Search results for: component labeling

Authors: Mukul Shukla, Rasheedat M. Mahamood, Esther T. Akinlabi, Sisa. Pityana

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Laser Metal Deposition (LMD) is an additive manufacturing process with capabilities that include: producing new part directly from 3 Dimensional Computer Aided Design (3D CAD) model, building new part on the existing old component and repairing an existing high valued component parts that would have been discarded in the past. With all these capabilities and its advantages over other additive manufacturing techniques, the underlying physics of the LMD process is yet to be fully understood probably because of high interaction between the processing parameters and studying many parameters at the same time makes it further complex to understand. In this study, the effect of laser power and powder flow rate on physical properties (deposition height and deposition width), metallurgical property (microstructure) and mechanical (microhardness) properties on laser deposited most widely used aerospace alloy are studied. Also, because the Ti6Al4V is very expensive, and LMD is capable of reducing buy-to-fly ratio of aerospace parts, the material utilization efficiency is also studied. Four sets of experiments were performed and repeated to establish repeatability using laser power of 1.8 kW and 3.0 kW, powder flow rate of 2.88 g/min and 5.67 g/min, and keeping the gas flow rate and scanning speed constant at 2 l/min and 0.005 m/s respectively. The deposition height / width are found to increase with increase in laser power and increase in powder flow rate. The material utilization is favoured by higher power while higher powder flow rate reduces material utilization. The results are presented and fully discussed.

Keywords: Laser Metal Deposition, Material Efficiency, Microstructure, Ti6Al4V.

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Authors: Akrem Sellami, Imed Riadh Farah

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Hyperspectral imagery (HSI) typically provides a wealth of information captured in a wide range of the electromagnetic spectrum for each pixel in the image. Hence, a pixel in HSI is a high-dimensional vector of intensities with a large spectral range and a high spectral resolution. Therefore, the semantic interpretation is a challenging task of HSI analysis. We focused in this paper on object classification as HSI semantic interpretation. However, HSI classification still faces some issues, among which are the following: The spatial variability of spectral signatures, the high number of spectral bands, and the high cost of true sample labeling. Therefore, the high number of spectral bands and the low number of training samples pose the problem of the curse of dimensionality. In order to resolve this problem, we propose to introduce the process of dimensionality reduction trying to improve the classification of HSI. The presented approach is a semi-supervised band selection method based on spatial hypergraph embedding model to represent higher order relationships with different weights of the spatial neighbors corresponding to the centroid of pixel. This semi-supervised band selection has been developed to select useful bands for object classification. The presented approach is evaluated on AVIRIS and ROSIS HSIs and compared to other dimensionality reduction methods. The experimental results demonstrate the efficacy of our approach compared to many existing dimensionality reduction methods for HSI classification.

Keywords: Hyperspectral image, spatial hypergraph, dimensionality reduction, semantic interpretation, band selection, feature extraction.

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Authors: Arijit Ghos, Tony Gigargis

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QoS routing is an important component of Traffic Engineering in networks that provide QoS guarantees. QoS routing is dependent on the link state information which is typically flooded across the network. This affects both the quality of the routing and the utilization of the network resources. In this paper, we examine establishing QoS routes with partial state updates in wired sensor networks.

Keywords:

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Authors: Evgeniy Burlutskiy

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The paper presents a numerical investigation on the rapid gas decompression in pure nitrogen which is made by using the one-dimensional (1D) and three-dimensional (3D) mathematical models of transient compressible non-isothermal fluid flow in pipes. A 1D transient mathematical model of compressible thermal multicomponent fluid mixture flow in pipes is presented. The set of the mass, momentum and enthalpy conservation equations for gas phase is solved in the model. Thermo-physical properties of multicomponent gas mixture are calculated by solving the Equation of State (EOS) model. The Soave-Redlich-Kwong (SRK-EOS) model is chosen. This model is successfully validated on the experimental data [1] and shows a good agreement with measurements. A 3D transient mathematical model of compressible thermal single-component gas flow in pipes, which is built by using the CFD Fluent code (ANSYS), is presented in the paper. The set of unsteady Reynolds-averaged conservation equations for gas phase is solved. Thermo-physical properties of single-component gas are calculated by solving the Real Gas Equation of State (EOS) model. The simplest case of gas decompression in pure nitrogen is simulated using both 1D and 3D models. The ability of both models to simulate the process of rapid decompression with a high order of agreement with each other is tested. Both, 1D and 3D numerical results show a good agreement between each other. The numerical investigation shows that 3D CFD model is very helpful in order to validate 1D simulation results if the experimental data is absent or limited.

