bluuebunny/crossref_metadata_2025 huggingface dataset:
A Model for Concurrency Using Single-Writer Single-Assignment Variables
Authors: Huntbach Matthew
Published: February 2025

This paper describes a model for concurrent computation based on single-writer single-assignment variables. The description is primarily graphical, resembling the interaction nets formalism. The model embodies rules in a process which may require two or more communications from other processes to respond. However, these are managed by a partial evaluation response on receiving a single communication.
Static Scoping and Name Resolution for Mobile Processes with Polymorphic Interfaces
Authors: Pedersen Jan Bækgaard  , Sowders Matthew
Published: February 2025

In this paper we consider a refinement of the concept of mobile processes in a process oriented language. More specifically, we investigate the possibility of allowing resumption of suspended mobile processes with different interfaces. This is a refinement of the approach taken currently in languages like occam-π. The goal of this research is to implement varying resumption interfaces in ProcessJ, a process oriented language being developed at UNLV.
13. Zinc in Allergy, Autoimmune, and Hard and Connective Tissue Diseases
Authors: Nishida Keigo  , Fukada Toshiyuki  , Yamasaki Satoru  , Murakami Masaaki  , Hirano Toshio
Published: February 2025

Zinc (Zn) is essential for normal cell structure and physiology. Its deficiency causes growth retardation, immunodeficiency, and neuronal degeneration. Zn homeostasis is tightly controlled through Zn transporters and metallothioneins, which regulate Zn concentration, its distribution in individual cells, and contribute to Zn signaling in cells. Zn intracellular signaling regulates immune reactions as well as hard and connective tissue development. Although many molecules involved in these processes have Zn-binding motifs, the molecular mechanisms of Zn's role have not been clarified. Recently, we and other groups demonstrated that Zn signaling plays diverse and specific roles in vivo and in vitro, in studies on the genetic knockout of Zn transporter functions. In this section, we discuss the impact of Zn signaling on the mast cell-mediated allergy response, T cell-mediated immune response, and development of hard and connective tissues. We also describe Zn signaling dysregulation as a leading health problem in allergy and immune response, and in skeletal and connective tissues' development.
18. Zinc Homeostasis and Signaling in the Brain
Authors: Hershfinkel Michal  , Sekler Israel
Published: February 2025

The role of zinc in the brain was a subject of intense interest, based particularly on the observation that a chelatable zinc pool is found at glutamatergic synaptic vesicles and is co-released during synaptic activity. Studies utilizing nutritional zinc deficiency or chelation linked brain zinc to cell death during ischemia and a role in development as well as learning and memory. Numerous studies in recent years led to identification of multiple zinc transporters among them the ZnT3 that is responsible for zinc accumulation in the vesicles. Generation of transgenic animals lacking specific zinc transporters together with the availability of zinc dyes led a dramatic progress in our insight on the role of brain zinc homeostasis. In this chapter we will discuss mechanisms by which zinc induces neuronal signaling or neuronal death, and how these may link zinc to learning and memory, seizure, ischemia and Alzheimer's disease (AD). Finally, we will focus on the emerging importance of zinc signaling in glia and glial-neuronal interaction.
19. Zinc and Cortical Plasticity
Authors: Nakashima Amy S.  , Wu Hsia-Pai  , Dyck Richard
Published: February 2025

In addition to the milieu of systems this nutritionally essential element contributes to in the human body, the divalent cation zinc also participates in neuronal signalling within the nervous system. Specifically, a subset of zinc within the brain is located in the synaptic vesicles of some glutatmatergic neurons and can be released at the presynaptic terminal in an activity-dependent manner. The location of zinc releasing neurons and pathways, and the co-release of synaptic zinc with neurotransmitters such as glutamate, supports the involvement of synaptic zinc in neuromodulation and, specifically, in cortical plasticity. In fact, chelation of extracellular zinc in vitro has been demonstrated to inhibit LTP, while sensory deprivation or sensory stimulation in intact animals can lead to activity-dependent increases or decreases of synaptic zinc, respectively.
29. Where We Are and Where to Go in Zinc Research?
Authors: Rink Lothar
Published: February 2025

The knowledge about zinc has increased dramatically during the last two decades. Especially the discovery of specific zinc transporters has pushed the field. However, we are just at the beginning of a new century for this trace element, since it becomes more and more obvious that zinc is regulating a multitude of cellular processes.
5. Zinc in Mammalian Cell Cycle and Cell Death
Authors: Zalewski Peter
Published: February 2025

