bluuebunny/crossref_metadata_2025 huggingface dataset:
Ontologising Semantic Relations into a Relationless Thesaurus
Authors: Gonçalo Oliveira Hugo  , Gomes Paulo
Published: February 2025

This paper proposes several algorithms for moving from term-based semantic relations to relations between the synsets of a thesaurus. The thesaurus does not encompass semantic relations, and the extraction context is not exploited for this task. The algorithms were compared after evaluation against a gold reference with manual attachments of Portuguese relations into a thesaurus.
Event Processing for Intelligent Resource Management
Authors: Artikis Alexander  , Marterer Robin  , Pottebaum Jens  , Paliouras Georgios
Published: February 2025

The need for intelligent resource management (IRM) spans across a multitude of applications. To address this requirement, we present EP-IRM, an event processing system recognising composite events given multiple sources of information in order to support IRM. EP-IRM has been deployed in two real-world applications. Moreover, with a small effort it may be used in a wide range of applications requiring IRM. We present an evaluation of the system, and discuss the lessons learnt during its development and deployment.
LSA for Mining Hidden Information in Action Game Semantics
Authors: Kermanidis Katia Lida  , Pandis Panagiotis  , Boletsis Costas  , Chasanidou Dimitra
Published: February 2025

This paper describes the application of Latent Semantic Analysis to the term-document matrices that result from modeling an action game. Innovative solutions to address challenges like the definition of “words” and “documents” in the dynamic and complex domain of action games are proposed, and interesting, previously unknown semantic information is extracted.
Wind speed forecasting using spatio-temporal indicators
Authors: Ohashi Orlando  , Torgo Luís
Published: February 2025

From small farms to electricity markets the interest and importance of wind power production is continuously increasing. This interest is mainly caused by the fact that wind is a continuous resource of clean energy. To take full advantage of the potential of wind power production it is crucial to have tools that accurately forecast the expected wind speed. However, forecasting the wind speed is not a trivial task. Wind speed is characterised by a random behaviour as well as several other intermittent characteristics. This paper proposes a new approach to the task of wind speed forecasting. The main distinguishing feature of this proposal is its reliance on both temporal and spatial characteristics to produce a forecast of the future wind speed. We have experimentally tested the proposed method with historical data concerning wind speed on the eastern region of the US. Nevertheless, the methodology that is described in the paper can be seen as a general approach to spatio-temporal prediction. We have compared our proposal to other standard approaches in the task of forecasting 2 hours ahead wind speed. Our extensive experiments show that our proposal has clear advantages in most setups.
Development of Pain Flowsheet Based on Electronic Nursing Record System
Authors: Lee JungMin  , Kim YoungAh  , Jung Hyunsoon  , Song Malsoon
Published: February 2025

Pain assessment and control is the most important issue in medical fields. To manage patient pain effectively with high quality, we need a Pain flowsheet to share patient information of pain between staffs. Nurses already input more information into their electronic nursing record. We focus how to integrate each data and show appropriately without nurse's duplicated work. Finally we develop the Pain flowsheet based on nursing record, that includes the pattern of pain, influential factors, how to implement previously, what to do pain control. This study shows that well designed structured nursing records is an essential basement to advance medical process. In addition, we expect to develop more helpful functions through how to reorganize and combine each data
INCA – Individual Nomad Clinical Assistant – supporting nurses with mobile devices
Authors: Ehrler Frederic  , Walesa Magali  , Sarrey Evelyne  , Wipfli Rolf  , Lovis Christian
Published: February 2025

Introduction: A completely structured nursing record has been deployed in the 8 hospitals of the University hospitals of Geneva. Even with laptops, the access to the records restrains nurses' mobility during their bedside work. It has lead to a strong demand for mobile devices.
Conducting Requirements Analyses for Research using Routinely Collected Health Data: a Model Driven Approach
Authors: de Lusignan Simon  , Cashman Josephine  , Poh Norman  , Michalakidis Georgios  , Mason Aaron  , Desombre Terry  , Krause Paul
Published: February 2025

Background: Medical research increasingly requires the linkage of data from different sources. Conducting a requirements analysis for a new application is an established part of software engineering, but rarely reported in the biomedical literature; and no generic approaches have been published as to how to link heterogeneous health data.
Towards a bilingual Alzheimer's disease terminology acquisition using a parallel corpus
Authors: Drame Khadim  , Diallo Gayo  , Mougin Fleur
Published: February 2025

We present in this paper a method for acquiring a bilingual terminology concerning the Alzheimer's disease using a parallel corpus. NLP techniques are used for parsing English and French texts in order to extract candidate terms. These terms are then matched automatically using an approach that combines two alignment techniques: one based on the calculation of an association score between two terms, and another technique based on the calculation of morphological similarity. This method provided good results on an Alzheimer's disease related corpus with a precision of 73%.
Exploring a methodology for eHealth indicator development
Authors: Hyppönen Hannele  , Ammenwerth Elske  , de Keizer Nicolet
Published: February 2025

