bluuebunny/crossref_metadata_2025 huggingface dataset:
A Novel Approach of Applying the Differential Evolution to Spatial Discrete Data
Authors: Uher Vojtěch  , Gajdoš Petr  , Radecký Michal  , Snášel Václav
Published: February 2025

The Differential Evolution (DE) is a powerful bio-inspired algorithm searching optimal solutions. The actual DE modifications can handle the real, integer and discrete valued problems. The values of the discrete-valued variables represent the integer indices addressing the discrete samples in the ordered array. The optimization in unordered samples leads to a random search. This paper proposes a novel modification dealing with d-dimensional discrete vertices. A vertex hashing is used to strengthen the local properties of a dataset and to improve the spatial convergence of the evolution.
Semi-Supervised Learning on an Augmented Graph with Class Labels
Authors: Li Nan  , Latecki Longin Jan
Published: February 2025

In this paper, we propose a novel graph-based method for semi-supervised learning. Our method runs a diffusion-based affinity learning algorithm on an augmented graph consisting of not only the nodes of labeled and unlabeled data but also artificial nodes representing class labels. The learned affinities between unlabeled data and class labels are used for classification. Our method achieves superior results on many standard data sets.
Enhancing Sketch-Based Image Retrieval via Deep Discriminative Representation
Authors: Huang Fei  , Cheng Yong  , Jin Cheng  , Zhang Yuejie  , Zhang Tao
Published: February 2025

In this paper we aim to employ deep learning to enhance SBIR via deep discriminative representation. Our main contributions focus on: 1) The deep discriminative representation is established to bridge both the visual appearance gap and the semantic gap between sketches and images; 2) The deep learning pattern is applied to our SBIR model through training on our transformed sketch-like images to overcome the rarity of training sketches. Our experiments on a large number of public sketch and image data have obtained very positive results.
GDL-III: A Proposal to Extend the Game Description Language to General Epistemic Games
Authors: Thielscher Michael
Published: February 2025

We propose an extension of the standard game description language for general game playing to include epistemic games, which are characterised by rules that depend on the knowledge of players. A single additional keyword suffices to define GDL-III, a general description language for games with imperfect information and introspection. We present an Answer Set Program for automatically reasoning about GDL-III games. Our extended language along with a suitable basic reasoning system can also be used to formalise and solve general epistemic puzzles.
Fault Manifestability Verification for Discrete Event Systems
Authors: Ye Lina  , Dague Philippe  , Longuet Delphine  , Brandán Briones Laura  , Madalinski Agnes
Published: February 2025

Fault diagnosis is a crucial and challenging task in the automatic control of complex systems, whose efficiency depends on the diagnosability property of a system. Diagnosability describes the system ability to determine whether a given fault has effectively occurred based on the observations. However, this is a very strong property that requires generally high number of sensors to be satisfied. Consequently, it is not rare that developing a diagnosable system is too expensive. To solve this problem, in this paper, we first define a new system property called manifestability that represents the weakest requirement on faults and observations for having a chance to identify on line fault occurrences and can be verified at design stage. Then, we propose an algorithm with PSPACE complexity to automatically verify it.
Rapid Adaptation of Air Combat Behaviour
Authors: Toubman Armon  , Roessingh Jan Joris  , Spronck Pieter  , Plaat Aske  , van den Herik Jaap
Published: February 2025

Adaptive behaviour for computer generated forces enriches training simulations with appropriate challenge levels. For adequate insight into the range of possible behaviour, the adaptation has to take place in a rapid fashion. Ideally, each new behaviour model should remain readable by (and thereby under the control of) human experts. Although various attempts have been made at creating adaptive behaviour, current solutions require large numbers of simulations. Moreover, usability by end users has been of subordinate interest, as is compliance with doctrine and ethics. In this work, we present a machine learning method that enables fast behaviour adaptation, while keeping the behaviour models in a human-readable format. We demonstrate the effectiveness of the proposed method in beyond-visual-range air combat simulations.
Even Angels Need the Rules: AI, Roboethics, and the Law
Authors: Pagallo Ugo
Published: February 2025

Over the past years, scholars have increasingly debated over the reasons why we should, or should not, deploy specimens of AI technology, such as robots, on the battlefields, in the market, or at our homes. Amongst the moral theories that discuss what is right, or what is wrong, about a robot's behaviour, virtue ethics, rather than utilitarianism and deontologism, offers a fruitful approach to the debate. The context sensitivity and bottom-up methodology of virtue ethics fits like hand to glove with the unpredictability of robotic behaviour, for it involves a trial-and-error learning of what makes the behaviour of that robot good, or bad. However, even advocates of virtue ethics admit the limits of their approach: All in all, the more societies become complex, the less shared virtues are effective, the more we need rules on rights and duties. By reversing the Kantian idea that a nation of devils can establish a state of good citizens, if they “have understanding,” we can say that even a nation of angels would need the law in order to further their coordination and collaboration. Accordingly, the aim of this paper is not only to show that a set of perfect moral agents, namely a bunch of angelic robots, need rules. Also, no single moral theory can instruct us as to how to legally bind our artificial agents through AI research and robotic programming.
Synthesizing Argumentation Frameworks from Examples
Authors: Niskanen Andreas  , Wallner Johannes P.  , Järvisalo Matti
Published: February 2025

