bluuebunny/crossref_metadata_2025 huggingface dataset:
Harmonising Nursing Terminologies Using a Conceptual Framework
Authors: Jansen Kay  , Kim Tae Youn  , Coenen Amy  , Saba Virginia  , Hardiker Nicholas
Published: February 2025

The International Classification for Nursing Practice (ICNP®) and the Clinical Care Classification (CCC) System are standardised nursing terminologies that identify discrete elements of nursing practice, including nursing diagnoses, interventions, and outcomes. While CCC uses a conceptual framework or model with 21 Care Components to classify these elements, ICNP, built on a formal Web Ontology Language (OWL) description logic foundation, uses a logical hierarchical framework that is useful for computing and maintenance of ICNP. Since the logical framework of ICNP may not always align with the needs of nursing practice, an informal framework may be a more useful organisational tool to represent nursing content. The purpose of this study was to classify ICNP nursing diagnoses using the 21 Care Components of the CCC as a conceptual framework to facilitate usability and inter-operability of nursing diagnoses in electronic health records. Findings resulted in all 521 ICNP diagnoses being assigned to one of the 21 CCC Care Components. Further research is needed to validate the resulting product of this study with practitioners and develop recommendations for improvement of both terminologies.
Promoting mHealth in Nursing Practice in China
Authors: Liu Yisi  , Wu Ying  , Gong Yang
Published: February 2025

The purpose of this project was to reveal the status quo of mHealth application in clinical settings in China, especially in reducing patient falls and pressure ulcers and discuss how patient safety could be enhanced in the context of global collaboration on patient safety. The literature search resulted in a total of 290 articles. A steady increase is witnessed in the field of mHealth, especially after the year 2010. Personal digital assistant and electronic cart are the two main devices used in mobile nursing workstation. mHealth was mainly focused on two clinical areas, nursing practice (60.69%) and nursing management (25.86%). mHealth has begun to change the way of nursing process in prevention of adverse nurse events with an encouraging results in reducing the rate of pressure ulcer and falls. Healthcare educators should fully recognize the characteristics of mHealth and enhance a clinical informatics component in the curricula.
A Systematic Review and Meta-Analysis of Intervention for Pediatric Obesity Using Mobile Technology
Authors: Lee Jisan  , Piao Meihua  , Byun Ahjung  , Kim Jeongeun
Published: February 2025

We reviewed the effect sizes of pediatric obesity intervention studies using mobile technology. Ten databases (Cochrane CENTRAL, CINAHL, EMBASE, PubMed/Medline, KoreaMED, KMBASE, KISS, NDSL, KSITI, and RISS) were reviewed, and four studies were included in a qualitative synthesis. To obtain significant change in obesity-related outcomes among elementary school students, including parents and utilizing text messages in interventions are recommended. Furthermore, devices such as accelerometers may aid obesity management. A meta-analysis of four studies indicated that the mobile intervention positively influenced dropout rates but was ineffective for outcomes of weight control, exercise, and sugar-sweetened beverage intake.
Heuristic Evaluation of a mHealth Diabetes Self-Management System Using Disease Specific Patient Profiles
Authors: Georgsson Mattias  , Staggers Nancy
Published: February 2025

Patient-centeredness is an important concept in diabetes treatment. We modified Nielsen's expert heuristic evaluation method addressing common gaps: a patient perspective and variability in findings. Two expert, dual-domain evaluators referred to validated patient profiles (mild, moderate, severe diabetes) when conducting uniform evaluation processes on a diabetes mHealth system. Evaluators found 103 usability problems and 224 heuristic violations. For 69% of the problems, the profiles had an effect on severity ratings. “Consistency and Standards” (n = 57) and “Match between the System and Real World” (n = 55) violations dominated at 50%. The overall system severity rating was major. Severity was highest for a severe diabetic profile due to likely visual issues (crowded elements), cognitive concerns (remembering many steps) and for insufficient medication information. Interrater reliability was respectable at Kappa = 0.67. Our novel evaluation method represents one way of improving on a usability expert technique making it more patient-centered with less individual evaluator variability.
Exploration of Risk Factors for Falls Using Electronic Nursing Records
Authors: Choi Eunju  , Lee Youngshin  , Yang Eunjung  , Kim Jihui  , Kim Yeonhee  , Park Hyeoun-Ae
Published: February 2025

Introduction: The purpose was to identify fall risk factors between admission day and fall occurred day using electronic nursing records and the Morse Fall Scale (MFS).
Improving Drugs Administration Safety in Pediatric Resuscitation Using Mobile Technology
Authors: Hagberg Hamdi  , Siebert Johan  , Gervaix Alain  , Daehne Peter  , Lovis Christian  , Manzano Sergio  , Ehrler Frederic
Published: February 2025

