bluuebunny/crossref_metadata_2025 huggingface dataset:
Improved Multi-Label Classification Using Inter-Dependence Structure via a Generative Mixture Model
Authors: Simha Ramanuja  , Shatkay Hagit
Published: February 2025

Single-label classification associates each instance with a single label, while multi-label classification (MLC), assigns multiple labels to instances. Simple MLC systems assume that labels are independent of one another, while more complex approaches capture inter-dependencies among labels. Experiments comparing performance of MLC systems demonstrate that there is much room for improvement.
False-Name-Proof Mechanisms for Path Auctions in Social Networks
Authors: Zhang Lei  , Chen Haibin  , Wu Jun  , Wang Chong-Jun  , Xie Junyuan
Published: February 2025

We study path auction mechanisms for buying path between two given nodes in a social network, where edges are owned by strategic agents. The well known VCG mechanism is the unique solution that guarantees both truthfulness and efficiency. However, in social network environments, the mechanism is vulnerable to false-name manipulations where agents can profit from placing multiple bids under fictitious names. Moreover, the VCG mechanism often leads to high overpayment. In this paper, we present core-selecting path mechanisms that are robust against false-name bids and address the overpayment problem. Specifically, we provide a new formulation for the core, which greatly reduces the number of core constraints. Based on the new formulation, we present a Vickery-nearest pricing rule, which finds the core payment profile that minimizes the L∞distance to the VCG payment profile. We prove that the Vickery-nearest core payments can be computed in polynomial time by solving linear programs. Our experiment results on real network datasets and reported cost dataset show that our Vickery-nearest core-selecting path mechanism can reduce VCG's overpayment by about 20%.
Transductive Learning for the Identification of Word Sense Temporal Orientation
Authors: Hasanuzzaman Mohammed  , Dias Gaël  , Ferrari Stéphane
Published: February 2025

The ability to capture the time information conveyed in natural language is essential to many natural language processing applications such as information retrieval, question answering, automatic summarization, targeted marketing, loan repayment forecasting, and understanding economic patterns. In this paper, we propose a graph-based semi-supervised classification strategy that makes use of WordNet definitions or ‘glosses’, its conceptual-semantic and lexical relations to supplement WordNet entries with information on the temporality of its word senses. Intrinsic evaluation results show that the proposed approach outperforms prior semi-supervised, non-graph classification approaches to the temporality recognition of word senses, and confirm the soundness of the proposed approach.
Crowdsourced Referral Auctions
Authors: Chandra Praphul  , Gujar Sujit  , Narahari Y.
Published: February 2025

Motivated by web based marketplaces where the number of bidders in an auction is a small subset of potential bidders, we consider auctions where the auctioneer (seller) wishes to increase her revenue and/or social welfare by expanding the pool of participants. To this end, the seller crowdsources this task by offering a referral bonus to the participants. With the introduction of referrals, a participant can now bid and/or refer other agents to bid. We call our auctions crowdsourced referral auctions since the seller exploits the knowledge that agents have about other potential participants in the crowd. We introduce the notion of price of locality to quantify the loss in social welfare due to restricted (local) access of the seller to potential bidders. We introduce the notion of Crowdsourced Referral Auction Mechanisms (CRAMs), propose two novel versions of CRAMs and study the induced referral game in the canonical context of an auction for selling a single indivisible item. We compare their revenue performance and game theoretic properties and show that both of them outperform the baseline auction without referrals.
Space Debris Removal: A Game Theoretic Analysis
Authors: Klima Richard  , Bloembergen Daan  , Savani Rahul  , Tuyls Karl  , Hennes Daniel  , Izzo Dario
Published: February 2025

We analyse active space debris removal efforts from a strategic, game-theoretic perspective. An active debris removal mission is a costly endeavour that has a positive effect (or risk reduction) for all satellites in the same orbital band. This leads to a dilemma: each actor (space agency, private stakeholder, etc.) has an incentive to delay its actions and wait for others to respond. The risk of the latter action is that, if everyone waits the joint outcome will be catastrophic leading to what in game theory is referred to as the ‘tragedy of the commons’. We introduce and thoroughly analyse this dilemma using simulation and empirical game theory in a two player setting.
Heuristic Constraint Answer Set Programming
Authors: Teppan Erich C.  , Friedrich Gerhard
Published: February 2025

Constraint answer set programming (CASP) is a family of hybrid approaches integrating answer set programming (ASP) and constraint programming (CP). These hybrid approaches have already proven to be very successful in various domains. In this paper we present first evaluation results for the CASP solver ASCASS, which provides novel methods for defining and exploiting problem-dependent search heuristics. Beyond the possibility of using already built-in problem-independent heuristics, ASCASS allows on the ASP level the definition of problem-dependent variable selection, value selection and pruning strategies, which guide the search of the CP solver. The proof-of-concept evaluation was carried out on benchmark instances of the real world Partner Units Problem (PUP). Due to a sophisticated heuristic, which cannot be represented by other ASP or CASP solvers, ASCASS shows superior performance.
Multi-Level Semantics with Vertical Integrity Constraints
Authors: Panisson Alison R.  , Bordini Rafael H.  , da Rocha Costa Antônio Carlos
Published: February 2025

