bluuebunny/crossref_metadata_2025 huggingface dataset:
Process Visibility Analysis in Ambulatory Care: A Simulation Study with RFID Data
Authors: Lin Yi-Chin  , Padman Rema
Published: February 2025

Healthcare is primarily delivered in the ambulatory care setting worldwide. The high variability in service delivery encountered in this environment negatively impacts process efficiency and patient satisfaction. In this study, we analyze care delivery process in ambulatory care using time and location stamped data collected via Radio Frequency Identification (RFID)-enabled badges worn by patients, clinicians, and staff as they complete each clinic visit. With the objective of improving process visibility and minimizing patient waiting time, we examine this data to delineate the major components of waiting time and use simulation modeling to evaluate the impact of possible interventions. Results indicate that as a prevalent strategy, different appointment scheduling rules can only reduce patient waiting time in the waiting room. Surprisingly, waiting time in the exam room is unchanged, requiring new approaches to improve care coordination that address this delay. The results also highlight the value of RFID technology and the challenges in deploying them to improve service delivery.
Santa Fé: Building a Virtual City to Develop a Family Health Game
Authors: Tubelo Rodrigo  , Dahmer Alessandra  , Pinheiro Luciana  , Pinto Maria E.
Published: February 2025

The current tendency of education in health is the use of new technologies like Virtual Reality. The course of UNASUS-UFCSPA specialization in family health was developed for health professionals that work in primary health care (PHC); in order to reach all Brazilian territory. Moodle is a platform where virtual activities are posted and evaluated. Santa Fé is a virtual city created in the Sketch up Pro, which aims to fit in specific clinical cases that involve matters of medicine, nursing and dentistry. The Software eAdventure was the tool used for the development of a game, offering interaction to the student with the Virtual City and the clinical cases, in the perspective of learning utilizing an entertainment method and evaluating individual performance of the students. The building of the city in the Sketch up Pro was successful and at low cost. The eAdventure was an efficient and intuitive tool, therefore, there was not necessarily a huge specific knowledge of technology or hardware with high speed processing and also speedy broad band internet for its use.
Information Security Requirements in Patient-Centred Healthcare Support Systems
Authors: Alsalamah Shada  , Gray W. Alex  , Hilton Jeremy  , Alsalamah Hessah
Published: February 2025

Enabling Patient-Centred (PC) care in modern healthcare requires the flow of medical information with the patient between different healthcare providers as they follow the patient's treatment plan. However, PC care threatens the stability of the balance of information security in the support systems since legacy systems fall short of attaining a security balance when sharing their information due to compromises made between its availability, integrity, and confidentiality. Results show that the main reason for this is that information security implementation in discrete legacy systems focused mainly on information confidentiality and integrity leaving availability a challenge in collaboration. Through an empirical study using domain analysis, observations, and interviews, this paper identifies a need for six information security requirements in legacy systems to cope with this situation in order to attain the security balance in systems supporting PC care implementation in modern healthcare.
A Continuum of Sociotechnical Requirements for Patient-Centered Problem Lists
Authors: Collins Sarah  , Tsivkin Kira  , Hongsermeier Tonya  , Dubois David  , Nandigam Hari Krishna  , Rocha Roberto A.
Published: February 2025

Specific requirements for patient-centered health information technology remain ill-defined. To create operational definitions of patient-centered problem lists, we propose a continuum of sociotechnical requirements with five stages: 1) Intradisciplinary Care Planning: Viewing and searching for problems by discipline; 2) Multi-disciplinary Care Planning: Categorizing problem states to meet discipline-specific needs; 3) Interdisciplinary Care Planning: Sharing and linking problems between disciplines; 4) Integrated and Coordinated Care Planning: Associating problems with assessments, tasks, interventions and outcomes across disciplines for coordination, knowledge development, and reporting; and 5) Patient-Centered Care Planning: Engaging patients in identification of problems and maintenance of their problem list.
mHealth to Revolutionize Information Retrieval in Low and Middle Income Countries: Introduction and Proposed Solutions Using Botswana as Reference Point
Authors: Littman-Quinn Ryan  , Luberti Anthony A.  , Kovarik Carrie
Published: February 2025

