bluuebunny/crossref_metadata_2025 huggingface dataset:
Looking Into Collaborative Learning: Design from Macro- and Micro-Script Perspectives
Authors: Villasclaras-Fernández Eloy D.  , Isotani Seiji  , Hayashi Yusuke  , Mizoguchi Riichiro
Published: February 2025

Design of collaborative learning (CL) scenarios is a complex task, but necessary if the goal of the collaboration is learning. Creating well-thought-out CL scenarios requires experience and knowledge about different learning/instructional theories and practices related to collaboration. Inexperienced designers, who may not have all the needed knowledge to formulate pedagogically sound collaborative learning plans, may have difficulties to design CL activities. Thus, although CL has shown to be effective, it is not often used in classroom adequately. To tackle this problem, this paper presents an ontology for CL, that aims at modeling not only the learning activities, but also the rationale for their configuration in pedagogical terms. This ontology allows modeling the expected interactions among students as well as the mechanisms that promote or enhance collaboration structured across several sessions and involve individual and collaborative activities. Finally, the paper discusses an application of the presented ontology to support the design of pedagogically sound CL scenarios.
A model of learners profiles management process
Authors: Eyssautier-Bavay Carole  , Jean-Daubias Stéphanie  , Pernin Jean-Philippe
Published: February 2025

Our research concerns teaching assistant systems. It deals with the question of reuse and exploitation of learners profiles by the different actors of the learning situation; teacher, learner, families, institution or scientist. This paper first describes the difficulties linked to the reuse of heterogeneous existing learners profiles. Then, REPro, a learners profiles management model is proposed. The deployment of this process within a computerized environment is presented as well as the results of first experiments.
Combining Partial Order Reduction with Bounded Model Checking
Authors: Vander Meulen José  , Pecheur Charles
Published: February 2025

Model checking is an efficient technique for verifying properties on reactive systems. Partial-order reduction (POR) and symbolic model checking are two common approaches to deal with the state space explosion problem in model checking. Traditionally, symbolic model checking uses BDDs which can suffer from space blowup. More recently bounded model checking (BMC) using SAT-based procedures has been used as a very successful alternative to BDDs. However, this approach gives poor results when it is applied to models with a lot of asynchronism. This paper presents an algorithm which combines partial order reduction methods and bounded model checking techniques in an original way that allows efficient verification of temporal logic properties (LTLX) on models featuring asynchronous processes. The encoding to a SAT problem strongly reduces the complexity and non-determinism of each transition step, allowing efficient analysis even with longer execution traces. The starting-point of our work is the Two-Phase algorithm (Namalesu and Gopalakrishnan) which performs partial-order reduction on process-based models. At first, we adapt this algorithm to the bounded model checking method. Then, we describe our approach formally and demonstrate its validity. Finally, we present a prototypal implementation and report encouraging experimental results on a small example.
Engineering Emergence: an occam-π Adventure
Authors: Welch Peter H.  , Wallnau Kurt  , Klein Mark
Published: February 2025

Future systems will be too complex to design and implement explicitly. Instead, we will have to learn to engineer complex behaviours indirectly: through the discovery and application of local rules of behaviour, applied to simple process components, from which desired behaviours predictably emerge through dynamic interactions between massive numbers of instances.
SVM Classification of EEG Signals for Brain Computer Interface
Authors: Costantini G.  , Todisco M.  , Casali D.  , Carota M.  , Saggio G.  , Bianchi L.  , Abbafati M.  , Quitadamo L.
Published: February 2025

In this paper, a brain/computer interface is proposed. The aim of this work is the recognition of the will of a human being, without the need of detecting the movement of any muscle. Disabled people could take, of course, most important advantages from this kind of sensor system, but it could also be useful in many other situations where arms and legs could not be used or a brain-computer interface is required to give commands. In order to achieve the above results, a prerequisite has been that of developing a system capable of recognizing and classifying four kind of tasks: thinking to move the right hand, thinking to move the left hand, performing a simple mathematical operation, and thinking to a carol. The data set exploited in the training and test phase of the system has been acquired by means of 61 electrodes and it is formed by time series subsequently transformed to the frequency domain, in order to obtain the power spectrum. For every electrode we have 128 frequency channels. The classification algorithm that we used is the Support Vector Machine (SVM).
Detection of Difference between News Articles on the Same Topic Based on Sequential Comparison
Authors: Noro Tomoya  , Tokuda Takehiro
Published: February 2025

