bluuebunny/crossref_metadata_2025 huggingface dataset:
Subchondral Bone Alterations Associated with Marrow Stimulation for Articular Cartilage Repair – Experimental Data and Clinical Implications
Authors: Orth Patrick  , Pape Dietrich  , Mainard Didier  , Cucchiarini Magali  , Madry Henning
Published: February 2025

Alterations of the subchondral bone have been associated with the clinical use of marrow stimulation techniques for articular cartilage repair. Such changes that have also been described in small and large animal models of cartilage defects include modifications of the subchondral bone microarchitecture, the formation of intralesional osteophytes, the appearance of subchondral bone cysts and the upward migration of the subchondral bone plate. Their extent varies among the different animal models and operative techniques and over time. Although marrow stimulation procedures are important options to treat small symptomatic cartilage defects, these emerging experimental and clinical data suggest that a possible deterioration of the underlying subchondral bone plate and subarticular spongiosa might be an additional, previously underestimated factor that influences the long-term outcome of articular cartilage repair following marrow stimulation. A deeper comprehension of the subchondral bone alterations associated with cartilage repair techniques is therefore essential to preserve and restore the entire osteochondral unit. The aim of this review is to give an overview on the effect of marrow stimulation procedures on the subchondral bone, focusing on recent knowledge gained from experimental animal models and clinical investigations of subchondral bone alterations following marrow stimulation.
Bioengineered Corneas: From Epithelial Cells Culture to 3D Models
Authors: Damour O.  , Burillon C.  , Auxenfans C.
Published: February 2025

The usual treatment of corneal tissue alteration is penetrating corneal grafting, but human cadaver donor corneas cannot always satisfy the demand for grafts and most particularly limbic deficiencies will always be rejected. It has led to the development of new therapeutic strategies for corneal repair. A breakthrough in tissue engineering occurred in 1975 when skin stem cells were successfully amplified in culture by Rheinwald and Green. A similar technique has been later adapted to the amplification of limbal then oral mucosa epithelial cells for the treatment of unilateral limbal epithelial stem cell deficiency (LSCD). For bilateral LSCD, oral mucosa epithelial cell sheets are now proposed. The sheets bring a functional epithelium able to push back conjunctivalization and neovascularisation.
Umbilical Cord Mesenchymal Stem Cells: Biology and Clinical Application
Authors: Liang Lu  , Han Zhong Chao
Published: February 2025

Mesenchymal stem cells (UC-MSC) are characterized by their multipotency, immunosuppression and hypo-immunogenicity. MSC transplant raises hope for treatment of various diseases including graft versus host disease, myocardial infarction and autoimmune disease. Human umbilical cord tissue is an abundant and accessible resource of MSC with no ethical concern, which takes great advantage in clinical application. We are dedicated in banking of clinical grade umbilical cord MSC (UC-MSC) and large-scale manufacturing of cell injection to insure the safety, efficiency and reproduction of UC-MSC as a cell drug.
Integrating OntoClean's Notion of Unity and Identity with a Theory of Classes and Types
Authors: Seyed A. Patrice
Published: February 2025

This paper provides a reformulation of OntoClean's notion of Unity and Identity within a formal theory of classes, and evaluates how the reformulations apply to BFO's theory of types, which was previously given within the same formal theory. For Unity, a definition schema and explication together express the underlying dependency between a unifying relation and some proper subrelation of the ‘part of’ relation, which together define how a particular of a class is a whole. For Identity, the notion of an identity criterion is ontologically grounded and formalized as an identity procedure. For both Unity and Identity the formulations are expressed within a sorted first-order logic, where staying within first-order expressivity proved difficult in past work. With our reformulations in hand we evaluate the primary type dichotomy for material entities of BFO, Object and ObjectAggregate. Together with the work that integrates OntoClean's notion of Rigidity with BFO's theory of types, this work augments ongoing efforts to build software designed to evaluate and standardize OBO Foundry candidate ontologies, of which BFO is the upper level ontology.
Finding Cross-browser JavaScript Codes using Sequential Pattern Mining
Authors: Fujitani Takahiro  , Kobayashi Takashi  , Atsumi Noritoshi  , Agusa Kiyoshi
Published: February 2025

Cross-browser support has become general requirements for Web sites. JavaScript, which is the most widely used client-side script, has several runtime engines. Because of differences between these engines each Web browser, developers must write alternative code to achieve the same behavior in each browser. We earlier proposed a method for finding simple alternative codes as function pairs from a code repository by using an itemset-based mining technique. In this paper, we propose a method for finding more complex alternative codes consisting of multiple statements, including assignment statements, by applying a sequential pattern mining technique. We assess the effectiveness of our method through the results of an experiment using JavaScript source files obtained from the Web.
Reward Function Learning for Dialogue Management
Authors: El Asri Layla  , Laroche Romain  , Pietquin Olivier
Published: February 2025

