bluuebunny/crossref_metadata_2025 huggingface dataset:
The Experiment of Sweden Game and the Effect of Students Education
Authors: Kawaguchi Masashi  , Atsumi Kiyotaka  , Baba Norio
Published: February 2025

In this research, we carried out the Sweden game and described its educational effect. The Sweden game is one way to determine cost-sharing for the construction of a pipeline. Three groups of about 40 students were used, with each group consisting of six teams. As a result, we obtained a good solution. Additionally, students learned practical methods, how to strategize, and how to bargain. We realized that this experiment brought the educational effect.
Performance comparison of non-RNN and RNN in Emergence of Discrete Decision Making through Reinforcement Learning
Authors: Samsudin Mohamad Faizal  , Shibata Katsunari
Published: February 2025

Using a neural network in the task that requires discrete decision making suffers from the problem of discrete decision making. On the other hand, using a lookup table suffers from the problem in generalization and the curse of dimensionality. In this paper, simple localized inputs in neural network are used in order to overcome this problem. Furthermore, by utilizing the internal dynamics in RNN, it is expected that quick discrete decision making can be obtained through learning.
An Information Recommendation System Focusing on Social Bookmarking
Authors: Kurahashi Setsuya  , Shirakawa Takahisa
Published: February 2025

This paper proposes an information recommendation system focusing on personal classification space based on bookmarks. This study handles the problem where the standard collaborative filtering method cannot offer recommendations with a better level of precision. This paper improves the collaborative filtering algorithm for users of social bookmark services. In this research, the classification-based method is proposed as the recommendation method, and Recall- DCG and Precision-DCG are proposed as evaluation scales. A user’s bookmarks are placed on his/her own classifying space made of tags. These bookmarks are transformed into a degree of similarity for recommendations. The degree is used to compare the personal classifying space with another’s space. Comparison with previous studies confirms the superiority of the method based on space classification. In particular, where the cos distance with the distribution weight added is used as similarity between items. The cos distance with the matching weight added is designed with the expectation of the effect of striking up the characteristics of other information. This proposed method shows a significant superiority in almost all experiments performed.
A General QBF-based Formalization of abstract Argumentation Theory
Authors: Arieli Ofer  , Caminada Martin W.A.
Published: February 2025

We introduce a unified logical approach, based on signed theories and Quantified Boolean Formulas (QBFs), that can serve as a basis for representing and reasoning with various argumentation-based decision problems. By this, we are able to represent, in a uniform and simple way, a wide range of extension-based semantics for argumentation theory, including complete, grounded, preferred, semi-stable, stage, ideal and eager semantics. Furthermore, our approach involves only propositional languages and quantifications over propositional variables, making decision problems like skeptical and credulous acceptance of arguments simply a matter of logical entailment and satisfiability, which can be verified by existing QBF-solvers.
Towards Experimental Algorithms for Abstract Argumentation
Authors: Nofal Samer  , Dunne Paul  , Atkinson Katie
Published: February 2025

From theoretical computational perspectives, decision problems in Dung's abstract argumentation frameworks (AFs) are either polynomial solvable or intractable. To investigate practical efficiency, theoretical evaluation of applied algorithms does not necessarily reveal performance dissimilarities. Although experimental analysis of algorithms is a well-established alternative exploited in other domains, such methodology is given a little attention in the context of AFs. The main purpose of this paper is to give an example of how such experiments can be conducted to get meaningful conclusions about algorithms' behavior in situations where theoretical analysis might be of little help. To this end, we pick an extended model of AFs as a case study to empirically examine the efficiency of algorithms related to the acceptability of arguments.
Argument Schemes for Reasoning about Trust
Authors: Parsons Simon  , Atkinson Katie  , Haigh Karen  , Levitt Karl  , McBurney Peter  , Rowe Jeff  , Singh Munindar P.  , Sklar Elizabeth
Published: February 2025

Trust is a natural mechanism by which an autonomous party can deal with the inherent uncertainty regarding the behaviors of other parties and the uncertainty in the information it shares with those parties. Trust is thus crucial in any decentralized system. We build on recent efforts to use argumentation to reason about trust. Specifically, we provide a set of schemes, abstract patterns of reasoning that apply in multiple situations, geared toward trust. We describe, in the form of a set of critical questions, the situations in which the schemes may default.
Video surveillance and security policy in France: From regulation to widespread acceptance
Authors: Heilmann Eric
Published: February 2025

This article presents a historical account of the introduction and use of video surveillance cameras in France. Specific reference is made of the introduction of regulatory and legislative arrangements and to political debates surrounding the provision of video surveillance cameras. A feature of the French context has been a desire by national government to install cameras more widely in public places and a resistance to do so by local regions (departments). This highlights a traditional tension between central and local government in France and the significance of political rhetoric to the ongoing installation and operation of video surveillance cameras.
E-Reconciliation in Rwanda
Authors: Bagambiki Erika
Published: February 2025

