bluuebunny/crossref_metadata_2025 huggingface dataset:
Motivated Agents in Virtual Worlds
Authors: Avradinis Nikos  , Anastassakis George  , Panayiotopoulos Themis
Published: February 2025

A basic requirement for intelligent virtual agents is believability, which largely consists in demonstrating autonomous behavior, consistent with the agents' personality and world conditions. This requires a mechanism to dynamically generate agents' goals and behavior. When no external stimulus is present, the agent should still be able to function coherently, due to self-motivation, dependent on internal factors. The concept of motivation has already been investigated by research works on intelligent agents, trying to achieve autonomy. The current work presents an architecture and model for action selection and goal generation in intelligent virtual agents, using the concept of motivations. Based on biopsychological needs theories, we present a motivational approach to represent human needs and produce emergent behavior through motivation synthesis.
System Prototype Generation Tool for Requirements Review
Authors: Saito Shinobu  , Hagiwara Jun
Published: February 2025

Recently, many system development projects have been using a screen prototype. On requirements definition phase, screen prototyping is effective to decrease some troubles, which are misunderstanding, lack of requirements, and conflict among requirements and so on. On the other hand, there are some problems caused by using a screen prototype. A screen prototype has been mainly used to review system's user interface requirements. Therefore, it could be difficult to review other type of requirements (i.e. requirement about interaction-process between system and user and decision rule which system executes). This paper proposes a system prototype generation tool which transforms three requirements artifacts into system prototype. Three requirements artifacts are business process, business rule and user interface. We also adapt this tool to the requirements definition phase of system development project. As a result of the case study, we introduce that the proposed tool is helpful to review requirements precisely and detect requirements errors.
Towards a Semantic Classifier Committee based on Rocchio
Authors: Albitar Shereen  , Fournier Sébastien  , Espinasse Bernard
Published: February 2025

This paper concerns supervised classification of text. Rocchio, the method we choose for its efficiency and extensibility, is tested on three reference corpora “20NewsGroups”, “OHSUMED” and “Reuters”, using several similarity measures. Analyzing statistical results, many limitations are identified and discussed. In order to overcome these limitations, this paper presents two main solutions: first constituting Rocchio-based classifier committees, and then using semantic resources (ontologies) in order to take meaning into consideration during text classification. These two approaches can be combined in a Rocchio-based semantic classifier committee.
Planning and Scheduling in Hybrid Domains
Authors: Chintabathina Sandeep
Published: February 2025

In this paper we present an Action Language-Logic Programming based approach to solving planning and scheduling problems in hybrid domains - domains that exhibit both discrete and continuous behavior. We use action language H to represent the domain and then translate the resulting theory into a logic program. In this way, we reduce the problem of finding solutions to planning and scheduling problems to computing models of logic programs. We present the syntax of H and model a planning and scheduling example in H. We show how to translate the resulting H theory into an equivalent logic program. We compute the models of the resulting program using EZCSP, a solver which allows us to reason about constraints over reals and compute solutions to complex planning and scheduling problems. Results have shown that our approach can be applied to any planning and scheduling problem in hybrid domains.
Combining Voting Rules Together
Authors: Narodytska Nina  , Walsh Toby  , Xia Lirong
Published: February 2025

We propose a simple method for combining together voting rules that performs a run-off between the different winners of each voting rule. We prove that this combinator has several good properties. For instance, even if just one of the base voting rules has a desirable property like Condorcet consistency, the combination inherits this property. On the other hand, some important properties can be lost by the introduction of a run-off, including monotonicity and consistency. In addition, we prove that combining voting rules together in this way can make finding a manipulation more computationally difficult.
Context-Based Search in Software Development
Authors: Antunes Bruno  , Cordeiro Joel  , Gomes Paulo
Published: February 2025

Software developers usually spend a large amount of time navigating their own source code or searching for a specific source code artifact they need to work with. We propose a context-based search approach that focuses in the source code artifacts that exist in the workspace of the developer. These artifacts are stored in a knowledge base and represented using ontologies. The contextual information of the developer is used to rank the search results according to their relevance for the developer. The results of an experiment performed with two groups of developers show that our approach has a positive impact in retrieving relevant artifacts for the developer, helping them find what they need more quickly and easily.
A Semantic Clinical Decision Support System: conceptual architecture and implementation guidelines
Authors: Sanchez Eider  , Toro Carlos  , Artetxe Arkaitz  , Graña Manuel  , Carrasco Eduardo  , Guijarro Frank
Published: February 2025

