bluuebunny/crossref_metadata_2025 huggingface dataset:
User Interface of Multimedia Delivery Platform for the Elderly
Authors: Limdumrongnukoon Naovarat  , Mongkolnam Pornchai  , Visutarrom Thammarsat  , Chan Jonathan H.
Published: February 2025

The world is facing the phenomena of rapidly growing population of the aged, in which there are more elderly people than children. The elderly people tend to live longer and hence have to live alone and feel lonely in large part due to healthcare advancement globally and structural social changes. This causes a great deal of concerns for loneliness, social isolation, and depression among the elderly. The elderly people also have mobility and vision-reducing eye problems. Therefore, it is important for the family to provide the proper health and social care environment to assist the elderly's daily living in order to enable them to live quality lives. This study aims to design and develop an interactive (bidirectional) multimedia delivery system to deliver multimedia contents among elderly people, family members, relatives and friends, and healthcare providers. The elderly can chat and send multimedia contents from a tablet PC via smart TV to family members and friends. Multimedia contents and the chat history are displayed on the elderly's smart TVs. The elderly can control the smart TV multimedia delivery application with ease by using our developed tablet PC touchpad features. It is intended to enhance the quality of lives of the elderly people by allowing them to stay connected with the family members, relatives and friends, in hope to replace the TV remote control, which is deemed not to be so user-friendly.
Partial Face Detection and Significant Feature Parts on Face
Authors: Kao Min-Chi  , Li Tzuu-Hseng S.
Published: February 2025

Face detection is an important technique and has been employed in many applications. Many literatures have been proposed to extract the features of face. However, in many cases, the human face may be obscured by other people or objects which cause the face cannot be detected. This paper focuses on how to do partial face detection and discusses what the significant feature parts on face are. We employed SURF algorithm to compute the reliable feature parts on face so that the partial face can be detected. In order to evaluate the degree of importance for each feature part, this paper introduces CV value to appraise each feature part of face. Finally, the experimental result demonstrates the effectiveness of the proposed algorithm.
Practical Applications of Secure Multiparty Computation
Authors: Talviste Riivo
Published: February 2025

As secure multiparty computation technology becomes more mature, we see more and more practical applications where computation moves from a lab setting to an actual deployment where each computation node is hosted by a different party. In this chapter, we present some of the practical SMC applications that have worked on real data. A few of these have been developed by Cybernetica AS, while others have been found from public sources. All scientific prototypes or simulations that work on generated or public data have been left out of this chapter. For each chosen SMC application, we give a brief overview and refer the reader to the corresponding published sources for more details.
Fusepool P3: A Linked Data Platform for Open Government Data
Authors: Selmi Luigi  , Neuroni Alessia
Published: February 2025

Many public administrations have been publishing data sets as open data for the last few years through portals based on CKAN or other platforms. Applications have been developed using, most of the time, one single data set as developers, data journalists and small businesses cannot afford the cost of re-using and integrating different data sets. This is due to many factors as the different formats used for the data, lack of documentation, different metadata and lack of public, trustworthy registries for entities of interest that could ease the task of connecting information provided by different authors about them. The Linked Data principles offer the guidelines to solve all these issues by leveraging the Semantic Web standards for describing resources on the Web. Moreover the Linked Data Platform specification, a recent W3C Recommendation, provides a realization of the guidelines defining some basic interactions between a client and a server to manage resources using the HTTP protocol. The purpose of this article is to present the Fusepool P3 platform that extends the LDP specification to support services which transform raw data sets into RDF format and enrich them.
Policy Compass: FCM-based Policy Impact Evaluation using Public Open Data
Authors: Choi Youngseok  , Lee Habin  , Sivarajah Uthayasankar
Published: February 2025

This paper presents how Fuzzy Cognitive Map (FCM) technique can be applied by a policy maker to support the policy impact evaluation using the example of Policy Compass, an EU research project. The practical usage example on interest rate policy shows the potential of FCMs as a policy impact modelling tool. Through the provision of a more intuitive and easier means of using open data based on FCM techniques, the Policy Compass project can play a critical role for both policy maker and lay public to evaluate the policy impact and prepare for future policy making.
Towards a Business Model for SMS-Based Government Services
Authors: Lanza Beatriz B. B.  , Gil-Garcia J. Ramon  , Gimenez Fernando A. P.
Published: February 2025