Life has evolved around Zn and so apparently has the regulation of cell division and cell death. An increase in cytosolic Zn during mid-G1 is essential for the induction of cyclins and other gene products required for the cell to prepare for replication of its DNA. A second requirement for Zn precedes mitotic division of the cell. A role for the action of specific Zn transporters in mitosis is rapidly emerging. The relationship of Zn to cell death is intriguing as this metal ion can both suppress and promote apoptosis, depending upon factors which are still poorly understood. Zn protects many types of cell from oxidant-induced apoptotic cell death by, amongst other things, inhibiting events leading to activation of the caspase executioner proteins. Recent studies showing a role for Zn in macrophage phagocytosis suggests impaired efferocytosis as an alternative mechanism by which apoptotic cells can accumulate in the tissues in Zn deficiency. Under some circumstances, Zn acts as a potent inducer of apoptosis, such as in neurons dying during seizures and brain injury where it contributes to pathogenesis. Other emerging mechanisms of cell death, including autophagy and pyroptosis, are also influenced by Zn and Zn deficiency. In addition to the above roles of Zn as either a suppressor or promoter of cell death, a general feature of apoptosis and autophagic cell death is a substantial increase in fluorophore-detectable, labile Zn within the dying cell's cytoplasm or vacuoles, respectively; the significance of this Zn release is not known. The dual roles of Zn in regulating cell proliferation and cell death point to a pivotal role for this metal ion in tissue homeostasis with important implications for diseases in which the delicate balance between cell birth and cell death goes amiss.
Determining Where to Grasp Cloth Using Depth Information
Authors: Ramisa Arnau  , Alenya Guillem  , Moreno-Noguer Francesc  , Torras Carme
Published: February 2025

In this paper we address the problem of finding an initial good grasping point for the robotic manipulation of textile objects lying on a flat surface. Given as input a point cloud of the cloth acquired with a 3D camera, we propose choosing as grasping points those that maximize a new measure of wrinkledness, computed from the distribution of normal directions over local neighborhoods. Real grasping experiments using a robotic arm are performed, showing that the proposed measure leads to promising results.
Extending Recommendation Systems with Semantics and Context-Awareness: Pre-Filtering Algorithms
Authors: Codina Victor  , Ceccaroni Luigi
Published: February 2025

During the last decade, several recommendation systems have been proposed that help people to tackle information overload of digital content by effectively presenting content adapted to user's tastes and needs. However, these personalization technologies are far from perfect and much research is needed to improve the quality of recommendations and, particularly, user satisfaction. In this paper we analyze and extend two relatively recent approaches for improving the effectiveness of recommendation systems: context-aware recommenders, which mainly focus on incorporating contextual information to the recommendation process; and semantically-enhanced recommenders, which focus on incorporating domain semantics. Although these approaches are compatible, how to properly combine them to maximize their strengths is still an unexplored research issue. The objective of this work is to provide the basis for this research. Concretely, we propose and evaluate an improved content-based model that exploits semantics and contextual information in an integrated way.
Experimenting Linear Cryptanalysis
Authors: Collard Baudoin  , Standaert François-Xavier
Published: February 2025

Linear cryptanalysis is one of the most investigated attack against modern block ciphers. It has significantly influenced the design of symmetric encryption algorithms. However, because of the large cardinality of the problems they raise, security evaluations against these attacks frequently rely on a number of simplifying assumptions. In this chapter, we provide an experimental review of the basic hypotheses used in linear cryptanalysis, and take advantage of our experiments to discuss the practical and provable security approaches for designing secure ciphers.
Identification of promoter regions in genomic sequences by 1-dimensional constraint clustering
Authors: Bertoni A.  , Rè M.  , Saccà F.  , Valentini G.
Published: February 2025

Size constrained clustering has been recently proposed to embed “a priori” knowledge in clustering methods. By exploiting the “string property” we propose an exact and efficient algorithm based on dynamic programming techniques to solve size-constrained one-dimensional clustering problems. We show the applicability of the proposed method in a difficult computational biology problem: the prediction of the transcription start sites of genes. The obtained experimental results clearly show the potential of the proposed approach when compared with previously published methods.
Automatic Alignment of Gel 2D Images
Authors: Rozza A.  , Arca S.  , Casiraghi E.  , Campadelli P.  , Natale M.  , Bucci E.  , Consoli P.
Published: February 2025

Proteomics has gained a wide interest in the last decade since it involves the comparative study of protein expressions to identify bio-markers for early diagnosis of unpredictable, and serious, pathologies. The most powerful techniques for protein investigation compare 2D gel electrophoresys images that represent the protein composition of healthy and diseased tissues. Nevertheless, this analysis is problematic since gel images are affected by high noise levels and they are distorted, so that the same protein spot has different locations on different gels. Furthermore, the acquisition of a statistically significant sample of gels from a unique laboratory is problematic due to ethical problems, to the rarity of certain diseases, and to the fact that the process of gel electrophoresys is time consuming and costly. However, a great deal of information is present in the scientific literature in the form of images reporting 2D gels acquired for different experiments, we have developed a framework to compare annotated 2D gel images extracted from state of the art, and publicly available papers. The system has been assessed by performing the comparative analysis of the Haptoglobin; although the analyzed images are much more noisy and distorted than their sources the system achieves promising results.
Relating Values in a Series of Supreme Court Decisions
Authors: Bench-Capon Trevor
Published: February 2025

