Performance Of Different Alternatives Research Articles

Avaliação ambiental do sistema construtivo de alvenaria de blocos de solo-cimento considerando diferentes especificações de projeto

Este trabalho teve o objetivo de avaliar os potenciais impactos ambientais no ciclo de vida de diferentes especificações de projeto do sistema de alvenaria estrutural de blocos de solo-cimento. As alternativas avaliadas foram comparadas com a alvenaria estrutural de blocos cerâmicos e de concreto. Foi utilizada a metodologia de Avaliação do Ciclo de Vida (ACV). Foram comparados diferentes tipos de processo de produção de blocos de solo-cimento, considerando um processo manual e outro mecanizado. Foram também comparados dois tipos de cimento, CP-II-E-40 e CP-V-ARI e diferentes tipos de revestimento utilizados em uma parede de blocos de solo-cimento. A alternativa de alvenaria com blocos de solo-cimento com processo manual e com cimento CP-II-E-40 foi a mais vantajosa. As alternativas de alvenaria de blocos de solo-cimento apresentaram menores impactos ambientais que a alvenaria estrutural de blocos cerâmicos e de concreto para a maioria dos casos avaliados principalmente quando o revestimento de resina acrílica é considerado, com diferenças de até 77% para a categoria de Potencial de Aquecimento Global. A pesquisa contribui por mostrar, de forma quantitativa, o desempenho ambiental de diferentes alternativas do sistema de alvenaria de blocos de solo-cimento, para o contexto brasileiro. Os resultados apresentados, especialmente as diretrizes ambientais de projeto, podem auxiliar projetistas e construtores desse sistema construtivo

Preprocessing alternatives for compositional data related to water, sanitation and hygiene

The Sustainable Development Goals (SDGs) 6.1 and 6.2 measure the progress of urban and rural populations in their access to different levels of water, sanitation and hygiene (WASH) services, based on multiple sources of information. Service levels add up to 100%; therefore, they are compositional data (CoDa). Despite evidence of zero value, missing data and outliers in the sources of information, the treatment of these irregularities with different statistical techniques has not yet been analyzed for CoDa in the WASH sector. Thus, the results may present biased estimates, and the decisions based on these results will not necessarily be appropriate. In this article, we therefore: i) evaluate methodological imputation alternatives that address the problem of having either zero values or missing values, or both simultaneously; and ii) propose the need to complement the point-to-point identification of the WHO/UNICEF Joint Monitoring Program (JMP) with other robust alternatives, to deal with outliers depending on the number of data points. These suggestions have been considered here using statistics for CoDa with isometric log-ratio (ilr) transformation. A selection of illustrative cases is presented to compare performance of different alternatives.

FINANCIAL PERFORMANCE EVALUATION USING FUZZY GRA AND FUZZY ENTROPY METHODS: WHOLESALE AND RETAIL INDUSTRY

Financial evaluation is the starting point for making business plan and strategy, therefore, this study aimed mainly to present an effective approach to evaluate the financial performance of the BIST Wholesale and Retail Industry firms listed on Istanbul Stock Exchange over the period of 2015-2018. The Fuzzy Grey Rational Analysis (GRA) method is used to evaluate financial performance of different alternatives considering the distances between fuzzy sets based on the grey and fuzzy theory. While, Fuzzy Entropy method is used to determine the relative importance of 15 financial criteria (ratios). Based on a comprehensive financial evaluation framework the study ranks the financial performance of the 17 wholesale and retail trade index firms and shows that MIPAZ firm has the best relative financial performance. Moreover, net profit margin ratio has the highest relative importance indicator for evaluating financial performance. A sensitivity analysis is presented for confirming validity of the proposed model, in addition to a comparison between fuzzy GRA and GRA is demonstrated to test the reliability of the proposed model.