Operational semantics is a fundamental approach to the formalisation of programming languages and almost a standard when it comes to agent-oriented programming languages. It helps ensure the correctness of interpreters, facilitates their implementation, and supports proofs of important properties. Multi-agent oriented systems are a particular kind of distributed systems and through the semantics of agent languages, operational semantics ended up playing an important role towards ensuring their desired behaviour, even though the operational semantics becomes more involved than originally intended. This work presents a new style for the operational semantics of systems with multiple levels of abstractions (such as multi-agent systems), by providing multi-level transitions (i.e., multiple hierarchical transition systems) with vertical (i.e., inter-level) integrity constraints to ensure consistency of interrelated transitions.
Toward Addressing Collusion Among Human Adversaries in Security Games
Authors: Gholami Shahrzad  , Wilder Bryan  , Brown Matthew  , Thomas Dana  , Sintov Nicole  , Tambe Milind
Published: February 2025

Security agencies including the US Coast Guard, the Federal Air Marshal Service and the Los Angeles Airport police are several major domains that have been deploying Stackelberg security games and related algorithms to protect against a single adversary or multiple, independent adversaries strategically. However, there are a variety of real-world security domains where adversaries may benefit from colluding in their actions against the defender. Given the potential negative effect of these collusive actions, the defender has an incentive to break up collusion by playing off the self-interest of individual adversaries. This paper deals with problem of collusive security games for rational and bounded rational adversaries. The theoretical results verified with human subject experiments showed that behavior model which optimizes against bounded rational adversaries provides demonstrably better performing defender strategies against human subjects.
Detecting Communities Using Coordination Games: A Short Paper
Authors: Arava Radhika  , Varakantham Pradeep
Published: February 2025

Communities typically capture homophily as people of the same community share many common features. This paper is motivated by the problem of community detection in social networks, as it can help improve our understanding of the network topology. Given the selfish nature of humans to align with like-minded people, we employ game theoretic models and algorithms to detect communities in this paper. Specifically, we employ coordination games to represent interactions between individuals in a social network. We provide a novel and scalable two phased algorithm NashOverlap to compute an accurate overlapping community structure in the given network. We evaluate our algorithm against the best existing methods for community detection and show that our algorithm improves significantly on benchmark networks with respect to standard normalised mutual information measure.
Pricing Options with Portfolio-Holding Trading Agents in Direct Double Auction
Authors: Abdullaev Sarvar  , McBurney Peter  , Musial Katarzyna
Published: February 2025

Options constitute integral part of modern financial trades, and are priced according to the risk associated with buying or selling certain asset in future. Financial literature mostly concentrates on risk-neutral methods of pricing options such as Black-Scholes model. However, it is an emerging field in option pricing theory to use trading agents with utility functions to determine the option's potential payoff for the agent. In this paper, we use one of such methodologies developed by Othman and Sandholm to design portfolio-holding agents that are endowed with popular option portfolios such as bullish spread, butterfly spread, straddle, etc to price options. Agents use their portfolios to evaluate how buying or selling certain option would change their current payoff structure, and form their orders based on this information. We also simulate these agents in a multi-unit direct double auction. The emerging prices are compared to risk-neutral prices under different market conditions. Through an appropriate endowment of option portfolios to agents, we can also mimic market conditions where the population of agents are bearish, bullish, neutral or non-neutral in their beliefs.
Case-Based Classification on Hierarchical Structure of Formal Concept Analysis
Authors: Zhang Qi  , Shi Chongyang  , Sun Ping  , Niu Zhengdong
Published: February 2025

We propose a novel Hierarchical CBC model (HCBC) based on Formal Concept Analysis (FCA). Firstly, Concept Lattice (CL), the hierarchical and conceptual structure in FCA, is adopted to represent cases. Thus a novel dynamic weight model is proposed from CL to measure similarities between cases and concepts. Then the similarity metric is applied to retrieve the top-K similar concepts which are used to vote for adaptive solutions for new cases by majority voting in case adaption. Experiments show our model shows good performance in terms of accuracy and outperforms the other classification methods.
Relational Grounded Language Learning
Authors: Becerra-Bonache Leonor  , Blockeel Hendrik  , Galván María  , Jacquenet François
Published: February 2025

