Case-based Reasoning Method for Real-time Expert Diagnostics Systems

The method of case-based reasoning for a solution of problems of real-time diagnostics and forecasting in intelligent decision support systems (IDSS) is considered. Special attention is drawn to case library structure for real-time IDSS (RT IDSS) and algorithm of k-nearest neighbors type. This work was supported by RFBR.

Generalized Scalarizing Problems GENS and GENSLex of Multicriteria Optimization

* This paper is partially supported by the National Science Fund of Bulgarian Ministry of Education and Science under contract № I–1401\2004 "Interactive Algorithms and Software Systems Supporting Multicriteria Decision Making".

A dynamic feature information model for integrated manufacturing planning and optimization

This paper presents a new, dynamic feature representation method for high value parts consisting of complex and intersecting features. The method first extracts features from the CAD model of a complex part. Then the dynamic status of each feature is established between various operations to be carried out during the whole manufacturing process. Each manufacturing and verification operation can be planned and optimized using the real conditions of a feature, thus enhancing accuracy, traceability and process control. The dynamic feature representation is complementary to the design models used as underlining basis in current CAD/CAM and decision support systems. © 2012 CIRP.

Consistency of the decision-maker in pair-wise comparisons

Most authors assume that the natural behaviour of the decision-maker is being inconsistent. This paper investigates the main sources of inconsistency and analyses methods for reducing or eliminating inconsistency. Decision support systems can contain interactive modules for that purpose. In a system with consistency control, there are three stages. First, consistency should be checked: a consistency measure is needed. Secondly, approval or rejection has to be decided: a threshold value of inconsistency measure is needed. Finally, if inconsistency is ‘high’, corrections have to be made: an inconsistency reducing method is needed. This paper reviews the difficulties in all stages. An entirely different approach is to elaborate a decision support system in order to force the decision-maker to give consistent values in each step of answering pair-wise comparison questions. An interactive questioning procedure resulting in consistent (sub) matrices has been demonstrated.

Vezetői döntéshozatal és versenyképesség (The managerial decision making and the competitiveness)

A tanulmány a vezetői döntéshozatal három lényeges aspektusát tárja fel. A Versenyben a világgal c. kutatási program eredményei alapján arra lehet következtetni, hogy a menedzserek döntéshozatali képességei és megközelítései, a vállalati teljesítménymérés és menedzsment döntéseket támogató szerepe, valamint a vállalatok érintettekhez fűződő viszonya meghatározó lehet a hatékony vezetői döntéshozatal során. A vállalati döntéshozatal jellemzőinek bemutatása után megvizsgáljuk azt is, hogy a különböző teljesítményű cégek döntéseit mennyire támogatja a menedzserek felkészültsége, a teljesítménymérési gyakorlat és az érintettek elvárásai. A szerzők úgy találták, hogy a fenti tényezők mindegyike hozzájárul a hazai cégek versenyképességéhez, általánosságban ugyanis elmondható, hogy a döntéseket támogató vállalati környezet jobb üzleti teljesítményhez és gyorsabb reagálóképességhez vezethet. Az eredmények összegzése mellett ajánlásokkal is éltek a vállalatok számára, amelyek alkalmazásával hatékonyabb döntéseket hozhatnak. _______ This study presents three main aspects of the managerial decision making. Based on the results of the research program In competition with the World it points to the fact that decision making abilities and approaches of the managers, the corporate performance appraisal and the management decision support role, and the corporate relations to the stakeholders will be determinant in the process of the efficient managerial decision making. After presentation of characteristics of the corporate decision making the authors examine that how the decisions of enterprises with different performances are supported by the preparedness of the managers, the performance appraisal practice and the stakeholders expectations. The authors have thought that every factor contributes to the competitiveness of the domestic enterprises, and generally the decision supporting corporate environment can lead to better business performance and faster responsive abilities. Besides the results summary the authors give useful recommendations to the corporations with which they can make more efficient decisions.

