bluuebunny/crossref_metadata_2025 huggingface dataset:
Argument Harvesting Using Chatbots
Authors: Chalaguine Lisa A.  , Hamilton Fiona L.  , Hunter Anthony  , Potts Henry W.W.
Published: February 2025

Much research in computational argumentation assumes that arguments can be obtained in some way. Yet, to improve and apply models of argument, we need methods for acquiring them. Current approaches include argument mining from text, hand coding of arguments by researchers, or generating arguments from knowledge bases. In this paper, we propose a new approach, which we call argument harvesting, that uses a chatbot to enter into a dialogue with a participant to get arguments and counterarguments from him or her. Because it is automated, the chatbot can be used repeatedly in many dialogues, and thereby it can generate a large corpus. We describe the architecture of the chatbot, provide methods for clustering arguments by their similarity and value, and an evaluation of our approach in a case study concerning attitudes of women to participation in sport.
Jebediah – Arguing with a Social Bot
Authors: Meter Christian  , Ebbinghaus Björn  , Mauve Martin
Published: February 2025

In this demonstration we will showcase Jebediah, a social bot based on Google's Dialogflow. Jebediah is a front-end to dialog-game execution platforms that enable their seamless integration into popular social networks such as Facebook or Twitter. Users can interact with the social bot using natural language while Jebediah translates the user input to a format that can be interpreted by a dialog game execution platform and vice versa.
Formal Argumentation and Epistemic Entrenchment
Authors: D'Agostino Marcello
Published: February 2025

The argumentation turn in logic paves the way for importing problems and ideas from general philosophy of science into logical formalisms. The main problems are: when faced with an inconsistency, how do we choose the hypotheses/beliefs that are the most plausible candidates for revision? Do we really need to react to each single inconsistency or should we focus on predictive success and temporarily ignore “minor” inconsistencies? How do we distinguish ad hoc adjustments from heuristically fruitful revisions? These questions call for a sophisticated notion of “epistemic entrenchment”. The basic idea has played an important role both in the area of belief revision (Gärdenfors and Makinson) and, under different denominations, in that of general philosophy of science (Quine, Kuhn, Lakatos), with little or no interaction between them. The main aim of this talk is to bring the philosophical debate on this notion to the attention of the formal argumentation community and suggest how this interaction could lead to substantial advances in the field.
Instantiating Metalevel Argumentation Frameworks
Authors: Young Anthony P.  , Kokciyan Nadin  , Sassoon Isabel  , Modgil Sanjay  , Parsons Simon
Published: February 2025

We directly instantiate metalevel argumentation frameworks (MAFs) to enable argumentation-based reasoning about information relevant to various applications. The advantage of this is that information that typically cannot be incorporated via the instantiation of object-level argumentation frameworks can now be incorporated, in particular information referencing (1) preferences over arguments, (2) the rationale for attacks, and (3) the dialectical effect of critical questions that shifts the burden of proof when posed. We achieve this by using a variant of ASPIC+ and a higher-order typed language that can reference object-level formulae and arguments. We illustrate these representational advantages with a running example from clinical decision support.
Informative Armstrong RDF Datasets for n-Ary Relations
Authors: Harmse Henriette  , Britz Katarina  , Gerber Aurona
Published: February 2025

The W3C standardized Semantic Web languages enable users to capture data without a schema in a manner which is intuitive to them. The challenge is that, for the data to be useful, it should be possible to query the data and to query it efficiently, which necessitates a schema. Understanding the structure of data is thus important to both users and storage implementers: The structure of the data gives insight to users in how to query the data while storage implementers can use the structure to optimize queries. In this paper we propose that data mining routines be used to infer candidate n-ary relations with related uniqueness- and null-free constraints, which can be used to construct an informative Armstrong RDF dataset. The benefit of an informative Armstrong RDF dataset is that it provides example data based on the original data which is a fraction of the size of the original data, while capturing the constraints of the original data faithfully. A case study on a DBPedia person dataset showed that the associated informative Armstrong RDF dataset contained 0.00003% of the statements of the original DBPedia dataset.
Speech-Based Identification of Children's Gender and Age with Neural Networks
Authors: Piel Leo Kristopher  , Alumäe Tanel
Published: February 2025

In this paper, we investigate using different types of neural networks for age and gender identification from children's speech, based on the Corpus of Estonian Adolescent Speech. Feed-forward deep neural networks using i-vectors as input are compared with recurrent neural networks using MFCCs as input. Results show that feed-forward neural networks outperform recurrent neural networks for gender classification, while a model that combines both i-vectors and MFCC via feed-forward and recurrent branches achieve the best performance for age group classification. We also show that for age group classification, it is beneficial to first identify gender and then use a gender-specific age identification model. Experiments with human listeners show that the neural network models outperform humans on both tasks by a big margin.
Latvian Tweet Corpus and Investigation of Sentiment Analysis for Latvian
Authors: Pinnis Mārcis
Published: February 2025