Argumentation is nowadays a core topic in AI research. Understanding computational and representational aspects of abstract argumentation frameworks (AFs) is a central topic in the study of argumentation. The study of realizability of AFs aims at understanding the expressive power of AFs under different semantics. We propose and study the AF synthesis problem as a natural extension of realizability, addressing some of the shortcomings arising from the relatively stringent definition of realizability. Specifically, AF synthesis seeks to construct, or synthesize, AFs that are semantically closest to the knowledge at hand even when no AFs exactly representing the knowledge exist. Going beyond defining the AF synthesis problem, we (i) prove NP-completeness of AF synthesis under several semantics, (ii) study basic properties of the problem in relation to realizability, (iii) develop algorithmic solutions to AF synthesis using constrained optimization, (iv) empirically evaluate our algorithms on different forms of AF synthesis instances, as well as (v) discuss variants and generalization of AF synthesis.
Budgeted Multi–Armed Bandit in Continuous Action Space
Authors: Trovò Francesco  , Paladino Stefano  , Restelli Marcello  , Gatti Nicola
Published: February 2025

Multi–Armed Bandits (MABs) have been widely considered in the last decade to model settings in which an agent wants to learn the action providing the highest expected reward among a fixed set of available actions during the operational life of a system. Classical techniques provide solutions that minimize the regret due to learning in settings where selecting an arm has no cost. Though, in many real world applications the learner has to pay some cost for pulling each arm and the learning process is constrained by a fixed budget B. This problem is addressed in the literature as the Budgeted MAB (BMAB). In this paper, for the first time, we study the problem of Budgeted Continuous–Armed Bandit (BCAB), where the set of the possible actions consists in a continuous set (e.g., a range of prices) and the learner suffers from a random reward and cost at each round. We provide a novel algorithm, named B–Zoom, which suffers a regret of, where d is the Zooming dimension of the problem. Finally, we provide an empirical analysis showing that, despite a lower average performance, the proposed approach is more robust to adverse settings as compared to existing algorithms designed for BMAB.
Solving Dynamic Controllability Problem of Multi-Agent Plans with Uncertainty Using Mixed Integer Linear Programming
Authors: Casanova Guillaume  , Pralet Cédric  , Lesire Charles  , Vidal Thierry
Published: February 2025

Executing multi-agent missions requires managing the uncertainty about uncontrollable events. When communications are intermittent, it additionally requires for each agent to act only based on its local view of the problem, that is independently of events which are controlled or observed by the other agents. In this paper, we propose a new framework for dealing with such contexts, with a focus on mission plans involving temporal constraints. This framework, called Multi-agent Simple Temporal Network with Uncertainty (MaSTNU), is a combination between Multi-agent Simple Temporal Network (MaSTN) and Simple Temporal Network with Uncertainty (STNU). We define the dynamic controllability property for MaSTNU, and a method for computing offline valid execution strategies which are then dispatched between agents. This method is based on a mixed-integer linear programming formulation and can also be used to optimize criteria such as the temporal flexibility of multi-agent plans.
Source Data and Bathymetry Editor in Tsunami Modeling Environment
Authors: Hayashi Kensaku  , Vazhenin Alexander  , Marchuk Andrey
Published: February 2025

The important part of the tsunami science is focused on studying the considerable influence of natural geographical objects, like islands and coast bathymetry, on the tsunami waves. Currently, such investigations are mostly implementing by physical modeling allowing obtaining good results on impacting submarine barriers on tsunami wave propagation but actually very expensive. We are designing a system allowing numerical computer simulations for crucial coastal areas supporting so-called hybrid bathymetry that combines natural and artificial underwater objects as well as tools allowing the user to manipulate with them. The paper describes the main features the original Bathymetry and Tsunami Source Data Editor that allows tuning/editing bathymetric and tsunami source data by including/removing artificial barriers as well as specifying their placement, shapes and sizes.
An Industrial Survey and Assessment on Free Mobile Testing Tools
Authors: Leung Hareton K.N.  , Lui Kim Man
Published: February 2025