Information retrieval (IR) practice is invaluable in health care, where the growth of medical knowledge has long surpassed human memory capabilities, and health care workers often have unmet information needs. While the information and communications technology (ICT) revolution is improving, IR in the Western world, the global digital divide has never been wider. Low and Middle Income Countries (LMICs) have the least advanced ICT infrastructure and service provision, and are also burdened with the majority of the world's health issues and severe shortages of health care workers. Initiatives utilizing mobile technology in healthcare and public health (mHealth) have shown potential at addressing these inequalities and challenges. Using Botswana as a reference point, this paper aims to broadly describe the healthcare and ICT challenges facing LMICs, the promise of mHealth as a field in health informatics, and then propose health informatics solutions that specifically address IR content and needs. One solution proposes utilizing Unstructured Supplementary Service Data (USSD) for accessing treatment guidelines, and the other solution outlines applications of smart devices for IR.
Analysis and Evaluation of Clinical Pathways in China
Authors: Xu Wei  , Wang Zhiyong  , Zhu Yanxin  , Wu Cheng  , Chen Weiwei  , Geng Yibing
Published: February 2025

and Objective To analyze and evaluate the Standard Clinical Pathways (CPs) in China and suggest improvements for future revisions, we reviewed and evaluated the Standard CPs in China based on CP evaluation framework and the standard functions for eCP. We found that Standard CPs in China can basically meet the requirements of evaluation criteria and the standard function for eCPs, but still have problems in recording, editing and statistics. Standard CPs in China are still paper-based designs, and are not applicable for the computer and network environment. Further improvement should be done in the following directions including regulating and standardizing representations of items in the cells of CP checklists, modeling and templating CP checklists, and developing variance codes.
Fostering Ontology Alignment Sharing: A General-Purpose RDF Mapping Format
Authors: Anguita Alberto  , Escrich Ana  , Maojo Victor
Published: February 2025

RDF has established in the last years as the language for describing, publishing and sharing biomedical resources. Following this trend, a great amount of RDF-based data sources, as well as ontologies, have appeared. Using a common language as RDF has provided a unified syntactic for sharing resources, but the semantics remain as the main cause of heterogeneity, hampering data integration and homogenization efforts. To overcome this issue, ontology alignment based solutions have been typically used. However, alignment information is usually codified using ad-hoc formats. In this paper, we present a general purpose ontology mapping format, totally independent from the homogenization approach to be applied. The format is accompanied with a Java API that offers mapping construction and parsing features, as well as some basic algorithms for applying it to data translation solutions.
Primary Care Provider's Acceptance of Health Information Exchange Utilizing IHE XDS
Authors: Haarbrandt Birger  , Schwartze Jonas  , Gusew Nathalie  , Seidel Christoph  , Kleinschmidt Thorsten  , Haux Reinhold
Published: February 2025

Objective We assessed primary care providers' perception of a health information exchange system (HIE) based on IHE XDS in the metropolitan area of Braunschweig, Lower Saxony, Germany.
Towards the Development of the Smart Grid: Fast Electricity Load Forecasting Using Different Hybrid Approaches
Authors: Jurado Sergio  , Mugica Francisco  , Nebot Àngela  , Avellana Narcís
Published: February 2025

Currently, worldwide scientific community is doing a great effort of research in the area of Smart Grids because energy production, distribution, and consumption play a critical role in the sustainability of the planet. In this context, electricity load forecasting methodologies with fast response is a key component for demand-side management and the emergence of prosumers in the electricity grid. In this research it is shown that the computational intelligence techniques presented can deal with real time forecast, cope with incomplete measurement data and forecast signals of great variability, when applied to three real locations, with distinctly different characteristics.
Natural Language-Based Automatic Qualitative Description of Clusters
Authors: Sánchez-Hernández Germán  , Agell Núria  , Aguado Juan Carlos
Published: February 2025

In this paper the design of a natural language generation (NLG) system is introduced to qualitatively describe the most important characteristics of each class, cluster or segment previously defined by means of a classification or clustering process. An adaptation of a generic architecture for data-to-text systems consisting of four stages is proposed. It includes the detection of the most relevant patterns of the data and the definition of a grammar that generates the natural language description of the considered clusters. A case study addressing a challenge in a marketing environment is included. The study takes place in a business-to-business (B2B) environment, in which a firm distributes its products via other firms.
Expansion of the Variational Garrote to a Multiple Measurement Vectors Model
Authors: Hansen Sofie Therese  , Stahlhut Carsten  , Hansen Lars Kai
Published: February 2025

The recovery of sparse signals in underdetermined systems is the focus of this paper. We propose an expanded version of the Variational Garrote, originally presented by Kappen (2011), which can use multiple measurement vectors (MMVs) to further improve source retrieval performance. We show its superiority compared to the original formulation and demonstrate its ability to correctly estimate both the sources' location and their magnitude. Finally evidence is given of the high performance of the proposed algorithm compared to other MMV models.
Solving the 15-Puzzle Game Using Local Value-Iteration
Authors: Bischoff Bastian  , Nguyen-Tuong Duy  , Markert Heiner  , Knoll Alois
Published: February 2025