Mobile government could be conceptualized as the use of diverse mobile technologies to provide information and services to citizens, businesses, and other stakeholders. Governments around the world, particularly in developing countries are finding mobile strategies to be useful ways to reach to their citizens, including disadvantaged groups. In fact, individuals are increasingly using mobile phones for accessing information and this trend is becoming stronger with the improvement of long-range technologies and the high penetration of mobile devices in developing countries. However, their use to deliver government services to citizens remains generally low. Since smart devices are not as widely spread as more traditional mobile phones, it is necessary to think about commonly available and low cost technologies such as Short Message Service (SMS) as a useful alternative for governments around the world. Therefore, based on some foundational concepts from configuration theory, this paper proposes a conceptual business model for SMS-based government services. We think that this model not only contributes to theory, but could also provide guidance to public managers for them to decide when and how to implement SMS-based government services.
The Smart Cities and Smart Government Research-Practice (SCSGRP) Consortium
Authors: Pardo Theresa A.  , Luna-Reyes Luis  , Scholl Hans Jochen
Published: February 2025

This workshop is a working meeting of the Smart Cities and Smart Government Research-Practice Consortium. The main goal of the workshop is to continue conversations started since 2012 among teams of researchers interested in doing collaborative work by sharing protocols and data with the purpose of advancing knowledge in the area of smart cities and smart government. The workshop will welcome current and future members of the Consortium and build on SCSGRP Consortium meeting held at dg.o 2015.
On the Use of User-generated Content in Critiquing Recommendation
Authors: Contreras David  , Salamó Maria
Published: February 2025

User-generated content is any form of content that is created by users of an online system or service, often made by available via social media websites. Usually, on eCommerce websites, user-generated content is created by means of reviews, opinions or ratings about products. We consider that a wealth of collaborative information (i.e., user-generated content) about the products can now be used in an critiquing recommendation process to improve its outcome. In this paper we describe and analyze two approaches for adding user-generated content to a critiquing-based recommender. Our analysis includes two recommendation scenarios and the results indicate that efficiency is improved in both of them when user-generated content is added to the recommender.
Task Assignment and Trajectory Planning in Dynamic environments for Multiple Vehicles
Authors: David Jennifer  , Philippsen Roland
Published: February 2025

We consider the problem of finding collision-free trajectories for a fleet of automated guided vehicles (AGVs) working in ship ports and freight terminals. Our solution computes collision-free trajectories for a fleet of AGVs to pick up one or more containers and transport it to a given goal without colliding with other AGVs and obstacles. We propose an integrated framework for solving the goal assignment and trajectory planning problem minimizing the maximum cost over all vehicle trajectories using the classical Hungarian algorithm. To deal with the dynamics in the environment, we refine our final trajectories with CHOMP (Covariant Hamiltonian optimization for motion planning) in order to trade off between path smoothness and dynamic obstacle avoidance.
Predicting Adverse Drug Events with Confidence
Authors: Löfström Tuve  , Zhao Jing  , Linusson Henrik  , Jansson Karl
Published: February 2025

This study introduces the conformal prediction framework to the task of predicting the presence of adverse drug events in electronic health records with an associated measure of statistically valid confidence. The imbalanced nature of the problem was addressed both by evaluating different machine learning algorithms, and by comparing different types of conformal predictors. A novel solution was also evaluated, where different underlying models, each model optimized towards one particular class, were combined into a single conformal predictor. This novel solution proved to be superior to previously existing approaches.
Business Process Management for Legal Domains: Supporting Execution and Management of Preliminary Injunctions
Authors: Capuzzimati Federico  , Violato Andrea  , Baldoni Matteo  , Boella Guido
Published: February 2025

Business Process Management Systems (BPMS) are widely recognized as fundamental component of the IT infrastructure supporting middle-large organization, thanks to their capacity of providing easy-to-read models of how the organization works, and to the capability of enacting these business processes, supporting and monitoring their execution. In this work we present results collected during a feasibility study, that aims to apply BPM concepts to a legal domain: decision and enforcement of preliminary injunctions.
Mapping Recitals to Normative Provisions in EU Legislation to Assist Legal Interpretation
Authors: Humphreys Llio  , Santos Cristiana  , di Caro Luigi  , Boella Guido  , van der Torre Leon  , Robaldo Livio
Published: February 2025

This paper looks at the use of recitals in the interpretation of EU legislation, and mechanisms for connecting them to normative provisions. The purposive approach to the interpretation of EU legislation taken by the European Court of Justice makes frequent references to recitals as helping to establish the purpose of normative provisions. Our research uses a cosine similarity based approach to link articles with relevant provisions to help legal professionals and lay end-users interpret the law. Such support can be used in legal knowledge-based systems.
Telephone-based social engineering attacks: An experiment testing the success and time decay of an intervention
Authors: Bullée Jan-Willem  , Montoya Lorena  , Junger Marianne  , Hartel Pieter H.
Published: February 2025