Keywords: Mathematical model, Rapid Gas Decompression

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Authors: F. M. Pisano, M. Ciminello

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Aerospace, mechanical, and civil engineering infrastructures can take advantages from damage detection and identification strategies in terms of maintenance cost reduction and operational life improvements, as well for safety scopes. The challenge is to detect so called “barely visible impact damage” (BVID), due to low/medium energy impacts, that can progressively compromise the structure integrity. The occurrence of any local change in material properties, that can degrade the structure performance, is to be monitored using so called Structural Health Monitoring (SHM) systems, in charge of comparing the structure states before and after damage occurs. SHM seeks for any "anomalous" response collected by means of sensor networks and then analyzed using appropriate algorithms. Independently of the specific analysis approach adopted for structural damage detection and localization, textual reports, tables and graphs describing possible outlier coordinates and damage severity are usually provided as artifacts to be elaborated for information extraction about the current health conditions of the structure under investigation. Visual Analytics can support the processing of monitored measurements offering data navigation and exploration tools leveraging the native human capabilities of understanding images faster than texts and tables. Herein, a SHM system enrichment by integration of a Visual Analytics component is investigated. Analytical dashboards have been created by combining worksheets, so that a useful Visual Analytics tool is provided to structural analysts for exploring the structure health conditions examined by a Principal Component Analysis based algorithm.

Keywords: Interactive dashboards, optical fibers, structural health monitoring, visual analytics.

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Authors: Mohd Azman Abdul Latif, Erwan Basiron

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A flaw or drift from expected operational performance in one component (NAND, PMIC, controller, DRAM, etc.) may affect the reliability of the entire Solid State Drive (SSD) system. Therefore, it is important to ensure the required quality of each individual component through qualification testing specified using standards or user requirements. Qualification testing is time-consuming and comes at a substantial cost for product manufacturers. A highly technical team, from all the eminent stakeholders is embarking on reliability prediction from beginning of new product development, identify critical to reliability parameters, perform full-blown characterization to embed margin into product reliability and establish control to ensure the product reliability is sustainable in the mass production. The paper will discuss a comprehensive development framework, comprehending SSD end to end from design to assembly, in-line inspection, in-line testing and will be able to predict and to validate the product reliability at the early stage of new product development. During the design stage, the SSD will go through intense reliability margin investigation with focus on assembly process attributes, process equipment control, in-process metrology and also comprehending forward looking product roadmap. Once these pillars are completed, the next step is to perform process characterization and build up reliability prediction modeling. Next, for the design validation process, the reliability prediction specifically solder joint simulator will be established. The SSD will be stratified into Non-Operating and Operating tests with focus on solder joint reliability and connectivity/component latent failures by prevention through design intervention and containment through Temperature Cycle Test (TCT). Some of the SSDs will be subjected to the physical solder joint analysis called Dye and Pry (DP) and Cross Section analysis. The result will be feedbacked to the simulation team for any corrective actions required to further improve the design. Once the SSD is validated and is proven working, it will be subjected to implementation of the monitor phase whereby Design for Assembly (DFA) rules will be updated. At this stage, the design change, process and equipment parameters are in control. Predictable product reliability at early product development will enable on-time sample qualification delivery to customer and will optimize product development validation, effective development resource and will avoid forced late investment to bandage the end-of-life product failures. Understanding the critical to reliability parameters earlier will allow focus on increasing the product margin that will increase customer confidence to product reliability.

Keywords: e2e reliability prediction, SSD, TCT, Solder Joint Reliability, NUDD, connectivity issues, qualifications, characterization and control.