Mobile app usage continues to increase and hence more and more small and medium sized enterprises (SME) start their m-commerce. Unfortunately, the importance of mobile software testing has not been equally addressed. Our initial survey showed that mobile testing has not been included in almost all the introductory mobile courses and many SMEs heavily reply on manual testing on physical devices. Practitioners with different backgrounds are learning mobile application development and many of them may not receive any software engineering training. Thus, it will be practical for them to learn software testing tools when studying software testing theory. This paper surveys 42 companies and analyzes the industrial practice on mobile application testing. Then it categorizes and assesses twenty free/open source mobile software testing tools. Eight tools were selected and we conducted workshops on them for SME developers. At the end of the workshops, we interviewed the participants to evaluate the usefulness of the testing tools in their workplaces. We concluded that for industrial SME developers, Sikuli (Advanced GUI testing) and JMeter (server performance testing) would be more helpful than AT&T ARO (power consumption tool) and Lookback (Usability Testing tool). The work contributes to those SME companies and developers which are interested in free mobile testing tools
Spectral Techniques in Argumentation Framework Analysis
Authors: Butterworth James  , Dunne Paul E.
Published: February 2025

Spectral analysis – the study of the properties of the eigenvalues associated with some matrix derived from an underlying graph form – has proven to offer valuable insights in many domains where graph-theoretic models are prevalent. Abstract argumentation frameworks (afs) are, of course, one such model and have provided a unifying basis for defining semantic properties related to concepts of “argument acceptability”. In this paper we consider the possible benefits of adopting spectral methods as a tool for analysing argumentation structures, presenting a preliminary empirical study of semantics in afs and properties of the associated spectrum.
On the Acceptability Semantics of Argumentation Frameworks with Recursive Attack and Support
Authors: Cohen Andrea  , Gottifredi Sebastian  , García Alejandro J.  , Simari Guillermo R.
Published: February 2025

The Attack-Support Argumentation Framework (ASAF) is an abstract argumentation framework that provides a unified setting for representing attack and support for arguments, as well as attack and support for the attack and support relations at any level. Currently, the extensions of the ASAF are obtained by translating it into a Dung's Argumentation Framework (AF). In this work we provide the ASAF with the ability of determining its extensions without requiring such a translation. We follow an extension-based approach for characterizing the acceptability semantics directly on the ASAF, considering the complete, preferred, stable and grounded semantics. Finally, we show that the proposed characterization satisfies different results from Dung's argumentation theory.
Argumentation as Information Input: A Position Paper
Authors: Gabbay Dov  , Gabbay Michael
Published: February 2025

Given a network (S,R) , with R ⊂ S2, we view the nodes of S as containing information and view xRy as x transmitting information to y. We argue that such networks provide a more general account of attack and defense as well as being able to simulate the traditional Dung approach.
A Qualitative Color Harmony Theory
Authors: Museros Lledó  , Sanz Ismael  , Falomir Zoe  , Gonzalez-Abril Luis
Published: February 2025

This paper presents a new qualitative color harmony (QCharm) theory based on a Qualitative Color Descriptor (QCD) together with the definition of 5 basic color combination operations. QCharm can construct color palettes (or color schemes) of compatible colors. Moreover, in this paper, palettes of 3 colors are constructed and their harmonious quality is predicted using a model defined using data from large datasets such as ColorLovershttp://www.colorlovers.com/
An Interdisciplinary Approach to Improving Cognitive Human-Robot Interaction – A Novel Emotion-Based Model
Authors: Fosch-Villaronga Eduard  , Barco Alex  , Özcan Beste  , Shukla Jainendra
Published: February 2025

Socially Assistive Robotics (SAR) aims to provide robot-assisted therapy, for physical as well as cognitive rehabilitation. The paper analyzes two distinct use cases of cognitive rehabilitation therapies, one among involving children with Traumatic Brain Injury (TBI); and another one; second among involving individuals with Intellectual Disability (ID), and raises concerns regarding emotional adaptation, personalization, design, and ELS issues of human-robot interaction in such cases. The paper's aim is to provide some guidance on how social robots should be designed in order to accommodate emotions in HRI as well as to respect the rights of the persons with disabilities. We argue that it is critically important to address the concerns highlighted in order to empower robots with empathetic behavior and to deliver effective cognitive rehabilitation therapies.
Can Artificial Systems Have Genuine Emotions? The Enactive Approach to Affectivity and Artificial Systems
Authors: Klein Maike
Published: February 2025

In order to investigate whether robots, or, more generally, artificial systems, can have emotions, I will shed a light on Giovanna Colombetti's enactive theory of emotions because the idea of an enactive approach, especially the role it grants biology, seems to be conflicting with the idea of emotional artificial systems. I will take a look at some points of contact between the enactive approach to emotions and its interest regarding artificial systems, first and foremost the enactive notions of autonomy and “sense-making”. In what way may these concepts be realized in artificial systems as well? This will entail the question of what living systems are and what distinguishes from an artificial system, in general but especially regarding to their emotions. Having analyzed these concepts, is there any case left in which we can speak of genuine emotions of an artificial system? If not, what kind of emotions may artificial systems then have?
Metadata as Support for Data Provenance
Authors: Kramer Frank  , Thalheim Bernhard
Published: February 2025