The objective of this study is to evaluate the effectiveness of an information campaign to counter a social engineering attack via the telephone. Four different offenders phoned 48 employees and made them believe that their PC was distributing spam emails. Targets were told that this situation could be solved by downloading and executing software from a website (i.e. an untrusted one). A total of 46.15 % of employees not exposed to the intervention followed the instructions of the offender. This was significantly different to those exposed to an intervention 1 week prior to the attack (9.1 %); however there was no effect for those exposed to an intervention 2 weeks prior to the attack (54.6 %). This research suggests that scam awareness-raising campaigns reduce vulnerability only in the short term.
Cyber and Physical Access Control in Legacy System Using Passwords
Authors: Xu Jia  , Zhou Jianying  , Lu Liming
Published: February 2025

Passwords—secret combinations of symbols—play an important role in physical world security (e.g. watchword to prevent unauthorized entry into military forbidden area) from ancient times. With emergence and advance of digital computers and computer network, passwords are also widely adopted in cyber world security protection. In most applications, password protection stands on the frontier of cyber/physical security defense. Compromise of passwords might render the whole system insecure, and make thereafter sophisticated cryptography solution ineffective. However, secure management of a large number of random passwords is a great challenge to human brains. We propose a visual cryptography technique, which allows users to store and manage ciphertexts of randomly chosen passwords in mobile phone and decrypt them manually on demand. The stored passwords remain confidential, even if the mobile phone is infected by spyware (Assume the spyware can capture phone screen, and monitor phone CPU and RAM). We also analyze the security and feasibility of proposed method. Leveraging on this technique, we give a simple access control system based on passwords, which provides a low cost alternative solution for legacy system besides smart card based solution.
Finding the Region Dependent Merchandises in Non-Defective Reverse Logistics: A Novel Association Rules based Approach
Authors: Shao Ming-Shun  , Zheng Hong-Zhen  , Chu Dian-Hui
Published: February 2025

Finding the relationship between hot merchandises and region is a new challenge in non-defective reverse logistics (NRL). In this paper, it was found that the similarity of merchandise categories purchased by users among the same region is higher than the users in different regions by analyzing the data from an Alibaba e-commerce platform. Then, an Association Rules based approach (ARA) was proposed to find the merchandises dependent region and create the points of NRL. Experimental results show that this method could decrease the distance between the user and the e-store, reduce the transportation cost in NRL and shorten the time of the logistic cycle. In addition, the quality of the reverse logistics (RL) services will be improved and customers' satisfaction will be indirectly enhanced.
Adaptive Step Length Method of Dead Reckoning
Authors: Fei Cheng-Yu  , Su Zhong  , Li Qing
Published: February 2025

Aimed at the demand of positioning in complicated environments such as indoor and built-up areas, the method of autonomous navigation positioning and orientation based on an adaptive step length model was proposed in this paper. Using an accelerometer placed on the human waist, stride was recognized and the relationship between the step length, stride factor, and walking speed was established. The stride factor was calibrated by least squares, which adaptively adjusted the calculation of the step length in situations of different walking speeds and manners, thus enhancing the accuracy of the step length. Additionally, information of the magnetometers, gyroscopes, and other sensors were fused to estimate heading with an extended Kalman filter. Personal dead reckoning was achieved based on the results of the moving distance and heading. The experimental results showed that positioning errors of the method were less than 3.5% of the travel distance, and it was able to meet the positioning requirements of pedestrians.
Suggesting Sub-Topics of Issued Queries by Using Concept Structure
Authors: Hagiwara Kazuki  , Hatano Kenji
Published: February 2025

In this paper, we propose a method for suggesting sub-topics of an issued queries by using the conceptual structure of WordNet. In existing search engines, sub-topics are created on the basis of the input histories of search engine users. Therefore, often-used pairs of key- and sub-topics can be issued; otherwise it is difficult for unaccustomed users to input both key- and sub-topics. We believe that the proposed method can help the users to issue appropriate search queries conveying their own information needs because sub-topics are general subsidiary information of a key-topic and are automatically suggested as the context of a key-topic irrespective of the input histories. To evaluate the proposed method, we conducted a usability test of the created search queries using a crowdsourcing site and compared the usability of the proposed method with that of the existing search engines.
Understanding Predication in Conceptual Spaces
Authors: Masolo Claudio  , Porello Daniele
Published: February 2025

We argue that a cognitive semantics has to take into account the possibly partial information that a cognitive agent has of the world. After discussing Gärdenfors's view of objects in conceptual spaces, we offer a number of viable treatments of partiality of information and we formalize them by means of alternative predicative logics. Our analysis shows that understanding the nature of simple predicative sentences is crucial for a cognitive semantics.
Knowing Whether Spatio-Temporal Analysis Procedures Are Applicable to Datasets
Authors: Scheider Simon  , Tomko Martin
Published: February 2025