Rwanda was characterized by divisionism, where one part of Rwandan (Tutsi) was excluded. In 1994 tutsi genocide more than 1 million people were killed, mutilated and injured. Based on the analysis of field data collected through interviews, this research provided to decision makers a web portal solution to address the reconciliation challenges in Rwanda. The findings show that one of the benefits of implementing e-reconciliation web portal will be to get easily the information related to reconciliation there will be other benefits, like avoiding history distortion, it will show negative impact of genocide, and it will be the best way to help Rwandans and international community to learn about the genocide. Although a number of challenges have been found, the main challenge would be the lack of internet access; other challenges include: the authenticity of information and the collection of information to be posted on the web portal. To address those challenges e-reconciliation can be accessible via mobile phone as the majority of Rwandan has access to mobile phone. The information posted on e-reconciliation web portal must have references recognized and the decision makers have to delegate who will manage the posted information.
A Probabilistic Verification Framework for SysML Activity Diagrams
Authors: Ouchani Samir  , Ait'Mohamed Otmane  , Debbabi Mourad
Published: February 2025

The standard OMG/INCOSE SysML activity diagrams are behavioral models for specifying and analyzing probabilistic systems. In this paper, we present a formal verification framework for these diagrams that helps to mitigate the state-explosion problem in probabilistic model checking. To do so, we propose to reduce the size of SysML activity diagrams by eliminating and merging precise behaviors. The resulting model is checked using Probabilistic Computation Tree Logic (PCTL) properties. Moreover, we present a calculus for SysML activity diagrams (NuAC) that captures their underlying semantics. In addition, we prove the soundness of our approach by defining a probabilistic weak simulation relation between the semantics of the abstract and the concrete models. This relation is shown to preserve the satisfaction of the PCTL properties. Finally, we demonstrate the effectiveness of our approach on an online shopping system case study.
System Dynamics Approach to Model a Hybrid Manufacturing System
Authors: Guizzi Guido  , Chiocca Daniela  , Romano Elpidio
Published: February 2025

The aim of this work is to create a simulation model of a manufacturing system operating within the supply chain by system dynamics approach heeding dynamics of system-company and factors that may affect performance, so that management can have a useful tool for decision support. The results have shown interesting correlations between management choices and the system outputs.
Syntactic Issues Identified Developing the Latvian Treebank
Authors: Pretkalniņa Lauma  , Rituma Laura
Published: February 2025

The Latvian Treebank is being developed since 2010. In this paper we describe the latest developments of this project and the problems currently faced. We examine several gaps in our annotation scheme like determinant, ellipsis and insertion annotation and describe solutions we have chosen.
Trust and ICT: New Challenges for Public Administration
Authors: Keymolen Esther  , Prins Corien  , Raab Charles
Published: February 2025

Trust and trust-building are key themes of public administration, involving trust in the networks of administration, citizens' trust in public authorities and the trustworthiness of the latter. This chapter explores the meaning of trust, thereby focusing on relations between citizens and the state, with a particular focus on information flows and the use of new digital tools (such as web 2.0), in a climate of public scepticism about government. People exchange their personal details for public services, and the state gives information to citizens as part of accountability. Also, ICT developments intensify personal data processing, data matching, and data sharing between different administrative domains. This raises questions of surveillance, privacy protection and public access to information. As some examples in this chapter will show, digital tools may also facilitate service delivery, democracy and the provision of information as tools for accountability and transparency. However, it is questionable whether ICT itself provides trustworthy and sufficient instruments for achieving administrative objectives as well as public benefits and privacy protection.
Cryptanalyses of Two Ultralightweight RFID Authentication Protocols
Authors: Lo Nai-Wei  , Yeh Kuo-Hui  , Chen Hsuan-Yu
Published: February 2025

Owing to the individual privacy, system security and resource limitation of low-cost RF tag, ultralightweight RFID authentication has been massively investigated in these years. Recently, Kianersi et al. [3] and Lee et al. [4] proposed two well-studied RFID authentication schemes which attempt to achieve data confidentiality and tag computation efficiency. However, these two protocols are vulnerable as the shared secrets can be out of synchronization via a series of challenge-response operations. In this paper, we demonstrate the detailed malicious procedures on these two mechanisms and show their vulnerabilities.
On Design of Secure APIs for IoT Applications – Using Taiwan Uniform e-Invoices as Examples
Authors: Cha Shi-Cho  , Chen Jyun-Fu  , Huang Shih-Chieh  , Tseng Chih-Teng  , Chen Wei-Kai
Published: February 2025