The fast preparation of drugs during pediatric resuscitation is of utmost importance. The influence of the patient's weight on the drug doses requires to perform complex calculations and is a source of errors. A technological solution could be a real help in avoiding these kinds of mistakes. Relying on a user centered approach we have developed an application supporting drug preparation. It has been tested in simulations with predefined scenario. The developed tool consists of a screen displaying a list of drug that can be administered. When the user select a drug, the instructions regarding its preparation are displayed with all dosage precisely calculated. The tool has demonstrated a significant reduction of errors associated to administration, a speeding up the overall process and has been well received by the nurses.
Patient Engagement: Opportunities and Challenges for Nursing and Health Care Professionals
Authors: Abdelhak Mervat
Published: February 2025

Patient (citizen) engagement argued as a critical initiative for the transformation of health care and improving health outcomes. Health care is experiencing patients that have expectations for value, transparency, choice, and engagement. However, meaningfully engaging patients in their own health care has often proven to be difficult. This panel will present commentary, research and educational initiatives, representing multiple and global perspectives on patient engagement. Global efforts in education to prepare the needed workforce will also be addressed. The audience will have an opportunity to share multiple perspectives and experiences within the panel framework.
POLESAT an Innovative e-Geoplatform in Health Management
Authors: Quesnel Anne  , Soula Julien  , Dufossez François  , Beuscart Régis
Published: February 2025

Health geography and geomatics have become major disciplines in the last few years and are the source of attractive concepts for medical informatics. POLESAT's e-geoplatform was built to present information and support decision-making during medical consultation. We have improved its usability with innovative and modern methodology. Results show five steps of the process. 1: we select one of three hospitals. 2: thanks to PiNoKio's anatomy, the related activity segments are displayed. 3: the activity segment “AB-Orthopedics, Rheumatology” is displayed. 4: click on “AB02-Amputations” product line and 5: go to hospital activity choropleth map.
Understanding Nurses' Perceptions of Electronic Health Record Use in an Acute Care Hospital Setting
Authors: Strudwick Gillian  , McGillis Hall Linda  , Nagle Lynn  , Trbovich Patricia
Published: February 2025

Electronic health records (EHRs) are being implemented in health care environments in an effort to improve the safety, quality and efficiency of care. However, not all of these potential benefits have been demonstrated in empirical research. One of the reasons for this may be a number of barriers that prevent nurses from being able to incorporate EHRs into their professional practice. A review of the literature revealed a number of barriers to, and facilitators of EHR use by nurses. Among these, EHR usability, organizational context, and individual nurse characteristics were found to be concepts that influence use. It is currently unknown how these concepts together might influence nurses' perceptions of their ability to use the technology to support the nursing process. In this poster, the authors will describe a study aimed at achieving a better understanding of nurses' perceptions of their EHR use by investigating the concepts of EHR usability, organizational context and select individual nurse characteristics.
A Customized Workflow-Driven Instant Messaging System Support Team Communication in the Hospital
Authors: Lee Ying-Li  , Chien Tsai-Feng  , Chen Hsiu-Chin
Published: February 2025

Effective communication among the healthcare team is a very important skill to support team resource management (TRM). However, we take too much effort to connect with other team members by using traditional telephone communication. In this study, we developed an instant messaging system embedded in the original hospital information system and evaluated the preliminary outcome and the usage of the system.
A Standard for Nursing Process – Clinical Decision Support Systems (NP-CDSS)
Authors: Müller-Staub Maria  , Paans Wolter
Published: February 2025

A Nursing Process-Clinical Decision Support System (NP-CDSS) Standard with 25 criteria to guide future developments of Nursing Process-Clinical Decision Support Systems was developed. The NP-CDSS Standards' content validity was established in qualitative interviews yielding fourteen categories that demonstrate international expert consensus. All experts judged the Advanced Nursing Process being the centerpiece for Nursing Process-Clinical Decision Support System that should suggest research-based, pre-defined nursing diagnoses and correct linkages between diagnoses, evidence-based interventions and patient outcomes.
Emergency Information Systems for Performance Assessment Value Before and After the Child Abuse and Sexual Assault of Time After Medical Intervention
Authors: Tang Siou-Jhen  , Jhan Shu-Jin  , Chen Siou-Ji  , Lan Ai-Ru  , You Huei-Jhu  , Jhang Huei-Lan  , Li Fang-Shan
Published: February 2025

This study was designed to investigate child abuse and sexual assault in the emergency medical treatment process, child abuse and sexual assault a total of 2014 years of the city informed of 82 accounted for 23 hospital. The use of teamwork and information systems intervention before and after, child abuse and sexual assault for the time required for medical treatment, the effectiveness of valuation step.Project object for child abuse and sexual abuse of patients in the emergency room. I Data were collected using direct observation and retrospective chart review method. The results show medical record was reduced from 11 to 4 step step; time from 1 hour 52 minutes to 46 minutes, greatly enhance emergency service satisfaction.
Early Assessment of Patient's Medical Condition in Ambulance Care Affects the Level of Care of Non Urgent Patients
Authors: Larsson Glenn  , Holmén Anders  , Ziegert Kristina
Published: February 2025