In recent years it has become quite usual to view legal decisions in terms of consideration of the values affected by deciding the case for or against a particular party. Often deciding for, say, the plaintiff will promote one value at the expense of another. Precedents are then supposed to guide the way in which this conflict is resolved. In this paper we will consider a series of cases exploring the so-called automobile exception to the requirement of the Fourth Amendment protecting against unreasonable search of persons, houses, papers, and effects. These cases highlight a conflict between the value of law enforcement and the value of privacy as protected by the Fourth Amendment, and will be used to illuminate questions about the treatment of value conflicts arising from previous work in AI and Law.
On Legal Argumentation Techniques: Towards a Systematic Approach
Authors: Damele Giovanni  , Dogliani Mario  , Mastropaolo Antonio  , Pallante Francesco  , Radicioni Daniele P.
Published: February 2025

In this paper a project for the investigation of the argumentative techniques adopted in the judgments of the Italian Constitutional Court is presented. The paper provides a taxonomy of the argumentation techniques, it introduces the representation of judgments and outlines the system to annotate judgments with arguments and to query the annotated corpus.
Experiences with “Lex Dania Live”
Authors: Petersen Knud Erik
Published: February 2025

Lex Dania is the XML-based system used to transfer documents between the Danish Parliament and Government and to promulgate those documents. The base is the Lex Dania XML schemas, the Lex Dania Editor and the Lex Dania Client. This tools are briefly presented by this paper that mentions also future works to be done for getting the Editor to cover all 56 document types promulgated in the official journals of the Parliament and the Government and for designing a system which can do consolidation of bills and amendments.
Client-Side Centric Model for Generating One-Page Modern Web Applications Dealing with Databases
Authors: Kumamoto Hiroki  , Noro Tomoya  , Tokuda Takehiro
Published: February 2025

Nowadays modern Web applications provide desktop-application-like flexible user experiences without using explicit requests. Modern Web applications need complex components: sever-side logic programs, server-side communication programs, output Web pages, client-side logic programs, and client-side communication programs. We present a new generation model called client-side centric model. This model allows us to define one-page modern Web applications dealing with databases easily. From GUI based declarative definitions, we can generate COMET technology based modern Web applications such as chat applications and calendar applications.
Creating Connective Capacities in Public Governance: Challenges and Contributions
Authors: Fenger Menno  , Bekkers Victor
Published: February 2025

This chapter starts by explaining the paradoxes, dilemmas and challenges that are connected with the simultaneous occurrence of fragmentation and interconnectivity. It then briefly introduces the backgrounds of fragmentation and interconnectivity in modern societies and describes how fragmentation and interconnectivity are manifested in the public domain. The key component of this contribution is the development of an analytical framework that enables us to develop a systematical perspective on possible solutions for the challenges of simultaneous fragmentation and interconnectivity in issues of public governance.
Beyond National Models of Integration? Rethinking Interconnectedness and Fragmentation in Dutch and French Integration Policies
Authors: Scholten Peter
Published: February 2025

National models of integration represent state-centric views of integration policies that are anchored to perceptions of national identity and historically rooted views of the role of the state. This chapter draws attention to the difficulties in balancing interconnections in terms of a single and coherent national policy frame with the fragmentation found in terms of frame-conflicts and in discrepancies in the logic of policymaking between policy levels. It reveals how Dutch and French integration policies were characterized by a multiplicity of discourses as well as by a growing gap or ‘décalage’ between policies on the local and the national level.
Integrating Business Analytics Systems with the Enterprise Environment: an Evolutionary Process Perspective
Authors: Shanks Graeme  , Bekmamedova Nargiza
Published: February 2025

Business analytics systems create value and provide competitive advantage for organisations. We argue that operational and dynamic business analytics capabilities can explain how value is created, sustained and renewed. We develop an evolutionary, process-oriented theoretical framework that describes how dynamic and operational business analytics capabilities interact over time to create value. We use the framework to explain how business analytics systems were integrated with the enterprise environment in a longitudinal case study of a large financial institution. A number of key factors for success with business analytics systems are identified.
The Impact of KMS Sophistication on Decision Support in Varying Contexts
Authors: Handzic Meliha  , Ozlen Kursad
Published: February 2025

The objective of this paper was to examine the impact of KMS sophistication on decision support in varying decision contexts. Specifically, the study was concerned with individual decision makers' performance and use of two types of KMS (unsophisticated, sophisticated) in two decision contexts (simple, complex). The results indicate that the availability of more sophisticated KMS led to a greater extent of system use irrespective of the decision context complexity. However, its positive performance impacts on the users' decision quality, confidence and satisfaction were limited to simple contexts only.
Flight Rescheduling Decisions for Robust Passenger Itineraries
Authors: Farley Susan  , Brodsky Alexander  , Sherry Lance
Published: February 2025

