Search results for: polishing component

Authors: A. Ouanane, A. Serir

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In this paper, a novel algorithm based on Ridgelet Transform and support vector machine is proposed for human action recognition. The Ridgelet transform is a directional multi-resolution transform and it is more suitable for describing the human action by performing its directional information to form spatial features vectors. The dynamic transition between the spatial features is carried out using both the Principal Component Analysis and clustering algorithm K-means. First, the Principal Component Analysis is used to reduce the dimensionality of the obtained vectors. Then, the kmeans algorithm is then used to perform the obtained vectors to form the spatio-temporal pattern, called set-of-labels, according to given periodicity of human action. Finally, a Support Machine classifier is used to discriminate between the different human actions. Different tests are conducted on popular Datasets, such as Weizmann and KTH. The obtained results show that the proposed method provides more significant accuracy rate and it drives more robustness in very challenging situations such as lighting changes, scaling and dynamic environment

Keywords: Human action, Ridgelet Transform, PCA, K-means, SVM.

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Authors: Kyogun Chang, Yoon Bok Lee

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Fault detection determines faultexistence and detecting time. This paper discusses two layered fault detection methods to enhance the reliability and safety. Two layered fault detection methods consist of fault detection methods of component level controllers and system level controllers. Component level controllers detect faults by using limit checking, model-based detection, and data-driven detection and system level controllers execute detection by stability analysis which can detect unknown changes. System level controllers compare detection results via stability with fault signals from lower level controllers. This paper addresses fault detection methods via stability and suggests fault detection criteria in nonlinear systems. The fault detection method applies tothe hybrid control unit of a military hybrid electric vehicleso that the hybrid control unit can detect faults of the traction motor.

Keywords: Two Layered Fault Detection, Stability Analysis, Fault-Tolerant Control

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Authors: O. Adjoul, A. Feugier, K. Benfriha, A. Aoussat

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In general, issues related to design and maintenance are considered in an independent manner. However, the decisions made in these two sets influence each other. The design for maintenance is considered an opportunity to optimize the life cycle cost of a product, particularly in the nuclear or aeronautical field, where maintenance expenses represent more than 60% of life cycle costs. The design of large-scale systems starts with product architecture, a choice of components in terms of cost, reliability, weight and other attributes, corresponding to the specifications. On the other hand, the design must take into account maintenance by improving, in particular, real-time monitoring of equipment through the integration of new technologies such as connected sensors and intelligent actuators. We noticed that different approaches used in the Design For Maintenance (DFM) methods are limited to the simultaneous characterization of the reliability and maintainability of a multi-component system. This article proposes a method of DFM that assists designers to propose dynamic maintenance for multi-component industrial systems. The term "dynamic" refers to the ability to integrate available monitoring data to adapt the maintenance decision in real time. The goal is to maximize the availability of the system at a given life cycle cost. This paper presents an approach for simultaneous optimization of the design and maintenance of multi-component systems. Here the design is characterized by four decision variables for each component (reliability level, maintainability level, redundancy level, and level of monitoring data). The maintenance is characterized by two decision variables (the dates of the maintenance stops and the maintenance operations to be performed on the system during these stops). The DFM model helps the designers choose technical solutions for the large-scale industrial products. Large-scale refers to the complex multi-component industrial systems and long life-cycle, such as trains, aircraft, etc. The method is based on a two-level hybrid algorithm for simultaneous optimization of design and maintenance, using genetic algorithms. The first level is to select a design solution for a given system that considers the life cycle cost and the reliability. The second level consists of determining a dynamic and optimal maintenance plan to be deployed for a design solution. This level is based on the Maintenance Free Operating Period (MFOP) concept, which takes into account the decision criteria such as, total reliability, maintenance cost and maintenance time. Depending on the life cycle duration, the desired availability, and the desired business model (sales or rental), this tool provides visibility of overall costs and optimal product architecture.

Keywords: Availability, design for maintenance, DFM, dynamic maintenance, life cycle cost, LCC, maintenance free operating period, MFOP, simultaneous optimization.

