Search results for: early identification
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1527

Search results for: early identification

1407 Error-Robust Nature of Genome Profiling Applied for Clustering of Species Demonstrated by Computer Simulation

Authors: Shamim Ahmed Koichi Nishigaki

Abstract:

Genome profiling (GP), a genotype based technology, which exploits random PCR and temperature gradient gel electrophoresis, has been successful in identification/classification of organisms. In this technology, spiddos (Species identification dots) and PaSS (Pattern similarity score) were employed for measuring the closeness (or distance) between genomes. Based on the closeness (PaSS), we can buildup phylogenetic trees of the organisms. We noticed that the topology of the tree is rather robust against the experimental fluctuation conveyed by spiddos. This fact was confirmed quantitatively in this study by computer-simulation, providing the limit of the reliability of this highly powerful methodology. As a result, we could demonstrate the effectiveness of the GP approach for identification/classification of organisms.

Keywords: Fluctuation, Genome profiling (GP), Pattern similarity score (PaSS), Robustness, Spiddos-shift.

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1406 Parameters Estimation of Multidimensional Possibility Distributions

Authors: Sergey Sorokin, Irina Sorokina, Alexander Yazenin

Abstract:

We present a solution to the Maxmin u/E parameters estimation problem of possibility distributions in m-dimensional case. Our method is based on geometrical approach, where minimal area enclosing ellipsoid is constructed around the sample. Also we demonstrate that one can improve results of well-known algorithms in fuzzy model identification task using Maxmin u/E parameters estimation.

Keywords: Possibility distribution, parameters estimation, Maxmin u/E estimator, fuzzy model identification.

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1405 Signature Identification Scheme Based on Iterated Function Systems

Authors: Nadia M. G. AL-Saidi

Abstract:

Since 1984 many schemes have been proposed for digital signature protocol, among them those that based on discrete log and factorizations. However a new identification scheme based on iterated function (IFS) systems are proposed and proved to be more efficient. In this study the proposed identification scheme is transformed into a digital signature scheme by using a one way hash function. It is a generalization of the GQ signature schemes. The attractor of the IFS is used to obtain public key from a private one, and in the encryption and decryption of a hash function. Our aim is to provide techniques and tools which may be useful towards developing cryptographic protocols. Comparisons between the proposed scheme and fractal digital signature scheme based on RSA setting, as well as, with the conventional Guillou-Quisquater signature, and RSA signature schemes is performed to prove that, the proposed scheme is efficient and with high performance.

Keywords: Digital signature, Fractal, Iterated function systems(IFS), Guillou-Quisquater (GQ) protocol, Zero-knowledge (ZK)

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1404 Application of Company Financial Crisis Early Warning Model- Use of “Financial Reference Database“

Authors: Chiung-ying Lee, Chia-hua Chang

Abstract:

In July 1, 2007, Taiwan Stock Exchange (TWSE) on market observation post system (MOPS) adds a new "Financial reference database" for investors to do investment reference. This database as a warning to public offering companies listed on the public financial information and it original within eight targets. In this paper, this database provided by the indicators for the application of company financial crisis early warning model verify that the database provided by the indicator forecast for the financial crisis, whether or not companies have a high accuracy rate as opposed to domestic and foreign scholars have positive results. There is use of Logistic Regression Model application of the financial early warning model, in which no joined back-conditions is the first model, joined it in is the second model, has been taken occurred in the financial crisis of companies to research samples and then business took place before the financial crisis point with T-1 and T-2 sample data to do positive analysis. The results show that this database provided the debt ratio and net per share for the best forecast variables.

Keywords: Financial reference database, Financial early warning model, Logistic Regression.

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1403 A New Biometric Human Identification Based On Fusion Fingerprints and Finger Veins Using monoLBP Descriptor

Authors: Alima Damak Masmoudi, Randa Boukhris Trabelsi, Dorra Sellami Masmoudi

Abstract:

Single biometric modality recognition is not able to meet the high performance supplies in most cases with its application become more and more broadly. Multimodal biometrics identification represents an emerging trend recently. This paper investigates a novel algorithm based on fusion of both fingerprint and fingervein biometrics. For both biometric recognition, we employ the Monogenic Local Binary Pattern (MonoLBP). This operator integrate the orginal LBP (Local Binary Pattern ) with both other rotation invariant measures: local phase and local surface type. Experimental results confirm that a weighted sum based proposed fusion achieves excellent identification performances opposite unimodal biometric systems. The AUC of proposed approach based on combining the two modalities has very close to unity (0.93).

