bluuebunny/crossref_metadata_2025 huggingface dataset:
Rib length discrepancy in patients with adolescent idiopathic scoliosis
Authors: Qiu Yong  , Sun Guang-quan  , Zhu Feng  , Wang Wei-jun  , Zhu Ze-zhang
Published: February 2025

The development of scoliosis in animal models with induced asymmetric rib growth suggested the possible role of asymmetric rib growth in the etiopathogenesis of adolescent idiopathic scoliosis (AIS). Asymmetric rib length is well recognized in idiopathic scoliosis, however, whether this rib asymmetry was primary or secondary has not been clearly documented. We measured the lengths of all ribs in 48 patients with AIS and 29 patients with scoliosis associated with syringomyelia and Chiari I malformation (SS). In both groups, ribs on the concave side were significantly longer than those on the convex side in apical area. The rib length difference was significantly associated with magnitude of the Cobb angle of thoracic curve. However, the rib length discrepancy showed no difference between AIS and SS group. The finding of similar asymmetry of rib length in both AIS and SS patients with thoracic curve indicated the discrepancy found in AIS might be secondary to the spinal deformity rather than its etiological factor.
Influencing Consumer Decisions Through Personalization
Authors: Phillips-Wren Gloria  , Wygant Jeffrey
Published: February 2025

Web-based technologies have enabled companies to reach out to their customers and influence decision making in new and different ways. Personalization has shown promise as an approach to attracting an individual's interest and influencing their decision making, and it can be effectively delivered over the Internet. New technologies allow a rich mix of media, interconnected streams of social conversation between users, and one-on-one interaction between the user and the technology delivering the message. These characteristics can be used to influence a decision maker based on research suggesting that consumers will respond more favorably to individualized messages than generalized ones. This paper focuses on socio-technical aspects of personalization by addressing human and technical issues in the implementation and impact of personalization. We provide a Understand-Measure-Deliver theory of personalization and report a case study of a global company that successfully used personalization to influence consumer decisions in the tourism industry. The findings are that customization based on relevant data provides a personalized experience; customers become product designers and product testers with Web 2.0 technologies; and interaction between a human and the technology amplifies user experience.
Using Action Research on the Process of Decision Support with VIP Analysis Software
Authors: Ventura Alecsandra  , Dias Luis C.  , Clímaco João N.
Published: February 2025

This paper presents a summary of a research done in a Portuguese network of travel agencies, as part of a PhD Research in Multicriteria Decision Aiding - MCDA. This study is a first contribution to suggest an Implementation Model of Decision Support with the VIP Analysis software, including the proposal of using Cognitive Maps as a Problem Structuring Method (PSM) and using Multi-Attribute Utility Theory (MAUT) to elaborate additive value functions. Action Research was selected as a Research Method in this case, because it enables the assessment of acceptability VIP Analysis Software in Organizations, at the same time that it makes possible the implementation of a decision aiding process by the researcher.
Case and Model Based Hybrid Reasoning for Group Decision Making
Authors: Adla Abdelkader  , Zarate Pascale  , Soubie Jean-Luc  , Taghezout Noria
Published: February 2025

Several organizational decision-making situations are critical and recurring in nature. The processes involve groups performing periodic and repetitive activities. It appears logical that the development of a shared repository that stores the experience invoked in prior decisions and retains the rules, policies and procedures of an organization can be useful for subsequent groups engaged in similar decision-making activities. We describe, in this paper, an approach that combines a case-based reasoning method and a model based reasoning method. The main goals are to reduce the time required to come to a decision, particularly, in a contingency situation, to compensate for lack of experience of young operators, and to distribute available experience to different sites.
Theory-building using Typologies – A Worked Example of Building a Typology of Knowledge Activities for Innovation
Authors: O'Raghallaigh Paidi  , Sammon David  , Murphy Ciaran
Published: February 2025

Literature reviews of innovation in organizations continue to demonstrate how the determinants of innovation are ambiguous and inconsistent across studies. In order to simplify the conceptualization of innovation processes, we propose a typology of innovation activities. We contend that typologies are more than simple classifications but are theories. In using typologies we don't assume that all activities are unique but neither do we consider all activities to be identical. Instead our theorizing is enriched by adopting a finer focus based on categories of activities, which will provide more meaningful conclusions about the determinants of innovation. It is the purpose of this paper to be one of the first to offer assistance through developing a blueprint, informed by principles of ‘good’ theory, for building theory through typologies. We concur with Doty & Glick (1994 p.248) who suggest that such a typology is “intuitively appealing and holds considerable promise for helping management researchers to understand complex, holistic phenomenon”.
Evaluating ERP Projects with Global Efficiency Factors
Authors: Bokovec Ksenča  , Damij Talib  , Rajkovic Tanja  , Rajkovic Vladislav
Published: February 2025

