Collaborative Decision Making Tools : A Comparative Study Based on Functionalities

International audienceThis paper is on collaborative decision making issues. The study is on collaborative decision making tools. To do that, a state of the art of these tools supporting collaborative work in general and especially the tools supporting collaborative decision making process GDSS (Group Decision Support System) has been realized. A comparative study of these systems is made in order to highlight their strengths and their weaknesses. That aims to be a kind of tools selection guide, useful for mediated decision makers, in particular the facilitator

Decentralized Smart Charging of Large-Scale EVs using Adaptive Multi-Agent Multi-Armed Bandits

The drastic growth of electric vehicles and photovoltaics can introduce new challenges, such as electrical current congestion and voltage limit violations due to peak load demands. These issues can be mitigated by controlling the operation of electric vehicles i.e., smart charging. Centralized smart charging solutions have already been proposed in the literature. But such solutions may lack scalability and suffer from inherent drawbacks of centralization, such as a single point of failure, and data privacy concerns. Decentralization can help tackle these challenges. In this paper, a fully decentralized smart charging system is proposed using the philosophy of adaptive multi-agent systems. The proposed system utilizes multi-armed bandit learning to handle uncertainties in the system. The presented system is decentralized, scalable, real-time, model-free, and takes fairness among different players into account. A detailed case study is also presented for performance evaluation.Comment: CIRED 2023 International Conference & Exhibition on Electricity Distribution, Jun 2023, Rome, Ital

Wiki Support for Automated Definition of Software Test Cases

The design of tests is a very important step in the software development process since it allows us to match the users’ expectations with the finished product. Considered as a cumbersome activity, efforts have been made to automatize and alleviate the burden of test generation, but it is still a largely neglected step. We propose taking advantage of existing requirement artifacts, like Scenarios that describe the dynamic of the domain in a very early stage of software development, to obtain tests from them. In particular, the approach proposed complement the Scenarios that are textually described with a glossary, the Language Extended Lexicon. Thus, a set of rules to derive tests from Scenarios is also proposed. The tests are then described using the Task/Method model. The main findings of this work consist of an extension of a previously presented set of rules. And a tool based on a media wiki platform that makes possible to record Scenarios and the Language Extended Lexicon and implement the rules to obtain the tests. The main originality of this work is the glossary which complements Scenarios, the semantic support to obtain tests and the tool to automatize the approach.Laboratorio de Investigación y Formación en Informática Avanzad

Wiki Support for Automated Definition of Software Test Cases

The design of tests is a very important step in the software development process since it allows us to match the users’ expectations with the finished product. Considered as a cumbersome activity, efforts have been made to automatize and alleviate the burden of test generation, but it is still a largely neglected step. We propose taking advantage of existing requirement artifacts, like Scenarios that describe the dynamic of the domain in a very early stage of software development, to obtain tests from them. In particular, the approach proposed complement the Scenarios that are textually described with a glossary, the Language Extended Lexicon. Thus, a set of rules to derive tests from Scenarios is also proposed. The tests are then described using the Task/Method model. The main findings of this work consist of an extension of a previously presented set of rules. And a tool based on a media wiki platform that makes possible to record Scenarios and the Language Extended Lexicon and implement the rules to obtain the tests. The main originality of this work is the glossary which complements Scenarios, the semantic support to obtain tests and the tool to automatize the approach.Laboratorio de Investigación y Formación en Informática Avanzad

A Modelling Approach to Generating User Acceptance Tests

Software testing, in particular acceptance testing, is a very important step in the development process of any application since it represents a way of matching the users’ expectations with the finished product´s capabilities. Typically considered as a cumbersome activity, many efforts have been made to alleviate the burden of writing tests by, for instance, trying to generate them automatically. However, testing still remains a largely neglected step. In this paper we propose taking advantage of existing requirement artifacts to semi-automatically generate acceptance tests. In particular, we use Scenarios, a requirement artifact used to describe business processes and requirements, and Task/Method models, a modelling approach taken from the Artificial Intelligence field. In order to generate User Acceptance tests, we propose a set of rules that allow transforming Scenarios (typically expressed in natural language), into Task/Methods that can in turn be used to generate the tests. Being high-level tests, close to the user experience, User Acceptance Tests verify that the expectations of the system are met from an end-user’s point of view. Using the proposed ideas, we show how the semi-automated generation of acceptance tests can be implemented by describing an ongoing development of a proof of concept web application designed to support the full process