Currently, a lot of news articles are published on the Web, and it is getting easier for us to read them. However, the number of articles are too large for us to read all of them. Although some Web sites cluster/classify news articles into some topics (categories), it is not enough since a large number of articles are still in each topic. Detecting difference between articles on one topic will be one of the solution to comprehend the whole topic. In this paper, we propose a method for detection of difference between news articles on the same topic. Articles are sequentially compared by three different comparison units: paragraphs, sentences, and simple sentences. Our method is evaluated by applying it to Japanese news articles.
Securing Low-cost RFID Systems: an Unconditionally Secure Approach
Authors: Alomair Basel  , Lazos Loukas  , Poovendran Radha
Published: February 2025

We explore a new direction towards solving the identity authentication problem in RFID systems. We break the RFID authentication process into two main problems: message authentication and random number generation. For parties equipped with a good source of randomness and a secure cryptographic primitive to authenticate messages, the literature of cryptography is rich with well-studied solutions for secure identity authentication. However, the two operations, random number generation and message authentication, can be expensive for low-cost RFID tags. In this paper, we lay down the foundations of a new direction towards solving these problems in RFID systems. We propose an unconditionally secure direction for authenticating RFID systems. We use the fact that RFID readers are computationally powerful devices to design a protocol that allows RFID readers to deliver random numbers to RFID tags in an unconditionally secure manner. Then, by taking advantage of the information-theoretic security of the transmitted messages, we develop a novel unconditionally secure message authentication code that is computed with a single multiplication operation. The goal of this work is to bring more research to the design of such unconditionally secure protocols, as opposed to the computationally secure protocols that have been proposed extensively, for the purpose of suiting the stringent computational capabilities of low-cost devices.
Security in the Internet of Things
Authors: Aigner Manfred
Published: February 2025

In this paper we illustrate security problems coming up with the new concept of the Internet of Things. Passive RFID tags will make up the majority of devices participating in this network. Since passive RFID tags are the devices with the least computing power in the IoT, we focus our investigations on this technology. If we can provide a proper protection for those devices, it will also be possible to use the same security mechanisms on other technologies. In the following section we explain the relevance of passive RFID and security for the upcoming IoT. Later we will provide information about security issues for this technology and explain the current state-of-the-art in research.
Securing RFID-supported Supply Chains
Authors: Kerschbaum Florian  , Aigner Manfred
Published: February 2025

Modern RFID-supported supply chains envision a seamless sharing of item-level data across multiple supply chain participants in the “Internet of Things”. However, many companies are reluctant to propagate large amounts of their track and trace information to others, as they fear the uncontrolled disclosure of vital business intelligence. Without built-in safeguards, such systems thus run the risk of hindering the adoption of efficient supply chain management infrastructures.
Skeletal Muscle Fatigue
Authors: Lindinger Michael I.
Published: February 2025

The force producing capability of skeletal muscle is regulated by a number of simultaneously occurring processes that provide real-time fine tuning of contractility. This allows for the locomotory demands of the individual to attempt to be met within functional confines of contracting muscle that change as exercise progresses. Fatigue occurs in response to high-intensity exercise, as well as during prolonged low-intensity exercise, although the ionic and metabolic factors contributing to these two types of fatigue may differ. Fatigue of high-intensity exercise is recognized to occur primarily by depression and failure of excitability, either at the sarcolemmal or perhaps within the t-tubule system, due to altered electrico-chemical gradients for K+, Cl-and Na+. There is increasing evidence that increased intra- and extracellular [H+] and [lactate-] help to stabilize the sarcolemma and help to maintain excitability. The fatigue of prolonged, low-intensity exercise may be characterized by depletion of energy substrate, primarily glycogen, and a decreased intracellular [K+] with ensuing depressed membrane excitability may also contribute. Both types of fatigue are also associated with increased concentrations of reactive oxygen species (ROS), and increased [ROS] appears to downregulate the activities of key ion transporting and metabolic enzymes, as well as contributing to muscle damage in the long term. The purpose of this chapter is to provide an overview of our current knowledge and speculations regarding these main contributors to skeletal muscle fatigue.
Apnea Diving
Authors: Bakovic Darija  , Palada Ivan  , Dujic Zeljko
Published: February 2025