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Authors: Rim Bouhaouel, Naoufel Kraïem, Zuhoor Al Khanjari

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Unified Modeling Language (UML) is considered as one of the widespread modeling language standardized by the Object Management Group (OMG). Therefore, the model driving engineering (MDE) community attempts to provide reuse of UML diagrams, and do not construct it from scratch. The UML model appears according to a specific software development process. The existing method generation models focused on the different techniques of transformation without considering the development process. Our work aims to construct an UML component from fragments of UML diagram basing on an agile method. We define UML fragment as a portion of a UML diagram, which express a business target. To guide the generation of fragments of UML models using an agile process, we need a flexible approach, which adapts to the agile changes and covers all its activities. We use the software product line (SPL) to derive a fragment of process agile method. This paper explains our approach, named RECUP, to generate UML fragments following an agile process, and overviews the different aspects. In this paper, we present the approach and we define the different phases and artifacts.

Keywords: UML, component, fragment, agile, SPL.

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Authors: Sarka Keprdova, Jiri Bydzovsky

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This article describes to what extent the addition of energy by-products into the structures of the technical hemp filling materials influence their properties. The article focuses on the changes in physical-mechanical and thermal technical properties of materials after the addition of ash or FBC ash or slag in the binding component of material. Technical hemp filling materials are made of technical hemp shives bonded by the mixture of cement and dry hydrate lime. They are applicable as fillers of vertical or horizontal structures or roofs. The research used eight types of energy by-products of power or heating plants in the Czech Republic. Secondary energy products were dispensed in three different percentage ratios as a replacement of cement in the binding component. Density, compressive strength and determination of the coefficient of thermal conductivity after 28, 60 and 90 days of curing in a laboratory environment were determined and subsequently evaluated on the specimens produced.

Keywords: Ash, binder, cement, energy by-product, FBC ash (fluidized bed combustion ash), filling materials, shives, slag, technical hemp.

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Authors: Muhammad F. Yaqub, Iqbal Gondal, Joarder Kamruzzaman

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Occurrence of a multiple-points fault in machine operations could result in exhibiting complex fault signatures, which could result in lowering fault diagnosis accuracy. In this study, a multiple-points defect model (MPDM) is proposed which can simulate fault signature-s dynamics for n-points bearing faults. Furthermore, this study identifies that in case of multiple-points fault in the rotary machine, the location of the dominant component of defect frequency shifts depending upon the relative location of the fault points which could mislead the fault diagnostic model to inaccurate detections. Analytical and experimental results are presented to characterize and validate the variation in the dominant component of defect frequency. Based on envelop detection analysis, a modification is recommended in the existing fault diagnostic models to consider the multiples of defect frequency rather than only considering the frequency spectrum at the defect frequency in order to incorporate the impact of multiple points fault.

Keywords: Envelop detection, machine defect frequency, multiple faults, machine health monitoring.

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Authors: Nida Rizvi, Deeksha Katyal, Varun Joshi

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River Hindon is an important river catering the demand of highly populated rural and industrial cluster of western Uttar Pradesh, India. Water quality of river Hindon is deteriorating at an alarming rate due to various industrial, municipal and agricultural activities. The present study aimed at identifying the pollution sources and quantifying the degree to which these sources are responsible for the deteriorating water quality of the river. Various water quality parameters, like pH, temperature, electrical conductivity, total dissolved solids, total hardness, calcium, chloride, nitrate, sulphate, biological oxygen demand, chemical oxygen demand, and total alkalinity were assessed. Water quality data obtained from eight study sites for one year has been subjected to the two multivariate techniques, namely, principal component analysis and cluster analysis. Principal component analysis was applied with the aim to find out spatial variability and to identify the sources responsible for the water quality of the river. Three Varifactors were obtained after varimax rotation of initial principal components using principal component analysis. Cluster analysis was carried out to classify sampling stations of certain similarity, which grouped eight different sites into two clusters. The study reveals that the anthropogenic influence (municipal, industrial, waste water and agricultural runoff) was the major source of river water pollution. Thus, this study illustrates the utility of multivariate statistical techniques for analysis and elucidation of multifaceted data sets, recognition of pollution sources/factors and understanding temporal/spatial variations in water quality for effective river water quality management.

Keywords: Cluster analysis, multivariate statistical technique, river Hindon, water Quality.

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Authors: Desmond B. Keenan, Paul Grossman

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In order to provide accurate heart rate variability indices of sympathetic and parasympathetic activity, the low frequency and high frequency components of an RR heart rate signal must be adequately separated. This is not always possible by just applying spectral analysis, as power from the high and low frequency components often leak into their adjacent bands. Furthermore, without the respiratory spectra it is not obvious that the low frequency component is not another respiratory component, which can appear in the lower band. This paper describes an adaptive filter, which aids the separation of the low frequency sympathetic and high frequency parasympathetic components from an ECG R-R interval signal, enabling the attainment of more accurate heart rate variability measures. The algorithm is applied to simulated signals and heart rate and respiratory signals acquired from an ambulatory monitor incorporating single lead ECG and inductive plethysmography sensors embedded in a garment. The results show an improvement over standard heart rate variability spectral measurements.

