Wavelet based on-line disturbance detection for power qualityapplications

This paper introduces a new online voltage disturbance detection approach based on the wavelet transform. The proposed approach: (1) identifies voltage disturbances; and (2) discriminates the type of event which has resulted in the voltage disturbance, e.g. either a fault or a capacitor-switching incident. The proposed approach is: (1) significantly faster; and (2) more precise in discriminating the type of transient event than conventional voltage-based disturbance detection approaches. The feasibility of the proposed disturbance detection approach is demonstrated based on digital time-domain simulation of a power distribution system using the PSCAD/EMTDC software package     

A reliability/availability approach to joint production and maintenance scheduling with multiple preventive maintenance services

In classical scheduling problems, it is often assumed that the machines are available during the whole planning horizon, while in realistic environments, machines need to be maintained and therefore may become unavailable within production periods. Hence, in this paper we suggest a joint production and maintenance scheduling (JPMS) with multiple preventive maintenance services, in which the reliability/availability approach is employed to model the maintenance aspects of a problem. To cope with the suggested JPMS, a mixed integer nonlinear programming model is developed and then a population-based variable neighbourhood search (PVNS) algorithm is devised for a solution method. In order to enhance the search diversification of basic variable neighbourhood search (VNS), our PVNS uses an epitome-based mechanism in each iteration to transform a group of initial individuals into a new solution, and then multiple trial solutions are generated in the shaking stage for a given solution. At the end of the local search stage, the best obtained solution by all of the trial solutions is recorded and the worst solution in population is replaced with this new solution. The evolution procedure is continued until a predefined number of iterations is violated. To validate the effectiveness and robustness of PVNS, an extensive computational study is implemented and the simulation results reveal that our PVNS performs better than traditional algorithms, especially in large size problems.     

Production scheduling with outsourcing scenarios: a mixed integer programming and efficient solution procedure

When market demand exceeds the company's capacity to manufacture, outsourcing is commonly considered as an effective alternative option. In traditional scheduling problems, processing of received orders is just possible via in-house resources, while in practice, outsourcing is frequently found in various manufacturing industries, especially in electronics, motor and printing companies. This paper deals with the scheduling problem, minimising the cost of outsourcing and a scheduling measure represented by weighted mean flow time, in which outsourcing of manufacturing operations is allowed through subcontracts. Each order can be either scheduled for in-house production or outsourced to an outside supplier in order to meet customer due dates. In this problem, not only should the sequence of orders be determined, but also decision on picking the jobs for outsourcing, selecting the appropriate subcontractor, and scheduling of the outsourced orders are considered as new variables. To formulate the given problem, four different outsourcing scenarios are derived and mixed integer programming models are developed for each one separately. Furthermore, to solve the suggested problem, a computationally effective team process algorithm is devised and then a constraint handling technique is embedded into the main algorithm in order to ensure satisfaction of customer due dates. Numerical results show that the suggested approach possesses high global solution rates as well as fast convergence.     

Novel anti‐bacterial acid dyes derived from naphthalimide: synthesis,characterisation and evaluation of their technical properties on nylon 6

As an attempt to combine the dyeing and functional finishing steps into one process, two novel anti‐bacterial monoazo acid dyes based on N‐ester‐1,8‐naphthalimide were synthesised. To do this, 4‐amino‐N‐ethyl glycinate‐1,8‐naphthalimide was prepared, diazotised and then coupled to thiosalicylic acid or salicylic acid to produce anti‐bacterial dyes. The synthesised dyes were purified and then fully characterised using Fourier Transform–infrared spectrometry, proton nuclear magnetic resonance spectroscopy and melting point analysis. Dispersion of the dyes was prepared in water and applied to nylon 6 fabrics. The novel dyes offered good build‐up properties on the substrate. The anti‐bacterial efficacy of the synthesised dyes was assessed, with the dyes showing activity against both Gram‐positive and Gram‐negative bacteria.     

Cubic-quintic saturable nonlinearity effects on a light pulse strongly distorted by the fourth-order dispersion

Abstract

We analyze a useful process able to safeguard the fundamental soliton light pulse stability in a strongly perturbed environment by the fourth-order dispersion (FOD). This optical pulse propagation is described by the nonlinear Schrödinger equation (NLSE) with cubic–quintic saturable nonlinearities. Some pulse parameters, called collective variables (CVs) such as amplitude, temporal position, width, chirp, frequency shift and constant phase are obtained analytically. Numerical evolution of CVs and their stability are studied under a typical example to verify our analysis.     