Keywords: fingerprint, fingervein, LBP, MonoLBP, fusion, biometric trait.

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1402 Evaluation of Sensor Pattern Noise Estimators for Source Camera Identification

Authors: Benjamin Anderson-Sackaney, Amr Abdel-Dayem

Abstract:

This paper presents a comprehensive survey of recent source camera identification (SCI) systems. Then, the performance of various sensor pattern noise (SPN) estimators was experimentally assessed, under common photo response non-uniformity (PRNU) frameworks. The experiments used 1350 natural and 900 flat-field images, captured by 18 individual cameras. 12 different experiments, grouped into three sets, were conducted. The results were analyzed using the receiver operator characteristic (ROC) curves. The experimental results demonstrated that combining the basic SPN estimator with a wavelet-based filtering scheme provides promising results. However, the phase SPN estimator fits better with both patch-based (BM3D) and anisotropic diffusion (AD) filtering schemes.

Keywords: Sensor pattern noise, source camera identification, photo response non-uniformity, anisotropic diffusion, peak to correlation energy ratio.

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1401 From Ritual City to Modern City: The City Space Transformation of Xi’an in the Early 20th Century

Authors: Zhang Bian, Zhao Jijun

Abstract:

The urban layout of Xi’an city (the capital Chang’an in the Tang dynasty) was shaped by feudal etiquette, but this dominant factor was replaced by modern city planning during the period of the Republic of China. This makes Xi’an a representative case to explore the transformation process of Chinese cities in the early 20th century. By analyzing the contrast and connection between the historical texts of city planning and the realistic construction activities recorded by the maps and images, this paper reviews the transformation process of the urban space of Xi’an in the early 20th century and divides it into four phases according to important events that significantly impacted planning and construction activities. Based on this, the entire transformation of Xi’an’s city planning and practices can be characterized by three aspects: 1) the dominant force of the city plan and construction changed with the establishment of modern city administrations; 2) the layout of the city was continuously broadened to meet the demand of modern economy and city life; and, 3) the ritual space was transformed into practical space for commercial and recreational activities.

Keywords: City space, early 20th century, transformation, Xi’an city.

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1400 Hybrid Algorithm for Hammerstein System Identification Using Genetic Algorithm and Particle Swarm Optimization

Authors: Tomohiro Hachino, Kenji Shimoda, Hitoshi Takata

Abstract:

This paper presents a method of model selection and identification of Hammerstein systems by hybridization of the genetic algorithm (GA) and particle swarm optimization (PSO). An unknown nonlinear static part to be estimated is approximately represented by an automatic choosing function (ACF) model. The weighting parameters of the ACF and the system parameters of the linear dynamic part are estimated by the linear least-squares method. On the other hand, the adjusting parameters of the ACF model structure are properly selected by the hybrid algorithm of the GA and PSO, where the Akaike information criterion is utilized as the evaluation value function. Simulation results are shown to demonstrate the effectiveness of the proposed hybrid algorithm.

Keywords: Hammerstein system, identification, automatic choosing function model, genetic algorithm, particle swarm optimization.

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1399 The Investment of Islamic Education Values toward Children in the Early Age through Story-Telling Method

Authors: Abdul Rofiq Badril Rizal Muzammil

Abstract:

Education is an absolute necessity for human’s life that one must fulfill for the entire life. Without education it is impossible for human to develop her/himself well. The education process is an effort to maintain a good behavior within one’s life. Good behavior will be absolutely achieved if it is taught to early-aged children. This paper focuses on how the story telling method enables teachers to make the students have the construction of good behavior and obtain the goal of national education in Indonesia. The targeted students would involve students in As-Solihin kindergarten, Salafiyah-Syafi’iyah Mumbulsari, Jember, Indonesia. Story is what early-aged children like most. Thus, it is a gorgeous chance to make story telling activity as a method to invest Islamic education values to children. This paper, however, also focuses on some deliberately important aspects which of course teachers need to consider including objectives and strategies of the method’s implementation. The teachers will be in need of knowing each student’s characteristic in the classroom so that it would enable them to select appropriate stories that fit best to early aged students. The selected stories are taken from Islamic stories that tell the life of Prophet and heroes of Islam as well as well-known persons in Islam. In addition, there will be a number of activities done in the classroom after the delivery of the story is over on purpose of leading students to have the fundamental foundation of how to build self-awareness in order they could understand better about the importance of being a well-behaved person. After reviewing relevant theories, secondary research and scholars’ opinion involved in all aspects of early-aged children behavior, the author concludes that by leveraging trusted sources, a proactive, co-operative and creative strategy, the teacher can successfully build up children’s good behavior by instilling the Islamic value toward early-aged children through story telling method.

