bluuebunny/crossref_metadata_2025 huggingface dataset:
Product Behavior Definition for Element Generation in RFLP Structure
Authors: Horváth László  , Rudas Imre J.
Published: February 2025

Lifecycle management of product information is a recent paradigm. It is essential at knowledge driven integration of model generation processes in virtual engineering. In the centre of virtual engineering environment complex product model includes representations for lifecycle of product. Recently, generic product models apply built in active knowledge at self generation of their instances. Widespread development of multidisciplinary products generated demand for higher level abstraction than representation of physically existing objects in product model. For this purpose, product models in leading product lifecycle management (PLM) systems apply the requirements, functions, logical, and physical (RFLP) structure from systems engineering (SE). Elements on the functions and logical levels of RFLP structure have capability for product behavior representation. Finding solutions for the generation of RFLP structure elements is new challenging task for researchers. One of the latest researches at the Laboratory of Intelligent Engineering Systems (LIES) attempted answer the question that how design intent can be applied for RFLP structure element generation with special attention to behavior representation. Result of this research is the Multilevel Abstraction Based Self Adaptive Definition (MAAD) modeling method and model structure. MAAD is considered as a possible solution for higher level abstraction based generation of RFLP elements. In this way, organic integration of MAAD structure in knowledge driven PLM model structure is very important. Although MAAD structure is devoted as application oriented user extension to industrially applied PLM models, it may gain general application in product modeling. Future research is planned to ensure its implementation and practical application in representative PLM environment. In this paper, the MAAD method and model structure are introduced, explained, analyzed, and discussed.
Universally Verifiable Outsourcing and Application to Linear Programming
Authors: de Hoogh Sebastiaan  , Schoenmakers Berry  , Veeningen Meilof
Published: February 2025

In this chapter, we show how to guarantee correctness when applying multiparty computation in outsourcing scenarios. Specifically, we consider how to guarantee the correctness of the result when neither the parties supplying the input nor the parties performing the computation can be trusted. Generic techniques to achieve this are too slow to be of practical use. However, we show that it is possible to achieve practical performance for specific problems by exploiting the existence of certificates proving that a computation result is correct.
The Communities of Practice model for understanding digital engagement by hyperlocal elected representatives
Authors: Cruickshank Peter  , Ryan Bruce
Published: February 2025

There has been much research into citizens' engagement with their representatives. This paper offers an approach to understanding sustained take-up of internet technologies by these representatives in a (hyperlocal) democratic context using Community Councils in Scotland a case study. A Community of Practice model was developed and initial data collected to evaluate whether the model can be adapted for contexts where community boundaries are not clear. The focus is the community of users of technology: representatives as primary content creators as a necessary first stage before higher levels of engagement and participation are possible. The CoP model is found to have potential, even in a context of weak, dispersed and non-self-aware communities. The importance of understanding transitions and level of engagement is highlighted and another avenue for further research identified.
Cloud for eGov: the state of the art
Authors: De Angelis Francesco  , Gagliardi Roberto  , Polzonetti Alberto  , Re Barbara
Published: February 2025

Specifically, the paper provides a detailed analysis of the state of the art regarding technological, regulatory and interoperability aspects, devoting particular attention to those projects (and related experience) in the field of cloud and distributed computing. The paper's aim is to evaluate benefits and risks of the applicability of solutions that are already in place for the specified areas of interest. The key factors that determine relevant regulations, with particular emphasis on the European target, have been listed in the paper. Finally, the main Italian projects and the situation in some European countries have also been mentioned.
Towards a “Balanced” Historical Assessment of E-government Research
Authors: Carter Lemuria
Published: February 2025

This paper utilizes the Balanced Scorecard to provide a forward looking historical assessment of e-government research. The Balanced Scorecard provides an interesting and strategic lens through which to view e-government research. This paper identifies prominent e-government articles to highlight the financial, customer, internal process and organizational capacity elements of e-government research. This paper is not a traditional literature review; rather, it is a call for a more strategic approach to e-government research. As the field matures, the community should identify our mission and vision for e-government research and target our efforts accordingly.
Standardization of Service Descriptions, Process Models and Forms in Public Administrations: Results from a Survey in Germany
Authors: Scholta Hendrik  , Balta Dian  , Wolf Petra  , Becker Jörg  , Krcmar Helmut
Published: February 2025