In the past, research on learning language models mainly used syntactic information during the learning process but in recent years, researchers began to also use semantic information. This paper presents such an approach where the input of our learning algorithm is a dataset of pairs made up of sentences and the contexts in which they are produced. The system we present is based on inductive logic programming techniques that aim to learn a mapping between n-grams and a semantic representation of their associated meaning. Experiments have shown that we can learn such a mapping that made it possible later to generate relevant descriptions of images or learn the meaning of words without any linguistic resource.
Integrating ARIMA and Spatiotemporal Bayesian Networks for High Resolution Malaria Prediction
Authors: Hasan A. H. M. Imrul  , Haddawy Peter
Published: February 2025

Since malaria is prevalent in less developed and more remote areas in which public health resources are often scarce, targeted intervention is essential in allocating resources for effective malaria control. To effectively support targeted intervention, predictive models must be not only accurate but they must also have high temporal and spatial resolution to help determine when and where to intervene. In this paper we take the first essential step towards a system to support targeted intervention in Thailand by developing a high resolution prediction model through the combination of Bayes nets and ARIMA. Bayes nets and ARIMA have complementary strengths, with the Bayes nets better able to represent the effect of environmental variables and ARIMA better able to capture the characteristics of the time series of malaria cases. Leveraging these complementary strengths, we develop an ensemble predictor from the two that has significantly better accuracy that either predictor alone. We build and test the models with data from Tha Song Yang district in northern Thailand, creating village-level models with weekly temporal resolution.
Schema-Based Debugging of Federated Data Sources
Authors: Nolle Andreas  , Meilicke Christian  , Chekol Melisachew Wudage  , Nemirovski German  , Stuckenschmidt Heiner
Published: February 2025

Information explosion leads to continuous growth of data distributed over different data sources. However, the increasing number of data sources increases the risk of inconsistency. In such a federative setting, description logics can be applied to define a central schema that serves as a conceptual view comprising and extending the semantics of each data source. Consequently, each data source is treated as a single knowledge base that is integrated in a federated knowledge base. Following this idea, we propose an approach for automated debugging of federated knowledge bases that targets the identification and repair of inconsistency. We report on experiments with a large distributed dataset from the domain of library science.
Randomized Distribution Feature for Image Classification
Authors: Shan Hongming  , Zhang Junping
Published: February 2025

Local image features can be assumed to be drawn from an unknown distribution. For image classification, such features are compared through the histogram-based model or the metric-based model. By quantizing these local features into a set of histograms, the histogram-based model is convenient and has vectorial representation of image but information could be lost in vector quantization. Unlike the histogram-based model, the metric-based model estimates the metrics over the underlying distribution of local features immediately, achieving better predictive performance. However, the model requires higher computational cost and loses the benefit of vectorial representation of image.
Observation-Based Multi-Agent Planning with Communication
Authors: Gasparini Luca  , Norman Timothy J.  , Kollingbaum Martin J.
Published: February 2025

Models of decentralized online planning vary in the information that individual agents use to make local action decisions. Some models consider only local observations, eschewing coordination through communication. Others use communication to ensure that all agents are aware of the action decisions of others, but assume costless and delay-free communication. In this paper, we propose a model of online planning (OB-MAP) that uses estimates of the value of communicating to manage coordination through communication as costs vary. We compare this approach to existing models in widely employed benchmark problems, demonstrating that OB-MAP performs significantly better in many scenarios regardless of varying (including infinite) cost of communication.
Attuning Ontology Alignments to Semantically Heterogeneous Multi-Agent Interactions
Authors: Chocron Paula  , Schorlemmer Marco
Published: February 2025

In this paper we tackle the problem of semantic heterogeneity in multi-agent communication, i.e., when agents in a multi-agent system use different vocabularies for message passing, or might interpret shared vocabulary in varying ways. The problem of achieving meaningful communication in such semantically heterogeneous multi-agent interactions has been mainly tackled either by using ontology alignments to translate vocabularies, or by using methods that learn an alignment by observing how the utterance of particular terms affects the unfolding of an interaction. We propose solutions that combine these approaches and study how agents can use external alignments with possibly incomplete or erroneous mappings when communicating with each other in the context of a multi-agent interaction. We further show experimentally that with the experience gained through repeated interactions and by using simple learning techniques agents can find and repair those mappings of an ontology alignment that lead to unsuccessful interactions, thus improving the success rate of their future interactions.
Combining Efficient Preprocessing and Incremental MaxSAT Reasoning for MaxClique in Large Graphs
Authors: Jiang Hua  , Li Chu-Min  , Manyà Felip
Published: February 2025

We describe a new exact algorithm for MaxClique, called LMC (short for Large MaxClique), that is especially suited for large sparse graphs. LMC is competitive because it combines an efficient preprocessing procedure and incremental MaxSAT reasoning in a branch-and-bound scheme. The empirical results show that LMC outperforms existing exact MaxClique algorithms on large sparse graphs from real-world applications.
You Can't Always Forget What You Want: On the Limits of Forgetting in Answer Set Programming
Authors: Gonçalves Ricardo  , Knorr Matthias  , Leite João
Published: February 2025