Efficient management of complex Enterprise Resource Planning (ERP) projects is of key importance for their successful implementation. The purpose of this paper is to define global efficiency factors (GEFs) and to apply them to a multi-attribute evaluation model, which allows us to evaluate global ERP implementation projects through their project lifecycle. Based on a study of prevalent critical success factors in the literature were defined five GEFs. They differ from the former by focusing on the global design of the ERP system and less on the project management alone. By the means of the GEFs an evaluation model was defined and used for evaluating five case studies – ERP implementation projects. The model is based on the multi-attribute utility theory. The analysis of the evaluation results showed which GEFs in were not defined according to the global design in specific projects, what the relationships among the evaluation criteria are and which measures should be undertaken to bring the projects back on track. The results show that such an evaluation model could be used in every project phase in order to assess if the ERP implementation is in accordance with the global design. In this way we can impact the complexity of the project management and ensure the expected business performance benefits. At the same time, the required improvements are recognized thus reducing the time span and the costs of the implementation.
Introduction: Ontologies, Semantic Technologies, and Intelligence
Authors: Janssen Terry  , Obrst Leo  , Ceusters Werner
Published: February 2025

In recent years ontologies and semantic technologies more generally have begun to be applied to assist the intelligence community, for information integration, information-sharing, decision-support, and in many other applications. This chapter introduces the topic of the book and provides background information concerning its rationale, historical perspective, a vision for the future, and briefly describes the chapters of the present volume.
Grid selection of models of nucleotide substitution
Authors: Loureiro Marta  , Pan Miguel  , Rodríguez-Pascual Manuel  , Posada David  , Mayo Rafael
Published: February 2025

jModelTest is a Java program for the statistical selection of models of nucleotide substitution with thousands of users around the world. For large data sets, the calculations carried out by this program can be too expensive for many users. Here we describe the port of the jModeltest code for Grid computing using DRMAA. This work should facilitate the use of jModelTest on a broad scale.
Welding of Aluminum Casting Alloys
Authors: Enomoto Masatoshi
Published: February 2025

It is well known that aluminum castings are hard to weld due to imperfections. However, they have several advantages and are therefore often used in industry. Nowadays, large components of medical equipments and automobile vehicles are manufactured using castings.
Mechanism of Grain Refinement in Mg-Al Alloys with Carbon Inoculations
Authors: Huang Yuanding  , Zheng Xiuhua  , Kainer Karl Ulrich  , Hort Norbert
Published: February 2025

Previous Al4C3nuclei hypothesis cannot explain the grain refinement mechanism of Mg-Al alloys inoculated by carbon because this nucleant is impossible to form during solidification. In the present investigation a ternary compound Al2MgC2was identified. It has a closer crystal structure to Mg than Al4C3. In the centre of grains, one or more “hillocks” with Al, Mn and C-enrichment were observed. A novel grain refinement mechanism is suggested to explain the grain refinement of Mg-Al alloys with carbon inoculations.
Design and evaluation of a semantic approach for the homogeneous identification of events in eight patient databases: a contribution to the European EU-ADR project
Authors: Avillach Paul  , Joubert Michel  , Thiessard Frantz  , Trifirò Gianluca  , Dufour Jean-Charles  , Pariente Antoine  , Mougin Fleur  , Polimeni Giovanni  , Catania Maria Antonietta  , Giaquinto Carlo  , Mazzaglia Giampiero  , Fornari Carla  , Herings Ron  , Gini Rosa  , Hippisley-Cox Julia  , Molokhia Mariam  , Pedersen Lars  , Fourrier-Réglat Annie  , Sturkenboom Miriam  , Fieschi Marius
Published: February 2025

The overall objective of the EU-ADR project is the design, development, and validation of a computerised system that exploits data from electronic health records and biomedical databases for the early detection of adverse drug reactions. Eight different databases, containing health records of more than 30 million European citizens, are involved in the project. Unique queries cannot be performed across different databases because of their heterogeneity: Medical record and Claims databases, four different terminologies for coding diagnoses, and two languages for the information described in free text. The aim of our study was to provide database owners with a common basis for the construction of their queries. Using the UMLS, we provided a list of medical concepts, with their corresponding terms and codes in the four terminologies, which should be considered to retrieve the relevant information for the events of interest from the databases.
Scientific discovery workflows in bioinformatics: A scenario for the coupling of molecular regulatory pathways and gene-expression profiles
Authors: Kanterakis Alexandros  , otamias Giorgos  , Zacharioudakis Giorgos  , Koumakis Lefteris  , Sfakianakis Stelios  , Tsiknakis Manolis
Published: February 2025