Men and women have been diving for thousands of years to gather a variety of products, including food, sponges, and pearls, to conduct salvage and military operations, and to explore. In 1911, one of the first freediving competitions was held when a Greek fisherman, Yorgos Haggi Statti, was offered a few dollars to dive and to rescue the anchor of an Italian ship which had become stuck in the Aegean Sea. The Italian ship was set free and Yorgos became known as the “father of freediving”. After World War II, breath hold diving became an international sport where athletes test the human limits of time, depth and distance. Exposure to excessive depths, though, can be very dangerous and cause a collapse of the lungs, cardiac arrest, blackouts, decompression sickness and, at worst, death. Whatever the reason for breath hold diving, its success depends on how a diver tolerates the physiological stress related to the depth and duration of dive. The human body has several adaptations under diving conditions, which stem from the mammalian diving reflex. These adaptations enable the human body to endure depth and lack of oxygen far beyond what would be possible without the reflex. Human diving response involves bradycardia, vasoconstriction of selected vascular beds with increase in blood pressure, changes in cardiac output and spleen contraction. Variety of studies frequently discussed parts of diving response. However, the concept of spleen contraction has recently been described as a property of diving response. The spleen serves as a dynamic blood cell reservoir which can be released into systemic circulation during exercise, diving or intermittent hypoxia. Since contraction of the spleen increases hemoglobin and hematocrit circulating in blood, than the O2transport will also be enhanced. In humans, the rapidity of spleen contraction indicates that the initial stimulation is likely neural in origin, but contraction may be sustained throughout the dive by circulating catecholamines released from the adrenal gland. Leucocytes and platelets accumulate in the human spleen to a much greater extent than erythrocytes, accounting for approximately 40% of both body populations. The destiny of these two populations during apnea induced spleen contraction is also the aim of our chapter.
Exercise Therapy for Obesity and Type 2 Diabetes
Authors: Praet Stephan F.E.  , Van Loon Luc J.C.
Published: February 2025

Structured exercise is considered an important cornerstone to treat insulin resistance, achieve good glycemic control, and improve cardiovascular risk profile in obesity and type 2 diabetes. Current clinical guidelines recognize the therapeutic strength of exercise intervention as an addendum to dietary and pharmacological measures. This chapter reviews the pathophysiological problems associated with obesity and type 2 diabetes and describes the benefits of exercise therapy on phenotype characteristics, insulin resistance, glycemic control and cardiovascular risk profile in these patients. We review the known effects of acute, vs medium- and long-term exercise interventions in insulin resistant and type 2 diabetes populations. Also, the influence of different exercise modalities, stage of the disease, and the presence of co-morbidities will be discussed. Since certain blood glucose lowering drugs may interact with exercise and increase the risk of hypoglycemic events, specific safety guidelines are provided. Also for optimal long-term exercise training results as well as safety reasons, prior exercise testing is recommended. Such exercise testing should consider cardiopulmonary fitness, blood pressure response, joint flexibility, as well as muscle strength. Based on test results and specific subgroup characteristics different exercise regimens should be applied. Overall, exercise modalities should be selected to define an exercise regimen that effectively increases energy expenditure and improves body composition while minimizing the risk of injury and drop-out. Proper corrective shoes and optimization of lower limb biomechanics may prevent overload injuries and diabetic foot ulceration and, as such, improve exercise training adherence and lower patient drop-out rates. Based on the currently available literature it is concluded that patients with obesity and/or type 2 diabetes should be stimulated to participate in specifically designed exercise intervention programs. More specifically, attention should be paid to cardiovascular and musculoskeletal deconditioning. More clinical research is warranted to study the interaction between medication and exercise and establish the efficacy of a more individualized approach, especially for type 2 diabetes subpopulations at different stages of the disease and the level of co-morbidity.
Cardiopulmonary Exercise Testing in Patients with Heart Failure
Authors: Antoine-Jonville Sophie  , Dayer Mark J.
Published: February 2025

Heart failure is a common condition affecting between one and two percent of the population in Western society, although it is a surprisingly poorly defined and understood condition. Cardiopulmonary exercise testing (CPET) can be carried out safely in a wide range of patients with heart failure, although there are some contraindications and the exercise protocol may have to be adjusted. CPET has shed some light on the pathophysiology of heart failure. The observation that patients with heart failure can achieve higher VO2 values when walking as opposed to cycling is one argument against the haemodynamic hypothesis. The cardiopulmonary exercise test is considered the ‘gold standard’ when assessing a patient's exercise tolerance. The peak VO2 is a measure which has been validated in numerous heart failure populations, and a value of 14mls/kg/min is still used as a cut-off when considering patients for cardiac transplantation. There are limitations with the use of peak VO2 alone, and numerous other values derived from the exercise data are discussed, of which the VE/VCO2 slope is the best researched. In summary CPET is of great value in the assessment of patients with heart failure.
Role of Regular Exercise in the Management of Asthma
Authors: Ram Felix S.F.
Published: February 2025

People with asthma have a unique response to exercise. In some, exercise can provoke an increase in airways resistance leading to exercise-induced asthma (EIA) but regular exercise is also considered to be useful in the management of asthma, especially in children and adolescents. EIA can be prevented or reduced by pre-treatment with a number of medications. However, the fear of inducing an episode of breathlessness inhibits many people with asthma from taking part in exercise. A low level of regular exercise leads to a low level of physical fitness, so it is not surprising that a number of studies have found that people with asthma have lower cardiorespiratory fitness than their peers although not every study has reported this finding.
A New Era for CIO and ICT Development
Authors: Sirirachatapong Pansak
Published: February 2025