A Modelling Approach to Generating User Acceptance Tests

Software testing, in particular acceptance testing, is a very important step in the development process of any application since it represents a way of matching the users’ expectations with the finished product´s capabilities. Typically considered as a cumbersome activity, many efforts have been made to alleviate the burden of writing tests by, for instance, trying to generate them automatically. However, testing still remains a largely neglected step. In this paper we propose taking advantage of existing requirement artifacts to semiautomatically generate acceptance tests. In particular, we use Scenarios, a requirement artifact used to describe business processes and requirements, and Task/Method models, a modelling approach taken from the Artificial Intelligence field. In order to generate acceptance tests, we propose a set of rules that allow transforming Scenarios (typically expressed in natural language), into Task/Methods that can in turn be used to generate the tests. Using the proposed ideas, we show how the semi-automated generation of acceptance tests can be implemented by describing an ongoing development of a proof of concept web application designed to support the full process.Laboratorio de Investigación y Formación en Informática Avanzad

UX Challenges in GDSS : An Experience Report

In this paper we present a user experience report on a Group Decision Support System. The used system is a Collaborative framework called GRoUp Support (GRUS). The experience consists in three user tests conducted in three different countries. While the locations are different, all three tests were run in the same conditions: same facilitator and tested process. In order to support the end-users. we teach the system in two different ways: a presentation of the system, and a video demonstrating how to use it. The main feedback of this experience is that the teaching step for using Collaborative tools in mandatory. The experience was conducted in the context of decision-making in the agriculture domain.Laboratorio de Investigación y Formación en Informática Avanzad

Tool support for Generating User Acceptance Tests

Software testing, in particular acceptance testing, is a very important step in the development process of any application since it represents a way of matching the users’ expectations with the finished product´s capabilities. Typically considered as a cumbersome activity, many efforts have been made to alleviate the burden of writing tests by, for instance, trying to generate them automatically. However, testing still remains a largely neglected step. In this paper we propose taking advantage of existing requirement artifacts to semi-automatically generate acceptance tests. This paper extends a previous paper in which we use Scenarios, a requirement artifact used to describe business processes and requirements, and Task/Method models, a modelling approach taken from the Artificial Intelligence field. The proposed approach derives a Task/Method model from Scenario (through rules) and from the Task/Method model specification, all alternatives in the flow of execution are provided. Using the proposed ideas, we show how the semi-automated generation of acceptance tests can be implemented by describing an ongoing development of a proof of concept web application designed to support the full process.Laboratorio de Investigación y Formación en Informática Avanzad

Exploring the genetics of irritable bowel syndrome: A GWA study in the general population and replication in multinational case-control cohorts

OBJECTIVE: IBS shows genetic predisposition, but adequately powered gene-hunting efforts have been scarce so far. We sought to identify true IBS genetic risk factors by means of genome-wide association (GWA) and independent replication studies. DESIGN: We conducted a GWA study (GWAS) of IBS in a general population sample of 11\u2005326 Swedish twins. IBS cases (N=534) and asymptomatic controls (N=4932) were identified based on questionnaire data. Suggestive association signals were followed-up in 3511 individuals from six case-control cohorts. We sought genotype-gene expression correlations through single nucleotide polymorphism (SNP)-expression quantitative trait loci interactions testing, and performed in silico prediction of gene function. We compared candidate gene expression by real-time qPCR in rectal mucosal biopsies of patients with IBS and controls. RESULTS: One locus at 7p22.1, which includes the genes KDELR2 (KDEL endoplasmic reticulum protein retention receptor 2) and GRID2IP (glutamate receptor, ionotropic, delta 2 (Grid2) interacting protein), showed consistent IBS risk effects in the index GWAS and all replication cohorts and reached p=9.31 710(-6) in a meta-analysis of all datasets. Several SNPs in this region are associated with cis effects on KDELR2 expression, and a trend for increased mucosal KDLER2 mRNA expression was observed in IBS cases compared with controls. CONCLUSIONS: Our results demonstrate that general population-based studies combined with analyses of patient cohorts provide good opportunities for gene discovery in IBS. The 7p22.1 and other risk signals detected in this study constitute a good starting platform for hypothesis testing in future functional investigations. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions

Prediction of Ideas Number During a Brainstorming Session

International audienceIn this paper, we present an approach allowing the prediction of ideas number during a brainstorming session. This prediction is based on two dynamic models of brainstorming, the non-cognitive and the cognitive models proposed by Brown and Paulus (Small Group Res 27(1):91–114, 1996). These models describe for each participant, the evolution of ideas number over time, and are formalized by differential equations. Through solution functions of these models, we propose to calculate the number of ideas of each participant on any time intervals and thus in the future (called prediction). To be able to compute solution functions, it is necessary to determine the parameters of these models. In our approach, we use optimization model for model parameters calculation in which solution functions are approximated by numerical methods. We developed two generic optimization models, one based on Euler’s and the other on the fourth order Runge–Kutta’s numerical methods for the solving of differential equations, and we apply them to the non-cognitive and respectively to the cognitive models. Through some feasibility tests, we show the adequacy of the proposed approach to our prediction context