Defining standard application programming interfaces (APIs) plays an important role in Internet of Things (IoT) applications to achieve interpretability. Among different issues of designing APIs for IoT applications, this study focuses on the security issue of designing an API for people to access data about machines, sensors, and other objects collected in servers. To address the issue, this study shares the experiences of designing APIs for Taiwan uniform e-invoices. To prevent tax evasion, Taiwan government holds uniform invoice lottery every two months. Because invoice owners may win NT $10,000,000, the security of APIs to access e-invoices is critical. This study illustrates the security considerations in designing major APIs of Taiwan uniform e-invoices. In addition to common security issues, such as communication security, authentication, and non-repudiation, the APIs consider special security issues in different scenarios. The API for point of sales (POS) applications and ERP systems addresses the security consideration to transfer bulk data among machines; the e-invoice donation API proposes a scheme to restrict that each authorized person can only invoke the API through a specific device; the API for mobile applications considers the issue that misused mobile applications may transfer personal sensitive data and credentials to others secretly; the API for invoice exchanging allows people to obtain e-invoices immediately after transactions with their smart phones and to verify the integrity of the invoices. While this study gives examples of designing secure API for IoT applications from different perspectives, the paper can hopefully contribute to the security of IoT applications.
Visualization of Graph Structures with Magnetic-Spring Model and Color-Coded Interaction
Authors: Zabiniako Vitaly
Published: February 2025

In this paper author provides description of the original approach for visual analysis of data represented with general graphs, based on modification of magnetic-spring model and color-coded cognitive manipulation with graph elements. The theoretical background of magnetic fields in application to graph drawing is presented along with discussion of appropriate visualization techniques for improved information analysis and comprehension. Usage of other existing graph layout strategies (e.g. hierarchical, circular) in conjunction with magnetic-spring approach are also considered for improved data representation capabilities. A concept of integrated virtual workshop for graph visualization is introduced which relies on aforementioned model and can be used in GVS (Graph Visualization Systems). A case study of application of proposed approach is presented along with conclusions of its usability and potential future work in this field.
Computational data protection law: trusting each other offline and online
Authors: Buchanan William  , Fan Lu  , Lawson Alistair  , Schafer Burkhard  , Scott Russel  , Thuemmler Christoph  , Uthmani Omair
Published: February 2025

The paper reports of a collaborative project between computer scientists, lawyers, police officers, medical professionals and social workers to develop a communication in infrastructure that allows information sharing while observing Data Protection law “by design”, through a formal representation of legal rules in a firewall type system.
Randomization Techniques for Secure Computation
Authors: Ishai Yuval
Published: February 2025

To what extent can a computation be made “simpler” by settling for computing a randomized encoding of the output? Originating from Yao's seminal idea of garbled circuits, answers to this question have found applications in cryptography and elsewhere. We will survey the state of the art on different flavors of this question that are motivated by different problems in secure computation and correspond to different notions of simplicity.
A Short Tutorial of Zero-Knowledge
Authors: Goldreich Oded
Published: February 2025

Zero-knowledge proofs are proofs that are both convincing and yet yield nothing beyond the validity of the assertion being proved. Their direct applications in cryptography are numerous, where they are typically used to force malicious parties to behave according to a predetermined protocol. In addition, zero-knowledge proofs serve as an excellent bench-mark for the study of various problems regarding cryptographic protocols.
Analysis-Driven Data Collection, Integration and Preparation for Visualisation
Authors: Thalheim Bernhard  , Kiyoki Yasushi
Published: February 2025

Data analysis based on spatial and temporal relationships leads to new knowledge discovery in multi-database environments. As various and almost infinite relationships are potentially existing among heterogeneous databases, it is important to realize an objective-based dynamic data analysis environment with appropriate data collection from selected databases.
A Technical Survey for Linked Open Data Federation Building
Authors: Nguyen Cuong Duc  , Duong Trong Hai
Published: February 2025

Linked Open Data (LOD) is a successfully initiative Semantic Web, which uses URIs and RDF techniques to connect related pieces of data on the Semantic Web. A rapidly growing number of LODs leads to new challenges for query processing. SPARQL-endpoint has been proposed to access LODs through SPARQL language, however, it requires a holistic understanding of the data when making a SPARQL query and supports a limited number of related LODs. To access distributed LODs, the LOD-federation is proposed. The LOD-federation is an abstract layer consisting a federated ontology and mechanisms for user query processing across LODs via the corresponding endpoints. In this study, a technical survey of recent works supporting for the LOD-federation building, is presented. An effective method of LOD ontology integration is suggested in order to build the federated ontology. Query decomposition algorithm is depicted to translate a query to the LOD-federation into subsequent LODs. Result integration method using co-reference entity and join operations, is also presented.
An Efficient Method for Hiding High Utility Itemsets
Authors: Vo Bay  , Lin Chun-Wei  , Hong Tzung-Pei  , Vu Vinh V.  , Nguyen Minh  , Le Bac
Published: February 2025

