preliminary applications of this language. The results indicate that it is well accepted by users and provides a good basis for the creation of a knowledge graph of scientific findings.
Putting Control into Language Learning
Authors: Lange Herbert  , Ljunglöf Peter
Published: February 2025

Controlled Natural Languages (CNLs) have many applications including document authoring, automatic reasoning on texts and reliable machine translation, but their application is not limited to these areas. We explore a new application area of CNLs, the use of CNLs in computer-assisted language learning. In this paper we present a a web application for language learning using CNLs as well as a detailed description of the properties of the family of CNLs it uses.
A Knowledge-Based Approach to Warrant Induction
Authors: Saint-Dizier Patrick
Published: February 2025

This contribution outlines the diversity of warrants which can connect a claim and a justification. Opposite justifications can support a claim and vice versa: two opposite claims can be supported by the same justification. Since warrants are seldom explicit, this contribution introduces a conceptual model, based on telicity, to automatically induce the content of warrants. This model is evaluated on a corpus of user generated content on various topics. The grammatical and conceptual subtleties of warrants, depending on the argument they support, is also analyzed.
Empirical Cognitive Study on Abstract Argumentation Semantics
Authors: Cramer Marcos  , Guillaume Mathieu
Published: February 2025

In abstract argumentation theory, multiple argumentation semantics have been proposed that allow to select sets of jointly acceptable arguments from a given set of arguments based on the attack relation between arguments. The existence of multiple argumentation semantics raises the question which of these semantics predicts best how humans evaluate arguments, possibly depending on the thematic context of the arguments. In this study we report on an empirical cognitive study in which we tested how humans evaluate sets of arguments depending on the abstract structure of the attack relation between them. Two pilot studies were performed to validate the intended link between argumentation frameworks and sets of natural language arguments. The main experiment involved a group deliberation phase and made use of three different thematic contexts of the argument sets involved. The data strongly suggest that independently of the thematic contexts that we have considered, strong acceptance and strong rejection according to the CF2 and preferred semantics are a better predictor for human argument acceptance than the grounded semantics (which is identical to strong acceptance/rejection with respect to complete semantics). Furthermore, the data suggest that CF2 semantics predicts human argument acceptance better than preferred semantics, but the data for this comparison is limited to a single thematic context.
Studying Dynamics in Argumentation with Rob
Authors: Bistarelli Stefano  , Faloci Francesco  , Santini Francesco  , Taticchi Carlo
Published: February 2025

The issue of handling dynamics is a central problem in Argumentation Theory. In order to understand how dynamics work, we extended the ConArg suite with Rob, a tool that is able to display Abstract Argumentation Frameworks and their corresponding sets of extensions, in a way suitable to understand what happens to the semantics when a modification to the graph occurs. In particular, Rob allows to inspect for a particular framework all the corresponding sets of extensions, and for every extension all the frameworks which admit it for some semantics.
Enumerating Preferred Extensions Using ASP Domain Heuristics: The ASPrMin Solver
Authors: Faber Wolfgang  , Vallati Mauro  , Cerutti Federico  , Giacomin Massimiliano
Published: February 2025

This paper briefly describes the solver ASPrMin, which enumerates preferred extensions and scored first in the Extension Enumeration problem—the only one implemented—of the Preferred Semantics Track of the Second International Competition on Computational Models of Argumentation, ICCMA17.
State-Centric Methodology of Ontology Engineering
Authors: Mizoguchi Riichiro
Published: February 2025

While working on ontology engineering for about 25 years, I think I unconsciously acquired my own methodology in ontology engineering. It is what I call ‘state-centric’ methodology. My background is in AI and Engineering rather than logic or philosophy, and it must have been driving me to understand reality in terms of states which are the heart of General Problem Solver (GPS). All my results on roles, functions, processes/events and causation (published in Applied Ontology) clearly show the utility of the state-centric methodology. My treatment of context seems rather unique since I claim that any object as a whole provides a context to its parts, and each of these play their assigned role to make the collection a unitary whole. The notion of ‘non-intentional goal’ together with the systemic context as its concretization works very well to capture temporal entities. The success of the unified definition of biological and artifact functions is largely based on this idea. The device ontology, which I have devised for enabling to capture dynamic and complex phenomena in a consistent manner, has been exploited in many of my works on function. It is a role assignment system and fully state-centric. In my recent work on causation, I have realized that any causation C → E can be mapped onto a function in which E is a non-intentional goal in the systemic context associated with C → E. The new functional talk of causation is fully state-centric which contrasts with the common idea that states should be excluded from the relata of causation. I found that the essence of causation exists in an occurrent in the form  where State is the resultant state of the Event. In my keynote, I discuss the state-centric methodology through typical achievements on roles, function, processes/events and causation.
Foundational Ontologies for Units of Measure
Authors: Grüninger Michael  , Aameri Bahar  , Chui Carmen  , Hahmann Torsten  , Ru Yi
Published: February 2025