Keywords: Heart rate variability, vagal tone, sympathetic, parasympathetic, spectral analysis, adaptive filter.

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Authors: Ploysai Ohama, Nattida Tumpat

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Natural dye extracted from Caesalpinia sappan Linn. was applied to a cotton fabric and silk yarn by dyeing process. The dyestuff component of Caesalpinia sappan Linn. was extracted using water and ethanol. Analytical studies such as UV–VIS spectrophotometry and gravimetric analysis were performed on the extracts. Brazilein, the major dyestuff component of Caesalpinia sappan Linn. was confirmed in both aqueous and ethanolic extracts by UV–VIS spectrum. The color of each dyed material was investigated in terms of the CIELAB (L*, a* and b*) and K/S values. Cotton fabric dyed without mordant had a shade of reddish-brown, while those post-mordanted with aluminum potassium sulfate, ferrous sulfate and copper sulfate produced a variety of wine red to dark purple color shades. Cotton fabric and silk yarn dyeing was studied using aluminum potassium sulfate as a mordant. The observed color strength was enhanced with increase in mordant concentration.

Keywords: Natural dyes, Plant materials, Dyeing, Mordant.

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Authors: Chih-Ming Wang, Chih-Yu Wen, Ying-Chung Chen, Chun-Chieh Wang, Chien-Chung Hsu, Jui-Yang Chang, Jyun-Min Lin

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In this study, we developed a complementary electrochromic device consisting of WO₃ and NiO films fabricated by rf-magnetron sputtered. The electrochromic properties of WO₃ and NiO films were investigated using cyclic voltammograms (CV), performed on WO₃ and NiO films immersed in an electrolyte of 1 M LiClO₄ in propylene carbonate (PC). Optical and electrochemical of the films, as a function of coloration–bleaching cycle, were characterized using an UV-Vis-NIR spectrophotometer and cyclic voltammetry (CV). After investigating the properties of WO₃ film, NiO film, and complementary electrochromic devices, we concluded that this device provides good reversibility, low power consumption of -2.5 V in color state, high variation of transmittance of 58.96%, changes in optical density of 0.81 and good memory effect under open-circuit conditions. In addition, electrochromic component penetration rate can be retained below 20% within 24h, showing preferred memory features; however, component coloring and bleaching response time are about 33s.

Keywords: Complementary electrochromic device, Rf-magnetron sputtered, Transmittance, Memory effect, Optical density change

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Authors: Teerawach Khamkorn, Laongtip Mathurasa, Savittree Rochanasmita Arnold, Witthaya Mekhum

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The objective of this research intends to create a suitable model of distance training for community leaders in the upper northeastern region of Thailand. The implementation of the research process is divided into four steps: The first step is to analyze relevant documents. The second step deals with an interview in depth with experts. The third step is concerned with constructing a model. And the fourth step takes aim at model validation by expert assessments. The findings reveal the two important components for constructing an appropriate model of distance training for community leaders in the upper northeastern region. The first component consists of the context of technology management, e.g., principle, policy and goals. The second component can be viewed in two ways. Firstly, there are elements comprising input, process, output and feedback. Secondly, the sub-components include steps and process in training. The result of expert assessments informs that the researcher-s constructed model is consistent and suitable and overall the most appropriate.

Keywords: Constructing, Distance Training, Management, Technology.

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Authors: Chonlada Bennett, Phumon Sookwong, Sakul Moolkam, Sivapong Naruebal Sugunya Mahatheeranont

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The cultivation of black glutinous rice rich in anthocyanins can provide great benefits to both farmers and consumers. Total anthocyanins content and yield component data of black glutinous rice cultivar (KHHK) grown with the addition of mineral elements (Ca, Mg, Cu, Cr, Fe and Se) under soilless conditions were studied. Ca application increased seed anthocyanins content by three-folds compared to controls. Cu application to rice plants obtained the highest number of grains panicle, panicle length and subsequently high panicle weight. Se application had the largest effect on leaf anthocyanins content, the number of tillers, number of panicles and 100-grain weight. These findings showed that the addition of mineral elements had a positive effect on increasing anthocyanins content in black rice plants and seeds as well as the heightened development of black glutinous rice plant growth.