Provenance tackles problems as: provides information to a user about his data that are given to him or passed by him; informs a user in which way a foreign user has used his data; allows rollback mechanisms on wrong data; observes the currentness of data for closed contracts and creates a history of data for a user. We show that with a sophisticated metadata support these problems can be solved.
Ad-Hoc Synthesis of Composite Content Ontology Design Patterns
Authors: Lomov Pavel  , Shishaev Maxim
Published: February 2025

Using of Ontology Design Patterns (ODPs) become useful for development and reengineering ontologies. ODPs represent encodings of best practices supporting ontology construction by facilitating reuse of proven solution principles. In this paper, we focus on Content ODPs (CDPs), which represent small ontology fragments that encode general use cases (e.g. participation in event, role playing, parts of object.). Content CDPs are used as building blocks during ontology development. In such cases they could be specializes, extends, integrates by user to obtain new composite CDP which would allow to provide more expressive representation of domain concept in the ontology being developed. But it may demands additional skills from the user. Therefore in this paper the automate selection of a CDP combination and subsequent synthesis of new composite CDP is considered.
Time Series Analysis and Forecasting Technique for Converting Industrial Waste Management: Case Study of a Tape Converting Production in Thailand
Authors: Lertpocasombut Krittiya  , Sriploy Supawut
Published: February 2025

The aim of this research study is to explore the forecasting technique to fit to the existing waste data of a tape converting production factory using a time series method. Optimal type of time series techniques to minimise the error between actual and forecasted data was chosen after comparing three types of time series techniques. The data analysis, based on the accuracy of their outputs, resulted in the “Double Exponential Smoothing” being the preferable choice since the error was less than that for other techniques. The projected forecasted amounts were 13.09, 11.08, 11.77 and 10.25 (Unit of measurement is 10,000 kilograms) for January, February, March and April 2015. After benchmarking error percentages (MAPE) that against similar techniques and problems from other references,the error in this study (18%) was less than the benchmarking source (21% [9] and 33% [10] respectively). Therefore this technique is more accurate than the benchmarking techniques by 17% and 83% respectively. After rechecking the actual data with forecast time series data, the average MAPE was found to be around 15% which is still lower that the errors quoted in other reference papers.
Hazardous Chemicals Accident Prediction Based on Accident State Vector Using Multimodal Data
Authors: Liu Kang-Wei  , Wan Jian-Hua  , Han Zhong-Zhi
Published: February 2025

Hazardous chemicals industry is a high-risk industry, all kinds of explosions, fires, leaks and poisoning incidents is occurred occasio1nally. So it is particularly important to forecast for hazardous chemical accidents and develop appropriate safety measures. In view of the analysis and summary of previous methods, an improved Hazardous Chemicals Accident Prediction method is proposed based on accident state vector in this paper. It defines the accident state vector using Multi-modal Data such as authoritative data, accident report, webpage, image, video, speech, etc. The Multi-modal Data is collected by web crawler which is built by open-source tools. The web crawler is an Internet bot which systematically browses the known hazardous chemical accident website, for the purpose of collecting Multi-modal accident data. As mentioned before, the Multi-modal Data is Multi format. In order to define the accident state vector easily, we divide the Multi-modal data into three dimensions based on the principle of accident causes. Respectively is the human factors, physical state factors, environmental factors. According to the geometrical distribution characteristics of support vector, it can be selected from the incremental samples that the sample of support vectors most likely to become forming a boundary vector set by adopting vector distance pre-extraction method, on which support vector training and accident prediction model build. It ensures the validity of predictive models due to various factors of the cause of the accident are fully considered by the accident state vector and advantages of support vector machines in high-dimensional, multi-factor, large sample datasets machine learning are exhibited. Sample experimental verification from the mastered accident of hazardous chemicals has showed that hazardous chemical accident prediction method proposed in this paper can effectively accumulate accident history information, possess higher learning speed and be positive significance for the safe development of hazardous chemicals industry.
Research on the Application-Driven Architecture in Internet of Things
Authors: Fang Wei-Dong  , He Wei  , Chen Wei  , Shan Lian-Hai  , Ma Feng-Ying
Published: February 2025

As we all know, the Internet of Things (IoT) has a promising future. However, the Internet of Things is an onward research and development (R&D) work as a system or technology. Currently, there is no strict definition of IoT system by the International Telecommunications Union (ITU), so most of the architecture design for IoT comes from the requirements of specific applications. In this paper, we focus on the architecture for IoT, especially the application-driven architecture. Firstly, we identify and summarize the applications in IoT. Then we give a more holistic overview of IoT's application-driven architecture, which are divided into three categories based on Radio Frequency Identification (RFID), Wireless Sensor Network (WSN) and Machine-to-Machine (M2M) respectively. Along the way, we analyze the pros and cons of proposed architecture in each category qualitatively. In addition, we also analyze the techniques and methods in these categories, and point out the open research issues and directions in this field.
Automatic Assignment of Section Structure to Texts of Dutch Court Judgments
Authors: Trompper Maarten  , Winkels Radboud
Published: February 2025