Indicators provide a practical method to monitor and benchmark eHealth progress towards objectives set in local, national and international policies, and to offer evidence for eHealth management. There is no agreed methodology to develop and define these indicators. The purpose of this paper is to present a proposal for an indicator development methodology and indicator classification. This proposal combines expert-led top–down and community-based bottom–up approaches. It offers a holistic approach for developing indicators for measuring progress and impacts of eHealth development consisting of four phases: (1) defining the context for measurement, (2) defining the goal of measurement, (3) defining the methods for indicator selection and indicator categorization and (4) defining the data to be collected and analyzed to calculate the indicator. Our preliminary results will be used as a starting point for developing a more detailed description of methods for indicator development and for identifying and classifying eHealth indicators and on testing them in practice.
Proactive Authenticated Notifications for Health Practitioners: two way Human Computer Interaction Through Phone
Authors: Majeed Raphael W.  , Stöhr Mark R.  , Röhrig Rainer
Published: February 2025

Notifications and alerts play an important role in clinical daily routine. Rising prevalence of clinical decision support systems and electronic health records also result in increasing demands on notification systems. Failure adequately to communicate a critical value is a potential cause of adverse events. Critical laboratory values and changing vital data depend on timely notifications of medical staff. Vital monitors and medical devices rely on acoustic signals for alerting which are prone to “alert fatigue” and require medical staff to be present within audible range. Personal computers are unsuitable to display time critical notification messages, since the targeted medical staff are not always operating or watching the computer. On the other hand, mobile phones and smart devices enjoy increasing popularity. Previous notification systems sending text messages to mobile phones depend on asynchronous confirmations. By utilizing an automated telephony server, we provide a method to deliver notifications quickly and independently of the recipients' whereabouts while allowing immediate feedback and confirmations. Evaluation results suggest the feasibility of the proposed notification system for real-time notifications.
An Engine for Compliance Checking of Clinical Guidelines
Authors: Mei Jing  , Liu Haifeng  , Xie Guotong  , Lakshmanan Geetika T.
Published: February 2025

Although, clinical guidelines are regarded as best practices for clinicians, clinician activities are not always compliant with guideline recommendations. This paper aims to improve clinician compliance with guidelines. We have developed an engine to automatically report three non-compliance situations: 1) guideline recommendations exist, and the clinician performed some activities, but not according to the guidelines; 2) guideline recommendations exist, but the clinician did nothing; 3) guideline recommendations do not exist, but the clinician performed some activities. In particular, we highlight effective time for compliance checking, as well as membership, numeric relationships, concept subsumption and contextualization. We deployed our engine to a clinical setting involving the daily care routine of diabetes patients, and generated non-compliance reports for pilot users.
Does Telecare Reduce the Number of Treatment Days?
Authors: Akematsu Yuji  , Tsuji Masatsugu
Published: February 2025

This paper analyzes the effect of telecare in reducing the number of days required for the treatment of telecare users. Statistical analysis was conducted on panel data about 400 individuals from 2002 to 2006 in Nishi-aizu Town, Fukushima Prefecture, Japan. Three estimation models were used, namely the Instrument Variable, Instrument Variable Panel, and system GMM (Generalized Method of Moments) methods, both to demonstrate causality and to ensure the robustness of the results. We attempted to reduce sample selection bias in this framework by controlling variables with bias. A negative correlation between outpatient days and telecare use was observed with the former two methods, while the system GMM proved causality for the effect of telecare in reducing the number of outpatient days. Telecare use reduced outpatient days in telecare users by 2.0 days per year. This result is consistent with those of other telecare implementations in the US and the UK.
Using Enterprise Ontology for Improving Emergency Management in Hospitals
Authors: Galego Dias David  , Lapão Luís Velez  , da Silva Miguel Mira
Published: February 2025

In a competitive world, healthcare organizations are forced to make improvements in order to compete and prosper. Healthcare services suffer from lack of change and inefficiency, which affects the delivery of sustainable services. We propose a method based on DEMO to find non value-added transactions that must be redesigned to simplify processes. This methodology was chosen as a basis for our solution because it provides a better understanding of the dynamics of an organization, has a strong and well-formed theory, and allows a good alignment between the enterprise design and operation. A demonstration of the method was accomplished in an emergency department, making it possible to find transactions that can be improved or automated. To evaluate the results we used interviews, Moody and Shanks Quality Framework, and the Four Principles from Österle et al., which shows that the method yields an adequate and clear process view and is reliable when it comes to improving healthcare operational processes.
Isolation of patients with Vancomycin Resistant Enterococci (VRE): Efficacy of an electronic alert system
Authors: Borbolla Damian  , Taliercio Vanina  , Schachner Bibiana  , Gomez Saldano Ana Maria  , Salazar Estela  , Luna Daniel  , Gonzalez Bernaldo de Quiros Fernan
Published: February 2025