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Authors: M. Nafi, A. El Amein, M. El Dawi, K. Salih, O. Elbahi, A. Abou

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In present study, a large deposit of oolitic iron ore of Late Carboniferous-Permotriassic-Lower Jurassic age was discovered in Wadi Halfa and Argein areas, North Sudan. It seems that the iron ore mineralization exists in the west and east bank of the River Nile of the study area that are found on the Egyptian-Sudanese border. The Carboniferous-Lower Jurassic age strata were covered by 67 sections and each section has been examined and carefully described. The iron-ore in Wadi Halfa occurs as oolitic ironstone and contained two horizons: (A) horizon and (B) horizon. Only horizon (A) was observed in southern Argein area. The texture of the ore is variable depending on the volume of the component. In thin sections, the average of the ooids was ranged between 90%-80%. The matrix varies between 10%-20% by volume and detritus quartz in other component my reach up to 30% by volume in sandy massive ore. Ooids size ranges from 0.2mm-1.00 mm on average in very coarse ooids may attend up to 1 mm in size. The matrix around the ooids is dominated by iron hydroxide, carbonate, fine, and amorphous silica. The probable ore reserve estimate of 1.234 billion at a head grade of 41.29% Fe for the Wadi Halfa Oolitic Ironstone Formation. The iron ore shows higher content of phosphorus ranges from 6.15% to 0.16%, with mean 1.45%. The new technology Hatch–Ironstone Chloride Segregation (HICS) can be used to produce commercial-quality of iron and reduce phosphorus and silica to acceptable levels for steel industry. The presence of infrastructures in addition to the presence of massive quantities of iron ore would make exploitation economically.

Keywords: HICS, Late Carboniferous age, Oolitic iron ore, phosphorus.

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Authors: Witthaya Mekhum

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The OTOP Entrepreneurship that used to create substantial source of income for local Thai communities are now in a stage of exigent matters that required assistances from public sectors due to over Entrepreneurship of duplicative ideas, unable to adjust costs and prices, lack of innovation, and inadequate of quality control. Moreover, there is a repetitive problem of middlemen who constantly corner the OTOP market. Local OTOP producers become easy preys since they do not know how to add more values, how to create and maintain their own brand name, and how to create proper packaging and labeling. The suggested solutions to local OTOP producers are to adopt modern management techniques, to find knowhow to add more values to products and to unravel other marketing problems. The objectives of this research are to study the prevalent OTOP products management and to discover direction to manage OTOP products to enhance the effectiveness of OTOP Entrepreneurship in Nonthaburi Province, Thailand. There were 113 participants in this study. The research tools can be divided into two parts: First part is done by questionnaire to find responses of the prevalent OTOP Entrepreneurship management. Second part is the use of focus group which is conducted to encapsulate ideas and local wisdom. Data analysis is performed by using frequency, percentage, mean, and standard deviation as well as the synthesis of several small group discussions. The findings reveal that 1) Business Resources: the quality of product is most important and the marketing of product is least important. 2) Business Management: Leadership is most important and raw material planning is least important. 3) Business Readiness: Communication is most important and packaging is least important. 4) Support from public sector: Certified from the government is most important and source of raw material is the least important.

Keywords: Management, OTOP Entrepreneurship, Local Wisdom

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Authors: S. K. Fasogbon

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Chaotic system may lead to instability, extreme sensitivity and performance reduction in control systems. It is therefore important to understand the causes of such undesirable characteristics in control system especially in the automobile fuel gauges. This is because without accurate fuel gauges in automobile systems, it will be difficult if not impossible to embark on a journey whether during odd hours of the day or where fuel is difficult to obtain. To this end, this work studied the impacts of fuel tank rust and faulty component of fuel gauge system (voltage stabilizer) on the chaotic characteristics of fuel gauges. The results obtained were analyzed using Graph iSOFT package. Over the range of experiments conducted, the results obtained showed that rust effect of the fuel tank would alter the flow density, consequently the fluid pressure and ultimately the flow velocity of the fuel. The responses of the fuel gauge pointer to the faulty voltage stabilizer were erratic causing noticeable instability of gauge measurands indicated. The experiment also showed that the fuel gauge performed optimally by indicating the highest degree of accuracy when combined the effect of rust free tank and non-faulty voltage stabilizer conditions (± 6.75% measurand error) as compared to only the rust free tank situation (± 15% measurand error) and only the non-faulty voltage stabilizer condition (± 40% measurand error). The study concludes that both the fuel tank rust and the faulty voltage stabilizer gauge component have a significant effect on the sensitivity of fuel gauge and its accuracy ultimately. Also, by the reason of literature, our findings can also be said to be valid for all other fluid meters and gauges applicable in plant machineries and most hydraulic systems.