The Rapid Emergency Triage and Treatment System (RETTS) is used by the Swedish ambulance care organization for assessment of patients medical condition. The aim of the present study was to evaluate prehospital assessment in collaboration with the ambulance nurse and primary health care physicians. If the patient's condition was priority GREEN by RETTS then the ambulance nurse decided to contact the primary care physicians for a dialogue and together they decided which level of care was the most appropriate for the patient's condition.
Telerehabilitation Services in Pakistan: A Rehabilitation Professional's Perspective
Authors: Zahid Zeshan  , Atique Suleman
Published: February 2025

Disabled community spending a miserable life and having no or very less access to basic health and rehabilitation care across Pakistan. WHO developed objectives for the provision of standard health and rehabilitation care to disables and emphasizes to achieve them till 2021. The Purpose of this study was to assess the future of tele-rehabilitation services in Pakistan. It was quantitative study with Sample size of 100 rehabilitation professionals across the country. Result showed that Telerehabilitation Services are strongly needed in Pakistan and professionals rated it as a best alternate of facility based rehabilitation services. We can provide a wide range of services through Telerehabilitation Services ranging from simple consultation to delivery of different therapeutic sessions and online monitoring.
How Do Information and Communication Technologies Influence Nursing Care?
Authors: Rouleau Geneviève  , Gagnon Marie-Pierre  , Côté José  , Payne-Gagnon Julie  , Hudson Emilie  , Dubois Carl-Ardy
Published: February 2025

Despite the well-known advantages of information and communication technologies (ICTs), their overall impact on nursing care has not been synthesized. The objective of this overview of systematic reviews is to summarize the best evidence regarding the effects of ICTs on nursing care. We considered quantitative, qualitative and mixed-method reviews published since January 1995. Two reviewers independently screened the title and abstract of 5515 papers to assess their eligibility. From these, 72 full-text papers were evaluated and 28 publications met the inclusion criteria. Three reviewers extracted and compared their data. Preliminary results show that the following dimensions of nursing care are the most frequently reported: assessment, care planning and evaluation, documentation time, quality of care and patient safety. This overview provides a starting point from which to compare and contrast findings of separate reviews regarding the positive, neutral and negative effects of ICTs on nursing care.
Adjective Semantics in Open Knowledge Extraction
Authors: Gangemi Aldo  , Nuzzolese Andrea Giovanni  , Presutti Valentina  , Reforgiato Recupero Diego
Published: February 2025

Adjectives carry a lot of discourse semantics, often being the core elements to understand the literal, emotional, cultural, and metaphoric meaning of a sentence. Their formal semantics has been investigated specially in lexical semantics and formal linguistics, with some contributions from formal ontology and the semantic web. However, no standard formal treatment of adjectives is available yet, which is capable to address the concerns of both theoretical and computational natural language understanding. In this paper we summarize the existing approaches, present some alternative solutions to approximate a rigorous but pragmatic representation, and describe an implementation of a lightweight adjective ontology as a core resource in FRED, a state-of-the-art open knowledge extraction tool.
Formalizing and Adapting a General Function Module for Foundational Ontologies
Authors: Borgo Stefano  , Mizoguchi Riichiro  , Kitamura Yoshinobu
Published: February 2025

We introduce and formalize the key elements of a recent approach [1] to function definition that covers both biological and artefact functions. The paper concentrates on the steps from informal definitions to formal expressions and aims to show how to develop an ontological module for generic function representation. This part is done assuming the YAMATO ontology as background system. The second goal of the paper discusses how the module could be adapted to other foundational ontologies. In this part, we first point out the ontological assumptions on which the module relies and then discuss problems in reformulating them in other systems. This step is needed to verify whether and how the function module can be meaningfully used in other ontologies. We exemplify this case by discussing BFO and DOLCE, and by formalizing the module in the latter ontology.
The Functions of Definitions in Ontologies
Authors: Seppälä Selja  , Ruttenberg Alan  , Smith Barry
Published: February 2025

To understand what ontologies do through their definitions, we propose a theoretical explanation of the functions of definitions in ontologies backed by empirical neuropsychological studies. Our goal is to show how these functions should motivate (i) the systematic inclusion of definitions in ontologies and (ii) the adaptation of definition content and form to the specific context of use of ontologies.
PROSIT Open Source Disease Models for Diabetes Mellitus
Authors: Schramm Wendelin  , Sailer Fabian  , Pobiruchin Monika  , Weiss Christian
Published: February 2025