This study investigates the implementation of an alert system for the isolation of vancomycin resistant enterococci (VRE) colonized patients. Given the risk of admitting a patient colonized by VRE it is necessary to implement efficient isolation measures. An electronic alert system integrated into a health information system (HIS) could help with the detection of these patients and their isolation in proper units.
Recognition and Privacy Preservation of Paper-based Health Records
Authors: Fenz Stefan  , Heurix Johannes  , Neubauer Thomas
Published: February 2025

While the digitization of medical data within electronic health records has been introduced in some areas, massive amounts of paper-based health records are still produced on a daily basis. This data has to be stored for decades due to legal reasons but is of no benefit for research organizations, as the unstructured medical data in paper-based health records cannot be efficiently used for clinical studies. This paper presents a system for the recognition and privacy preservation of personal data in paper-based health records with the aim to provide clinical studies with medical data gained from existing paper-based health records.
Rare diseases knowledge management: the contribution of proximity measurements in OntoOrpha and OMIM
Authors: Aimé X.  , Charlet J.  , Furst F.  , Kuntz P.  , Trichet F.  , Dhombres F.
Published: February 2025

In this paper, we introduce an application of Proxima and define a new measure of proximity between two concepts present in an ontology. The approach is based on the three dimensions of a conceptualization: intension with relations between concepts, expression with terms denoting concepts, and extension with instances of concepts. This preliminary work, in the field of rare diseases, involved the Orphanet Ontology of Rare Diseases (OntoOrpha) and corpus of texts extracted from Online Inheritance in Man (OMIM). The proximity measurements are consistent with an appropriate representation of groups of diseases in the ontology, which are derived from the Orphanet classifications of rare diseases. Other semantic relations are explored and new perspectives in medical knowledge curation are proposed.
Method for Modeling Social Care Processes for National Information Exchange
Authors: Miettinen Aki  , Mykkänen Juha  , Laaksonen Maarit
Published: February 2025

Finnish social services include 21 service commissions of social welfare including Adoption councelling, Income support, Child welfare, Services for immigrants and Substance abuse care. This paper describes the method used for process modeling in the National project for IT in Social Services in Finland (Tikesos). The process modeling in the project aimed to support common national target state processes from the perspective of national electronic archive, increased interoperability between systems and electronic client documents. The process steps and other aspects of the method are presented. The method was developed, used and refined during the three years of process modeling in the national project.
Knowledge Representation for Fuzzy Inference Aided Medical Image Interpretation
Authors: Gal Norbert  , Stoicu-Tivadar Vasile
Published: February 2025

Knowledge defines how an automated system transforms data into information. This paper suggests a representation method of medical imaging knowledge using fuzzy inference systems coded in XML files. The imaging knowledge incorporates features of the investigated objects in linguistic form and inference rules that can transform the linguistic data into information about a possible diagnosis. A fuzzy inference system is used to model the vagueness of the linguistic medical imaging terms. XML files are used to facilitate easy manipulation and deployment of the knowledge into the imaging software. Preliminary results are presented.
Combined classifier constructed from the reduced dataset obtained using fuzzy C-means and differential evolution algorithms
Authors: JĘDrzejowicz Joanna  , JĘDrzejowicz Piotr
Published: February 2025

In this paper we propose a simple and effective combined classifier based on the data reduction carried-out through applying fuzzy C-means clustering and differential evolution techniques. The idea is to produce clusters from the training set instances applying fuzzy C-means algorithm. In further step cluster centroids are used as seeds in the differential evolution algorithm to construct prototypes, each representing a single cluster. Simple distance-based weak classifiers are then used to produce the Ada Boost combined classifier. The approach has been validated experimentally. Computational experiment results confirm good quality of the proposed classifier.
Risk based Government Audit Planning using Naïve Bayes Classifiers
Authors: Balaniuk Remis  , Bessiere Pierre  , Mazer Emmanuel  , Cobbe Paulo
Published: February 2025

In this paper we consider the application of a naïve Bayes model for the evaluation of fraud risk connected with government agencies. This model applies probabilistic classifiers to support a generic risk assessment model, allowing for more efficient and effective use of resources for fraud detection in government transactions, and assisting audit agencies in transitioning from reactive to proactive fraud detection model.
Multi-Agent Based System for Analysing Stress using the StressCafé
Authors: Ghosh Anusua  , Tweedale Jeffery W.  , Nafalski Andrew  , Dollard Maureen
Published: February 2025