Keywords: Story, Islam, children, early age.

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1398 Smartphone Video Source Identification Based on Sensor Pattern Noise

Authors: Raquel Ramos López, Anissa El-Khattabi, Ana Lucila Sandoval Orozco, Luis Javier García Villalba

Abstract:

An increasing number of mobile devices with integrated cameras has meant that most digital video comes from these devices. These digital videos can be made anytime, anywhere and for different purposes. They can also be shared on the Internet in a short period of time and may sometimes contain recordings of illegal acts. The need to reliably trace the origin becomes evident when these videos are used for forensic purposes. This work proposes an algorithm to identify the brand and model of mobile device which generated the video. Its procedure is as follows: after obtaining the relevant video information, a classification algorithm based on sensor noise and Wavelet Transform performs the aforementioned identification process. We also present experimental results that support the validity of the techniques used and show promising results.

Keywords: Digital video, forensics analysis, key frame, mobile device, PRNU, sensor noise, source identification.

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1397 Native Language Identification with Cross-Corpus Evaluation Using Social Media Data: 'Reddit'

Authors: Yasmeen Bassas, Sandra Kuebler, Allen Riddell

Abstract:

Native Language Identification is one of the growing subfields in Natural Language Processing (NLP). The task of Native Language Identification (NLI) is mainly concerned with predicting the native language of an author’s writing in a second language. In this paper, we investigate the performance of two types of features; content-based features vs. content independent features when they are evaluated on a different corpus (using social media data “Reddit”). In this NLI task, the predefined models are trained on one corpus (TOEFL) and then the trained models are evaluated on a different data using an external corpus (Reddit). Three classifiers are used in this task; the baseline, linear SVM, and Logistic Regression. Results show that content-based features are more accurate and robust than content independent ones when tested within corpus and across corpus.

Keywords: NLI, NLP, content-based features, content independent features, social media corpus, ML.

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1396 Texture Feature-Based Language Identification Using Wavelet-Domain BDIP and BVLC Features and FFT Feature

Authors: Ick Hoon Jang, Hoon Jae Lee, Dae Hoon Kwon, Ui Young Pak

Abstract:

In this paper, we propose a texture feature-based language identification using wavelet-domain BDIP (block difference of inverse probabilities) and BVLC (block variance of local correlation coefficients) features and FFT (fast Fourier transform) feature. In the proposed method, wavelet subbands are first obtained by wavelet transform from a test image and denoised by Donoho-s soft-thresholding. BDIP and BVLC operators are next applied to the wavelet subbands. FFT blocks are also obtained by 2D (twodimensional) FFT from the blocks into which the test image is partitioned. Some significant FFT coefficients in each block are selected and magnitude operator is applied to them. Moments for each subband of BDIP and BVLC and for each magnitude of significant FFT coefficients are then computed and fused into a feature vector. In classification, a stabilized Bayesian classifier, which adopts variance thresholding, searches the training feature vector most similar to the test feature vector. Experimental results show that the proposed method with the three operations yields excellent language identification even with rather low feature dimension.

Keywords: BDIP, BVLC, FFT, language identification, texture feature, wavelet transform.

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1395 Iris Localization using Circle and Fuzzy Circle Detection Method

Authors: Marzieh. Savoj, S. Amirhassan. Monadjemi

Abstract:

Iris localization is a very important approach in biometric identification systems. Identification process usually is implemented in three levels: iris localization, feature extraction, and pattern matching finally. Accuracy of iris localization as the first step affects all other levels and this shows the importance of iris localization in an iris based biometric system. In this paper, we consider Daugman iris localization method as a standard method, propose a new method in this field and then analyze and compare the results of them on a standard set of iris images. The proposed method is based on the detection of circular edge of iris, and improved by fuzzy circles and surface energy difference contexts. Implementation of this method is so easy and compared to the other methods, have a rather high accuracy and speed. Test results show that the accuracy of our proposed method is about Daugman method and computation speed of it is 10 times faster.