Clinical Decision Support Systems (CDSS) are computer applications that focus on assisting medical decisions required during clinical tasks. Although CDSS have been extensively studied for more than 30 years, their use is not broadly extended yet in daily clinical practice. Identified challenges of CDSS include (i) automating decision support, (ii) clinical workflow integration, (iii) ability of the system to be maintained and extended, (iv) timely advice and (v) evaluation of decisions effects and costs. In this paper, we hypothesize that Knowledge Engineering techniques and semantic technologies could be applied to CDSS in order to overcome the current identified challenges. We present a generic architecture for a Semantic CDSS, which we call SCDSS, and implementation guidelines for the breast cancer domain. Our approach follows a cyclic-federated paradigm allowing the reutilization of knowledge gathered at every stage of the clinical cycle.
The Effectiveness of Three Communication Methods in a Realtime KJ Method Creativity Support Groupware
Authors: Viriyayudhakorn Kobkrit  , Kunifuji Susumu
Published: February 2025

Team creativity is essential to successful products. Creativity support groupware is invented to stimulate team creativity by allowing teams to communicate and to perform group creative techniques over geographic distances and different time availabilities. Since the intensive discussion among members are needed to derive creative ideas, communication methods in creativity support groupwares have a great impact to team creativity. Based on 90 KJ charts constructed by 30 innovation teams supported by a KJ method creativity support groupware, this study examine the effects of three communication methods which are the task interactions only, the text chat, and the face-to-face methods on team creativity. It is found that the task interactions only method yields higher degree of team creativity than the face-to-face method by both quantitative and qualitative evaluations on divergent thinking, but not on convergent thinking. The experiment is explained in detail, and the conclusion is drawn.
Optimisation of Ensemble Classifiers using Genetic Algorithm
Authors: Gaber Mohamed Medhat  , Bader-El-Den Mohamed
Published: February 2025

Ensemble learning is a well established machine learning approach that utilises a number of classifiers to aggregate the decision about determining the class label. In its basic form this aggregation is achieved via majority voting. A generic approach, termed EV-Ensemble, for evolving a new ensemble from an existing one is proposed in this paper. This approach is applied to the high performance ensemble technique Random Forests. This study uses a genetic algorithm approach to further enhance the accuracy of Random Forests, based on the EV-Ensemble approach. The new technique is termed as Genetic Algorithm based Random Forests (GARF). Our extensive experimental study has proved that Random Forests performance could be boosted when evolved using the genetic algorithm approach.
Metanode Composition Method for Multilingual Parallel-text Having Many-to-many Relationship
Authors: Fukushima Taku  , Yoshino Takashi
Published: February 2025

Parallel texts are sets of example sentences in one language with their unique translations in other languages. Such corpora can be used for accurate multilingual communication. However, parallel texts often have many-to-many relations because of semantic polysemy, which can complicate way to use parallel texts. This problem cannot be easily solved with only the information of association between example sentences. Here, we propose a metanode composition method for parallel-text graphs having many-to-many combinations. The metanodes relate sentences with the same meaning to resolve the many-to-many relations into one-to-one relations. We compare the proposed method with existing approaches and show that it has several advantages that outweigh the increased computational cost.
Multi-Agent Stock Trading Algorithm – A Neural Network Approach
Authors: Tirea Monica  , Tandau Ioan  , Negru Viorel
Published: February 2025

The goal of this paper is to create a hybrid model that helps the investor to make a good decision on when to buy/sell on a stock market in order to maximize his gain. Artificial Neural Networks are often used in stock market prediction because of their ability to find patterns and correlations in past data. We propose a Multi-Agent Architecture that by combining techniques from fundamental and technical analysis with Neural Networks (namely Multi-Layer Perceptron) tries to compare the result given by all three of them in order to give a much valuable result on which can be a good moment to buy/sell on a stock market. In order to validate our model a prototype was developed.
Complexity of logic-based argumentation in Schaefer's framework
Authors: Creignou Nadia  , Egly Uwe  , Schmidt Johannes
Published: February 2025

We consider logic-based argumentation in which an argument is a pair (Φ, α), where the support Φ is a minimal consistent set of formulæof a given knowledge base that entails the formula α. We study the complexity of two different problems: the existence of a support and the verification of the validity of an argument. When arguments are given in the full language of propositional logic these problems are computationally costly tasks, they are respectively ΣP2- and DP-complete. We study these problems in Schaefer's famous framework. We consider the case where formulæare taken from a class of formulæin generalized conjunctive normal form. This means that the propositional formulæ considered are conjunctions of constraints taken from a fixed finite language Γ. We show that according to the properties of this language Γ, deciding whether there exists a support for a claim in a given knowledge base is either polynomial, NP-complete, coNP-complete or ΣP2
Towards an Argument-based Music Recommender System
Authors: Briguez Cristian E.  , Budán Maximiliano C.D.  , Deagustini Cristhian A. D.  , Maguitman Ana G.  , Capobianco Marcela  , Simari Guillermo R.
Published: February 2025