Work related stress affects people from all professions and is a growing concern because it is reported as a common cause of occupational illness. Work stress can be prevented if it is identified; measured and appropriate changes are made to the work environment. Intelligent agent technology to solve both simple and complex problems has been used in many applications but this technology has not been applied in psychology. These agents provide better management of complex systems or processes as the level of abstraction is much higher and the programming problems focus on specifying an agent’s behaviour and communication with other agents. In this paper, we present a novel approach of using Multi-Agent System (MAS) to effectively maintain, analyse and update work-stress related data. The MAS part of Intelligent Multi-Agent Decision Analyser (IMADA) has been integrated with the existing Intelligent Agent Framework (IAF) model that has been developed in conjunction with the StressCafé using the Australian Workplace Barometer (AWB) tool. The intelligent decision analyser Decision Analyser (DA) will be developed using a hybridized algorithm that uses neural network and fuzzy logic.
An Efficient Algorithm to Predict Three-way Interaction of Proteins from Expression Data Based on Conditional Probability
Authors: Fujiki Takatoshi  , Inoue Etsuko  , Yoshihiro Takuya  , Nakagawa Masaru
Published: February 2025

It is important to predict interaction among proteins to understand the system of life. We have proposed a method to predict threeway interactions among proteins from expression data based on conditional probability in our previous study. However, the proposed method has a problem of significant computational time, because it requires computation of a probability distribution as a preprocess of the algorithm. In this study, we propose a method to significantly reduce the computational time by computing the probability distribution with analytical approach, instead of simulation approach used in our previous study. We evaluated the computational time and accuracy of the proposed analytical computation method.
A Novel Channel Estimation Scheme Combining Adaptive Supervised and Unsupervised Algorithms
Authors: Dapena Adriana  , Labrador Josmary  , Castro Paula M.  , García-Naya Josée A.
Published: February 2025

Channel estimation is a fundamental operation in digital communication systems that could be done using supervised or unsupervised (blind) strategies. Supervised techniques estimate the channel parameters using training symbols (pilots) included in the data frame, while unsupervised methods acquire information directly from the received signals. In this paper, we compare both strategies and propose a novel hybrid channel estimation method which provides performance similar to that achieved with the supervised algorithm but using a significantly more reduced number of pilot symbols. Such a hybrid scheme uses the information obtained at the receiver during the frame synchronization to decide the algorithm to be used in the data retrieval.
Mobile Sentiment Analysis
Authors: Chambers Lorraine  , Tromp Erik  , Pechenizkiy Mykola  , Medhat Gaber Mohamed
Published: February 2025

Mobile devices play a significant part in a user’s communication methods and much data that they read and write is received and sent via mobile phones, for instance SMS messages, e-mails, Twitter tweets and social media networking feeds. One of the main goals is to make people aware of how much negative and positive content they read and write via their mobile phones. Existing sentiment analysis applications perform sentiment analysis on downloaded data from mobile phones or use an application installed on another computer to perform the analysis. The sentiment analysis described in this paper is to be performed locally on the mobile phone enabling immediate and private analysis of personal messages and social media contents, allowing the users to be able to reason about their mood and stress level that may be affected by what they had been receiving. Experimental results showed the effectiveness of the proposed system on Android smartphones with varying computational capabilities.
Privacy Aware Community based Recommender Service for Conferences Attendees
Authors: Elmisery Ahmed M.  , Doolin Kevin  , Botvich Dmitri
Published: February 2025

With the rapid growth of social networks and users communities the need to attain privacy for end-users becomes mandatory especially with the recent privacy breaches and the inefficiency of anonymisation techniques [1]. The problem of maintaining privacy in recommender services become increasingly important since it aims at finding information that might be interesting to end-users without disclosing their real interests to the service. In this paper, we present a middleware that runs in end-users’ mobile phones to provide referrals for joining different sub-communities in conferences or exhibitions in private way. Moreover, the proposed middleware facilitates identifying similarity between various attendees in order to build a community with specific interest without disclosing their real preferences or interests to other parties. Our proposed middleware equipped with two cryptography protocols in order to achieve this purpose. In such case, the attendees can submit their preferences in an encrypted form and the further computation of recommendation proceeds over the encrypted data using secure multiparty computation protocols. We also provide a scenario for community based recommender service for conferences along with experimentation results. Our results shows that our proposed middleware not only protect the attendees’ privacy, but also can maintain the recommendation accuracy.
Evaluation of Random Subspace and Random Forest Regression Models Based on Genetic Fuzzy Systems
Authors: Lasota Tadeusz  , Telec Zbigniew  , Trawiński Bogdan  , Trawiński Grzegorz
Published: February 2025

The random subspace and random forest ensemble methods using a genetic fuzzy rule-based system as a base learning algorithm were developed in Matlab environment. The methods were applied to the real-world regression problem of predicting the prices of residential premises based on historical data of sales/purchase transactions. The computationally intensive experiments were conducted aimed to compare the accuracy of ensembles generated by the proposed methods with bagging, repeated holdout, and repeated cross-validation models. The statistical analysis of results was made employing nonparametric Friedman and Wilcoxon statistical tests.
Generating Abstract Arguments: A Natural Language Approach
Authors: Cabrio Elena  , Villata Serena
Published: February 2025