The purpose of this paper is to emphasize the importance of the International Academy of CIO in the development of the CIO and to encourage further closer cooperation between members to ensure further progress. The paper also presents the status of ICT initiatives in Thailand, especially the efforts to implement the Second ICT Master Plan (2009–2013).
The modular structure of an ontology: an empirical study
Authors: del Vescovo Chiara  , Parsia Bijan  , Sattler Uli  , Schneider Thomas
Published: February 2025

Efficiently extracting a module from a given ontology that captures all the ontology's knowledge about a set of specified terms is a well-understood task. This task can be based, for instance, on locality-based modules.
Rational and Intuitive Decision-makers from Two Continents
Authors: Zoltay Paprika Zita
Published: February 2025

Strategic decision making is usually conducted by a firm's top management, led by the CEO or the President of the company. In keeping with this, 40 top level managers from two continents (North America and Europe) were targeted in a comparative research study. In the two countries (California US and Hungary), twelve of the managers were CEOs, Presidents, Vice Presidents or Chief Officers (hereafter referred to as Executives) while eight were founders and majority owners of their own enterprises (hereafter referred to as Entrepreneurs). The research focused on the following 3 areas: 1) How top level managers really make strategic decisions in these two different parts of the world; 2) How Entrepreneurs and Executives differ, if at all, in their approach to strategic decision making when they combine analytical thinking with their intuition; 3) The similarities and differences in management skills and decision making practices between Entrepreneurs and Executives within the investigated management cultures.
Understanding the Impact of Technology on Managerial Decision Making – The Case of the ERP System
Authors: Carton Fergal  , Adam Frédéric
Published: February 2025

Previous research has illustrated the difficulty in understanding the impact of new technologies on the work of managers, e.g. their decision making. The breadth of functionality and level of integration in ERP applications means that research on their impact on organisations is particularly difficult to conduct without looking at a very granular level of business process. This paper reports on two in-depth studies of mature ERP applications in two organisations, from the point of view of managers in charge of managing key business processes. The key objective was to construct a framework to represent the impact of ERP on the ability of firms to make good decisions rapidly. We found that, although ERPs are sold as tools to increase speed and visibility of operations, they don't always deliver such benefits. They can distort the reality they seek to represent. Our cross case analysis show that much of the benefits associated with real time access to key operational data is compromised by the use of other technologies, such as offline data warehouses, business intelligence tools and spreadsheets that are required to correct the distorted reality represented in ERP applications. Thus, decision makers still need to manually combine data from a variety of information systems, thereby losing out on the integration promised by ERP technology.
Assigning Emergency Vehicles to Urban Incidents
Authors: Borges Marcos R.S.  , Ochoa Sergio F.  , Pino José A.  , Vivacqua Adriana
Published: February 2025

Urban emergency situations require accurate and timely decisions in order to reduce the impact of these incidents on human lives and civil property. Decision making in this time critical scenario is a challenging task because there are several variables influencing the process, and some of them change quickly. This process characteristic requires that decision makers monitor and adjust their decisions almost permanently until the situation is under control. Therefore, information availability and understandability become a key issue to improve the decision making process. This paper presents two decision support systems that implement a decision making model. The model helps determine which information must be used to support the decision making process, and also how frequently such information must be updated. The systems are intended to help allocate ambulances and fire trucks to urban emergencies.
Interval Forecast of Water Quality Parameters
Authors: Ohashi Orlando  , Torgo Luís  , Ribeiro Rita P.
Published: February 2025

The current quality control methodology adopted by the water distribution service provider in the metropolitan region of Porto - Portugal, is based on simple heuristics and empirical knowledge. Based on the domain complexity and data volume, this application is a perfect candidate to apply data mining process. In this paper, we propose a new methodology to predict the range of normality for the values of different water quality parameters. These intervals of normality are of key importance to decide on costly inspection activities. Our experimental evaluation confirms that our proposal achieves good results on the task of forecasting the normal distribution of values for the following 30 days. The proposed method can be applied to other domains with similar network monitoring objectives.
Improving Hierarchical Classification with Partial Labels
Authors: Nguyen Nam
Published: February 2025