The 15-puzzle is a well-known game which has a long history stretching back in the 1870's. The goal of the game is to arrange a shuffled set of 15 numbered tiles in ascending order, by sliding tiles into the one vacant space on a 4×4 grid. In this paper, we study how Reinforcement Learning can be employed to solve the 15-puzzle problem. Mathematically, this problem can be described as a Markov Decision Process with the states being puzzle configurations. This leads to a large state space with approximately 1013elements. In order to deal with this large state space, we present a local variation of the Value-Iteration approach appropriate to solve the15-puzzle starting from arbitrary configurations. Furthermore, we provide a theoretical analysis of the proposed strategy for solving the 15-puzzle problem. The feasibility of the approach and the plausibility of the analysis are additionally shown by simulation results.
Predictive Incremental Parsing and its Evaluation
Authors: Beuck Niels  , Köhn Arne  , Menzel Wolfgang
Published: February 2025

For incomplete sentences, different structural descriptions with different levels of prediction are possible. Two existing dependency parsers have been modified to generate sequences of output hypotheses in an incremental manner. The parsing results can be characterized with respect to different criteria like the amount of predicted information, its quality, monotonicity, delay, inclusiveness and connectedness. We propose an evaluation scheme able to capture these properties and apply it to the parsers in different configurations.
Legal Conflict Detection in Interacting Legal Systems
Authors: Li Tingting  , Balke Tina  , De Vos Marina  , Padget Julian  , Satoh Ken
Published: February 2025

Acting under several jurisdictions at the same time is becoming the norm rather than the exception, certainly for companies but also (sometimes without knowing) for individuals. In these circumstances disparities among the different laws are inevitable. Here, we present a mathematical and a computational model of interacting legal specifications, along with a mechanism to find conflicts between them. We illustrate the approach by a case study using European Privacy law.
Unfolding Crime Scenarios with Variations: A Method for Building a Bayesian Network for Legal Narratives
Authors: Vlek Charlotte S.  , Prakken Henry  , Renooij Silja  , Verheij Bart
Published: February 2025

Legal reasoning can be approached from various perspectives, traditionally argumentation, probability and narrative. The communication between forensic experts and a judge or jury would benefit from an integration of these approaches. In previous papers we worked on the connection between the narrative and the probabilistic approach. We developed techniques for representing crime scenarios in a Bayesian network. But for complex cases, the construction of a Bayesian network structure using these techniques remained a cumbersome task.
Identifying and Propagating Contextually Appropriate Deep-Topics amongst Collaborating Web-Users
Authors: Hall Jeremy  , Kiyoki Yasushi
Published: February 2025

This paper describes a method for discovering URLs with contextually relevant deep-topics, and then propagating such information to collaborating users lacking such information. When a user is knowledgeable about a subject, their reasons for frequently browsing a URL extend beyond the fact that it is merely related to said subject. This paper's method includes an algorithm for discovering the surface-topic of a URL, and the underlying deep-topic that a user is truly interested in with respect to a given URL. The deep-topic extraction process works by using URLs linked together through a user's behavioral browsing patterns in order to discover the surface or group-topic of surrounding URLs, and then subtracting those topics to discover hidden deeper topics. This paper describes the three parts of the method: Information Extraction, Propagation, and Verification & Integration, which together form a method with high levels of parallelism due to its distributed and independent nature. This paper also discusses concrete usage-scenarios for the included method, and data structures which would support the implementation of this paper's method.
The Conceptual Model ≡ An Adequate and Faithful Artifact Enhanced by Concepts
Authors: Thalheim Bernhard
Published: February 2025

Conceptional modelling is one of the central activities in Computer Science. Conceptual models are mainly used as intermediate artifact for system construction. The notion of the conceptual model is at present rather informal. Conceptional modelling is performed by a modeller who directs the process based on his/her experience, education, understanding, intention, and attitude.
An Image-based Multiproxy Palpation Algorithm for Patient-Specific VR-Simulation
Authors: Fortmeier Dirk  , Mastmeyer Andre  , Handels Heinz
Published: February 2025

Palpation is the first step for many medical interventions. To provide an immersive virtual training and planning environment, the palpation step has to be successfully modeled and simulated. Here, we present a multiproxy approach that calculates friction and surface resistance forces for multiple contact points on finger tips or virtual tools like ultrasound probes and displays the resulting force and torque on a 6DOF haptic device. No manual or time intensive segmentation of patient image data is needed to create a simulation based on CT data and thus our approach is usable for patient-specific simulation of palpation.
Human Eye Haptics-Based Multimedia
Authors: Velandia David  , Uribe-Quevedo Alvaro  , Perez-Gutierrez Byron
Published: February 2025

Immersive and interactive multimedia applications offer complementary study tools in anatomy as users can explore 3D models while obtaining information about the organ, tissue or part being explored. Haptics increases the sense of interaction with virtual objects improving user experience in a more realistic manner. Common eye studying tools are books, illustrations, assembly models, and more recently these are being complemented with mobile apps whose 3D capabilities, computing power and customers are increasing. The goal of this project is to develop a complementary eye anatomy and pathology study tool using deformable models within a multimedia application, offering the students the opportunity for exploring the eye from up close and within with relevant information. Validation of the tool provided feedback on the potential of the development, along with suggestions on improving haptic feedback and navigation.
The influence of personality traits on online information behaviour during political campaigns
Authors: Wood Miguel  , Milton Simon  , Shanks Graeme
Published: February 2025