Keywords: Anthocyanins, black glutinous rice, mineral elements, soilless culture.

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Authors: Muhammad Tufail, Jawad Hussain, Hammad Hussain, Imran Hafeez, Naveed Ahmad

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Road safety performance index is a composite index which combines various indicators of road safety into single number. Development of a road safety performance index using appropriate safety performance indicators is essential to enhance road safety. However, a road safety performance index in developing countries has not been given as much priority as needed. The primary objective of this research is to develop a general Road Safety Performance Index (RSPI) for developing countries based on the facility as well as behavior of road user. The secondary objectives include finding the critical inputs in the RSPI and finding the better method of making the index. In this study, the RSPI is developed by selecting four main safety performance indicators i.e., protective system (seat belt, helmet etc.), road (road width, signalized intersections, number of lanes, speed limit), number of pedestrians, and number of vehicles. Data on these four safety performance indicators were collected using observation survey on a 20 km road section of the National Highway N-125 road Taxila, Pakistan. For the development of this composite index, two methods are used: a) Principal Component Analysis (PCA) and b) Equal Weighting (EW) method. PCA is used for extraction, weighting, and linear aggregation of indicators to obtain a single value. An individual index score was calculated for each road section by multiplication of weights and standardized values of each safety performance indicator. However, Simple Average technique was used for weighting and linear aggregation of indicators to develop a RSPI. The road sections are ranked according to RSPI scores using both methods. The two weighting methods are compared, and the PCA method is found to be much more reliable than the Simple Average Technique.

Keywords: Aggregation, index score, indicators, principal component analysis, weighting.

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Authors: Mingtao Ding, Zheng Tian, Haixia Xu

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The batch nature limits the standard kernel principal component analysis (KPCA) methods in numerous applications, especially for dynamic or large-scale data. In this paper, an efficient adaptive approach is presented for online extraction of the kernel principal components (KPC). The contribution of this paper may be divided into two parts. First, kernel covariance matrix is correctly updated to adapt to the changing characteristics of data. Second, KPC are recursively formulated to overcome the batch nature of standard KPCA.This formulation is derived from the recursive eigen-decomposition of kernel covariance matrix and indicates the KPC variation caused by the new data. The proposed method not only alleviates sub-optimality of the KPCA method for non-stationary data, but also maintains constant update speed and memory usage as the data-size increases. Experiments for simulation data and real applications demonstrate that our approach yields improvements in terms of both computational speed and approximation accuracy.

Keywords: adaptive method, kernel principal component analysis, online extraction, recursive algorithm

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Authors: Parvinder S. Sandhu, Hardeep Singh

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Automatic reusability appraisal could be helpful in evaluating the quality of developed or developing reusable software components and in identification of reusable components from existing legacy systems; that can save cost of developing the software from scratch. But the issue of how to identify reusable components from existing systems has remained relatively unexplored. In this paper, we have mentioned two-tier approach by studying the structural attributes as well as usability or relevancy of the component to a particular domain. Latent semantic analysis is used for the feature vector representation of various software domains. It exploits the fact that FeatureVector codes can be seen as documents containing terms -the idenifiers present in the components- and so text modeling methods that capture co-occurrence information in low-dimensional spaces can be used. Further, we devised Neuro- Fuzzy hybrid Inference System, which takes structural metric values as input and calculates the reusability of the software component. Decision tree algorithm is used to decide initial set of fuzzy rules for the Neuro-fuzzy system. The results obtained are convincing enough to propose the system for economical identification and retrieval of reusable software components.

Keywords: Clustering, ID3, LSA, Neuro-fuzzy System, SVD

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Authors: P. Mounnarath, U. Schmitz, Ch. Zhang