In this paperwe address the problem of semi-supervised hierarchical learning when some cases are fully labeled while other cases are only partially labeled, named Hierarchical Partial Labels. Given a label hierarchy, a fully labeled example provides a path from the root node to a leaf node while a partially labeled example only provides a path from the root node to an internal node. We introduce a discriminative learning approach, called Partial HSVM, that incorporates partially labeled information into the hierarchical maximum margin-based learning framework. The partially labeled hierarchical learning problem is formulated as a quadratic optimization that minimizes the empirical risk with L2-norm regularization. We also present an efficient algorithm for the hierarchical classification in the presence of partially labeled information. In our experiments with the WIPO-alpha patent collection, we compare our proposed algorithm with two other baseline approaches: Binary HSVM, a standard approach to hierarchical classification, which builds a binary classifier (SVM) at each node in the hierarchy, and PL-SVM, a flat multiclass classifier which can take advantages of the partial label information. Our empirical results show that Partial HSVM outperforms Binary HSVM and PL-SVM across different performance metrics. The experimental results demonstrate that our proposed algorithm, Partial HSVM, combines the strength of both methods, the Binary HSVM and PL-SVM, since it utilizes both the hierarchical information and the partially labeled examples. In addition, we observe the positive correlation between the labeling effort in obtaining partially labeled data and the improvement in performance.
Sound and Complete Landmarks for And/Or Graphs
Authors: Keyder Emil  , Richter Silvia  , Helmert Malte
Published: February 2025

Landmarks for a planning problem are subgoals that are necessarily made true at some point in the execution of any plan. Since verifying that a fact is a landmark is PSPACE-complete, earlier approaches have focused on finding landmarks for the delete relaxation Π+. Furthermore, some of these approaches have approximated this set of landmarks, although it has been shown that the complete set of causal delete-relaxation landmarks can be identified in polynomial time by a simple procedure over the relaxed planning graph. Here, we give a declarative characterisation of this set of landmarks and show that the procedure computes the landmarks described by our characterisation. Building on this, we observe that the procedure can be applied to any delete-relaxation problem and take advantage of a recent compilation of the m-relaxation of a problem into a problem with no delete effects to extract landmarks that take into account delete effects in the original problem. We demonstrate that this approach finds strictly more causal landmarks than previous approaches and discuss the relationship between increased computational effort and experimental performance, using these landmarks in a recently proposed admissible landmark-counting heuristic.
Enriching ℰℒ-Concepts with Greatest Fixpoints
Authors: Lutz Carsten  , Piro Robert  , Wolter Frank
Published: February 2025

We investigate the expressive power and computational complexity of ℰℒν, the extension of the lightweight description logic ℰℒ with concept constructors for greatest fixpoints. It is shown that ℰℒνhas the same expressive power as ℰℒ extended with simulation quantifiers and that it can be characterized as a largest fragment of monadic second-order logic that is preserved under simulations and has finite minimal models. As in basic ℰℒ, all standard reasoning problems for general TBoxes can be solved in polynomial time. ℰℒνhas a range of very desirable properties that ℰℒ itself is lacking. Firstly, least common subsumers w.r.t. general TBoxes as well as most specific concepts always exist and can be computed in polynomial time. Secondly, ℰℒνshares with ℰℒ the Craig interpolation property and the Beth definability property, but in contrast to ℰℒ allows the computation of interpolants and explicit concept definitions in polynomial time.
Multitask Kernel-based Learning with Logic Constraints
Authors: Diligenti Michelangelo  , Gori Marco  , Maggini Marco  , Rigutini Leonardo
Published: February 2025

This paper presents a general framework to integrate prior knowledge in the form of logic constraints among a set of task functions into kernel machines. The logic propositions provide a partial representation of the environment, in which the learner operates, that is exploited by the learning algorithm together with the information available in the supervised examples. In particular, we consider a multi-task learning scheme, where multiple unary predicates on the feature space are to be learned by kernel machines and a higher level abstract representation consists of logic clauses on these predicates, known to hold for any input. A general approach is presented to convert the logic clauses into a continuous implementation, that processes the outputs computed by the kernel-based predicates. The learning task is formulated as a primal optimization problem of a loss function that combines a term measuring the fitting of the supervised examples, a regularization term, and a penalty term that enforces the constraints on both supervised and unsupervised examples. The proposed semi-supervised learning framework is particularly suited for learning in high dimensionality feature spaces, where the supervised training examples tend to be sparse and generalization difficult. Unlike for standard kernel machines, the cost function to optimize is not generally guaranteed to be convex. However, the experimental results show that it is still possible to find good solutions using a two stage learning schema, in which first the supervised examples are learned until convergence and then the logic constraints are forced. Some promising experimental results on artificial multi-task learning tasks are reported, showing how the classification accuracy can be effectively improved by exploiting the a priori rules and the unsupervised examples.
Belief-Goal Relationships in Possibilistic Goal Generation
Authors: da Costa Pereira Célia  , Tettamanzi Andrea G.B.
Published: February 2025

The way in which the relationships between beliefs, goals, and intentions are captured by a formalism can have a significant impact on the design of a rational agent. In particular, what Rao and Georgeff underline about the relationships between goals and beliefs is that it is reasonable to require a rational agent not to allow goal-belief inconsistency, while goal-belief incompleteness can be allowed.
Goal Selection in Argumentation Processes
Authors: Ballnat Stefan  , Gordon Thomas F.
Published: February 2025