Public administrations face a high need for service orientation, process efficiency as well as digitalization of documents. Thus, service descriptions, process models and forms are relevant artifacts of administrative procedures. Due to their interrelation, an integrated standardization regarding these information artifacts is promising. Our overall research objective is to analyze initiatives that aim at a standardization regarding service descriptions, process models and forms in German public administrations. This article provides a first step of ongoing research to reach this aim by investigating initiatives that deal with forms. It builds upon interviews with public managers of 15 IT standardization initiatives and describes those concerning criteria such as supported standardization features, targeted federal levels and number of application domains. Given the lack of standardization found in practice, this article raises the need for an instrument that enables the integrated standardization of service descriptions, process models and forms in public administrations.
A Framework for Evaluating Online Services and E-Participation Tools: UN Methodology Application to Russian Regions
Authors: Bershadskaya (Vidiasova) Lyudmila  , Chugunov Andrei  , Trutnev Dmitrii  , Abdrakhmanova Gulnara
Published: February 2025

The article discusses the experience of UN international methodology for assessing e-government development at federal and regional levels in Russia. United Nations procedure for e-government development measuring is widely used in the world and allows comparison of 191 countries. Focusing on international standards, the authors conducted survey of federal and regional executive authorities' web-sites. The article describes methodological approaches to web monitoring in accordance with UN methodology, web-monitoring results and recommendations to international methods' application in assessment of regional specificity of e-government and e-participation in Russia. The paper touches the limitations of international rankings and provides supply-side assessment of e-government implementation.
Integrated Public Service Delivery in Agile e-Government System through Service Oriented Enterprise Model in the Context of India
Authors: Paul Anu
Published: February 2025

The efficient public administration becomes a universal phenomenon in developed and developing countries. It aims better, faster, convenient, and cost-effective services to citizens, business, and employees. The revolution of ICT with the citizens changing demands enforced e-Government (EG) researchers and practitioners for developing new skills, competencies, capabilities, and knowledge to respond to changes in its service delivery environment. This requirement rooted to achieve an agile EG system (EGS). Since the business environment of enterprises is undergoing rapid changes, researchers are trying to find an appropriate approach toward the creation of an enterprise agility to cope with this vicissitudes. Transforming the traditional enterprise model to Service-Oriented Enterprise Architecture (SOEA) is one of the best state-of-the-art solutions for an organization to get agile. It is the evolution of Enterprise Architecture style and it integrate the business and IT logic to create an agile enterprise system. This research adopted this philosophy and applied in the EGS. The researcher proposed a Service-Oriented e-Government Enterprise Architecture to achieve agile EG system in view of Indian context. Government of India has taken various EG initiatives with high importance given to citizen-centric service delivery, but they are islands of attempts in the absence of interoperability. The proposed approach is capable to solve the interoperability and integration issues of EGS and is illustrated using a public service provided by Government of India.
In a Search for Open Budget Effects: The Context of Russia
Authors: Bolgov Radomir  , Chugunov Andrei  , Misnikov Yuri  , Karachay Vitalina
Published: February 2025

The paper seeks to understand how ICT tools are used in Russia to obtain information about government budgets, how to participate online in discussing government spending, and what the effects of open budget initiatives are.
Constructing a Methodology Toward Policy Analysts for Understanding Online Public Opinions: A Probabilistic Topic Modeling Approach
Authors: Zhang Nan  , Ma Baojun
Published: February 2025

Public opinion always has an important influence on the policy process. The development of social networking sites and applications has given the public more opportunities to express their views about the related policies. In cases where the coverage of the traditional hearing system challenged the policy process, how to measure accurately the public concern and attitudes regarding policies based on online public generated content using a data mining method will be very important issue in policy informatics. Our paper provides a probabilistic topic modeling approach, mainly based on Latent Dirichlet Allocation (LDA) model, to transform the complex semanteme of online public opinions into the values could be measured. A simple case could show the usefulness of the too toward policy analysts also be provided and discussed briefly.
Delivery of Public Value to Multiple Stakeholders through Open Government Data Platforms
Authors: Pereira Gabriela Viale  , Macadar Marie Anne  , Testa Maurício Gregianin
Published: February 2025

Governments around the world are trying to realize the benefits of technology to make a real difference in people's lives. The use of data provided by open government data platforms has a great potential to enable new services, improve the lives of citizens and make government and society work better. This research proposes a conceptual model to explain how open government data platforms are used to enhance the access to and delivery of government information and services in order to make a real difference in people's lives. This study explores and illustrates the model by taking the perspective that Open Government Data (OGD), as a platform, influences the way city agencies are delivering information and services to increase feedback for stakeholders, including citizens, government agencies and employees. To analyze the impact on citizen's lives, government agencies and employees we used the public value perspective that can helps to determine the value of government activities from multiple stakeholders' perspectives. Specifically, this working paper presents preliminary results of our analyzes from the NYC Open Data portal. We aimed to understand how citizens, employees and other agencies are using OGD to improve their activities, the impact of that and unintended consequences.
Incorporating Expert Knowledge into a Self-Organized Approach for Predicting Compressor Faults in a City Bus Fleet
Authors: Fan Yuantao  , Nowaczyk Sławomir  , Rögnvaldsson Thorsteinn
Published: February 2025