A growing number of Dutch court judgments is openly distributed on Rechtspraak.nl. Currently, many documents are not marked up or marked up only very sparsely, hampering our ability to process these documents automatically. In this paper, we explore the problem of automatic assignment of a section structure to these texts. We experiment with Linear-Chain Conditional Random Fields to label text elements with their roles in the document (text, title or numbering). In this subtask, we report F1scores of around 0.91 for tagging section titles, and around 1.0 for the other types. Given a list of labels, we experiment with Probabilistic Context-Free Grammars to generate a parse tree which represents the section hierarchy of a document. In this task, we report an F1score of 0.92.
New Zealand Legislation Network
Authors: Sakhaee Neda  , Wilson Mark C.  , Zakeri Golbon
Published: February 2025

This paper concerns the recently introduced concept of Legislation Networks, with an application focus on the New Zealand legislation network. Legislation networks have some novel features which make them an excellent test case for new network science tools. We develop several such networks, compute relevant centrality measures, and apply community detection algorithms. We study the relationship between the legislation network measures and legal/political factors.
Mind the Gap: Security Analysis of Metro Platform Screen Door System
Authors: Zhou Luying  , Guo Huaqun  , Li Dong  , Wong Jun Wen  , Zhou Jianying
Published: February 2025

A smooth operation of the Platform Screen Door (PSD) system is critical to the Metro system, and any disturbance to it may disrupt the train's normal operation. The paper presents the security analysis of a Metro Supervisory Control and Data Acquisition (SCADA) system, specifically the cyber security vulnerabilities in its PSD system. The PSD system includes control subsystem and signaling subsystem, and its operation can be controlled from the moving train and the station as well. The security features of communication protocols that are employed in the SCADA system and PSD system operation mechanisms are discussed in this paper. The weak security features render the PSD vulnerable to cyber attacks. Countermeasures, from both technical and human aspects, to protect the PSD system are studied. An experiment is conducted on a testbed of simulating Metro supervisory control system to test the system vulnerabilities. The results demonstrate that the PSD control system could be compromised by an attacker who gains physical access to the control network and launches forged message or replay message attacks. A firewall cyber security countermeasure is evaluated to show that it can prevent some of the attacks but has limitations due to its rule-based mechanism. Thus, it is necessary to mind the gap for the security of metro PSD system.
Attribute-Based Secure Messaging in the Public Cloud
Authors: Poh Zhi Yuan  , Cui Hui  , Deng Robert H.  , Li Yingjiu
Published: February 2025

Messaging systems operating within the public cloud are gaining popularity. To protect message confidentiality from the public cloud including the public messaging servers, we propose to encrypt messages in messaging systems using Attribute-Based Encryption (ABE). ABE is an one-to-many public key encryption system in which data are encrypted with access policies and only users with attributes that satisfy the access policies can decrypt the ciphertexts, and hence is considered as a promising solution for realizing expressive and fine-grained access control of encrypted data in public servers. Our proposed system, called Attribute-Based Secure Messaging System with Outsourced Decryption (ABSM-OD), has three key features: enabling expressive and fine-grained access control of encrypted messages by users, supporting outsourced decryption to the cloud while without compromising confidentiality of decrypted messages, and allowing server-aided revocation to provide effective and instant user revocations.
Mobile Application Development Process for Health Control in Pregnancy
Authors: Godoy Andrea  , Barrientos Eduardo  , Rodríguez Anastacio
Published: February 2025

In the current context (year: 2017) there are many medical advances applied to women pregnancy state, however the lack of information at the female young sector and the shortage of mobile tools which provide a satisfactory control of the health of the fetus, they lead to prenatal care problems or to the born ofa baby. This is a proposal generated to be applied at the North Region of the state of Guanajuato, Mexico a zone affected by chronic-degenerative health problems is developed by a team of teachers to control better pregnancy, preventing suffering for the mother and the gestating.
Control of a Synchronous Magnet Generator Using Sliding Modes for Wind Turbine Application
Authors: Ortega Meza Daniel Gerardo  , Morfín Garduño Onofre Amador  , Castellanos García Manuel Iván
Published: February 2025

On this paper a robust decentralized control system at cascade scheme applied to medium capacity wind systems is proposed. On the first closed-loop subsystem, the PMSG-side converter controller is designed for controlling the angular rotor velocity of a permanent magnet synchronous generator to maximize the wind energy capture. On the second closed-loop subsystem, the grid-side converter controller is designed for regulating the link DC-bus voltage located between two converters, and the reactive power to set a unity power factor. The two proposed controllers are based on a combination of the block control linearization technique and SOSM-super-twisting algorithm. Finally, simulation results of the wind systems are reported to validate the performance of the proposed controller having an oscillatory wind speed as input.
Big Data Analysis for Output of Chinese Research Papers Based on SCI
Authors: Yang Li  , Xu Fang
Published: February 2025