How can data analysts identify spatio-temporal datasets that are suitable for their task? Answering this question is not only dependent on the aim of the analysis and the semantic contents of the data, but also on knowing whether the required data combinations and transformations, spatio-temporal analysis methods, charts and map visualizations are meaningfully applicable to the data. Operators need to assess whether they can meaningfully apply analytical operations to data to derive the information required. Answering this question in a general and computationally executable way is a crucial step on our way towards supporting data analysts and their research practice in e-Science. We propose an ontology design pattern for spatio-temporal information that enables to reason about the applicability of a number of fundamental classes of analyses in relation to given data, i.e., whether data sets can be compared, transformed, combined, and whether summary statistics can be applied to them. We demonstrate this ontology implemented in OWL through a set of corresponding SPARQL queries applied to meta-data of datasets from the AURIN portal.
E-Government Implementation in Developing Countries: Enterprise Content Management in Rwanda
Authors: Bakunzibake Pierre  , Grönlund Åke  , Klein Gunnar O.
Published: February 2025

E-Government is now on the rise in developing countries. While developing countries can “leapfrog” technology generations, the necessary organizational change is another matter. In industrialized countries technical systems have been developed over long time in parallel with institutional development; developing countries hope to make that journey faster. Most of the e-Government implementation research focuses on developed countries. It is important to explore the relation between the literature and the findings in the context of developing countries as to come up with a gap to reduce. An interview study with 56 people in 10 government organizations involved in implementing a government-wide enterprise content management system was conducted to find out how critical success factors found in literature on implementation of information management systems relate to the situation in the Rwanda public sector to discover the step forward in Rwanda. We find a large gap between expectations and results due to a strong focus on the technical tool and little concerns about issues related to organizational change.
Evaluation for Improving eGovernment in Least Developed Countries
Authors: Mukamurenzi Solange
Published: February 2025

E-government evaluation is challenging. However, it is important to design evaluations that support development towards the grand though often distant goal of better government. Although developing countries now have the same technology with developed ones, they still need to “leapfrog” in terms of administrative maturity. This is difficult as it requires changes not only in processes but also policies and organizational culture. The objective of this research is to contribute to finding ways of using evaluation effectively to support e-government development as a whole, including not just technology but also organizational maturity for least developed countries. Design science research methodology is used to investigate the problems involved, propose and develop an artifact to solve at least parts of the problems, and to test and evaluate the artifacts effectiveness. This research will also help to increase awareness among the e-government practitioners in Rwanda on how to achieve the ambitious e-government's goals.
Open Statistical Data: Potential and Challenges
Authors: Tambouris Efthimios  , Janssen Marijn  , Kalampokis Evangelos  , Roberts Bill  , Hermans Paul  , Whyte Jamie  , Alcorn Trevor  , Tarabanis Konstantinos
Published: February 2025

Opening up data is a political priority worldwide. Linked open data is considered as the most mature technology for publishing and reusing open data. A large number of open data is numerical and actually concerns statistics. In the literature, statistical data have been heavily studied using the data cube model. Recently, ICT tools have emerged aiming to exploit linked open data technologies for providing advanced visualizations and analytics of open statistical data residing in geographically dispersed open data portals. The aim of this panel is to discuss the potential and challenges of open statistical data.
Mobile Government Readiness: Proposing a Multidimensional Framework and an Assessment Tool
Authors: Lanza Beatriz B.B.  , Gil-Garcia J. Ramon  , Costello Jim  , Werthmuller Derek
Published: February 2025

Public managers at all levels of government are increasingly facing a great diversity of technological changes, from the arrival and rapid adoption of social media to the emergence and growing popularity of mobile phones and related technologies. Many times, they need to make decisions regarding the implementation of mobile government without the necessary knowledge and tools. Based on a review of recent literature and a set of group and individual interviews, this paper proposes a preliminary multidimensional framework to assess an agency's readiness for mobile government. The variables included in the framework are categorized into three main dimensions: (1) Technical, (2) Organizational, and (3) Workforce Environments. The paper also shows how these dimensions have been integrated into the prototype of a tool called Mobile-Readiness Assessment, which public managers could use to better understand mobile technologies and help them ask the right questions and collect appropriate data before starting a mobile government project.
DARDIS: Distributed And Randomized DIspatching and Scheduling
Authors: Bridi Thomas  , Lombardi Michele  , Bartolini Andrea  , Benini Luca  , Milano Michela
Published: February 2025

Scheduling and dispatching are critical enabling technologies in supercomputing and grid computing. In these contexts, scalability is an issue: we have to allocate and schedule up to tens of thousands of tasks on tens of thousands of resources. This problem scale is out of reach for complete and centralized scheduling approaches.
On Inconsistency Measuring and Resolving
Authors: Jabbour Said
Published: February 2025