Keywords: Convolution, Edge detector filter, Fuzzy circle, Identification

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1394 Early-Warning Lights Classification Management System for Industrial Parks in Taiwan

Authors: Yu-Min Chang, Kuo-Sheng Tsai, Hung-Te Tsai, Chia-Hsin Li

Abstract:

This paper presents the early-warning lights classification management system for industrial parks promoted by the Taiwan Environmental Protection Administration (EPA) since 2011, including the definition of each early-warning light, objectives, action program and accomplishments. All of the 151 industrial parks in Taiwan were classified into four early-warning lights, including red, orange, yellow and green, for carrying out respective pollution management according to the monitoring data of soil and groundwater quality, regulatory compliance, and regulatory listing of control site or remediation site. The Taiwan EPA set up a priority list for high potential polluted industrial parks and investigated their soil and groundwater qualities based on the results of the light classification and pollution potential assessment. In 2011-2013, there were 44 industrial parks selected and carried out different investigation, such as the early warning groundwater well networks establishment and pollution investigation/verification for the red and orange-light industrial parks and the environmental background survey for the yellow-light industrial parks. Among them, 22 industrial parks were newly or continuously confirmed that the concentrations of pollutants exceeded those in soil or groundwater pollution control standards. Thus, the further investigation, groundwater use restriction, listing of pollution control site or remediation site, and pollutant isolation measures were implemented by the local environmental protection and industry competent authorities; the early warning lights of those industrial parks were proposed to adjust up to orange or red-light. Up to the present, the preliminary positive effect of the soil and groundwater quality management system for industrial parks has been noticed in several aspects, such as environmental background information collection, early warning of pollution risk, pollution investigation and control, information integration and application, and inter-agency collaboration. Finally, the work and goal of self-initiated quality management of industrial parks will be carried out on the basis of the inter-agency collaboration by the classified lights system of early warning and management as well as the regular announcement of the status of each industrial park.

Keywords: Industrial park, soil and groundwater quality management, early-warning lights classification, SOP for reporting and treatment of monitored abnormal events.

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1393 A New Damage Identification Strategy for SHM Based On FBGs and Bayesian Model Updating Method

Authors: Yanhui Zhang, Wenyu Yang

Abstract:

One of the difficulties of the vibration-based damage identification methods is the nonuniqueness of the results of damage identification. The different damage locations and severity may cause the identical response signal, which is even more severe for detection of the multiple damage. This paper proposes a new strategy for damage detection to avoid this nonuniqueness. This strategy firstly determines the approximates damage area based on the statistical pattern recognition method using the dynamic strain signal measured by the distributed fiber Bragg grating, and then accurately evaluates the damage information based on the Bayesian model updating method using the experimental modal data. The stochastic simulation method is then used to compute the high-dimensional integral in the Bayesian problem. Finally, an experiment of the plate structure, simulating one part of mechanical structure, is used to verify the effectiveness of this approach.

Keywords: Bayesian method, damage detection, fiber Bragg grating, structural health monitoring.

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1392 Assessing the Value of Virtual Worlds for Post- Secondary Instructors: A Survey of Innovators, Early Adopters and the Early Majority in Second Life

Authors: K. Westmoreland Bowers, Matthew W. Ragas, Jeffrey C. Neely

Abstract:

The purpose of this study was to assess the value of Second Life among post-secondary instructors with experience using Second Life as an educational tool. Using Everett Rogers-s diffusion of innovations theory, survey respondents (N = 162), were divided into three adopter categories: innovators, early adopters and the early majority. Respondents were from 15 countries and 25 academic disciplines, indicating the considerable potential this innovation has to be adopted across many different borders and in many areas of academe. Nearly 94% of respondents said they plan to use Second Life again as an educational tool. However, no significant differences were found in instructors- levels of satisfaction with Second Life as an educational tool or their perceived effect on student learning across adopter categories. On the other hand, instructors who conducted class fully in Second Life were significantly more satisfied than those who used Second Life as only a small supplement to a real-world class. Overall, personal interest factors, rather than interpersonal communication factors, most influenced respondents- decision to adopt Second Life as an educational tool. In light of these findings, theoretical implications are discussed and practical suggestions are provided.