In the automotive industry, cost effective methods for predictive maintenance are increasingly in demand. The traditional approach for developing diagnostic methods on commercial vehicles is heavily based on knowledge of human experts, and thus it does not scale well to modern vehicles with many components and subsystems.
Human Factors in Cyber-Physical Social Systems: Leveraging Social Sensor Data
Authors: Sowe Sulayman K.  , Zettsu Koji
Published: February 2025

Cyber-Physical Social Systems (CPSS) are transforming how we live and interact with the physical world by semantically linking devices, data, and people. However, while tremendous progress have been made in modelling various CPSS physical components such as sensors and actuators, the involvement of humans in CPSS poses additional challenges for conceptual modelling experts and systems designers. Part of the problem is due to the fact that, even though humans sense, actuate, and process information like other CPSS component, they do these things differently. Furthermore, it is difficult to exactly know, in advance, how the human entity will interact with a CPSS. In this paper, we present a framework for modelling human's involvement in CPSS. Use cases, lessons learnt, and challenges we face in using the framework to develop a CPSS for research and development in the environmental sciences are also discussed.
Acceptance analysis based on behavioural operational research methods
Authors: Pušnik Maja  , Heričko Marjan  , Šumak Boštjan
Published: February 2025

Acceptance analysis is a well-known and widely used approach to evaluate the level of a product's or a solution's acceptance. A lot of research has been conducted in the field of software quality and acceptance. However, there is still a gap between potential users and the percentage of users that positively accept and use certain products. In addition, the process of gathering information regarding users' decisions is difficult and subjective. Users often decide against the use of solutions due to several reasons, not all of them objective, having different attitudes toward solutions due to a variety of factors. The paper focuses on the acceptance analysis based on existing models and users' behaviour characteristics. Research results present a foundation for an integrated acceptance model based on the integration of behavioural operational research and theory acceptance models, proposing a foundation for measuring and increasing the acceptance level of solutions based on human behaviour.
Privacy-Preserving and Verifiable Data Aggregation
Authors: Tran Hieu N.  , Deng Robert H.  , Pang HweeHwa
Published: February 2025

There are several recent research studies on privacy-preserving aggregation of time series data, where an aggregator computes an aggregation of multiple users' data without learning each individual's private input value. However, none of the existing schemes allows the aggregation result to be verified for integrity. In this paper, we present a new data aggregation scheme that protects user privacy as well as integrity of the aggregation. Towards this end, we first propose an aggregate signature scheme in a multi-user setting without using bilinear maps. We then extend the aggregate signature scheme into a solution for privacy-preserving and verifiable data aggregation. The solution allows multiple users to periodically send encrypted data to an untrusted aggregator such that the latter is able to compute the sum of the input data values and verify its integrity, without learning any other information. A formal security analysis shows that the solution is semantically secure and unforgeable.
ECG Steganography Using Contourlet Transform For Transmission of Secured Patient Identity
Authors: Sam Jeeva Raj Edward Jero  , Ramu Palaniappan
Published: February 2025

ECG steganography hides patient data inside their ECG signal to ensure the protection of patient's identity. In this work, an attempt has been made to evaluate ECG Steganography where Quantization Index Modulation (QIM) method is used to embed patient data into the Contourlet transform coefficients of ECG image. Tompkins QRS detection algorithm is used to construct ECG image and which is decomposed into a series of multiscale, local and directional image expansion using contour segments. QIM scheme is applied on the appropriate coefficients of the selected frequency sub-bands. QIM divides the selected frequency sub-bands into non overlapping blocks of matrix size 2×2. Two quantizers are used to embed binary watermark 0 and 1. The reverse Contourlet transform provides the watermarked ECG image from which 1D stego-ECG signal is re-ordered. The proposed scheme retrieves the watermark without the need of cover image. The deterioration due to the modified coefficients are reduced using adaptive selection of a coefficient to hide watermark bit. The efficiency of ECG steganography is measured using imperceptibility of watermark and Bit Error Rate of the retrieved watermark. Similarity metrics such as Peak Signal to Noise ratio, Percentage Residual Difference and Kullback-Leibler distance are used to estimate the imperceptibility of watermark on the stego-ECG signal. It is demonstrated that the proposed approach provides higher imperceptibility and less Bit Error Rate in the retrieved watermark, which is closed to zero. ECG signals obtained from MIT-BIH normal sinus rhythm data base are used to evaluate the performance of the proposed ECG Steganography approach.
Detecting Multi-Point Attacks in a Water Treatment System Using Intermittent Control Actions
Authors: Adepu Sridhar  , Mathur Aditya
Published: February 2025

