Soft Computational Approaches for Prediction and Estimation of Software Development.

Peer reviewe

A fuzzy DEMATEL approach based on intuitionistic fuzzy information for evaluating knowledge transfer effectiveness in GSD projects

The offshore/onsite teams' effectiveness of knowledge transfer is significantly measured by various kinds of factors. In this paper, we propose a knowledge transfer (KT) assessment framework which integrates four criteria for evaluating the KT effectiveness of GSD teams. These are: knowledge, team, technology, and organisation factors. In this context, we present a fuzzy DEMATEL approach for assessing GSD teams KT effectiveness based on intuitionistic fuzzy numbers (IFNs). In this approach, decision makers provide their subjective judgments on the criteria, characterised on the basis of intuitionistic fuzzy sets. Moreover, intuitionistic fuzzy sets used in the fuzzy DEMATEL approach can effectively assess the KT effectiveness criteria and rank the alternatives. Subsequently, the entire process is illustrated with GSD teams' KT evaluation criteria samples, and the factors are ranked using fuzzy linguistic variables which are mapped to IFNs. Afterwards, the IFNs are converted into their corresponding basic probability assignments (BPAs) and then the Dempster-Shafer theory is used to combine the group decision making process. Besides, illustrative applicability and usefulness of the proposed approach in group decision making process for the evaluation of multiple criteria under fuzzy environment has been tested by software professionals at Inowits Software Organisation in India

Object Tracking in Vary Lighting Conditions for Fog based Intelligent Surveillance of Public Spaces

With rapid development of computer vision and artificial intelligence, cities are becoming more and more intelligent. Recently, since intelligent surveillance was applied in all kind of smart city services, object tracking attracted more attention. However, two serious problems blocked development of visual tracking in real applications. The first problem is its lower performance under intense illumination variation while the second issue is its slow speed. This paper addressed these two problems by proposing a correlation filter based tracker. Fog computing platform was deployed to accelerate the proposed tracking approach. The tracker was constructed by multiple positions' detections and alternate templates (MPAT). The detection position was repositioned according to the estimated speed of target by optical flow method, and the alternate template was stored with a template update mechanism, which were all computed at the edge. Experimental results on large-scale public benchmark datasets showed the effectiveness of the proposed method in comparison with state-of-the-art methods

A Reliability-Aware Approach for Resource Efficient Virtual Network Function Deployment

OAPA Network function virtualization (NFV) is a promising technique aimed at reducing capital expenditures (CAPEX) and operating expenditures (OPEX), and improving the flexibility and scalability of an entire network. In contrast to traditional dispatching, NFV can separate network functions from proprietary infrastructure and gather these functions into a resource pool that can efficiently modify and adjust service function chains (SFCs). However, this emerging technique has some challenges. A major problem is reliability, which involves ensuring the availability of deployed SFCs, namely, the probability of successfully chaining a series of virtual network functions (VNFs) while considering both the feasibility and the specific requirements of clients, because the substrate network remains vulnerable to earthquakes, floods and other natural disasters. Based on the premise of users & #x2019; demands for SFC requirements, we present an Ensure Reliability Cost Saving (ER & #x005F;CS) algorithm to reduce the CAPEX and OPEX of telecommunication service providers (TSPs) by reducing the reliability of the SFC deployments. The results of extensive experiments indicate that the proposed algorithms perform efficiently in terms of the blocking ratio, resource consumption, time consumption and the first block

IoT-Based Wireless Polysomnography Intelligent System for Sleep Monitoring

© 2013 IEEE. Polysomnography (PSG) is considered the gold standard in the diagnosis of obstructive sleep apnea (OSA). The diagnosis of OSA requires an overnight sleep experiment in a laboratory. However, due to limitations in relation to the number of labs and beds available, patients often need to wait a long time before being diagnosed and eventually treated. In addition, the unfamiliar environment and restricted mobility when a patient is being tested with a polysomnogram may disturb their sleep, resulting in an incomplete or corrupted test. Therefore, it is posed that a PSG conducted in the patient's home would be more reliable and convenient. The Internet of Things (IoT) plays a vital role in the e-Health system. In this paper, we implement an IoT-based wireless polysomnography system for sleep monitoring, which utilizes a battery-powered, miniature, wireless, portable, and multipurpose recorder. A Java-based PSG recording program in the personal computer is designed to save several bio-signals and transfer them into the European data format. These PSG records can be used to determine a patient's sleep stages and diagnose OSA. This system is portable, lightweight, and has low power-consumption. To demonstrate the feasibility of the proposed PSG system, a comparison was made between the standard PSG-Alice 5 Diagnostic Sleep System and the proposed system. Several healthy volunteer patients participated in the PSG experiment and were monitored by both the standard PSG-Alice 5 Diagnostic Sleep System and the proposed system simultaneously, under the supervision of specialists at the Sleep Laboratory in Taipei Veteran General Hospital. A comparison of the results of the time-domain waveform and sleep stage of the two systems shows that the proposed system is reliable and can be applied in practice. The proposed system can facilitate the long-Term tracing and research of personal sleep monitoring at home

Neutrosophic AHP-Delphi Group decision making model based on trapezoidal neutrosophic numbers

The main objective of this research is to study the integration of Analytic Hierarchy Process (AHP) into Delphi framework in neutrosophic environment and present a new technique for checking consistency and calculating consensus degree of expert’s opinions

A robust green traffic‐based routing problem for perishable products distribution

Nowadays, transportation and logistics are considered as the drivers of economic development in the countries due to their impacts on the main variables of the country's economy such as production, employment, price, and the cost of living. Statistics indicate that fuel consumption constructs a major part of transportation costs, where its optimization leads to the creation of an energy-efficient and sustainable transportation system. On the other hand, vehicles' traffic is also one of the main criteria affecting the travel time of vehicles between demand nodes in a supply chain, increasing fuel consumption, and, consequently, damaging effects of greenhouse gasses. In this paper, a novel robust mixed-integer linear programming model is developed for a green vehicle routing problem with intermediate depots considering different urban traffic conditions, fuel consumption, time windows of services, and uncertain demand for perishable products. To validate and solve the suggested model, CPLEX solver of GAMS software is employed as an exact method. Finally, a case study problem is investigated to evaluate the applicability of the proposed model and determine the optimal managerial insights and policies in the real-world conditions using sensitivity analyses. Moreover, a novel robustness threshold comparison is conducted to find the optimal level of budget assignment