The paper is carried out based on the problem that is not solved by the current Knowledge Inventory systemically. It means science and technology output of Chinese researchers and their international influence of the academy output. To study the scientific issue feasibly, choose the data base from 2007 to 2016 of the most important scientific and technological literature retrieval system of scientific statistics and scientific evaluation with international recognition, SCI as data source and collect the paper data of Chinese researchers which is inspected by SCI. Made use of information to explore the general situation of the science and technology output of Chinese researchers from quantitative to qualitative scientific practice based on the data analysis. Some feasible suggestions are provided to the strategic allocation of scientific talents.
PCA Based Improved Face Recognition System
Authors: Dharejo Fayaz Ali  , Jatoi Munsif Ali  , Hao Zongbo  , Tunio Majid Ali
Published: February 2025

Due to the rapid evolution of modern image processing and pattern recognition techniques, there exists a variety of biometric techniques like fingerprints, iris (retina) scans, and speech recognition etc. nowadays. However, among them, face recognition is still the most common technique which is in use due to the fact that it is easy to install and has less complexity. It has been a prominent research field for security applications such as video surveillance, fraud detection, person tracking and crowd recognition. This research work discusses and implements the facial recognition by using MATLAB environment in real time. In this work, the face recognition system is implemented using Principal Component Analysis (PCA) and Eigenface approach by dealing with large dataset. A methodology is proposed to produce more accuracy and efficiency by removing the unrelated space from the image. Also, a graphical Interface System (GUI) is developed in order to make our system clearer and to measure the training time. Furthermore, large databases (ORL and private Database named face-100) are tested through PCA and Eigenfaces approach and then the person identification is carried out. The system successfully recognized the human faces and worked better in different conditions like illumination and blur conditions of the face. The rate of male and female accuracy is also calculated.
The Relationship Between Product Modularization and Open Innovation Based on Sports Industry
Authors: Zhang Min  , Wen Xun
Published: February 2025

This article defines incremental innovation in modular organization as the independent innovation within the module and the synergetic innovation among modules. Intensity of knowledge interaction increases along with the transformation of independent innovation into synergetic innovation, while empirical data validate inverted U-shaped relationship between intensity of knowledge interaction and modular knowledge autonomy. The process of open innovation in modularization complies with the path of spiral and amplified evolution. Basing on case studies of Chinese sport industry, we analyzed the actual operation of open innovation model in sport modularization. Standards of Communication and operating system were both influenced by independent and synergetic open innovation.
A Conversational Chatbot Based on Kowledge-Graphs for Factoid Medical Questions
Authors: Minutolo Aniello  , Esposito Massimo  , De Pietro Giuseppe
Published: February 2025

In the last years, the interest about enhancing the interface usability of applications has strongly increased, focusing, in particular, on chatbots, i.e. conversational agent that interacts with users, turn by turn using natural language. However, building chatbots for answering to questions over structured medical knowledge bases is a very thorny task and is still considered an open research challenge. In order to face this issue, this paper proposes a knowledge-based conversational chatbot for medical question answering, aimed at supporting: i) the formulation of factoid questions over medical knowledge bases; ii) the generation of more precise and contextualized dialog responses by analyzing the relations between entities in knowledge bases; iii) the detection of ambiguous user intents, with respect to the current dialog state and the suggestion of some interaction hints aimed at clarifying and/or confirming their meaning. A relevant characteristic of this system is represented by the usage of Knowledge Graphs to formally represent textual inputs given by the user as well as templates of questions and, contextually, efficiently navigate and use the domain knowledge of interest to provide an answer. The proposed chatbot has been implemented as a desktop application named “Medical Assistant” able to conversate with users interested to diagnose and identify the possible diseases causing a symptom, and find the most suitable treatment for a medical problem. It has been proficiently tested with respect to some factoid questions, showing its capability to help user reach the desired information also in the case of initial missing information.
Perfect COKB Model and Reasoning Methods for the Design of Intelligent Problem Solvers
Authors: Do Nhon V.  , Mai Thanh T.
Published: February 2025