The significance of recommender systems has steadily grown in recent years as they help users to access relevant items from the vast universe of possibilities available these days. However, most of the research in recommenders is based purely on quantitative aspects, i.e., measures of similarity between items or users. In this paper we introduce a novel hybrid approach to refine recommendations achieved by quantitative methods with a qualitative approach based on argumentation, where suggestions are given after considering several arguments in favor or against the recommendations. In order to accomplish this, we use Defeasible Logic Programming (DeLP) as the underlying formalism for obtaining recommendations. This approach has a number of advantages over other existing recommendation techniques. In particular, recommendations can be refined at any time by adding new polished rules, and explanations may be provided supporting each recommendation in a way that can be easily understood by the user, by means of the computed arguments.
A system for building Image Ontologies from Web Information Sources
Authors: Moscato Vincenzo  , Picariello Antonio  , Chianse Angelo
Published: February 2025

The definition of ontologies within the multimedia domain still remains a challenging task, due to the complexity of multimedia data and the related knowledge. In this paper, we present a novel framework (MOWIS) that aims at realizing a system for building Multimedia Ontologies from Web Information Sources. In particular, we propose: i) a multimedia ontology model that combines both low level descriptors and high level semantic concepts; ii) automatic construction of ontologies using the Flickr web services that provide images, tags, keywords and sometimes useful annotation describing both the image content and personal interesting information. Eventually, we describe an example of automatic ontology generation in a specific domain and present some preliminary experimental results.
Learning Topological SLAM using Visual Information
Authors: Romero Anna  , Cazorla Miguel
Published: February 2025

The map building from data collected form the environment is an important field in robotics. The map could be used in different tasks, as localization, place recognition, obstacle avoidance, SLAM, etc. A topological map does not seek accurate measures, but the classification of the real environment in different areas. The use of learning techniques can help us to define areas which the robot is able to recognize in subsequent steps. In this paper, we propose the adaptation of the Viola-Jones supervised learning method based on AdaBoost to learn what visual features are good to classify an image into a given area. In our case, AdaBoost will select the best MSER features that best define each node of the map.
GeoLoc: Robust Resource Allocation Method for Query Optimization in Data Grid Systems
Authors: Epimakhov Igor  , Hameurlain Abdelkader  , Morvan Franck
Published: February 2025

Resource allocation (RA) is one of the key stages of distributed query processing in the Data Grid environment. In the last decade were published a number of works in the field that deals with different aspects of the problem. We believe that in those studies authors paid less attention to such important aspects as definition of allocation space and criterion of parallelism degree determination. In this paper we propose a method of RA that extends existing solutions in those two points of interest and resolves the problem in the specific conditions of the large scale heterogeneous environment of Data Grids. Firstly, we propose to use a geographical proximity of nodes to data sources to define the Allocation Space (AS). Secondly, we present the principle of execution time parity between scan and join (build and probe) operations for determination of parallelism degree and for generation of load balanced query execution plans. We conducted an experiment that proved the superiority of our GeoLoc method in terms of response time over the RA method that we chose for the comparison. The present study provides also a brief description of existing methods and their qualitative comparison with respect to proposed method.
Analysis of legal narratives: a conceptual framework
Authors: Sileno Giovanni  , Boer Alexander  , van Engers Tom
Published: February 2025

This article presents a conceptual framework intended to describe and to abstract cases or scenarios of compliance and non-compliance. These scenarios are collected in order to be animated in an agent-based platform for purposes of design and validation of both new regulations and new implementations, or to be used as reference base for a diagnosis tool. In our approach, legal narratives become a source of agent-roles descriptions, i.e. abstractions of individual characters/agents from singular stories, feeding the target applicative framework.
Multimedia Information Systems for Social, Cross-Cultural and Environmental Computing
Authors: Sasaki Shiori  , Vojtáš Peter  , Jannaschk Kai  , Thalheim Bernhard  , Jaakkola Hannu  , Kiyoki Yasushi
Published: February 2025

This paper includes five contributions on the topic of multimedia information systems for social, cross-cultural and environmental computing. Approaches, models, and methods for Web Semantization, Cross-cultural Image Computing, Information Modelling and Data Mining, Mobile Information Systems for Ubiquitous Society, and Multimedia Systems for Cross-cultural and Environmental Computing are introduced and discussed. This paper is based on the contributions presented in the panel discussion of EJC 2012 Conference.
Tunnelling in Hard Soils – Weak Rocks: General Report
Authors: Kavvadas M.
Published: February 2025