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Fragility analysis is an effective tool for the seismic vulnerability assessment of civil structures in the last several years. The design of the expansion joints according to various bridge design codes is almost inconsistent, and only a few studies have focused on this problem so far. In this study, the influence of the expansion joint clearances between the girder ends and the abutment backwalls on the seismic fragility assessment of continuous integral bridge frames is investigated. The gaps (ranging from 60 mm, 150 mm, 250 mm and 350 mm) are designed by following two different bridge design code specifications, namely, Caltrans and Eurocode 8-2. Five bridge models are analyzed and compared. The first bridge model serves as a reference. This model uses three-dimensional reinforced concrete fiber beam-column elements with simplified supports at both ends of the girder. The other four models also employ reinforced concrete fiber beam-column elements but include the abutment backfill stiffness and four different gap values. The nonlinear time history analysis is performed. The artificial ground motion sets, which have the peak ground accelerations (PGAs) ranging from 0.1 g to 1.0 g with an increment of 0.05 g, are taken as input. The soil-structure interaction and the P-Δ effects are also included in the analysis. The component fragility curves in terms of the curvature ductility demand to the capacity ratio of the piers and the displacement demand to the capacity ratio of the abutment sliding bearings are established and compared. The system fragility curves are then obtained by combining the component fragility curves. Our results show that in the component fragility analysis, the reference bridge model exhibits a severe vulnerability compared to that of other sophisticated bridge models for all damage states. In the system fragility analysis, the reference curves illustrate a smaller damage probability in the earlier PGA ranges for the first three damage states, they then show a higher fragility compared to other curves in the larger PGA levels. In the fourth damage state, the reference curve has the smallest vulnerability. In both the component and the system fragility analysis, the same trend is found that the bridge models with smaller clearances exhibit a smaller fragility compared to that with larger openings. However, the bridge model with a maximum clearance still induces a minimum pounding force effect.

Keywords: Expansion joint clearance, fiber beam-column element, fragility assessment, time history analysis.

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Authors: Abbas Keramati, Abtin Boostani, Mohammad Jamal Sadeghi

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This paper examines the influence of knowledge management factors on organizational commitment for employees in the oil and gas drilling industry of Iran. We determine what knowledge factors have the greatest impact on the personnel loyalty and commitment to the organization using collected data from a survey of over 300 full-time personnel working in three large companies active in oil and gas drilling industry of Iran. To specify the effect of knowledge factors in the organizational commitment of the personnel in the studied organizations, the Principal Component Analysis (PCA) is used. Findings of our study show that the factors such as knowledge and expertise, in-service training, the knowledge value and the application of individuals’ knowledge in the organization as the factor “learning and perception of personnel from the value of knowledge within the organization” has the greatest impact on the organizational commitment. After this factor, “existence of knowledge and knowledge sharing environment in the organization”; “existence of potential knowledge exchanging in the organization”; and “organizational knowledge level” factors have the most impact on the organizational commitment of personnel, respectively.

Keywords: Knowledge management, organizational commitment, loyalty, drilling industry, principle component analysis.

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Authors: Kuo-Cheng Liu

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Effective estimation of just noticeable distortion (JND) for images is helpful to increase the efficiency of a compression algorithm in which both the statistical redundancy and the perceptual redundancy should be accurately removed. In this paper, we design a DCT-based model for estimating JND profiles of color images. Based on a mathematical model of measuring the base detection threshold for each DCT coefficient in the color component of color images, the luminance masking adjustment, the contrast masking adjustment, and the cross masking adjustment are utilized for luminance component, and the variance-based masking adjustment based on the coefficient variation in the block is proposed for chrominance components. In order to verify the proposed model, the JND estimator is incorporated into the conventional JPEG coder to improve the compression performance. A subjective and fair viewing test is designed to evaluate the visual quality of the coding image under the specified viewing condition. The simulation results show that the JPEG coder integrated with the proposed DCT-based JND model gives better coding bit rates at visually lossless quality for a variety of color images.

Keywords: Just-noticeable distortion (JND), discrete cosine transform (DCT), JPEG.

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Authors: D. S. Fardhyanti, A. Damayanti

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The utilization of biomass as a source of new and renewable energy is being carried out. One of the technologies to convert biomass as an energy source is pyrolysis which is converting biomass into more valuable products, such as bio-oil. Bio-oil is a liquid which is produced by steam condensation process from the pyrolysis of coconut shells. The composition of a coconut shell e.g. hemicellulose, cellulose and lignin will be oxidized to phenolic compounds as the main component of the bio-oil. The phenolic compounds in bio-oil are corrosive; they cause various difficulties in the combustion system because of a high viscosity, low calorific value, corrosiveness, and instability. Phenolic compounds are very valuable components which phenol has used as the main component for the manufacture of antiseptic, disinfectant (known as Lysol) and deodorizer. The experiments typically occurred at the atmospheric pressure in a pyrolysis reactor at temperatures ranging from 300 ^oC to 350 ^oC with a heating rate of 10 ^oC/min and a holding time of 1 hour at the pyrolysis temperature. The Gas Chromatography-Mass Spectroscopy (GC-MS) was used to analyze the bio-oil components. The obtained bio-oil has the viscosity of 1.46 cP, the density of 1.50 g/cm³, the calorific value of 16.9 MJ/kg, and the molecular weight of 1996.64. By GC-MS, the analysis of bio-oil showed that it contained phenol (40.01%), ethyl ester (37.60%), 2-methoxy-phenol (7.02%), furfural (5.45%), formic acid (4.02%), 1-hydroxy-2-butanone (3.89%), and 3-methyl-1,2-cyclopentanedione (2.01%).