Keywords: Chaotic system, degree of accuracy, measurand, sensitivity of fuel gauge.

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Authors: F. Amin, S. Feizi

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This paper describes the complex nature of organizational culture and its role in telecom organizations. To set the stage for culture change, the literature is reviewed for perspective on the role and function of culture in organizations. Organizational the­orists as well as business consultants report that a strong organizational culture is essential for success because the shared assumptions, values and culture of an organization influence the behavior of its individual members.

Keywords: Component, Telecommunication, Management, Cultural, Transformation.

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Authors: Saisundar. S., I Made Darmayuda, Zhou Jun, Krishna Mainali, Simon Ng Sheung Yan, Eran Ofek

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This paper compares the recent transformerless ACDC power converter architectures and provides an assessment of each. A prototype of one of the transformerless AC-DC converter architecture is also presented depicting the feasibility of a small form factor, power supply design. In this paper component selection guidelines to achieve high efficiency AC-DC power conversion are also discussed.

Keywords: AC-DC converter, digitally controlled, switched mode power supply, transformerless.

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Authors: Chun-Wei Huang, Jyh-Cherng Gu, Ming-Ta Yang

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Non-synchronous breakage or line failure in power systems with light or no loads can lead to core saturation in transformers or potential transformers. This can cause component and capacitance matching resulting in the formation of resonant circuits, which trigger ferroresonance. This study employed a wavelet transform for the detection of ferroresonance. Simulation results demonstrate the efficacy of the proposed method.

Keywords: Ferroresonance, Wavelet Transform, Intelligent Electronic Device, Transformer.

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Authors: Elia Favarelli, Enrico Testi, Andrea Giorgetti

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Autonomous structural health monitoring (SHM) of many structures and bridges became a topic of paramount importance for maintenance purposes and safety reasons. This paper proposes a set of machine learning (ML) tools to perform automatic feature selection and detection of anomalies in a bridge from vibrational data and compare different feature extraction schemes to increase the accuracy and reduce the amount of data collected. As a case study, the Z-24 bridge is considered because of the extensive database of accelerometric data in both standard and damaged conditions. The proposed framework starts from the first four fundamental frequencies extracted through operational modal analysis (OMA) and clustering, followed by time-domain filtering (tracking). The fundamental frequencies extracted are then fed to a dimensionality reduction block implemented through two different approaches: feature selection (intelligent multiplexer) that tries to estimate the most reliable frequencies based on the evaluation of some statistical features (i.e., entropy, variance, kurtosis), and feature extraction (auto-associative neural network (ANN)) that combine the fundamental frequencies to extract new damage sensitive features in a low dimensional feature space. Finally, one-class classification (OCC) algorithms perform anomaly detection, trained with standard condition points, and tested with normal and anomaly ones. In particular, principal component analysis (PCA), kernel principal component analysis (KPCA), and autoassociative neural network (ANN) are presented and their performance are compared. It is also shown that, by evaluating the correct features, the anomaly can be detected with accuracy and an F1 score greater than 95%.

Keywords: Anomaly detection, dimensionality reduction, frequencies selection, modal analysis, neural network, structural health monitoring, vibration measurement.