Many argumentation tools have been proposed nowadays to support the users in on-line social discussions. However, the main drawback of these tools is that they do not cope with the automatic generation of the arguments from the natural language discussions of the users. In this paper, we propose to use a technique from computational linguistics, namely textual entailment, to generate in an automatic way the abstract arguments from the dialogues. The abstract arguments as well as their relationships are then structured in an argumentation graph to evaluate the dialogue as a whole. The success criteria of the proposed approach is that it is able to represent the dynamics of the dialogues among users allowing to find the use of argumentation natural enough to be really adopted.
Improving Social Behaviour in Schizophrenia Patients using an Integrated Virtual Reality Programme: A Case Study
Authors: Rus-Calafell M.  , Gutiérrez-Maldonado J.  , Ribas-Sabaté J.
Published: February 2025

Social skills training programmes are among the treatments of choice in schizophrenia. Virtual reality (VR) can improve the results obtained with traditional social skills programmes by helping to generalize the acquired responses to patients' daily lives. We present the results of a case study involving the application of an integrated VR programme for social skills training. A 30-year-old woman with a well-established diagnosis of schizophrenia was enrolled in the study. She completed four baseline sessions, 16 treatment sessions and four follow-up sessions three months after the end of the treatment. Using a multiple baseline across-behaviours design, three target behaviours were analysed: facial emotion recognition, social anxiety and conversation time. Symptoms and social function variables were also assessed. The results showed a positive change in the three target behaviours and improvements in interpersonal communication, assertiveness and negative symptoms. The VR programme proved useful for training the patient's social behaviour and, consequently, for improving her performance.
Nicotine Craving: ERPs correlates after VR exposure to smoking cues
Authors: Gamito Pedro  , Oliveira Jorge  , Baptista André  , Morais Diogo  , Lopes Paulo  , Saraiva Tomaz  , Rosa Pedro  , Santos Nuno  , Soares Fábio  , Sottomayor Catarina  , Barata Filipa
Published: February 2025

Even though it is diminishing in Europe, smoking is still a serious health problem. The craving of Nicotine is one of the hardest behaviours to tackle when a smoking cessation programme is implemented. Following on previous work [1], which aimed at evaluating the possibility of inducing smoking craving in smokers using a VR platform, the present study was devised to assess the role of craving in cognitive processing through event related potentials (ERP). From an initial sample of 89 university students (smokers and non-smokers), which was randomly exposed to VR smoking cues and VR non-smoking cue scenarios, a subsample of 13 smokers and non-smokers was drawn. This subsample (M = 23.08; SD = 4.39), which had previously been immersed in the VR smoking cues environment, was presented to a rapid (1 sec) serial of smoking and neutral images. Data on brain activity was recorded through an EEG during this task to further estimate ERPs. When compared to non-smokers, smokers showed higher frontal activation when watching smoking related images.
Assessment of Executive Functions in Patients with Obsessive Compulsive Disorder by NeuroVR
Authors: La Paglia Filippo  , La Cascia Caterina  , Rizzo Rosalinda  , Riva Giuseppe  , La Barbera Daniele
Published: February 2025

Executive functions are often impaired in obsessive-compulsive disorder (OCD). We used a Virtual Reality version of the Multiple Errand Test (VMET) – developed dusing the free NeuroVR software (http://www.neurovr.org) – to evaluate the executive functions in daily life in 10 OCD patients and 10 controls. It is performed in a shopping setting where there are items to be bought and information to be obtained. The execution time for the whole task was higher in patients with OCD compared to controls, suggesting that patients with OCD need more time in planning than controls. The same difference was found in the partial errors during the task. Furthermore, the mean rank for and for interpretation failures is higher for controls, while the values of divided attention and the of self correction seems to be lower in controls. We think that obsessive patients tend to work with greater diligence and observance of rules than controls. In conclusion, these results provide initial support for the feasibility of VMET as assessment tool of executive functions. Specifically, the significant correlation found between the VMET and the neuropsychological battery support the ecological validity of VMET as an instrument for the evaluation of executive functions in patients with OCD.
Integrating Non-Monotonic Reasoning into High Level Component-Based Modelling Using Behavior Trees
Authors: Chan Lin Wah  , Hexel René  , Wen Lian
Published: February 2025

In this paper we investigate how combining two types of modelling languages will increase their expressive power. The Behavior Tree method and non-monotonic logic will be integrated.
Decision Support System for Handling Interruption in Tasks for Workers
Authors: Sugawara Kohei  , Fujita Hamido
Published: February 2025