This paper addresses the problem of defining, from data, a reward function in a Reinforcement Learning (RL) problem. This issue is applied to the case of Spoken Dialogue Systems (SDS), which are interfaces enabling users to interact in natural language. A new methodology which, from system evaluation, apportions rewards over the system's state space, is suggested. A corpus of dialogues is collected on-line and then evaluated by experts, assigning a numerical performance score to each dialogue according to the quality of dialogue management. The approach described in this paper infers, from these scores, a locally distributed reward function which can be used on-line. Two algorithms achieving this goal are proposed. These algorithms are tested on an SDS and it is showed that in both cases, the resulting numerical rewards are close to the performance scores and thus, that it is possible to extract relevant information from performance evaluation to optimise on-line learning.
A SAT-Based Approach for Discovering Frequent, Closed and Maximal Patterns in a Sequence
Authors: Coquery Emmanuel  , Jabbour Said  , Sais Lakhdar  , Salhi Yakoub
Published: February 2025

In this paper we propose a satisfiability-based approach for enumerating all frequent, closed and maximal patterns with wildcards in a given sequence. In this context, since frequency is the most used criterion, we introduce a new polynomial inductive formulation of the cardinality constraint as a Boolean formula. A nogood-based formulation of the anti-monotonicity property is proposed and dynamically used for pruning. This declarative framework allows us to exploit the efficiency of modern SAT solvers and particularly their clause learning component. The experimental evaluation on real world data shows the feasibility of our proposed approach in practice.
An Analysis of Chaining in Multi-Label Classification
Authors: Dembczyński Krzysztof  , Waegeman Willem  , Hüllermeier Eyke
Published: February 2025

The idea of classifier chains has recently been introduced as a promising technique for multi-label classification. However, despite being intuitively appealing and showing strong performance in empirical studies, still very little is known about the main principles underlying this type of method. In this paper, we provide a detailed probabilistic analysis of classifier chains from a risk minimization perspective, thereby helping to gain a better understanding of this approach. As a main result, we clarify that the original chaining method seeks to approximate the joint mode of the conditional distribution of label vectors in a greedy manner. As a result of a theoretical regret analysis, we conclude that this approach can perform quite poorly in terms of subset 0/1 loss. Therefore, we present an enhanced inference procedure for which the worst-case regret can be upper-bounded far more tightly. In addition, we show that a probabilistic variant of chaining, which can be utilized for any loss function, becomes tractable by using Monte Carlo sampling. Finally, we present experimental results confirming the validity of our theoretical findings.
Choosing Combinatorial Social Choice by Heuristic Search
Authors: Li Minyi  , Bao Vo Quoc
Published: February 2025

This paper studies the problem of computing aggregation rules in combinatorial domains, where the set of possible alternatives is a Cartesian product of (finite) domain values for each of a given set of variables, and these variables are usually not preferentially independent. We propose a very general heuristic framework SC* for computing different aggregation rules, including rules for cardinal preference structures and Condorcet-consistent rules. SC* highly reduces the search effort and avoid many pairwise comparisons, and thus it significantly reduces the running time. Moreover, SC* guarantees to choose the set of winners in aggregation rules for cardinal preferences. With Condorcet-consistent rules, SC* chooses the outcomes that are sufficiently close to the winners.
Width and Serialization of Classical Planning Problems
Authors: Lipovetzky Nir  , Geffner Hector
Published: February 2025

We introduce a width parameter that bounds the complexity of classical planning problems and domains, along with a simple but effective blind-search procedure that runs in time that is exponential in the problem width. We show that many benchmark domains have a bounded and small width provided that goals are restricted to single atoms, and hence that such problems are provably solvable in low polynomial time. We then focus on the practical value of these ideas over the existing benchmarks which feature conjunctive goals. We show that the blind-search procedure can be used for both serializing the goal into subgoals and for solving the resulting problems, resulting in a ‘blind’ planner that competes well with a best-first search planner guided by state-of-the-art heuristics. In addition, ideas like helpful actions and landmarks can be integrated as well, producing a planner with state-of-the-art performance.
Bad equilibria (and what to do about them)
Authors: Wooldridge Michael
Published: February 2025