Multiple ontologies for units of measure have been proposed within the Applied Ontology community, and all of these ontologies introduce an array of new classes based on supposed distinctions between quantities, quantity kinds, and measures. Units are combined using notions of dimensional analysis that often conflate the combination of units with algebraic operations on real numbers. In this paper we present an alternative approach that shifts the focus to the connection between the units of measure and the physical objects and processes that are being measured. One of the key features of this approach is that it makes minimal ontological commitments with respect to the TUpperWare upper ontology – the only new classes that are introduced are the classes for the units of measure. We propose correct and complete axiomatizations for combining units of measure, and the correct axiomatization of the relationship between the units of measure and the existing upper ontology.
Using the Behaviour Change Wheel for Designing an Online Platform for Healthy Weight Loss – “POEmaS”
Authors: Beleigoli Alline M.  , Andrade Andre Q.  , Diniz Maria de Fátima H.  , Alvares Roberta S.  , Ferreira Marina H.  , Silva Leticia A.  , Rodrigues Marcia C.  , Jacomassi Luma  , Cerqueira Amanda G.  , Ribeiro Antonio L.
Published: February 2025

Introduction: Behaviour change is a key point in weight management. Digital health interventions are attractive tools to deliver behaviour interventions for weight loss, due to the potential to reach a large number of people. We aimed to report how the Behaviour Change Wheel (BCW) was used to develop and implement a web platform to promote weight loss in Brazilian adults with overweight and obesity. Moreover, we aimed to describe the first 12 weeks of usage of the platform in a randomized controlled trial.
Health Information Technology and Telehealth Challenges in the U.S. Affiliated Pacific Islands Region
Authors: Higa Christina  , Okamura Jessica  , Okamoto Sean  , Okamura Norman
Published: February 2025

Small island developing states (SIDS) have much to gain from the use of Health Information Technology (HIT) and telehealth to improve care, improve population health, increase access to care, and lessen costs. At the same time, planning, implementing, and operationalizing HIT is costly and requires significant technical, human, financial and planning resource infrastructure to support implementation and operations. This paper provides a broad overview of how HIT and telehealth has evolved in the U.S. Affiliated Pacific Islands (USAPI) SIDS, the progress that has been achieved, the role of political affiliations and international assistance, and the many challenges that remain. The paper highlights the differences in treatment between the territories and the nations affiliated with the United States through the Compacts of Free Association (COFA), and the important roles of other donor countries, regional, and international organizations. The paper also raises questions of how advances in HIT and telehealth can be further achieved and sustained in the USAPIs. Finally, the paper identifies the need for the building of knowledge and skills to develop careful plans so pitfalls of silos, proprietary systems, and inadequate technical support can be lessened or avoided in the grand challenge of adoption and maturing of HIT and telehealth.
What Needs to Be Done to Ensure the Ethical Use of AI?
Authors: Steels Luc
Published: February 2025

It is now clear to even the greatest doubters that AI is a powerful technology with considerable practical usage. But it has also become clear that this usage can be both positive and negative. AI can improve healthcare, aid environmental monitoring, support community formation, make culture more widely accessible, and do many other good things – always in combination of course with other digital technologies. But AI can also play a role in deceit and manipulation of public opinion, stoking societal divisions, enforcing senseless bureaucracy, cyberattacks, autonomous weapons, job loss, etc. Moreover the application and promises of AI appear to be premature in the face of autonomous cars going through red traffic lights, unacceptable decisions on granting parole, perpetuation of racial and gender bias in recruitment, etc. This discussion paper provides some ideas to foster positive uses of AI and guard us against negative ones, building further on the ‘Barcelona Declaration for the Proper Development and Use of AI in Europe’, which you can read and sign here: http://www.iiia.csic.es/barcelonadeclaration/.
Big Data Analytics for Obesity Prediction
Authors: Bilal Ahsan  , Vellido Alfredo  , Ribas Vicent
Published: February 2025