In dealing with the field of inconsistency, measuring and resolving conflicts are two interesting concepts allowing to make a better reasoning. In this paper, we address these two essential questions. Firstly, we propose a new framework for inconsistency handling based on independent sets of MUSes. In fact, we propose to rank the knowledge bases using a sequence of number that represents independent sets of MUSes. Such sequence is able to catch more finely the structure of MUSes. Moreover, an inconsistency measure is instantiated based on such sequence. Secondly, we address the question of inconsistency resolving through hitting set deletion. In this case we show the interesting points of our new approach which selects hitting sets covering minimum subset of MUSes. Indeed, a framework is defined for the computation of such hitting sets. Furthermore, a derived underlying decision problem is defined. A special case of such decision problem is known to be defined in the literature as SIM-UNSAT and its complexity is still open.
Person Re-Identification via Multiple Coarse-to-Fine Deep Metrics
Authors: Xiong Mingfu  , Chen Jun  , Wang Zheng  , Wang Zhongyuan  , Hu Ruimin  , Liang Chao  , Shi Daming
Published: February 2025

Person re-identification, aiming to identify images of the same person from various cameras views in different places, has attracted a lot of research interests in the field of artificial intelligence and multimedia. As one of its popular research directions, the metric learning method plays an important role for seeking a proper metric space to generate accurate feature comparison. However, the existing metric learning methods mainly aim to learn an optimal distance metric function through a single metric, making them difficult to consider multiple similar relationships between the samples. To solve this problem, this paper proposes a coarse-to-fine deep metric learning method equipped with multiple different Stacked Auto-Encoder (SAE) networks and classification networks. In the perspective of the human's visual mechanism, the multiple different levels of deep neural networks simulate the information processing of the brain's visual system, which employs different patterns to recognize the character of objects. In addition, a weighted assignment mechanism is presented to handle the different measure manners for final recognition accuracy. The experimental results conducted on two public datasets, i.e., VIPeR and CUHK have shown the prospective performance of the proposed method.
The Game of Reciprocation Habits
Authors: Polevoy Gleb  , de Weerdt Mathijs  , Jonker Catholijn
Published: February 2025

People often have reciprocal habits, almost automatically responding to others' actions. A robot who interacts with humans may also reciprocate, in order to come across natural and be predictable. We aim to facilitate decision support that advises on utility-efficient habits in these interactions. To this end, given a model for reciprocation behavior with parameters that represent habits, we define a game that describes what habit one should adopt to increase the utility of the process. This paper concentrates on two agents. The used model defines that an agent's action is a weighted combination of the other's previous actions (reacting) and either i) her innate kindness, or ii) her own previous action (inertia). In order to analyze what happens when everyone reciprocates rationally, we define a game where an agent may choose her habit, which is either her reciprocation attitude (i or ii), or both her reciprocation attitude and weight. We characterize the Nash equilibria of these games and consider their efficiency. We find that the less kind agents should adjust to the kinder agents to improve both their own utility as well as the social welfare. This constitutes advice on improving cooperation and explains real life phenomena in human interaction, such as the societal benefits from adopting the behavior of the kindest person, or becoming more polite as one grows up.
An Assessment Study of Features and Meta-Level Features in Twitter Sentiment Analysis
Authors: Carvalho Jonnathan  , Plastino Alexandre
Published: February 2025

Sentiment analysis is the task of determining the opinion expressed on subjective data, which may include microblog messages, such as tweets. This type of message has been considered the target of sentiment analysis in many recent studies, since they represent a rich source of opinionated texts. Thus, in order to determine the opinion expressed in tweets, different studies have employed distinct strategies, which mainly include supervised machine learning methods. For this purpose, different kinds of features have been evaluated. Despite that, none of the state-of-the-art studies has evaluated distinct categories of features, regarding their similar characteristics. In this context, this work presents a literature review of the most common feature representation in Twitter sentiment analysis. We propose to group features sharing similar aspects into specific categories. We also evaluate the relevance of these categories of features, including meta-level features, using a significant number of Twitter datasets. Furthermore, we apply important and well-known feature selection strategies in order to identify relevant subsets of features for each dataset. We show in the experimental evaluation that the results achieved in this study, using feature selection strategies, outperform the results reported in previous works for the most of the assessed datasets.
Complexity and Tractability Islands for Combinatorial Auctions on Discrete Intervals with Gaps
Authors: Döcker Janosch  , Dorn Britta  , Endriss Ulle  , Krüger Dominikus
Published: February 2025

Combinatorial auctions are mechanisms for allocating bundles of goods to agents who each have preferences over these goods. Finding an economically efficient allocation, the so-called winner determination problem, is computationally intractable in the general case, which is why it is important to identify special cases that are tractable but also sufficiently expressive for applications. We introduce a family of auction problems in which the goods on auction can be rearranged into a sequence, and each bid submitted concerns a bundle of goods corresponding to an interval on this sequence, possibly with multiple gaps of bounded length. We investigate the computational complexity of the winner determination problem for such auctions and explore the frontier between tractability and intractability in detail, identifying tractable, intractable, and fixed-parameter tractable cases.
xGame: A Novel Approach for Developing Accessible Mobile Games
Authors: Moanes Aly  , Ibrahim Ahmed H.  , Hosny Abdelrahman
Published: February 2025