A novel technique for detecting multi-point attacks on an Industrial Control System (ICS) is described. The technique, referred to as Intermittent Control Actions (ICA), sends control signals intermittently to selected components to monitor the system using a process invariant. ICA was assessed experimentally for its effectiveness in an operational water treatment testbed. The experiments revealed (a) multi-point attack scenarios where ICA succeeds or fails to detect an attack, (b) issues in the design of key ICS components to ensure that the control actions in ICA do not lead to undesirable process behavior, and (c) constraints on the design of the physical system for safe use of ICA.
Data-Driven Damage Detection for Beam-Like Structures under Moving Loads Using Quasi-Static Responses
Authors: Lin Yi-Zhou  , Zhao Zhan  , Nie Zhen-Hua  , Ma Hong-Wei
Published: February 2025

Due to safety problems of modern structures continuously becoming more serious, structural health monitoring (SHM) systems are attracting increasing attention. The huge amounts of data being generated by SHM systems every day are challenging to analyze. Due to data-driven methods only considering the changes in signals, they are well-suited for this problem. This study considered an application of a data-driven method, moving principal component analysis (MPCA), for damage detection and location for moving-load quasi-static responses of a beam. The MPCA is an adaption version of principal component analysis (PCA) in which a fixed-length window is used to limit the data length so that it has some advantages in adapting to damage detection. Both finite element model and experimentation were used to prepare the time series for detection. It was noted that the MPCA algorithm showed good performances on both numerical and experimental data.
Fuzzy Comprehensive Assessment on Risk Tolerance of Oil and Gas Pipelines
Authors: Tong Shu-Jiao  , Wang Ru-Jun
Published: February 2025

There are many risk factors such as corrosion, design defect, third party damage and so on during the process of the oil and gas pipeline. It is necessary for the enterprise to take the appropriate strategies to eliminate control, transfer or evade those risk factors. Because of the different risk tolerance, different oil and gas pipeline enterprises may take a different risk strategy to the same risk. At present, researches on the risk of the oil and gas pipelines is focused on the existing pipelines, and less on the risk tolerance of the oil and gas pipelines enterprises. Therefore, from the enterprise's risk tolerance of risk decision, the risk tolerance assessment model was established based on the AHP (Analytic Hierarchy Process), and the risk value were carried out by the fuzzy comprehensive assessment in this paper. And then the model was applied to an oil pipeline project, the risk factors were identified and assessed, the risk tolerance decision value of each risk was calculated to determine the major risk factors of the pipeline engineering. Also the corresponding risk strategies were put forward finally. The practical application shows that the risk assessment model based on the risk tolerance is comprehensive, reliable, and applicable, and can be used as an effective tool of risk evaluation and decision-making of oil and gas pipeline engineering.
Preventing Web Page Plagiarism in Investigative Report Writing
Authors: Mitsuhara Hiroyuki  , Shishibori Masami  , Kashihara Akihiro
Published: February 2025

Plagiarised reports on the web are a social problem and should be eliminated. In addition, such report writing results in ineffective knowledge construction. In this study, in order to prevent web page plagiarism, we have developed an investigative report writing support system that restricts copying and pasting information within web pages. With this system, students can externalise their knowledge constructed through web browsing into notes, write reports with these notes as report materials and remove inadequacies in the report content by reflection.
The Two Ontological Faces of Velocity
Authors: Barton Adrien  , Ethier Jean-François
Published: February 2025

This article presents a formalization of velocity in the context of a realist and perspectivalist upper ontology like BFO. It argues that the term “velocity” can refer to two different entities: a motion-velocity, which is a process profile characterizing a motion process; and an object-velocity, which is a disposition inhering in the moving object. Three different kinds of motion-velocity are presented: left-velocity, right-velocity and bilateral velocity. Motion-velocity could exist without object-velocity, as revealed by a thought experiment presented by Tooley; but in our world, Newton's first law of inertia implies that every object has both an inertial disposition and a closely related but different disposition that we call “object-velocity.” Those two dispositions are realized by the right-velocity. The left-velocity is a trigger of the inertial disposition, and brings into existence the object-velocity.
First Choice, Free Choice or No Choice
Authors: Jansen Arild  , Berger Jesper B.  , Goldkuhl Göran
Published: February 2025

As part of their egovernment plans, many countries aim at digitizing their communication with its citizens and the business sector. The effects of e-government depend on particular policy and design decisions. The aim of this paper is to compare the enactment of particular policies in supposedly similar contexts. The comparative case constitutes digital communication between public sector and citizens in the Scandinavian countries. From a grounded approach, we have described the policy, design and effects elements of the three case settings. Our study indicates that apparently similar solutions in comparable contexts may be enacted in rather different ways and have quite different effects. The three countries operate on a scale of coercion from mandatory (Denmark), over nudging (Norway) to voluntary (Sweden).
User Centric E-Government: The Modernization of National Migration Institute in the Southern Mexican Border
Authors: Garcia Luz Maria
Published: February 2025