This report discusses the following main characteristics of Hard Soils – Weak Rocks (HSWR) influencing tunnel design and construction: (1) The presence of systematic structural features which prevent representative sampling, thus making classical Soil and Rock Mechanics testing methods inapplicable in measuring mechanical properties and necessitate the use of empirical classification methods. (2) Stiffness and strength of HSWR are usually too low compared to the geostatic stresses at the depths where these materials are encountered, resulting in face instability and time dependent behaviour (squeezing conditions).
Discussion Session 1.2: Laboratory testing
Authors: Georgiannou V.N.
Published: February 2025

Papers in this session refer to various facets of laboratory testing namely: instrumentation, apparatus and/or testing techniques development, testing a wide range of materials and theories prompting the tests. In the professional world published results are looked to constantly; typical results on soil properties are included in this conference session.
Caisson foundation subjected to normal faulting: Experiment vs. analysis
Authors: Anastasopoulos I.  , Loli M.  , Gazetas G.  , Bransby F.
Published: February 2025

Dramatic failures have occurred in large magnitude earthquakes due to the interplay of surface structures with outcropping fault ruptures. Employing both centrifuge testing and numerical analysis, this paper explores the mechanisms of normal fault rupture interaction with rigid caisson foundations. First, a series of centrifuge tests were conducted to study the response of a 5m x 5m x 10 m caisson founded on a layer of dry dense sand. Nonlinear 3-D numerical modelling of the problem was then developed and adequately validated against the centrifuge tests results. Depending on its position relative to the fault, the caisson is found to interact with the fault rupture, sometimes modifying spectacularly the free field rupture path. Acting as a kinematic constraint, the caisson causes the rupture to divert on either one, or both, of its sides. The numerical study was subsequently extended to a parametric investigation of the effect of the exact position of the caisson relative to the fault outcrop. Different mechanisms taking place for different caisson positions are identified, and their effect on the response of the soil-foundation system is discussed.
On the hydromechanical behaviour of argillaceous hard soils-weak rocks
Authors: Gens A.
Published: February 2025

The paper examines some aspects of the hydromechanical behaviour of argillaceous hard soils and weak rocks. After considering the wide variety of this class of materials, some common behaviour features are sought concerning compressibility, structure development, uplift and swelling, microfabric, anisotropy, effects of discontinuities and hydraulic properties. Those features are examined in the context of appropriate behaviour frameworks developed for this type of materials. Two themes are then selected for special consideration: brittleness and progressive failure and the response of argillaceous weak rocks to deep underground excavations. For the second topic, particular attention is given to field results obtained in deep underground laboratories for nuclear waste disposal. The paper concludes with a summary of the main points.
A Deduction-based System for Formal Verification of Agent-ready Web Services
Authors: Klimek Radosław
Published: February 2025

The work concerns the formal verification of systems using logical inference and considers web service models expressed in BPEL. Agent technologies and web services may be consistent with some features and mutual goals like independence, interoperability, service and aims discovery, etc. A method for an automatic extraction of logical specifications, considered as a set of temporal logic formulas, for web services is proposed. The generation procedure is based on predefined BPEL-based patterns. The patterns are considered primitives, which enables the transformation to temporal logic formulas. The inference process is based on the semantic tableaux method. The proposed method of formal verification could be helpful in avoiding arbitrariness and laxity with agent-oriented web services.
A Method for the Generation of Semantic Annotation from Sport News Using Ontology Based Patterns
Authors: Nguyen Quang-Minh  , Cao Tuan-Dung  , Phan Thanh-Hien  , Nguyen Hoang-Cong  , Hagino Tatsuya
Published: February 2025

In the framework of this research, we focus on describing the algorithm to collect, process information in natural language to turn it into semantic annotations based on ontology, patterns and the knowledge ground in sport. This paper will concentrate to solve the problem of enhancing the named entities recognition by developing ontology and enriching the knowledge base for the recognition engine. Besides this, it is at the same time solving the problem of semantic recognition in texts using ontology-based patterns, harnessing the power of ontology in identifying synonyms, aliases.
Dynamic Word Clouds: Context-based Word Clouds of Presentation Slides for Quick Browsing
Authors: Wang Yuanyuan  , Sumiya Kazutoshi
Published: February 2025

With the advent of online education services such as iTunes U and SlideShare, students are able to access various presentation files from many universities for study purposes. However, self-learners retrieving such files still need support to decide which files are worth learning because it can be difficult to understand the context of each file. In this paper, we introduce a quick browsing system to help a user effectively decide whether a presentation content is appropriate for his/her specific learning needs. Our method provides context-based word clouds that summarize slide information to help the user visually understand the context of a presentation content. In our method, words important to the “presentation context,” that is, the relevant information on the slides, are first extracted based on components of the presentation content (i.e., intra-slide structure and inter-slide structure). Then the word cloud is generated by weighting the words within the presentation context for each slide. Finally, the word clouds are interactively presented with visual effects that reflect their semantic meanings.
How to “share” the tactile sense?, a putative approach
Authors: Suzuki Rieko  , Suzuki Yasuhiro
Published: February 2025