Actionable pattern analysis in computing and business intelligence systems

With advances in science and technology, computing and business intelligence (BI) systems are steadily becoming more complex with an increasing variety of heterogeneous software and hardware components. They are thus becoming progressively more difficult to monitor, manage and maintain. Traditional approaches to system management have largely relied on domain experts through a knowledge acquisition process that translates domain knowledge into operating rules and policies. It is widely acknowledged as a cumbersome, labor intensive, and error prone process, besides being difficult to keep up with the rapidly changing environments. In addition, many traditional business systems deliver primarily pre-defined historic metrics for a long-term strategic or mid-term tactical analysis, and lack the necessary flexibility to support evolving metrics or data collection for real-time operational analysis. There is thus a pressing need for automatic and efficient approaches to monitor and manage complex computing and BI systems. To realize the goal of autonomic management and enable self-management capabilities, we propose to mine system historical log data generated by computing and BI systems, and automatically extract actionable patterns from this data. This dissertation focuses on the development of different data mining techniques to extract actionable patterns from various types of log data in computing and BI systems. Four key problems—Log data categorization and event summarization, Leading indicator identification , Pattern prioritization by exploring the link structures , and Tensor model for three-way log data are studied. Case studies and comprehensive experiments on real application scenarios and datasets are conducted to show the effectiveness of our proposed approaches.

Jury decision making and the Story Model: How do deliberation style and evidence order influence the story that juries create?

This study investigated the utility of the Story Model for decision making at the jury level by examining the influence of evidence order and deliberation style on story consistency and guilt. Participants were shown a video-taped trial stimulus and then provided case perceptions including a guilt judgment and a narrative about what occurred during the incident. Participants then deliberated for approximately thirty minutes using either an evidence-driven or verdict-driven deliberation style before again providing case perceptions, including a guilt determination, a narrative about what happened during the incident, and an evidence recognition test. Multi-level regression analyses revealed that evidence order, deliberation style and sample interacted to influence both story consistency measures and guilt. Among students, participants in the verdict-driven deliberation condition formed more consistent pro-prosecution stories when the prosecution presented their case in story-order, while participants in the evidence-driven deliberation condition formed more consistent pro-prosecution stories when the defense's case was presented in story-order. Findings were the opposite among community members, with participants in the verdict-driven deliberation condition forming more consistent pro-prosecution stories when the defense's case was presented in story-order, and participants in the evidence-driven deliberation condition forming more consistent pro-prosecution stories when the prosecution's case was presented in story-order. Additionally several story consistency measures influenced guilt decisions. Thus there is some support for the hypothesis that story consistency mediates the influence of evidence order and deliberation style on guilt decisions.

Parental involvement and group cognitive behavioral treatment for anxiety disorders in children and adolescents: Treatment specificity and mediation effects of parent and peer variables

Phobic and anxiety disorders are one of the most common, if not the most common and debilitating psychopathological conditions found among children and adolescents. As a result, a treatment research literature has accumulated showing the efficacy of cognitive behavioral treatment (CBT) for reducing anxiety disorders in youth. This dissertation study compared a CBT with parent and child (i.e., PCBT) and child group CBT (i.e., GCBT). These two treatment approaches were compared due to the recognition that a child’s context has an effect on the development, course, and outcome of childhood psychopathology and functional status. The specific aims of this dissertation were to examine treatment specificity and mediation effects of parent and peer contextual variables. The sample consisted of 183 youth and their mothers. Research questions were analyzed using analysis of variance for treatment outcome, and structural equation modeling, accounting for clustering effects, for treatment specificity and mediation effects. Results indicated that both PCBT and GCBT produced positive treatment outcomes across all indices of change (i.e., clinically significant improvement, anxiety symptom reduction) and across all informants (i.e., youths and parents) with no significant differences between treatment conditions. Results also showed partial treatment specific effects of positive peer relationships in GCBT. PCBT also showed partial treatment specific effects of parental psychological control. Mediation effects were only observed in GCBT; positive peer interactions mediated treatment response. The results support the use CBT with parents and peers for treating childhood anxiety. The findings’ implications are further discussed in terms of the need to conduct further meditational treatment outcome designs in order to continue to advance theory and research in child and anxiety treatment.