It has been the practice of the majority of airlines to reschedule passengers and flights so as to minimize flight delay. Some airlines are now starting to look at the problem of rescheduling from the perspective of the passenger and are trying to minimize the impact of missed and cancelled connecting flights on the consumer. In this paper we propose the algorithm Schedule Minimization foR Generalized Operational Logistics (SMRGOL) for minimizing airline passenger trip delay. Though SMRGOL is the first step in developing an algorithm for decreasing passenger trip delay, we demonstrate improvement in passenger delay.
Transforming Organizations with Business Intelligence: Comparing Theory with the Vendor Perspective
Authors: Meredith Rob  , Remington Steve  , O'Donnell Peter  , Sharma Nikit
Published: February 2025

Business Intelligence (BI) vendors have often asserted that the use of their tools can lead to organizational transformation. This paper compares the vendor literature on the topic with two management theories. The results of a content analysis of the vendor literature are presented, followed by an overview of dynamic capability theory and absorptive capacity. This comparison shows that the BI vendor literature treats transformation in a simplistic and narrow way. The paper argues for greater engagement between academia, BI vendors and BI customers.
Cancer Stem Cells: The Example of Leukemic Stem Cells
Authors: Sarry Jean Emmanuel  , Recher Christian
Published: February 2025

Cancer Stem Cells (CSCs) represent a small minority of cells that have properties of tumor initiation, self-renewal, unlimited proliferation, and have the ability to differentiate to give rise to progeny cells that are more differentiated and non-tumorigenic. CSCs can be derived from somatic stem cells, progenitors or even differentiated cells that have reacquired properties of self-renewal. Such populations of cells have been identified in various cancers. Here, we will focus on leukemic stem cells (LSCs) as a paradigm for CSC biology. We will discuss on the hierarchical and clonal organization of the leukemic clone, the frequency of LSCs as well as their fundamental properties and murine models used to study LSCs. Furthermore, we will describe several potential mechanisms that could be modulated to eradicate these LSCs, a therapeutic strategy which is believed to represent a major step forward in leukemia therapy.
Mesenchymal Stem Cells in Regenerative Medicine
Authors: Murphy Mary  , Curtin Caroline  , Duffy Garry  , Kavanagh Claire  , O'Brien Timothy  , Barry Frank
Published: February 2025

Cellular therapy involves the isolation, expansion and transplantation of human cells for the replacement or regeneration of injured tissues. It is one of the most significant repair strategies in Regenerative Medicine today. Mesenchymal stem cells represent a versatile, multimodal cellular therapy for the treatment of a broad spectrum of diseases. They stimulate a host repair response by paracrine mechanisms involving immunomodulatory, cytoprotective and pro-angiogenic mechanisms. It also appears that they may be tolerated as a fully allogeneic therapy.
Umbilical Cord Blood: From Current Use to Future Applications
Authors: Decot Véronique  , Bensoussan Danièle  , Stoltz Jean-Francois
Published: February 2025

Umbilical cord blood is a readily available source of hematopoietic stem cells used with increasing frequency as an alternative to bone marrow or peripheral stem cells for transplantation in the treatment of malignant and nonmalignant conditions in children and adults. The recent interest in stem cell research and public fascination with promises of stem cell-based therapies, fueled by the media, have led researchers to explore the potential of UCB stem cells in therapy for regenerative medicine applications.
Question Answering System Using Web Relevance Score and Translation Probability
Authors: Abe Yuji  , Morita Hajime  , Komiya Kanako  , Kotani Yoshiyuki
Published: February 2025

Question Answering (QA) is a task of answering natural language question with an adequate sentence. This paper proposes the method to evaluate candidate answer sentences using two methods, i.e., the Web relevance score and the translation probability. The experiments revealed the proposed method was significantly better than the original methods when MRRs were compared.
Artificial Immune System-based Music Piece Recommendation
Authors: Lampropoulos Aristomenis S.  , Sotiropoulos Dionysios N.  , Tsihrintzis George A.
Published: February 2025

In this paper, we address the recommendation process as a one-class classification problem based on content features and a Negative Selection (NS) algorithm that captures user preferences. Specifically, we develop an Artificial Immune System (AIS) based on a Negative Selection Algorithm that forms the core of a music recommendation system. A NS-based learning algorithm allows our system to build a classifier of all music pieces in a database and make personalized recommendations to users. This is achieved quite efficiently through the intrinsic property of the NS algorithm to discriminate “self-objects” (i.e. music pieces of user's like) from “non self-objects”, especially when the class of non self-object is vast when compared to the class of self-objects and the examples (samples) of music pieces come only from the class of self-objects (music pieces of user's like). Our recommender system has been fully implemented and evaluated and found to outperform state of the art recommender systems based on support vector machines-based methodologies.
Adaptive Negotiation for Resource Intensive Tasks in Grids
Authors: Haberland Valeriia  , Miles Simon  , Luck Michael
Published: February 2025