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Authors: Yoshitaka Fujiwara, Jun-ichirou Fukushima, Yasunari Maeda

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Keys to high-quality face-to-face education are ensuring flexibility in the way lectures are given, and providing care and responsiveness to learners. This paper describes a face-to-face education support system that is designed to raise the satisfaction of learners and reduce the workload on instructors. This system consists of a lecture adaptation assistance part, which assists instructors in adapting teaching content and strategy, and a Q&A assistance part, which provides learners with answers to their questions. The core component of the former part is a “learning achievement map", which is composed of a Bayesian network (BN). From learners- performance in exercises on relevant past lectures, the lecture adaptation assistance part obtains information required to adapt appropriately the presentation of the next lecture. The core component of the Q&A assistance part is a case base, which accumulates cases consisting of questions expected from learners and answers to them. The Q&A assistance part is a case-based search system equipped with a search index which performs probabilistic inference. A prototype face-to-face education support system has been built, which is intended for the teaching of Java programming, and this approach was evaluated using this system. The expected degree of understanding of each learner for a future lecture was derived from his or her performance in exercises on past lectures, and this expected degree of understanding was used to select one of three adaptation levels. A model for determining the adaptation level most suitable for the individual learner has been identified. An experimental case base was built to examine the search performance of the Q&A assistance part, and it was found that the rate of successfully finding an appropriate case was 56%.

Keywords: Bayesian network, face-to-face education, lecture adaptation, Q&A assistance.

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Authors: A.R Alesaadi, M. Nafar, A.H. Gheisari

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In this paper sensitivity analysis is performed for reliability evaluation of power systems. When examining the reliability of a system, it is useful to recognize how results change as component parameters are varied. This knowledge helps engineers to understand the impact of poor data, and gives insight on how reliability can be improved. For these reasons, a sensitivity analysis can be performed. Finally, a real network was used for testing the presented method.

Keywords: sensitivity analysis, reliability evaluation, powersystems.

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Authors: Lai-Fen Yang

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In this increasingly visual world, how can we best decipher and understand the many ways that our everyday lives are organized around looking practices and the many images we encounter each day? Indeed, how we interact with and interpret visual images is a basic component of human life. Today, however, we are living in one of the most artificial visual and image-saturated cultures in human history, which makes understanding the complex construction and multiple social functions of visual imagery more important than ever before. Themes regarding our experience of a visually pervasive mediated culture, here, termed visual spectacle.

Keywords: Visual culture, contemporary, visual spectacle.

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Authors: K. K. Kaldybay, T. K. Abdrassilov, G. K. Abdygalieva, P. M. Suleymenov, M. O. Nassimov

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People have always needed to believe in some supernatural power, which could explain nature phenomena. Different kinds of religions like Christianity, Hinduism, Islam, Buddhism have thought believers in all world, how to behave themselves. We think the most important role of religion in modern society most important role of religion in modern society is safety of the People. World and traditional religion played a prominent role in the socio-cultural progress, and in the development of man as a spiritual being. At the heart of religious morals the belief in god and responsibility before it lies and specifies religious and ethical values and categories . The religion is based on ethical standards historically developed by society, requirements and concepts, but it puts all social and moral relations of the person in dependence on religious values. For everything that the believer makes on a debt or a duty, he bears moral responsibility before conscience, people and god. The concept of value of religious morals takes the central place because the religion from all forms of public consciousness most values is painted as it is urged to answer vital questions. Any religion not only considers questions of creation of the world, sense of human existence, relationship of god and the person, but also offers the ethical concept, develops rules of behavior of people. The religion a long time dominated in the history of culture, and during this time created a set of cultural and material values. The identity of Kazakh culture can be defined as a Cultural identity traditional ,national identity and the identity values developed by Kazakh people in process of cultural-historical development, promoting formation of Kazakh culture identity on public consciousness. Identity is the historical process but always the tradition exists in it as a component of stability, as a component of self that what this identity formed .

Keywords: Philosophy, religion, education, culture, human, national value, security, religious value.