Work continuity is interrupted by other work. Worker must consider appropriate approach for the generated task from interruption. The proposed system assists the worker's decision to improve the work efficiency by recommending the alternatives based on expert knowledge for the interruption context. The context of the interruption is reasoned according to the worker's profile. The generated task by interruption is related to each worker's historical experience. The proposed system recommends appropriate next action to the worker by computing the effect of the alternatives through the reasoning of interruption context.
Asymmetric Agreement in Pronominal Anaphora
Authors: Di Sciullo Anna Maria
Published: February 2025

Adjuncts contribute to the spatiotemporal anchoring of events and situations described by linguistic expressions, while arguments describe the participants of events and situations. We show how a deterministic parser, based on the recovery of asymmetric relations, enables the identification of adjuncts as possible antecedents to pronouns, whether they are located in the domain of the sentence or in the domain of the discourse. We suggest that Information technologies and Natural language processing more generally should rely on pronominal anaphora resolution based on asymmetric agreement in order to improve their performance.
Towards a Latvian Valency Lexicon
Authors: Nešpore Gunta  , Saulīte Baiba  , Grūzītis Normunds  , Garkāje Ginta
Published: February 2025

A development of a verb valency lexicon for Latvian has been recently started. The chosen approach combines and supplements the experience of similar lexical resources developed for other languages. The paper describes our approach to the verb valency annotation—the valency layers (syntactic and semantic valency, selectional restrictions) and the set of the semantic roles. The annotation process using an online tool developed for the valency annotation is also briefly described. From the annotated corpus examples, the valency patterns (models) for each verb are generated considering only the core semantic roles. As a result of this work, a summarized information of valency patterns for each verb will be available, as well as a corpus of the annotated examples. Currently, more than 150 verbs (more than 16 000 sentences) have been annotated using data from the Balanced Corpus of Modern Latvian.
Telemonitoring of Medication Adherence in Patients with Major Mental Illness: Watching the Patient as well as the Pills
Authors: Zimmerman Norman
Published: February 2025

Many patients with major mental illness do not take their medication. This leads to repeated relapses. Some of these patients are managed by clinicians who visit the patient seven days a week long term and supervise their taking of medication. This paper explores the design and implementation of an Android telemonitoring application to supervise patients taking medication in their homes.
Design of a Large Scale Community-Based Self-Management System for Diabetes Mellitus
Authors: Chan Ka C.  , Wong Lucia  , Chan David B.
Published: February 2025

This paper presents the ongoing development of a community based, self-management system for diabetes mellitus, which incorporates web-based, SMS and mobile-terminal functionalities. SMS represents the first stage of our system development as it is widely available on all mobile phones, convenient and becoming increasingly popular. We discuss past findings and the need for such a system, as well as design, implementation and system architecture. Poor self-management of diabetes is associated with progression into more complex health issues, manifesting as a significant public health burden and impacting negatively on an individual's quality of life. This approach recognizes that telehealth systems will play an increasingly pertinent role in health systems worldwide.
Software Self-Testing
Authors: Diebelis Edgars  , Bicevskis Janis
Published: February 2025

The paper presents an overview of the results of 5 years of research in the field of self-testing. In 2007, self-testing was defined as one direction of smart technologies, a common idea of which is the desire to fit software with features of living beings: abilities to adapt to changing external environment, to optimize themselves and to defend themselves against threats. The purpose of self-testing is to provide a possibility to verify that the software is working correctly at any point of its life cycle. The research was carried out in several stages: at first, the concept and functionality of self-testing and its applicability in various software operating environments were defined; it was followed by implementing the self-testing functionality by integrating testing support options into the software developed. After that, the self-testing concept was compared against the possibilities offered by traditional testing support tools and implemented in an actual banking information system, and the efficiency of self-testing options was evaluated. The final conclusions drawn are: self-testing offers a number of advantages in achieving the software quality at comparatively low costs, at the same time ensuring the same functionality as provided by conventional testing support tools.
Qualitative Reasoning about Space with Hybrid Logic
Authors: Norgėla Stanislovas  , Andrikonis Julius  , Stočkus Arūnas
Published: February 2025

This article describes the way to employ hybrid logic ℋ(@,↓) in the analysis of qualitative spatial information. Moreover, it shows how the complexity of model checking algorithm is derived using the Kripke structure of qualitative spatial information and the query, which is presented as a formula of hybrid logic.
Specification, Configuration and Implementation of DSL Tool
Authors: Sprogis Arturs  , Barzdins Janis
Published: February 2025

A new specification method for DSL and DSL tools is proposed. The method is based on an advanced stereotype mechanism. A special feature of the proposed method is a precise definition of the extension mechanism for realization of non-standard features of DSL tools. In conclusions the architecture of a DSL tool building framework based on the proposed specification method is described.
What Makes a System a Legal Expert?
Authors: Bench-Capon Trevor
Published: February 2025

