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Supervised fuzzy C-means techniques to solve the capacitated vehicle routing problem

Fuzzy C-Means (FCM) clustering technique is among the most effective partitional clustering algorithms available in the literature. The Capacitated Vehicle Routing Problem (CVRP) is an important industrial logistics and managerial NP-hard problem. Cluster-First Route-Second Method (CFRS) is one of the efficient techniques used to solve CVRP. In CFRS technique, customers are first divided into clusters in the first phase, then each cluster is solved independently as a Traveling Salesman Problem (TSP) in the second phase. This research is concerned with the clustering phase of CFRS, and TSP is

Artificial Intelligence
Innovation, Entrepreneurship and Competitiveness

Sustainable Product Design through Non-dominated Sorting Cuckoo Search

Sustainability is an important consideration in product design. The sustainable design should fully consider the environmental, social, and economic factors of the product. However, the three factors are often conflicting with each other. This paper aims to strike a balance between these factors and achieve sustainable product design through multi-objective optimization. The three influencing factors of sustainability, namely, the environmental factor, social factor and economic factor, were respectively defined as environmental impact, labor time and labor cost. Then, the product to be

Artificial Intelligence
Innovation, Entrepreneurship and Competitiveness

Neural Knapsack: A Neural Network Based Solver for the Knapsack Problem

This paper introduces a heuristic solver based on neural networks and deep learning for the knapsack problem. The solver is inspired by mechanisms and strategies used by both algorithmic solvers and humans. The neural model of the solver is based on introducing several biases in the architecture. We introduce a stored memory of vectors that holds up items representations and their relationship to the capacity of the knapsack and a module that allows the solver to access all the previous outputs it generated. The solver is trained and tested on synthetic datasets that represent a variety of

Artificial Intelligence
Software and Communications
Innovation, Entrepreneurship and Competitiveness

Stochastic travelling advisor problem simulation with a case study: A novel binary gaining-sharing knowledge-based optimization algorithm

This article proposes a new problem which is called the Stochastic Travelling Advisor Problem (STAP) in network optimization, and it is defined for an advisory group who wants to choose a subset of candidate workplaces comprising the most profitable route within the time limit of day working hours. A nonlinear binary mathematical model is formulated and a real application case study in the occupational health and safety field is presented. The problem has a stochastic nature in travelling and advising times since the deterministic models are not appropriate for such real-life problems. The

Artificial Intelligence
Software and Communications
Innovation, Entrepreneurship and Competitiveness

Neural Network Based Switching State Selection for Direct Power Control of Three Phase PWM-Rectifier

This article proposes an intelligent approach to the Direct Power Control technique of the PWM rectifier, this control technique improves the performance of PWM converter, called Direct Power Control Based on Artificial Neural Network (ANN), applied for the selection of the optimal control vector. DPC-ANN ensures smooth control of active and reactive power in all Sectors and reduces current ripple. Finally, the developed DPC was tested by simulation, the simulation results proved the excellent performance of the proposed DPC scheme. © 2018 IEEE.

Artificial Intelligence
Software and Communications
Innovation, Entrepreneurship and Competitiveness

Neuro-fuzzy system for 3-dof parallel robot manipulator

Planar Parallel manipulators (PPMs) are widely used these days, as they have many advantages compared to their serial counterparts. However, their inverse and direct kinematics are hard to obtain, due to the complexity of the manipulators' behavior. Therefore, this paper provides a comparative analysis for two methods that were used to obtain the inverse kinematics of a 3-RRR manipulator. Instead of the conventional algebraic and graphical methods used for attaining the mathematical models for such manipulators, an adaptive neuro-fuzzy inference structure (AFNIS) model was alternatively

Artificial Intelligence
Software and Communications
Innovation, Entrepreneurship and Competitiveness

Study of Energy Harvesters for Wearable Devices

Energy harvesting was and still an important point of research. Batteries have been utilized for a long time, but they are now not compatible with the downsizing of technology. Also, their need to be recharged and changed periodically is not very desirable, therefore over the years energy harvesting from the environment and the human body have been investigated. Three energy harvesting methods which are the Piezoelectric energy harvesters, the Enzymatic Biofuel cells, and Triboelectric nanogenerators (TENGs) are being discussed in the paper. Although Biofuel cells have been investigated for a

Artificial Intelligence
Healthcare
Circuit Theory and Applications
Innovation, Entrepreneurship and Competitiveness

Fractional canny edge detection for biomedical applications

This paper presents a comparative study of edge detection algorithms based on integer and fractional order differentiation. A performance comparison of the two algorithms has been proposed. Then, a soft computing technique has been applied to both algorithms for better edge detection. From the simulations, it shows that better performance is obtained compared to the classical approach. The noise performances of those algorithms are analyzed upon the addition of random Gaussian noise, as well as the addition of salt and pepper noise. The performance has been compared to peak signal to noise

Artificial Intelligence
Circuit Theory and Applications
Software and Communications
Innovation, Entrepreneurship and Competitiveness

Improved Production Key Performance Indicators (KPI’s) Using Intelligent-Manufacturing Execution Systems (I-MES)

The aim of this research is to reduce the gap between manufacture expertise and management expertise by using modern technology like Manufacturing Execution System (MES) via Artificial Intelligence (AI) and Machin Learning (ML). A design of MES has been proposed and implemented on El-Araby Plastic Injection Molding (PIM) factory. This work is based on the International Society of Automation Standard (ISA-S95). A fully automated data management system has been designed and implemented to control data follow between shop floor e.g. (machines and operators) and management floor e.g. (production

Artificial Intelligence
Circuit Theory and Applications
Mechanical Design
Innovation, Entrepreneurship and Competitiveness

Salinity stress reveals three types of RNA editing sites in mitochondrial Nad7 gene of wild barley both in silico and in qRT-PCR experiments

Cellular respiration is an important process performed by mitochondria. Nad complex is the major complex involved in this process and one of the main subunits in this complex is the nad7 (nad dehydrogenase subunit 7). In Hordeum vulgare subsp. spontaneum, four nad7 cDNAs are described at 500 mM salinity, 0 h, or control (GenBank accession no. MW433884), after 2 h (GenBank accession no. MW433885), after 12 h (GenBank accession no. MW433886) and after 24 h (GenBank accession no. MW433887). Twenty six RNA editing sites were revealed in positions: C44, C45, C77, C83, C99, C137, C224, C244, C251

Artificial Intelligence
Healthcare