The adoption of social analytics heralds the arrival of a new paradigm in political campaign practice, driven by both behavioural science and social networks. Yet these domains have historically been in tension with opposite perspectives on political behaviour. The increasing focus on online social networks offers an opportunity to synthesise complementary research traditions on political behaviour to better understand the relationship between individual personality and information behaviour. We propose a model based on core dispositional personality traits, political participation as information consumption and information diffusion theory to explain online information behaviour during election events. Information diffusion requires users to perform several actions in combination - engage, rate content, comment, share and interpret information received. The research model enables us to observe in experimental settings how personality type guides interaction with and diffusion of political information across online social networks. The learned behaviours and direct responses of participants may help political campaigns in the design of future behavioural targeting strategies that activate social network effects to achieve campaign goals.
Qualitative Decision Support in the Process of Patient's Health Problem Evaluation
Authors: Rajkovič Uroš  , Dinevski Dejan  , Šušteršič Olga  , Rajkovič Vladislav
Published: February 2025

Evaluating patient's health status can be viewed as a multi attribute decision making (MADM) problem. Patients' problems are evaluated on the basis of symptoms. Contemporary information technology enables application of theoretical methods in practice. Such case is Henderson's model of basic leaving activities for patient health evaluation in nursing. In the paper we present the implementation of this model using DEX methodology. DEX is a qualitative MADM tool and offers user friendly acquisition and explanation of expert knowledge. The solution was tested in clinical practice and evaluated by using SWOT (strengths, weaknesses, opportunities and threats) analysis.
Comparison of Triangular and Trapezoidal Membership Functions for Improving Decision Making In Crime Prevention
Authors: Mohamad Noor Noor Maizura  , Ab Hamid Siti Haslini
Published: February 2025

Recently, crime prevention is one of the overall strategies to reduce crime around the world including Malaysia. This is in lines with one of the Malaysian government agendas as stated in National Key Result Area (NKRA) which is to reduce crime. Because of the decision making process for crime prevention is manually done by the police, so it is difficult to determine the level of crime based on crime volume. That requires a method of selection to help the police to determine which is the most appropriate decision based on the level of crime. Therefore, this research developed prototype of decision support system (DSS) by using Mamdani-type fuzzy inference system (FIS) to classify the crime level and to improve the process of decision making for crime prevention. But, it is well-known that selection of membership functions (MF) is the key problem in the design of a FIS. Therefore, this paper outlines the basic comparisons between the triangular MF and trapezoidal MF. The experimental results of the two MFs are compared. It also shows which one is a better choice of the two MFs used in FIS in order to improve the efficiency of decision making for crime prevention. The result of the study indicates that triangular MF gives better classification of crime level but trapezoidal MF gives result closer to triangular MF.
NIRS Study of the Effects of Computerized Brain Training Games for Cognitive Rehabilitation of Major Depressive Disorder Patients in Remission: A Pilot Study
Authors: Payzieva Shaira  , Maxmudova D.
Published: February 2025

We used functional Near-Infrared Spectroscopy (fNIRS) to estimate brain activity in Major Depressive Disorder (MDD) patients (in remission), while they played a computerized brain training games for cognitive rehabilitation. MDD is characterized by marked deterioration in affect as well as significant impairment in cognitive function. It was found, that depressed patients showed long-lasting impaired cognitive performance on cognitive demanding tasks despite significant improvement in the depression symptoms. Previous studies have shown that video games can improve cognitive functions. But assessment was made only with cognitive tests. The main objective of this research was to study the effects of brain training games on cognitive functions of MDD patients in remission with objective instrumental NIRS method. Tissue oxygen saturation (StO2) and absolute concentrations of oxyhemoglobin ([O2Hb]), deoxyhemoglobin ([HHb]) and total hemoglobin ([tHb]) were measured by functional near-infrared spectroscopy (fNIRS) – Oxyprem (BORL, Zurich, Switzerland). Preliminary results are discussed.
Gaussian Mixture Model Learning for Desired Speech Discrimination Based on Kurtosis of Linear Prediction Residual Signals
Authors: Hayashida Kohei  , Nakayama Masato  , Nishiura Takanobu  , Yamashita Yoichi
Published: February 2025