Automated negotiation is especially important when tasks, which require many resources, enter a Grid where resources are scarce. The level of resource scarcity dynamically changes in a Grid and the client's negotiation strategy has to adapt to this dynamism. In addition, we consider the non-transparency of a Grid with respect to a client. That is, a client is only able to observe proposals sent to it by the Grid resource allocator (GRA) but it does not have direct knowledge about availability of Grid resources. In our work, the client's strategy is to estimate the dynamism in a Grid by inferring the criteria influencing the GRA's proposals, and to adapt to this dynamism using fuzzy control rules. These rules define whether the client has to make smaller or larger concessions towards the GRA considering Grid dynamism. The simulation results show that a client who applies our adaptive negotiation strategy can obtain higher utility and significantly reduce the number of failed negotiations comparing to a client who applies the non-adaptive negotiation strategy.
Three-valued possibilistic networks
Authors: Benferhat Salem  , Tabia Karim
Published: February 2025

Possibilistic networks are graphical models that compactly encode joint possibility distributions. This paper studies a new form of possibilistic graphical models called three-valued possibilistic networks. Contrary to standard belief networks where the beliefs are encoded using belief degrees within the interval [0, 1], three-valued possibilistic networks only allow three values: 0, 1 and 0, 1. The first part of this paper addresses foundational issues of three-valued possibilistic networks. In particular, we show that the semantics that can be associated with a three-valued possibilistic network is a family of compatible boolean networks. The second part of the paper deals with inference issues where we propose an extension to the min-based chain rule for three-valued networks. Then, we show that the well-known junction tree algorithm can be directly adapted for the three-valued possibilistic setting.
Finding and Proving the Optimum: Cooperative Stochastic and Deterministic Search
Authors: Alliot Jean-Marc  , Durand Nicolas  , Gianazza David  , Gotteland Jean-Baptiste
Published: February 2025

In this article, we introduce a global cooperative approach between an Interval Branch and Bound Algorithm and an Evolutionary Algorithm, that takes advantage of both methods to optimize a function for which an inclusion function can be expressed. The Branch and Bound algorithm deletes whole blocks of the search space whereas the Evolutionary Algorithm looks for the optimum in the remaining space and sends to the IBBA the best evaluation found in order to improve its Bound. The two algorithms run independently and update common information through shared memory.
Convex Solutions of RCC8 Networks
Authors: Schockaert Steven  , Li Sanjiang
Published: February 2025

RCC8 is one of the most widely used calculi for qualitative spatial reasoning. Although many applications have been explored where RCC8 relations refer to geographical or physical regions in two- or three-dimensional spaces, their use for conceptual reasoning is still at a rather preliminary stage. One of the core obstacles with using RCC8 to reason about conceptual spaces is that regions are required to be convex in this context. We investigate in this paper how the latter requirement impacts the realizability of RCC8 networks. Specifically, we show that consistent RCC8 networks over 2n + 1 variables are guaranteed to have a convex solution in Euclidean spaces of n dimensions and higher. We furthermore prove that our bound is optimal for 2- and 3-dimensional spaces, and that for any number of dimensions n ≥ 4, there exists a network of RCC8 relations over 3n variables which is consistent, but does not allow a convex solution in the n-dimensional Euclidean space.
Multi-unit Double Auction under Group Buying
Authors: Zhao Dengji  , Zhang Dongmo  , Perrussel Laurent
Published: February 2025

Group buying is a business model in which a number of buyers join together to make an order of a product in a certain quantity in order to gain a desirable discounted price. Such a business model has recently received significant attention from researchers in economics and computer science, mostly due to its successful application in online businesses, such as Groupon. This paper deals with the market situation when multiple sellers sell a product to a number of buyers with discount for group buying. We model this problem as a multi-unit double auction. We first examine two deterministic mechanisms that are budget balanced, individually rational and only one-sided truthful, i.e. it is truthful for either buyers or sellers. Then we find that, although there exists a “trivial” (non-deterministic) mechanism that is (weakly) budget balanced, individually rational and truthful for both buyers and sellers, such a mechanism is not achievable if we further require that both the trading size and the payment are neither seller-independent nor buyer-independent. In addition, we show that there is no budget balanced, individually rational and truthful mechanism that can also guarantee a reasonable trading size.
POMDP-based online target detection and recognition for autonomous UAVs
Authors: Carvalho Chanel Caroline P.  , Teichteil-Königsbuch Florent  , Lesire Charles
Published: February 2025

This paper presents a target detection and recognition mission by an autonomous Unmanned Aerial Vehicule (UAV) modeled as a Partially Observable Markov Decision Process (POMDP). The POMDP model deals in a single framework with both perception actions (controlling the camera's view angle), and mission actions (moving between zones and flight levels, landing) needed to achieve the goal of the mission, i.e. landing in a zone containing a car whose model is recognized as a desired target model with sufficient belief. We explain how we automatically learned the probabilistic observation POMDP model from statistical analysis of the image processing algorithm used on-board the UAV to analyze objects in the scene. We also present our “optimize-while-execute” framework, which drives a POMDP sub-planner to optimize and execute the POMDP policy in parallel under action duration constraints, reasoning about the future possible execution states of the robotic system. Finally, we present experimental results, which demonstrate that Artificial Intelligence techniques like POMDP planning can be successfully applied in order to automatically control perception and mission actions hand-in-hand for complex time-constrained UAV missions.
An Overview of a News Map System for Local News in Newspapers
Authors: Ito Hideaki
Published: February 2025