There has been legitimate criticism with regard to the quality and the transparency of health economic modelling studies. For that reason, the aim of the PROSIT Disease Modelling Community is to develop transparent open source health economic disease models for diabetes mellitus. Results: Markov type models were developed in the open source spread sheet software OpenOffice Calc for myocardial infarction, stroke, retinopathy, nephropathy, diabetic foot syndrome, and hypoglycemia. The basic concept is to describe a disease as a cascade of disease states with transitions between them. The transition probability is based on time, gender, age, disease related risks and medical interventions. An internet platform hosts the models and the documentation for public download. Incidence rates of complications were derived from population data and clinical studies. The models have to be adapted according to the specific needs and type of health economic analysis. The software is prepared to allow validation and model testing. The PROSIT Disease Modelling Community with its Markov models for diabetes mellitus suggests a new approach and methodology for developing health economic disease models in a transparent and sustainable manner. Going open source with disease models could overcome the lack in credibility that hampers modelling based health economic studies.
Show-Me ECHO: Complex Disease Care Capacity-Building Telehealth Program
Authors: Becevic Mirna  , Mutrux Rachel  , Edison Karen
Published: February 2025

INTRODUCTION: The University of Missouri, Missouri Telehealth Network has partnered with the State of Missouri to build provider capacity and increase healthcare outcomes in rural Missouri in six disease states. The Show-Me ECHO project was created in 2014, continuously going through program evaluation.
mHealth in Chronic Pain Assessment: Present and Future
Authors: Pliakos Ioannis  , Kefaliakos Antonios  , Diomidous Marianna
Published: February 2025

Chronic Pain (CP) is a condition which is difficult to assess. Existing methods are based on self-management treatments and leaving the big part of the assessment on the patient. According on this method, mHealth applications offer tools to CP patients to self-manage their condition and improve it. All the applications are limited by the type of data they collect and the data based on self-reporting. In the future the applications for CP management will not be based only on this type of data. Multiple types of data will be gathered and analyzed, as well as the specialists will be able to have a better prospective for the patients' pain levels.
The Prevalence of Internet and Social Media Based Medication Information Seeking Behavior in Saudi Arabia
Authors: Bahkali Salwa  , Alfurih Suha  , Aldremly Maha  , Alzayyat Ma'an  , Alsurimi Khaled  , Househ Mowafa
Published: February 2025

The internet has become an important resource to help people search for online medication information. This study aims to report the prevalence and profile of Saudi online medication seeking behavior. Conducted via a web-based survey with Twitter participants between January-February, 2015, the primary outcome measures were the self-reported rates of using the internet to search for medication related information. A valid sample of 4847 participants was collected over the period of the study. Out of the total participants, 68.3% (n=3311) were found to seek online medication related information frequently. Most of the social media users were female 83.5% (n=2766). The majority of respondents 63.6% (n= 3081) used Google, followed by Twitter 28.7% (n= 1392), Snapchat 21%, (n=1019), WhatsApp 13.8% (n= 670), Instagram 11.4%, (n= 553), and Facebook 5.5 % (n= 267), with few searching YouTube 1.3% (n=65) to access online medication information. Findings indicate that the Saudi population actively uses the internet and social media to obtain medication information. Further studies are needed to explore the influence of the internet and social media on user perception, attitude, and behavior with the use of online medication information.
Towards Realizing Benefits of Information Technology in Organ Transplant: A Review
Authors: Rashidi Khazaee Parviz  , Pirnejad Habibollah  , Bagherzadeh Jamshid  , Niazkhani Zahra
Published: February 2025

Organ transplantation comprises of many phases, processes, and activities and involves multiple stakeholders. Effective management of such a complex and costly medical domain requires an efficient, multifaceted solution. Although, Information Technology (IT) can basically play an important role here, it is not clear how IT potentials have been deployed so far. We systematically reviewed MEDLINE, EMBASE, CINAHL, The Cochrane and IEEE databases and identified 27 publications describing IT application in organ transplantation. Although the IT coverage spans over waiting list management, donor-recipient matching, and inpatient and outpatient medication and lab monitoring practices, the coverage is still patchy and whole process IT support is missing in practice.
Evaluation of Scientific Journal Validity, It's Articles and Their Authors
Authors: Masic Izet  , Begic Edin
Published: February 2025

The science that deals with evaluation of a scientific article refer to the finding quantitative indicators (index) of the scientific research success is called scientometrics. Scientometrics is part of scientology (the science of science) that analyzes scientific papers and their citations in a selected sample of scientific journals. There are four indexes by which it is possible to measure the validity of scientific research: number of articles, impact factor of the journal, the number and order of authors and citations number. Every scientific article is a record of the data written by the rules recommended by several scientific associations and committees. Growing number of authors and lot of authors with same name and surname led to the introduction of the necessary identification agent – ORCID number.
Evaluation of Dynamic Changes in Rating of Russian Information Sources of Medical Education Sites
Authors: Vasilyeva Irina V.  , Arseniev Sergey B.
Published: February 2025

The aim of the present study is to analyze dynamic changes in the rating of information sources of medical literature in the sites of the following electronic libraries (, , ) and the rating of information sources for electronic medical books (,  ). While using the on-line programs Alexa and Cy-pr, we have analyzed their website's rating and identified basic data and time-varying site data obtained for fourteen months. Alexa Rank rating was calculated for each sitemonthly. Our study has shown that the most popular information sources of medical education among the six studied sites for Russian users is ; the site  is at the second place.
Avoiding Failure for Australia's Digital Health Record: The Findings from a Rural E-Health Participatory Research Project
Authors: Almond H.  , Cummings E.  , Turner P.
Published: February 2025