Feature selection (FS) is essential for the analysis of genomic datasets with millions of features. In such context, Big Data tools are paramount, but the use of standard machine learning models is limited for data with such low instances to features ratios. Apache Spark is a distributed in-memory big data system with the potential to overcome this bottleneck. This study analyzes genomic data related to prediction of human obesity. Since Apache Spark is unable to cope with our dataset containing ≈ 0.74 million features, we propose here a pipeline to solve this problem using partitioning strategies, both vertical, by dividing the data based on gender, and horizontal, by splitting each chromosome into 5,000-instances subsets. For each subset, Minimum Redundancy and Maximum Relevance FS was used to find rankings of the most relevant features. The challenge, thus, is making accurate obesity predictions with parsimonious subsets of features selected from millions of them. We tackle it by defining a 2-phase pipeline: first learning with individual chromosomes and then learning with joined 22 chromosomes from selected features.
Do Positive Twitter Messages Have Impact on Stock Liquidity?
Authors: Abdirahmani Aliasghar  , Angulo Cecilio
Published: February 2025

Social media is a phenomenon that has transformed the interaction and communication of individuals throughout the world. In recent times, social media has affected many aspects of human communication, as well as business. The main objective of our research is to figure out about the role of Twitter on stock market to find out how social media impacts on the business that predictions fail.
Sentient Embodied Conversational Agents: Architecture and Evaluation
Authors: Tellols D.  , Lopez-Sanchez M.  , Rodriguez I.  , Almajano P.
Published: February 2025

This paper introduces Sentient Embodied Conversational Agents (SECAs) as virtual characters able to engage users in complex conversations. Our proposal includes the formalisation of a SECA architecture together with a software library that facilitates their inclusion in applications requiring proactive and sensitive agent behaviours. Since educational and eldercare applications constitute paradigmatic examples of such requirements, we evaluate our proposal with a virtual tutor embedded in an educational application. The obtained results show that children are satisfied both in terms of their perception of learning and overall conversational experience. Additionally, we found significant differences in quantity of user data gathered by our application (with SECA) and its previous version (without SECA).
An Approach to Gait Analysis from Human-Rollator Interaction: The i-Walker
Authors: Cortés Atia  , Ojeda Maribel  , Béjar Javier  , Martínez Antonio B.
Published: February 2025

Falls are one of the main causes of injury and injury-related deaths in the older demographic sector. During the last decade, several solutions have been proposed for fall detection or prevention, but also to assist old adults in their mobility. The main concern is to provide means to improve their quality of life, allowing them to live in community as long as possible, but also to help maintaining public health systems as sustainable as possible. In this paper, we compare two different methodologies that aim to define walking patterns in 42 adults aged 22 to 94 years that participated in a pilot study. Two methodologies are compared: one focused on the whole exercise performance, while the other tries to identify strides and categorize them. Both proposals use a technique based on the bag-of-words approach.
Modular Knowledge-Based Decision Support System Dedicated to a Cooperative Decision to Prevent Cardiovascular Diseases
Authors: Ugon Adrien  , Jobez Emmanuel  , Falcoff Hector  , Jaulent Marie-Christine  , Meneton Pierre  , Favre Madeleine  , Tsopra Rosy
Published: February 2025

Despite the success of artificial intelligence solutions in the recent years, physicians are still reticent to use integrated functionalities to support their decision. Methods used to create these functionalities can be divided into two groups, each being associated to different questions. Data-based methods are seen as black boxes for which it is impossible to understand how the decision is taken; knowledge-based methods need to rely on formalized knowledge sources on the basis of evidence, which can be discussed and criticized by physicians for their use in real life. This paper presents a new modular decision support system for the prevention of cardiovascular diseases, based on knowledge and on cooperative decision between the patient and the physician. The decision support system is based on two layers: (i) the first layer is a knowledge-based module which generates automatically patient profile, and prevention strategies associated to the profile; (ii) the second layer is a dynamic collaborative graphic user interface which displayed information about the risks of treatment adherence failure, personalized motivation and follow-up strategies. In the future, we aim at assessing the platform in real life.
Mixed Reality Supporting Modern Medical Education
Authors: Nicola Stelian  , Stoicu-Tivadar Lacramioara
Published: February 2025