I begin by arguing that the notion of economic equilibrium is an important analytical tool with which to understand the behaviour of today's networked computer systems. This is because the behaviours that such systems exhibit are in part a function of the preferences and desires of system participants; this gives such systems the flavour of an economic system. In economics, an equilibrium is a steady-state situation, which obtains because no participant has any rational incentive to deviate from it. Equilibrium concepts are arguably the most important and widely used analytical weapons in the game theory arsenal. The concept of Nash equilibrium in particular has found a huge range of applications, in areas as diverse and seemingly unrelated as evolutionary biology and moral philosophy. However, there remain fundamental problems associated with Nash equilibria and their application, which must be considered if we want to apply them to the analysis of computer systems. First, there may be multiple Nash equilibria, in which case, how should we choose between them? Second, some equilibria may be undesirable, in which case, how can we avoid them? In this essay, I will introduce work that we have done addressing these problems from a computational/AI perspective. Assuming no prior knowledge of game theory or economic solution concepts, I will discuss various ways in which we can try to engineer a scenario so that desirable equilibria result, or else engineer out undesirable equilibria.
Detecting Human Patterns in Laser Range Data
Authors: Varvadoukas Theodoros  , Giotis Ioannis  , Konstantopoulos Stasinos
Published: February 2025

In this paper we present a novel method for detecting humans from laser range scans, where the core idea is to treat neither individual frames, which hold so little information that the task is impossible, nor motion patterns, as is the case with tracking methods. Rather, we map short time series of planar scans to 3D objects with time as the depth dimension; we then cluster and classify these 3D objects using unsupervised and off-line training, circumventing the need for predefining and parametrizing motion models.
Intermediary Local Consistencies
Authors: Petit Thierry
Published: February 2025

We propose a new definition for characterizing levels of consistency. A perspective is to provide new tools for classifying filtering algorithms, including incomplete algorithms based on the semantics of constraints.
The Consistency of Majority Rule
Authors: Porello Daniele
Published: February 2025

We propose an analysis of the impossibility results in judgement aggregation by means of a proof-theoretical approach to collective rationality. In particular, we use linear logic in order to analyse the group inconsistencies and to show possible ways to circumvent them.
VOI-aware MCTS
Authors: Tolpin David  , Shimony Solomon Eyal
Published: February 2025

UCT, a state-of-the art algorithm for Monte Carlo tree search (MCTS) in games and Markov decision processes, is based on UCB1, a sampling policy for the Multi-armed Bandit problem (MAB) that minimizes the cumulative regret. However, search differs from MAB in that in MCTS it is usually only the final “arm pull” (the actual move selection) that collects a reward, rather than all “arm pulls”. In this paper, an MCTS sampling policy based on Value of Information (VOI) estimates of rollouts is suggested. Empirical evaluation of the policycomparison to UCB1UCT is performed on random MAB instances as well as on Computer Go.
A Reinforcement Learning Approach to Optimize the longitudinal Behavior of a Partial Autonomous Driving Assistance System
Authors: Pietquin Olivier  , Tango Fabio
Published: February 2025

The Partially Autonomous Driving Assistance System (PADAS) is an artificial intelligent co-driver, able to act in critical situations, whose objective is to assist people in driving safely, by providing pertinent and accurate information in real-time about the external situation. Such a system intervenes continuously from warnings to automatic intervention in the whole longitudinal control of the vehicle. This paper illustrates the optimization process of the PADAS, following a statistical machine learning methods - Reinforcement Learning - where the action selection is derived from a set of recorded interactions with human drivers. Experimental results on a driving simulator prove this method achieves a significant reduction in the risk of collision.
An Interface for Browsing Electronic Novels Using Attractiveness Map
Authors: Murai Souichi  , Ushiama Taketoshi
Published: February 2025

Today, the electronic book (e-book) market is growing rapidly and people can choose e-books that they would like to read from a large amount of e-books on the Internet. In order to support people to select books, many techniques for searching and recommending books have been proposed. However the user would have to decide whether each book in candidates is worth reading. Performing a query on a book is effective when they know what they want to know, so it is not effective at unread-novel. In this paper, we propose a browsing interface for supporting a user to decide whether he/she reads an e-book novel or not effectively. Our interface allows the user to select browsing sentences in the novel efficiently by an attractiveness map, which visualizes the transition of attractiveness in the novel according to its story flow. Characteristic keywords are assigned to characteristic points on the attractiveness map and the user can grasp an overview of the story flow effectively.
A study on the variables related to software quality: a data mining based approach
Authors: Campos Fábio Bianchi  , Ferneda Edilson  , Cornelio Nildo Nunes  , Filho Aluizio Haendchen
Published: February 2025

Advances in information technology have made possible ac-cumulation of large amount of data arising from information systems. This fact enabled the emergence and growth of research on Data Min-ing (DM), which aims primarily at identifying new and useful patterns in databases. Recently, software quality has received attention among areas of application. The quality of software has become an important issue for the maintenance and customer attraction for businesses and can be considered a competitive weapon. On the other hand, the quality of decision making in project management software is closely related to information available about the process of organizational development. This information can be stored in data warehouses to be analyzed and interpreted using techniques of DM. This paper describes an application of DM bases of quality metrics for software products, which are aimed at identifying the variables of the development process that would mostly affect the error rate during the phases of testing, approval, and production. The study of the target company has a high level of stand-ardization of processes. The results obtained in the models indicated a strong or moderate correlation of some variables of the process with product quality, which may be the target of management attention in order to: (i) improve the overall quality of the development process, (ii) Advances in Knowledge-Based and Inreduce the error rate in the systems developed and (iii) promote greater customer satisfaction.
CommunyFilm: A social network for collaborative video creation
Authors: Prado-Gesto Diego  , Gil Pons Eva
Published: February 2025