We have developed an approach to “share” the tactile sense with others; in order to that we have designed the “body workshop” focused on tactile sense as a method of science communication. Throughout these experiences in workshops and investigations of tactile senses, especially of massaging in cosmetic treatment we proposed a method of describing tactile sense, the tactile score; by using this novel notation, we are able to describe and exchange tactile senses with each other.
Towards Practical Tabled Abduction Usable in Decision Making
Authors: Saptawijaya Ari  , Pereira Luís Moniz
Published: February 2025

Abduction as reasoning paradigm has been much explored in Artificial Intelligence, but not yet taken up by decision making as much as its potential warrants. Indeed, abduction permits the generation of hypothetical knowledge based scenarios, about which one can then equate decisions. One reason for this state of affairs is that abduction is difficult to implement efficaciously, even by experts, which entails that abductive systems are not readily available for decision making. Our concept of tabled abduction mitigates this, in the abductive logic programming system TABDUAL.
How to Successfully Implement Automated Engineering Design Systems: Reviewing Four Case Studies
Authors: Johansson Joel  , Elgh Fredrik
Published: February 2025

Introducing computerized systems to automate engineering design activities (design automation) on manufacturing companies promises improved product quality, shortened time to production, increased control on cost, less effort to adapt products to new customer requirements. Due to these motives, big effort has been put on developing computer systems automating a variety of engineering design activities throughout the product and production development process. The question is now: Is design automation ready to launch yet? In this paper, we review four cases of design automation of engineer-to-order to give guidelines for developing engineering design automation systems.
Kernel Functions for Categorical Variables with Application to Problems in the Life Sciences
Authors: Belanche Lluís A.  , Villegas Marco A.
Published: February 2025

We introduce a family of positive definite kernels specifically designed for problems described by categorical information. The kernels are based on the comparison of the probability mass function of the variables and have a clear interpretation in terms of similarity computations between the modalities.
An Approach to Couple Two Forms of Feedback in Conversational Recommenders
Authors: Salamó Maria  , Puig Anna  , Contreras David
Published: February 2025

Critiquing is a common and a powerful form of feedback in conversational recommender systems. The goal of such systems is to retrieve the best product that satisfies the user preferences minimizing the session length. However, in some cases critiquing feedback may greatly lengthen a user navigation time. Although the user is unaware of her preferred target product, it is common that she has a particular preference over at least one of the product's features. In this case, the user iteratively makes a critique on that feature until reaching the preference. In this paper we propose a new recommendation algorithm that couple critiquing and direct selection of preferred products as feedback in a conversational recommender. Additionally, we describe how the user model is updated and we report on a simulator and a user study its advantage for reducing session length.
Classification of movement patterns in skiing
Authors: Holst Anders  , Jonasson Arndt
Published: February 2025

In cross country skiing there are different skiing techniques, known as gears. For professional skiers it is useful to analyze a ski session with respect to the gears used in different parts of the track. We have developed a statistical machine learning method that uses data from accelerometers in e.g. a mobile phone placed on the chest of a skier to classify the gears used. The statistical model used is based on a Markov chain of multivariate Gaussian distributions. The same model can in addition to classification be used for anomaly detection and unsupervised clustering of skiing movements. The method is evaluated on real data from elite skiers collected during a training race.
Dependency and Valency: From Structural Syntax to Constructive Adpositional Grammars
Authors: Gobbo Federico  , Benini Marco
Published: February 2025

In linguistics, the influence of the results by Tesnière cannot be under-estimated: above all, he introduced the concepts of dependency and valency, which had a considerable influence in the development of linguistics by the second half 20thcentury. However, his Structural Syntax remains still uninvestigated in most parts: in particular, there is still no grammar formalism directly inspired by it, that is suitable for theoretical and practical applications in Artificial Intelligence and computational linguistics. The aim of this paper is to fill this gap, in proposing a formal grammar that adopts Tesnière's intuitions and concepts of Structural Syntax—as much as possible—in adapting them to the needs of contemporary linguistics, notably natural language processing. The result of this modelling process is a new formalism derived from Tesnière's, where natural language grammars are expressed in constructive mathematical terms (and therefore suitable for computational treatment) where the abstract notion of adposition is of the greatest importance. For these reasons, they are called Constructive Adpositional Grammars (CxAdGrams). This paper explains the linguistic and formal reasons of CxAdGrams, with a special regard to the heritage of Tesnière and its relations with existing dependency grammar formalisms in terms of similarities and differences.
Argumentation Schemes for Reasoning about Factors with Dimensions
Authors: Atkinson Katie  , Bench-Capon Trevor  , Prakken Henry  , Wyner Adam
Published: February 2025

