33,593 research outputs found

    Design de fiabilidade bidimensional do software de múltiplos lançamentos tendo em conta o fator de redução de falhas na depuração imperfeita

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    Introduction: The present research was conducted at the University of Delhi, India in 2017. Methods: We develop a software reliability growth model to assess the reliability of software products released in multiple versions under limited availability of resources and time. The Fault Reduction Factor (frf) is considered to be constant in imperfect debugging environments while the rate of fault removal is given by Delayed S-Shaped model. Results: The proposed model has been validated on a real life four-release dataset by carrying out goodness of fit analysis. Laplace trend analysis was also conducted to judge the trend exhibited by data with respect to change in the system’s reliability. Conclusions: A number of comparison criteria have been calculated to evaluate the performance of the proposed model relative to only time-based multi-release Software Reliability Growth Model (srgm). Originality: In general, the number of faults removed is not the same as the number of failures experienced in given time intervals, so the inclusion of frf in the model makes it better and more realistic. A paradigm shift has been observed in software development from single release to multi release platform. Limitations: The proposed model can be used by software developers to take decisions regarding the release time for different versions, by either minimizing the development cost or maximizing the reliability and determining the warranty policies.Introducción: la presente investigación se realizó en la Universidad de Delhi, India en 2017. Métodos: desarrollamos un modelo de crecimiento de confiabilidad de software para evaluar la confiabilidad de los productos de software lanzados en múltiples versiones bajo disponibilidad limitada de recursos y tiempo. El factor de reducción de fallas (frf) se considera una constante en entornos de depuración imperfecta, mientras que la tasa de eliminación de fallas está dada por el modelo de forma retardada en S. Resultados: se valida el modelo propuesto en un conjunto de datos de cuatro lanzamientos de la vida real mediante un análisis de bondad de ajuste. También se aplicó el análisis de tendencia de Laplace para juzgar la tendencia que presentan los datos con respecto al cambio en la confiabilidad del sistema. Conclusiones: se calculó una serie de criterios de comparación para evaluar el rendimiento del modelo propuesto en relación con el modelo de crecimiento de confiabilidad del software (srgm) de múltiples lanzamientos basado únicamente en el tiempo. Originalidad: en general, el número de fallas eliminadas no es el mismo que el número de fallas experimentadas en intervalos de tiempo determinados, por lo que la inclusión de frf en el modelo lo mejora y lo hace más realista. Se ha observado un cambio de paradigma en el desarrollo de software, que pasa de un lanzamiento único a una plataforma múltiples lanzamientos. Limitaciones: los desarrolladores de software pueden emplear el modelo propuesto para tomar decisiones con respecto al tiempo de lanzar diferentes versiones, ya sea minimizando el costo de desarrollo o maximizando la confiabilidad y determinando las políticas de la garantía.Introdução: esta pesquisa foi realizada na Universidade de Deli, na Índia, em 2017. Métodos: desenvolvemos um modelo de crescimento de confiabilidade de software para avaliar a confiabilidade dos produtos de software lançados em múltiplas versões sob disponibilidade limitada de recursos e tempo. O fator de redução de falhas (frf) é considerado uma constante em contextos de depuração imperfeita, enquanto a taxa de eliminação de falhas é dada pelo modelo de forma retardada em S.Resultados: o modelo proposto é avaliado em um conjunto de dados de quatro lançamentos da vida real mediante uma análise de bondade de ajuste. Também foi utilizada a análise de tendência de Laplace para avaliar a tendência apresentada pelos dados com respeito à mudança na confiabilidade do sistema.Conclusões: uma série de critérios de comparação foi calculada para avaliar o rendimento do modelo proposto em relação com o modelo de crescimento de confiabilidade do software (srgm) de múltiplos lançamentos baseado unicamente no tempo.Originalidade: em geral, o número de falhas eliminadas não é o mesmo que o número de falhas existentes em intervalos de tempo determinados, sendo assim, a inclusão do frf no modelo o torna melhor e mais realista. Foi observada uma mudança de paradigma no desenvolvimento de software, que passa de um lançamento único a uma plataforma de múltiplos lançamentos.Limitações: o modelo proposto pode ser utilizado pelos desenvolvedores de software para tomar decisões com respeito ao tempo de lançar diferentes versões, seja para minimizar o custo de desenvolvimento ou maximizar a confiabilidade e determinar as políticas de garantia

    Entropy based Software Reliability Growth Modelling for Open Source Software Evolution

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    During Open Source Software (OSS) development, users submit "new features (NFs)", "feature improvements (IMPs)" and bugs to fix. A proportion of these issues get fixed before the next software release. During the introduction of NFs and IMPs, the source code files change. A proportion of these source code changes may result in generation of bugs. We have developed calendar time and entropy-dependent mathematical models to represent the growth of OSS based on the rate at which NFs are added, IMPs are added, and bugs introduction rate.The empirical validation has been conducted on five products, namely "Avro, Pig, Hive, jUDDI and Whirr" of the Apache open source project. We compared the proposed models with eminent reliability growth models, Goel and Okumoto (1979) and Yamada et al. (1983) and found that the proposed models exhibit better goodness of fit

    AI and OR in management of operations: history and trends

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    The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested

    Curses, Tradeoffs, and Scalable Management:Advancing Evolutionary Multiobjective Direct Policy Search to Improve Water Reservoir Operations