Keywords: Bio-oil, pyrolysis, coconut shell, phenol, gas chromatography-mass spectroscopy.

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Authors: Bindu Sankar, Jaideep Chakraborty, Rashmi Nawlakha, A. Venkatesan, S. Raghupathy, T. Jayanthi, S.A.V. Satya Murty

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Component handling system is one of the important sub systems of Prototype Fast Breeder Reactor (PFBR) used for fuel handling. Core handling system is again a sub system of component handling system. Core handling system consists of in-vessel and ex-vessel subassembly handling. In-vessel core handling involves transfer arm, large rotatable plug and small rotatable plug operations. Modeling and simulation of in-vessel core handling is a part of development of Prototype Fast Breeder Reactor Operator Training Simulator. This paper deals with simulation and modeling of operations of transfer arm, large rotatable plug and small rotatable plug needed for in-vessel core handling. Process modeling was developed in house using platform independent Cµ code with OpenGL (Open Graphics Library). The control logic models and virtual panel were modeled using simulation tool.

Keywords: Animation, Core Handling System, Prototype Fast Breeder Reactor, Simulator

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Authors: Mert Tosun, Tuğba Tosun

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The evaporator is the utmost important component in the refrigeration system, since it enables the refrigerant to draw heat from the desired environment, i.e. the refrigerated space. Studies are being conducted on this component which generally affects the performance of the system, where energy efficient products are important. This study was designed to enhance the effectiveness of the evaporator in the refrigeration cycle of a domestic refrigerator by adjusting the capillary tube length, refrigerant amount, and the evaporator pipe diameter to reduce energy consumption. The experiments were conducted under identical thermal and ambient conditions. Experiment data were analysed using the Design of Experiment (DOE) technique which is a six-sigma method to determine effects of parameters. As a result, it has been determined that the most important parameters affecting the evaporator performance among the selected parameters are found to be the refrigerant amount and pipe diameter. It has been determined that the minimum energy consumption is 6-mm pipe diameter and 16-g refrigerant. It has also been noted that the overall consumption of the experiment sample decreased by 16.6% with respect to the reference system, which has 7-mm pipe diameter and 18-g refrigerant.

Keywords: Heat exchanger, refrigerator, design of experiment, energy consumption.

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Authors: Alexiou Dimitra, Fragkaki Maria

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The objective of the paper is the study of geographic, economic and educational variables and their contribution to determine the position of each member-state among the EU-28 countries based on the values of seven variables as given by Eurostat. The Data Analysis methods of Multiple Factorial Correspondence Analysis (MFCA) Principal Component Analysis and Factor Analysis have been used. The cross tabulation tables of data consist of the values of seven variables for the 28 countries for 2014. The data are manipulated using the CHIC Analysis V 1.1 software package. The results of this program using MFCA and Ascending Hierarchical Classification are given in arithmetic and graphical form. For comparison reasons with the same data the Factor procedure of Statistical package IBM SPSS 20 has been used. The numerical and graphical results presented with tables and graphs, demonstrate the agreement between the two methods. The most important result is the study of the relation between the 28 countries and the position of each country in groups or clouds, which are formed according to the values of the corresponding variables.

Keywords: Multiple factorial correspondence analysis, principal component analysis, factor analysis, E.U.-28 countries, statistical package IBM SPSS 20, CHIC Analysis V 1.1 Software, Eurostat.eu statistics.