Desired/undesired speech discrimination is as important as speech/non-speech discrimination to achieve useful applications such as speech interfaces and teleconferencing systems. Conventional methods for voice activity detection (VAD) utilize the directional information of sound sources to distinguish desired from undesired speech. However, these methods have to use multiple microphones to estimate the directions of sound sources. Here, we propose a new method that uses a single microphone to discriminate desired from undesired speech. We assumed that the desired talkers would be close to the microphone, so the proposed method discriminates close/distant-talking speech from observed signals with a Gaussian mixture model that was constructed by the kurtosis of the linear prediction (LP) residual signals in advance. The experimental results revealed that the proposed method could distinguish close-talking speech from distant-talking speech within a 10% equal error rate (EER) in ordinary reverberant environments.
A Mechanism Design of Solar Power Trading by Autonomous Agent based on Reinforcement Learning
Authors: Suzuki Masayoshi  , Nakatani Ryuji  , Nishikawa Ikuko
Published: February 2025

Power exchange network composed of ordinary houses equipped with photovoltaics (solar panel) units is considered to effectively use the unsteady and uncontrollable solar power. In the previous study, an optimal power transfer schedule with the least wasted power is obtained as an optimal solution of linear programming model under the given power generation and consumption amounts. The present study considers a trading market mediated by brokers with pricing strategy. The goal is to design the market which leads to the optimal transfer obtained by the mathematical model. Simulation results show that reinforcement learning is effective to acquire the pricing strategy even for the unsteady daily generation of the solar power.
A New Approach to the Classification of Positional Numeral Systems
Authors: Borisenko Alexei A.  , Kalashnikov Vyacheslav V.  , Protasova Tatiana A.  , Kalashnykova Nataliya I.
Published: February 2025

We propose a new classification of positional numeral systems with positive bases represented by either fixed numbers or by functions. The simplest functions used are the factorial and binomial ones. The proposed classification comprises all existing numeral systems with both uniform and non-uniform numbers, as well as possible new systems that could be developed in the future.
Challenges associated with introduction of real-time quality monitoring and feedback during colonoscopy within a secure, tightly regulated healthcare network
Authors: De Groen Piet C.  , Tavanapong Wallapak  , Oh JungHwan  , Wong Johnny
Published: February 2025

Colorectal cancer is a preventable disease if precursor lesions, polyps, are removed with colonoscopy. Yet, regular colonoscopy has not led to the expected decrease in mortality due to colorectal cancer; the likely reason for this is insufficiently high quality of colonoscopy. We have created novel software that performs real-time analysis of video streams for quality features during colonoscopy. The software also provides real-time feedback intended to drive the endoscopist towards high quality; in essence our software encourages continuous learning during colonoscopy on live patients. Introduction of this software at Mayo Clinic, an institution with a secure, tightly regulated network, required us to overcome an unexpected large number of challenges. Here we describe the challenges we encountered and the solutions we implemented. Of all challenges, security and network issues were most difficult to detect and resolve.
Development of an Electronic Instruction System to Promote Multidisciplinary Teams
Authors: Uto Yumiko  , Muranaga Fuminori  , Iwaanakuchi Takashi  , Kumamoto Ichiro
Published: February 2025

While the provision of medical care incorporating safety measures, etc. that can earn the trust of the people, patients in particular, is required, the content of instruction is diverse, complex and rapidly increasing in volume along with the sophistication and specialization of medical care. However, until now, the development of electronic instruction systems has lagged behind in the development of HIS. All instructions must be linked to orders and the input of the implementation of instructions in the electronic instruction system incorporated into medical accounting. The system must aim at integrating physician and nursing records and be of a specification that can ensure reliability and efficiency. We report on the efforts at Kagoshima University Hospital to systematize instruction in order to promote multidisciplinary teams.
The National Mobile Health Worker Project in England
Authors: Drayton Kathryn  , Robinson Karen
Published: February 2025

Community services provide essential care to many, often vulnerable, people, families and communities along the spectrum from health promotion to end of life care. The Mobile Health Worker Project is part of a larger project, the Transforming Community Services programme, which was established to support providers make changes to service provision that would provide better health outcomes, as well as increasing efficiency through the use of technology. This paper draws on the results of the two phase Mobile Health Worker project which involved 11 sites around England, the aim of which was to understand the requirements of mobile working. The results demonstrate that increased productivity and efficiency can be achieved by making changes to working processes. The project also provides guidance to increase the rate of mobile working adoption by providing a solid economic basis for investment in and deployment of mobile solutions to community organisations.
Using multiple contexts to distinguish standing from sitting with a single accelerometer
Authors: Gjoreski Hristijan  , Kozina Simon  , Luštrek Mitja  , Gams Matjaž
Published: February 2025

Activity recognition with a single accelerometer placed on the torso is fairly common task, but distinguishing standing from sitting in this way is very difficult because the torso is oriented the same way during both activities, and the transition between the two is very hard to classify into going down or up. We propose a novel approach based on the Multiple Contexts Ensemble (MCE) algorithm which classifies the activity with an ensemble of classifiers, each of which considers the problem in the context of a single feature. The improvement stems from using multiple viewpoints, based on accelerometer data only, designed specifically to distinguish standing from sitting. This approach improves the accuracy on the two activities by 24 percentage points compared to regular machine learning.
Negotiation to Execute Continuous Long-Term Tasks
Authors: Haberland Valeriia  , Miles Simon  , Luck Michael
Published: February 2025