The objective of this research is to analyze two important aspects: e-government processes associated with migration and the centrality of the user in e-government projects. This study aims to address migration issues, in particular the modernization of National Migration Institute (NMI) at the Mexico's southern border, in the city of Tapachula state of Chiapas the border with Guatemala, specifically with those migrants who came to Mexico for labor objectives. Regarding the second, studies of e-government have not addressed in depth the centrality of the citizen. They have partially studied some way, either from the supply side or the demand side, so this study aims to analyze the three elements: organizational process, web portal, and necessities and capabilities from user's perspective.
Towards an eGovernment Interoperability Assessment Framework
Authors: Gerontas Alexandros
Published: February 2025

The electronic cooperation of public organisations is a precondition for better public service provisioning to citizens and companies. Interoperability is a key challenge for electronic cooperation. Interoperability is a multilateral issue that incorporates technical, managerial and socioeconomic aspects. In this environment, assessing interoperability of systems and organisations is becoming increasingly important. However, interoperability assessment is a complex task. In the literature, a number of interoperability assessment models have been proposed. These incorporate different metrics and attributes to address one or some interoperability aspects. Currently, however, no commonly accepted eGovernment interoperability assessment framework exists. The aim of this PhD thesis is to develop and evaluate a comprehensive eGovernment interoperability assessment framework.
Open and Big Data Partnerships for Public Good: Interactive Live Polling of Influential Factors
Authors: Susha Iryna  , Janssen Marijn  , Grönlund Åke  , Tambouris Efthimios
Published: February 2025

There is much potential for open and big data to be used for addressing societal challenges of today. This drives a new kind of partnership called “data collaborative” emphasizing the value of data for public good. Data collaboratives stand for cross-sector partnerships, whereby organizations in the private or public sector disclose their data, as an act of good will, in order to contribute to a societal cause (such as e.g. healthcare, humanitarian, or other policy issues). In this workshop we focus on this emerging topic which so far has deserved little attention in research. In our previous research an initial framework of influential factors for data collaboratives was introduced. The workshop objective is to validate and refine this initial framework by inviting participants to take part in an interactive live polling exercise and assess a number of propositions about influential factors.
Comparing and Contrasting e-Government Maturity Models: A Qualitative-Meta Synthesis
Authors: Almuftah Hamad  , Weerakkody Vishanth  , Sivarajah Uthayasankar
Published: February 2025

The e-government maturity model has dissimilar stages that range from basic to advance online interaction competence. E-government's portals use the stages to determine maturity. The aim of this paper is to evaluate e-government maturity models through a comprehensive review of related literature by identifying and mapping cohesions across the models. Apparently, the paper picks seventeen different e-government maturity models and makes contrasts and comparisons using a qualitative meta-synthesis method. Ideally, the paper draws two key results namely presence, communication and integration are main stages involved in all the maturity models and the level of interaction and complexity are found in all models
A Temporal-Causal Modelling Approach to Integrated Contagion and Network Change in Social Networks
Authors: Blankendaal Romy  , Parinussa Sarah  , Treur Jan
Published: February 2025

This paper introduces an integrated adaptive temporal-causal network model for dynamics in networks of social interactions addressing contagion between states, and changing connections within these social networks by two principles: the homophily principle and the more-becomes-more principle. The model has been evaluated in three different manners: by simulation experiments, by verification based on mathematical analysis, and by validation against an empirical data set.
Multi-Robot Adversarial Coverage
Authors: Yehoshua Roi  , Agmon Noa
Published: February 2025

This work discusses the problem of adversarial coverage, in which one or more robots are required to visit every point of a given area, which contains threats that might stop the robots. The objective of the robots is to cover the target area as quickly as possible, while maximizing the percentage of covered area before they are stopped. This problem has many real-world applications, from performing coverage missions in hazardous fields such as nuclear power plants, to surveillance of enemy forces in the battlefield and field demining. Previous studies of the problem dealt with single-robot coverage. Using a multi-robot team for the coverage has clear advantages in terms of both coverage time and robustness: even if one robot is totally damaged, others may take over its coverage subtask. Hence, in this paper we describe a multi-robot coverage algorithm for adversarial environments that tries to maximize the percentage of covered area before the team is stopped, while minimizing the coverage time. We analytically show that the algorithm is robust, in that as long as a single robot is able to move, the coverage will be completed. We also establish theoretical bounds on the minimum covered area guaranteed by the algorithm and on the coverage time. Lastly, we evaluate the effectiveness of the algorithm in an extensive set of environments and settings.
Value-Based Reasoning and Norms
Authors: Bench-Capon Trevor
Published: February 2025