We present the Latvian Tweet Corpus and its application in sentiment analysis by comparing four different machine learning algorithms and a lexical classification method. We show that the best results are achieved by an averaged perceptron classifier. In our experiments, the more complex neural network-based classification methods (using recurrent neural networks and word embeddings) did not yield better results.
Topic Interpretation Using Wordnet
Authors: Barbu Eduard  , Orav Heili  , Vare Kadri
Published: February 2025

This is a preliminary study in topic interpretation for the Estonian language. We estimate empirically the best number of topics to compute for a 185 million newspaper corpus. To assess the difficulty of topics, they are independently labeled by two annotators and translated into English. The Estonian Wordnet and Princeton Wordnet are then used to compute the word pairs in the topics that have high taxonomic similarity.
Comparative Study of Medical Reference and Information Mobile Apps for Healthcare Professionals and Students
Authors: Irfan Muhammad Ehtisham  , Ginige Jeewani Anupama
Published: February 2025

This paper presents a framework upon which medical applications can be evaluated both in terms of basic functionality, and their target area of users. The study was conducted on 40 mobile applications that were published within Google Play and Apple App store targeted for clinicians, medical practitioners and students. It was important to first classify the mobile apps selected because there are many generic applications, and some focus on special areas within the medical field. The classification process included determining the specialist areas of these applications such as educational and training, nursing, diagnosis and treatment, patient monitoring, testing and laboratories, and social networking. After the classification, a criterion to evaluate applications within individual categories, as well as in more general aspects such as their performance, security, user interface, and other software quality attributes, was developed. Test data was used to test the applications using the developed evaluation criteria, and the results were then used to determine the apps with surpassing features. As per the category-wise results, Medicine References and Education & Training categories had applications that had better scores than other categories. However, an equally important finding concluded that there are not enough applications to help with lab testing, and this gap needs to be filled. Most applications lacked the usability aspect and needed work in user interface (UI) and user experience (UX) areas.
Citizens and Health Data – Untapped Resource for Telehealth?
Authors: Moen Anne
Published: February 2025

In this paper I will engage with the discussion on Citizen and Health Data, and look specifically at challenges in citizen-centered digital health information management, if the goal is to stimulate self-management, support holistic trajectories of health and wellbeing, and implement new practice models with efficient use of health care services. A focus will be citizens' opportunities to engage in activities to a) collect, b) curate, c) control access to personal Health Data and relate these activities to telehealth locally and globally.
Clinician Perspectives of an Avatar-Directed Scheduling and Memory App
Authors: Morris Claire  , Barr Christopher  , George Stacey  , Crotty Maria  , van den Berg Maayken
Published: February 2025

Background and aims: Effective strategies are needed to address the need for scheduling support in the unique setting of a home rehabilitation service, providing home based therapy, as well as telerehabilitation. One approach is an electronic avatar-directed scheduling and memory aid in the form of an app. The aim of this study is to investigate clinician perspectives on the use of this type of technology.
Measuring Distances Between Medical Entities. Step 1: DrugBank
Authors: Olivares-Alarcos Alberto  , Stankovic Iva  , González Humberto  , Rodríguez Horacio
Published: February 2025

We face in this paper the problem of computing distance measures between medical entities. Specifically we deal with the most challenging type of medical entity: drugs. Three different similarity measures between drugs are presented, based each one on specific dimensions of drugs description, namely textual, taxonomic and molecular information. All the information has been extracted from the same resource, the DrugBank database.
Limits of Multi-Agent Predictive Models in the Formation of Social Conventions
Authors: Freire Ismael T.  , Arsiwalla Xerxes D.  , Puigbò Jordi-Ysard  , Verschure Paul F.M.J.
Published: February 2025

A major challenge in cognitive science and AI is to understand how intelligent agents might be able to predict mental states of other agents during complex social interactions. What are the computational principles of such a Theory of Mind (ToM)? In previous work, we have investigated hypotheses of how the human brain might realize a ToM of other agents in a multi-agent social scenario. In particular, we have proposed control-based cognitive architectures to predict the model of other agents in a game-theoretic task (Battle of the Exes). Our multi-layer architecture implements top-down predictions from adaptive to reactive layers of control and bottom-up error feedback from reactive to adaptive layers. We tested cooperative and competitive strategies among different multi-agent models, demonstrating that while pure RL leads to reasonable efficiency and fairness in social interactions, there are other architectures that can perform better in specific circumstances. However, we found that even the best predictive models fall short of human data in terms of stability of social convention formation. In order to explain this gap between humans and predictive AI agents, in this work we propose introducing the notion of trust in the form of mutual agreements between agents that might enhance stability in the formation of conventions such as turn-taking.
The Effect of Space-Time Representation Learning in Predicting People's Next Location
Authors: Al-Molegi Abdulrahman  , Martinez-Balleste Antoni
Published: February 2025