Tracking the Genetic Susceptibility Background of B-Cell Non-Hodgkin’s Lymphomas from Genome-Wide Association Studies

B-cell non-Hodgkin’s lymphoma (NHL) risk associations had been mainly attributed to family history of the disease, inflammation, and immune components including human leukocyte antigen (HLA) genetic variations. Nevertheless, a broad range of genome-wide association studies (GWAS) have shed light into the identification of several genetic variants presumptively associated with B-cell NHL etiologies, survival or shared genetic risk with other diseases. The present review aims to overview HLA structure and diversity and summarize the evidence of genetic variations, by GWAS, on five NHL subtypes (diffuse large B-cell lymphoma DLBCL, follicular lymphoma FL, chronic lymphocytic leukemia CLL, marginal zone lymphoma MZL, and primary central nervous system lymphoma PCNSL). Evidence indicates that the HLA zygosity status in B-cell NHL might promote immune escape and that genome-wide significance variants can give biological insight but also potential therapeutic markers such as WEE1 in DLBCL. However, additional studies are needed, especially for non-DLBCL, to replicate the associations found to date.     

An evidential fusion approach for activity recognition in ambient intelligence environments

With the growing emergence of ambient intelligence, ubiquitous computing, sensor networks and wireless networking technologies, “ubiquitous networked robotics” is becoming an active research domain of intelligent autonomous systems. It targets new innovative applications in which robotic systems will become part of these networks of artifacts to provide novel capabilities and various assistive services anywhere and anytime, such as healthcare and monitoring services for elderly in Ambient Assisted Living (AAL) environments. Situation recognition, in general, and activity recognition, in particular, provide an added value on the contextual information that can help the ubiquitous networked robot to autonomously provide the best service that meet the needs of the elderly. Dempster–Shafer theory of evidence and its derivatives are an efficient tool to handle uncertainty and incompleteness in smart homes and ubiquitous computing environments. However, their combination rules yield counter-intuitive results in high conflicting activities. In this paper, we propose a new approach to support conflict resolution in activity recognition in AAL environments. This approach is based on a new mapping for conflict evidential fusion to increase the efficiency and accuracy of activity recognition. It gives intuitive interpretation for combining multiple sources in all conflicting situations. The proposed approach, evaluated on a real world smart home dataset, achieves 78% of accuracy in activity recognition. The obtained results outperform those obtained with the existing combination rules.     

Numerical solution of some initial optimal control problems using the reproducing kernel Hilbert space technique

ABSTRACT

In this paper, we present a general technique for solving a class of linear/nonlinear optimal control problems. In fact, an analytical solution of the state variable is represented in the form of a series in a reproducing kernel Hilbert space. Sometimes with the aid of this series form, we can also present the optimal control variable in a series form. An iterative method is given to obtain the approximate optimal control and state variables and the cost functional is numerically obtained. Convergence analysis of the method is also provided. Several numerical examples are tested to demonstrate the applicability and efficiency of the method.     

A hierarchical congestion control method in clustered internet of things

The Journal of Supercomputing - Internet of things (IoT) is a modern technology where data can be transmitted to any things (human, animal, or object) over communications networks, whether internet...     

NuMDG: A New Tool for Multiway Decision Graphs Construction

Multiway Decision Graphs(MDGs) are a canonical representation of a subset of many-sorted first-order logic. This subset generalizes the logic of equality with abstract types and uninterpreted function symbols.The distinction between abstract and concrete sorts mirrors the hardware distinction between data path and control.Here we consider ways to improve MDGs construction.Efficiency is achieved through the use of the Generalized-If-Then-Else(GITE) commonly operator in Binary Decision Diagram packages.Consequently,we review the main algorithms used for MDGs verification techniques.In particular,Relational Product and Pruning by Subsumption are algorithms defined uniformly through this single GITE operator which will lead to a more efficient implementation.Moreover,we provide their correctness proof.This work can be viewed as a way to accommodate the ROBBD algorithms to the realm of abstract sorts and uninterpreted functions.The new tool,called NuMDG,accepts an extended SMV language,supporting abstract data sorts.Finally,we present experimental results demonstrating the efficiency of the NuMDG tool and evaluating its performance using a set of benchmarks from the SMV package.