Knowledge Representation and Reasoning is at the heart of the great challenge of Artificial Intelligence, especially intelligent problem solvers (IPSs). Applications such as the intelligent problem solver in plane geometry and linear algebra have knowledge bases containing a complicated system of concepts, relations, operators, functions, and rules. Therefore, designing of the knowledge bases and the inference engines of those systems requires knowledge representations in the form of ontologies. Ontology COKB (Computational Object Knowledge Base) is suitable for these requirements. COKB model and reasoning algorithms for solving problems on it are essential parts of the ontology. Previous results of COKB model together with reasoning methods have not been complete, and it is needed to develop the knowledge representation model and reasoning algorithms. The perfect COKB model helps to represent knowledge domains and problems more adequately; reasoning techniques with new methods of reasoning and heuristics produce inference engines that solve more kinds of problems, more efficiently and more naturally. They have been used to design and to implement IPSs in plane geometry, analytic geometry, discrete mathematics and linear algebra.
Towards Taming Variability Models in the Wild
Authors: Fernandez-Amoros David  , Heradio Ruben  , Cerrada Carlos  , Herrera-Viedma Enrique  , Cobo Manuel J.
Published: February 2025

Software Product Lines (SPLs) are families of related software systems that provide different combinations of features. Extensive research and application attest to the significant economical and technological benefits of employing SPL practices. Variability models represent the feature combinations and the properties of the software products of SPLs. Kconfig configuration files from open source projects have been proposed as large and realistic case studies for research on analysis of variability models. However, despite the extensive work on this subject, the seemingly direct approach of translating Kconfig to Binary Decision Diagrams (BDDs) — a representation that has shown significant advantages for complex analysis of variability models — has not been explored. To address this gap, we propose a simple translation scheme which we evaluate with five case studies. Our encouraging results indicate the feasibility of our approach and open up avenues for further research.
The Cooperative Defense Strategy by Multi-USVs
Authors: Liu Yuan  , Wu Xing  , Guo Yike  , Xie Shaorong  , Pu Huayan  , Peng Yan
Published: February 2025

Based on the multi-agents system control theory and technology, this paper presents the cooperative defense process of multiple unmanned surface vehicles (USVs) operating in complicated sea environment, and explains the quantification of the battle effectiveness, cooperative strategy, task allocation and finally describes in detail the cooperative strategies on random graph. Then we point out the problems in the current cooperative defense process and the future development direction. The cooperative defense research of USVs in the sea environment has a great significance to the effective promotion of social and military efficiency.
Modelling Spatial and Temporal Context to Support Activity Recognition
Authors: Guesgen Hans W.  , Marsland Stephen
Published: February 2025

With the dawn of mobile computing and the Internet of Things, context-aware computing has gained increasing attention. The idea is to not only consider explicit inputs when computing an output, but also to consider contextual factors such as location, time, and environmental data. Context-aware computing is not restricted to mobile computing and the Internet of Things, but is also beneficial in other areas. The area we focus on in this chapter is activity recognition in smart environments.
Behavioral Biometrics and Ambient Intelligence: New Opportunities for Context-Aware Applications
Authors: Carneiro Davide  , Novais Paulo
Published: February 2025

Ambient Intelligence has always been associated with the promise of exciting new applications, aware of the users' needs and state, and proactive towards their goals. However, the acquisition of the necessary information for supporting such high-level learning and decision-making processes is not always straightforward. In this chapter we describe a multi-faceted smart environment for the acquisition of relevant contextual information about its users. This information, acquired transparently through the technological devices in the environment, supports the building of high-level knowledge about the users, including a quantification of aspects such as performance, attention, mental fatigue and stress. The environment described is particularly suited for milieus such as workplaces and classrooms, in which this kind of information may be very important for the effective management of human resources, with advantages for organizations and individuals alike.
Solving MaxSAT with Natural Deduction
Authors: Casas-Roma Joan  , Huertas Antonia  , Manyà Felip
Published: February 2025

In this paper, we rethink the way Natural Deduction systems are usually used in logic, and adapt them in order to solve the MaxSAT problem. By adapting some existing rules and defining some new ones, the Natural Deduction method can be used to provide an elegant and straightforward solution to maximum satisfiability problems of multisets of Boolean and many-valued clauses.
Prediction of Glucose Level Conditions from Sequential Data
Authors: Mordvanyuk Natalia  , Torrent-Fontbona Ferran  , López Beatriz
Published: February 2025

In type 1 diabetes management, mobile health applications are becoming a cornerstone to empower people to self-manage their disease. There are many applications addressed to calculate insulin doses based on the current information (e.g. carbohydrates intake) and a few of them are accompanied by modules able to supervise postprandial conditions and recommend corrective actions if the user falls in an abnormal state (i.e. hyperglycaemia or hypoglycaemia). On the other hand, mobile apps favour the gathering of historical data from which machine learning techniques can be used to predict if user conditions will worsen.
Author-Centered Argumentation Analysis for Twitter Discussions
Authors: Alsinet Teresa  , Argelich Josep  , Béjar Ramón
Published: February 2025