Selectively forgetting information while preserving what matters the most is becoming an increasingly important issue in many areas, including in knowledge representation and reasoning. Depending on the application at hand, forgetting operators are defined to obey different sets of desirable properties. Of the myriad of desirable properties discussed in the context of forgetting in Answer Set Programming, strong persistence, which imposes certain conditions on the correspondence between the answer sets of the program pre-and post-forgetting, and a certain independence from non-forgotten atoms, seems to best capture its essence, and be desirable in general. However, it has remained an open problem whether it is always possible to forget a set of atoms from a program while obeying strong persistence. In this paper, after showing that it is not always possible to forget a set of atoms from a program while obeying this property, we move forward and precisely characterise what can and cannot be forgotten from a program, by presenting a necessary and sufficient criterion. This characterisation allows us to draw some important conclusions regarding the existence of forgetting operators for specific classes of logic programs, to characterise the class of forgetting operators that achieve the correct result whenever forgetting is possible, and investigate the related question of determining what we can forget from some specific logic program.
Gaining Insight by Structural Knowledge Extraction
Authors: Cottone Pietro  , Gaglio Salvatore  , Lo Re Giuseppe  , Ortolani Marco
Published: February 2025

The availability of increasingly larger and more complex datasets has boosted the demand for systems able to analyze them automatically. The design and implementation of effective systems requires coding knowledge about the application domain inside the system itself; however, the designer is expected to intuitively grasp the most relevant features of the raw data as a preliminary step.
Early Requirements Analysis for a Socio-Technical System Based on Goal Dependencies
Authors: Kaiya Haruhiko  , Ogata Shinpei  , Hayashi Shinpei  , Saeki Motoshi
Published: February 2025

A socio-technical system (STS) consists of many different actors such as people, organizations, software applications and infrastructures. We call actors except both people and organizations machines. Machines should be carefully introduced into the STS because the machines are beneficial to some people or organization but harmful to others. We thus propose a goal-oriented requirements modelling language called GDMA based on i* so that machines with the following characteristics can be systematically specified. First, machines make the goals of each people be achieved more and better than ever. Second, machines make people achieve goals fewer and easier than ever. We also propose analysis techniques of GDMA to judge whether or not the introduction of machines are appropriate or not. Several machines are introduced into an as-is model of GDMA locally with the help of model transformation techniques. Then, such an introduction is evaluated globally on the basis of metrics derived from the model structure. We confirmed that GDMA could evaluate the successful and failure of existing projects.
Design and Control of Quad-Copter Using GPS and Inertial Sensors for Parcel Delivery
Authors: Pattar Prathamesh  , Naik Apurva
Published: February 2025

This paper highlights our research towards development of a quadcopter to deliver postal mails and confidential letters from source to destination. The system consists of Unmanned Aerial Unit, Control System, Control Link and other Support equipment. The Unmanned Aerial Unit is controlled by the Control System which communicates with the Ground Control Station (GCS) via a control link that is Micro Air Vehicle (MAV) link. A GCS is a software application that communicates with the quadcopter via radio telemetry. The basic flight of the quadcopter all depends on the motor speed and direction. Motor speed is controlled by the Pulse Width Modulation (PWM) signal by changing the duty cycle as required. Inertial sensors are sensors that work on the principle of inertia. The inertial measurement unit consists of Accelerometer, magnetometer and gyroscope. These sensors are placed on the quadcopter to acquire current position and orientation along with a roll, yaw and pitch positions. The Ultrasonic sensor is also used in order to detect any obstacles in the desired path of the fly. As a result, the software application at the GCS will have a panel which will display all the information related to the quadcopter system. Global Positioning System (GPS) is used in order to decide the coordinates or the waypoints from source to destination. As a final product, the quadcopter flies autonomously from source to destination tracing the path all by itself using the GPS module placed on it. Another option of controlling the quadcopter by remote control is also possible.
Software for Engineering Representations in University Course
Authors: Gáti József  , Némethy Krisztina  , Szakál Anikó
Published: February 2025

Application of extensive software systems changed work of in engineers at development and application of products in industry. New situation is characterized by control of generation representations in contextual model environment, definition of automatically reused knowledge for adaptive model, cooperation of disciplines, and survey of complex structures of model representations. This new situation requires new approach, concept, and methodology to curriculum definition, course planning, laboratory environment configuration, and knowledge transfer to students considering software system as teaching environment. Considerations about engineering purposed software system, definition and representation of engineering objects in this system, and knowledge content of higher education should be coordinated at course specification. This paper introduces a new approach to organized analysis of effects of the above new situation on higher education courses. It starts with discussion of the new situation considering the anticipated changes of course programs. Following this new generalized model of engineering course in virtual environment is conceptualized. Finally, analysis of effects on higher education courses is introduced considering the above model.
A Secure Cloud-Based SCADA Application: The Use Case of a Water Supply Network
Authors: Cerullo Gianfranco  , Mazzeo Giovanni  , Papale Gaetano  , Sgaglione Luigi  , Cristaldi Rosario
Published: February 2025