At present, web users have the need to create their own professional content and share with others. Under this situation, CommunyFilm arises and it is based on the collaborative creation of audiovisual products. CommunyFilm establishes a new mode of producing contents that differs a lot from the traditional way in economic, social and artistic terms: reducing production costs, generating a democratisation in the creative process -allowing any person getting involved in the project-, and breaking some of the deepest principles in the audiovisual context. To carry out this idea, a software platform is needed in order to allow people to participate in community projects and get in touch with other users.
Obtaining Shape from SEM Image Using Intensity Modification via Neural Network
Authors: Iwahori Yuji  , Shibata Kazuhiro  , Kawanaka Haruki  , Funahashi Kenji  , Woodham Robert J.  , Adachi Yoshinori
Published: February 2025

This paper proposes a new approach to recover 3-D shape from a SEM image. When SEM image is used to recover 3-D shape, one can apply the algorithm based on the solving the Eikonal equation with Fast Marching Method (FMM). However, when the vertical and oblique light source image is observed, the correct shape cannot be obtained by the usual one-pass FMM. The approach proposes a method to modify the original SEM image with intensity modification via neural network so that the correct 3-D shape could be obtained with FMM. The proposed approach is demonstrated through computer simulation and real experiment.
Impact of Analysis Circularity: a Case Study in Cocaine Addiction detection on MRI
Authors: Termenon M.  , Fernández E.  , Barrós-Loscertales A.  , Bustamante J.C.  , Ávila C.
Published: February 2025

The inclusion of circularity in the analysis of neuroimaging data can lead to some bias in the results, often leading to optimistic conclusions. In this study, we show the differences in results obtained performing an experiment with no circularity and the same one with circularity effect (double dipping). We obtain discriminant features from structural magnetic resonance images (MRI) to train and test classifiers able to discriminate cocaine dependent patients from healthy subjects. Feature selection is done computing Pearson’s correlation between voxel values across subjects with the subject class as control variable. Feature selection processes with double dipping obtain higher accuracy and specificity values.
Ontology Integration by Using Context and Ontology Violation Check
Authors: Wu Dan  , Håkansson Anne
Published: February 2025

By integrating ontologies, knowledge represented in these ontologies can be extended and reused for purposes like building new ontologies, composing advanced services on the semantic web and sharing knowledge. The ontology integration is a difficult task because of semantic barriers. In this paper, an approach of building context for ontology integration is presented. The integration of the ontologies is carried out by using context and ontology violation check. To provide context for the integration, context rules are utilized for interpretation and reasoning across ontologies. The ontology violation check is applied in the process of building ontology intersection under the open world assumption. As a result of the integration, an ontology intersection is produced, which is larger than the intersection of entities, but not larger than the union of the original entities.
Deterministic Approach for Biclustering of Co-Regulated Genes from Gene Expression Data
Authors: Roy S  , Bhattacharyya D K  , Kalita J K
Published: February 2025

This paper presents an expression pattern based biclustering technique for grouping both positively and negatively regulated genes together as co-regulated genes from microarray expression data. Most interesting variants of this problem are NP-complete requiring either large computational effort or the use of lossy heuristics to short circuit the calculation. Our approach deterministically finds all biclusters using a non-greedy approach in polynomial time. Various real datasets have been used for experiments and results are excellent.
Building Knowledge for Characterization of the Bad Debt Customers in the Mail Order Industry with Random Forest
Authors: Takahashi Masakazu  , Azuma Hiroki  , Ikeda Masanori  , Tsuda Kazuhiko
Published: February 2025

This paper presents investigating the customercharacteristics from the bad debt list ofa mail order corporation. So far, suchinvestigations have not made intensively, especiallyprivate defaultrisks and conventional method for predicting such risks depend on the employee's working experiences. For these reason, at first,we observedtheactual bad debt list from amail order corporationand analyzedsales data. From the results of the observation, we makeuse of the machine learningmethod to characterizethe potential bad debt customers. Intensive research hasrevealed that the characteristicsof customers, who might fall into the bad debt list, popularitems and so on. This method willmake use forthe revenue expansion;improvement of collectionof the bad debts.
A logic for strategies in persuasion dialogue games
Authors: Kacprzak Magdalena  , Budzynska Katarzyna  , Yaskorska Olena
Published: February 2025