When argumentation is conceived as a kind of process, typically a dialogue, for reasoning rationally with limited resources under conditions of incomplete and inconsistent information, arguers need heuristics for controlling the search for arguments to put foward, so as to move from stage to stage in the process in an efficient, goal-directed way. For this purpose, we have developed a formal model of abduction in argument evalution structures. An argument evaluation structure consists of the arguments of a stage, assumptions about audience and an assignment of proof standards to issues. A derivability relation is defined over argument evaluation structures for the literals ‘in’ a stage. Literals which are not derivable in a stage are ‘out’. Abduction is defined as a relation between an argument evaluation structure and sets of literals, called ‘positions’, which, when the assumptions are revised to include the literals of the position, would make a goal literal in or out, depending of the standpoint of the agent. Soundness, minimiality, consistency and completeness properties of the abduction relation are proven. A heuristic cost function estimating how difficult it is to find or construct arguments pro a literal in the domain can be used to order positions and literals within positions. We compare our work to abduction in propositional logic, in particular the Assumption-Based Truth Maintenance System (ATMS).
Developing the Human Language Technology Infrastructure in Lithuania
Authors: Marcinkevičienė Rūta  , Vitkutė-Adžgauskienė Daiva
Published: February 2025

This paper aims at a short overview of the development of the Lithuanian human language technology infrastructure in the context of European co-operation. It also presents national policies related to research infrastructures and joint activities planned for different levels, institutional, national and European.
Estonian Large Vocabulary Speech Recognition System for Radiology
Authors: Alumäe Tanel  , Meister Einar
Published: February 2025

This paper describes implementation and evaluation of an Estonian large vocabulary continuous speech recognition system prototype for the radiology domain. We used a 44 million word corpus of radiology reports to build a word trigram language model. We recorded a test set of dictated radiology reports using ten radiologists. Using speaker independent speech recognition, we achieved a 9.8% word error rate. Recognition worked in around 0.5 real-time. One of the prominent sources of errors were mistakes in writing compound words.
A Density-based Hierarchical Clustering Algorithm for Highly Overlapped Distributions with Noisy Points
Authors: Pascual Damaris  , Pla Filiberto  , Sánchez J. Salvador
Published: February 2025

In this work, we present a new two-stage technique to find clusters of different shapes, densities and sizes in the presence of overlapped clusters and noise. Firstly, a density-based clustering approach is developed using a density function estimated by the EM algorithm and in the second stage, a hierarchical strategy is used to merge clusters according to a dissimilarity measure here introduced in order to assess the overlap and proximity of the clusters. Several synthetic and real world data sets are used to evaluate the effectiveness and the efficiency of the new algorithm, indicating that it obtains satisfactory clustering results.
A Bio-inspired Model for Executive Control
Authors: Srinivasa Narayan  , Chelian Suhas E.
Published: February 2025

Prefrontal cortex (PFC) is implicated in executive control, herein defined as the ability to map external inputs and internal goals toward actions that solve problems or elicit rewards. In this work, we present a computational model of PFC and accompanying brain systems (e.g. limbic, motor control, and sensory areas) based on a review of structure and function. The current design leverages previous models, but organizes them in novel ways to provide transparent and efficient computation. We propose this model provides a biologically plausible architecture that learns from and uses multimodal spatio-temporal working memories to develop and refine reward-eliciting behaviors. It addresses several anatomical and physiological constraints consistent with neurophysiology. The functional competence of the model is illustrated using the “Egg Hunt” scenario.
Towards Understanding Trust Through Computational Cognitive Modeling
Authors: Kennedy William G.
Published: February 2025

Trust is a vital component of human society. Without trust, we would all have to continuously focus on survival, i.e., our physical security and the daily finding of food and water. With trust, we developed the division of labor that allowed us to sleep safely and develop a complex society. However, the concept of trust is very defused and not described operationally, i.e., in terms of the mechanisms by which we build, maintain, and decide to trust. There is now evidence that trust has a biological foundation [1]. That brain imaging data shows that some of the regions of our brain associated with trust are part of our high-level reasoning but others are deep within the brain. Like emotions, deep brain processes are typically fast, unconscious, and unexplainable. My hypothesis is that trust is based on cognitive mechanisms, likely the brain's slow and fast processes [2]. This talk focuses on a computational cognitive modeling approach to developing and understanding the mechanisms of trust in humans. The approach to investigating the mechanisms of trust is the use of computational cognitive modeling, specifically ACT-R [3]. Cognitive modeling is the development of declarative and procedural knowledge that “runs” on a cognitive architecture and produces outputs/behaviors comparable to those of humans. The result of this work will be an ACT-R model replicating human behavior on trust and explaining possible mechanisms of trust. However, the ACT-R system is intended to model rational behavior. Therefore, I will be also discussing mechanisms not normally considered to be “rational” [2]. Knowing the mechanisms associated with trust will allow a principled approach to developing intelligent systems we can and will trust.
An Externalist and Fringe Inspired Cognitive Architecture
Authors: Manzotti Riccardo
Published: February 2025