Cloud computing paradigm is gaining more and more momentum, to the extent that it is no more confined to its initial application domains, i.e. use by enterprises and businesses willing to lower costs or to increase computing capacity in a flexible manner. In particular, increasing interest is recently being paid to the huge potentials – in terms of benefits for the society at large – that might result from the adoption of cloud computing technology by critical infrastructure (CI) operators. This is of course putting special emphasis on the need for dependable and trustworthy security mechanisms in cloud technology based services, since a critical infrastructure is vital for essential functioning of a country. Incidental or deliberate damages to a CI have serious impacts on the economy, and possibly make essential services unavailable to the communities it serves. In this paper we present the proof-of concept of a cloud-based Water Supply Network Monitoring (WSNM) application, named RiskBuster (RB), that ensures the confidentiality and integrity of SCADA monitoring data collected from dam sensors and stored in the cloud by using the innovative Intel Software Guard eXtension (SGX) technology.
A Virtual Patient Representation in the Medical Rehabilitation Domain
Authors: Gal Norbert  , Andrei Diana  , Poenaru Dan V.  , Stoicu-Tivadar Vasile  , Gal-Nădăşan Emanuela
Published: February 2025

This paper proposes a virtual patient (VP) for the medical rehabilitation domain using the digital representation of the real life patient's matchstick skeleton. This virtual patient is used to analyze and track the recovery of the orthopedic patient with malicious posture problems. The creation of the digital patient was realized using a markerless depth camera, the Microsoft Kinect. The gathered data was saved in to a BVH type motion capture file. This file records not only the skeletal structure of the patient but its movements as well from witch the adduction, rotation and flexion angles of the joints can be analyzed. The data is stored in structured text format making it suitable to be used in telemedicine. The results confirm the utility and usability of the digital patient in clinical reasoning and in educational applications.
A Web-Based Database for Nurse Led Outreach Teams (NLOT) in Toronto
Authors: Li Shirley  , Kuo Mu-Hsing  , Ryan David
Published: February 2025

A web-based system can provide access to real-time data and information. Healthcare is moving towards digitizing patients' medical information and securely exchanging it through web-based systems. In one of Ontario's health regions, Nurse Led Outreach Teams (NLOT) provide emergency mobile nursing services to help reduce unnecessary transfers from long-term care homes to emergency departments. Currently the NLOT team uses a Microsoft Access database to keep track of the health information on the residents that they serve. The Access database lacks scalability, portability, and interoperability. The objective of this study is the development of a web-based database using Oracle Application Express that is easily accessible from mobile devices. The web-based database will allow NLOT nurses to enter and access resident information anytime and from anywhere.
Architecture of a Biomedical Informatics Research Data Management Pipeline
Authors: Bauer Christian R.  , Umbach Nadine  , Baum Benjamin  , Buckow Karoline  , Franke Thomas  , Grütz Romanus  , Gusky Linda  , Nussbeck Sara Yasemin  , Quade Matthias  , Rey Sabine  , Rottmann Thorsten  , Rienhoff Otto  , Sax Ulrich
Published: February 2025

In University Medical Centers, heterogeneous data are generated that cannot always be clearly attributed to patient care or biomedical research. Each data set has to adhere to distinct intrinsic and operational quality standards. However, only if high-quality data, tools to work with the data, and most importantly guidelines and rules of how to work with the data are addressed adequately, an infrastructure can be sustainable. Here, we present the IT Research Architecture of the University Medical Center Göttingen and describe our ten years' experience and lessons learned with infrastructures in networked medical research.
A Strategy for Reusing the Data of Electronic Medical Record Systems for Clinical Research
Authors: Matsumura Yasushi  , Hattori Atsushi  , Manabe Shiro  , Tsuda Tsutomu  , Takeda Toshihiro  , Okada Katsuki  , Murata Taizo  , Mihara Naoki
Published: February 2025