This paper describes a system that shows places on maps, where crimes and/or accidents occur, named LonMaps. A number of news articles on local news are published in newspapers, since such local news are interested in a sense of daily life. In order to realize the system, three information items are extracted from news articles, which are incidents, places and dates. A thesaurus is utilized to extract incidents, which consists of legal terms and daily terms with respect to incidents and law. Moreover, places and dates are extracted based on patterns for describing them in news articles. In the description of many articles, similar sentence patterns are used.
A knowledge-based process for selecting management professionals
Authors: Ferneda Edilson  , do Prado Hercules A.  , Cancian Sobrinho Alexandre G.
Published: February 2025

The search for employees aligned to the companies needs and with a high performance profile has led them to adopt several approaches for recruiting, selecting and evaluating in order to identify the candidates that best fit to the requirements of the position. There are many different approaches used but the companies, however, the decision about what is the most effective in terms of personnel performance management is a hard task. In this paper, a study based in data mining techniques is presented to help managers in this process. The common practice, used by the companies, is classify the candidates according the personal characteristics that are necessary to achieve a good performance using normally internal/personal characteristics more than external/environmental influences as determinant for the behaviors. The existing tools can be categorized according to their objectives, ranging from the selection process to the measurement of the performance achieved by the employees. Usually, these tools are not interconnected and the information generated by them does not allow a consistent analysis of the different stages of the employee and his professional evolution. It was mapped the different standards of leadership profile and performance results of the employees that work a specific company. Also, a classifier based in the Combinatorial Neural Model was built to find the relations between the personal characteristics and performance results.
A Description Logics Geographical Ontology for Effective Semantic Analysis of Satellite Images
Authors: Cravero Maximiliano  , de Bertrand de Beuvron François  , Zanni-Merk Cecilia  , Marc-Zwecker Stella
Published: February 2025

The increasing availability of high spatial resolution satellite images is an opportunity to characterize and identify urban objects. Object-based approaches using domain knowledge for image analysis are necessary to classify data. A major issue in these approaches is domain knowledge formalization and exploitation. The use of formal ontologies seems a judicious choice to deal with these issues, and therefore, an ontology concerning urban objects has been developed. Description logics (DL) have been used to exploit the knowledge in the ontologies and develop software tools to assist the automatic labelling of satellite images.
OWL
Authors: Guebaili_Djider Ratiba  , Mokhtari Aicha  , Boustia Narhimene
Published: February 2025

OWLδϵis an ontological language for the semantic web extended by two operators “Default(C)” and “Exception(C)”. The aim of this extension is to bring out the typical aspect of concepts and their exceptions. This language is based on a non monotonic description logic named ExtDLδϵ.
Tensor-based Relational Learning for Ontology Matching
Authors: Szwabe Andrzej  , Misiorek Pawel  , Walkowiak Przemyslaw
Published: February 2025

In this paper we propose the Tensor-based Reective Relational Learning System (TRRLS) as a first tensor-based approach to decision support in the area of ontology alignment. The system may be seen as realizing a probabilistic inference with regard to the relation representing the ‘semantic equivalence’ of ontology classes or their properties. Despite the fact that TRRLS is based on the new idea of algebraic modeling of multi-relational data, it provides similar results to the best approaches of the Ontology Alignment Evaluation Initiative (OAEI) competitors to the task of matching concepts of Adult Mouse Anatomy ontology and NCI Thesaurus ontology on the basis of partially known expert matches.
Optimization of Approximate Decision Rules Relative to Number of Misclassifications
Authors: Amin Talha  , Chikalov Igor  , Moshkov Mikhail  , Zielosko Beata
Published: February 2025

In the paper, we study an extension of dynamic programming approach which allows optimization of approximate decision rules relative to the number of misclassifications. We introduce an uncertainty measure J(T) which is a difference between the number of rows in a decision table T and the number of rows with the most common decision for T. For a nonnegative real number γ, we consider γ-decision rules that localize rows in subtables of T with uncertainty at most γ.
A Robust-Adaptive Control Strategy of a Class of Bioprocesses Using Interval Observers
Authors: Petre Emil  , Selişteanu Dan  , Şendrescu Dorin
Published: February 2025

