Formalization of the prediction and ranking of software development life cycle models

The study of software engineering professional practices includes the use of the formal methodology in a software development. Identifying the appropriate methodology will not only reduce the failure of software but will also help to deliver the software in accordance with the predetermined budget and schedule. In literature, few works have been developed a tool for prediction of the most appropriate methodology for the specific software project. In this paper, a method for selecting an appropriate software development life cycle (SDLC) model based on a ranking manner from the highest to the lowest scoring is presented. The selection and ranking of appropriate SDLC elaborate the related SDLC’s critical factors, these factors are given different weights according to the SDLC, then these weights are used by the proposed mathematical method. The proposed approach has been extensively experimented on a dataset by software practitioners who are working in the software industry. Experimental results show that, the proposed method represents an applicable tool in predicting and ranking suitable SDLC models on various types of projects, such as: life-critical systems, commercial uses systems, and entertainment applications.

Selection and Ranking of the Most Suitable Drones for Sustainable Traffic Management Using Multi-Criteria Analysis Approach

The traffic problem is one of the significant issues facing many large cities. So, transportation plans should be analyzed very well. Static cameras are tools and the right solution for traffic monitoring and management. But, nowadays, drones come into prominence as popular, effective, and more sustainable tools in traffic control and have been used for various traffic applications. In this study, a model is proposed for the selection of the most suitable drone under the specific characteristics to ensure a contributor to traffic management efforts. The decision model is structured with AHP and MOORA-TOPSIS and VIKOR ranking methods. The weighting of criteria is carried out by the AHP method, and a combination of AHP and ranking methods are used for the best selection. The results of the analysis were compared using Spearman's rank correlation, and it is seen that the results are at the desired level.

Selection and Ranking of Fog Computing-Based IoT for Monitoring of Health Using the Analytic Network Approach

Numerous raised areas are established in the field of fog computing (FC), applied for various purposes, and are evaluated for running analytics on various devices including devices of internet of things and many others in a disseminated way. FC progresses the prototype of cloud computing to network edge leading various possibilities and services. FC improves processing, decision, and intervention to take place through devices of IoT and communicate essential details. The idea of FC in healthcare based on frameworks of IoT is exploited by determining dispersed delegate layer of comprehension between the cloud and sensor hubs. The clouds suggested systems improved to overcome several challenges in ubiquitous frameworks of medical services such as energy efficiency, portability, adaptableness, and quality issues by accommodating right to take care of definite weights of the distant medical services group and sensor networks. The proposed research work has considered the analytic network process (ANP) for selection and ranking of FC-based IoT for health monitoring systems. The approach works in situation when complexity arises for health monitoring. Results of the study show the success of the research for facilitating healthcare.

COMPUTATIONAL TOOL FOR SELECTION AND RANKING OF PULL-TYPE FORAGE HARVESTERS

The variety of forage harvester models available on Brazilian market demand practical tools for selecting and ranking these equipments. The present study aimed at the elaboration of an algorithm capable of providing simple and objective criteria that assist in the decision making. The communication channel of the companies was used to obtain technical specifications and price of the equipment, which were tabulated in spreadsheets. The instructions for the manipulation of the obtained data were elaborated in the software R, being calculated ranks for the following requirements considering simulated information about a farm: price (COT), productivity and price relation (PROD.COT), fuel consumption (CONS), operational comfort (CONF), versatility (VERS) and overall (GERAL). We obtained information from 45 models belonging to 8 companies. The best machine in the overall rank got similar rank in the COT, PROD.COT and CONS ranks and worst rank for CONF. The algorithm established allowed the selection and ranking of the forage harvesters analyzed, providing simple, objective and easily interpreted criteria for the use of the farmers and the technicians who assist them.

Screening and Ranking Methodology Applied to Biochars Aimed at Acidic and Calcareous Sandy Soil Improvement

The application of biochar (the by-product of biomass pyrolysis), as a soil amendment has been accepted as a sustainable solution to improve soil quality. The current study aims to establish a decision support tool for characterizing, ranking, and selecting biochars of different origins for soil improvement, thereby contributing to the development of a systematic approach, which lacks in the existing literature.The development of a Multi-Criteria Decision Support Approach applying a banded and weighted rating and scoring system allowed the selection and ranking of various biochars suitable for improving sandy soils before application. First, 14 selected, different biochar products (produced from industrial by-products, herbaceous, wood-based and manure-based feedstocks) were characterized with several physicochemical, biological and ecotoxicological methods taking into account both the technological and the environmental efficiency aspects of biochar utilization. Then, a system for the assessment and ranking of biochars for acidic, and calcareous neutral sandy soil improvement was developed, which could be flexibly adapted to different soil problems as well. Based on their performance in the tests, scores from (−5) to (+5) were assigned to each biochar. As a result, the grain husks and paper fiber sludge biochar was ranked as the most suitable for both acidic and neutral calcareous sandy soil improvement, with 55 and 43 scores, respectively (from the maximum 100). The applicability of this innovative multicriteria scoring-ranking system, as a tool for potential biochar users, was verified in microcosms and field-scale experiments, demonstrating the positive influence of this biochar on the acidic sandy soil.

A customizable web service selection framework using MCDM approaches

With the tremendous increase of web services published online, the problem of selecting the best service offers becomes more challenging. Users need to make their decisions on multiple and conflicting non-functional requirements. It is a natural fit to apply the Multi-Criteria Decision Making (MCDM) theory to the service selection and ranking process. In our proposed QoS-based service selection system, we take the user-centric standpoint to design the system. We improve the original MCDM models so that the user requirements on the QoS criteria are included in the rank calculation process. Our proposed QoS weighting method considers the well-defined ANP method combined with the user-defined weights. We compared the improved selection methods and we found that the Constraint Programming method is the best in terms of its sensitivity to the changes made to the QoS weights. Consequently, the results produced from this comparison would be presented to the user.

A customizable web service selection framework using MCDM approaches

With the tremendous increase of web services published online, the problem of selecting the best service offers becomes more challenging. Users need to make their decisions on multiple and conflicting non-functional requirements. It is a natural fit to apply the Multi-Criteria Decision Making (MCDM) theory to the service selection and ranking process. In our proposed QoS-based service selection system, we take the user-centric standpoint to design the system. We improve the original MCDM models so that the user requirements on the QoS criteria are included in the rank calculation process. Our proposed QoS weighting method considers the well-defined ANP method combined with the user-defined weights. We compared the improved selection methods and we found that the Constraint Programming method is the best in terms of its sensitivity to the changes made to the QoS weights. Consequently, the results produced from this comparison would be presented to the user.