Many biological agents are characterized by consciousness both as a capacity to feel as a style of cognitive access to integrated information. It is plausible to assume that some essential feature of cognition has not yet been addressed although it is implemented in many biological agents. Among the aspects of biological cognition underrepresented in the literature on cognitive agents it is worth to mention the double layered fringe-nucleus model proposed by William James. This model outlines the relation between what is already in the focus of attention and what is not. In the recent past it has already been suggested to use James's fringe as a viable model for cognition particularly by Bruce Mangan. Here, the main idea is that the fringe-nucleus model is not limited to the cognitive modeling but rather it shapes the relation between the conscious mind and the environment. The fringe zone could model the transition area between what is integrated inside the cognitive domain and the environment. In this paper, we explore the link between the fringe-nucleus model and an externalist, situated and embodied framework whereby the vehicles of cognition are spread so to comprehend the external world.
Towards Effective ‘Any-Time’ Music Tracking
Authors: Arzt Andreas  , Widmer Gerhard
Published: February 2025

The paper describes a new method that permits a computer to listen to, and follow, live music in real-time, by analysing the incoming audio stream and aligning it to a symbolic representation (e.g, score) of the piece(s) being played. In particular, we present a multi-level music matching and tracking algorithm that, by continually updating and evaluating multiple high-level hypotheses, effectively deals with almost arbitrary deviations of the live performer from the score – omissions, forward and backward jumps, unexpected repetitions, or (re-)starts in the middle of the piece. Also, we show that additional knowledge about the structure of the piece (which can be automatically computed by the system) can be used to further improve the robustness of the tracking process. The resulting system is discussed in the context of an automatic page-turning device for musicians, but it will be of use in a much wider class of scenarios that require reactive and adaptive musical companions.
Associations as First-class Elements
Authors: Bildhauer Daniel
Published: February 2025

Models in general and class diagrams as defined by the UML in particular play an important role throughout all steps of modern software development. However, the UML contains several modeling concepts which are not defined precisely and hence are used either rarely or in varying ways and with different semantics. In this article, an extension of n-ary associations as one of those concepts is presented including their refinement by specialization, subsetting and redefinition. DHHTGraphs are introduced as one realization of this extension treating associations and links as first-class objects. In particular, a metamodel and a possible implementation realizing association end refinement by association specialization are presented.
On Context Modelling in Systems and Applications Development
Authors: Heimbürger Anneli  , Kiyoki Yasushi  , Kärkkäinen Tommi  , Gilman Ekaterina  , Kim Kyoung-Sook  , Yoshida Naofumi
Published: February 2025

Context is a multi-dimensional concept. It is hard to define context generally for computer science. Which information is considered as context, which is not? Why are the certain context elements relevant for a certain case, but irrelevant for another? How to explain this to computers? Can computers learn these issues as humans do? In our paper we present different viewpoints to the concept of context and to context modelling starting from requirements engineering and ending up to multi-disciplinary education. Based on context related literature research and discussions in our paper, we can summarize that a complete and comprehensive definition and model of context is difficult to achieve and may not even be appropriate at all. However we can conclude that there is a common understanding that context always relates to an entity, context is used to solve a problem, context depends on the domain of use, context depends on time and context is evolutionary.
A Comparison Study for a Neural Network Based Embedded Appliance
Authors: Motto Ros Paolo
Published: February 2025

In a previous work [1] the design of a reader device for blind people was presented from the algorithmic standpoint. In this paper we will discuss the study, design and development of its evolution toward an embedded appliance. Two hardware platforms will be analyzed, considering their pros and cons respect to the target application, based on image processing algorithms and Artificial Neural Networks (ANNs). The comparison will take into account the available computational power, the power consumption, the ease of interfacing with other devices and the overall development cycle.
Types for Security Protocols
Authors: Focardi Riccardo  , Maffei Matteo
Published: February 2025

We revise existing type-based analyses of security protocols by devising a core type system for secrecy, integrity and authentication in the setting of spi-calculus processes. These fundamental security properties are usually studied independently. Our exercise of considering all of them in a uniform framework is interesting under different perspectives: (i) it provides a general overview of how type theory can be applied to reason on security protocols; (ii) it illustrates and compares the main results and techniques in literature; (iii) perhaps more importantly, it shows that by combining techniques deployed for different properties, existing type-systems can be significantly simplified.
Innovation in the Microfoundations of Governance: Explaining the Flaws in the UK New Labour Government's Reform of Public Services
Authors: Stoker Gerry
Published: February 2025