Since the 1980s, AI and Law has attempted to capture legal expertise in computer programs. But what is this expertise? This paper reviews a number of approaches, from the 1980s to the present day, which represent different answers to this question. It argues that our notion, and understanding, of expertise has developed and improved over the decades. As yet, however, only a few rather specific aspects have been addressed in detail, in particular the move from intermediate predicates to legal consequences, and the distinguishing of precedents. Much more, including the moves from evidence to facts and from facts to intermediate predicates, awaits exploration.
ThinkData: a Data Protection and Transparency Awareness Service based on Storytelling
Authors: Morin Jean-Henry  , Glassey Olivier
Published: February 2025

ThinkData is an interactive online service that aims at raising awareness about data protection and transparency within organizations in Switzerland. This service was created by an interdisciplinary group using design thinking techniques. ThinkData was designed with the very pragmatic objective of engaging its users in becoming familiar with data protection and transparency concepts through storytelling. Scenarios can be browsed by activities, by topics and by data types. This paper reports on the design and deployment of this service making the case for the underlying issue of using storytelling as a valuable approach for awareness and training on complex legal issues.
Topic Detection about the East Japan Great Earthquake based on Emerging Modularity
Authors: Hashimoto Takako  , Kuboyama Tetsuji  , Shirota Yukari
Published: February 2025

Once a disaster occurs, people discuss various topics in social media such as electronic bulletin boards, SNSs and video services, and their decision-making tends to be affected by discussions in social media. Under the circumstance, a mechanism to detect topics in social media has become important. This paper targets the East Japan Great Earthquake, and proposes a time series topic detection method based on modularity measure which shows the quality of a division of a network into modules or communities. Our proposed method clarifies emerging topics from social media messages by computing the modularity and analyzing them over time, and visualizes topic structures. An experimental result by actual social media data about the East Japan Great Earthquake is also shown.
Tunnelling projects in Greece, challenges, gained experiences and achievements
Authors: Michalis Ilias K.
Published: February 2025

Tunnelling in Greece has shown a remarkable development in the last 20 years and this is due to the real “cosmogony”, which was occurred during the aforesaid period, in the infrastructure projects. Indeed, since the early 1990's and until even recently, a very large number of motorway and railway projects (i.e. Egnatia Motorway, Motorways Concession Projects, Athens and Thessaloniki Metros, ERGOSE railway lines, etc.), either were fully constructed or are in the stage of their completion. As a consequence, significant design and construction experiences, which are related directly to the tunnels' excavation schemes, primary support measures and different types of final lining (i.e reinforced, lightly reinforced or unreinforced) in a wide variety of geological / geotechnical conditions, were gained. The obvious merit from all these experiences, is that if they will be applied within reasonable frameworks of application, can offer significantly to the necessary tunnels designs' optimisations and to the rationalisation of the corresponding tunnels' construction costs. The future of tunnelling in Greece seems promising through new financing models (i.e. concession agreements), since one of the obvious mid-term “antidote” to the economic recession is the investment to the construction of new but necessary infrastructure projects. Some of these new projects are the extensions of Athens and Thessaloniki Metros, new urban and suburban motorways and new railway lines.
The Aspherical Human Hip: Implication for Early Osteoarthritis
Authors: Hefny Mohamed S.  , Dickinson Andrew W.L.  , Giles Andrew E.  , Wood Gavin C.A.  , Ellis Randy E.
Published: February 2025

One marker for early-onset hip arthritis is femoral acetabular impingement. The current standard way of quantifying impingement is manual calculation of anatomical measures on plain radiographs, including the α-angle. Such measurements are user-dependent and prone to error. We provided a robust computational alternative and proposed using numerical fitting of geometrical shapes. We applied least-squares fitting of an ellipse to the femoral head contour and used the difference between the ellipse axes as a quantification method. The results showed a good correlation between the new measure and previous definitions of the α-angle.
Pupil Response to Precision in Surgical Task Execution
Authors: Jiang Xianta  , Zheng Bin  , Tien Geoffrey  , Atkins M. Stella
Published: February 2025

Task-evoked pupil response (TEPR) has been extensively studied and well proven to be sensitive to mental workload changes. We aimed to explore how TEPR reflects mental workload changes in a surgical environment. We conducted a simulated surgical task that has 3 different subtasks with different levels of motor precision and different mental workload requirements. We found a significant effect among these different subtask groups by measuring pupil diameter change rate. This finding may improve patient safety in a real operating room by non-intrusively monitoring the surgeon's mental workload while performing a surgery using an eye-tracking system.
Kinematic Analysis of Motor Performance in Robot-Assisted Surgery: A Preliminary Study
Authors: Nisky Ilana  , Patil Sangram  , Hsieh Michael H.  , Okamura Allison M.
Published: February 2025