This paper proposes an algorithm to hide quickly high utility sensitive itemsets. To reduce the execution time, when an item from the sensitive itemset is selected, the rated value is calculated from each transaction containing this item and all values which need be hidden are modified at the same time. Experimental results show that the proposed algorithm improves significantly the runtime.
Comparative Study of Correlations in Financial Markets
Authors: Yoshikawa Takeo  , Arai Yuta  , Iyetomi Hiroshi
Published: February 2025

We elucidate correlations among stock price movements in S&P 500 and Tokyo Stock Exchange (TSE) taking advantage of the concept of community in networks. The correlation matrix, purified by random matrix theory, is regarded as the adjacency matrix for a stock correlation network. The network thus constructed has links with weights of either sign depending on whether stocks are correlated (positive) or anticorrelated (negative). Community is defined here as a group of stocks related to each other with positive correlation coefficients. The community detection allows us to find that the stocks in S&P 500 are split up into four communities with two conflicting triangular relations. In TSE, there exists three communities of stocks forming a conflicting triangle. We thus see that the frustrated correlation structure is common to the well-developed financial markets.
Development of A Decision Support System for Hybrid and Cloud Computing
Authors: Balachandran Bala M.
Published: February 2025

Cloud computing is undoubtedly one of the most widely discussed innovations of the last decade. The governance and enterprise architecture to obtain repeatable, scalable and secure business outcomes from cloud computing is still greatly undefined. In this paper we present a Cloud Computing Tipping Point (C2TP) framework that not only considers financial motivations, but also business initiatives, IT governance structures, IT operational control structures and technical architecture requirements to evaluate the benefits regarding cloud investment. This model can be leveraged by an ICT organization to evaluate the “tipping point” where the organization can make an informative decision to embrace cloud computing at the expense of on-premise hosting options. The model is a service centric framework created by mapping cloud computing attributes with industry best practices such as ValIT, Control Objectives for Information and related Technology (COBIT) and Information Technology Infrastructure Library (ITIL). This paper discusses the development of the C2TP model in detail with its findings.
Thailand One Tablet PC per First Grade Student, an Efficient Tool to Leverage Education Quality
Authors: Sirisaengtaksin Jantima  , Praneetpolgrang Prasong  , Tubtimhin Jirapon
Published: February 2025

The Thai government's One Tablet PC per Child (OTPC) policy is a noble effort to help children gain access to information, and to keep up with changing information technologies. But will it help them to think? (nationmultimedia.com, June 2012) The answer lies upon the good deed children, under certain circumstance.
Improving Early Diagnosis of Alzheimer's Disease Using Synchrony Measures
Authors: Gallego-Jutglà Esteve  , Solé-Casals Jordi
Published: February 2025

It is well-known that Alzheimer's disease causes changes on the electroencephalography of the patients. However those changes are difficult to parameterize. In this paper a new ratio between synchrony in θ and α band is investigated in order to get an early diagnosis of Mild Alzheimer's patients. The presented ratio is compared using two types of classifiers, Linear Discriminant Analysis and Artificial Neural Networks, with values of synchrony in the standard frequency bands. Presented results improve using the ratio in the linear classifier. Using the non-linear classifier, best results are obtained using synchrony measures in θ and α band simultaneously.
A Max-SAT-Based Approach to Constructing Optimal Covering Arrays
Authors: Ansótegui Carlos  , Izquierdo Idelfonso  , Manyà Felip  , Torres Jiménez José
Published: February 2025

This paper investigates a new exact method for constructing optimal covering arrays based on first encoding the problem as a Partial MaxSAT instance, and then solving the resulting instance with a state-of-the-art MaxSAT solver. To this end, we define an original MaxSAT encoding for covering arrays, and report on the experimentation performed to evaluate our MaxSAT-based approach. The obtained results indicate that MaxSAT is a good alternative for constructing optimal covering arrays, and it is worth to further investigate this new research direction in the area of combinatorial designs.
Selection of Gabor Filters with Choquet Integral for Texture Analysis in Mammogram Images
Authors: Valls Aida  , Medina Cindy  , Moreno Antonio  , Puig Domenec
Published: February 2025