Recently, research has focused on processing tasks that require continuous execution to produce data in a real-time manner. Such tasks often also need to be executed for long periods of time such as years, requiring large amounts of resources (e.g. CPUs) that can be found in a Grid. However, a Grid may be unwilling or unable to allocate resources for continuous usage far in advance, because of high fluctuations in resource availability and/or resource demand. Therefore, a client must relax its requirements in terms of long-term execution, and negotiate a shorter period of execution time; when this period ends, the client must negotiate again to continue task's execution. We propose a negotiation strategy, ConTask, which helps to increase the periods of execution time, and reduce the length of interruptions between them.
Video Event Recognition by Dempster-Shafer Theory
Authors: Hong Xin  , Huang Yan  , Ma Wenjun  , Miller Paul  , Liu Weiru  , Zhou Huiyu
Published: February 2025

This paper presents an event recognition framework, based on Dempster-Shafer theory, that combines evidence of events from low-level computer vision analytics. The proposed method employing evidential network modelling of composite events, is able to represent uncertainty of event output from low level video analysis and infer high-level events with semantic meaning along with degrees of belief. The method has been evaluated on videos taken of subjects entering and leaving a seated area. This has relevance to a number of transport scenarios, such as onboard buses and trains, and also in train stations and airports. Recognition results of 78% and 100% for four composite events are encouraging.
Probabilistic Active Learning: A Short Proposition
Authors: Krempl Georg  , Kottke Daniel  , Spiliopoulou Myra
Published: February 2025

Active Mining of Big Data requires fast approaches that ideally select for a user-specified performance measure and arbitrary classifier the optimal instance for improving the classification performance. Existing generic approaches are either slow, like error reduction, or heuristics, like uncertainty sampling. We propose a novel, fast yet versatile approach that directly optimises any user-specified performance measure: Probabilistic Active Learning (PAL).
A weakening of independence in judgment aggregation: agenda separability
Authors: Lang Jérôme  , Slavkovik Marija  , Vesic Srdjan
Published: February 2025

One of the better studied properties for operators in judgment aggregation is independence, which essentially dictates that the collective judgment on one issue should not depend on the individual judgments given on some other issue(s) in the same agenda. Independence is a desirable property for various reasons, but unfortunately it is too strong, as, together with mild additional conditions, it implies dictatorship. We propose here a weakening of independence, named agenda separability and show that this property is discriminant, i.e., some judgment aggregation rules satisfy it, others do not.
Momentum Online LDA for Large-scale Datasets
Authors: Ouyang Jihong  , Lu You  , Li Ximing
Published: February 2025

Modeling large-scale document collections is a significant direction in machine learning research. Online LDA uses stochastic gradient optimization technology to speed the convergence; however the large noise of stochastic gradients leads to slower convergence and worse performance. In this paper, we employ the momentum term to smooth out the noise of stochastic gradients, and propose an extension of Online LDA, namely Momentum Online Lda (MOLDA). We collect a large-scale corpus consisting of 2M documents to evaluate our model. Experimental results indicate that MOLDA achieves faster convergence and better performance than the state-of-the-art.
Surrogate-Agent Modeling for Improved Training
Authors: Tavcar Ales  , Kaluza Bostjan  , Kvassay Marcel  , Schneider Bernhard  , Gams Matjaz
Published: February 2025

Computer-aided practice can help improve personnel training for demanding scenarios in terms of time and quality. In this paper, we concentrate on asymmetrical conflicts, such as a unit that deals with hostile crowds robbing a store, with the aim of preventing further criminal activity and at the same time minimizing physical and emotional damage. We propose a surrogate-agent modeling approach based on execution of the following loop: (i) observe a human (the unit leader) playing a set of scenarios in a simulated environment and induce strategic patterns of human play; (ii) use patterns to construct a surrogate agent (digital clone); (iii) test the surrogate under all possible circumstances through data farming; and (iv) evaluate the performance and highlight deficiencies in the agent's responses, thereby enabling human improvements in new attempts. Experiments on two domains indicate that the proposed approach could significantly improve the training procedure and help trainees to properly perceive the cognitive properties of the crowds.
Fast Instantiation of GGP Game Descriptions Using Prolog with Tabling
Authors: Vittaut Jean-Noël  , Méhat Jean
Published: February 2025

We present a method to instantiate game descriptions used in General Game Playing with a Prolog interpreter using tabling. Instantiation is a crucial step for speeding up the interpretation of game descriptions and increasing the playing strength of general players. Our method allows us to ground almost all of the game descriptions present on the GGP servers in a time that is compatible with the common time settings of the GGP competition. It instantiates more rapidly than previous published methods.
Bicycle Route Planning with Route Choice Preferences
Authors: Hrncir Jan  , Song Qing  , Zilecky Pavol  , Nemet Marcel  , Jakob Michal
Published: February 2025