The aim of the paper is to extend the syntax and semantics of the AGnlogic with components allowing the representation and verification of strategies in persuasion dialogue games. The AGnlogic was introduced to express beliefs and persuasive actions of agents, and then it was used to perform model checking in persuasive inter-agent communication. In this paper, we enrich AGnby adapting strategy operators from Alternating-time Temporal Logic and adding new ones to allow reasoning about the success and persuasive power of dialogues.
An analysis and hypothesis generation platform for heterogeneous cancer databases
Authors: Quinlan Philip Roy  , Thompson Alastair  , Reed Chris
Published: February 2025

The field of cancer research is now generating vast amounts of data from a variety of high throughput techniques and these have helped to define cancers based on their genetic foundations. As this knowledge on the processes and underlying genetics of cancer improve, these should be factored back into the research and analyses conducted by other researchers. Managing this volume of data, often conflicting, is becoming increasingly challenging for researchers. This work demonstrates an innovative application of argumentation theory within cancer research by providing a framework to accommodate missing data, address critical questions and generate hypotheses. The prototype system has been validated to demonstrate it identifies the same interesting interactions and molecules as researchers, even when certain key data was deliberately withheld from the system.
Pure flour in your bag: Governmental rationalities of camera surveillance in Sweden
Authors: Björklund Fredrika
Published: February 2025

Surveillance is an important governance technique of modern societies and is linked to particular governmental rationalities. This article examines the Swedish policy on camera surveillance, using the analytical framework of governmentality, the art of government, in advanced liberal societies as its theoretical framework. The focus is on three features that characterise current developments in the Swedish policy. These are labelled situational prevention, generalisation of distrust and the significance of the informed citizen. The study shows how prevention, i.e. situational prevention, was successfully introduced as a main rationale for monitoring only after the technology had been in place for some years. Monitoring as a form of general situational prevention, the congruent generalised distrust that affects the public and the Swedish requirement to inform citizens about cameras are viewed as elements of a governmental rationality based on the notion of the autonomous, free and self-responsible subject. Accordingly, the popular idea that camera surveillance is an indicator of an expanding security state must be modified.
The Impact of inclusive e-government applications
Authors: Nshimbi Isabel
Published: February 2025

Three e-government applications, e-democracy, e-participation and e-voting are discussed and an analysis of the impact that these inclusive applications have had on the general population, where they have been used is given. As the terms are closely linked, they are further elaborated upon as they have impact on each other. E-voting implies e-participation which would further imply e-democracy. The impact of these applications at various levels of society mainly government, civil society and non-governmental organisations as well as on the general population is considered, and whether these applications have led to governments being able to reach a bigger part of the population through an increase in participation in civic activities and achieved greater turnout, for example, in elections. The criteria for assessing the impact of the applications are: (1) Demand for the applications and the need to access them; (2) Accessibility of the applications; (3) Availability of national e-strategies; (4) Quality of the content being provided and (5) Cost of providing and accessing the applications available. The discussion ends with what the expected or preferred impact would be as well as specific proposals and strategies that may be used for effective impact of these specific applications.
Internet Access Commons
Authors: Gamboni Jacques
Published: February 2025

As soon as Internet penetrated the public area, it became a whole new world of freedom and thanks to its extraterritoriality mostly escaped existing legal rules. It is still a huge and little explored territory, providing to some pioneers immensely profitable opportunities. Therefore, it is not surprising that the Private Sector is actively striving to enclose this newfound land in order to preserve existing and future benefits. Considering Internet's tremendous impact on all aspects of the social life, governments try by different means to govern it, with little effectiveness. The concept of Internet Access Commons introduces a new participant in the game: the Third Sector, and a renewed governance model, the Commons which together allow for a complete paradigm change. Technically, the FTTH based Internet access Commons relies on a pure horizontal topology where each of the multiple points of the network form its centre; it does not know any owner, meaning it cannot be controlled by third parties nor can it be sold. On the contrary, being open and respectful of standards, it allows each of the interested value added service providers (i.e. infrastructure builder, service, maintenance of the physical network, acquisition, distribution and management of applications and services, customers management, local communities, etc.) to stand out against in an open market not dominated by giants protected in their vertical and enclosed structures.
E-Tourism: A Catalyst for Promoting the East African Community as Competitive Tourist Destination
Authors: Kagoda-Batuwa Sarah
Published: February 2025