Keywords: Second Life, Virtual Worlds, Educational Technology, Diffusion of Innovations

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1391 Pregnancy Myths and Early Chilcare: Research Reflections from the Rural Punjab, Pakistan

Authors: Azher H. Qamar

Abstract:

Pregnancy is considered a special period in a woman’s life. There are myths about pregnancy that describe gender predictions, dietary beliefs, pregnancy signs, and risk of magic or witchcraft. Majority of these myths is in connection with the early childcare. In traditional societies midwives and experienced women practice and teach these myths to young mothers. Mother who feel special and vulnerable, at the same time feel secure in following these socially transmitted myths. Rural Punjab, a province of Pakistan has a culture rich with beliefs and myths. Myths about pregnancy are significant in rural culture and pregnancy care is seen as mother and childcare. This paper presents my research reflections that I did as a part of my Ph.D studies about early childcare beliefs and rituals practiced in rural Punjab, Pakistan.

Keywords: Myths, Pregnancy, BabyCare, Culture

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1390 Acoustic Detection of the Red Date Palm Weevil

Authors: Mohammed A. Al-Manie, Mohammed I. Alkanhal

Abstract:

In this paper, acoustic techniques are used to detect hidden insect infestations of date palm tress (Phoenix dactylifera L.). In particular, we use an acoustic instrument for early discovery of the presence of a destructive insect pest commonly known as the Red Date Palm Weevil (RDPW) and scientifically as Rhynchophorus ferrugineus (Olivier). This type of insect attacks date palm tress and causes irreversible damages at late stages. As a result, the infected trees must be destroyed. Therefore, early presence detection is a major part in controlling the spread and economic damage caused by this type of infestation. Furthermore monitoring and early detection of the disease can asses in taking appropriate measures such as isolating or treating the infected trees. The acoustic system is evaluated in terms of its ability for early discovery of hidden bests inside the tested tree. When signal acquisitions is completed for a number of date palms, a signal processing technique known as time-frequency analysis is evaluated in terms of providing an estimate that can be visually used to recognize the acoustic signature of the RDPW. The testing instrument was tested in the laboratory first then; it was used on suspected or infested tress in the field. The final results indicate that the acoustic monitoring approach along with signal processing techniques are very promising for the early detection of presence of the larva as well as the adult pest in the date palms.

Keywords: Acoustic emissions, acoustic sensors, nondestructivetests, Red Date Palm Weevil, signal processing..

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1389 Comparative Study of Fault Identification and Classification on EHV Lines Using Discrete Wavelet Transform and Fourier Transform Based ANN

Authors: K.Gayathri, N. Kumarappan

Abstract:

An appropriate method for fault identification and classification on extra high voltage transmission line using discrete wavelet transform is proposed in this paper. The sharp variations of the generated short circuit transient signals which are recorded at the sending end of the transmission line are adopted to identify the fault. The threshold values involve fault classification and these are done on the basis of the multiresolution analysis. A comparative study of the performance is also presented for Discrete Fourier Transform (DFT) based Artificial Neural Network (ANN) and Discrete Wavelet Transform (DWT). The results prove that the proposed method is an effective and efficient one in obtaining the accurate result within short duration of time by using Daubechies 4 and 9. Simulation of the power system is done using MATLAB.

Keywords: EHV transmission line, Fault identification and classification, Discrete wavelet transform, Multiresolution analysis, Artificial neural network

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1388 Accurate Fault Classification and Section Identification Scheme in TCSC Compensated Transmission Line using SVM

Authors: Pushkar Tripathi, Abhishek Sharma, G. N. Pillai, Indira Gupta

Abstract:

This paper presents a new approach for the protection of Thyristor-Controlled Series Compensator (TCSC) line using Support Vector Machine (SVM). One SVM is trained for fault classification and another for section identification. This method use three phase current measurement that results in better speed and accuracy than other SVM based methods which used single phase current measurement. This makes it suitable for real-time protection. The method was tested on 10,000 data instances with a very wide variation in system conditions such as compensation level, source impedance, location of fault, fault inception angle, load angle at source bus and fault resistance. The proposed method requires only local current measurement.