Screening programs in high-risk populations constitute a major asset in the struggle against Breast Cancer. Currently, screening programs focus in the task of analyzing digital mammography images. In this sense, computer vision techniques are suitable to provide decisive help in this task. In particular, computer-based texture image analysis is an important discipline that is able to gather some evidences oriented to the early diagnosis of breast cancer, such as the analysis of mammographic density. In order to extract textural features, Gabor Filters have been extensively used. The image is filtered with a set of Gabor Filters having different frequencies, resolutions and orientations. In this paper, we address the problem of mammogram images analysis by means of a Gabor Filter bank. Specifically, we analyze the texture features provided by the Gabor Filter bank in three regions, namely: tumor region, tumor-border region, and normal tissue region. An important objective is to reach a suitable subset of Gabor Filters that produce a collection of texture features sufficiently different to distinguish among the three regions. In this work, we have used the Choquet integral operator in order to score each filter in the bank, giving thus the possibility to select the most appropriate Gabor Filters to face the task of identifying relevant features for each of the three regions mentioned above. A learning procedure based on optimization is used to find the appropriate parameters for the Choquet integral, taking into account some training examples and constraints.
Towards Cognitive Image Interpretation – Qualitative Descriptors, Domain Knowledge and Narrative Generation
Authors: Falomir Zoe
Published: February 2025

Qualitative image descriptors are combined with domain knowledge (object feature detectors and qualitative definitions) for generating narratives which provide cognitive interpretations of images in a specific domain. This approach is tested and analysed in two study cases: (i) a robot navigating through the corridors of the TI building at Universitat Jaume I (Spain) and (ii) a ambient intelligent system in corporated at Cartesium building at Universitäat Bremen (Germany).
A Survey of Side Channel Attacks on MPKCs potential for RFID
Authors: Li Weijian  , Tang Shaohua  , He Daojing
Published: February 2025

MPKC is one of the most promising public-key cryptosystems against cryptanalysis on quantum computer. Its effecient implementation is also suitable for low-resource portable devices such as smart cards and RFID tags. In this paper, we investigate the existing side channel attacks against MPKCs, give a survey of power analysis attacks and fault attacks, including DPA against SFLASH, and fault attacks against HFE.
Chameleon RFID and Tracking Prevention
Authors: Klonowski Marek  , Kutyłowski Mirosław  , Syga Piotr
Published: February 2025

We propose a method for prevention of tracking RFID tags. We consider the model in which the adversary may eavesdrop a large fraction of interactions, but not all of them.
SSL Usage in Commercial Internet of Things Platforms
Authors: Fisher Roy  , Hancke Gerhard
Published: February 2025

The uses for the Internet of Things are growing and cloud platforms have become available to manage deployed devices. The security of the Internet of Things is an important consideration and a challenge. There are potentially a large number of devices of limited capability that need to be managed and are required to perform tasks that depend on data flow to the back-end platform. Most platforms use the current industry standard for secure online communication – SSL (HTTPS). However, SSL allows for many different configurations, some of which are not secure. This paper offers an initial study of SSL communications security between devices and platforms by investigating the SSL implementations offered for prominent Internet of Things platforms. It is found that amongst these platforms the strength of the SSL configuration supported vary greatly.
Towards Systematic Research on Statutory Interpretation in AI and Law
Authors: Araszkiewicz Michał
Published: February 2025

This paper proposes a semi-formal model of legal argumentation concerning statutory interpretation in civil law countries, encompassing set-theoretical analysis of extensions of legal terms and the use of argumentation schemes. An actual example decided by the Polish Supreme Administrative Court is discussed in the context of the proposed model. It is contended that the scheme proposed here should be useful for the development of practically significant legal knowledge bases concerning statutory law.
Towards Twitter User Recommendation Based on User Relations and Taxonomical Analysis
Authors: Slabbekoorn Kristian  , Noro Tomoya  , Tokuda Takehiro
Published: February 2025

Twitter is one of the largest social media platforms in the world. Although Twitter can be used as a tool for getting valuable information related to a topic of interest, it is a hard task for us to find users to follow for this purpose. In this paper, we present a method for Twitter user recommendation based on user relations and taxonomical analysis. This method first finds some users to follow related to the topic of interest by giving keywords representing the topic, then picks up users who continuously provide related tweets from the user list. In the first phase we rank users based on user relations obtained from tweet behaviour of each user such as retweet and mention (reply), and we create topic taxonomies of each user from tweets posted during different time periods in the second phase. Experimental results show that our method is very effective in recommending users who post tweets related to the topic of interest all the time rather than users who post related tweets just temporarily.
Decision-Maker Modeling for Decision Support Application
Authors: Ölmez Manuela  , Lindemann Udo
Published: February 2025