Predicting users' next location becomes an important requirement in various Location-based applications and services. This prediction provides the most probable next location in order to make proactive offerings or services based on those predicted locations. However, prediction models in the literature achieve satisfactory results, but ignore an important fact that values and representations of some variables can be much more relevant to the final location prediction than the rest of variables. In this paper, we study the impact of Space-Time representation learning in location prediction model through evaluating different architectural configurations. First, we evaluate the impact of many different data inputs on the model final prediction performance. Based on that, different prediction models are proposed that vary in terms of the number and type of input features. Second, we investigate the impact of input representation techniques on the prediction performance using both embedding representation learning and one-hot vector representation (i.e. static vectors). We conduct thorough experiments in all our previous models on two real-world datasets, GeoLife and Gowalla.
Caveats for the Use of the Active Problem List as Ground Truth for Decision Support
Authors: Ceusters Werner  , Blaisure Jonathan
Published: February 2025

Diagnoses recorded on the problem list are increasingly being used for decision support applications. To obtain insight in the adequacy of the clinical user interface to capture what the clinician has in mind, and to reconstruct the clinical reality of the patient, we analyzed in the database of an EHR system the transactions that resulted from managing the problem list. Our findings indicate (1) that caution is required when using the evolution of the problem list for determining comorbidity or ongoing disease, and (2) that similarities or differences in problem list annotation sequences do not always correspond with similarities resp. differences in disease courses. It is to be investigated whether automatically identifiable subsets of problem list evolution patterns exist from which ground truth reliably can be inferred or whether clinicians need more education in how problem list user interfaces should be used to avoid erroneous interpretations by clinical decision support applications.
Intelligent Patient Flow Management System at a Primary Healthcare Center – The Effect on Service Use and Costs
Authors: Tenhunen Henni  , Hirvonen Petteri  , Linna Miika  , Halminen Olli  , Hörhammer Iiris
Published: February 2025

An intelligent patient flow management system (IPFM) was piloted at a large primary healthcare center in Finland in August 2017. The goals of the system are to help patients avoid unnecessary calls and visits to their health center and to enhance the use of professional resources through more streamlined patient pathways and the re-allocation of professionals from assessment tasks to actual patient care. These goals should be reflected in the decreased service costs through optimized contact forms. Using multiple regression analysis, we studied the associations between IPFM and patients' service utilization (17,943 patients; 73,038 service contacts) during the first five months of the pilot in 2017. The results indicated that the use of IPFM by the patient was associated with a decrease of EUR 31 in the total service costs of the patient in the study period. This decrease is 14% of patient's average total service cost.
Specification and Description Language of Medical Activities
Authors: Muteba Eustache
Published: February 2025

Modern health care management takes place in organizations and institutions that are becoming more and more complex. The management of these institutions requires broad clinical and business administrative knowledge, but also excellent scientific skills. The scope of our study, presented in this paper, is to emphasis the management of medical activities. Based on set theory and scientific management of work, we developed a method called Specification and Description Language of Medical Activities (SDLMA) that can monitor performance, and can provide instructions to ensure the most efficient ways of working.
Designing a Coding Data Warehouse to Support and Enhance Medical Act Coding
Authors: Noussa-Yao Joseph  , Heudes Didier  , Degoulet Patrice
Published: February 2025

Standards Data Warehouse has been implemented in many hospitals. It has enormous potential to improve performance measurement and health care quality. Accessing, organizing, and using these data to optimize clinical coding are evolving challenges for hospital systems. This paper describes development of a coding data warehouse based Entities-Attribute-Value (EAV) that we created by importing data from the clinical data warehouse (CDW) of public hospital. In particular, it focuses on design, implementation, and evaluation of the warehouse. Moreover, it defines the rules to convert a conceptual model of coding into an EAV logical model and his implementation using integrating biology and the bedside (i2b2). We evaluate it using data research mono and multi-criteria and then calculate the precision of our model. The result shows that, the coding data warehouse provides with good accuracy, an association of diagnostic code and medical act closer the patient's clinical landscape. Doctors without knowledge of coding rules could use this information to optimize and improve the diagnostic coding.
Universal Design in Housing in Australia: Getting to Yes
Authors: Ward Margaret  , Bringolf Jane
Published: February 2025