Low adoption and use of Australia's digital health record has driven the Australian Government to trial ‘opt-out’ registration from mid-June 2016. The assumption that automatic registration will increase use and thereby deliver benefit requires further investigation especially amongst those sections of the population in rural, regional, remote Australia living with complex chronic conditions. This paper reports on findings from a community based participatory e-health research project based on an initiative where people with complex chronic conditions and their carers attended a rural health promotion and lifestyle modification program. Through co-operative enquiry, health promotion officers and their clients were actively supported to adopt and use Australia's digital health record as an intervention. Simultaneously they were encouraged to reflect on its design and their perceptions of its overall impact on their individual ability to self-manage complex chronic conditions. The findings, ultimately contributing to a conceptual implementation and evaluation framework for Australia's digital health record that could directly avoid failure of the new ‘opt-out’ approach being adopted.
Constant Time EXPected Similarity Estimation for Large-Scale Anomaly Detection
Authors: Schneider Markus  , Ertel Wolfgang  , Palm Günther
Published: February 2025

A new algorithm named EXPected Similarity Estimation (EXPOSE) was recently proposed to solve the problem of large-scale anomaly detection. It is a non-parametric and distribution free kernel method based on the Hilbert space embedding of probability measures. Given a dataset of n samples, EXPOSE takes 𝒪(n) time to build a model and 𝒪(1) time per prediction.
Parameterised Model Checking for Alternating-Time Temporal Logic
Authors: Kouvaros Panagiotis  , Lomuscio Alessio
Published: February 2025

We investigate the parameterised model checking problem for specifications expressed in alternating-time temporal logic. We introduce parameterised concurrent game structures representing infinitely many games with different number of agents. We introduce a parametric variant of ATL to express properties of the system irrespectively of the number of agents present in the system. While the parameterised model checking problem is undecidable, we define a special class of systems on which we develop a sound and complete counter abstraction technique. We illustrate the methodology here devised on the prioritised version of the train-gate-controller.
CUBE: A CUDA Approach for Bucket Elimination on GPUs
Authors: Bistaffa Filippo  , Bombieri Nicola  , Farinelli Alessandro
Published: February 2025

We consider Bucket Elimination (BE), a popular algorithmic framework to solve Constraint Optimisation Problems (COPs). We focus on the parallelisation of the most computationally intensive operations of BE, i.e., join sum and maximisation, which are key ingredients in several close variants of the BE framework (including Belief Propagation on Junction Trees and Distributed COP techniques such as ActionGDL and DPOP). In particular, we propose CUBE, a highly-parallel GPU implementation of such operations, which adopts an efficient memory layout allowing all threads to independently locate their input and output addresses in memory, hence achieving a high computational throughput. We compare CUBE with the most recent GPU implementation of BE. Our results show that CUBE achieves significant speed-ups (up to two orders of magnitude) w.r.t. the counterpart approach, showing a dramatic decrease of the runtime w.r.t. the serial version (i.e., up to 652× faster). More important, such speed-ups increase when the complexity of the problem grows, showing that CUBE correctly exploits the additional degree of parallelism inherent in the problem.
Complexity Results for Probabilistic Datalog
Authors: Ceylan İsmail İlkan  , Lukasiewicz Thomas  , Peñaloza Rafael
Published: February 2025

We study the query evaluation problem in probabilistic databases in the presence of probabilistic existential rules. Our focus is on the Datalog±family of languages for which we define the probabilistic counterpart using a flexible and compact encoding of probabilities. This formalism can be viewed as a generalization of probabilistic databases, as it allows to generate new facts from the given ones, using so-called tuple-generating dependencies, or existential rules. We study the computational cost of this additional expressiveness under two different semantics. First, we use a conventional approach and assume that the probabilistic knowledge base is consistent and employ the standard possible world semantics. Thereafter, we introduce a probabilistic inconsistency-tolerant semantics, which we call inconsistency-tolerant possible world semantics. For both of these cases, we provide a thorough complexity analysis relative to different languages, drawing a complete picture of the complexity of probabilistic query answering in this family.
Realisability of Production Recipes
Authors: de Silva Lavindra  , Felli Paolo  , Chaplin Jack C.  , Logan Brian  , Sanderson David  , Ratchev Svetan
Published: February 2025

There is a rising demand for customised products with a high degree of complexity. To meet these demands, manufacturing lines are increasingly becoming autonomous, networked, and intelligent, with production lines being virtualised into a manufacturing cloud, and advertised either internally to a company, or externally in a public cloud. In this paper, we present a novel approach to two key problems in such future manufacturing systems: the realisability problem (whether a product can be manufactured by a set of manufacturing resources) and the control problem (how a particular product should be manufactured). We show how both production recipes specifying the steps necessary to manufacture a particular product, and manufacturing resources and their topology can be formalised as labelled transition systems, and define a novel simulation relation which captures what it means for a recipe to be realisable on a production topology. We show how a controller that can orchestrate the resources in order to manufacture the product on the topology can be extracted from the simulation relation, and give an algorithm to compute a simulation relation and a controller.
Data Set Operations to Hide Decision Tree Rules
Authors: Kalles Dimitris  , Verykios Vassilios S.  , Feretzakis Georgios  , Papagelis Athanasios
Published: February 2025