In this paper, we introduce xGame – a game engine for mobile audio games. The xGame engine not only offers an open source framework for building screen reader friendly games, but also introduces a new approach for developers to design and develop audio games. Using the developed game engine, we built an Android application that serves as a hub for all games developed using the engine. xGame boosts the development of audio games, hence fills the gap between blinds and sighted.
Solving MDPs with Unknown Rewards Using Nondominated Vector-Valued Functions
Authors: Alizadeh Pegah  , Chevaleyre Yann  , Lévy François
Published: February 2025

This paper addresses vectorial form of Markov Decision Processes (MDPs) to solve MDPs with unknown rewards. Our method to find optimal strategies is based on reducing the computation to the determination of two separate polytopes. The first one is the set of admissible vector-valued functions and the second is the set of admissible weight vectors. Unknown weight vectors are discovered according to an agent with a set of preferences. Contrary to most existing algorithms for reward-uncertain MDPs, our approach does not require interactions with user during optimal policies generation. Instead, we use a variant of approximate value iteration on vectorial value MDPs based on classifying advantages, that allows us to approximate the set of non-dominated policies regardless of user preferences. Since any agent's optimal policy comes from this set, we propose an algorithm for discovering in this set an approximated optimal policy according to user priorities while narrowing interactively the weight polytope.
Argument Mining Using Argumentation Scheme Structures
Authors: Lawrence John  , Reed Chris
Published: February 2025

Argumentation schemes are patterns of human reasoning which have been detailed extensively in philosophy and psychology. In this paper we demonstrate that the structure of such schemes can provide rich information to the task of automatically identify complex argumentative structures in natural language text. By training a range of classifiers to identify the individual proposition types which occur in these schemes, it is possible not only to determine where a scheme is being used, but also the roles played by its component parts. Furthermore, this task can be performed on segmented natural language, with no prior knowledge of the text's argumentative structure.
Understanding Group Polarization with Bipolar Argumentation Frameworks
Authors: Proietti Carlo
Published: February 2025

Group polarization occurs when an initial attitude or belief of individuals becomes more radical after group discussion. Polarization often leads subgroups towards opposite directions. Since the 1960s this effect has been observed and repeatedly confirmed in lab experiments by social psychologists. Persuasive Arguments Theory (PAT) emerged as the most convincing explanation for this phenomenon. This paper is a first attempt to frame the PAT explanation more formally by means of Bipolar Argumentation Frameworks (BAFs). In particular, I show that polarization may emerge in a BAF by simple and rational belief updates by participants.
Rethinking the Rationality Postulates for Argumentation-Based Inference
Authors: Prakken Henry
Published: February 2025

Much research on structured argumentation aims to satisfy the rationality postulates of direct and indirect consistency and strict (deductive) closure. However, examples like the lottery paradox indicate that it is sometimes rational to accept sets of propositions that are indirectly inconsistent or not deductively closed. This paper proposes a variant of the ASPIC+ framework that violates indirect consistency and full strict closure but satisfies direct consistency and restricted forms of strict closure and indirect consistency.
Gorgias-B: Argumentation in Practice
Authors: Spanoudakis Nikolaos I.  , Kakas Antonis C.  , Moraitis Pavlos
Published: February 2025

Gorgias-B is a new tool that supports a methodology for the development of real life applications. It can be used by non-argumentation experts generating and testing automatically the target argumentation theory in Gorgias.
Argument Schemes for Reasoning About the Actions of Others
Authors: Atkinson Katie  , Bench-Capon Trevor
Published: February 2025

In practical reasoning, it is important to take into consideration what other agents will do, since this will often influence the effect of actions performed by the agent concerned. In previous treatments, the actions of others must either be assumed, or argued for using a similar form of practical reasoning. Such arguments, however, will also depend on assumptions about the beliefs, values and preferences of the other agents, and so are difficult to justify. In this paper we capture, in the form of argumentation schemes, reasoning about what others will do, which depends not on assuming particular actions, but through consideration of the expected utility (based on the promotion and demotion of values) of particular actions and alternatives. Such arguments depend only on the values and preferences of the agent concerned, and do not require assumptions about the beliefs, values and preferences of the other relevant agents. We illustrate the approach with a running example based on Prisoner's Dilemma.
Classification of Foods Using Spatial Pyramid Convolutional Neural Network
Authors: Heravi Elnaz J.  , Aghdam Hamed H.  , Puig Domenec
Published: February 2025