The East African Community (EAC) Partner States have a shared vision and have agreed in principle to develop a regional strategy to market and promote the region as “a single tourist destination.” The EAC tourism destination has a comparative advantage of inherited natural resources, core resources and attractors ranging from game parks; cultural and historical sites; mountains; coastal zones and waterfalls; game viewing and gorilla tracking. E-Tourism plays a critical role for the competiveness of tourism organizations and destinations and for the entire tourism industry as a whole. However, application of e-tourism that would enable global visibility of the EAC destination is yet to be fully utilized. There is minimal online information about the EAC tourist destinations and attractions, and online booking is still a challenge. The chapter discusses the global and EAC trends in tourism, the tourist destinations and attractions in East Africa. E-tourism application and its catalystic role in promoting and enhancing the competitiveness of the EAC as a single tourist destination is examined and analysed and challenges and prospects of adopting e-tourism discussed. E-tourism strategic and operational recommendations for promoting EAC as a single competitive tourist destination are put forward.
An Introduction to Software Mining
Authors: Kennard Richard  , Leaney John
Published: February 2025

Software mining is related to both data mining and reverse engineering. It is focused on mining software artefacts such as code bases, program states and structural entities for useful information related to the characteristics of a system. This paper provides an introduction to the field. It first reviews a representative selection of the ways software mining has been applied. It then divides software mining into three subcategories and explains each one in detail. Finally this paper summarises some of the advantages and limitations of software mining, both now and in the future. These advantages and limitations have been informed by the author's own research applying software mining to the field of User Interface generation.
Automatic Generation of Specialized Dictionaries Using the Dictionary Writing System EELex
Authors: Kallas Jelena  , Langemets Margit
Published: February 2025

EELex is a web-based dictionary writing system with Estonian language support including various linguistic resources necessary for dictionary making [1, 2]. Nearly 40 dictionaries of different types (monolingual and bilingual, general and learners' dictionaries, etc.) with standard XML markup make EELex a multipurpose lexicographic database. Using the example of the active Basic Estonian Dictionary [3], this paper describes from the point of a lexicographer the functions of EELex that allow various specialized dictionaries to be generated. We focus on the generation of syntagmatic dictionaries, mainly the valency and collocation dictionaries.
Noisy-Channel Spelling Correction Models for Estonian Learner Language Corpus Lemmatisation
Authors: Sirts Kairit
Published: February 2025

Morphological analysis is an important task in Estonian learner language studies that gives information about the words and forms used by the learners. Because of the spelling errors frequently occurring in language learner texts, these texts should undergo some error correction step before applying the conventional morphological analysis tools because the morphological analyser fails to find the correct analysis for the misspelled words. In this paper we compare several different spelling correction models with the aim of improving the lemmatisation accuracy of learner language texts. Experiments show that the simplest non-word noisy-channel spelling correction model with a disambiguation model applied on top of the morphological analyser output performs the best while some of the more complicated models even fail to beat the baseline that does not include any spelling correction.
Multimodal Feedback Signaling in Finnish
Authors: Toivio Emmi  , Jokinen Kristiina
Published: February 2025

This paper discusses multimodal feedback signalling in Finnish first encounter conversations, especially the use of head nodding to signal shared understanding of the presented information. The goal of the paper is to study the correlation between gestures and speech, and to build a model to describe to which extent head movements correlate with verbal feedback. We distinguish single and repeated nodding, as well as up-nods and down-nods, and hypothesise that downnods are used as backchannels while up-nods signal unexpected information.
In-domain Data FTW
Authors: Fishel Mark
Published: February 2025

We describe experiments on Estonian-English statistical machine translation with a strong emphasis on domain adaptation. We show that disregarding text domains can harm a translation system and that even a small in-domain corpus can lead to significant translation quality improvements.
Using a RGB-D camera for 6DoF SLAM
Authors: Muñoz Jose  , Pastor Daniel  , Gil Pablo  , Puente Santiago  , Cazorla Miguel
Published: February 2025

This paper presents a method for fast calculation of the egomotion done by a robot using visual features. The method is part of a complete system for automatic map building and Simultaneous Localization and Mapping (SLAM). The method uses optical flow in order to determine if the robot has done a movement. If so, some visual features which do not accomplish several criteria (like intersection, unicity, etc,) are deleted, and then the egomotion is calculated. We use a state-of-the-art algorithm (TORO) in order to rectify the map and solve the SLAM problem. The proposed method provides better efficiency that other current methods.
Intelligent Building Energy Management through holistic knowledge based approach
Authors: Anzaldi Gabriel  , Corchero Aitor  , Gutu Dan  , Marinov Milan  , Dibley Michael James  , McGlinn Kris
Published: February 2025