In previous work we presented argumentation schemes to capture the CATO and value based theory construction approaches to reasoning with legal cases with factors. We formalised the schemes with ASPIC+, a formal representation of instantiated argumentation. In ASPIC+ the premises of a scheme may either be a factor provided in a knowledge base or established using a further argumentation scheme. Thus far we have taken the factors associated with cases to be given in the knowledge base. While this is adequate for expressing factor based reasoning, we can further investigate the justifications for the relationship between factors and facts or evidence. In this paper we examine how dimensions as used in the HYPO system can provide grounds on which to argue about which factors should apply to a case. By making this element of the reasoning explicit and subject to argument, we advance our overall account of reasoning with legal cases and make it more robust.
Contextual and Differential Computing for the Multi-Dimensional World Map with Context-Specific Spatial-Temporal and Semantic Axes
Authors: Kiyoki Yasushi  , Chen Xing
Published: February 2025

In the natural environment research field, computer systems are widely utilized. The majority of computer systems are used to store observed data. Super computers are used to simulate environment changes, for example, the global climate change. Prior research has shown that computer systems make it possible to store and access huge amount of observed data based on database manage systems. The simulation accuracy of nature environment changes is also improved accompanied by the progress of computer technology. In this work, we propose a new method to discover what are happening in the nature of our planet utilizing differential computing in our Multi-dimensional World Map. We have various (almost infinite) aspects and contexts in environmental changes in our planet, and it is essential to realize a new analyzer for computing differences in those situations for discovering actual aspects and contexts existing in the nature of our planet. By using Differential Computing, important factors that change natural environment are highlighted. Furthermore, the highlighted factors are visualized by using our Multi-dimensional World Map, which makes it possible to view the nature environment changes in the view of history, geographic, etc.
A Method for Precedent Analysis of Spatial Artefacts
Authors: Guney Ali
Published: February 2025

This paper will treat two issues regarding innovative/ creative morphological analysis of spatial artefacts in relation to their Form, Operation and Performance. One will be about precedents and their usage in the design process, analogically; the second will be an example of a comparative architectural precedent analysis of two buildings by the same architecture firm.
Urban Morphology and Architectural Design of City Edges and Vertical Connections in Historical Contexts
Authors: Camiz Alessandro
Published: February 2025

The papers considers, with a comparative approach, the architecture of vertical connections and city edges. We hypothesize that the city edge, when its elevation overwhelms the surrounding urban fabric, cannot be redesigned within a basic typological repertoire. This research considers the transformations of the edge in historical towns, taking into consideration the architectural models used and investigating the contextual deformations impressed. The design of vertical connections between different city levels redefines the image of the city from its meaningful points of view, changing the collectively recognized city image. A repertoire of models, divided into typologies according to the morphology of the site, is the base for a new theory outlining which parameters (i.e. measure, elevation, slope, and major urban nodes) to use to deform models in each context. The study cases range throughout the history of architecture, focusing on some pre-modern examples such as Laurana's Torricini façade in the Palazzo Ducale of Urbino.
The Construction of Open Space System Integrated with Rainwater Management
Authors: Tu Mengru  , Hua Xiaoning
Published: February 2025

The article explores the possibility of constructing a system of open urban and regional spaces through rainwater management. This system takes advantage of the existing urban open spaces (mainly parks and squares), and makes them into multifunctional places for absorbing rainwater during rainy days. Normally they are leisure areas for the public. The first part of this article collects geographical and hydrological information. The second part focuses on the hydrological structure, and determines the area of study. In this phase, DEM (Digital Elevation Model) will be used to automatically divide the city by the function of hydrological analysis in a Geographic Information System (GIS). The third part analyses the spatial accessibility (the accessibility of rainwater into the open spaces) of such an integrated system of open spaces and rainwater management. The network analysis in GIS, including descriptive and statistical analysis and the road networkbased distance measurement, is mainly applied to investigate spatial accessibility. The last part analyses the spatial configuration of the open space system integrated with rainwater management. On the basis of this information and analyses, quantitative constraints for landscape design are acquired, rendering the storage capacity of functional open space. Based on these results, applied to a substantially urbanized region, this article finally discusses the feasibility of the approach presented in this study and its eventual application to similar landscape and urban planning scenarios.
Towards Early Detection of Influenza Epidemics by Using Social Media Analytics
Authors: Kim Kwang Deok  , Hossain Liaquat
Published: February 2025