Impact assessment of short-term management measures on travel demand

Travel Demand Management (TDM) can be considered as the most viable option to manage the increasing traffic demand by controlling excessive usage of personalized vehicles. TDM provides expanded options to manage existing travel demand by redistributing the demand rather than increasing the supply. To analyze the impact of TDM measures, the existing travel demand of the area should be identified. In order to get quantitative information on the travel demand and the performance of different alternatives or choices of the available transportation system, travel demand model has to be developed. This concept is more useful in developing countries like India, which have limited resources and increasing demands. Transport related issues such as congestion, low service levels and lack of efficient public transportation compels commuters to shift their travel modes to private transport, resulting in unbalanced modal splits. The present study explores the potential to implement travel demand management measures at Kazhakoottam, an IT business hub cum residential area of Thiruvananthapuram city, a medium sized city in India. Travel demand growth at Kazhakoottam is a matter of concern because the traffic is highly concentrated in this area and facility expansion costs are pretty high. A sequential four-stage travel demand model was developed based on a total of 1416 individual household questionnaire responses using the macro simulation software CUBE. Trip generation models were developed using linear regression and mode split was modelled as multinomial logit model in SPSS. The base year traffic flows were estimated and validated with field data. The developed model was then used for improving the road network conditions by suggesting short-term TDM measures. Three TDM scenarios viz; integrating public transit system with feeder mode, carpooling and reducing the distance of bus stops from zone centroids were analysed. The results indicated an increase in public transit ridership and considerable modal shift from private to public/shared transit.

A methodology for the long-term simulation and uncertainty analysis of the operational lifetime performance of wave energy converter arrays

This work presents a new methodology for the long-term simulation and uncertainty analysis of the performance of different alternatives of wave energy converter arrays. With it, we can analyze complete operational lifetime time-series of energy production for any type of wave energy converter. The methodology is based on the application of cutting edge methods, including complex wave climate simulations, downscaling techniques, numerical wave propagation and the application of Monte Carlo techniques for the uncertainty analysis of the results. The methodology was applied to arrays of 9 overtopping wave energy converters for which 9 different geometric alternatives were defined. Results of the mean energy available for the experiments carried out with Monte Carlo techniques indicate that the arrow-shaped array with a distance between devices of 6 times their diameter is the alternative in which more energy is produced. However, the results for some of the 500 experiments indicate that a different alternative is the one with the highest potential production, revealing that the most likely outcome of the experiments can be different from the hindcast results. These results highlight that simulations provide much more information for the decision-makers and that an uncertainty analysis is key towards optimizing energy production.

Variability models for generating efficient configurations of functional quality attributes

Context: Quality attributes play a critical role in the architecture elicitation phase. Software Sustainability and energy efficiency is becoming a critical quality attribute that can be used as a selection criteria to choose from among different design or implementation alternatives. Energy efficiency usually competes with other non-functional requirements, like for instance, performance.Objective: This paper presents a process that helps developers to automatically generate optimum configurations of functional quality attributes in terms of energy efficiency and performance. Functional quality attributes refer to the behavioral properties that need to be incorporated inside a software architecture to fulfill a particular quality attribute (e.g., encryption and authentication for the security quality attribute, logging for the usability quality attribute).Method: Quality attributes are characterized to identify their design and implementation variants and how the different configurations influence both energy efficiency and performance. A usage model for each characterized quality attribute is defined. The variability of quality attributes, as well as the energy efficiency and performance experiment results, are represented as a constraint satisfaction problem with the goal of formally reasoning about it. Then, a configuration of the selected functional quality attributes is automatically generated, which is optimum with respect to a selected objective function.Results: Software developers can improve the energy efficiency and/or performance of their applications by using our approach to perform a richer analysis of the energy consumption and performance of different alternatives for functional quality attributes. We show quantitative values of the benefits of using our approach and discuss the threats to validity.Conclusions: The process presented in this paper will help software developers to build more energy efficient software, whilst also being aware of how their decisions affect other quality attributes, such as performance.