There is a great need to reuse data stored in electronic medical records (EMR) databases for clinical research. We previously reported the development of a system in which progress notes and case report forms (CRFs) were simultaneously recorded using a template in the EMR in order to exclude redundant data entry. To make the data collection process more efficient, we are developing a system in which the data originally stored in the EMR database can be populated within a frame in a template. We developed interface plugin modules that retrieve data from the databases of other EMR applications. A universal keyword written in a template master is converted to a local code using a data conversion table, then the objective data is retrieved from the corresponding database. The template element data, which are entered by a template, are stored in the template element database. To retrieve the data entered by other templates, the objective data is designated by the template element code with the template code, or by the concept code if it is written for the element. When the application systems in the EMR generate documents, they also generate a PDF file and a corresponding document profile XML, which includes important data, and send them to the document archive server and the data sharing saver, respectively. In the data sharing server, the data are represented by an item with an item code with a document class code and its value. By linking a concept code to an item identifier, an objective data can be retrieved by designating a concept code. We employed a flexible strategy in which a unique identifier for a hospital is initially attached to all of the data that the hospital generates. The identifier is secondarily linked with concept codes. The data that are not linked with a concept code can also be retrieved using the unique identifier of the hospital. This strategy makes it possible to reuse any of a hospital's data.
A SOA-Based Solution to Monitor Vaccination Coverage Among HIV-Infected Patients in Liguria
Authors: Giannini Barbara  , Gazzarata Roberta  , Sticchi Laura  , Giacomini Mauro
Published: February 2025

Vaccination in HIV-infected patients constitutes an essential tool in the prevention of the most common infectious diseases. The Ligurian Vaccination in HIV Program is a proposed vaccination schedule specifically dedicated to this risk group. Selective strategies are proposed within this program, employing ICT (Information and Communication) tools to identify this susceptible target group, to monitor immunization coverage over time and to manage failures and defaulting. The proposal is to connect an immunization registry system to an existing regional platform that allows clinical data re-use among several medical structures, to completely manage the vaccination process. This architecture will adopt a Service Oriented Architecture (SOA) approach and standard HSSP (Health Services Specification Program) interfaces to support interoperability. According to the presented solution, vaccination administration information retrieved from the immunization registry will be structured according to the specifications within the immunization section of the HL7 (Health Level 7) CCD (Continuity of Care Document) document. Immunization coverage will be evaluated through the continuous monitoring of serology and antibody titers gathered from the hospital LIS (Laboratory Information System) structured into a HL7 Version 3 (v3) Clinical Document Architecture Release 2 (CDA R2).
Visualization of Large Ontologies in University Education from a Tool Point of View
Authors: Schaaf Michael  , Jahn Franziska  , Tahar Kais  , Kücherer Christian  , Winter Alfred  , Paech Barbara
Published: February 2025

The realization of ontology visualization requirements in university education is a challenging task and should be supported by appropriate tools. This applies in particular, if the ontology to be visualized is based on a large text corpus that comprises a huge number of concepts, relations and annotations. In SNIK, we developed such an ontology of information management in hospitals in order to support the transfer of knowledge in the context of the university education. The challenge is to identify tools and methods, which are capable to support ontology visualization and usage as efficiently as possible. Related research fields (e.g. bioinformatics) are confronted with similar visualization problems. These tools and methods used could provide a suitable solution in our research field. In total, we assessed eight tools concerning the visualization of large ontologies to evaluate their suitability representing knowledge in the field of medical informatics.
An Ontology-Based Scenario for Teaching the Management of Health Information Systems
Authors: Jahn Franziska  , Schaaf Michael  , Kahmann Christian  , Tahar Kais  , Kücherer Christian  , Paech Barbara  , Winter Alfred
Published: February 2025

The terminology for the management of health information systems is characterized by complexity and polysemy which is both challenging for medical informatics students and practitioners. SNIK, an ontology of information management (IMI) in hospitals, brings together IM concepts from different literature sources. Based on SNIK, we developed a blended learning scenario to teach medical informatics students IM concepts and their relationships. In proof-of-concept teaching units, students found the use of SNIK in teaching and learning motivating and useful. In the next step, the blended learning scenario will be rolled out to an international course for medical informatics students.
Converting ODM Metadata to FHIR Questionnaire Resources
Authors: Doods Justin  , Neuhaus Philipp  , Dugas Martin
Published: February 2025

Interoperability between systems and data sharing between domains is becoming more and more important. The portal medical-data-models.org offers more than 5.300 UMLS annotated forms in CDISC ODM format in order to support interoperability, but several additional export formats are available. CDISC's ODM and HL7's framework FHIR Questionnaire resource were analyzed, a mapping between elements created and a converter implemented. The developed converter was integrated into the portal with FHIR Questionnaire XML or JSON download options. New FHIR applications can now use this large library of forms.
Expansion of the Hierarchical Terminology Auditing Framework Through Usage of Levenshtein Distance-Based Criterion
Authors: Zakharchenko Aleksandr  , Geller James
Published: February 2025

We continue our previous work of creating and improving a framework for detecting the differences between hierarchical terminologies and suggesting ways to connect them, which is implemented in an automated tool.
Assessment of Content-Based Image Retrieval Approaches for Mammography Based on Breast Density Patterns
Authors: Purwadi Nabila Sabatini  , Atay Hüseyin Tanzer  , Kurt Kenan Kaan  , Turkeli Serkan
Published: February 2025