Product development decisions represent challenging processes with various stakeholders from different disciplines and with different perspectives involved. Decisions can be highly complex due to the high amount of influencing factors that have to be considered simultaneously. Among other methods and tools, decision support systems (DSS) were developed to support decision-makers in handling complex decisions. One main disadvantage of DSS is the little adaptation to and integration of decision-maker needs and characteristics. Thus, current trends focus on the development of human- and decision-maker-centered DSS. This paper aims in providing a multilevel stepwise procedure for the modeling of decision-makers in order to enable a more effective decision support. The decision-maker modeling procedure is based on findings from literature research and results from research projects performed in cooperation with industry partners. The procedure serves as a guideline for generating diverse decision-maker models for different applications and for integrating human cognitive thinking procedures within the design and functionality of decision support methodologies and systems. The procedure represents an important design element of the human-centered decision support methodology currently being developed at the Institute of Product Development of the Technische Universität München (Germany).
A Conceptual Construct for Employing Decision Support Systems in Road Tunnels Emergency Management
Authors: Rokou Elena  , Chatzoglou Konstantinos  , Kirytopoulos Konstantinos  , Tatsiopoulos Ilias P.
Published: February 2025

Most of the times in emergency situations, individuals need to act decisively within tight time schedules having no or limited information. In this paper we propose the exploration of a real time data Decision Support System (DSS) for emergency management. The proposed conceptual construct is based on the idea that a bridge should be built between the road operator that has the knowledge on how to react in emergency situations and as many drivers located in the tunnel, who hold pieces of information about the situation, sometimes relevant, other times not, and need guidance on how to react. Furthermore, providing individualised guidelines to different groups of people based on their location, health conditions and even ability to help others can be of paramount importance. Therefore, the proposed DSS, named SOSTunnel, is composed of two parts: a) a GPS or smart phone embedded application that acts as the user interface for drivers and the data collector for the operator and b) a DSS located in the operator's control centre that gathers, classifies and filters data while suggesting possible evacuation plans per drivers group. Apart from the proposed DSS, limitations of such systems in road tunnels are highlighted and guidelines for experimentation before their use in practice are offered.
The Experience of Developing a Fuzzy-Logic Based Negotiation System for E-Commerce
Authors: Balachandran Bala M.
Published: February 2025

In this paper we present our experience in developing a fuzzy-logic based negotiation system capable of achieving a mutually beneficial deal for the seller and buyer in uncertain situations. Fuzzy utility in our system allows users who are often unsure about their utility function to express their preferences in fuzzy terms such as low, middle and high. The system evaluates offers based on this fuzzy utility and feeds utility score along with remaining negotiation time to a fuzzy inference system to compute conceding rate of its next counter offer. The experimental results have shown that that the system concedes less when negotiated item matches its preferences less and concedes more when the negotiated item matches its preferences closely and when negotiation is ending. Our concluding remarks and future research are presented.
Coordinated Team Learning and Difference Rewards for Distributed Intrusion Response
Authors: Malialis Kleanthis  , Devlin Sam  , Kudenko Daniel
Published: February 2025

Distributed denial of service attacks constitute a rapidly evolving threat in the current Internet. Multiagent Router Throttling is a novel approach to respond to such attacks. We demonstrate that our approach can significantly scale-up using hierarchical communication and coordinated team learning. Furthermore, we incorporate a form of reward shaping called difference rewards and show that the scalability of our system is significantly improved in experiments involving over 100 reinforcement learning agents. We also demonstrate that difference rewards constitute an ideal online learning mechanism for network intrusion response. We compare our proposed approach against a popular state-of-the-art router throttling technique from the network security literature, and we show that our proposed approach significantly outperforms it. We note that our approach can be useful in other related multiagent domains.
Trustworthy Advice
Authors: Osman Nardine  , Gutierrez Patricia  , Sierra Carles
Published: February 2025

We propose a novel trust model for assessing the trustworthiness of advice. We say an advice is composed of a plan to execute and a goal to be fulfilled. The expectation of an advice's outcome is calculated by assessing the probabilities of commiting to and executing the plan, and the probability of the executed plan fulfiling the intended goal. The probabilities are learned from similar past experiences.
‘Being a Manifold’ as the Topological Primitive of Mereotopology
Authors: Borgo Stefano
Published: February 2025

Mereotopology is an approach to modeling space that allows to formalize human spatial intuition without reference to points. A predominant formal theory in this area is the Regions Connection Calculus (RCC) introduced in 1992. RCC has an original fault: it relies on the notion of (Euclidean) point for the interpretation of its primitive, i.e., the connection relation C. In this paper we show that in the natural structures for mereotopology, RCC is a theory of manifolds in disguise. It follows that RCC can be reformulated without reference to any notion of point both at the syntactic and at the semantic levels.
Communicating with Unknown Teammates
Authors: Barrett Samuel  , Agmon Noa  , Hazon Noam  , Kraus Sarit  , Stone Peter
Published: February 2025