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Authors: David E. Culler, Noah D. Anderson

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Integrated systems for product design, manufacturing, and lifecycle management are difficult to implement and customize. Commercial software vendors, including CAD/CAM and third party PDM/PLM developers, create user interfaces and functionality that allow their products to be applied across many industries. The result is that systems become overloaded with functionality, difficult to navigate, and use terminology that is unfamiliar to engineers and production personnel. For example, manufacturers of automotive, aeronautical, electronics, and household products use similar but distinct methods and processes. Furthermore, each company tends to have their own preferred tools and programs for controlling work and information flow and that connect design, planning, and manufacturing processes to business applications. This paper presents a methodology and a case study that addresses these issues and suggests that in the future more companies will develop personalized applications that fit to the natural way that their business operates. A functioning system has been implemented at a highly competitive U.S. aerospace tooling and component supplier that works with many prominent airline manufacturers around the world including The Boeing Company, Airbus, Embraer, and Bombardier Aerospace. During the last three years, the program has produced significant benefits such as the automatic creation and management of component and assembly designs (parametric models and drawings), the extensive use of lightweight 3D data, and changes to the way projects are executed from beginning to end. CATIA (CAD/CAE/CAM) and a variety of programs developed in C#, VB.Net, HTML, and SQL make up the current system. The web-based platform is facilitating collaborative work across multiple sites around the world and improving communications with customers and suppliers. This work demonstrates that the creative use of Application Programming Interface (API) utilities, libraries, and methods is a key to automating many time-consuming tasks and linking applications together.

Keywords: CAD/CAM, CAPP, PDM, PLM, Scalable Systems.

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Authors: Abdulaziz Alsadhan, Naveed Khan

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In recent years intrusions on computer network are the major security threat. Hence, it is important to impede such intrusions. The hindrance of such intrusions entirely relies on its detection, which is primary concern of any security tool like Intrusion detection system (IDS). Therefore, it is imperative to accurately detect network attack. Numerous intrusion detection techniques are available but the main issue is their performance. The performance of IDS can be improved by increasing the accurate detection rate and reducing false positive. The existing intrusion detection techniques have the limitation of usage of raw dataset for classification. The classifier may get jumble due to redundancy, which results incorrect classification. To minimize this problem, Principle component analysis (PCA), Linear Discriminant Analysis (LDA) and Local Binary Pattern (LBP) can be applied to transform raw features into principle features space and select the features based on their sensitivity. Eigen values can be used to determine the sensitivity. To further classify, the selected features greedy search, back elimination, and Particle Swarm Optimization (PSO) can be used to obtain a subset of features with optimal sensitivity and highest discriminatory power. This optimal feature subset is used to perform classification. For classification purpose, Support Vector Machine (SVM) and Multilayer Perceptron (MLP) are used due to its proven ability in classification. The Knowledge Discovery and Data mining (KDD’99) cup dataset was considered as a benchmark for evaluating security detection mechanisms. The proposed approach can provide an optimal intrusion detection mechanism that outperforms the existing approaches and has the capability to minimize the number of features and maximize the detection rates.

Keywords: Particle Swarm Optimization (PSO), Principle component analysis (PCA), Linear Discriminant Analysis (LDA), Local Binary Pattern (LBP), Support Vector Machine (SVM), Multilayer Perceptron (MLP).

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Authors: T. Özdal, N. Şahin Yeşilcubuk

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Bisphenol-A (BPA) is one of the highest volume chemicals produced worldwide in the plastic industry. This compound is mostly used in producing polycarbonate plastics that are often used for food and beverage storage, and BPA is also a component of epoxy resins that are used to line food and beverage containers. Studies performed in this area indicated that BPA could be extracted from such products while they are in contact with food.  Therefore, BPA exposure is presumed. In this paper, the chemical structure of BPA, factors affecting BPA migration to food and beverages, effects on health, and recent regulations will be reviewed.

Keywords: BPA, health, regulations, toxicity.