Scientific workflow technologies and tools have become an important weapon in the arsenal of the bioinformaticians and computational biologists. To support this view we present a typical exploratory data analysis scenario involving the combination of information from Gene Regulatory Networks and gene expression data. We further describe the implementation of this scenario using the Workflow Environment implemented in the context of a large EU funded project. In this process desirable features that similar environments should offer are identified and analyzed. The ICT platform presented is evaluated using the chosen scenario as a benchmark. Finally we conclude with an outlook to future work.
Building a Logical EHR architecture based on ISO 13606 standard and Semantic Web Technologies
Authors: Santos Marcelo R.  , Bax Marcello P.  , Kalra Dipak
Published: February 2025

Among the existing patterns of EHR interoperability, the ISO 13606 standard is an important consideration. It is believed that the use of this norm, in conjunction with semantic technologies, may aid in the construction of a robust architecture, keeping in mind the challenges of semantic interoperability. The objective of this paper is to present a proposal for an EHR architecture, based on ISO 13606 and on the utilization of semantic technologies, for a real EHR scenario. In order to accomplish that, a real EHR scenario is described, as well as its main interoperability requirements and a candidate architecture is proposed to solve the presented challenges of interoperability. The ability of the ISO 13606 EHR reference model to accommodate the scenario was highlighted, together with the support provided by the use of the ontology specification languages – RDF and OWL – in respect to the maintenance of a controlled vocabulary.
Learning lessons from electronic prescribing implementations in secondary care
Authors: Cornford Tony  , Savage Imogen  , Jani Yogini  , Franklin Bryony Dean  , Barber Nick  , Slee Ann  , Jacklin Ann
Published: February 2025

This paper reports a study undertaken in the UK to gather lessons learned from hospital sites that have implemented electronic prescribing systems. The work was commissioned by NHS Connecting for Health, the UK Department of Health agency responsible for the implementation of the National Programme for Information Technology. The aim was to capture front-line experience of the project and systems implementation, and to share it with staff who will in the future participate in other implementations. Data were drawn from detailed interviews with staff and a survey in 13 hospitals in England, as well as a review of published studies of implementations. The study output is a report and six user-facing briefing documents targeted at key stakeholder groups; nurses, pharmacist, doctors, senior executives, implementation team members and IM&T staff.
The Evolution of Hospital Information Systems and the Role of Electronic Patient Records: From the Italian Scenario to a Real Case
Authors: Locatelli Paolo  , Restifo Nicola  , Gastaldi Luca  , Sini Elena  , Torresani Michele
Published: February 2025

Health care organizations can gain great value from Information and Communication Technologies (ICT), yet, although there is growing awareness of the potential benefits associated with their use, results often fall far short of expectations. Each year, the “ICT in Health Care” Observatory – part of the Politecnico di Milano School of Management – outlines a profile of the role of ICT in the Italian health care industry, investigating current projects in terms of their impact on processes and organizations, implementation state of the art, governance models, and prospective pathways. The 2009 collaborative research process outlines the need for a change in the way health care CIOs approach technological and organizational evolutions. ICT departments lack vision, governance mechanisms, skilled resources, and top management commitment. This has led to a series of distortions in the innovation of Hospital Information Systems (HISs) and ICT departments themselves. Currently they are too concerned with day-to-day operations and delay comprehensive initiatives capable of leading to effective ICT-driven innovations. The paper points out the problems that health care organizations are tackling and how they are trying to solve them. The case of the Italian National Cancer Institute in Milan provides a valuable example of how a health care organization is developing its HIS.
Peri-operative Communication Patterns and Media Usage – Implications for Systems Design
Authors: Karlsen Ero S.  , Toussaint Pieter Jelle
Published: February 2025

Inter-hospital communication amounts for a great deal of clinicians' work time. While communication is essential to coordinate care, it can also be time consuming and interruptive, and breakdown in communication is an important source of medical errors. One contributor to the interruptive nature of communication is the use of synchronous media, and there is clearly a potential for novel technologies. To assess communication patterns and media usage we performed an ethnographic field study in the peri-operative environment at a Norwegian hospital, as well as interviews with nurses. We analyze the results with regards to choice of media, characteristics of the conversations taking place and meta-messages, and account for addressing, obtrusiveness and information richness in the message exchanges. We find a relative high degree of interruptiveness in communication, and ascribe it to 1) a lack of situational awareness between locations in the peri-operative domain, as well as 2) use of synchronous media. This suggests that design of novel technology for intra-hospital communication should aim at supporting sender-receiver awareness and signaling of availability.
Factors associated with health information system success: Results of a survey of hospitals in South Africa
Authors: Hanmer Lyn A.  , Isaacs Sedick  , Roode J. Dewald
Published: February 2025

A survey of computerised hospital information system (CHIS) use was conducted in two South African provinces, in order to test a conceptual model of CHIS use developed in previous phases of this study. Relationships between factors of the conceptual model and user assessment of CHIS success; and between pairs of conceptual model factors, were derived from the survey data.
Monitoring diseases across borders: African regional integrative information systems
Authors: Simbini Tungamirirai  , Foster Rosemary  , Nesara Paul  , Hullin Lucay Cossio Carola
Published: February 2025