In Australia, the last frontier for universal design is mainstream housing. Developers in the private residential sector have consistently, and successfully, argued for the status quo to remain. Developers' claims of cost and lack of demand have swayed governments that are in favor of “letting the market decide”. Disability- and age-specific housing and one-off projects have included many features that are considered universal design. So, the technical details are not an issue. The house-building sector in Australia consists of many parts, all held together by regulations and professional codes and norms of practice. Calls for accessible housing were heard by the Australian Government in 2010 and a set of voluntary guidelines were developed jointly by industry and disability advocacy groups. These became the “Livable Housing Design Guidelines”. It was understood that industry needed time to reorganize to bring about the changes needed. Consequently, it was agreed to progressively introduce accessible features over ten years so that by 2020 all new homes should be built to a basic level of accessibility. However, it was obvious in 2017 that this goal was unachievable with voluntary guidelines. Mandating these guidelines has been shunned at every turn, but the need to mandate could no longer be ignored. Through community advocacy efforts, the body that regulates the National Construction Code has been brought to the negotiating table to discuss mandating basic access features in all new homes. This paper reports on the processes and progress of these negotiations and the outcomes to date.
Universal Design as a Technical Norm and Juridical Term – A Factor of Development or Recession?
Authors: Bringa Olav Rand
Published: February 2025

Universal design was introduced as an ideological and technical concept in Norway in 1996 and was introduced in the first law in 2003. Since then universal design has replaced accessibility for people with disabilities in national policies, laws, regulations, standards, projects and everyday language. Accessibility is now used to characterize solutions made more exclusively for people with disabilities or when a high, general quality is not required. Few countries have made this extensive use of the concept of universal design and the concept has faced several challenges from lawmakers, architects, economists, user organizations, entrepreneurs and debaters. This paper reflects on some aspects of more than 20 years of extensive use of the concept of universal design and try to answer the question: Is universal design an academic invention with little extra positive impact compared to accessibility for people with disability, or does the concept defend its supposed role as a step towards a society with equal opportunities for all?
Exploring Maker Cultures and Pedagogies to Bridge the Gaps for Students with Special Needs
Authors: Hughes Janette  , Fridman Lauren  , Robb Jennifer
Published: February 2025

Through this ethnographic study, the researchers investigate the efficacy of using “makerspace” pedagogies with students who are identified as having special needs. These pedagogies include the transferable skills and global competencies as outlined by the Ontario Ministry of education. The research questions address how teachers view changes in his/her special education students' behaviour and learning based on their participation in maker-related activities, including, but not limited to coding, programmable robots, and circuits, in the classroom. Teachers were supported through professional development by our STEAM 3D Maker Team at the Faculty of Education and then subsequent visits made to each of 20 different schools investigated how maker pedagogies were being employed. Qualitative data was collected in the form of digital video and audio recordings, photographs, observational field notes, and individual and focus group interviews. The data suggest that the use of maker pedagogies can facilitate a number of improved outcomes for students with exceptionalities, including confidence and perseverance, engagement and motivation, self-regulation, collaborative skills, and increased academic achievement.
The Use of Social Robots for Supporting Language Training of Children
Authors: Fuglerud Kristin S.  , Solheim Ivar
Published: February 2025

A number of studies have found that robots can contribute to engagement and motivation in educational settings. We wanted to explore the possibilities and challenges of using a social robot as an assistive tool for learning and training of basic concepts and words. Robots are considered promising tools in language training because they can contribute to systematic interaction and repetition. A prototype was developed using an Aldebaran NAO robot combined with pictures that could be presented on a tablet, PC or on the wall using a projector. The prototype was piloted in two pre-projects with different groups of children learning Norwegian. One project targeted second language learners in a kindergarten and the other targeted young primary school pupils with autism spectrum disorder. Both of these groups need more systematic training than they usually get during the normal kindergarten and school schedule. We wanted to study whether and how the use of a social robot could contribute to more systematic training, increased learning intensity, more repetitions and ultimately more effective language learning. In this paper we present experiences from developing, implementing and using the prototype in the two different settings. The prototype is described, as well as the pedagogical settings of the two pilots. We present results from observations of the children and interviews with teachers and supporting personnel. We discuss differences between the two cases and methodological limitations. Finally, we discuss possibilities and challenges of using robots in language learning and training of children.
Curriculum Development Discourse and Practice
Authors: O'Riordan Fiona
Published: February 2025

Curricula in higher education is under increasing pressure to contribute to economic and societal enhancement. Educators are the primary source of curricula development and thus most centrally placed to help deliver on these significant requirements for higher education. Given their central role, the aim of this research was to elucidate the voice of educators with regard to their experience of curriculum development practice and discourse, in the context of higher education. The key objectives in realising this aim was to engage educators in curriculum development discourse; illuminate their philosophical beliefs and influence on curriculum development; irradiate current curriculum development practice; and contribute to capacity building among educators in relation to their role in curriculum development. The study was conducted across four higher education institutions in Ireland, and is part of wider piece of research which formed my Ed.D. Discourse analysis was used as a methodology within a post-structural theoretical framework which facilitated layered analysis and questioning of curriculum development practice and discourse. The findings contribute to the current curriculum development conversation by offering a framework for curriculum development practice and discourse. I argue if this framework is used as an early discourse and planning tool it can offer transformative potential for curricula.
Re-Making Teacher Professional Development
Authors: Hughes Janette  , Morrison Laura  , Dobos Laura
Published: February 2025