The continuous rise of energy consumption, energy prices and the harshness of natural resources have generated a change in people and companies' behavior towards energy efficient awareness. Currently, building automation controls commercial and residential buildings to try to satisfy energy saving goals. However, the use of this kind of systems does not assure an optimal energy behavior. An intelligent energy management approach based on Artificial Intelligence techniques arise as a most advantageous solution to improve the benefits provided for new control systems. This paper describes an approach, developed under the EU project called KnoHolEMKnoHolEM: Knowledge-based Energy Management for public buildings through holistic information modeling and 3D visualization – EU project, FP7-2011-NMP-ENV-ENERGY-ICT-EeB, 09/11 – 08/14
Information-Theoretic Secure Multiparty Computation
Authors: Maurer Ueli  , Zikas Vassilis
Published: February 2025

Most of this book has considered two-party and multiparty computation with security with (unfair) abort. This security notion allows the adversary to force the honest parties to abort even depending on the outputs of corrupted parties. (Note, however, that the adversary is not allowed to bias the output of honest parties in any other manner.) This relaxation of security is necessary if one wishes to tolerate arbitrarily many corruptions. A further relaxation considers computational security, where the adversary is assumed to be computationally bounded, e.g., probabilistic polynomial time. In this setting, any circuit can be securely realized even when arbitrarily many parties are corrupted, as long as one is willing to sacrifice fairness and robustness.
Experiences Implementing Developed Industrial Software for the Center Quality Modeling of Slabs in Metalography
Authors: Praks Pavel  , Kotas Petr  , Jagla Pavel  , Válek Ladislav
Published: February 2025

Recognizing the central quality of a metallographic sample represents, for a metallographic laboratory expert, a challenging task involving analyzing the size and number of defects at the evaluated segment. In order to help human experts, a software tool was developed for machine evaluation of these metallographic samples. The aim of the paper is to present the properties of the developed software and to demonstrate its practical application in industry. The developed software tool is based on the machine recognition of small but important non-homogeneity objects located at the central part of the metallographic sample and on a statistical evaluation of the properties of these extracted central objects. Because the central objects are very similar to noise, machine recognition is not straightforward. However, this paper contains promising results of comparing machine and expert assessments of an industrial image database of digitized metallographic samples. The image database is provided by the research department of ArcelorMittal Ostrava, a.s., in the Czech Republic.
Towards a smart State? Inter-agency collaboration, information integration, and beyond
Authors: Gil-Garcia J. Ramon
Published: February 2025

Information technologies (IT) can now be considered one of the key components of government administrative reform. The potential is even greater when working across organizational boundaries. Unfortunately, inter-agency collaboration appears to face an even greater number of challenges than similar IT initiatives within a single organization. The challenges include data and technological incompatibility, the lack of institutional incentives to collaborate, and the politics and power struggles around a pervasive silo structure in most governments, among many others. This paper argues that there are clear trends towards greater inter-organizational collaboration, information sharing, and integration, which could lead, in the near future, to what might be called a smart State. The paper starts discussing the promises and challenges that have already been identified for government information sharing and integration initiatives. Then it describes two trends in terms of inter-organizational collaboration and information technologies in government settings. The paper ends by providing reflections about the technical and political feasibility, as well as the social desirability, of an integrated virtual State in which the executive, legislative, and judicial branchesFor this paper, the description of government is based on a federal system with three branches of government (executive, legislative, and judicial) and multiple levels of government (national, regional, and local). The reader is invited to apply these ideas to different government settings.
Software Bug Ontology Supporting Bug Search on Peer-to-Peer Networks
Authors: Tran Ha Manh  , Le Son Thanh  , Ha Synh Viet Uyen  , Huynh Tu Kha
Published: February 2025

This paper presents a semantics-based bug search system that allows users to solve bugs by searching similar bug reports on peer-to-peer networks. This system uses a bug schema to obtain and format bug reports from different bug tracking systems. The bug schema modified from the existing bug schemas supports several properties for search purpose. The system also extends the Gnutella protocol to provide search operations on peers. We have implemented and experimented the prototyping system on a distributed computing testbed. The paper also includes performance evaluation and lessons learned.
Multi-Level Agent-Based Modeling: a Generic Approach and an Implementation
Authors: Võ Đúc-Ân  , Drogoul Alexis  , Zucker Jean-Daniel
Published: February 2025

Multi-level agent-based modeling (ML-ABM) requires representing agents at different levels of representation in the same model w.r.t. to time, space and behavior. This paper describes a generic and operational proposal for ML-ABM. First, a generic meta-model for ML-ABM and an associated “morphogenesis” operation are introduced. The generic meta-model allows a modeler to describe multiple levels of representation in the same model, while the “morphogenesis” operation supports agent change of representation level dynamically during the course of the simulation. Second, in order to demonstrate how to operationalize the proposal, we present an implementation of the generic meta-model and the “morphogenesis” operation in the GAMA ABM platform. Finally, we illustrate how our proposal, implemented in the GAMA platform, allows modeler in practice to develop a multi-level agent-based model. To do so, we rely on the famous “Boids” model of Craig Reynolds and show how the modeler can easily introduce a new level of representation of an entity to transform the model into a two-levels agent-based model without having to modify the existing model.
Multimedia Support Systems as Assistive Technology for Hearing Impaired Students
Authors: Poobrasert Onintra  , Cercone Nick
Published: February 2025