In African countries, communicable diseases remain the chief cause of a heavy disease burden. Regional economic, political and social integration bring new challenges in the management of these diseases, many of which are treatable. Information Communication Technology (ICT) applied through electronic health systems has the potential to strengthen healthcare service delivery and disease surveillance within these countries. This paper discusses the importance of well-defined e-Health strategies within countries and, in addition, proposes that countries within regions collaborate in planning for health information exchange across borders. It is suggested that particular attention be paid to technical and data standards enabling interoperability, and also to issues of security, patient privacy and governance.
Understanding Effective Clinical Communication in Medical Errors
Authors: Khairat Saif  , Gong Yang
Published: February 2025

Clinical Communication failures are considered the leading cause of medical errors [1]. Minimizing communication problems among clinical team members could directly reduce medical errors and hence, increase patient safety and improve health care quality. Our main focus is, through knowledge representation approach, to develop an understanding of communication problems applied to health care settings. This will serve as the foundation to our long term goal of building an ontology-driven educational tool that will be used to educate clinicians about miscommunication issues and as a means to improve it.
Empirical Analysis of the Reduction of Medical Expenditures by eHealth
Authors: Akematsu Yuji  , Tsuji Masatsugu
Published: February 2025

This paper aims to examine reduction of medical expenditures by utilizing the system of Nishi-aizu Town, Fukushima Prefecture. The town office has been implementing it since 1994 and keeps receipts on medical expenditures of its approximately 4,000 residents paid by National Health Insurance for 5 years from 2002 to 2006. We select (1) users; and (2) non-users of the e-health system, and by comparing their medical expenditures, we examine: (i) difference in medical expenditures between two groups; and (ii) negative correlation between medical expenditures and the length of usage of the e-health system. We find that total medical expenditures of users are larger than those of non-users, whereas by restricting to lifestyle-related illnesses such as high blood pressure, cerebral infarction, strokes, and diabetes, medical expenditures of users are found to be smaller than those of non-users. The results we obtained here provide the rigorous economic foundation of the e-health system.
Evaluation of the use of an “ask-the-expert” e-consultation service for support on health-related requests
Authors: Nijland N.  , van Gemert-Pijnen J.E.W.C.  , Kelders S.M.  , Brandenburg B.J.  , Seydel E.R.
Published: February 2025

E-consultation in health care can be used to respond to an increasing demand for care by offering support on health-related requests. In this study we evaluated the use of an “ask-the-expert” e-consultation service in order to assess whether the service is efficient and useful. A content analysis of e-mail exchange between clients and online health professionals was performed to gain insight in the purposes of use of the service. Our findings show that the e-consultation service was used for health requests on not urgent, minor ailments. Clients asked for health information to increase knowledge on the cause of their injury or disease, its consequences, possible self-care solutions and treatment options. Decision support on assessing the necessity to visit a doctor for a certain health problem was another important reason to use the service. We believe that web-based triage systems could be used to more easily assess whether certain symptoms need to be investigated.
Measuring Use of Electronic Health Record Functionality Using System Audit Information
Authors: Bowes III Watson A.
Published: February 2025

Meaningful and efficient methods for measuring Electronic Health Record (EHR) adoption and functional usage patterns have recently become important for hospitals, clinics, and health care networks in the United State due to recent government initiatives to increase EHR use. To date, surveys have been the method of choice to measure EHR adoption. This paper describes another method for measuring EHR adoption which capitalizes on audit logs, which are often common components of modern EHRs. An Audit Data Mart is described which identified EHR functionality within 836 Departments, within 22 Hospitals and 170 clinics at Intermountain Healthcare, a large integrated delivery system. The Audit Data Mart successfully identified important and differing EHR functional usage patterns. These patterns were useful in strategic planning, tracking EHR implementations, and will likely be utilized to assist in documentation of “Meaningful Use” of EHR functionality.
Desiderata for a Computer-Assisted Audit Tool for Clinical Data Source Verification Audits
Authors: Duda Stephany N.  , Wehbe Firas H.  , Gadd Cynthia S.
Published: February 2025

Clinical data auditing often requires validating the contents of clinical research databases against source documents available in health care settings. Currently available data audit software, however, does not provide features necessary to compare the contents of such databases to source data in paper medical records. This work enumerates the primary weaknesses of using paper forms for clinical data audits and identifies the shortcomings of existing data audit software, as informed by the experiences of an audit team evaluating data quality for an international research consortium. The authors propose a set of attributes to guide the development of a computer-assisted clinical data audit tool to simplify and standardize the audit process.
Foundations for a Nursing Services Reference Model
Authors: Heslop Liza  , Toh Keith  , Hovenga Evelyn
Published: February 2025