With the introduction of the new two-year Bachelor of Education program across Ontario, our Faculty of Education has introduced a twenty-hour internship. This internship is meant to provide real-world teaching experience for teacher candidates, who are nearing the end of their formal education. By maker pedagogies, we refer to the inquiry-based, student-directed, constructionist approaches to learning typically used in makerspaces. Makerspaces have gained traction in Ontario classrooms, particularly in the last two years. These spaces and their pedagogies facilitate the development of students' global competencies (Hughes, 2017; Somanath et al., 2016). We welcomed eleven teacher candidates (TCs) into our STEAM 3D Maker Lab as part of their internship course for professional development (PD) to provide them with pedagogical experience in a makerspace environment. Our research focused on exploring how the TCs developed a better understanding of maker pedagogies and the associated tools through this PD. As the internship was created and facilitated by an education graduate student in the lab, we extended the research to also investigate this student's development in identifying and understanding some of the best practices associated with making as learning. Through analysis of the TCs' and graduate student's experiences, we identify some best practices in maker-focused professional development for beginning teachers.
Civil War: A Board Game as Pedagogy and Critique
Authors: McCabe Hugh
Published: February 2025

This paper describes the use of a board game, Civil War, as a learning experience in the context of a course on critical theory. Civil War was created by the Educational Games Company of Lebanon and is set during the 1975–1990 Lebanese civil war. The game functions both as a pedagogical instrument, in that players learn about the situation in Lebanon while playing the game, but also as a form of critique, in that its makers are clearly using it as a means of articulating their lived experiences and challenging the dominant narratives around the conflict. We suggest that the game is a rare example of one that is counter ideological in nature, as rather than perpetuating stereotyped views of Middle East conflicts that are constructed and imposed from outside, it instead directly presents the experience of those who are inside. A case study of using the game in the context of a class on postcolonialism is presented and responses by students are analysed. We argue that the active experience of playing a board game is an effective way of engaging students with a topic, and in this case in particular, an effective way of connecting them with the lived experiences of others.
Universal Design, but at What Cost? A Case Study on Lifts in Norwegian School Competitions
Authors: Houck Leif D.
Published: February 2025

In a larger perspective, this paper investigates architects' and contractors' attitude towards universal design in the competition phase of the largest school building projects. Three Design Build school competitions with negotiations and one limited architecture competition are examined in terms of to what degree the competitors are willing to invest in lifts. The Norwegian Building Code requires a lift in all public buildings with two or more storeys, and the lift should be easy to locate with its access close to the main entrance. However, a school building often has more main entrances, as the different age groups each tend to have their own entrances. This seems to put the competitors in a dilemma concerning the correct interpretation: Is it sufficient with simply the one lift at the official main entrance, or is it necessary with more lifts in connection with the entrances for the different age groups? The results show that despite the requirements in the Building Codes and the competition briefs, the competitors tend to prioritize lower bids in favor of optimal universally designed buildings. The results also show that any school design, with some reasonable effort, could reach a lift detour of maximum three minutes when using the calculation model applied in this research. However, from a lift user's point of view, any kind of detour may be experienced socially excluding and unacceptable.
TCF–SAE Algorithm for m-Sequence Recognition
Authors: Qiang Fangfang  , Zhao Zhijin  , Chen Ying  , Shen Lei  , Jiang Xianyang
Published: February 2025

A new triple correlation function–sparse autoencoder (TCF–SAE) algorithm based on SAE for m-sequence recognition is proposed. First, the peak characteristic of the TCF of m-sequences is introduced. The peak characteristic is found to be well kept irrespective of periodic or aperiodic m-sequence. Second, a construction method of input sample for network based on the TCF characteristic of m-sequence is proposed. Finally, a feature learning network is constructed by a SAE, and the learned features are classified by softmax regression. A network model with optimal recognition performance is then obtained by simulation experiments with different numbers of hidden layers and hidden units. The results show that the proposed TCF-SAE algorithm for the m-sequence classification is effective and displays a good recognition performance at low signal-to-noise ratio.
Fuzzy Knowledge Discovery and Decision-Making Through Clustering and Dynamic Tables: Application to Bioengineering
Authors: Hernández-Julio Yamid Fabián  , Prieto-Guevara Martha Janeth  , Nieto-Bernal Wilson  , Jiménez-Velásquez César  , Ruíz-Guzmán Javier
Published: February 2025