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Authors: Mohammed Rziza, Mohamed El Aroussi, Mohammed El Hassouni, Sanaa Ghouzali, Driss Aboutajdine

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In this paper, an efficient local appearance feature extraction method based the multi-resolution Curvelet transform is proposed in order to further enhance the performance of the well known Linear Discriminant Analysis(LDA) method when applied to face recognition. Each face is described by a subset of band filtered images containing block-based Curvelet coefficients. These coefficients characterize the face texture and a set of simple statistical measures allows us to form compact and meaningful feature vectors. The proposed method is compared with some related feature extraction methods such as Principal component analysis (PCA), as well as Linear Discriminant Analysis LDA, and independent component Analysis (ICA). Two different muti-resolution transforms, Wavelet (DWT) and Contourlet, were also compared against the Block Based Curvelet-LDA algorithm. Experimental results on ORL, YALE and FERET face databases convince us that the proposed method provides a better representation of the class information and obtains much higher recognition accuracies.

Keywords: Curvelet, Linear Discriminant Analysis (LDA) , Contourlet, Discreet Wavelet Transform, DWT, Block-based analysis, face recognition (FR).

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Authors: T. Cornelius, G. Secilmis

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When dealing with safety in structures, the connections between structural components play an important role. Robustness of a structure as a whole depends both on the load- bearing capacity of the structural component and on the structures capacity to resist total failure, even though a local failure occurs in a component or a connection between components. To avoid progressive collapse it is necessary to be able to carry out a design for connections. A connection may be executed with anchors to withstand local failure of the connection in structures built with prefabricated components. For the design of these anchors, a model is developed for connections in structures performed in prefabricated autoclaved aerated concrete components. The design model takes into account the effect of anchors placed close to the edge, which may result in splitting failure. Further the model is developed to consider the effect of reinforcement diameter and anchor depth. The model is analytical and theoretically derived assuming a static equilibrium stress distribution along the anchor. The theory is compared to laboratory test, including the relevant parameters and the model is refined and theoretically argued analyzing the observed test results. The method presented can be used to improve safety in structures or even optimize the design of the connections

Keywords: Robustness, anchors, connections, aircrete, prefabricated components.

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Authors: V. Venkatachalam, S. Selvan

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The security of computer networks plays a strategic role in modern computer systems. Intrusion Detection Systems (IDS) act as the 'second line of defense' placed inside a protected network, looking for known or potential threats in network traffic and/or audit data recorded by hosts. We developed an Intrusion Detection System using LAMSTAR neural network to learn patterns of normal and intrusive activities, to classify observed system activities and compared the performance of LAMSTAR IDS with other classification techniques using 5 classes of KDDCup99 data. LAMSAR IDS gives better performance at the cost of high Computational complexity, Training time and Testing time, when compared to other classification techniques (Binary Tree classifier, RBF classifier, Gaussian Mixture classifier). we further reduced the Computational Complexity of LAMSTAR IDS by reducing the dimension of the data using principal component analysis which in turn reduces the training and testing time with almost the same performance.

Keywords: Binary Tree Classifier, Gaussian Mixture, IntrusionDetection System, LAMSTAR, Radial Basis Function.

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Authors: Eric Jacob Bacon, Chaoyang Jin, Dianning He, Shuaishuai Hu, Lanbo Wang, Han Li, Shouliang Qi

Abstract:

Refractory epilepsy is a complicated type of epilepsy that can be difficult to diagnose. Recent technological advancements have made resting-state functional magnetic resonance (rsfMRI) a vital technique for studying brain activity. However, there is still much to learn about rsfMRI. Investigating rsfMRI connectivity may aid in the detection of abnormal activities. In this paper, we propose studying the functional connectivity of rsfMRI candidates to diagnose epilepsy. 45 rsfMRI candidates, comprising 26 with refractory epilepsy and 19 healthy controls, were enrolled in this study. A data-driven approach known as Independent Component Analysis (ICA) was used to achieve our goal. First, rsfMRI data from both patients and healthy controls were analyzed using group ICA. The components that were obtained were then spatially sorted to find and select meaningful ones. A two-sample t-test was also used to identify abnormal networks in patients and healthy controls. Finally, based on the fractional amplitude of low-frequency fluctuations (fALFF), a chi-square statistic test was used to distinguish the network properties of the patient and healthy control groups. The two-sample t-test analysis yielded abnormal in the default mode network, including the left superior temporal lobe and the left supramarginal. The right precuneus was found to be abnormal in the dorsal attention network. In addition, the frontal cortex showed an abnormal cluster in the medial temporal gyrus. In contrast, the temporal cortex showed an abnormal cluster in the right middle temporal gyrus and the right fronto-operculum gyrus. Finally, the chi-square statistic test was significant, producing a p-value of 0.001 for the analysis. This study offers evidence that investigating rsfMRI connectivity provides an excellent diagnosis option for refractory epilepsy.