The inherent dynamics of the master manipulator of a teleoperated robot-assisted surgery (RAS) system can affect the movements of a human operator, in comparison with free-space movements. To measure the effects of these dynamics on operators with differing levels of surgical expertise, a da Vinci Si system was instrumented with a custom surgeon grip fixture and magnetic pose trackers. We compared users' performance of canonical motor control movements during teleoperation with the manipulator and freehand cursor control, and found significant differences in several aspects of motion, including target acquisition error, movement speed, and acceleration. In addition, there was preliminary evidence for differences between experts and novices. These findings could impact robot design, control, and training methods for RAS.
Impedance Measurements in the Biomedical Sciences
Authors: Coffman Frederick D.  , Cohen Stanley
Published: February 2025

Biological organisms and their component organs, tissues and cells have unique electrical impedance properties. Impedance properties often change with changes in structure, composition, and metabolism, and can be indicative of the onset and progression of disease states. Over the past 100 years, instruments and analytical methods have been developed to measure the impedance properties of biological specimens and to utilize these measurements in both clinical and basic science settings. This chapter will review the applications of impedance measurements in the biomedical sciences, from whole body analysis to impedance measurements of single cells and cell monolayers, and how cellular impedance measuring instruments can now be used in high throughput screening applications.
Supporting Drug Prescription through Autocompletion
Authors: Ehrler Frederic  , Lovis Christian
Published: February 2025

Computerized prescription is a central component in modern clinical information systems. It allows scheduling drugs delivery, exams and other types of care. It is thought to be a useful tool for the reduction of medication errors and for the improvement of medication logistics. Whereas the success of the computerized prescription depends on the unambiguous selection of the manipulated concepts, there is a strong variability between the preferred terms of clinicians of different backgrounds. Moreover, users sometimes want to use synonyms or don't know the exact spelling of the term. This makes the search for desired procedure name through large size vocabularies time-consuming for users. In order to facilitate the prescriptions process, we have built a tool that proposes the most likely terms based on the first letters inputted by the user. The tool helps selecting the most appropriate term by ranking the possible results in a clever manner. Experimental evaluation shows promising results and indicates the tool ease the terminology manipulations.
Computational Cognitive Modeling for the Diagnosis of Specific Language Impairment
Authors: Oliva Jesus  , Serrano J. Ignacio  , Del Castillo M. Dolores  , Iglesias Ángel
Published: February 2025

Specific Language Impairment (SLI), as many other cognitive deficits, is difficult to diagnose given its heterogeneous profile and its overlap with other impairments. Existing techniques are based on different criteria using behavioral variables on different tasks. In this paper we propose a methodology for the diagnosis of SLI that uses computational cognitive modeling in order to capture the internal mechanisms of the normal and impaired brain. We show that machine learning techniques that use the information of these models perform better than those that only use behavioral variables.
Agent-based Military Engagement Simulation System Architecture with Implementation
Authors: Hwam Won K.  , Chung Yongho  , Kim Junghoon  , Park Sang C.
Published: February 2025

Presented in this paper is architecture of a simulation system for the military engagement. The architecture proposed in this paper is for the construction of a simulation system based on agent simulation design methodology. Every entity of the proposed architecture is defined of assemblage of modularized agent components, and it enhances the reusability and composability of the entity. Consequently, time, costs, and efforts that are required to develop a new simulation system are able to be reduced by the improved entity modeling methodology of the architecture. In the case of the military engagement simulation, reflection of environmental effects to simulation entities is very important, because real battle entities are operating in the battlefield of which cannot be controlled by operators. The proposed architecture contains the synthetic battlefield to simulate interaction between the environment and simulation entities. Thus, each behavior of simulation entities is changeable by the effects, and it can derive more precise results that well-represent real system operation. In conclusion, the proposed architecture supports swift construction of various engagement simulation systems that are based on the synthetic battlefield. The architecture of this paper is implemented to construct an example system for verification of the advantages.
PHM-Ethics and ETICA: Complementary Approaches to Ethical Assessment
Authors: Mittelstadt Brent  , Stahl Bernd  , Fairweather Ben
Published: February 2025

The chapter undertakes a comparison of different approaches to the ethical assessment of novel technologies by looking at two recent research projects. ETICA was a FP7 sister project to PHM-Ethics, responsible for identification and ethical evaluation of information and communication technologies emerging in the next 10–15 years. The aims, methods, outcomes and recommendations of ETICA are compared to those of PHM-Ethics, with identification of linkages and similar findings. A relationship is identified between the two projects, in which the assessment methodologies developed in the projects are shown to operate at separate, but complementary levels. ETICA sought to reform EU ethics governance for emerging ICTs. The outcomes of PHM-Ethics are analyzed within the policy recommendations of ETICA, which demonstrate how the PHM-Ethics toolbox can contribute to ethics governance reform and context-sensitive ethical assessment of the sort called for by ETICA.