Bicycle route planning is a challenging problem because of the diverse set of factors considered by cyclists in choosing their cycling routes. We provide a solution to this problem based on a formal model expressive enough to represent transport network features and cyclists' preferences grounded in the studies of real-world bicycle route choice behaviour. Our solution employs the A* algorithm together with vectors of cost and heuristic functions – able to optimise routes for travel time, comfort, quietness, and flatness. We have implemented, practically deployed and experimentally evaluated our solution in the challenging setting of the city of Prague. The experiments confirmed that the planner is able to return high-quality plans in less than 250 milliseconds per query.
No One is Left “Unwatched”: Fairness in Observation of Crowds of Mobile Targets in Active Camera Surveillance
Authors: Natarajan Prabhu  , Low Kian Hsiang  , Kankanhalli Mohan
Published: February 2025

Central to the problem of active multi-camera surveillance is the fundamental issue of fairness in the observation of crowds of targets such that no target is “starved” of observation by the cameras for a long time. This paper presents a principled decision-theoretic multi-camera coordination and control (MC2) algorithm called fair-MC2that can coordinate and control the active cameras to achieve max-min fairness in the observation of crowds of targets moving stochastically. Our fair-MC2algorithm is novel in demonstrating how (a) the uncertainty in the locations, directions, speeds, and observation times of the targets arising from the stochasticity of their motion can be modeled probabilistically, (b) the notion of fairness in observing targets can be formally realized in the domain of multi-camera surveillance for the first time by exploiting the max-min fairness metric to formalize our surveillance objective, that is, to maximize the expected minimum observation time over all targets while guaranteeing a predefined image resolution of observing them, and (c) a structural assumption in the state transition dynamics of a surveillance environment can be exploited to improve its scalability to linear time in the number of targets to be observed during surveillance. Empirical evaluation through extensive simulations in realistic surveillance environments shows that fair-MC2outperforms the state-of-the-art and baseline MC2algorithms. We have also demonstrated the feasibility of deploying our fair-MC2algorithm on real AXIS 214 PTZ cameras.
Combining Engineering and Qualitative Models to Fault Diagnosis in Air Handling Units
Authors: Struss Peter  , Sterling Raymond  , Febres Jesús  , Sabir Umbreen  , Keane Marcus M.
Published: February 2025

This paper presents a methodology for model-based fault localization and identification that exploits both numerical (Modelica) models and a qualitative model-based approach to diagnosis. It has been applied to diagnosis of an air handling unit based on data recorded by a building management system. The main steps from model development to diagnosis based on the recorded data are discussed.
ParkinsonCheck Smart Phone App
Authors: Sadikov Aleksander  , Groznik Vida  , Žabkar Jure  , Možina Martin  , Georgiev Dejan  , Pirtošek Zvezdan  , Bratko Ivan
Published: February 2025

The paper introduces the ParkinsonCheck application. It is an app for smart phones based on spirography (spiral drawing) intended to detect signs of Parkinson's disease (PD) and essential tremor (ET), which is the main differential diagnosis from PD in the early stage of the disease. The app is equipped with an expert system and is the first such app to be completely automated. Its intended use is twofold: (a) to act as a standalone test for general population, advising potential patients to seek medical help as early as possible, and (b) to be used by neurologists as a portable and inexpensive fully digitalised clinical decision support system. ParkinsonCheck is currently freely available in Slovenia on four mobile platforms as a pilot study. After potentially upgrading its expert system with new learning data, the plan is for it to be translated into English and offered worldwide.
Orwellian Eye: Video Recommendation with Microsoft Kinect
Authors: Kliegr Tomáš  , Kuchař Jaroslav
Published: February 2025

This paper demonstrates Interest Beat (InBeat.eu) as a recommender system for online videos, which determines user interest in the content based on gaze tracking with Microsoft Kinect in addition to explicit user feedback. Content of the videos is represented using a semantic wikifier. User profile is constructed from preference rules, which are discovered with an association rule learner.
Abstract Disjunctive Answer Set Solvers
Authors: Brochenin Remi  , Lierler Yuliya  , Maratea Marco
Published: February 2025

A fundamental task in answer set programming is to compute answer sets of logic programs. Answer set solvers are the programs that perform this task. The problem of deciding whether a disjunctive program has an answer set is ΣP2
Reducing global consistency to local consistency in Ontology-based Data Access
Authors: Console Marco  , Lenzerini Maurizio
Published: February 2025