The Nursing Services Reference Model (NSRM) is presented as a theoretical position and discussion paper. The aims are to describe the components of the NSRM concept, to explain why such a model needs to be developed and to explore methodological issues in the development of a NSRM. The concept is important to address as it may illuminate a most pressing problem faced by the Australian health care industry where the content and activity of nursing practice is not embedded as computer processable data in health information system structures. Digital documentation of nursing content and activity is urgently needed to enable reliable electronic processing of nursing services. However, it is necessary, prior to this, to develop a reference model that describes the range of nursing services in an unambiguous manner.
Data mining techniques for analyzing stroke care processes
Authors: Panzarasa Silvia  , Quaglini Silvana  , Sacchi Lucia  , Cavallini Anna  , Micieli Giuseppe  , Stefanelli Mario
Published: February 2025

Controlled randomized clinical trials and meta-analyses show that stroke patients benefit from access to specialized Stroke Units, in terms of mortality, disability and dependency. However, many issues relating to stroke diagnosis and therapy and to the organization of stroke care remain to be solved and little is known about what interventions make Stroke Units more effective. It is also agreed that compliance with clinical practice guidelines improves health outcomes for these patients, but little is known about the relative weight of the different guideline recommendations. Over the last decade, many hospital- or population-based stroke registers have been set up with the aim of identifying specific key indicators able to monitor the quality and adequacy of acute stroke care. Registers seem to be adequate tools for collecting the data needed to analyze care processes, providing data useful for both national healthcare planning and scientific research. In this paper we applied data mining techniques to data collected within the stroke register of the Lombardia region in Italy. From our analyses both expected and unexpected results have been found: not always compliance to recommendations is related to a good patients' outcome.
Text Mining approaches for Automated Literature Knowledge Extraction and Representation
Authors: Nuzzo Angelo  , Mulas Francesca  , Gabetta Matteo  , Arbustini Eloisa  , Zupan Blaž  , Larizza Cristiana  , Bellazzi Riccardo
Published: February 2025

Due to the overwhelming volume of published scientific papers, information tools for automated literature analysis are essential to support current biomedical research. We have developed a knowledge extraction tool to help researcher in discovering useful information which can support their reasoning process. The tool is composed of a search engine based on Text Mining and Natural Language Processing techniques, and an analysis module which process the search results in order to build annotation similarity networks. We tested our approach on the available knowledge about the genetic mechanism of cardiac diseases, where the target is to find both known and possible hypothetical relations between specific candidate genes and the trait of interest. We show that the system i) is able to effectively retrieve medical concepts and genes and ii) plays a relevant role assisting researchers in the formulation and evaluation of novel literature-based hypotheses.
Data Mining to Assess Variations in Oral Anticoagulant Treatment
Authors: Nielsen Peter Brønnum  , Lundbye-Christensen Søren  , Larsen Torben Bjerregaard  , Hvilsted Rasmussen Lars  , Risom Kristensen Søren  , Münster Anna-Marie  , Hejlesen Ole K.
Published: February 2025

Variations in International Normalized Ratio's (INR) are closely related to bleeding and thrombosis incidents in patients on oral anticoagulation treatment. This study investigates predictive factors that affect INR values. Data sampled with relatively high frequency allows for detection of local INR variations, and hence also allows detection and evaluation of predictive factors where time is taken into consideration. Univariate linear regression was applied and different models were reduced into a final predictive model. F-tests were utilized to test whether or not a model reduction would benefit INR predictions, in terms of decreasing observed variance. In addition to an INR submodel, the final model includes individual interaction from the last three days change in mean warfarin intake and three days change in mean vitamin K intake. Prediction residual error was mainly reduced by the INR submodel, while the warfarin model and the vitamin K submodel did not benefit predictions to same extend compared to the INR submodel. However, more studies on the temporal aspects of the effect of warfarin seem to be relevant.
What if it Suddenly Fails? Behavioral Aspects of Advanced Driver Assistant Systems on the Example of Local Danger Alerts
Authors: Mahr Angela  , Cao Yujia  , Theune Mariët  , Dimitrova-Krause Veronika  , Schwartz Tim  , Müller Christian
Published: February 2025

Many researchers argue, in assessing the benefits of Advanced Driver Assistance Systems (ADAS) it has to be taken into account that any gains in terms of security may be again reduced by the fact they affect the drivers' behavior. In this paper, we present results of a driving simulation study in which we compare driving performance as well as driver stress in three conditions: 1) when no assistance is available (NOASSIST) ; 2) when the system is working as it should (WORK); 3) when the system suddenly fails (FAIL). Results show that the driving performance is severely affected by system failures. The drivers' ability to effectively react to suddenly appearing obstacles FAIL is significantly lower than in NOASSIST. At the same time, the stress level is significantly higher in FAIL compared to WORK.
Data-Driven Detection of Recursive Program Schemes
Authors: Hofmann Martin  , Schmid Ute
Published: February 2025