Modelling nitrous oxide emissions from mown-grass and grain-cropping systems : Testing and sensitivity analysis of DailyDayCent using high frequency measurements

The lead author, Nimai Senapati (Post doc), was funded by the European community’s Seventh Framework programme (FP2012-2015) under grant agreement no. 262060 (ExpeER). The research leading to these results has received funding principally from the ANR (ANR-11-INBS-0001), AllEnvi, CNRS-INSU. We would like to thank the National Research Infrastructure ‘Agro-écosystèmes, Cycles Biogéochimique et Biodiversité (SOERE-ACBB http://www.soere-acbb.com/fr/) for their support in field experiment. We are deeply indebted to Christophe deBerranger, Xavier Charrier for their substantial technical assistance and Patricia Laville for her valuables suggestion regarding N2O flux estimation.

Decisions, decisions everywhere (in the open data era).

Abstract: Decision support systems have been widely used for years in companies to gain insights from internal data, thus making successful decisions. Lately, thanks to the increasing availability of open data, these systems are also integrating open data to enrich decision making process with external data. On the other hand, within an open-data scenario, decision support systems can be also useful to decide which data should be opened, not only by considering technical or legal constraints, but other requirements, such as "reusing potential" of data. In this talk, we focus on both issues: (i) open data for decision making, and (ii) decision making for opening data. We will first briefly comment some research problems regarding using open data for decision making. Then, we will give an outline of a novel decision-making approach (based on how open data is being actually used in open-source projects hosted in Github) for supporting open data publication. Bio of the speaker: Jose-Norberto Mazón holds a PhD from the University of Alicante (Spain). He is head of the "Cátedra Telefónica" on Big Data and coordinator of the Computing degree at the University of Alicante. He is also member of the WaKe research group at the University of Alicante. His research work focuses on open data management, data integration and business intelligence within "big data" scenarios, and their application to the tourism domain (smart tourism destinations). He has published his research in international journals, such as Decision Support Systems, Information Sciences, Data & Knowledge Engineering or ACM Transaction on the Web. Finally, he is involved in the open data project in the University of Alicante, including its open data portal at http://datos.ua.es

Decision making models embedded into a web-based tool for assessing pest infestation risk

Current practices in agricultural management involve the application of rules and techniques to ensure high quality and environmentally friendly production. Based on their experience, agricultural technicians and farmers make critical decisions affecting crop growth while considering several interwoven agricultural, technological, environmental, legal and economic factors. In this context, decision support systems and the knowledge models that support them, enable the incorporation of valuable experience into software systems providing support to agricultural technicians to make rapid and effective decisions for efficient crop growth. Pest control is an important issue in agricultural management due to crop yield reductions caused by pests and it involves expert knowledge. This paper presents a formalisation of the pest control problem and the workflow followed by agricultural technicians and farmers in integrated pest management, the crop production strategy that combines different practices for growing healthy crops whilst minimising pesticide use. A generic decision schema for estimating infestation risk of a given pest on a given crop is defined and it acts as a metamodel for the maintenance and extension of the knowledge embedded in a pest management decision support system which is also presented. This software tool has been implemented by integrating a rule-based tool into web-based architecture. Evaluation from validity and usability perspectives concluded that both agricultural technicians and farmers considered it a useful tool in pest control, particularly for training new technicians and inexperienced farmers.

Using an end-of-life care pathway in acute stroke: a mixed methods study of decision-making and care experiences

Background: The evidence base on end-of-life care in acute stroke is limited, particularly with regard to recognising dying and related decision-making. There is also limited evidence to support the use of end-of-life care pathways (standardised care plans) for patients who are dying after stroke. Aim: This study aimed to explore the clinical decision-making involved in placing patients on an end-of-life care pathway, evaluate predictors of care pathway use, and investigate the role of families in decision-making. The study also aimed to examine experiences of end-of-life care pathway use for stroke patients, their relatives and the multi-disciplinary health care team. Methods: A mixed methods design was adopted. Data were collected in four Scottish acute stroke units. Case-notes were identified prospectively from 100 consecutive stroke deaths and reviewed. Multivariate analysis was performed on case-note data. Semi-structured interviews were conducted with 17 relatives of stroke decedents and 23 healthcare professionals, using a modified grounded theory approach to collect and analyse data. The VOICES survey tool was also administered to the bereaved relatives and data were analysed using descriptive statistics and thematic analysis of free-text responses. Results: Relatives often played an important role in influencing aspects of end-of-life care, including decisions to use an end-of-life care pathway. Some relatives experienced enduring distress with their perceived responsibility for care decisions. Relatives felt unprepared for and were distressed by prolonged dying processes, which were often associated with severe dysphagia. Pro-active information-giving by staff was reported as supportive by relatives. Healthcare professionals generally avoided discussing place of care with families. Decisions to use an end-of-life care pathway were not predicted by patients’ demographic characteristics; decisions were generally made in consultation with families and the extended health care team, and were made within regular working hours. Conclusion: Distressing stroke-related issues were more prominent in participants’ accounts than concerns with the end-of-life care pathway used. Relatives sometimes perceived themselves as responsible for important clinical decisions. Witnessing prolonged dying processes was difficult for healthcare professionals and families, particularly in relation to the management of persistent major swallowing difficulties.