Ontology-based data access (OBDA) is a new paradigm aiming at accessing and managing data by means of an ontology, i.e., a conceptual representation of the domain of interest in the underlying information system. In the last years, this new paradigm has been used for providing users with suitable mechanisms for querying the data residing at the information system sources. Most of the research has been concentrating on making query answering efficient. Howeverquery answering is not the only service that an OBDA system must provide. Another crucial service is consistency checking. Current approaches to this problem involves executing expensive queries at run-time. In this paper we address a fundamental problem for OBDA system: given an OBDA specification, can we avoid the consistency check on the whole OBDA system (global consistency check), and rely instead on the constraint checking carried out by the DBMS on the data source (local consistency checking)? We present algorithms and complexity analysis for this problem, showing that it can be solved efficiently for a class of OBDA systems that is very relevant in practice.
Characterising Semantic Relatedness using Interpretable Directions in Conceptual Spaces
Authors: Derrac Joaquín  , Schockaert Steven
Published: February 2025

Various applications, such as critique-based recommendation systems and analogical classifiers, rely on knowledge of how different entities relate. In this paper, we present a methodology for identifying such semantic relationships, by interpreting them as qualitative spatial relations in a conceptual space. In particular, we use multi-dimensional scaling to induce a conceptual space from a relevant text corpus and then identify directions that correspond to relative properties such as “more violent than” in an entirely unsupervised way. We also show how a variant of FOIL is able to learn natural categories from such qualitative representations, by simulating a fortiori inference, an important pattern of commonsense reasoning.
The Significance of Bidding, Accepting and Opponent Modeling in Automated Negotiation
Authors: Baarslag Tim  , Dirkzwager Alexander  , Hindriks Koen V.  , Jonker Catholijn M.
Published: February 2025

Given the growing interest in automated negotiation, the search for effective strategies has produced a variety of different negotiation agents. Despite their diversity, there is a common structure to their design. A negotiation agent comprises three key components: the bidding strategy, the opponent model and the acceptance criteria. We show that this three-component view of a negotiating architecture not only provides a useful basis for developing such agents but also provides a useful analytical tool. By combining these components in varying ways, we are able to demonstrate the contribution of each component to the overall negotiation result, and thus determine the key contributing components. Moreover, we study the interaction between components and present detailed interaction effects. Furthermore, we find that the bidding strategy in particular is of critical importance to the negotiator's success and far exceeds the importance of opponent preference modeling techniques. Our results contribute to the shaping of a research agenda for negotiating agent design by providing guidelines on how agent developers can spend their time most effectively.
Collective Rationality in Graph Aggregation
Authors: Endriss Ulle  , Grandi Umberto
Published: February 2025

Suppose a number of agents each provide us with a directed graph over a common set of vertices. Graph aggregation is the problem of computing a single “collective” graph that best represents the information inherent in this profile of individual graphs. We consider this aggregation problem from the point of view of social choice theory and ask what properties shared by the individual graphs will transfer to the graph computed by a given aggregation procedure. Our main result is a general impossibility theorem that applies to a wide range of graph properties.
Breaking Conditional Symmetry in Automated Constraint Modelling with CONJURE
Authors: Akgun Ozgur  , Gent Ian P.  , Jefferson Christopher  , Miguel Ian  , Nightingale Peter
Published: February 2025

Many constraint problems contain symmetry, which can lead to redundant search. If a partial assignment is shown to be invalid, we are wasting time if we ever consider a symmetric equivalent of it. A particularly important class of symmetries are those introduced by the constraint modelling process: model symmetries. We present a systematic method by which the automated constraint modelling tool CONJURE can break conditional symmetry as it enters a model during refinement. Our method extends, and is compatible with, our previous work on automated symmetry breaking in CONJURE. The result is the automatic and complete removal of model symmetries for the entire problem class represented by the input specification. This applies to arbitrarily nested conditional symmetries and represents a significant step forward for automated constraint modelling.
Monte-Carlo Tree Search: To MC or to DP?
Authors: Feldman Zohar  , Domshlak Carmel
Published: February 2025

State-of-the-art Monte-Carlo tree search algorithms can be parametrized with any of the two information updating procedures: MC-backup and DP-backup. The dynamics of these two procedures is very different, and so far, their relative pros and cons have been poorly understood. Formally analyzing the dependency of MC- and DP-backups on various MDP parameters, we reveal numerous important issues that get hidden by the worst-case bounds on the algorithm performance, and reconfirm these findings by a systematic experimental test.
A Practical, Integer-Linear Programming Model for the Delete-Relaxation in Cost-Optimal Planning
Authors: Imai Tatsuya  , Fukunaga Alex
Published: February 2025

We propose a new integer-linear programming model for the delete relaxation in cost-optimal planning. While a naive formulation of the delete relaxation as IP is impractical, our model incorporates landmarks and relevance-based constraints, resulting in an IP that can be used to directly solve the delete relaxation. We show that our IP model outperforms the previous state-of-the-art solver for delete-free problems.We then use LP relaxation of the IP as a heuristics for a forward search planner, and show that our LP-based solver is competitive with the state-of-the-art for cost-optimal planning.