We present an extension to a current approach to inductive programming (IGOR2), that is, learning (recursive) programs from incomplete specifications such as input/outout examples. IGOR2 uses an analytical, example-driven strategy for generalization. We extend the set of IGOR2's refinement operators by a further operator – identification of higher-order schemes – and can show that this extension does improve speed as well as scope.
Formal Analysis of Models for the Mammalian Vision System
Authors: Mender Bedeho
Published: February 2025

In this paper we present a rigorous definition of classification in a common family of models for the mammalian vision system, and provide a formal analysis of classification power in this family. We characterize the power of a single unit, and subsequently demonstrate how to reduce a network of arbitrary topology and size to such a single unit. We finally show how such a network, via a reduction to a single unit, is equivalent to a simple 3 layer feed forward network of threshold unitsNumenta Inc.(http://www.numenta.com) is a private company, founded by D. Dubinsky, D. George and J. Hawkins, developing a general purpose computing platform, called NuPiC, based on the HTM model.
Automatically Constructing Dictionaries for Extracting Meaningful Crime Information from Arabic Text
Authors: Alruily Meshrif  , Ayesh Aladdin  , Zedan Hussein
Published: February 2025

Arabic is widely spoken language but very few text mining tools have been developed for Arabic language. This paper presents an algorithm for automatically building dictionaries. The target domain is crime profiling. The corpus is mined for crime type, location and nationality. This work is then validated through three experiments, the results of which show that the algorithm developed here is promising.
Computation in Extended Argumentation Frameworks
Authors: Dunne Paul E.  , Modgil Sanjay  , Bench-Capon Trevor
Published: February 2025

Extended Argumentation Frameworks (EAFs) are a recently proposed formalism that develop abstract argumentation frameworks (AFs) by allowing attacks between arguments to be attacked themselves: hence EAFs add a relationship 𝒟 ⊆ 𝒳 × 𝒜 to the arguments (𝒳) and attacks (𝒜 ⊆ 𝒳 × 𝒳) in an AF's basic directed graph structure ⟨𝒳,𝒜⟩. This development provides a natural way to represent and reason about preferences between arguments. Studies of EAFs have thus far focussed on acceptability semantics, proof-theoretic processes, and applications. However, no detailed treatment of their practicality in computational settings has been undertaken. In this paper we address this lacuna, considering algorithmic and complexity properties specific to EAFs. We show that (as for standard AFs) the problem of determining if an argument is acceptable w.r.t. a subset of 𝒳 is polynomial time decidable and, thus, determining the grounded extension and verifying admissibility are efficiently solvable. We, further, consider the status of a number of decision questions specific to the EAF formalism in the sense that these have no counterparts within AFs.
Landmarks in Hierarchical Planning
Authors: Elkawkagy Mohamed  , Schattenberg Bernd  , Biundo Susanne
Published: February 2025

In this paper we introduce a novel landmark technique for hierarchical planning. Landmarks are abstract tasks that are mandatory. They have to be performed by any solution plan. Our technique relies on a landmark extraction procedure that pre-processes a given planning problem by systematically analyzing the ways in which relevant abstract tasks can be decomposed. We show how the landmark information is used to guide hierarchical planning and present some experimental results that give evidence for the considerable performance increase gained through our technique.
Identifying Necessary Reactions in Metabolic Pathways by Minimal Model Generation
Authors: Soh Takehide  , Inoue Katsumi
Published: February 2025

In systems biology, identifying vital functions like glycolysis from a given metabolic pathway is important to understand living organisms. In this paper, we focus on the problem of finding minimal sub-pathways producing target metabolites from source metabolites. We translate laws of biochemical reactions into propositional formulas and compute its minimal models to solve the problem. An advantage of our method is that it can treat reversible reactions. Moreover the translation enables us to obtain solutions for large pathways. We apply our method to a whole Escherichia coli metabolic pathway. As a result, we have found the conventional glycolysis sub-pathway described in a biological database EcoCyc.
Adaptive Gaussian Process for Short-Term Wind Speed Forecasting
Authors: Jiang Xiaoqian  , Dong Bing  , Xie Le  , Sweeney Latanya
Published: February 2025

We study the problem of short term wind speed prediction, which is a critical factor for effective wind power generation. This is a challenging task due to the complex and stochastic behavior of the wind environment. Observing various periods in the wind speed time series present different patterns, we suggest a nonlinear adaptive framework to model various hidden dynamic processes. The model is essentially data driven, which leverages non-parametric Heteroscdastic Gaussian Process to model relevant patterns for short term prediction. We evaluate our model on two different real world wind speed datasets from National Data Buoy Center. We compare our results to state-of-arts algorithms to show improvement in terms of both Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE).
A note on the complexity of some multiobjective A* search algorithms
Authors: Mandow Lawrence  , Pérez de la Cruz José-Luis
Published: February 2025