The objective of this study was to evaluate the main reproductive aspects of the marine cyclopoid copepod Cyclopina sp under laboratory conditions and to design, to implement and to validate a framework for the development of decision system support based on fuzzy set theory using clusters and dynamic tables. To validate the proposed framework, a fuzzy inference system was developed with the aim to estimate reproductive performance (Average fertility – AF, Reproductive frequency – RF, and Reproductive events number – REN) of the marine copepod cyclopina sp submitted to different thermal water and pH values conditions and compared with other Artificial Neural Networks models. The results show that the determination coefficients (R2) for the three output variables for the Fuzzy Inference System – FIS were 1.0, 1.0, and 0.999, respectively. The mean values of the standard deviations were 0.037 eggs, 0.061 hours, and 0.027 reproductive events, respectively, representing mean percentage errors of 0.240, 0.181, and 1.039 %, showing a better accuracy than the ANN-based one. The proposed framework may provide an effective means to draw a pattern to the development of fuzzy systems.
Design for Values for Social Robot Architectures
Authors: Dignum Virginia  , Dignum Frank  , Vazquez-Salceda Javier  , Clodic Aurélie  , Gentile Manuel  , Mascarenhas Samuel  , Augello Agnese
Published: February 2025

The integration of social robots in human societies requires that they are capable to take decisions that may affect the lives of people around them. In order to ensure that these robots will behave according to shared ethical principles, an important shift in the design and development of social robots is needed, one where the main goal is improving ethical transparency rather than technical performance, and placing human values at the core of robot designs. In this abstract, we discuss the concept of ethical decision making and how to achieve trust according to the principles of Autonomy, Responsibility and Transparency (ART).
Event Based Social Networks for Coping Loneliness in Smart Cities
Authors: Kovalevskiy Nikita  , Dahanayake Ajantha  , Zudilova Tatiana
Published: February 2025

The rapid development of smart cities has prompted the increase of different social and psychological problems. The most common are the problems of social anxiety, isolation, and loneliness. This study has revealed how people's lifestyle in smart cities lead to the social isolation, as the result of increase in the level of anxiety and loneliness. Social isolation of lonely people is connected to factors such as the lack of face-to-face communication and the dominance of virtual communications. This research explores development of an event based social network for introducing face-to-face contact for generating events to overcome social isolation and loneliness in smart cities.
Feasibility and System Architecture for Vision Field Measurement Using Virtual Reality Technology
Authors: Manninen Eemeli  , Valve Henrik  , Amarakoon Sankha  , Dahanayake Ajantha
Published: February 2025

The research presented in this paper explores the feasibility of using comparatively inexpensive and highly modifiable virtual reality hardware and software combined with already existing eye tracking solutions to provide alternatives to the field of vision measurement. Virtual reality technology has been rising as a means for gaming for several years now, but the adaptation of this technology to other fields is still in progress. The technology required for such a solution already exists and some relevant prototypes have already been tested, but the applications of virtual reality usage in vision measurement are for now limited to relatively simple operations. The system proposed focuses on perimetry using integrated eye tracking as input for data gathering, software for data validation, and virtual reality headset to show the stimuli.
A Question Answering System on Regulatory Documents
Authors: Collarana Diego  , Heuss Timm  , Lehmann Jens  , Lytra Ioanna  , Maheshwari Gaurav  , Nedelchev Rostislav  , Schmidt Thorsten  , Trivedi Priyansh
Published: February 2025

In this work, we outline an approach for question answering over regulatory documents. In contrast to traditional means to access information in the domain, the proposed system attempts to deliver an accurate and precise answer to user queries. This is accomplished by a two-step approach which first selects relevant paragraphs given a question; and then compares the selected paragraph with user query to predict a span in the paragraph as the answer. We employ neural network based solutions for each step, and compare them with existing, and alternate baselines. We perform our evaluations with a gold-standard benchmark comprising over 600 questions on the MaRisk regulatory document. In our experiments, we observe that our proposed system outperforms other baselines.
Speech Emotion Recognition Based on Back Propagation Neural Network
Authors: Yang Ningning  , Shi Fuqian
Published: February 2025

Speech Emotion Recognition (SER) has become a hot topic recently. In this paper, Back Propagation Neural Network (BPNN) was used as a training system for SER classification, and four emotional speeches of the German Berlin Emotional Database (EMO-DB) were selected as the experimental data-set. The recognition accuracy was compared under different number of nodes in the hidden layer, and the best classification model was determined by combining the training time and the mean squared error (MSE). The experimental results showed that when the number of nodes in the hidden layer is 14, the MSE is minimum, and the average recognition rate of BPNN reaches 98.81%. By compared with different number of nodes in the hidden layer, the average recognition rate increased by 0.2% to 23.5%.
A Semantic Model for Product Configuration in Timber Industry
Authors: Haav Hele-Mai  , Maigre Riina
Published: February 2025