Controlling food intake is important to tackle obesity. This is achievable by developing apps to automatically classifying foods and estimating their calories. However, classification of foods is hard since it is highly deformable and variable. The key for solving this problem is to find an appropriate representation for foods. In this paper, we propose a Convolutional Neural Network for representing and classifying foods. Our ConvNet is different from common ConvNet architectures in the sense that it uses spatial pyramid pooling and it directly feeds the information from the middle layers to the fully connected layer. Our experiments show that while the best-performed hand-crafted feature classifies only 40.95% of the test samples, correctly, our ConvNet classifies them with 79.10% accuracy. In addition, it achieves 94% top-5 accuracy on the test set. Finally, we show that spatial pyramid pooling has a significant impact on the accuracy of our ConvNet.
Monitoring Atmospheric Moisture Using GPS Precipitable Water Vapor
Authors: Uang-aree Prawit  , Kingpaiboon Sununtha
Published: February 2025

This article is aimed at indicating correlation between climatic changes and atmospheric moisture and precipitation using GPS precipitable water vapor values (PWV) and meteorological data in Khon Kaen, Thailand. PWV, average temperature, and precipitation data from 2001 to 2014 were analyzed to determine the changes over the time period. The estimation showed the average, maximum and minimum values of PWV in Khon Kaen at 48.42, 69.88, and 11.23 mm, respectively, with the standard deviation of 13.42 mm. Additionally, there was an increasing trend of PWV changes following temperature changes which could be due to the warm atmospheric properties that can hold vapor better than dry atmosphere. Again, at high temperatures, water in the environment vaporizes more easily than at low temperatures. However, precipitation tends to decrease which could be due to topographical condition of Khon Kaen which is on a high plain surrounded by mountains. As a result, monsoon wind is not able to bring moisture into the area. Therefore, the slightly increasing moisture cannot be a major cause of precipitation similar to a storm.
Performance Degradation Analysis Method Using Satellite Telemetry Big Data
Authors: Zhou Feng  , Pi De-Chang  , Kang Xu  , Tian Hua-Dong
Published: February 2025

Satellites have features of high control integration, various working modes, and complex telemetry big data, which make it difficult to evaluate their performance degradation. In this paper, a novel data mining analysis method is proposed to analyze the satellite's telemetry big data, in which sample entropy is calculated to characterize states and the support vector data description is utilized to analyze the satellite performance degradation process. The experimental results show that our proposed method could generally describe the performance degradation process of satellites. Meanwhile, it also provides an important approach for the ground-station-monitor to analyze the performance of satellites.
Regularized Level Set for Inhomogeneity Segmentation
Authors: Liu Guo-Qi  , Li Hai-Feng
Published: February 2025

Active contour model based on level set method is a popular method for image segmentation. However, intensity inhomogeneity universally exists in images and it greatly influences image segmentation. Local binary fitting model (LBF) is a effective method to cope with inhomogeneous intensity. However, the energy function of LBF is non-convex and it costs much computational cost. Otherwise, LBF could not preserve the weak edges. The non-convexity always causes the contour suffer from local minimum, and the computational cost is large. In order to cope with these shortcomings, we introduce a regularized minimization for improved LBF model. In proposed model, the edge information is integrated into the energy functional. The energy functional of improved LBF model is convex, and the local minimum is avoid. Furthermore, some fast optimal method can be utilized. In this paper, the regularized method is utilized to make the contour converge to minimization. Experimental results confirm that proposed method attains a similar segmentation effect with the LBF but costs less computation times.
Toward a Fuzzy Minimum Cost Flow Problem for Damageable Items Transportation
Authors: Lu Si-Chao  , Wang Xi-Fu
Published: February 2025

In this paper, we have proposed a mathematical formulation of fuzzy minimum cost flow problem for damageable items transportation. For the imprecise model, capacity, cost, percentage of unit damage of each route have been considered as triangular fuzzy numbers. This problem has been solved by using the k-preference integration method, the area compensation method, and the signed distance method. Finally, to show the validity of the proposed model, a numerical example is provided and solved with Wolfram Mathematica 9.
Neural Reasoning for Legal Text Understanding
Authors: Adebayo Kolawole John  , Boella Guido  , Di Caro Luigi
Published: February 2025

We propose a domain specific Question Answering system. We deviate from approaching this problem as a Textual Entailment task. We implemented a Memory Network-based Question Answering system which test a Machine's understanding of legal text and identifies whether an answer to a question is correct or wrong, given some background knowledge. We also prepared a corpus of real USA MBE Bar exams for this task. We report our initial result and direction for future works.
Adaptive Methodology for Designing a Predictive Model of Cardiac Arrhythmia Symptoms Based on Cubic Neural Unit
Authors: Rodriguez Jorge Ricardo  , Bila Jiri  , Mizera-Pietraszko Jolanta  , Loya Orduño Ricardo Ezequiel  , Martinez Garcia Edgar  , Torres Córdoba Rafael
Published: February 2025