This paper deals with the design and analysis of new robust-adaptive control schemes for a class of anaerobic wastewater treatment processes. The design procedures are developed under the realistic assumption that the bacterial growth rates are unknown and the influent flow rates are disturbed, but some lower and upper bounds – possibly varying with time – of these uncertainties are known. Firstly, a new state asymptotic observer is designed, and secondly a robust observer for a class of bioprocesses is presented. Using these observers, a new robust-adaptive control scheme is developed and analyzed. This approach is applied to a particular wastewater treatment bioprocess based on anaerobic fermentation and the effectiveness of the designed algorithms is validated by several numerical simulations.
RCA based Local Image Feature Transform and its Application to Object Recognition
Authors: Nishimura Tomoki  , Wu Haiyuan  , Chen Qian  , Taki Hirokazu
Published: February 2025

This paper describes a method for transforming local image features with relevant component analysis (RCA) for extracting a compact set of visual words from a large set of local image features. By applying this method to a set of local image features that distributed in chaos, the local image features are transformed to a proper number of well separated groups. By selecting a visual-word from each group, a compact set of visual words can be obtained that has much less ambiguity and redundancy than the un-transformed set of local features, thus the performance of object recognition can be improved much by using those visual words. We applied this method to the recognition of daily necessities and confirmed its effectiveness through several comparison experiments using common image database. The proposed method should be useful for supporting the daily life of disabled people.
Comparing the Expressiveness of Argumentation Semantics
Authors: Dvoř ák Wolfgang  , Spanring Christof
Published: February 2025

In this work we complement recent investigations of the intertranslatability of argumentation semantics. Our focus is on the expressiveness of argumentation semantics and thus we expand the area of interest beyond efficiently computable translations. To this end we provide new translations between semantics as well as new translational impossibility results. This allows us to draw a hierarchy for the expressiveness of argumentation semantics.
Towards Argumentation about Subjective Probabilities
Authors: Keppens Jeroen
Published: February 2025

The Bayesian approach of evidential reasoning is fairly widely used, e.g. by forensic scientists in crime investigation. However, its application can be controversial because it relies on a numerical parameters, in the form of probability distributions, that are difficult to scrutinise, e.g. by juries. This is particularly important when these parameters are not derived from databases or mathematical models, but are expressions of expert opinion in their own right. Argumentation driven approaches to evidential reasoning provide a means to scrutinise expert opinion, but existing techniques are not capable of reasoning about probability distributions. This paper introduces a novel approach to enable arguments concerning probability distributions to be formulated and used in Bayesian evidential reasoning. As such,it extends conventional argumentation driven evidential reasoning approaches to scrutinise the probability distributions that underpin a Bayesian analysis of evidence.
Work Organization and e-Governance
Authors: Gakis Konstantinos
Published: February 2025

In managing the transformation of states in e-governance, an essential aspect is that of organizational design. In academic works there are three approaches addressing the relationship between technology and organization. After briefly discussing these three viewpoints, this paper looks into possible ways of evolving organizational forms and elaborates ways of approaching organizational design for e-governance. Case studies are presented relating: (a) to the emergence of the organizational paradigm of “one-stop-shops” as part of broader e-governance policies, highlighting the ‘shop-floor’ organizational aspects of the new organizations and (b) e-governance for taxation systems. The first element of organizational design to be deeply affected by e-governance is ‘fragmentation’ or ‘departmentalization’ of the organizations. An immediate consequence of that –at the level of work organization– is job design, which is discussed in the paper. A new model of roles and functions for public administration is proposed. The potential for new uses of technology and possible multiplicative effects is being recognized as the future challenge for the new organizations and the paper concludes in supporting the thesis that –with maturing technologies– e-governance is turning to be more of an organizational and political challenge at the micro-level, rather than a technological one.
Escaping Patchwork Adoption of ICTs in Developing Countries
Authors: Dec Agnieszka
Published: February 2025

A patchwork adoption is a technology diffusion pattern introduced by Garcia-Murillo. It is based on the observation of many developing countries which are facing high and growing income disparities, which determine ICTs market dynamics. A patchwork adoption happens when only limited group of wealthy consumers can afford state-of-the-art technologies while less privileged majority is stuck with obsolete ones. Market evolution differs from S-curve adoption pattern, which is typical for developed countries, as price decrease accompanying technology maturity is not sufficient to reach affordability level of majority of customers. Original research by Garcia-Murillo brings a recommendation that Regulators should stimulate deployment of affordable technologies, even if they are imperfect or obsolete. Recent analysis of a case study from the Armenian mobile Internet market and a computer simulation imitating consumer purchase decisions bring a conclusion that patchwork adoption doesn't need to be a long lasting trend. Decreasing costs of technology deployment can bring end-user service prices to the level, which is affordable for majority of customers, still keeping telecom business profitable. In light of the above, actions of the Regulator should rather focus on stimulating private sector investment in state-of-the-art technology solutions and encouraging competition.
The role of ICT in social and economic development of Turkmenistan
Authors: Orazbayev Serdar
Published: February 2025