"Last-Mile" preparation for a potential disaster - Interdisciplinary approach towards tsunami early warning and an evacuation information system for the coastal city of Padang, Indonesia

Extreme natural events, like e.g. tsunamis or earthquakes, regularly lead to catastrophes with dramatic consequences. In recent years natural disasters caused hundreds of thousands of deaths, destruction of infrastructure, disruption of economic activity and loss of billions of dollars worth of property and thus revealed considerable deficits hindering their effective management: Needs for stakeholders, decision-makers as well as for persons concerned include systematic risk identification and evaluation, a way to assess countermeasures, awareness raising and decision support systems to be employed before, during and after crisis situations. The overall goal of this study focuses on interdisciplinary integration of various scientific disciplines to contribute to a tsunami early warning information system. In comparison to most studies our focus is on high-end geometric and thematic analysis to meet the requirements of smallscale, heterogeneous and complex coastal urban systems. Data, methods and results from engineering, remote sensing and social sciences are interlinked and provide comprehensive information for disaster risk assessment, management and reduction. In detail, we combine inundation modeling, urban morphology analysis, population assessment, socioeconomic analysis of the population and evacuation modeling. The interdisciplinary results eventually lead to recommendations for mitigation strategies in the fields of spatial planning or coping capacity. © Author(s) 2009.

Knowledge-based management systems for the police force

Knowledge-Based Management Systems enable new ways to process and analyse knowledge to gain better insights to solve a problem and aid in decision making. In the police force such systems provide a solution for enhancing operations and improving client administration in terms of knowledge management. The main objectives of every police officer is to ensure the security of life and property, promote lawfulness, and avert and distinguish wrongdoing. The administration of knowledge and information is an essential part of policing, and the police ought to be proactive in directing both explicit and implicit knowledge, whilst adding to their abilities in knowledge sharing. In this paper the potential for a knowledge based system for the Mauritius police was analysed, and recommendations were also made, based on requirements captured from interviews with several long standing officers, and surveying of previous works in the area.

Analysis of Dyscalculia Evidences through Artificial Intelligence Systems

Dyscalculia is usually perceived of as a specific learning difficulty for mathematics or, more appropriately, arithmetic. Because definitions and diagnoses of dyscalculia are in their infancy and sometimes are contradictory. However, mathematical learning difficulties are certainly not in their infancy and are very prevalent and often devastating in their impact. Co-occurrence of learning disorders appears to be the rule rather than the exception. Co-occurrence is generally assumed to be a consequence of risk factors that are shared between disorders, for example, working memory. However, it should not be assumed that all dyslexics have problems with mathematics, although the percentage may be very high, or that all dyscalculics have problems with reading and writing. Because mathematics is very developmental, any insecurity or uncertainty in early topics will impact on later topics, hence to need to take intervention back to basics. However, it may be worked out in order to decrease its degree of severity. For example, disMAT, an app developed for android may help children to apply mathematical concepts, without much effort, that is turning in itself, a promising tool to dyscalculia treatment. Thus, this work will focus on the development of a Decision Support System to estimate children evidences of dyscalculia, based on data obtained on-the-fly with disMAT. The computational framework is built on top of a Logic Programming approach to Knowledge Representation and Reasoning, grounded on a Case-based approach to computing, that allows for the handling of incomplete, unknown, or even self-contradictory information.