This paper focuses on preserving the privacy of sensitive patterns when inducing decision trees. Our record augmentation approach for hiding sensitive classification rules in binary datasets is preferred over other heuristic solutions like output perturbation or cryptographic techniques since the raw data itself is readily available for public use. We describe the process and an indicative experiment using a prototype hiding tool.
A Data Driven Similarity Measure and Example Mapping Function for General, Unlabelled Data Sets
Authors: Lejeune Damien  , Driessens Kurt
Published: February 2025

Deep networks such as autoencoders and deep belief nets are able to construct alternative, and often informative, representations of unlabeled data by searching for (hidden) structure and correlations between the features chosen to represent the data and combining them into new features that allow sparse representations of the data. These representations have been chosen to often increase the accuracy of further classification or regression accuracy when compared to the original, often human chosen representations. In this work, we attempt an investigation of the relation between such discovered representations found using related but differently represented sets of examples. To this end, we combine the cross-domain comparison capabilities of unsupervised manifold alignment with the unsupervised feature construction of deep belief nets, resulting in an example mapping function that allows re-encoding examples from any source to any target task. Using the t-Distributed Stochastic Neighbour Embedding technique to map translated and real examples to a lower dimensional space, we employ KL-divergence to define a dissimilarity measure between data sets enabling us to measure found representation similarities between domains.
All-Transfer Learning for Deep Neural Networks and Its Application to Sepsis Classification
Authors: Sawada Yoshihide  , Sato Yoshikuni  , Nakada Toru  , Ujimoto Kei  , Hayashi Nobuhiro
Published: February 2025

In this article, we propose a transfer learning method for deep neural networks (DNNs). Deep learning has been widely used in many applications. However, applying deep learning is problematic when a large amount of training data are not available. One of the conventional methods for solving this problem is transfer learning for DNNs. In the field of image recognition, state-of-the-art transfer learning methods for DNNs re-use parameters trained on source domain data except for the output layer. However, this method may result in poor classification performance when the amount of target domain data is significantly small. To address this problem, we propose a method called All-Transfer Deep Learning, which enables the transfer of all parameters of a DNN. With this method, we can compute the relationship between the source and target labels by the source domain knowledge. We applied our method to actual two-dimensional electrophoresis image (TDEI) classification for determining if an individual suffers from sepsis; the first attempt to apply a classification approach to TDEIs for proteomics, which has attracted considerable attention as an extension beyond genomics. The results suggest that our proposed method outperforms conventional transfer learning methods for DNNs.
Reputation in the Academic World
Authors: Osman Nardine  , Sierra Carles
Published: February 2025

This paper proposes a computational model based on peer reviews for assessing the reputation of researchers and research work. We argue that by relying on peer opinions, we address some of the pitfalls of current approaches for calculating the reputation of authors and papers. We also introduce a much needed feature for review management: calculating the reputation of reviews and reviewers.
A History Tree Heuristic to Generate Better Initiation Sets for Options in Reinforcement Learning
Authors: Demir Alper  , Çilden Erkin  , Polat Faruk
Published: February 2025

Options framework is a prominent way to improve learning speed by means of temporally extended actions, called options. Although various attempts focusing on how to derive high quality termination conditions for options exist, the impact of initiation set generation of an option is relatively unexplored. In this work, we propose an effective heuristic method to derive useful initiation set elements via an analysis of the recent history of events.
On Truthful Auction Mechanisms for Electricity Allocation
Authors: Song Heng  , Zhu Junwu  , Li Bin  , Jiang Yi
Published: February 2025

As technology evolves and electricity demand rises, more and more research focus on the efficient electricity allocation mechanisms so as to make consumer demand adaptive to the supply of electricity at all times. In this paper, we formulate the problem of electricity allocation as a novel combinatorial auction model, and then put forward a directly applicable mechanisms. It is proven that the proposed mechanism is equipped with some useful economic properties and computational traceability. Our works offer potential avenues for the stduy about efficient electricity allocation methods in smart grid.
Towards a BDI Player Model for Interactive Narratives
Authors: Rivera-Villicana Jessica  , Zambetta Fabio  , Harland James  , Berry Marsha
Published: February 2025

Player Modelling is one of the challenges in Interactive Narratives (INs), where a precise representation of the players mental state is needed to provide a personalised experience. However, how to represent the interaction of the player with the game to make the appropriate decision in the story is still an open question. In this paper, we aim to bridge this gap identifying the information needed to capture the players interaction with an IN using the Belief-Desire-Intention (BDI) model of agency. We present a BDI design to mimic a players interaction with a simplified version of the interactive fiction Anchorhead.
Scalable Exact MAP Inference in Graphical Models
Authors: Marinescu Radu  , Kishimoto Akihiro  , Botea Adi
Published: February 2025

