Useful life prediction of woolen hand-knotted carpets using multivariate multiple regression

In this study, the main purpose is to predict the useful life of woolen hand-knotted carpets using multivariate multiple regression. Thickness loss of surface pile yarns and compression toughness index were chosen as representative of the compression properties. Also, color difference index (ΔE) of pile yarns, tuft size index, and evenness of texture index were considered as representative of the appearance characteristics. Eighteen woolen hand-knotted carpet samples (symmetric knot) with different structural specifications were produced. The carpet samples were subjected to 4000, 8000, and 12000 drum revolutions (wear factor) using a Hexapod tumbler tester and functional properties of samples were investigated in original and worn out carpet samples. At first, the effective variables were selected using multivariate test, and then multivariate analysis of variance was used for evaluating the significance of obtained models. Optimal separate equations of the functional properties on hand-knotted carpets were determined through multivariate multiple regression method. Reverse model of wear factor can be considered as a proper equation to predict the useful life of carpets.     

Determination methodology for optimising the energy storage size for power system

A methodology for determining the optimal size of energy storage system (ESS) integrated with thermal power system is presented in this study. The optimal size is characterised by the rated stored energy and the maximum power rating of installed ESS for which the power system can achieve maximum revenue. Therefore the ESS cost formulation is conducted by analysing economic cost benefit measures considering life cycle of ESS. Since unit commitment (UC) scheduling is an important and integral part of power system cost optimisation, this study considers the operating schedule of thermal units (TU) while resolving ESS schedule. This proposed method uses tabu search (TS)-based evolutionary technique for solving this optimisation problem. TS is included in this algorithm to avoid re-evaluation of already evaluated ESS size which is powered by max priority heap and hash table data structure. The weekly schedule period is considered instead of daily to achieve more precise results. The proposed method is applied in two different power systems to determine the appropriate size of to be installed ESS. Experimental results reported that establishing the proposed method is an effective one to compute the optimal size of ESS for different sized power systems.     

Positive and normative use of fuzzy DEA‐BCC models: A critical view on NATO enlargement

Data envelopment analysis (DEA) is a widely used mathematical programming approach for comparing the input and output of a set of comparable decision‐making units (DMUs) by evaluating their relative efficiency. The traditional DEA methods require accurate measurement of both the inputs and outputs. However, the real evaluation of the DMUs is often characterized by imprecision and uncertainty in data definitions and measurements. The development of fuzzy DEA (FDEA) with imprecise and ambiguous data has extended the scope of application for efficiency measurement. The purpose of this paper is to develop a fuzzy DEA framework with a BCC model for measuring crisp and interval efficiencies in fuzzy environments. We use an α‐level approach to convert the fuzzy Banker, Charnes, and Cooper (BCC) (variable returns to scale) model into an interval programming model. Instead of comparing the equality (or inequality) of the two intervals, we define a variable in the interval to satisfy our constraints and maximize the efficiency value. We present a numerical example to show the similarities and differences between our solution and the solutions obtained from four fuzzy DEA methods in the literature. In addition, a case study for NATO enlargement is presented to illustrate the applicability of the proposed method.     

Determination of aflatoxins in animal feeds by HPLC with multifunctional column clean-up

A reversed-phase HPLC method with fluorescence detection for the determination of the aflatoxins B1, B2, G1 and G2 in 42 animal feeds, comprising corn (16), soya bean meal (8), mixed meal (13), sunflower, wheat, canola, palm kernel, copra meals (1 each) was carried out. The samples were first extracted using acetonitrile:water (9:1), and was further cleaned-up using a multifunctional column. Optimum conditions for the extraction and chromatographic separation were investigated. By adopting an isocratic chromatographic system using a mobile phase comprising acetonitrile:methanol:water (8:27:65, v/v/v), the separation of the four aflatoxins was possible within 30 min. Recoveries for aflatoxins B1, B2, G1 and G2 were 98 ± 0.7%, 95 ± 1.0%, 94 ± 3.6% and 97 ± 4.3%, respectively. The results show that eight samples (19%) were contaminated with aflatoxins, ranging from 6.5 to 101.9 ng g^?1. Total aflatoxin levels in three samples exceed the legal limits of many countries of 20 ng g^?1.     