The paper presents new learning support for medical students exemplifying with several 3D applications for training on specific topics in medicine and investigates the impact on medical students. The applications were built using new concepts: Virtual Reality, Augmented Reality, as environments agreed by young people, and gamification to make learning easy and fun. Leap Motion and the VR headset are the devices to control the applications and provide a better human-computer/mobile phone interaction as compared to the current ones. The concepts and the new technologies to display/visualize the applications are the core of the Mixed Reality concept resulting from combining the 4 applications implemented for medical education.
Harnessing Ontologies to Improve Prescription in Pediatric Medicine
Authors: Lupşe Oana-Sorina  , Chirila Ciprian-Bogdan  , Stoicu-Tivadar Lăcrămioara
Published: February 2025

There are many drug databases, but sometimes the data quality may result in wrong medication for patients. Results that it is very important to provide a good quality drug information, supply structured information and build useful relations between the drugs related information and the patient status in terms of particularities. Children are the most sensitive to drug dosage or certain substances that is why pediatrics was our first choice for the research. To support this, we propose an ontology starting from on-line drug prospectuses. We start extracting the prospectuses information from the web pages, investigate the sections of the prospectuses structure (indications, contraindications, dosage, etc.) and use the information in an ontology that we integrate into a pediatric application. In the background of the application this solution provides the correct matching between the patient and the treatment, extracting for the physician only the best prescription options for the current case. The application allows the physician to select the appropriate drug and decide the best treatment in terms of correct substances and dosage for a certain child. We use the prospectuses solution because the application is in Romanian and other resources are not very well provided. For the future the solution will be adapted to other languages and other databases. This model can be generalized in different languages. The application is improved with the new ontology module and helps physicians to give a good treatment considering all relationships, constraints or antagonistic situations that may occur in providing a treatment.
Design and the Mind Engaging and Collaborative Workshops for the Neurodiverse
Authors: Trotman Natasha  , McGinley Chris
Published: February 2025

This project seeks to reframe notions and approaches for engagement with neurodiverse groups and individuals using a developed design suite of functioning and dynamic tools and methods underpinned by inclusive principled guidelines which will be used by The Wellcome Collection Hub, the wider organisation and Hub partners to improve inclusion and accessibility. These orthodoxies will aid the reframing of neurodiverse inclusive museum focused interactions and co-creation at the Wellcome Collection Hub. The project, has been undertaken in partnership with the Helen Hamlyn Centre for Design, Royal College of Art and the Wellcome Collection.
Diversity of “Pedestrians on Wheels”, New Challenges for Cities in 21st Century
Authors: Jiménez Delfín  , de la Fuente Yolanda  , Hernández-Galán Jesús
Published: February 2025

Traditionally, pedestrians were identified as singular entities with standard needs. Reality shows us that pedestrian diversity is a reality that is becoming increasingly complex. How does urban design face the changing reality of pedestrian typologies? In the same way that in the 20th century the car set aside horse carriages and pedestrians, in the 21st century pedestrians are returning to take centre stage with regard to motor vehicles, but with new formalizations that imply new considerations in the design of streets, many of they are still unsolved. Citizens strolling on scooters, skates, skateboard, segway, unicycles, are added to the already traditional baby strollers, wheelchairs, and suitcases with wheels … “pedestrians on wheels” that pose new challenges of coexistence and design. Own functional requirements to walk and maneuver, to see and be seen … functional requirements of coexistence with other pedestrians that make a different use of the street (people looking at shop windows, pedestrians with umbrellas, reading on the smartphone…) or changes of use of the same space when the conditions are different: snow, strong sun, fog, at night … These are considerations of Universal Accessibility and Design for all that we cannot leave out while our society progresses. This paper identifies some of these new needs and studies this new pedestrian mobility is carried out through a progressive analysis in three phases: 1 classification of the different user of the street, 2 study of the Personal Mobility Devices (PMD) and 3 the new accessibility barriers that arise with the use of PMD. As a result, some action strategies are pointed out to respond to the difficulties of accessibility derived from this new reality and to integrate them into the Universal Design of the urban public space.
Universal Balance?
Authors: Magnusson Charlotte  , Caltenco Héctor  , Rassmus-Gröhn Kirsten  , Rydeman Bitte
Published: February 2025