This paper studies the complexity of two different algorithms proposed as extensions of A* for multiobjective search: MOA* and NAMOA*. It is known that, for any given problem, NAMOA* requires the consideration of no more alternatives than MOA* when provided with the same heuristic information.
Learning better together
Authors: Bourgne Gauvain  , Soldano Henry  , El Fallah Seghrouchni Amal
Published: February 2025

This article addresses collaborative concept learning in a MAS. In a concept learning problem an agent incrementally revises a hypothetical representation of some target concept to keep it consistent with the whole set of examples that it receives from the environment or from other agents. In the program SMILE, this notion of consistency was extended to a group of agents. A surprising experimental result of that work was that a group of agents learns better the difficult boolean problems, than a unique agent receiving the same examples. The first purpose of the present paper is to propose some explanation about such unexpected superiority of collaborative learning. Furthermore, when considering large societies of agents, using pure sequential protocols is unrrealistic. The second and main purpose of this paper is thus to propose and experiment broadcast protocols for collaborative learning.
The Complexity of Handling Minimal Solutions in Logic-Based Abduction
Authors: Pichler Reinhard  , Woltran Stefan
Published: February 2025

Logic-based abduction is an important reasoning method with many applications in Artificial Intelligence including diagnosis, planning, and configuration. The goal of an abduction problem is to find a “solution”, i.e., an explanation for some observed symptoms. Usually, many solutions exist, and one is often interested in minimal ones only. Previous definitions of “solutions” to an abduction problem tacitly made an open-world assumption. However, as far as minimality is concerned, this assumption may not always lead to the desired behavior. To overcome this problem, we propose a new definition of solutions based on a closed-world approach. Moreover, we also introduce a new variant of minimality where only a part of the hypotheses is subject to minimization. A thorough complexity analysis reveals the close relationship between these two new notions as well as the differences compared with previous notions of solutions.
A NEAT Way for Evolving Echo State Networks
Authors: Chatzidimitriou Kyriakos C.  , Mitkas Pericles A.
Published: February 2025

The Reinforcement Learning (RL) paradigm is an appropriate formulation for agent, goal-directed, sequential decision making. In order though for RL methods to perform well in difficult, complex, real-world tasks, the choice and the architecture of an appropriate function approximator is of crucial importance. This work presents a method of automatically discovering such function approximators, based on a synergy of ideas and techniques that are proven to be working on their own. Using Echo State Networks (ESNs) as our function approximators of choice, we try to adapt them, by combining evolution and learning, for developing the appropriate ad-hoc architectures to solve the problem at hand. The choice of ESNs was made for their ability to handle both non-linear and non-Markovian tasks, while also being capable of learning online, through simple gradient descent temporal difference learning. For creating networks that enable efficient learning, a neuroevolution procedure was applied. Appropriate topologies and weights were acquired by applying the NeuroEvolution of Augmented Topologies (NEAT) method as a meta-search algorithm and by adapting ideas like historical markings, complexification and speciation, to the specifics of ESNs. Our methodology is tested on both supervised and reinforcement learning testbeds with promising results.
Unsupervised Layer-Wise Model Selection in Deep Neural Networks
Authors: Arnold Ludovic  , Paugam-Moisy Hélène  , Sebag Michèle
Published: February 2025

Deep Neural Networks (DNN) propose a new and efficient ML architecture based on the layer-wise building of several representation layers. A critical issue for DNNs remains model selection, e.g. selecting the number of neurons in each DNN layer. The hyper-parameter search space exponentially increases with the number of layers, making the popular grid search-based approach used for finding good hyper-parameter values intractable. The question investigated in this paper is whether the unsupervised, layer-wise methodology used to train a DNN can be extended to model selection as well. The proposed approach, considering an unsupervised criterion, empirically examines whether model selection is a modular optimization problem, and can be tackled in a layer-wise manner. Preliminary results on the MNIST data set suggest the answer is positive. Further, some unexpected results regarding the optimal size of layers depending on the training process, are reported and discussed.
Dealing with the dynamics of proof-standard in argumentation-based decision aiding
Authors: Ouerdane Wassila  , Maudet Nicolas  , Tsoukias Alexis
Published: February 2025

Usually, in argumentation, the proof-standards that are used are fixed a priori by the procedure. However (multicriteria) decision-aiding is a context where it may be modified dynamically during the process, depending on the responses of the decision-maker. The expert indeed needs to adapt and refine its choice of an appropriate method of aggregating arguments pros and cons, so that it fits the preference model inferred from the interaction. In this short paper we introduce how this aspect can be handled in an argumentation-based decision-aiding framework. The first contribution of the paper is conceptual: the notion of a concept lattice based on simple properties and allowing to navigate among the different proof-standards is put forward. We then show how this can be integrated within the Carneades model.
Research of Modeling System for Soil Classification in Geological Reconnaissance Based APNN-RBF Neural Network
Authors: Cheng Tao  , Yan Keqin
Published: February 2025