Keywords: Fault Classification, Section Identification, Feature Selection, Support Vector Machine (SVM), Thyristor-Controlled Series Compensator (TCSC)

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1387 Early-Age Structural and Thermal Performance of GGBS Concrete

Authors: Kangkang Tang

Abstract:

A large amount of blast furnace slag is generated in China. Most ground granulated blast furnace slag (GGBS) however ends up in low-grade applications. Blast furnace slag, ground to an appropriate fineness, can be used as a partial replacement of cementitious material in concrete. The potential for using GGBS in structural concrete, e.g. concrete beams and columns is investigated at Xi’an Jiaotong-Liverpool University (XJTLU). With 50% of CEM I cement replaced with GGBS, peak hydration temperatures determined in a suspended concrete slab reduced by 20%. This beneficiary effect has not been further improved with 70% of CEM I replaced with GGBS. Partial replacement of CEM I with GGBS has a retardation effect on the early-age strength of concrete. More GGBS concrete mixes will be conducted to identify an ‘optimum’ replacement level which will lead to a reduced thermal loading, without significantly compromising the early-age strength of concrete.

Keywords: GGBS, thermal effect, sustainable construction, CEM I.

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1386 A Proposed Technique for Software Development Risks Identification by using FTA Model

Authors: Hatem A. Khater, A. Baith Mohamed, Sara M. Kamel

Abstract:

Software Development Risks Identification (SDRI), using Fault Tree Analysis (FTA), is a proposed technique to identify not only the risk factors but also the causes of the appearance of the risk factors in software development life cycle. The method is based on analyzing the probable causes of software development failures before they become problems and adversely affect a project. It uses Fault tree analysis (FTA) to determine the probability of a particular system level failures that are defined by A Taxonomy for Sources of Software Development Risk to deduce failure analysis in which an undesired state of a system by using Boolean logic to combine a series of lower-level events. The major purpose of this paper is to use the probabilistic calculations of Fault Tree Analysis approach to determine all possible causes that lead to software development risk occurrence

Keywords: Software Development Risks Identification (SDRI), Fault Tree Analysis (FTA), Taxonomy for Software Development Risks (TSDR), Probabilistic Risk Assessment (PRA).

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1385 An Electronic and Performance Test for the Applicants to Faculty of Education for Early Childhood in Egypt for Measuring the Skills of Teacher Students

Authors: Ahmed Amin Mousa, Gehan Azam

Abstract:

The current study presents an electronic test to measure teaching skills. This test is a part of the admission system of the Faculty of Education for Early Childhood, Cairo University. The test has been prepared to evaluate university students who apply for admission the Faculty. It measures some social and physiological skills which are important for successful teachers, such as emotional adjustment and problem solving; moreover, the extent of their love for children and their capability to interact with them. The test has been approved by 13 experts. Finally, it has been introduced to 1,100 students during the admission system of the academic year 2016/2017. The results showed that most of the applicants have an auditory learning style. In addition, 97% of them have the minimum requirement skills for teaching children.

Keywords: Electronic test, early childhood, skills, teacher student.

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1384 Combining Color and Layout Features for the Identification of Low-resolution Documents

Authors: Ardhendu Behera, Denis Lalanne, Rolf Ingold

Abstract:

This paper proposes a method, combining color and layout features, for identifying documents captured from lowresolution handheld devices. On one hand, the document image color density surface is estimated and represented with an equivalent ellipse and on the other hand, the document shallow layout structure is computed and hierarchically represented. The combined color and layout features are arranged in a symbolic file, which is unique for each document and is called the document-s visual signature. Our identification method first uses the color information in the signatures in order to focus the search space on documents having a similar color distribution, and finally selects the document having the most similar layout structure in the remaining search space. Finally, our experiment considers slide documents, which are often captured using handheld devices.

Keywords: Document color modeling, document visual signature, kernel density estimation, document identification.