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Authors: T. Jayanthi, K. Velusamy, H. Seetha, S. A. V. Satya Murty

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Verification and Validation of Simulated Process Model is the most important phase of the simulator life cycle. Evaluation of simulated process models based on Verification and Validation techniques checks the closeness of each component model (in a simulated network) with the real system/process with respect to dynamic behaviour under steady state and transient conditions. The process of Verification and Validation helps in qualifying the process simulator for the intended purpose whether it is for providing comprehensive training or design verification. In general, model verification is carried out by comparison of simulated component characteristics with the original requirement to ensure that each step in the model development process completely incorporates all the design requirements. Validation testing is performed by comparing the simulated process parameters to the actual plant process parameters either in standalone mode or integrated mode. A Full Scope Replica Operator Training Simulator for PFBR - Prototype Fast Breeder Reactor has been developed at IGCAR, Kalpakkam, INDIA named KALBR-SIM (Kalpakkam Breeder Reactor Simulator) where in the main participants are engineers/experts belonging to Modeling Team, Process Design and Instrumentation & Control design team. This paper discusses about the Verification and Validation process in general, the evaluation procedure adopted for PFBR operator training Simulator, the methodology followed for verifying the models, the reference documents and standards used etc. It details out the importance of internal validation by design experts, subsequent validation by external agency consisting of experts from various fields, model improvement by tuning based on expert’s comments, final qualification of the simulator for the intended purpose and the difficulties faced while co-coordinating various activities.

Keywords: Verification and Validation (V&V), Prototype Fast Breeder Reactor (PFBR), Kalpakkam Breeder Reactor Simulator (KALBR-SIM), Steady State, Transient State.

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Authors: Haj Najafi Leila, Tehranizadeh Mohsen

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Dependencies between diverse factors involved in probabilistic seismic loss evaluation are recognized to be an imperative issue in acquiring accurate loss estimates. Dependencies among component damage costs could be taken into account considering two partial distinct states of independent or perfectly-dependent for component damage states; however, in our best knowledge, there is no available procedure to take account of loss dependencies in story level. This paper attempts to present a method called "modal cost superposition method" for decoupling story damage costs subjected to earthquake ground motions dealt with closed form differential equations between damage cost and engineering demand parameters which should be solved in complex system considering all stories' cost equations by the means of the introduced "substituted matrixes of mass and stiffness". Costs are treated as probabilistic variables with definite statistic factors of median and standard deviation amounts and a presumed probability distribution. To supplement the proposed procedure and also to display straightforwardness of its application, one benchmark study has been conducted. Acceptable compatibility has been proven for the estimated damage costs evaluated by the new proposed modal and also frequently used stochastic approaches for entire building; however, in story level, insufficiency of employing modification factor for incorporating occurrence probability dependencies between stories has been revealed due to discrepant amounts of dependency between damage costs of different stories. Also, more dependency contribution in occurrence probability of loss could be concluded regarding more compatibility of loss results in higher stories than the lower ones, whereas reduction in incorporation portion of cost modes provides acceptable level of accuracy and gets away from time consuming calculations including some limited number of cost modes in high mode situation.

Keywords: Dependency, story-cost, cost modes, engineering demand parameter.

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Authors: Dmitriy Yu. Korulkin, Raissa A. Muzychkina

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The article represents the results of isolation and component chromatographic analysis of essential oils of Polygonum L. plants growing in Kazakhstan in commercial reserves at the territory of Kazakhstan. The results of research of antibacterial and antifungal activity of isolated compounds have been represented.

Keywords: Antibacterial, antifungal, bioactive substances, essential oils, isolation, Polygonum L.

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Authors: Hazem M. El-Bakry

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Principal Component Analysis (PCA) has many different important applications especially in pattern detection such as face detection / recognition. Therefore, for real time applications, the response time is required to be as small as possible. In this paper, new implementation of PCA for fast face detection is presented. Such new implementation is designed based on cross correlation in the frequency domain between the input image and eigenvectors (weights). Simulation results show that the proposed implementation of PCA is faster than conventional one.