This paper presents parallel dovetailing in a distributed-memory environment for exact MAP inference in graphical models. Parallel dovetailing is a simple procedure which performs multiple searches in parallel with different parameter configurations. We evaluate empirically the performance of parallel dovetailing with three state-of-the-art AND/OR search algorithms in solving various MAP inference benchmarks. Our results clearly show that parallel dovetailing is effective, yielding considerable speedups and improving the solving abilities of these state-of-the-art baseline methods.
Shaping Proto-Value Functions Using Rewards
Authors: Maity Raj Kumar  , Lakshminarayanan Chandrashekar  , Padakandla Sindhu  , Bhatnagar Shalabh
Published: February 2025

In reinforcement learning (RL), an important sub-problem is learning the value function, which is chiefly influenced by the architecture used to represent value functions. is often expressed as a linear combination of a pre-selected set of basis functions. These basis functions are either selected in an ad-hoc manner or are tailored to the RL task using the domain knowledge. Selecting basis functions in an ad-hoc manner does not give a good approximation of value function while choosing functions using domain knowledge introduces dependency on the task. Thus, a desirable scenario is to have a method to choose basis functions that are task independent, but which also provide a good approximation for the value function. In this paper, we propose a novel task-independent basis function construction method that uses the topology of the underlying state space and the reward structure to build the reward-based Proto Value Functions (RPVFs). The approach we propose gives good approximation for the value function and enhanced learning performance. The performance is demonstrated via experiments on grid-world tasks.
Dialogues as Social Practices for Serious Games
Authors: Augello Agnese  , Gentile Manuel  , Weideveld Lucas  , Dignum Frank
Published: February 2025

The paper describes an architecture for a social conversational agent. The aim is to use the agent in a serious game to improve the social and communicative skills of the players, showing the social effects of conversational choices on the emotions and behavioural changes of the interlocutors.
Hole in One: Using Qualitative Reasoning for Solving Hard Physical Puzzle Problems
Authors: Ge Xiaoyu  , Lee Jae Hee  , Renz Jochen  , Zhang Peng
Published: February 2025

The capability of determining the right sequence of physical actions to achieve a given task is essential for AI that interacts with the physical world. The great difficulty in developing this capability has two main causes: (1) the world is continuous and therefore the action space is infinite, (2) due to noisy perception, we do not know the exact physical properties of our environment and therefore cannot precisely simulate the consequences of a physical action.
More than a Name? On Implications of Preconditions and Effects of Compound HTN Planning Tasks
Authors: Bercher Pascal  , Höller Daniel  , Behnke Gregor  , Biundo Susanne
Published: February 2025

There are several formalizations for hierarchical planning. Many of them allow to specify preconditions and effects for compound tasks. They can be used, e.g., to assist during the modeling process by ensuring that the decomposition methods' plans “implement” the compound tasks' intended meaning. This is done based on so-called legality criteria that relate these preconditions and effects to the method's plans and pose further restrictions. Despite the variety of expressive hierarchical planning formalisms, most theoretical investigations are only known for standard HTN planning, where compound tasks are just names, i.e., no preconditions or effects can be specified. Thus, up to know, a direct comparison to other hierarchical planning formalisms is hardly possible and fundamental theoretical properties are yet unknown. To enable a better comparison between such formalisms (in particular with respect to their computational expressivity), we first provide a survey on the different legality criteria known from the literature. Then, we investigate the theoretical impact of these criteria for two fundamental problems to planning: plan verification and plan existence. We prove that the plan verification problem is at most NP-complete, while the plan existence problem is in the general case both semi-decidable and undecidable, independent of the demanded criteria. Finally, we discuss our theoretical findings and practical implications.
When Do Rule Changes Count-As Legal Rule Changes?
Authors: King Thomas C.  , Dignum Virginia  , Jonker Catholijn M.
Published: February 2025

Institutions regulate societies. Comprising Searle's constitutive counts-as rules, “A counts-as B in context C”, an institution ascribes from brute and institutional facts (As), a social reality comprising institutional facts (Bs) conditional on the social reality (contexts Cs). When brute facts change an institution evolves from one social reality to the next. Rule changes are also regulated by rule-modifying counts-as rules ascribing rule change in the past/present/future (e.g. a majority rule change vote counts-as a rule change). Determining rule change legality is difficult, since changing counts-as rules both alters and is conditional on the social reality, and in some cases hypothetical rule-change effects (e.g. not retroactively criminalising people). However, without a rigorous account of rule change ascriptions, AI agents cannot support humans in understanding the laws imposed on them. Moreover, advances in automated governance design for socio-technical systems, are limited by agents' ability to understand how and when to enact institutional changes. Consequently, we answer “when do rule changes count-as legal rule changes?” in a temporal setting with a novel formal framework.
A Framework for Actionable Clustering Using Constraint Programming
Authors: Dao Thi-Bich-Hanh  , Vrain Christel  , Duong Khanh-Chuong  , Davidson Ian
Published: February 2025