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1383 VISMA: A Method for System Analysis in Early Lifecycle Phases

Authors: Walter Sebron, Hans Tschürtz, Peter Krebs

Abstract:

The choice of applicable analysis methods in safety or systems engineering depends on the depth of knowledge about a system, and on the respective lifecycle phase. However, the analysis method chain still shows gaps as it should support system analysis during the lifecycle of a system from a rough concept in pre-project phase until end-of-life. This paper’s goal is to discuss an analysis method, the VISSE Shell Model Analysis (VISMA) method, which aims at closing the gap in the early system lifecycle phases, like the conceptual or pre-project phase, or the project start phase. It was originally developed to aid in the definition of the system boundary of electronic system parts, like e.g. a control unit for a pump motor. Furthermore, it can be also applied to non-electronic system parts. The VISMA method is a graphical sketch-like method that stratifies a system and its parts in inner and outer shells, like the layers of an onion. It analyses a system in a two-step approach, from the innermost to the outermost components followed by the reverse direction. To ensure a complete view of a system and its environment, the VISMA should be performed by (multifunctional) development teams. To introduce the method, a set of rules and guidelines has been defined in order to enable a proper shell build-up. In the first step, the innermost system, named system under consideration (SUC), is selected, which is the focus of the subsequent analysis. Then, its directly adjacent components, responsible for providing input to and receiving output from the SUC, are identified. These components are the content of the first shell around the SUC. Next, the input and output components to the components in the first shell are identified and form the second shell around the first one. Continuing this way, shell by shell is added with its respective parts until the border of the complete system (external border) is reached. Last, two external shells are added to complete the system view, the environment and the use case shell. This system view is also stored for future use. In the second step, the shells are examined in the reverse direction (outside to inside) in order to remove superfluous components or subsystems. Input chains to the SUC, as well as output chains from the SUC are described graphically via arrows, to highlight functional chains through the system. As a result, this method offers a clear and graphical description and overview of a system, its main parts and environment; however, the focus still remains on a specific SUC. It helps to identify the interfaces and interfacing components of the SUC, as well as important external interfaces of the overall system. It supports the identification of the first internal and external hazard causes and causal chains. Additionally, the method promotes a holistic picture and cross-functional understanding of a system, its contributing parts, internal relationships and possible dangers within a multidisciplinary development team.

Keywords: Analysis methods, functional safety, hazard identification, system and safety engineering, system boundary definition, system safety.

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1382 An Intelligent Text Independent Speaker Identification Using VQ-GMM Model Based Multiple Classifier System

Authors: Cheima Ben Soltane, Ittansa Yonas Kelbesa

Abstract:

Speaker Identification (SI) is the task of establishing identity of an individual based on his/her voice characteristics. The SI task is typically achieved by two-stage signal processing: training and testing. The training process calculates speaker specific feature parameters from the speech and generates speaker models accordingly. In the testing phase, speech samples from unknown speakers are compared with the models and classified. Even though performance of speaker identification systems has improved due to recent advances in speech processing techniques, there is still need of improvement. In this paper, a Closed-Set Tex-Independent Speaker Identification System (CISI) based on a Multiple Classifier System (MCS) is proposed, using Mel Frequency Cepstrum Coefficient (MFCC) as feature extraction and suitable combination of vector quantization (VQ) and Gaussian Mixture Model (GMM) together with Expectation Maximization algorithm (EM) for speaker modeling. The use of Voice Activity Detector (VAD) with a hybrid approach based on Short Time Energy (STE) and Statistical Modeling of Background Noise in the pre-processing step of the feature extraction yields a better and more robust automatic speaker identification system. Also investigation of Linde-Buzo-Gray (LBG) clustering algorithm for initialization of GMM, for estimating the underlying parameters, in the EM step improved the convergence rate and systems performance. It also uses relative index as confidence measures in case of contradiction in identification process by GMM and VQ as well. Simulation results carried out on voxforge.org speech database using MATLAB highlight the efficacy of the proposed method compared to earlier work.

Keywords: Feature Extraction, Speaker Modeling, Feature Matching, Mel Frequency Cepstrum Coefficient (MFCC), Gaussian mixture model (GMM), Vector Quantization (VQ), Linde-Buzo-Gray (LBG), Expectation Maximization (EM), pre-processing, Voice Activity Detection (VAD), Short Time Energy (STE), Background Noise Statistical Modeling, Closed-Set Tex-Independent Speaker Identification System (CISI).