Keywords: Fast Face Detection, PCA, Cross Correlation, Frequency Domain

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Authors: R. Arulmurugan, P. Sengottuvelan

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Object detection using Wavelet Neural Network (WNN) plays a major contribution in the analysis of image processing. Existing cluster-based algorithm for co-saliency object detection performs the work on the multiple images. The co-saliency detection results are not desirable to handle the multi scale image objects in WNN. Existing Super Resolution (SR) scheme for landmark images identifies the corresponding regions in the images and reduces the mismatching rate. But the Structure-aware matching criterion is not paying attention to detect multiple regions in SR images and fail to enhance the result percentage of object detection. To detect the objects in the high-resolution remote sensing images, Tagged Grid Matching (TGM) technique is proposed in this paper. TGM technique consists of the three main components such as object determination, object searching and object verification in WNN. Initially, object determination in TGM technique specifies the position and size of objects in the current image. The specification of the position and size using the hierarchical grid easily determines the multiple objects. Second component, object searching in TGM technique is carried out using the cross-point searching. The cross out searching point of the objects is selected to faster the searching process and reduces the detection time. Final component performs the object verification process in TGM technique for identifying (i.e.,) detecting the dissimilarity of objects in the current frame. The verification process matches the search result grid points with the stored grid points to easily detect the objects using the Gabor wavelet Transform. The implementation of TGM technique offers a significant improvement on the multi-object detection rate, processing time, precision factor and detection accuracy level.

Keywords: Object Detection, Cross-point Searching, Wavelet Neural Network, Object Determination, Gabor Wavelet Transform, Tagged Grid Matching.

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Authors: John Kabuba, Antoine Mulaba-Bafubiandi

Abstract:

The elution process for the removal of Co and Cu from clinoptilolite as an ion-exchanger was investigated using three parameters: bed volume, pH and contact time. The present paper study has shown quantitatively that acid concentration has a significant effect on the elution process. The favorable eluant concentration was found to be 2 M HCl and 2 M H2SO4, respectively. The multi-component equilibrium relationship in the process can be very complex, and perhaps ill-defined. In such circumstances, it is preferable to use a non-parametric technique such as Neural Network to represent such an equilibrium relationship.

Keywords: Clinoptilolite, elution, modeling, neural network.

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Authors: András Barta, István Vajk

Abstract:

In pattern recognition applications the low level segmentation and the high level object recognition are generally considered as two separate steps. The paper presents a method that bridges the gap between the low and the high level object recognition. It is based on a Bayesian network representation and network propagation algorithm. At the low level it uses hierarchical structure of quadratic spline wavelet image bases. The method is demonstrated for a simple circuit diagram component identification problem.

Keywords: Object recognition, Bayesian network, Wavelets, Document processing.

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Authors: M. Rodionov, Z. Dedovets

Abstract:

This article discusses ways to implement a differentiated approach to developing academic motivation for mathematical studies which relies on defining the primary structural characteristics of motivation. The following characteristics are considered: features of realization of cognitive activity, meaningmaking characteristics, level of generalization and consistency of knowledge acquired by personal experience. The assessment of the present level of individual student understanding of each component of academic motivation is the basis for defining the relevant educational strategy for its further development.

Keywords: Learning activity, mathematics, motivation, student.

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Authors: Pei-Chann Chang, Jui-Chien Hsieh, Jyun-Jie Lin, Feng-Ming Yeh

Abstract:

Atrial Fibrillation is the most common sustained arrhythmia encountered by clinicians. Because of the invisible waveform of atrial fibrillation in atrial activation for human, it is necessary to develop an automatic diagnosis system. 12-Lead ECG now is available in hospital and is appropriate for using Independent Component Analysis to estimate the AA period. In this research, we also adopt a second-order blind identification approach to transform the sources extracted by ICA to more precise signal and then we use frequency domain algorithm to do the classification. In experiment, we gather a significant result of clinical data.

Keywords: 12-Lead ECG, Atrial Fibrillation, Blind SourceSeparation, Kurtosis

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Authors: Carla Layana Luis Diambra

Abstract:

Microarrays technique allows the simultaneous measurements of the expression levels of thousands of mRNAs. By mining this data one can identify the dynamics of the gene expression time series. By recourse of principal component analysis, we uncover the circadian rhythmic patterns underlying the gene expression profiles from Cyanobacterium Synechocystis. We applied PCA to reduce the dimensionality of the data set. Examination of the components also provides insight into the underlying factors measured in the experiments. Our results suggest that all rhythmic content of data can be reduced to three main components.

Keywords: circadian rhythms, clustering, gene expression, PCA.

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