In the ActivAbles and STARR projects we are developing interactive training tools for stroke survivors. As our initial user studies pointed to balance being a key ability, one of the developed tools is an interactive balance mat. While balance equipment is common, interactive balancing equipment for persons with poor balance is less common. Equipment exists for persons with good balance (eg. Wii), but most games and exercises are less suited for many stroke survivors. The development process has been done in close collaboration with stroke survivors. We have used both creative workshops and individual iterative testing in the development, and have currently a prototype that is being tested in the home of 12 stroke survivors. This prototype is based on a foam mat which incorporates pressure sensing, and which allows you to see the pressure distribution as you exercise, but also allows you to play music or play different games. The feedback is designed to be inclusive – designs are multimodal (visual and auditory), and the setup is flexible and can easily be adapted. Initial test results show that the overall design is promising and works well (is robust, motivating and used). Problems identified are connected to the fact that we use main stream tablets for feedback, which adds complexity for the user both with interaction and charging. We are currently working on solving these problems, and expect to end up with a balance mat well suited for a wide range of users – not only stroke survivors.
Making Learning Materials Accessible in Higher Education—Attitudes Among Technology Faculty Members
Authors: Chen Weiqin  , Sanderson Norun C.  , Kessel Siri
Published: February 2025

With the increasing popularity of digital technologies, more and more digital learning materials are available in education. However, making digital learning materials accessible to diverse students can be a challenging task. In higher education institutions, faculty members play a vital role in ensuring the accessibility of digital learning materials. This paper aims to provide a better understanding of the attitudes among faculty members towards this task by conducting a thematic analysis of 35 semi-structured interviews with computer science and engineering faculty members at four universities in Norway and Poland.
Fuzzimetric Sets: An Integrated Platform for Both Types of Interval Fuzzy Sets
Authors: Kouatli Issam
Published: February 2025

Type-2 sets are the generalized “fuzzified” sets that can be used in the fuzzy system. Unlike type-1 fuzzy sets, Type-2 allow the fuzzy sets to be “fuzzy” rather than the crisp definition of the set. Although this would improve the flexibility of inferring a decision, the implementation of Type-2 is rather more complex than type-1. Based on this principle, this paper proposes the mechanism of “Fuzzimetric Sets” that is capable of defining a rigid fuzzy set as well as “fuzzy” Fuzzy sets (Type-2). This is based on the concept of Fuzzimetric Arcs which will also be reviewed in this paper. Most of the implementations of this type of fuzzification would be suitable for decision support systems where an example of how to implement Fuzzimetric sets is also presented in this article. The platform of Fuzzimetric sets is composed of the initial definition of the fuzzy sets within the context of Fuzzimetric Arcs and then, the use of mutation and crossover operations on the sets allow the “Fuzziness” property of the set. To control the level of fuzziness in such sets, the introduction of “Degree of Fuzziness” factor was also proposed. DOF is composed of two dimensions: Vertical-DOF: Allowing changes in the level of the fuzzy membership of the set (0-1) and Horizontal-DOF: allowing the fuzziness level between maximum and minimum tolerances of the fuzzy sets, causing the centroid to move between the maximum and minimum allowed tolerances. If V-DOF was equated to zero, and H-DOF range defined between [90-90] then the set becomes type-1, otherwise, fuzziness level of the fuzzy sets can be controlled via this factor.
Efficient Basis Pursuit DeNoising via Active Sets and Homotopy
Authors: Oliveira Suely P.  , Stewart E.
Published: February 2025