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1381 Failure to React Positively to Flood Early Warning Systems: Lessons Learned by Flood Victims from Flash Flood Disasters: The Malaysia Experience

Authors: Mohamad Sukeri Khalid, Che Su Mustaffa, Mohd Najib Marzuki, Mohd Fo’ad Sakdan, Sapora Sipon, Mohd Taib Ariffin, Shazwani Shafiai

Abstract:

This paper describes the issues relating to the role of the flash flood early warning system provided by the Malaysian Government to the communities in Malaysia, specifically during the flash flood disaster in the Cameron Highlands, Malaysia. Normally, flash flood disasters can occur as a result of heavy rainfall in an area, and that water may possibly cause flooding via streams or narrow channels. The focus of this study is the flash flood disaster which occurred on 23 October 2013 in the Cameron Highlands, and as a result the Sungai Bertam overflowed after the release of water from the Sultan Abu Bakar Dam. This release of water from the dam caused flash flooding which led to damage to properties and also the death of residents and livestock in the area. Therefore, the effort of this study is to identify the perceptions of the flash flood victims on the role of the flash flood early warning system. For the purposes of this study, data were gathered through face-to-face interviews from those flood victims who were willing to participate in this study. This approach helped the researcher to glean in-depth information about their feelings and perceptions of the role of the flash flood early warning system offered by the government. The data were analysed descriptively and the findings show that the respondents of 22 flood victims believe strongly that the flash flood early warning system was confusing and dysfunctional, and communities had failed to response positively to it. Therefore, most of the communities were not well prepared for the releasing of water from the dam which caused property damage, and 3 people were killed in the Cameron Highland flash flood disaster.

Keywords: Communities affected, disaster management, early warning system, flash flood disaster.

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1380 Gas Flow Rate Identification in Biomass Power Plants by Response Surface Method

Authors: J. Satonsaowapak, M. Krapeedang, R. Oonsivilai, A. Oonsivilai

Abstract:

The utilize of renewable energy sources becomes more crucial and fascinatingly, wider application of renewable energy devices at domestic, commercial and industrial levels is not only affect to stronger awareness but also significantly installed capacities. Moreover, biomass principally is in form of woods and converts to be energy for using by humans for a long time. Gasification is a process of conversion of solid carbonaceous fuel into combustible gas by partial combustion. Many gasified models have various operating conditions because the parameters kept in each model are differentiated. This study applied the experimental data including three inputs variables including biomass consumption; temperature at combustion zone and ash discharge rate and gas flow rate as only one output variable. In this paper, response surface methods were applied for identification of the gasified system equation suitable for experimental data. The result showed that linear model gave superlative results.

Keywords: Gasified System, Identification, Response SurfaceMethod

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1379 Material Parameter Identification of Modified AbdelKarim-Ohno Model

Authors: M. Cermak, T. Karasek, J. Rojicek

Abstract:

The key role in phenomenological modelling of cyclic plasticity is good understanding of stress-strain behaviour of given material. There are many models describing behaviour of materials using numerous parameters and constants. Combination of individual parameters in those material models significantly determines whether observed and predicted results are in compliance. Parameter identification techniques such as random gradient, genetic algorithm and sensitivity analysis are used for identification of parameters using numerical modelling and simulation. In this paper genetic algorithm and sensitivity analysis are used to study effect of 4 parameters of modified AbdelKarim-Ohno cyclic plasticity model. Results predicted by Finite Element (FE) simulation are compared with experimental data from biaxial ratcheting test with semi-elliptical loading path.

Keywords: Genetic algorithm, sensitivity analysis, inverse approach, finite element method, cyclic plasticity, ratcheting.

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1378 Comparison of Performance between Different SVM Kernels for the Identification of Adult Video

Authors: Hajar Bouirouga, Sanaa El Fkihi , Abdeilah Jilbab, Driss Aboutajdine

Abstract:

In this paper we propose a method for recognition of adult video based on support vector machine (SVM). Different kernel features are proposed to classify adult videos. SVM has an advantage that it is insensitive to the relative number of training example in positive (adult video) and negative (non adult video) classes. This advantage is illustrated by comparing performance between different SVM kernels for the identification of adult video.

Keywords: Skin detection, Support vector machine, Pornographic videos, Feature extraction, Video filtering, Classification.

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