Keywords: Independent Component Analysis, Resting State Network, refractory epilepsy, rsfMRI.

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Authors: C. Wan, A. Mita

Abstract:

This paper proposes a novel system for monitoring the health of underground pipelines. Some of these pipelines transport dangerous contents and any damage incurred might have catastrophic consequences. However, most of these damage are unintentional and usually a result of surrounding construction activities. In order to prevent these potential damages, monitoring systems are indispensable. This paper focuses on acoustically recognizing road cutters since they prelude most construction activities in modern cities. Acoustic recognition can be easily achieved by installing a distributed computing sensor network along the pipelines and using smart sensors to “listen" for potential threat; if there is a real threat, raise some form of alarm. For efficient pipeline monitoring, a novel monitoring approach is proposed. Principal Component Analysis (PCA) was studied and applied. Eigenvalues were regarded as the special signature that could characterize a sound sample, and were thus used for the feature vector for sound recognition. The denoising ability of PCA could make it robust to noise interference. One class SVM was used for classifier. On-site experiment results show that the proposed PCA and SVM based acoustic recognition system will be very effective with a low tendency for raising false alarms.

Keywords: One class SVM, pipeline monitoring system, principal component analysis, sound recognition, third party damage.

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Authors: Ebrahim Safarian, Kadir Bilen, Akif Ceviz

Abstract:

The turbocharger and turbocharging have been the inherent component of diesel engines, so that critical parameters of such engines, as BSFC (Brake Specific Fuel Consumption) or thermal efficiency, fuel consumption, BMEP (Brake Mean Effective Pressure), the power density output and emission level have been improved extensively. In general, the turbocharger can be considered as the most complex component of diesel engines, because it has closely interrelated turbomachinery concepts of the turbines and the compressors to thermodynamic fundamentals of internal combustion engines and stress analysis of all components. In this paper, a waste gate for a conventional single stage radial turbine is investigated by consideration of turbochargers operation constrains and engine operation conditions, without any detail designs in the turbine and the compressor. Amount of opening waste gate which extended between the ranges of full opened and closed valve, is demonstrated by limiting compressor boost pressure ratio. Obtaining of an optimum point by regard above mentioned items is surveyed by three linked meanline modeling programs together which consist of Turbomatch®, Compal®, Rital® madules in concepts NREC® respectively.

Keywords: Turbocharger, Wastegate, diesel engine, CONCEPT NREC programs.

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Authors: Ziba Omidi, Min-Ki Kim

Abstract:

This research presents the design, fabrication and application of a flavor sensor for an integrated electronic tongue and electronic nose that can allow rapid characterization of multi-component mixtures in a solution. The odor gas and liquid are separated using hydrophobic porous membrane in micro fluidic channel. The sensor uses an array composed of microbeads in micromachined cavities localized on silicon wafer. Sensing occurs via colorimetric and fluorescence changes to receptors and indicator molecules that are attached to termination sites on the polymeric microbeads. As a result, the sensor array system enables simultaneous and near-real-time analyses using small samples and reagent volumes with the capacity to incorporate significant redundancies. One of the key parts of the system is a passive pump driven only by capillary force. The hydrophilic surface of the fluidic structure draws the sample into the sensor array without any moving mechanical parts. Since there is no moving mechanical component in the structure, the size of the fluidic structure can be compact and the fabrication becomes simple when compared to the device including active microfluidic components. These factors should make the proposed system inexpensive to mass-produce, portable and compatible with biomedical applications.

Keywords: Optical Sensor, Semiconductor manufacturing, Smell sensor, Taste sensor.

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Authors: Daniela I. Borissova, Ivan C. Mustakerov, Evgeni D. Bantutov

Abstract:

Nowadays the devices of night vision are widely used both for military and civil applications. The variety of night vision applications require a variety of the night vision devices designs. A web-based architecture of a software system for design assessment before producing of night vision devices is developed. The proposed architecture of the web-based system is based on the application of a mathematical model for designing of night vision devices. An algorithm with two components – for iterative design and for intelligent design is developed and integrated into system architecture. The iterative component suggests compatible modules combinations to choose from. The intelligent component provides compatible combinations of modules  satisfying given user requirements to device parameters. The proposed web-based architecture of a system for design assessment of night vision devices is tested via a prototype of the system. The testing showed the applicability of both iterative and intelligent components of algorithm. 

Keywords: Night vision devices, design modeling, software architecture, web-based system.

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