Norms are designed to guide choice of actions. Value-based practical reasoning is an approach to explaining and justifying choice of actions in terms of value preferences. Here we explore how value-based practical reasoning can be related to norms and their evolution. Starting from a basic model of a society and the norms that can arise from it, we consider how additional values, and a more sophisticated model, with more detailed states and a history, and a finer grained description of actions, can accommodate more complex norms, and a correspondingly more complex social order.
An Efficient and Expressive Similarity Measure for Relational Clustering Using Neighbourhood Trees
Authors: Dumančić Sebastijan  , Blockeel Hendrik
Published: February 2025

Clustering is an underspecified task: there are no universal criteria for what makes a good clustering. This is especially true for relational data, where similarity can be based on the features of individuals, the relationships between them, or a mix of both. Existing methods for relational clustering have strong and often implicit biases in this respect. In this paper, we introduce a novel similarity measure for relational data. It is the first measure to incorporate a wide variety of types of similarity, including similarity of attributes, similarity of relational context, and proximity in a hypergraph. We experimentally evaluate how using this similarity affects the quality of clustering on very different types of datasets. The experiments demonstrate that (a) using this similarity in standard clustering methods consistently gives good results, whereas other measures work well only on datasets that match their bias; and (b) on most datasets, the novel similarity outperforms even the best among the existing ones.
Delete-Free Reachability Analysis for Temporal and Hierarchical Planning
Authors: Bit-Monnot Arthur  , Smith David E.  , Do Minh
Published: February 2025

Reachability analysis is a crucial part of the heuristic computation for many state of the art classical and temporal planners. In this paper, we study the difficulty that arises in assessing the reachability of actions in planning problems containing sets of interdependent actions, notably including problems with required concurrency as well as hierarchical planning problems. We show the limitation of state-of-the-art techniques and propose a new method suitable for both temporal and hierarchical planning problems. Our proposal is evaluated on FAPE, a constraint-based temporal planner.A long version of this paper was presented at the HSDIP workshop [1].
One-Class to Multi-Class Model Update Using the Class-Incremental Optimum-Path Forest Classifier
Authors: Riva Mateus  , Ponti Moacir  , de Campos Teofilo
Published: February 2025

Incremental learning capabilities of classifiers is a relevant topic, specially when dealing with scenarios such as data stream mining, concept drift and active learning. We investigate the capabilities of an incremental version of the Optimum-Path Forest classifier (OPF-CI) in the context of learning new classes and compare its behavior against Support Vector Machines and k Nearest Neighbours classifiers. The OPF-CI classifier is a parameter-free, graph-based approach to incremental training that runs in linear time with respect to the number of instances. Our results show OPF-CI keeps the running time low while producing an accuracy behavior similar to the other classifiers for increments of instances. Also, it is robust to variations on the order of the learned classes, demonstrating the applicability of the method.
A Uniform Account of Realizability in Abstract Argumentation
Authors: Linsbichler Thomas  , Pührer Jörg  , Strass Hannes
Published: February 2025

We introduce a general framework for analyzing realizability in abstract dialectical frameworks (ADFs) and various of its subclasses. In particular, the framework applies to Dung argumentation frameworks, SETAFs by Nielsen and Parsons, and bipolar ADFs. We present a uniform characterization method for the admissible, complete, preferred and model/stable semantics. We employ this method to devise an algorithm that decides realizability for the mentioned formalisms and semantics; moreover the algorithm allows for constructing a desired knowledge base whenever one exists. The algorithm is built in a modular way and thus easily extensible to new formalisms and semantics. We have implemented our approach in answer set programming, and used the implementation to obtain several novel results on the relative expressiveness of the abovemen-tioned formalisms.
A Scalable Clustering-Based Local Multi-Label Classification Method
Authors: Sun Lu  , Kudo Mineichi  , Kimura Keigo
Published: February 2025

Multi-label classification aims to assign multiple labels to a single test instance. Recently, more and more multi-label classification applications arise as large-scale problems, where the numbers of instances, features and labels are either or all large. To tackle such problems, in this paper we develop a clustering-based local multi-label classification method, attempting to reduce the problem size in instances, features and labels. Our method consists of low-dimensional data clustering and local model learning. Specifically, the original dataset is firstly decomposed into several regular-scale parts by applying clustering analysis on the feature subspace, which is induced by a supervised multi-label dimension reduction technique; then, an efficient local multi-label model, meta-label classifier chains, is trained on each data cluster. Given a test instance, only the local model belonging to the nearest cluster to it is activated to make the prediction. Extensive experiments performed on eighteen benchmark datasets demonstrated the efficiency of the proposed method compared with the state-of-the-art algorithms.
Multiscale Triangular Centroid Distance for Shape-Based Plant Leaf Recognition
Authors: Yang Chengzhuan  , Wei Hui  , Yu Qian
Published: February 2025