This study is trying to assess methods commonly used in content-based image retrieval (CBIR) for screening mammography analysis. A database consists of 12 different BI-RADS classes related to breast density patterns of mammogram patches which are taken from IRMA database is used in this study. Three feature extraction methods, namely grey-level co-occurrence matrix (GLCM), principal component analysis (PCA), and scale-invariant feature transform (SIFT) are being investigated and compared with prior studies. Two retrieval methods are also used in this study, namely k-nearest neighbor (KNN) and mutual information (MI) to measure the similarity between query image and images in database. The result will be evaluated using positive count rate in each query for each class. The result of this study is expected to contribute more towards better Computed-Aided Diagnosis (CADx) and specifically screening mammography analysis in clinical cases.
Spatiotemporal Bayesian Networks for Malaria Prediction: Case Study of Northern Thailand
Authors: Haddawy Peter  , Kasantikul Rangwan  , Hasan A.H.M. Imrul  , Rattanabumrung Chunyanuch  , Rungrun Pichamon  , Suksopee Natwipa  , Tantiwaranpant Saran  , Niruntasuk Natcha
Published: February 2025

While a diversity of modeling technique have been used to create predictive models of malaria, no work has made use of Bayesian networks. Bayes nets are attractive due to their ability to represent uncertainty, model time lagged and nonlinear relations, and provide explanations of inferences. This paper explores the use of Bayesian networks to model malaria, demonstrating the approach by creating a village level model with weekly temporal resolution for Tha Song Yang district in northern Thailand. The network is learned using data on cases and environmental covariates. The network models incidence over time as well as evolution of the environmental variables, and captures time lagged and nonlinear effects. Out of sample evaluation shows the model to have high accuracy for one and two week predictions.
Modeling Single-Peakedness for Votes with Ties
Authors: Fitzsimmons Zack  , Hemaspaandra Edith
Published: February 2025

Single-peakedness is one of the most important and well-known domain restrictions on preferences. The computational study of single-peaked electorates has largely been restricted to elections with tie-free votes, and recent work that studies the computational complexity of manipulative attacks for single-peaked elections for votes with ties has been restricted to nonstandard models of single-peaked preferences for top orders. We study the computational complexity of manipulation for votes with ties for the standard model of single-peaked preferences and for single-plateaued preferences. We show that these models avoid the anomalous complexity behavior exhibited by the other models. We also state a surprising result on the relation between the societal axis and the complexity of manipulation for single-peaked preferences.
Tackling the Winograd Schema Challenge Through Machine Logical Inferences
Authors: Isaak Nicos  , Michael Loizos
Published: February 2025

Levesque has argued that the problem of resolving difficult pronouns in a carefully chosen set of twin sentences, which he refers to as the Winograd Schema Challenge (WSC), could serve as a conceptually and practically appealing alternative to the well-known Turing Test. As he said, probably anything that answers correctly a series of these questions is thinking in the full-bodied sense we usually reserve for people. In this paper we examine the task of resolving cases of definite pronouns. Specifically, we examine those for which traditional linguistic constraints on co-reference as well as commonly-used resolution heuristics are not useful, or the procedure they follow is very similar to a statistical approach, without invoking common logic like humans do.
Inclusive Planning: Paramount in Today's Norway
Authors: Nohr Trine  , Langset Eli Kristin
Published: February 2025

Democratic rights are granted by its nations legislation and systems, but needs enforcement by its institutions to be effective. This also relates to Universal Design. The refugee crisis in Europe raises questions as to how planning in the societies can be designed and implemented to include the new groups of the population. The Norwegian Planning and Building Act (PBA) put weight on the individual's or a group's right to influence public assessment and decision making processes. In this article a case from the Veitvet-Sletteløkka area in the ward of Bjerke, Oslo, is presented to show how these principles can be put into practice. The case clearly demonstrates how the presence of representatives from the ward and planning authority built trust to the various parts of the local community by a consistent and inclusive approach. Also, to further enhance inclusion and effectiveness in planning, the case illustrates the need for adapting new technologies, communication modes and perspectives.
How to Solve Dilemmas Arising from the Idea of Improving Physical Accessibility in Relation to Aesthetics and Architectural Heritage
Authors: Asmervik Sigmund
Published: February 2025

The Norwegian state has been working for more than fifteen years on various ways of improving accessibility for the general public. An important part of this work has been to develop new legislation and other forms of formal guidelines to reduce physical barriers. The new Anti-Discrimination and Accessibility Act, Obligation to ensure general accommodation (universal design), came into force January 2009, and introduces some complicated dilemmas, especially when it states: “When assessing whether the design or accommodation entails an undue burden, particular importance shall be attached to the effect of the accommodation on the dismantling of disabling barriers, the necessary costs associated with the accommodation, the undertaking's resources, whether the normal function of the undertaking is of a public nature, safety considerations and cultural heritage considerations.” What is an “undue burden” in relation to architectural visual qualities and to the historical heritage expressed in buildings and townscapes? This paper will look into these dilemmas by discussing specific cases from some cities in different countries. What kinds of procedure are suitable and decisive when it comes to these complicated questions? Is this a task exclusively reserved for professionals, or should the voice of lay people be heard and taken into consideration? By presenting examples from architecture and landscape architecture, I will show how universal design even can be implemented in old buildings and environments. The paper will argue for more focus on procedures than just physical solutions. The procedures should be based on accepted principles for changing historical monuments, such as wholeness, readability, reversibility and sustainability.
On Efficiently Enumerating Semi-Stable Extensions via Dynamic Programming on Tree Decompositions
Authors: Bliem Bernhard  , Hecher Markus  , Woltran Stefan
Published: February 2025

