Goal-oriented design of value and process models from patterns

This thesis defines a design framework and a method for modelling networked businesses. The intended application domain is electronic businesses that extensively use information and communication technology to coordinate work. The key property of the proposed approach is the reuse of design knowledge in the form of design patterns. Design patterns are extracted from models of existing electronic intermediaries considered successful. These businesses have been reverse-engineered to two types of models: economic value exchange models and business process models. The identified patterns comprise two libraries of value exchange and business process patterns, respectively. Patterns are catalogued with, among others, their context, solved problem, and proposed solution. Most importantly, they are annotated with a machine-readable\ud capability model used as a search key in the library. Capability models are part of the goal-modelling technique for business requirements proposed here. Our goal-modelling technique operationalizes each business goal with a variable and an evaluation function: the evaluation function determines when a measured variable value satisfies the goal. A goal model represents requirements if goals are assigned evaluation functions but the variable values are unknown. In such a case, the goal model specifies what is desired to happen. If, on the other hand, variable values are known, the goal model documents the capabilities of a pattern. The proposed design framework structures the development process into: (1) available design knowledge in libraries of value and process patterns, (2) business requirements captured in a goal model, and (3) economic value and business process perspectives to look at a business system. The design method prescribes steps to transform patterns and requirements into a system specification. These include: (i) identification of relevant pattern based on matching capability and requirements goal models; (ii) synthesis of value and process patterns into value and process models, respectively; and (iii) consistency check procedure for value and process model.\ud The usefulness of the approach is demonstrated in a real-life example, which shows that the framework and method exhibit a predefined set of desired properties

Optimizing cell size in Pico-cell networks

International audienceIn this paper, we present a systematic study of the uplink capacity and coverage of pico-cell wireless networks. Both the one dimensional as well as the two dimensional cases are investigated. Our goal is to compute the size of pico-cells that maximizes the spatial throughput density. To achieve this goal, we consider fluid models that allow us to obtain explicit expressions for the interference and the total received power at a base station. We study the impact of various parameters on the performance: the path loss factor, the spatial reuse factor and the receiver structure (matched filter or multiuser detector). We relate the performance of the fluid models to that of the original discrete system and show that the fluid model provides a bound for the discrete one

J Int Soc Respir Prot

Background:Coronavirus disease 2019 (COVID-19) has led to severe shortages of filtering facepiece respirators (FFRs). As a result, extended use, limited reuse, and FFR decontamination have been utilized to extend the life of single-use FFRs. Although some studies have raised concerns that reuse could affect the FFR\u2019s ability to form a seal, no comprehensive literature review of the effect of extended use or limited reuse on FFR seal exists.Objective:The goal of this review was to assess the effect of extended use and reuse on respirator fit, with and without decontamination.Methods:Searches of PubMed and Medrxiv yielded 24 papers that included assessment of fit after extended use or limited reuse on a human. One additional handpicked paper was added.Results:Studies report a wide variation in the number of donnings and doffings before fit failure between different models of respirators. Additionally, while seal checks lack sufficient sensitivity to reliably detect fit failures, individuals who failed fit testing were often able to pass subsequent tests by re-positioning the respirator. Even with failure, respirators often maintained a substantially higher level of fit than a surgical mask, so they may still provide a level of protection in crisis settings.Conclusion:Based on currently available data, this literature review was unable to establish a consensus regarding the amount of time a respirator can be worn or the number of uses before fit failure will occur. Furthermore, variations in reuses before fit failure between different models of N95 respirators limit the ability to offer a comprehensive recommendation of greater than one reuse or a specific amount of wear time.CC999999/ImCDC/Intramural CDC HHSUnited States

CiberMouse design: a case study for SAIA model reuse

The paper describes the approach proposed during the international robotic challenge : cibermouse.In the context of last year RTSS robotic competition, SAIA models and their implementation have been proposed. The goal was the development of an exploration robot. This year, the paper proposes the reuse one of these models for the ciberMouse design. The realized modifications are presented and an emphasis is made on benefits and limits of SAIA model reuse

A collective intelligence approach for building student's trustworthiness profile in online learning

(c) 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Information and communication technologies have been widely adopted in most of educational institutions to support e-Learning through different learning methodologies such as computer supported collaborative learning, which has become one of the most influencing learning paradigms. In this context, e-Learning stakeholders, are increasingly demanding new requirements, among them, information security is considered as a critical factor involved in on-line collaborative processes. Information security determines the accurate development of learning activities, especially when a group of students carries out on-line assessment, which conducts to grades or certificates, in these cases, IS is an essential issue that has to be considered. To date, even most advances security technological solutions have drawbacks that impede the development of overall security e-Learning frameworks. For this reason, this paper suggests enhancing technological security models with functional approaches, namely, we propose a functional security model based on trustworthiness and collective intelligence. Both of these topics are closely related to on-line collaborative learning and on-line assessment models. Therefore, the main goal of this paper is to discover how security can be enhanced with trustworthiness in an on-line collaborative learning scenario through the study of the collective intelligence processes that occur on on-line assessment activities. To this end, a peer-to-peer public student's profile model, based on trustworthiness is proposed, and the main collective intelligence processes involved in the collaborative on-line assessments activities, are presented.Peer ReviewedPostprint (author's final draft

OntoVIP: An ontology for the annotation of object models used for medical image simulation.

International audienceThis paper describes the creation of a comprehensive conceptualization of object models used in medical image simulation, suitable for major imaging modalities and simulators. The goal is to create an application ontology that can be used to annotate the models in a repository integrated in the Virtual Imaging Platform (VIP), to facilitate their sharing and reuse. Annotations make the anatomical, physiological and pathophysiological content of the object models explicit. In such an interdisciplinary context we chose to rely on a common integration framework provided by a foundational ontology, that facilitates the consistent integration of the various modules extracted from several existing ontologies, i.e. FMA, PATO, MPATH, RadLex and ChEBI. Emphasis is put on methodology for achieving this extraction and integration. The most salient aspects of the ontology are presented, especially the organization in model layers, as well as its use to browse and query the model repository

Software development: A paradigm for the future

A new paradigm for software development that treats software development as an experimental activity is presented. It provides built-in mechanisms for learning how to develop software better and reusing previous experience in the forms of knowledge, processes, and products. It uses models and measures to aid in the tasks of characterization, evaluation and motivation. An organization scheme is proposed for separating the project-specific focus from the organization's learning and reuse focuses of software development. The implications of this approach for corporations, research and education are discussed and some research activities currently underway at the University of Maryland that support this approach are presented

CoaCor: Code Annotation for Code Retrieval with Reinforcement Learning

To accelerate software development, much research has been performed to help people understand and reuse the huge amount of available code resources. Two important tasks have been widely studied: code retrieval, which aims to retrieve code snippets relevant to a given natural language query from a code base, and code annotation, where the goal is to annotate a code snippet with a natural language description. Despite their advancement in recent years, the two tasks are mostly explored separately. In this work, we investigate a novel perspective of Code annotation for Code retrieval (hence called `CoaCor'), where a code annotation model is trained to generate a natural language annotation that can represent the semantic meaning of a given code snippet and can be leveraged by a code retrieval model to better distinguish relevant code snippets from others. To this end, we propose an effective framework based on reinforcement learning, which explicitly encourages the code annotation model to generate annotations that can be used for the retrieval task. Through extensive experiments, we show that code annotations generated by our framework are much more detailed and more useful for code retrieval, and they can further improve the performance of existing code retrieval models significantly.Comment: 10 pages, 2 figures. Accepted by The Web Conference (WWW) 201