The shapes of plant leaves are very important to plant ecologists and botanists because these can help distinguish plant species as well as serve as health indicators. In this paper, we present a novel contour-based shape descriptor named multiscale triangular centroid distance (MTCD) for plant leaf recognition. MTCD features at different triangles are extracted from each contour point to provide a compact, multiscale shape descriptor. Both local and global features of a plant leaf are effectively captured by the proposed method. A simple cosine distance is used to calculate the dissimilarity measurement between MTCD descriptors. Therefore, MTCD is a rapid approach for shape matching and is suitable for real-time application. The proposed method has been evaluated using four publicly available plant leaf datasets, including the Swedish Leaf dataset, the Smithsonian Leaf dataset, the Flavia Leaf dataset, and the ImageCLEF2012 Leaf dataset. The experimental results show that this novel approach can achieve high recognition accuracy. Comparisons with other state-of-the-art shape-based plant leaf recognition methods further demonstrate the effectiveness and efficiency of MTCD.
Beyond IC Postulates: Classification Criteria for Merging Operators
Authors: Haret Adrian  , Pfandler Andreas  , Woltran Stefan
Published: February 2025

Merging is one of the central operations in the field of belief change, which is concerned with aggregating the opinions of individuals. Representation theorems provide a family of merging operators satisfying some natural desiderata for merging beliefs. However, little is known about how these operators can be further distinguished. In the field of social choice, on the other hand, numerous properties have been proposed in order to classify voting rules. In this work, we adapt these properties to the context of merging and investigate how they relate to the standard postulates. Our results thus lead to a more fine-grained classification of merging operators and shed light on the question of which particular merging operator is best suited in a concrete application domain.
A Novel Cross-Modal Topic Correlation Model for Cross-Media Retrieval
Authors: Cheng Yong  , Huang Fei  , Jin Cheng  , Zhang Yuejie  , Zhang Tao
Published: February 2025

A novel cross-modal topic correlation model CMTCM is developed in this paper to facilitate more effective cross-modal analysis and cross-media retrieval for large-scale multimodal document collections. It can be modeled as a cross-modal topic correlation model which explores the inter-related correlation distribution over the deep representations of multimodal documents. It integrates the deep multimodal document representation, relational topic correlation modeling, and cross-modal topic correlation learning, which aims to characterize the correlations between the heterogeneous topic distributions of inter-related visual images and semantic texts, and measure their association degree more precisely. Very positive results were obtained in our experiments using a large quantity of public data.
Adaptive Binary Quantization for Fast Nearest Neighbor Search
Authors: Li Zhujin  , Liu Xianglong  , Wu Junjie  , Su Hao
Published: February 2025

Hashing has been proved an attractive technique for fast nearest neighbor search over big data. Compared to the projection based hashing methods, prototype based ones own stronger capability of generating discriminative binary codes for the data with complex inherent structure. However, our observation indicates that they still suffer from the insufficient coding that usually utilizes the complete binary codes in a hypercube. To address this problem, we propose an adaptive binary quantization method that learns a discriminative hash function with prototypes correspondingly associated with small unique binary codes. Our alternating optimization adaptively discovers the prototype set and the code set of a varying size in an efficient way, which together robustly approximate the data relations. Our method can be naturally generalized to the product space for long hash codes. We believe that our idea serves as a very helpful insight to hashing research. The extensive experiments on four large-scale (up to 80 million) datasets demonstrate that our method significantly outperforms state-of-the-art hashing methods, with up to 58.84% performance gains relatively.
Perfection in Abstract Argumentation
Authors: Spanring Christof
Published: February 2025

It is a well-known fact that stable semantics might not provide any extensions for some given abstract argumentation framework. Arguably such frameworks might be considered futile, at least with respect to stable semantics. We propagate σ-perfection stating that for a given argumentation graph all induced subgraphs provide σ-extensions. We discuss perfection and conditions for popular abstract argumentation semantics and possibly infinite frameworks.
DALEK: A Tool for Dialectical Explanations in Inconsistent Knowledge Bases
Authors: Arioua Abdallah  , Croitoru Madalina  , Buche Patrice
Published: February 2025

In this paper we present a prototype of a framework called dalek (DiALectical Explanation in Knowledge-bases). This framework implements dialectical approaches to explain query answers in inconsistent knowledge bases. The motivation behind the prototype is as follows: given an inconsistent knowledge base represented within Datalog±, a semantics for handling inconsistency and a query 𝒬, the goal is to explain why 𝒬 is accepted or not accepted under such semantics. The explanation takes a dialogical form (cf. [1,3]).
Completing Ambiguous Plans in Cognitive Robotics with Delayed Information
Authors: Kothakota Sai Kishor  , Angulo Cecilio
Published: February 2025