Past research has investigated a number of methods for coordinating teams of agents, but with the growing number of sources of agents, it is likely that agents will encounter teammates that do not share their coordination methods. Therefore, it is desirable for agents to adapt to these teammates, forming an effective ad hoc team. Past ad hoc teamwork research has focused on cases where the agents do not directly communicate. However when teammates do communicate, it can provide a valuable channel for coordination. Therefore, this paper tackles the problem of communication in ad hoc teams, introducing a minimal version of the multiagent, multiarmed bandit problem with limited communication between the agents. The theoretical results in this paper prove that this problem setting can be solved in polynomial time when the agent knows the set of possible teammates. Furthermore, the empirical results show that an agent can cooperate with a variety of teammates following unknown behaviors even when its models of these teammates are imperfect.
The Persistence of Most Probable Explanations in Bayesian Networks
Authors: Pastink Arnoud  , van der Gaag Linda C.
Published: February 2025

Monitoring applications of Bayesian networks require computing a sequence of most probable explanations for the observations from a monitored entity at consecutive time steps. Such applications rapidly become impracticable, especially when computations are performed in real time. In this paper, we argue that a sequence of explanations can often be feasibly computed if consecutive time steps share large numbers of observed features. We show more specifically that we can conclude persistence of an explanation at an early stage of propagation. We present an algorithm that exploits this result to forestall unnecessary re-computation of explanations.
From Formal Requirements on Technical Systems to Complete Designs – A Holistic Approach
Authors: Böttcher Björn  , Moriz Natalia  , Niggemann Oliver
Published: February 2025

The design processes of todays more and more complex automation systems require computer-based support to maintain their manageability. As a base for that, the authors introduce a holistic design approach for these systems. Requirements on the system to be designed are represented by an extended feature model which serves as consistent requirements model during the entire design process. A grammar-based synthesis applies formalised expert knowledge to generate solutions to these requirements. The paper's main contribution is to combine formalisms from overlapping areas of artificial intelligence and software engineering to obtain a holistic design process for industrial automation systems.
Multi-objective learning of accurate and comprehensible classifiers – A case study
Authors: Piltaver Rok  , Luštrek Mitja  , Gams Matjaž
Published: February 2025

Accuracy and comprehensibility are two important classifier properties, however they are typically conflicting. Research in the past years has shown that Pareto-based multi-objective approach for solving this problem is preferred to the traditional single-objective approach. Multi-objective learning can be represented as search that starts either from an accurate classifier and modifies it in order to produce more comprehensible classifiers (e.g. extracting rules from ANNs) or the other way around: starts from a comprehensible classifier and modifies it to produce more accurate classifiers. This paper presents a case study of applying a recent algorithm for multi-objective learning of hybrid trees MOLHC in human activity recognition domain. Advantages of MOLHC for the user and limitations of the algorithm are discussed on a number of datasets from the UCI repository.
The Margin of Victory in Schulze, Cup, and Copeland Elections: Complexity of the Regular and Exact Variants
Authors: Reisch Yannick  , Rothe Jörg  , Schend Lena
Published: February 2025

The margin of victory is a critical measure for the robustness of voting systems in terms of changing election outcomes due to errors in the ballots or fraud in using electronic voting machines. Applications include risk-limiting post-election audits so as to restore the trust in the correctness of election outcomes.
Workshop on Critical Success Factors for Open Data – From Policy to Participation and Innovation
Authors: Susha Iryna  , Zuiderwijk Anneke  , Janssen Marijn  , Parycek Peter  , Loukis Euripidis
Published: February 2025

Open data offer tremendous potential for participation and innovation. Yet open data providers and users are puzzled about what to do and what are key issues they should concentrate on. In this workshop, we provide insight in and discuss critical success factors for open data participation and innovation from various perspectives. The workshop contains various interactive elements, including a discussion about a research agenda for open data innovation and a brainstorming session about critical success factors for open data provision and use.
Synchronous Gravitational Search Algorithm vs Asynchronous Gravitational Search Algorithm: A Statistical Analysis
Authors: Ab. Aziz Nor Azlina  , Ibrahim Zuwairie  , Nawawi Sophan Wahyudi  , Sudin Shahdan  , Mubin Marizan  , Ab. Aziz Kamarulzaman
Published: February 2025

Gravitational search algorithm (GSA) is a new member of swarm intelligence algorithms. It stems from Newtonian law of gravity and motion. The performance of synchronous GSA (S-GSA) and asynchronous GSA (A-GSA) is studied here using statistical analysis. The agents in S-GSA are updated synchronously, where the whole population is updated after each member's performance is evaluated. On the other hand, an agent in A-GSA is updated immediately after its performance evaluation. Hence an agent in A-GSA is updated without the need to synchronize with the entire population. Asynchronous update is more attractive from the perspective of parallelization. The results show that both implementations have similar performance.
Towards an integrated theory of causal scenarios and evidential arguments
Authors: Bex Floris
Published: February 2025

The process of proof is one of inference to the best explanation, in which alternative scenarios are supported and attacked by arguments. This combination of scenarios and arguments was previously presented as a formal hybrid theory. In this paper, the aim is to further integrate scenarios and arguments by defining a notion of attack between alternative explanations. Thus, scenarios and arguments can be incorporated in the same dialectical framework.
Resilience as a Disposition
Authors: Daniel Desiree
Published: February 2025