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    Optimal management policies for water reservoir operation are generally designed via stochastic dynamic programming (SDP). Yet, the adoption of SDP in complex real-world problems is challenged by the three curses of dimensionality, modeling, and multiple objectives. These three curses considerably limit SDP’s practical application. Alternatively, this study focuses on the use of evolutionary multiobjective direct policy search (EMODPS), a simulation-based optimization approach that combines direct policy search, nonlinear approximating networks, and multiobjective evolutionary algorithms to design Pareto-approximate closed-loop operating policies for multipurpose water reservoirs. This analysis explores the technical and practical implications of using EMODPS through a careful diagnostic assessment of the effectiveness and reliability of the overall EMODPS solution design as well as of the resulting Pareto-approximate operating policies. The EMODPS approach is evaluated using the multipurpose Hoa Binh water reservoir in Vietnam, where water operators are seeking to balance the conflicting objectives of maximizing hydropower production and minimizing flood risks. A key choice in the EMODPS approach is the selection of alternative formulations for flexibly representing reservoir operating policies. This study distinguishes between the relative performance of two widely-used nonlinear approximating networks, namely artificial neural networks (ANNs) and radial basis functions (RBFs). The results show that RBF solutions are more effective than ANN ones in designing Pareto approximate policies for the Hoa Binh reservoir. Given the approximate nature of EMODPS, the diagnostic benchmarking uses SDP to evaluate the overall quality of the attained Pareto-approximate results. Although the Hoa Binh test case’s relative simplicity should maximize the potential value of SDP, the results demonstrate that EMODPS successfully dominates the solutions derived via SDP

    Modeling water resources management at the basin level: review and future directions

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    Water quality / Water resources development / Agricultural production / River basin development / Mathematical models / Simulation models / Water allocation / Policy / Economic aspects / Hydrology / Reservoir operation / Groundwater management / Drainage / Conjunctive use / Surface water / GIS / Decision support systems / Optimization methods / Water supply

    Deriving optimal operational policies for off-stream man-made reservoir considering conjunctive use of surface- and groundwater at the Bar dam reservoir (Iran)

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    Study region: The off-stream artificial Bar lake, built in 2015 to store the flood flows of the Bar river for domestic and industrial needs and with the objective to intentionally recharge the aquifer, is situated in the Razavi Khorasan province (Iran). Study focus: We present a methodology, based on the combination of a MODFLOW groundwater flow model for estimating seepage rates, and an optimization model, for the management and operation of an artificial reservoir considering surface/groundwater interactions for satisfying 12 Mm3/year of water demand. We simulated the reliable amount of water that can be supplied from the reservoir, considering reservoir seepage, maximizing water supply yields subject to the water supply reliability requirements, and the additional intentional volume of groundwater recharge. New hydrological insights for the region: Our results demonstrate the reliability of conjunctive use of surface-and ground-water in water scarce areas by exploiting reservoir infrastructures with relevant leakage losses, also for creating additional aquifer storage. In such systems, man-induced changes of lake stages can significantly affect the volume of water that seeps through the lakebed. The aquifer, under managed aquifer recharge operations, may then provide the resource not satisfied by the reservoir release, fulfilling 100 % reliability of water supply. The conjunctive use of surface- and ground-water, by improving water security, may open new sustainability views for leaking reservoirs, even if they were not initially designed for increasing aquifer recharge, in many areas worldwide

    Requirements for building information modeling based lean production management systems for construction

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    Smooth flow of production in construction is hampered by disparity between individual trade teams' goals and the goals of stable production flow for the project as a whole. This is exacerbated by the difficulty of visualizing the flow of work in a construction project. While the addresses some of the issues in Building information modeling provides a powerful platform for visualizing work flow in control systems that also enable pull flow and deeper collaboration between teams on and off site. The requirements for implementation of a BIM-enabled pull flow construction management software system based on the Last Planner System™, called ‘KanBIM’, have been specified, and a set of functional mock-ups of the proposed system has been implemented and evaluated in a series of three focus group workshops. The requirements cover the areas of maintenance of work flow stability, enabling negotiation and commitment between teams, lean production planning with sophisticated pull flow control, and effective communication and visualization of flow. The evaluation results show that the system holds the potential to improve work flow and reduce waste by providing both process and product visualization at the work face

    Recent advances in 3D printing of biomaterials.

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    3D Printing promises to produce complex biomedical devices according to computer design using patient-specific anatomical data. Since its initial use as pre-surgical visualization models and tooling molds, 3D Printing has slowly evolved to create one-of-a-kind devices, implants, scaffolds for tissue engineering, diagnostic platforms, and drug delivery systems. Fueled by the recent explosion in public interest and access to affordable printers, there is renewed interest to combine stem cells with custom 3D scaffolds for personalized regenerative medicine. Before 3D Printing can be used routinely for the regeneration of complex tissues (e.g. bone, cartilage, muscles, vessels, nerves in the craniomaxillofacial complex), and complex organs with intricate 3D microarchitecture (e.g. liver, lymphoid organs), several technological limitations must be addressed. In this review, the major materials and technology advances within the last five years for each of the common 3D Printing technologies (Three Dimensional Printing, Fused Deposition Modeling, Selective Laser Sintering, Stereolithography, and 3D Plotting/Direct-Write/Bioprinting) are described. Examples are highlighted to illustrate progress of each technology in tissue engineering, and key limitations are identified to motivate future research and advance this fascinating field of advanced manufacturing

    Optimal operation of dams/reservoirs emphasizing potential environmental and climate change impacts

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    Mahdi studied the potential ecological and climate change impacts on management of dams. He developed several new optimization frameworks in which benefits of dams are maximized, while above impacts are mitigated. Governments and consulting engineers can use the proposed frameworks for managing dams considering environmental challenges in river basins
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