In a recent work we have developed an analysis system based on valued abstract argumentation to model and reason about the accepted and rejected tweets of a Twitter discussion. Given a Twitter discussion, the system builds an argument graph where each node denotes a tweet and each edge denotes a criticism relationship between a pair of tweets of the discussion. In the social network Twitter, a tweet always refers to previous tweets in the discussion, so the obtained underlying argument graph is acyclic. In this work we introduce and investigate a natural extension of the system, referred as author-centered analysis system, in which tweets within a discussion are grouped by authors, such that tweets of a same author represent his/her opinion in the discussion with a single node in the graph, and criticism relationships denote controversies between the opinions of Twitter users in the discussion. With this new approach, the interactions between authors can give rise to circular criticism relationships and thus the underlying argument graph can contain cycles. The output of the author-centered analysis system is the set of authors such that their opinions are consistent and are globally accepted within a Twitter discussion. The system can be of special relevance for assessing Twitter discussions in fields where identifying groups of authors whose opinions are globally compatible or consistent, but at the same time are widely accepted, is of particular interest.
Transforming and prolonging design lifespans: design education cases for sustainability
Authors: Doğan Ç.
Published: February 2025

This paper aims to present an approach focusing on design education for sustainability through providing two exemplary cases from third-year industrial design projects. The main themes explored in these projects involve personalization via design transformation, adaption and upgrading during design, use and post-use phases. The first project developed and facilitated at Carleton University, the School of Industrial Design mainly addresses the key theme of transformation of LED lighting from indoors to outdoors during use phase for the adaptation of design solutions for diverse tasks (e.g. mood to therapy lighting, task to outdoor lighting etc.). Second educational project developed and facilitated at METU Department of Industrial Design, aims to develop design solutions for open kitchen platform enabling transformation and upgrading during design, use and post-use phases. For each case, users are considered as active participants in the design process. The first project was undertaken individually whereas for the second one, the design students worked in teams due to the complexity of the project scope and objectives. This paper outlines the main intentions, phases and outcomes of these educational projects through providing insights and suggestions from design educators' perspective. The illustrative student projects demonstrate some of the key principles and considerations being aimed throughout the phases of the projects. This paper also provides some future directions that can be implemented in further researches and educational projects.
Playing for time: seven practice-led workshop tools for making design decisions to extend the life of fashion textile materials and products
Authors: Earley R.  , Goldsworthy K.
Published: February 2025

Since 2011, the authors have been developing creative and playful sustainable design workshop tools to understand, develop and share knowledge and ideas with other designers. These tools originated through practice-led research methods, involving prototyping, to explore and consolidate research theories. By translating design strategies into both realised artefacts and tools for engaging others through design, the authors have continuously transformed practice and theory in the field. More recently the theory has become focused on the starting point of ‘circular models for design’, in particular, designing for lifecycle speeds. This paper discusses some of the tools used for exploring ‘product longevity’ and ‘circular’, resulting in further insights for future design, including the current understanding of ‘longevity’ as both a product and a material consideration, with two seemingly opposed strategies. The authors research groups' primary methodological approach is through designing and making textile/fashion artifacts to generate new theory; in order to share this approach and support others outside of the group to use making as a key research method they often design and facilitate workshops and create tools, which are then shared via the project website. In this paper tools developed specifically to design to extend the life of a fashion textile product are discussed and the creative outcomes generated are presented. The playful tools generated playful ideas and by reflecting via field notes on these industry workshop outputs the authors here offer a set of tools to support designing sustainable and circular textiles for long life.
Sustainability Cards: design for longevity
Authors: Hasling K.M.  , Ræbild U.
Published: February 2025

Product longevity is considered widely as a relevant strategic approach, amongst many, within the field of sustainability. Yet, how to design for increased product lifetime may not be so obvious for practitioners. The complexity of the surrounding issues can constitute a barrier for designers and companies, in terms of adopting and implementing the approach in the design process. This paper explores whether, and possibly how, the ‘design card’ format (i.e. method card or alike), can be a way to support dissemination, application and communication of knowledge related to the notion of product longevity for designers and other stakeholders in the design process. The paper is based on a developmental project carried out in the Autumn 2017, within a larger research and collaboration project between raw fur manufacturer Kopenhagen Fur and Design School Kolding investigating sustainability perspectives. The paper describes the development of a deck of sustainability cards aiming for product longevity and presents the final deck. Furthermore, the paper contributes with insights on how designers may apply design cards in the design process and how this practice can further sustainable considerations and strategies in terms of product longevity. As the paper builds on a single case study and is situated within a single discipline (fashion and apparel), the outcome should be considered as tentative indications of future potential.
Throwaway culture as a status symbol with fashion in India
Authors: Kumar V.
Published: February 2025

India is a country with people of different cultural background and community. Clothing is treated differently in India. Owing to the significant social meaning held by textiles, clothing used to be rarely discarded. Instead, it used to be frequently recycled for both the domestic and global markets. But with influx of global brands with affordable, machine-made, synthetic clothing and an excess disposable income, buying in excess has become accessible to all.