In domains concerned with global change, achieving resilience in socio-ecological systems is highly desired; however making this concept operational in reality has been a struggle partly due to the conflation of the term by these domains. Although resilience is vastly researched in sustainability science, climate change and disaster management for some reason this concept is not dealt with from an ontological perspective. In this paper, the foundation for a formal theory of resilience is laid out. I propose that the common view of resilience as ‘the ability of a system to cope with a disturbance’ is a disposition that is realized through processes since resilience cannot exist without its bearer i.e. a system and can only be discerned over a period of time when a potential disturbance is identified. To this end, the constructs of the Basic Formal Ontology are applied to ground the proposed categorization of resilience. In so doing, I adhere to the notion of semantic reference frames by employing a top-level ontology to anchor the notion of resilience.
Automated Web Services Network Construction Using Schema Matching Technique
Authors: Omelkova Svetlana  , Küngas Peep
Published: February 2025

In this paper we describe an experiment on using message-level schema matching for Web services network construction. The aim of this study is to empirically determine a similarity threshold for schema matching which will leverage the same Web service message annotation quality as domain experts will through manual efforts. Since we use message annotations for construction of Web services networks, determining the proper threshold is essential in construction of a dataset for large-scale Web services network studies in realistic settings.
An Authentication Scheme for Ubiquitous RFID Systems
Authors: Yeh Kuo-Hui  , Chen YuShan  , Wang Fan-Wei
Published: February 2025

In order to fulfill system security and computation limitation of low-cost RF tags at the same time, the research of the lightweight RFID authentication has promptly become one of the hottest topics in recent years. Recently, Morshed et al. proposed an authentication scheme, called SUAP3, to achieve the security and efficiency under ubiquitous RFID-based systems. Later, Safkhani et al. and Wang et al. had demonstrated that SUAP3 is insecure against full-disclosure attack and tag traceability attack. However, these attacks are based on powerful assumptions, and the feasibilities of the two attacks are thus a little doubtful. In this paper, we present a real passive tag-tracking attack without any specific assumptions. An adversary can exploit a series of challenge-response procedures to derive the secrets maintained at the tag. With the cryptanalysis proposed by us, the insecurity of SUAP3 is truly proved. In addition, we present a novel and robust ubiquitous authentication scheme for RFID based application systems.
Towards a Legal Recommender System
Authors: Winkels Radboud  , Boer Alexander  , Vredebregt Bart  , van Someren Alexander
Published: February 2025

In this paper we present the results of ongoing research aimed at a legal recommender system where users of a legislative portal receive suggestions of other relevant sources of law, given a focus document. We describe how we make references in case law to legislation explicit and machine readable, and how we use this information to adapt the suggestions of other relevant sources of law. We also describe an experiment in categorizing the references in case law, both by human experts and unsupervised machine learning. Results are tested in a prototype for Immigration Law.
Managing Motivation at the Workplace through Negotiation
Authors: Carneiro Davide  , Novais Paulo  , Zeleznikow John  , Andrade Francisco  , Neves José
Published: February 2025

Recent research shows that our performance and satisfaction at work depends more on motivational factors than the number of hours or the intensity of the work. In this paper we propose a framework aimed at managing motivation to improve workplace indicators. The key idea is to allow team managers and workers to negotiate over the conditions of the tasks so as to find the best motivation for the worker within the constraints of what the organization may offer.
Sociable Robots: From Reliability to Cooperative-Mindedness
Authors: Schmid Hans Bernhard
Published: February 2025

Robots are entering service-based areas of our societies, which raises new issues. The question seems to be whether robots can graduate from reliable aids to truly cooperative-minded partners. This paper aims at addressing this question by making a couple of relevant conceptual distinctions while suggesting a certain view concerning the kind or nature of the relation in question.
Investigating Human-Robot Interaction through an Interactive Art Installation
Authors: Nielsen Morten  , Nielsen Vibeke H.  , Rasmussen Rie  , Skjødt Axelgaard Trine  , Kłusak Agata
Published: February 2025

In this paper we describe a Human-Robot Interaction (HRI) field experiment, situated in a public space and based on observations of participants interacting with an art installation. The art installation is developed from research in bio-inspired robotics, anthropomorphism, behaviors in nature, and biology. The article explains an interdisciplinary study in HRI using methodologies from art, Human Computer Interaction (HCI), and scientific research. Research observations are conducted using methods as cognitive walkthrough, bodystorming, interviews, and video recordings. The experiment is realised in order to investigate how new technology can be implemented in nature without acting as an obstructive element to the ecological system and the inhabitants of the environment.