This study aims at the possibility of early detection of seasonal influenza causing a major public health concern each year worldwide. Furthermore, the viability of social media analytics for the early detection of disease outbreak is examined. To conduct an analysis, three sets of data are used and investigated; search query data and two influenza related data collected from the nine US census bureau divisions on a weekly basis during a period from week 1, 2012 to week 52, 2013 from Google and Centers for Disease Control and Prevention (CDC), respectively. Pearson's correlation coefficient is calculated among the data as a statistical measure of the strength of a relationship, and the significant Pearson's rho confirms the existence of a very strong positive correlation. This study argues that the relative frequency of search queries is highly correlated with the actual number of influenza activity in each division of the US, and that social media analytics may be utilized to make an early detection of influenza epidemics possible. The importance of a detailed analysis is also discussed to assess the statistical methods for the phenomenon because the data from Google is still in its early stage which may contain inaccuracies.
Distributed Framework for Big Data Processing: a Goal Driven Approach
Authors: Sliman Layth  , Charroux Benoit  , Stroppa Yvan
Published: February 2025

Nowadays, it becomes crucial to researchers to launch simulations and running scripts to evaluate and test their models and algorithms on computer platforms. However, finding effective online tools to facilitate research reproducibility for big data is a real challenge. In this paper, we describe a new online “paper oriented” social media platform called Exec&Share. Exec&Share allows an open dissemination and reproducibility of research findings. The platform is well-appointed with a new Distributed Processing Framework for Big Data in such a way to allow testing and demonstrating massive data and computation-based research such as multimedia processing.
Software for finding M-matrices
Authors: Balonin Yuri  , Vostrikov Anton  , Sergeev Mikhail
Published: February 2025

the paper contains description of “MMatrix-2” software intended for finding and examining orthogonal basic matrices — minimax matrices (so called “M-matrices”). General functions of the software initiated with its buttons and presented with interface windows are described. In the paper there are also portraits of matrices been found with the software and ways of its transformation from some types to some others.
Organizational Aspects and Needs of E-government: a Knowledge Path for Designing and Implementing Value Interoperable Services
Authors: Casalino Nunzio  , Anohina-Naumeca Alla  , Sitikovs Vjaceslavs  , Georgogianni Nicole  , Goetzen Piotr  , Manolov Slavcho  , Ubrich Thomas
Published: February 2025

The LLP European Leonardo da Vinci projcct “ELGI - eLearning for eGovernment” aims at the development of an e-course for acquiring knowledge concerning interoperability in the field of e-government. It considers European and national dimensions of interoperability and provides the design specification of the e-course. The course modular structure is described and screenshots of the ecourse are included. The essay presents main results of the project and the development of an e-course for acquiring knowledge concerning interoperability. The goal of the paper is to present the experience of the authors, the development activities, and the main results achieved so far.
Publish your Data and Model Code: Research Output is More Than “Just” a Research Paper
Authors: Rasmusen Martin
Published: February 2025

Research output is not only research articles. To provide outlets for publishing other outputs than articles, Copernicus Publications, an innovative open access publisher based in Göttingen, Germany, currently publishes the journals Earth System Science Data and Geoscientific Model Development. The first journal is dedicated to the peer-reviewed publication of articles on original research data sets in the Earth System Sciences. The second journal is dedicated to publish the description, development and evaluation of numerical models of the Earth System and its components. Both journals apply an innovative interactive open access peer-review with public referee reports, public comments from the community prior to editor's decision, and public author's responses. The motivation is to make the whole research output from data, to models, to the scientific findings and novel interpretations freely accessible, to foster scientific discussion, to increase transparency in scientific quality assurance, and to give credit to all involved contributors.
Propositional Merging and Judgment Aggregation: Two Compatible Approaches?
Authors: Everaere Patricia  , Konieczny Sébastien  , Marquis Pierre
Published: February 2025

There are two theories of aggregation of logical formulae: merging and judgment aggregation. In this work we investigate the relationships between these theories; one of our objectives is to point out some correspondences/discrepancies between the associated rationality properties.
INTELLIREQ: Intelligent Techniques for Software Requirements Engineering
Authors: Ninaus Gerald  , Felfernig Alexander  , Stettinger Martin  , Reiterer Stefan  , Leitner Gerhard  , Weninger Leopold  , Schanil Walter
Published: February 2025

Requirements Engineering is considered as one of the most critical phases of a software development project. Low-quality requirements are a major reason for the failure of a project. Consequently, techniques are needed that help to improve the support of stakeholders in the development of requirements models as well as in the process of deciding about the corresponding release plans. In this paper we introduce the INTELLIREQ Requirements Engineering environment. This environment is based on different recommendation approaches that support stakeholders in requirements-related activities such as definition, quality assurance, reuse, and release planning. We provide an overview of recommendation approaches integrated in INTELLIREQ and report results of empirical studies that show in which way recommenders can improve the quality of Requirements Engineering processes.
Pattern-based Explanation for Automated Decisions
Authors: Nunes Ingrid  , Miles Simon  , Luck Michael  , Barbosa Simone  , Lucena Carlos
Published: February 2025