Noninferiority and Equivalence Evaluation of Clinical Performance among Computed Radiography, Film, and Digitized Film for Telemammography Services

Objective. The aim of this study was to evaluate and compare the clinical performance of different alternatives to implement low-cost screening telemammography. We compared computed radiography, film printed images, and digitized films produced with a specialized film digitizer and a digital camera. Material and Methods. The ethics committee of our institution approved this study. We assessed the equivalence of the clinical performance of observers for cancer detection. The factorial design included 70 screening patients, four technological alternatives, and cases interpreted by seven radiologists, for a total of 1,960 observations. The variables evaluated were the positive predictive value (PPV), accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curves (AUC). Result. The mean values for the observed variables were as follows: accuracy ranged from 0.77 to 0.82, the PPV ranged from 0.67 to 0.68, sensitivity ranged from 0.64 to 0.74, specificity ranged from 0.87 to 0.90, and the AUC ranged from 0.87 to 0.90. At a difference of 0.1 to claim equivalence, all alternatives were equivalent for all variables. Conclusion. Our findings suggest that telemammography screening programs may be provided to underserved populations at a low cost, using a film digitizer or a digital camera.

Port management and multiple-criteria decision making under uncertainty

The methodology for port management in this study takes into account the stochastic nature of climate as well as of use and exploitation agents. It provides a probabilistic characterization of the performance of different alternatives in terms of a set of indicators that reflect the potential benefits for different interest groups. The joint distribution functions thus obtained for a set of pre-defined management alternatives are used to compare strategies and to make decisions, based on stochastic multi-criteria analysis. This method, which also addresses the uncertainty of decision-maker preferences, ranked the strategies, and at the same time, specified the typical decision-maker preferences for each strategy. In the analysis of a hypothetical port, four alternatives were designed as solutions for port congestion. The criteria selected were the service quality provided to vessels, the total goods handled and the profits accrued by the Port Authority. The criteria measuring the performance of each strategy were statistically analyzed first. Then, assuming the uniform distribution of decision-maker preferences, the alternatives were ranked, and the relative importance of each criterion in the decision-making process was obtained.

Conducting Repeatable Experiments and Fair Comparisons using 802.11n MIMO Networks

A commonly used technique for evaluating and comparing the performance of systems using 802.11 (WiFi) networks is to conduct experiments. This approach is appealing and important because it inherently captures critical properties of wireless signal transmission that are difficult to analytically model and simulate. Unfortunately, obtaining consistent and statistically meaningful empirical results using 802.11 networks, even in well-controlled environments, can be quite challenging and time consuming because channel conditions can vary over time. In this paper, we use 2.4 and 5 GHz 802.11n MIMO networks to study different methodologies that could be used to evaluate and compare the performance of different alternatives used in 802.11 systems (e.g., different systems, configurations or algorithms). We first illustrate that some of the more commonly used methods in existing research are flawed and explain why. We then describe a methodology called multiple interleaved trials that, to our knowledge, has not been used for, or studied on, 802.11 networks. We evaluate this methodology and find that it can be used to repeat experiments and to compare the performance of different alternatives. Finally, we discuss other possible applications of this approach for comparative performance evaluations.

Application of Multi-Criterion Decision Making Analysis to Integrated Water Resources Management

In the context of integrated water resources management (IWRM), account should be taken of a wide range of factors including economic, social and environmental issues. Multi-criterion decision making (MCDM) approaches are applied to the case study in this paper to integrate different objectives into the planning, management and decision making process. A variety of criteria in terms of economic, social and environmental dimensions are identified and formulated for the purpose of MCDM analysis. A set of different management scenarios is proposed for the desired goals. They include reductions in irrigated areas, improved irrigation efficiencies, increased system loss for groundwater irrigation and changes in cropping pattern. An integrated water resources optimisation model (IWRO) is used to optimise surface and groundwater allocation, through which the identified criteria can be enumerated. Compromise programming (CP), which results in a compromise solution located as close as possible to an ideal solution, is adopted to carry out the MCDM analysis for the case study. The sensitivity of different sets of weights and different values of parameters related to CP is investigated. Results indicate that compromise programming is able to lead to satisfactory solutions. Performance of different alternatives is evaluated based on the compromise programming analysis, and potential decisional alternatives are proposed for further investigation.