Turkmenistan's government has witnessed numerous profound changes since early 2007. President Berdimukhamedov has pledged to build a harmonious, inspired, humane and developed society in Turkmenistan and to strengthen national capacity to cope with a fast-changing global environment, resulting in tangible improvements to people's lives. Ultimately, the goal is to raise the living standards of people in Turkmenistan to the level of developed countries. Turkmenistan has made significant progress in social and economic reforms last years. In May 2010 the government adopted the National Program for Social and Economic Development of Turkmenistan for 2011-30. In April 2010 President Berdimukhamedov signed order to improve document management system of state agencies and develop e-Government in Turkmenistan. Use of ICTs for achieving positive results on social and economic reforms in Turkmenistan is one of the priorities of National program. Therefore, Turkmenistan needs to set up correct e-Government development strategy and plan of implementation e-Government applications into state agencies. The aim of this work is to explore of e-Government initiatives in Turkmenistan and its impact on social and economic development of the country.
ICT, Innovation and Governance Capacity. Looking beyond the Explanatory Emptiness of the E-government Concept
Authors: Bekkers Victor
Published: February 2025

E-government studies can benefit from three theoretical discourses, when e-government studies want to increase their explanatory power. These discourses relate to innovation theory, the technology debate and the debate on the governance potential of ICT. An answer is given to the question why e-government looks as it looks as well as questions for further research are being addressed.
Too Early To Say
Authors: King John Leslie  , Kraemer Kenneth L.
Published: February 2025

The impact of ICT on public administration as illustrated in the previous chapters appears to be less than was anticipated by the 1998 book. This does not mean that the cumulative impact is trivial. Over time the effects could be significant. There has been a great deal of change since 1998, but not in areas anticipated. This is a surprise, and this chapter comments on the nature of surprise and the lessons learned about ICT, civil society and public administration that might affect design.
Types of Rights in Two-Party Systems: A Formal Analysis
Authors: Pace Gordon J.  , Schapachnik Fernando
Published: February 2025

We present a formalization of Kanger's types of rights in the context of interacting two-party systems, such as contracts. We show that in this setting basic rights such as claim, freedom, power and immunity can be expressed in terms of (possibly negated) permissions and obligations over presence or absense of actions. Another way of saying this is that, at least in the context of contracts, neither claim, nor power, nor freedom nor immunity are foundational modalities, as they can be defined in terms of others. We also show that the set of atomic type rights is different from Kanger's original proposal.
Twitter User Rank Using Keyword Search
Authors: Noro Tomoya  , Ru Fei  , Xiao Feng  , Tokuda Takehiro
Published: February 2025

Twitter has attracted attention recently as a new way of collecting, providing and sharing information on the Internet. However, it is difficult for us to find Twitter users to follow for getting valuable information related to a topic of interest. In this paper, we propose a method for ranking Twitter users using the Twitter keyword search. This method utilizes tweet relation among Twitter users and tweets (retweet and reply) as well as tweet count of each Twitter user. Experimental results show our method outperforms methods using only tweet count, tweet relation, or follow relation.
Partiality and Inconsistency in Agents' Belief Bases
Authors: Małuszyński Jan  , Szałas Andrzej
Published: February 2025

Agents' beliefs can be incomplete and partially inconsistent. The process of agents' belief formation in such contexts has to be supported by suitable tools allowing one to express a variety of inconsistency resolving and nonmonotonic reasoning techniques.
Exploiting Linked Open Data for Attribute Selection on Recommendation Systems
Authors: Pham Xuan Hau  , Jung Jason J.  , Takeda Hideaki
Published: February 2025

Recommendation systems have extracted items that users may be interested in. However, most of the recommendation applications have restricted on recommending only items in a specific domain (e.g., movies, books, and musics). In this paper, we propose a novel approach to enable the existing recommendation systems to extract addition items in various other domains. Thereby, this work is focusing on integrating all available Linked Open Data (LOD) for selecting more relevant attributes which can improve the performance of recommendation processes.
Multivariate clustering for group language learning in Facebook
Authors: Troussas Christos  , Virvou Maria  , Caro Jaime  , Espinosa Kurt Junshean
Published: February 2025

The massive use of Facebook opens new horizons in the areas of information and communications technology, which induced changes in pedagogy. Towards this direction, we implemented an educational application for learning languages. In order to cover the heterogeneous group of people to which educational applications are targeted and to further emphasize the educational aspect of Facebook, we implemented and present the multivariate clustering for group learning in Facebook. By the incorporation of the multiple parameter based clustering, the problem of grouping students, in order to provide sophisticated user models, is further treated. Multivariate clustering is conducted by the k-means algorithm which takes as input, to initialize the process, multiple students' characteristics.
Towards Optimal Solutions in a Constantly Changing Environment
Authors: Encheva Sylvia
Published: February 2025

Looking for an optimal solution in a constantly changing environment is both time consuming and costly. Decision making problems are becoming more complicated when a number of alternatives have to be evaluated with respect to several criteria. In this paper we are discussing an approach to minimize some of the preliminary work by using closure systems.