The Basis Pursuit DeNoising problem is a variant of the well-known lasso method for obtaining sparse least-squares approximations, which can be represented as the minimization problem min β½‖Aβ−y‖22+λ‖β‖1. In this paper the problem is treated as a parametric quadratic program with parameter λ≥0. By this technique, very large scale problems can be essentially solved exactly for a range of values of λ, as long as the number of non-zero components of β is small to modest.
Design of Field Station System Based on Internet of Things
Authors: Ye Lun  , Dong Limei  , Zhang Zhipeng  , Song Xiaotao
Published: February 2025

There are two key problems in the field station systems related to the maintenance of long-distance data transmission and the power needed for a longterm operation of the field devices. In order to solve these problems, a new-design field station system that adopts the Internet of things technology and low-power consumption technology is proposed to achieve data acquisition and transmission in the field. The aim of the proposed field station system is to help researchers to get the valuable data in the field, and to provide some assistance support for in-depth scientific research. The overall design and parameters of the proposed system are explained in detail. Moreover, the conducted test shows that the proposed system can achieve not only the long-term stable data acquisition and transmission in the field with low-power consumption but also visualization of the scientific data. The proposed system has high practical value and has been used in the soil monitoring.
The Performance of Weak Underwater Acoustic Signal Detection Based on Passive Time Reversal and Stochastic Resonance
Authors: Liu Lei  , Shen Xiaohong  , Ma Shilei  , Zhang Zhichen
Published: February 2025

There are mainly two factors, multipath effect and strong background noise, affecting the performance of underwater weak acoustic signal detection. In this paper, to improve the performance, we propose a joint detection approach for underwater weak acoustic signal by combining the approaches of Passive Time Reversal (PTR) and Stochastic Resonance (SR). By calculating the input and output signal-to-noise ratios (SNR) theoretically, it's found that the proposed PTR-SR approach could improve the SNR of received signal, which is obtained by utilizing the multipath propagation channel and background noise simultaneously. Further, we propose a strategy to properly setting the free amplitude parameter Asrto optimize the SNR gain. Based on the Neyman-Pearson criterion, simulation results also highlight the performance of the proposed joint detection approach over single PTR approach and SR approach, especially in the circumstance of low SNR.
Fuzzy-Logic Controller Based Multi-Port DC-DC Converter for Photo-Voltaic Power System
Authors: Venkateshkumar M.  , Chin Cheng Siong
Published: February 2025

The mathematical model of the photovoltaic (PV) system is developed and simulated. The maximum level of power point tracking is implemented for operating the PV system at optimal power generation using an intelligent controller with analysis of the system performance. A multi-port converter design is proposed and simulated. The proposed converter is controlled by Fuzzy-logic controller for effective utilization of PV power generation and battery management system. The proposed Fuzzy logic based controller is designed for PV and battery management system at various load demand and weather conditions. The proposed system performance is analyzed at the different weather and load demand. The simulated results show the effectiveness of the proposed system.
A New Secure Chip File Access Method Based on Security Level Information
Authors: Fu Qingqin  , Ang Zhengquan  , Liu Jia  , Yuan Yanfang  , Yuan Jiahui
Published: February 2025

This paper analyzes the shortcomings of two commonly used secure chip file access methods and proposes a new secure chip file access method based on security level information. The method sets the security level information in the key file; sets the access operation permission information in the application file; obtains the security level information, determines the security status information of the directory file corresponding to the key file according to the security level information; and obtains the access operation permission. The information determines the file access authority according to the access operation authority information and the security state information. This method effectively reduces the complexity of the security mechanism within the secure chip, increases the convenience of file access, and overall and comprehensively guarantees the security of file access.
Neural Network Hybrid Modeling of Nonlinear Wirerope Vibration Isolation System
Authors: Zhao Heming  , Zhao Xingmin
Published: February 2025

The wirerope vibration isolator represents a type of nonlinear hysteretic damping component. The hysteretic constitutive relation between restoring force and deformation is complex and the dynamics modeling is difficult. A method was proposed in order to conduct neural network hybrid modeling of hysteretic restoring force based on analysis of the dynamics features of nonlinear wirerope vibration isolators. It was learnt through experimentation and simulation results under random excitation that the constructed model has fast training rate, small calculation amount, and strong generalization ability. In addition, some parameters of the knowledge-based model have physical meaning, which allow it to provide references for the structural design and simulation of vibration isolation systems.