The Knowledge-Gradient Algorithm for Sequencing Experiments in Drug Discovery

We present a new technique for adaptively choosing the sequence of molecular compounds to test in drug discovery. Beginning with a base compound, we consider the problem of searching for a chemical derivative of the molecule that best treats a given disease. The problem of choosing molecules to test to maximize the expected quality of the best compound discovered may be formulated mathematically as a ranking-and-selection problem in which each molecule is an alternative. We apply a recently developed algorithm, known as the knowledge-gradient algorithm, that uses correlations in our Bayesian prior distribution between the performance of different alternatives (molecules) to dramatically reduce the number of molecular tests required, but it has heavy computational requirements that limit the number of possible alternatives to a few thousand. We develop computational improvements that allow the knowledge-gradient method to consider much larger sets of alternatives, and we demonstrate the method on a problem with 87,120 alternatives.

Multicriteria group decision making under incomplete preference judgments: Using fuzzy logic with a linguistic quantifier

In the face of increasing global competition and complexity of the socioeconomic environment, many organizations employ groups in decision making. Inexact or vague preferences have been discussed in the decision-making literature with a view to relaxing the burden of preference specifications imposed on the decision makers and thus taking into account the vagueness of human judgment. In this article, we present a multiperson decision-making method using fuzzy logic with a linguistic quantifier when each group member specifies incomplete judgment possibly both in terms of the evaluation of the performance of different alternatives with respect to multiple criteria and on the criteria themselves. Allowing for incomplete judgment in the model, however, makes a clear selection of the best alternative by the group more difficult. So, further interactions with the decision makers may proceed to the extent to compensate for the initial comfort of preference specifications. These interactions, however, may not guarantee the selection of the best alternative to implement. To circumvent this deadlock situation, we present a procedure for obtaining a satisfactory solution by the use of a linguistic-quantifier-guided aggregation that implies the fuzzy majority. This is an approach that combines a prescriptive decision method via mathematical programming and a well-established approximate solution method to aggregate multiple objects. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 641–660, 2007.

Multiple criteria rainfall–runoff model calibration using a parallel genetic algorithm in a cluster of computers / Calage multi-critères en modélisation pluie–débit par un algorithme génétique parallèle mis en œuvre par une grappe d'ordinateurs

Genetic algorithms are among of the global optimization schemes that have gained popularity as a means to calibrate rainfall–runoff models. However, a conceptual rainfall–runoff model usually includes 10 or more parameters and these are interdependent, which makes the optimization procedure very time-consuming. This may result in the premature termination of the optimization process which will prejudice the quality of the results. Therefore, the speed of optimization procedure is crucial in order to improve the calibration quality and efficiency. A hybrid method that combines a parallel genetic algorithm with a fuzzy optimal model in a cluster of computers is proposed. The method uses the fuzzy optimal model to evaluate multiple alternatives with multiple criteria where chromosomes are the alternatives, whilst the criteria are flood performance measures. In order to easily distinguish the performance of different alternatives and to address the problem of non-uniqueness of optimum, two fuzzy ratios are defined. The new approach has been tested and compared with results obtained by using a two-stage calibration procedure. The current single procedure produces similar results, but is simpler and automatic. Comparison of results between the serial and parallel genetic algorithms showed that the current methodology can significantly reduce the overall optimization time and simultaneously improve the solution quality.

Passive options for thermal comfort in building envelopes—An assessment

Building envelopes that have been developed so far often require mechanical systems involving expensive equipment utilising fuel and electrical energy for thermal comfort. These sophisticated systems (active systems) cannot be adopted by an average person in developing countries because it is difficult to afford and to maintain them. A study conducted by the author in a Ph.D. programme at the Bartlett School of Architecture and Planning, University of London, U.K., examines the building envelope of houses common in the Delhi region of India. The thermal environment in a traditional building envelope is determined, an index quantifying discomfort is established, and the degree of discomfort calculated. A vailable passive options for modifying the internal climate of building envelopes are considered one by one and an attempt is made to examine how far the thermal discomfort can be controlled with each of these options. The extent of the integrated effect of passive options is also established. The methodology of computer simulation is used to determine the thermal performance of different alternatives. It is concluded that two-thirds of the discomfort can be eliminated by the judicious use of simple passive options based on thermophysical properties and configuration of building envelopes.