Many computational problems in the area of abstract argumentation are intractable. For some semantics like preferred and semi-stable, important decision problems can even be hard for classes of the second level of the polynomial hierarchy. One approach to deal with this inherent difficulty is to exploit structure of argumentation frameworks. In particular, algorithms that run in linear time for argumentation frameworks of bounded treewidth have been proposed for several semantics. In this paper, we contribute to this line of research and propose a novel algorithm for the semi-stable semantics. We also present an implementation of the algorithm and report on some experimental results.
Minimal Cost Semantics in Argumentation Framework on Semiring Cost Assignment
Authors: Bundo Shuya  , Yamaguchi Kazunori
Published: February 2025

Cost based methods have been proposed as ways to extend Argumentation frameworks proposed by Dung but have been found to contain an anomaly. In this paper, we introduce a new cost based method that is free from the anomaly. We also describe a preliminary algorithm to calculate the cost.
Comparison of Features, Window Sizes and Classifiers in Detecting Freezing of Gait in Patients with Parkinson's Disease Through a Waist-Worn Accelerometer
Authors: Rodríguez-Martín Daniel  , Samà Albert  , Pérez-López Carlos  , Català Andreu  , Mestre Berta  , Alcaine Sheila  , Bayès Àngels
Published: February 2025

Freezing of gait is one of the most disturbing and incapacitating symptoms in Parkinson's Disease. This is defined as a sudden block in effective stepping, provoking anxiety, stress and falls. FoG is usually evaluated by means of different questionnaires; however, this method has shown not to be reliable since it is subjective due to its dependence on patients' and caregivers' judgement. Several authors have analysed the usage of MEMS inertial systems to detect FoG with the aim of objective evaluate this symptom. So far, a threshold-based method based on accelerometer's frequency response has been employed in many works; nonetheless, since it has been developed and tested in laboratory conditions, it provides a much lower accuracy at patients' home. This work proposes a new set of features to detect FoG by using accelerometers, which is compared with three previously reported approaches to detect FoG. The different feature sets are trained by means of several machine learning classifiers; furthermore, different window sizes are also evaluated. Results show that the proposed method detects FoG at patients' home with 91.7% and 87.4% of sensitivity and specificity, respectively, enhancing the results of former methods between a 5% and 11% and providing a more balanced rate of true positives and true negatives.
Is Consciousness a Control Process?
Authors: Arsiwalla Xerxes D.  , Herreros Ivan  , Moulin-Frier Clément  , Sanchez Marti  , Verschure Paul
Published: February 2025

Understanding the nature of consciousness has been an outstanding scientific puzzle at the crossroads of neuroscience and artificial intelligence. While brains have long since known to be the bearers of consciousness and machines, that of computation, the history of cybernetics has been full of attempts trying to synthesize consciousness in computational architectures. In recent years, ideas from control theory have proven to be extremely useful for addressing systems-level questions in neuroscience and designing cognitive architectures. Extending these ideas to the study of consciousness, we discuss the core functions of consciousness and control architectural specifications of agents capable of operationalizing these functionalities. We suggest that evolutionary pressures on social dynamics of interacting agents leads to the emergence of consciousness, which is a process for predicting intentional states of other agents (and self) in order to generate social cooperative and competitive behaviors necessary to optimize an agent's survival drives in a world with limited resources.
Egocentric Image Retrieval with Convolutional Neural Networks
Authors: Oliveira-Barra Gabriel  , Dimiccoli Mariella  , Radeva Petia
Published: February 2025

Recent advances in lifelogging technologies, and in particular, in the field of wearable cameras, have made possible to capture continuously our daily life from a first-person point of view and in a free-hand fashion. However, given the huge amount of images captured and the rate to which they increase (up to 2000 images per day), there is a strong need for efficient and scalable indexing and retrieval systems over egocentric images. To cope with those requirements, we develop a full Content-Based Image Retrieval system based on Convolutional Neural Network (CNN) features. We use egocentric images to create a Lucene index with off-the-shelf features extracted from a pre-trained CNN. Finally, we provide a web-based prototype for egocentric image search and retrieval and tested its performances on the EDUB egocentric dataset.