Explanations play an essential role in decision support and recommender systems as they are directly associated with the acceptance of those systems and the choices they make. Although approaches have been proposed to explain automated decisions based on multi-attribute decision models, there is a lack of evidence that they produce the explanations users need. In response, in this paper we propose an explanation generation technique, which follows user-derived explanation patterns. It receives as input a multi-attribute decision model, which is used together with user-centric principles to make a decision to which an explanation is generated. The technique includes algorithms that select relevant attributes and produce an explanation that justifies an automated choice. An evaluation with a user study demonstrates the effectiveness of our approach.
The semantics of behavior
Authors: Roos Nico
Published: February 2025

The BDI architecture is one of the most popular architectures for agents with symbolic reasoning capabilities. To formally define the notions of Beliefs, Desires and Intentions, different formal logics have been proposed in the literature. Although these proposals often refer to the work of Bratman [2], none, however, correctly capture the form of practical reasoning that Bratman describes. What is lacking, is a proper characterization of the agent's behavior. The formal logics proposed so far, do not allow for an adequate characterization of the refinement of behaviors that Bratman describes.
Decidable Model-Checking for a Resource Logic with Production of Resources
Authors: Alechina Natasha  , Logan Brian  , Nga Nguyen Hoang  , Raimondi Franco
Published: February 2025

Several logics for expressing coalitional ability under resource bounds have been proposed and studied in the literature. Previous work has shown that if only consumption of resources is considered or the total amount of resources produced or consumed on any path in the system is bounded, then the model-checking problem for several standard logics, such as Resource-Bounded Coalition Logic (RB-CL) and Resource-Bounded Alternating-Time Temporal Logic (RB-ATL) is decidable. However, for coalition logics with unbounded resource production and consumption, only some undecidability results are known. In this paper, we show that the model-checking problem for RB-ATL with unbounded production and consumption of resources is decidable.
Learning Probabilistic CP-nets from Observations of Optimal Items
Authors: Bigot Damien  , Mengin Jérôme  , Zanuttini Bruno
Published: February 2025

Modelling preferences has been an active research topic in Artificial Intelligence for more than fifteen years. Existing formalisms are rich and flexible enough to capture the behaviour of complex decision rules. However, for being interesting in practice, it is interesting to learn not a single model, but a probabilistic model that can compactly represent the preferences of a group of users – this model can then be finely tuned to fit one particular user. Even in contexts where a user is not anonymous, her preferences can depend on the value of a non controllable state variable. In such contexts, we would like to be able to answer questions like “What is the probability that o is preferred to o′ by some (unknown) agent?”, or “Which item is most likely to be the preferred one, given some constraints?”
Highlighting Value and Effort Drivers Early in Business and System Models
Authors: Book Matthias  , Grapenthin Simon  , Gruhn Volker
Published: February 2025

In complex business modelling and software development projects, we often observe that teams focus on those aspects of a system that are well understood or easy to resolve, while a blind eye is turned (consciously or subconsciously) to the actual value and effort drivers – i.e. those components that require higher effort due to their intrinsic value, risk, complexity or uncertainty. In this paper, we introduce a pragmatic approach for highlighting elements of high-level business and system models with visual annotations that mark particular issues, requirements or complexities that would otherwise not immediately meet the eye, and would thus present risks to a project's successful completion if uncovered too late.
A bottom-up approach for visualisation system development using Game Engine
Authors: Mohamed Farhan  , Grant Phil W.  , Chen Min
Published: February 2025

This paper describes the process of developing a visualisation system with the use of Game Engine. A bottom up approach was used in developing the system, which allows process alignment with the Game Engine structure. The approach allows large abstract data processing, which are channelled through the components of visual interfaces and supported with relational data input structure. The developed system provides automation in much of the pipeline in producing dynamic visualisation selections. As case studies, the UK Research Assessment Exercise (RAE2008) and 2010 World Oil Reserves datasets were used to demonstrate the usability of the Game Engine based visualisation system.
Automatic Classification of Cross-document Structural Relations for Discussion Summarization
Authors: Almahy Ibrahim  , Salim Naomie
Published: February 2025

We propose a method to summarize threaded texts, particularly online discussions (forums and blogs) and e-mail conversations. These texts have semantic relations between their sentences since each post replies to another one. While cross-document structural theory (CST) concerns about links in documents, this work examines the use of CST in summarizing threaded document since no one use it in this domain before. To do so, this work has two phases: first, we identify and extract four CST relations by using supervised machine learning. Second, we develop a new sentence weighting method based on model selection technique over the identified cross-document relations. The experiments show that using of CST in the thread summarization gives promised results. The performances of all methods were evaluated using ROUGE—a standard evaluation metric used in text summarization.