Nowadays, customers require customized products instead of standard offers and in many cases prefer web shops and market places for purchasing goods and services. Therefore, intelligent product configuration tools are great value for many companies. One of the main components of these tools is a configuration model. In order to integrate the configuration model to the semantic web new approaches to the representation of product configuration knowledge are needed. In this paper, we present a layered ontology modelling framework for building semantic product configuration models and provide the corresponding methodological approach to product configuration. The approach enables building distributed product configurators that use semantic configuration models in the form of web ontologies and Shapes Constraint Language (SHACL) to validate integrity constraints of individual configurations. SHACL is also used to query the model and to represent additional constraints required by different applications. The provided method is demonstrated on the basis of the real case study from timber industry that specifically covers thermally modified timber (sawn wood) products.
Morphology-Inspired Word Segmentation for Neural Machine Translation
Authors: Zuters Jānis  , Strazds Gus  , Ļeonova Viktorija
Published: February 2025

This paper proposes the Prefix-Root-Postfix-Encoding (PRPE) algorithm, which performs close-to-morphological segmentation of words as part of text pre-processing in machine translation. PRPE is a cross-language algorithm requiring only minor tweaking to adapt it for any particular language, a property which makes it potentially useful for morphologically rich languages with no morphological analysers available. As a key part of the proposed algorithm we introduce the ‘Root alignment’ principle to extract potential sub-words from a corpus, as well as a special technique for constructing words from potential sub-words. In addition, we supplemented the algorithm with specific processing for named-entities based on transliteration. We conducted experiments with two different neural machine translation systems, training them on parallel corpora for English-Latvian and Latvian-English translation. Evaluation of translation quality showed improvements in BLEU scores when the data were pre-processed using the proposed algorithm, compared to a couple of baseline word segmentation algorithms. Although we were able to demonstrate improvements in both translation directions and for both NMT systems, they were relatively minor, and our experiments show that machine translation with inflected languages remains challenging, especially with translation direction towards a highly inflected language.
Patient and Family Member Readiness, Needs, and Perceptions of a Mental Health Patient Portal: A Mixed Methods Study
Authors: Leung Kevin  , Clark Carrie  , Sakal Moshe  , Friesen Madison  , Strudwick Gillian
Published: February 2025

Patient portals are a form of technology that supports patients in accessing their health information, and other functions like scheduling appointments. The presence and utilization of patient portals in mental health contexts is relatively new. Despite research existing in the mental health literature that indicates that there may be benefits when patients have access to their mental health notes, there is limited information as to how best to implement portals, and support adoption among patients and their family members. Given this gap in literature, this study aimed to identify patient and family readiness, needs, and perceptions of a mental health patient portal. Surveys were administered to patients (n = 103) and family members (n = 7) either in-person or over the phone by a Peer Support Worker. The sample of participants consisted of patients and family members affiliated with Canada's largest mental health hospital located in Toronto, Ontario. Study results indicated that patients had the highest interest in the following portal functions: scheduling appointments, checking appointment times, and accessing their health record. Both patients and family members expressed their concerns about cybersecurity and potential privacy breaches. The results of this study, as well as the approach, can inform future patient portal planning and implementation activities at other healthcare organizations.
A Usability Evaluation of the InfoSAGE App for Family-Based Medication Management
Authors: Quintana Yuri  , Fahy Darren  , Crotty Bradley  , Gorenberg Maxwell  , Jain Ruchira  , Kaldany Eli  , Lipsitz Lewis  , Chen Yi-Pei  , Henao Juan  , Safran Charles
Published: February 2025

The design of a mobile medication manager within a broader family and elder-centric collaboration platform faces challenges of usability and wide applicability. To inform the development and use cases of eldercare apps, we present the preliminary results of a usability study of an iOS and Android app intended for both family members and aging adults for the mobile management of medication lists. Seven participants were recorded during the performance of eight typical use-case scenarios of the medication portion of the InfoSAGE app. Audio and video recordings were analyzed for themes and events. The aim of this paper is to help inform future design choices for eldercare mobile apps.
Smart Home Interactions for People with Reduced Hand Mobility Using Subtle EMG-Signal Gestures
Authors: Vasylkiv Yurii  , Neshati Ali  , Sakamoto Yumiko  , Gomez Randy  , Nakamura Keisuke  , Irani Pourang
Published: February 2025