Robots equipped with a set of simple action skills should complete complex tasks, defined as the concatenation of a number of those basic abilities. Traditionally, planners have been used to decide skills to be activated, as well as in which sequence, like state machines. Recently, cognitive architectures like SOAR have been proposed to act as the reasoner by selecting which competence the robot should perform, addressing it towards the goal. However, they have been unidirectionally integrated: once the plan is completely designed by the cognitive architecture, it is sent to the robot, but no feedback is provided to the reasoner. Instead, our proposal allows to establish bi-directional communication between the reasoner and the robot. In this form, the reasoner can develop incomplete plans under the assumption that a part of the information to complete the plan for achieving the goal will arrive delayed from the robot's environment as well as the user. Our work develops this bi-directional communication between the SOAR cognitive architecture and the ROS (Robot Operating System) environment, usual in mobile robotics. The proposed architecture has been tested on a UAV (Unmanned Aerial Vehicle) Parrot AR.Drone 2.0, which acts as mobile robot, in a searching task.
Multi-Word Expressions in English-Latvian SMT: Problems and Solutions
Authors: Skadiņa Inguna
Published: February 2025

Processing of multi-word expressions (MWEs) is well known ‘pain in the neck’ of human language technology researchers. The problem of MWE treatment affects almost any natural language processing task, including different levels of text analysis and automated translation. It is extremely complicated task for machine translation (MT), as it includes identification, alignment and translation. Many on-line machine translation systems translate MWEs as phrases, not as one complex unit. In this paper several experiments are presented where possible ways how statistical MT system could learn translations are investigated. Although there is no significant improvement achieved in automatic evaluation, manual inspection of translations revealed some improvement in fluency and adequacy of translations.
The Ethical Impact of an Increased Presence of Robots on Human-Human Interaction (HHI) Within Aging Populations
Authors: Pearson Yvette  , Borenstein Jason
Published: February 2025

This paper examines ethical issues related to the use of robots as companions or caregivers for older adults. While so-called doom scenarios that depict myriad negative effects of increased robot presence and expanded human-robot interaction (HRI) raise engaging concerns, this paper seeks to diffuse some of those concerns and examine the potential impact of an increased robot presence and HRI on human-human interaction (HHI). Dystopian scenarios that focus almost exclusively on HRI neglect to acknowledge that humans will likely continue to interact, perhaps in novel ways, and fail to incorporate the possible beneficial effects of robot presence on HHI. The importance of supporting HHI must be kept in view when speculating about the future of HRI.
Using Language Games as a Way to Investigate Interactional Engagement in Human-Robot Interaction
Authors: Jensen Lars Christian
Published: February 2025

Social robots are employed in many classrooms and have been shown to aid learning. However, studies show that while schools intend for these robots to be social actors, they are not treated as such by the students. As the social factor is crucial for interactional engagement, this paper discusses how students' engagement with a social robot can be systematically investigated and evaluated. For this purpose, I present a small user study in which a robot plays a word formation game with a human, in which engagement is determined by means of an analysis of the ‘language games’ played with the robot.
Designing Smart Space Based Information Systems: The Case Study of Services for IoT-Enabled Collaborative Work and Cultural Heritage Environments
Authors: Korzun Dmitry
Published: February 2025

Smart spaces define a development approach to creation of service-oriented information systems for computing environments of the Internet of Things (IoT). Semantic-driven resource sharing is applied to make fusion of the physical and information worlds based on the methods of ontology modeling. Knowledge from both worlds is selectively encompassed in the smart space to serve for users' needs. This paper considers several principles of the smart spaces approach to semantic-driven design of service-oriented information systems. Applying these principles the information system development achieves such properties as (a) involvement for service construction many surrounding devices and personal mobile devices of the user, (b) use of external Internet services and data sources for enhancing the constructed services, (c) information-driven programming of service construction based on resource sharing. The principles are explained using such application domains as collaborative work and cultural heritage environments.
HRVBased Stress Recognizing by Random Forest
Authors: Zheng Gang  , Chen Yan-Hui  , Dai Min
Published: February 2025

When attempting to recognize mental stress using heart rate variability (HRV), single classification models tend to have lower accuracy in detecting different stress levels accurately, and are likely to lead to over fitting, therefore affecting the accuracy of stress recognition. This study employed the ensemble learning method of random forests (RF) and proposed a method to recognize stress by using HRV. By analyzing the short-term (120–180 sec) electrocardiography (ECG) data of the subjects during a stress-inductive video game, we extracted their HRV readings using a time-domain method, frequency-domain method, and non-linear method. Next we constructed a stress recognition model based on the RF technique, which was able to identify low, medium, and high level of stress. Then the model was applied to 200 groups of stress level data collected from the 10 subjects. The results showed that, compared to traditional k-nearest neighbor (KNN) and logistic regression (LR) methods, the RF model could be used to automatically detect and identify stress of different levels with a higher level of accuracy, and with 90% accuracy in recognizing higher levels of stress.