A cubic neural unit is a kind of a higher-order neural unit which can be used for prediction tasks among others, in the medical field. The example of the tasks includes monitoring cardiac behavior in real-time either for preemptive treatment, or for supporting a doctor to reach a more accurate diagnosis. We propose a predictive model which has been developed as an application in open source code with the aim to make it publicly accessible for research community and medical professionals and also to decrease the implementation cost. The proposed model uses sample-by-sample adaptation of the gradient descent method with error back-propagation. This paper presents an application of a cubic neural unit as a prediction mechanism for abnormal cardiac behavior, and it describes a new adaptive methodology based on application of a dynamic cubic neural unit for cardiac arrhythmia prediction. To validate the model, it has been tested on the data from the Massachusetts Institute of Technology-Beth Israel Hospital Cardiac Record Database. This paper is focused on premature ventricular contraction, atrial premature contraction and normal heartbeat records.
Relation Extraction for Circadian Rhythm Using the EEG
Authors: Ohta Eisaku  , Ogino Mikito  , Mitsukura Yasue
Published: February 2025

The evaluation of human emotions has been a multi-disciplinary area of research interest. Human emotion that feel good or bad, like or dislike, interest or not interest in the case when we have been done the same routine, has some kind of relation in rhythm with the days or seasons. Although there are several methods for such evaluation, such as subjective evaluation and behavioral taxonomy, direct evaluation from the human brain is more reliable. Electroencephalograph (EEG) signal analysis is particularly widely used because of its simplicity and convenience. In the present study, human emotional states were investigated using a newly developed electroencephalograph device with a single electrode. The developed device is lighter and cheaper than existing devices, although its feasibility is yet to be proven. In our former study, we can confirm that the proposed simple device is robust for noise and effective for getting five emotions (concentration, stress, like, sleepiness, interest degree). In this study we could find the circadian rhythm about woman stress level using the pre-proposed method. This is said that there is some relation the hormone. We can obtain the hormone change using the emotion obtained by the EEG. Moreover, we can find the stress level change for sanitary goods.
Improving the Performance of Diabetic Retinopathy Computer-Aided Diagnosis Systems Using an Ensemble of Texture Analysis Methods
Authors: Ragab Shimaa  , Abdel-Nasser Mohamed  , Moreno Antonio  , Puig Domenec
Published: February 2025

Diabetes is a major cause of blindness. Patients with history of diabetes are more prone to diabetic retinopathy (DR), which is the damage of the retina due to diabetes. Computer-aided diagnosis (CAD) systems have been used to detect DR early, which can reduce the occurrence of blindness. In this paper we analyze the performance of robust texture analysis methods in order to improve the performance of DR CAD systems. We used six texture analysis methods: the color autocorrelogram, local binary pattern, histogram of oriented gradients, local directional number, co-occurrence matrix features and Gabor filters. We also propose new combinations of different texture analysis methods to further improve the detection results. The proposed CAD system gave promising DR detection results and it is on par with related methods.
On the meaningfulness of data in product design for lifetime optimization
Authors: Fiore E.  , Bourgeois J.
Published: February 2025

Planned obsolescence is generally considered as a negative business strategy that induces replacement needs and affects attachment dynamics, as opposed to the goal of elongating product lifetime. At the present, however, an early replacement of long-lasting products is preferred in at least two cases which can be addressed during the design stage i.e. when the cost of maintaining is higher than product benefits and when there are environmental reasons to replace obsolete products. Furthermore, designing meaningful products that help the user in his/her daily activities, while addressing environmental issues, could help affecting attachment even in standardized and utilitarian products, such as home appliances. In this study, the holistic view and the management of the complexity of Systemic Design, combined with the use of the IoT technologies are proposed using the refrigerator as a case study. Acquiring information is considered as a tool for product innovation; the data is divided into (i) static data, related to the product and (ii) dynamic data, which derive from the context of use and interaction with users. The latter can be acquired by investigating the object's daily use and environment, with data acquisition through quantitative tools (sensors) and qualitative ones (feedback, questionnaires, interviews). IoT and data retrieval open a variety of possibilities in monitoring, accessing more precise knowledge of products and households useful for design purposes. This paper seeks to demonstrate how IoT can support and trigger a design transition towards more durable products and components, by focusing on sustainability and simplifying people's lives in daily actions.
What's hot what's not: the social construction of product obsolescence and its relevance for strategies to increase functionality
Authors: Jaeger-Erben M.  , Proske M.
Published: February 2025

“Is it ethical to deny our products what we wish ourselves: A long live?” is one of the major questions the German documentary “Do mixers go to heaven?”German: “Kommen Rührgeräte in den Himmel”, see also www.rg28.de.