This chapter provides a UK case study of public service reform to illustrate how a microfoundational base premised on instrumental rationality – in particular a principal-agent framework – can extensively influence policy towards innovation in the governance of public services. It also provides evidence of the failure of the New Labour Government's reform program in the context of relatively benign conditions and argues that the failure was to a substantial degree because of the inadequacies of the microfoundations that guided the reform program. The chapter concludes by discussing the circumstances when microfoundations are most likely to impact on policymaking. It argues for a greater awareness by policymakers of their microfoundational assumptions and for the advantage of developing policy in a manner that gives due recognition to the plurality of microfoundations commonly used in the social sciences.
Privatization as Innovation in Governance in India
Authors: Bharti Nalin
Published: February 2025

Market-State interactions are quite interesting these days in dual preference economies like India, in which both the public and private sectors are equally active. The Market expects minimal interference from the State but the question is: does the market require assistance from the State or should the State leave the market alone? In this connection India is an interesting economy to observe new trends in the interrelationship between Market and State, where both are uncomfortable in decisionmaking, especially in the field of privatization. Another equally important question is: in which capacity does the State have its role? Does the responsibility of the State end or start after privatization? These questions are essential to answer because the Constitution of India places a very high degree of welfare responsibility on the State. This paper traces the unique and innovative responsibility of the state and the market to govern privatization properly.
Innovation in Local Governance: Decentralization and Citizen Participation in Bangladesh
Authors: Asaduzzaman Mohammed
Published: February 2025

Due to the tremendous growth of information technology, economic globalization and development and the increasing role of the third sector and civil society organizations, the innovation of public governance in developing countries can be considered an important policy issue in meeting the challenges of the 21st century. This chapter attempts to explain the major innovations in local governance during the various successive regimes in Bangladesh since 1971. Two major aspects of democratic local governance and good governance, such as decentralization and people's participation, have been examined in a descriptive and analytical manner. It has been found that despite many past reforms, decentralization of local governance and people's participation in local development have not taken place due to lack of political and bureaucratic will, the patron-client relationship, massive corruption, institutional incapability and conflicting political culture of the country. As a result, local governance institutions became a meeting place of the elites rather than of the local people and corruption remained endemic.
Modelling Intermolecular Structures and Defining Ambiguity in Gene Sequences using Matrix Insertion-Deletion Systems
Authors: Kuppusamy Lakshmanan  , Mahendran Anand  , Villemonte de la Clergerie Eric
Published: February 2025

Gene insertion and deletion are considered as the basic operations in DNA processing and RNA editing. Based on these evolutionary transformations, a computing model has been formulated in formal language theory known as insertion-deletion systems. Recently, in [6], a new computing model named Matrix insertion-deletion system has been introduced to model various bio-molecular structures such as hairpin, stem and loop, pseudoknot, attenuator, cloverleaf, dumbbell that occur at intramolecular level. In this paper, we model some of the intermolecular structures such as double strand languages, nick languages, hybrid molecules (with R-loops), holliday structure, replication fork and linear hybridization (ligated) languages using Matrix insertion-deletion system. In [2], the ambiguity in gene sequence was defined as deriving more than one structure for a single gene sequence. Here, we propose a different view of understanding the ambiguity in gene sequences: A gene sequence is obtained by more than one way such that their intermediate sequences are different. We further classify the ambiguity into many levels based on the components axiom, string (order of deletion/insertion) and contexts (order of the used contexts). We notice that some of the inter and intramolecular structures obey the newly defined ambiguity levels.
Experiments in Multicore and Distributed Parallel Processing using JCSP
Authors: Kerridge Jon
Published: February 2025

It is currently very difficult to purchase any form of computer system be it, notebook, laptop, desktop server or high performance computing system that does not contain a multicore processor. Yet the designers of applications, in general, have very little experience and knowledge of how to exploit this capability. Recently, the Scottish Informatics and Computer Science Alliance (SICSA) issued a challenge to investigate the ability of developers to parallelise a simple Concordance algorithm. Ongoing work had also shown that the use of multicore processors for applications that have internal parallelism is not as straightforward as might be imagined. Two applications are considered: calculating π using Monte Carlo methods and the SICSA Concordance application. The ease with which parallelism can be extracted from a single application using both single multicore processors and distributed networks of such multicore processors is investigated. It is shown that naïve application of parallel programming techniques does not produce the desired results and that considerable care has to be taken if multicore systems are to result in improved performance. Meanwhile the use of distributed systems tends to produce more predictable and reasonable benefits resulting from parallelisation of applications.