Smart home technology is receiving significant attention. This is largely in response to an increase in the size of demographic those who require assistance due to reduced mobility, in particular, older adults. Smart home technology enables the assistance individuals with limited mobility need for their daily routines: these limitations can be addressed using modern ambient assisted living technologies. In particular we discuss the benefits of using electromyography (EMG) sensors to capture gestural input that would normally be difficult to sense in the absence of such sensors. With EMG, we can provide user control of a smart environment through the use of gestures based on muscle activity of the hands. This paper will focus on presenting the benefits of EMG technologies that can potentially assist individuals with hand mobility issues. We will describe the current state of EMG sensory technologies and their role in shaping gesture-based interaction techniques. We present our approach using such EMG signals and demonstrate their value in a smart home scenario. Finally we introduce the concept of subtle EMG gestures and build a better understanding of how we might improve accessibility for those with limited upper limb motion.
Design and Usability Evaluation of Mobile Cloud Healthcare System for Diabetes Prevention
Authors: Wang Shu-Lin  , Chiang I-En  , Kuo Alex  , Lin Hsin-I
Published: February 2025

In this study, a mobile cloud healthcare system was implemented to assist middle- and old-aged people with diabetes preventive healthcare. First of all, a prototype system was developed. It was a system relying on data mining computing technology and big data analytics. Besides, it was constructed under the environment architecture of VMware cloud computing. This mobile cloud healthcare system was developed via mobile devices. Its purpose was to set up a diabetes preventive healthcare service for users, and to further assess the usability of this mobile cloud care system.
A Socio-Technical and Lean Approach Towards a Framework for Health Information Systems-Induced Error
Authors: Yusof Maryati Mohd
Published: February 2025

The evaluation of Health Information Systems (HIS)-induced medication errors is crucial in efforts to understand its cause, impact and mitigation measures when trying to minimize errors and increase patient safety. A review of evaluation studies on HIS-induced medication errors was carried out, which indicated the need to further structure complex socio technical aspects of the subject. In order to satisfy this requirement, a new framework was introduced for the evaluation of HIS-induced error management in clinical settings. The proposed HO(P)T-fit framework (Human, Organization, Process and Technology-fit) was developed after critically appraising existing findings in HIS related evaluation studies. It also builds on previous models related to HIS evaluation, in particular, the HOT-fit (Human, Organization, Process and Technology-fit) framework, error model, business process management, Lean method, and medication workflow. HOPT-fit incorporates the concept of fit between the four factors. The framework has the potential to be used as a tool to conduct a structured, systematic, and comprehensive HIS evaluation.
A Social Networks Data Historian Supporting Research in Emergency & Disaster Medicine and Management
Authors: Benis Arriel  , Boim Almog  , Notea Amos
Published: February 2025

The aim of this initial research is to show that data and information collected from Internet Social Networks support the understanding of individual and collective behaviors which can help emergencies and disasters managers to mitigate and to improve preparedness programs for future similar events and to make more suitable decisions.
Wearable Sensors for Nurses: Which Requirements Have to Be Considered?
Authors: Hechtel Nicole  , Krückeberg Jörn  , Marschollek Michael
Published: February 2025

To measure and compare the workload of nurses in a clinical setting raises up some questions. On the one hand we worked out which criteria can represent workload and how it can be measured. On the other hand we compile different requirements for wearable sensors. These requirements can be categorized in four groups: data, robustness, hygiene and usability. These results can support the selection of wearable sensors for a survey of the workload of nurses in a clinical setting.
eHealth Service for Integrated Care and Outpatient Rehabilitation – Pilot Application of the Tyrol Stroke Pathway
Authors: Reiter Kristina  , Runge Julia  , Welte Stefan  , Geley Theresa  , Rissbacher Clemens  , Kastner Peter
Published: February 2025

Background: Stroke is one of third most common causes of death and the main cause for permanent disabilities. The Tyrol Stroke Pathway covers, all steps from stroke onset to outpatient rehabilitation.
Exchanging Appointment Data Among Healthcare Institutions
Authors: Kyburz Philip  , Gfeller Sascha  , Bürkle Thomas  , Denecke Kerstin
Published: February 2025

The introduction of national electronic patient records such as the electronic patient dossier EPD in Switzerland provides a new basis for digitizing healthcare processes at a national level. One process however, that is currently neglected within the Swiss EPD, is the scheduling process in healthcare. The objective of this work is to analyze the appointment scheduling process and the involved IT systems in order to develop an appointment data structure and a concept for cross-institutional exchange of appointment data. The analysis showed that various outpatient and inpatient information systems support appointment booking through proprietary solutions. A true standard for appointment data exchange is missing. We suggest an appointment data structure and a corresponding data exchange process based on the FHIR standard. In its current implementation, the Swiss EPD does not support this proposed appointment scheduling process. We discuss how potential additions such as the IHE Care Services Discovery (CSD) profile can provide better compatibility.