Multimedia technology, applied to education, typically involves the use of computer assisted instruction in conjunction with other media and is very helpful when incorporated in an intelligent tutoring system. The use of computer animation and colorful graphics may also aid in motivation and attention processes for children. Although the computer cannot replace a teacher in the classroom, when used as supplement, multimedia use in the classroom provides undeniable benefits for both teachers and students. In addition, multimedia is interactive and synthesizes sound, images, and text. Therefore it is also known that multimedia are an excellent technology when using with students with disabilities as an assistive technology. Assistive technology is used by individuals with disabilities in order to perform functions that might be difficult or impossible. It also refers to products, devices, or equipment, whether acquired commercially, modified or customized, used to maintain, increase or improve functional capabilities of individuals with disabilities. Hence, findings from this study emphasize multimedia support systems such as our program extended teachers' reach for hearing impaired students in Thailand. Additionally, study evidence results indicated our program assists students to learn more successfully when they are learning difficult words.
Sensor Network Analytics for Intelligent Facility Management
Authors: Kriksciuniene Dalia  , Pitner Tomas  , Kucera Adam  , Sakalauskas Virgilijus
Published: February 2025

The article addresses the problem of intelligent monitoring of facility management data flows collected from heterogeneous sources, including low-level data of sensors and probes, geographical indicators, scheduling and personal identification systems. We suggest the framework of analytical model, based on deriving descriptors which could sentinel the level of thermal comfort of working environments. The model aims to facilitate process of extracting essential characteristics of facility management for detecting dependencies and observing anomalies. The performance of the model was tested by experimental analysis of facility management of the university campus, designed for exploring how various environment variables affect temperature in the lecture rooms, equipped by the air conditioning devices.
Support System for Analyzing the Solution Process for Network Construction Exercises with Virtual Machines
Authors: Tateiwa Yuichiro  , Noumi Junya  , Yamamoto Daisuke  , Takahashi Naohisa
Published: February 2025

When evaluating student network construction exercises with virtual machines, teachers must spend so much time analyzing student work that they interrupt the students' progress. We propose a support system to help teachers analyze the solution process. Our LiNeS system has the following functions. It collects students' virtual management network (VMN) operations and results and stores them in a database on the network. It then generates graphs that illustrate students' progress according to dependence of correct operations for problem statements and students' VMN operations. Lastly, LiNeS displays progress graphs, operational histories, and ”next correct” operations on teachers PCs on the network.
Concept of the intelligent energy technology integration to support sustainable development of energy utilities, energy savings and CO
Authors: Podgornik Ales  , Sucic Boris  , Urosevic Ljubisa
Published: February 2025

This paper presents a concept of an analytical engine for real time energy consumption analysis on the utility and consumer level which should enable smooth integration of new energy technologies and services in the complex environment, industrial or urban. Proposed concept aims at supporting energy utilities in optimizing energy performance on both supply and demand sides of their operations. After the validation and in order to achieve significant energy savings proposed concept should be realized in platform which should provide its users with: (i) real time energy consumption data gathered on one minute interval using smart meters, (ii) analysis and contextualization of energy consumption (including benchmarking) and (iii) knowledge sharing system for communicating results and enabling active cooperation between energy utilities and their consumers. Early detection of unnecessary energy consumption and contextualization of energy consumption should enable elimination of unnecessary leakages and should be the first visible result which would boost the confidence between partners. With the support of the proposed concept, energy utilities should become the key promoters of new energy technologies and support final consumers in their exploitation. The proposed concept should be realized as a platform with the modular architecture, allowing future expansion of user's portfolio and inventory management (new measures, technologies, different industries, urban districts and regions).
Coping with Disruptions in Public Tram Systems: Cases in Germany, China and the United States
Authors: Fang Yan  , Durach Christian F.  , Zeng Amy Z.  , Hou Jing
Published: February 2025

Trams are reviving in many regions of the world due to its low carbon emission and better utilization of resources. However, this above-ground rail system is prone to unexpected disruptions such as vehicle breakdowns, track misalignment, power outages, and natural disasters. The fast response to disruptions is important for continuous operations of tram systems and provision of high-quality passenger service. This research is inspired by the tram system operations in cities of China, Germany and the United States with respect to their strategies for dealing with disruptions, particularly the collaboration strategy with taxi companies to provide quick replacement service, as practiced in Germany. Comparisons between the tram systems from different regions have been made to find indicators for adopting different strategies. The case study of disruption handling methods in public transport system will provide managerial insights for both academic and practical directions.