This paper introduced the method and principle of a traditional probability neural network (PNN) and an adaptive probability neural network (APNN). Based on inverse problem theory, the question of soil classify is investigated. A new method based on the APNN and RBF neural network is put forward. And an intellectualized analysis system of soil classification is established, consisting of parameter estimation and pat-tern recognition. In the system, the variability of soil physical parameters is thought to be small, whereas variability of mechanics parameters is large. A RBF neural network model is established to reflect mechanics pa-rameters according physics parameters. It can offer a good approach to soil classify by APNN. Examples presented in the paper indicate that this method is neat and effective.
Using Artificial Neural Networks For Evaluation of Collapse Potential of Some Iraqi Gypseous Soils
Authors: Mahmood Khalid R.  , Aziz Juneid
Published: February 2025

In this research, Artificial Neural Networks (ANNs) is used in an attempt to predict collapse potential of gypseous soils. Two models are built; one for collapse potential obtained by single oedemeter test and the other is for collapse potential obtained by double oedemeter test. A database of laboratory measurements for collapse potential is used. Six parameters, which are 1.Gypsum content, 2.Initial void ratio, 3.Total unit weight, 4.Initial water content, 5.Dry unit weight, 6.Soaking pressure. are considered to have the most significant impact on the magnitude of collapse potential and used as an input to the models. The output model is the corresponding collapse potential. Multi-layer perceptron trainings using back propagation algorithm are used in this work. A number of issues in relation to ANN construction such as the effect of ANN geometry and internal parameters on the performance of ANN models are investigated. Information on the relative importance of the factors affecting the collapse potential are presented and practical equations for prediction of collapse potential of single oedemeter test and double oedemeter test in gypseous soils are developed. It is found that ANNs have the ability to predict the collapse potential of single oedemeter test and double oedemeter test in gypseous soil samples with a good degree of accuracy. The ANN models developed to study the impact of the internal network parameters on model performance indicate that ANN performance is sensitive to the number of hidden layer nodes, momentum terms, learning rate, and transfer functions. The sensitivity analysis indicated that the initial void ratio and gypsum content have the most significant affect on the prediction of collapse potential.
3D Reconstruction of Rock Cracks CT Image Fractal Damage Study
Authors: Zhang Fei  , Zhou Haidong  , Zhao Yunxia
Published: February 2025

Based on the CT image of rock, we come up with a new method of CT image analysis and make the best use of information of CT images. Accomplish reinforcement of CT image of rock according to regulating contrast of CT image. The real microstructure, cranny and hole could be extracted through the technique of image segmentation. On the basis stated above, Marching Cube algorithm is applied to conduct a 3D reconstruction of successive CT tomographic images, visualization is implemented on rock cracks distribution during different damage stages, In this way we can get not only the directly visual course of damage propagation but also a digital representation of the actual spatial distribution of different materials in the rock. And we define the damage variable about damage volume and obtained the relation between damage variable and damage deviatoric stress which correspond exactly to the damage propagation characteristics. Lastly, we calculate the box counting dimension of the rock sample, and through observation of the dimension curve, we summarize the changes of rock damage under stress.
Exploratory Drilling with Recorded Parameters using Wireless Technology
Authors: Alkassis Carla  , Nassif Eliane  , Elhajj Imad  , Najjar Shadi  , Sadek Salah
Published: February 2025

Instrumented exploratory drilling in rock has been widely used in geotechnical engineering and in the oil and gas industry to characterize geological formations and to investigate the presence of subsurface cavities and soft spots. Instrumented drilling involves monitoring the drilling process by measuring a number of drilling parameters using sensors that are mounted to the drill rig. The data collection process used in conventional instrumented borehole drilling suffers from several limitations that are associated with the use of cables. The cables are susceptible to damage during drilling and could cause disruption to the drilling process. The objective of this paper is to present an enhanced system for instrumented borehole drilling that was developed to achieve (1) wireless data acquisition that would eliminate the need for cables and allow for remote access and control of the data, (2) automated real-time detection of cavities and soft spots, and (3) enhanced measurement of the rate of penetration using a laser sensor. Field implementation and testing of the wireless drilling system indicated an adequate functionality of the sensors used and their proper communication with the wireless data acquisition system and offered a realistic demonstration of the system.
Integration of surface and subsurface data for civil engineering
Authors: Hack Robert
Published: February 2025

Digital geoinformation for the surface and subsurface is virtually never integrated in civil engineering projects. Reasons are that the surface information is gathered by different person's and that the subsurface information is in different formats from the surface information. Likelihood and uncertainty of subsurface models is not quantifiable. To quantify the likelihood and correctness of the subsurface information the civil engineer would have to have full access to the original data, which is not available due to the none integration of the data. In the last 10 years considerable progress has been made in use of geographic information systems but the progress in the integration of data and the addressing of likelihood of subsurface data is limited.