PMU-based Fault Location Technique for Three-terminal Parallel Transmission Lines with Series Compensation

Abstract

This study introduces a fault location technique for three-terminal series-compensated untransposed parallel transmission lines utilizing the three terminals’ synchronized data. The proposed technique is applicable for short or long lines as distributed parameter line model is employed and the potential couplings are considered. The fault location for both uncompensated line sections is obtained adopting previously introduced fault location technique. The faulty phases are required initially to be recognized for series-compensated transmission line. The adopted fault location technique for series-compensated line section is derived based on the resistive nature of the fault impedance. The obtained fault locations for each line section are compared with each other to distinguish the faulty branch and obtain the fault location. DIgSILENT Power Factory and MATLAB programs are utilized for simulation studies and required calculations. The obtained results prove the efficacy of the introduced technique.     

Discrete wavelet transform and support vector machine‐based parallel transmission line faults classification

This paper presents a scheme for classification of faults on double circuit parallel transmission lines using combination of discrete wavelet transform and support vector machine (SVM). Only one cycle post fault of the phase currents was employed to predict the fault type. Two features for each phase current were extracted using discrete wavelet transform. Thus, a total of 12 features were extracted for the six phase currents. The training data were collected, and SVM was employed to establish the fault classification unit. After that, the fault classification unit was tested for different fault states. The power system simulation was conducted using the MATLAB/Simulink program. The proposed technique took into account the mutual coupling between the parallel transmission lines and the randomness of the faults on transmission line considering time of occurrence, fault location, fault type, fault resistance, and loading conditions. The results show that the proposed technique can classify all the faults on the parallel transmission lines correctly. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Real time evaluation of DWT-based high impedance fault detection in EHV transmission

It is possible to capture the required travelling wave information contained in fault transients using wavelet transform. This paper presents practical real time testing for the high impedance fault (HIF) detection algorithm based on real time accidents data. The proposed scheme is implemented for HIF detection in extra high voltage transmission lines. The classifier is based on an algorithm that uses recursive method to sum the absolute values of the high frequency signal generated over one cycle and shifting one sample. Characteristics of this scheme are analyzed by extensive real time studies that clearly reveal that this technique can accurately detect HIFs in the EHV transmission lines within only half a cycle from the instant of fault occurrence. The reliability of this scheme is not affected by different fault conditions such as fault distance and fault inception angle.     

HTPC机箱新势力 打造客厅娱乐全能王

在《微型计算机》2010年4月上《高性能HTPC打造详解》一文中,作者改造出了一款兼顾高清娱乐、静音和散热的HTPC。在笔者看来,这套HTPC方案在游戏性能、扩展性和监控方面还有所欠缺,因此笔者另行打造了一套新的HTPC方案,实现了全面的客厅娱乐,高清影音和大型3D游戏都能轻松应对。     

THE GRID-E-CARD: ARCHITECTURE TO SHARE COLLECTIVE INTELLIGENCE ON THE GRID

Using the Grid for electronic learning can be considered a major innovation that increases the potential of the Internet for collaborative learning and transforms it into a gigantic high speed network of knowledge and services. Furthermore, with the refinement of peer-to-peer communication, the emerging network models will allow thousands of learners to access these solutions, regardless of their different computer systems. These solutions can be compared to storage devices that share learning resources according to the user' s needs. With the substantial increase of information nodes and the multiplicity of computers making use of this complex network, cognitive overload or transactional distance inherent to the technology can quickly become an obstacle to the learning process. Therefore, the Grid requires the development of appropriate learning tools and services. This paper presents an approach to reduce cognitive overload and transactional distance for a virtual learning community (VLC) on the Grid. This paper proposes a computer-Grid communication device called “Grid-e-Card.” Its goal is to bring users together according to their signature to share collective intelligence in a social context: the knowledge they have acquired, the objectives they wish to meet, or the learning services that correspond to their needs. This methodology is based on a set of P2P-agents who handle users' electronic portfolios (e-Portfolios) as knowledge prosthesis and exploit e-Learning qualification (e-Qualification) processes as aggregation methods to dynamically organize people in relevant virtual learning communities.