Consider if you wish to cluster your ego network in Facebook so as to find several useful groups each of which you can invite to a different dinner party. You may require that each cluster must contain equal number of males and females, that the width of a cluster in terms of age is at most 10 and that each person in a cluster should have at least r other people with the same hobby. These are examples of cardinality, geometric and density requirements/constraints respectfully that can make the clustering useful for a given purpose. However existing formulations of constrained clustering were not designed to handle these constraints since they typically deal with low-level, instance-level constraints. We formulate a constraint programming (CP) languages formulation of clustering with these cluster-level styles of constraints which we call actionable clustering. Experimental results show the potential uses of this work to make clustering more actionable. We also show that these constraints can be used to improve the accuracy of semi-supervised clustering.
Set-Valued Conditioning in a Possibility Theory Setting
Authors: Benferhat Salem  , Levray Amélie  , Tabia Karim  , Kreinovich Vladik
Published: February 2025

Possibilistic logic is a well-known framework for dealing with uncertainty and reasoning under inconsistent or prioritized knowledge bases. This paper deals with conditioning uncertain information where the weights associated with formulas are in the form of sets of uncertainty degrees. The first part of the paper studies set-valued possibility theory where we provide a characterization of set-valued possibilistic logic bases and set-valued possibility distributions by means of the concepts of compatible possibilistic logic bases and compatible possibility distributions respectively. The second part of the paper addresses conditioning set-valued possibility distributions. We first propose a set of three natural postulates for conditioning set-valued possibility distributions. We then show that any set-valued conditioning satisfying these three postulates is necessarily based on conditioning the set of compatible standard possibility distributions. The last part of the paper shows how one can efficiently compute set-valued conditioning over possibilistic knowledge bases.
An Improved CNF Encoding Scheme for Probabilistic Inference
Authors: Bart Anicet  , Koriche Frédéric  , Lagniez Jean-Marie  , Marquis Pierre
Published: February 2025

We present and evaluate a new CNF encoding scheme for reducing probabilistic inference from a graphical model to weighted model counting. This new encoding scheme elaborates on the CNF encoding scheme ENC4 introduced by Chavira and Darwiche, and improves it by taking advantage of log encodings of the elementary variable/value assignments and of the implicit encoding of the most frequent probability value per conditional probability table. From the theory side, we show that our encoding scheme is faithful, and that for each input network, the CNF formula it leads to contains less variables and less clauses than the CNF formula obtained using ENC4. From the practical side, we show that the C2D compiler empowered by our encoding scheme performs in many cases significantly better than when ENC4 is used, or when the state-of-the-art ACE compiler is considered instead.
Exploiting Bayesian Network Sensitivity Functions for Inference in Credal Networks
Authors: Bolt Janneke H.  , De Bock Jasper  , Renooij Silja
Published: February 2025

A Bayesian network is a concise representation of a joint probability distribution, which can be used to compute any probability of interest for the represented distribution. Credal networks were introduced to cope with the inevitable inaccuracies in the parametrisation of such a network. Where a Bayesian network is parametrised by defining unique local distributions, in a credal network sets of local distributions are given. From a credal network, lower and upper probabilities can be inferred. Such inference, however, is often problematic since it may require a number of Bayesian network computations exponential in the number of credal sets. In this paper we propose a preprocessing step that is able to reduce this complexity. We use sensitivity functions to show that for some classes of parameter in Bayesian networks the qualitative effect of a parameter change on an outcome probability of interest is independent of the exact numerical specification. We then argue that credal sets associated with such parameters can be replaced by a single distribution.
Exploring Parallel Tractability of Ontology Materialization
Authors: Zhou Zhangquan  , Qi Guilin  , Glimm Birte
Published: February 2025

Materialization is an important reasoning service for applications built on the Web Ontology Language (OWL). To make materialization efficient in practice, current research focuses on deciding tractability of an ontology language and designing parallel reasoning algorithms. However, some well-known large-scale ontologies, such as YAGO, have been shown to have good performance for parallel reasoning, but they are expressed in ontology languages that are not parallelly tractable, i.e., the reasoning is inherently sequential in the worst case. This motivates us to study the problem of parallel tractability of ontology materialization from a theoretical perspective. That is, we aim to identify the ontologies for which materialization is parallelly tractable, i.e., in NC complexity. In this work, we focus on datalog rewritable ontology languages. We identify several classes of datalog rewritable ontologies (called parallelly tractable classes) such that materialization over them is parallelly tractable. We further investigate the parallel tractability of materialization of a datalog rewritable OWL fragment DHL (Description Horn Logic) and an extension of DHL that allows complex role inclusion axioms. Based on the above results, we analyze real-world datasets and show that many ontologies expressed in DHL or its extension belong to the parallelly tractable classes.