Search results for: cartesian product.Mathematics Subject Classification[2000] :08A72
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3165

Search results for: cartesian product.Mathematics Subject Classification[2000] :08A72

2175 Content Based Image Retrieval of Brain MR Images across Different Classes

Authors: Abraham Varghese, Kannan Balakrishnan, Reji R. Varghese, Joseph S. Paul

Abstract:

Magnetic Resonance Imaging play a vital role in the decision-diagnosis process of brain MR images. For an accurate diagnosis of brain related problems, the experts mostly compares both T1 and T2 weighted images as the information presented in these two images are complementary. In this paper, rotational and translational invariant form of Local binary Pattern (LBP) with additional gray scale information is used to retrieve similar slices of T1 weighted images from T2 weighted images or vice versa. The incorporation of additional gray scale information on LBP can extract more local texture information. The accuracy of retrieval can be improved by extracting moment features of LBP and reweighting the features based on users feedback. Here retrieval is done in a single subject scenario where similar images of a particular subject at a particular level are retrieved, and multiple subjects scenario where relevant images at a particular level across the subjects are retrieved.

Keywords: Local Binary pattern (LBP), Modified Local Binary pattern (MOD-LBP), T1 and T2 weighted images, Moment features.

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2174 Consumer Product Demand Forecasting based on Artificial Neural Network and Support Vector Machine

Authors: Karin Kandananond

Abstract:

The nature of consumer products causes the difficulty in forecasting the future demands and the accuracy of the forecasts significantly affects the overall performance of the supply chain system. In this study, two data mining methods, artificial neural network (ANN) and support vector machine (SVM), were utilized to predict the demand of consumer products. The training data used was the actual demand of six different products from a consumer product company in Thailand. The results indicated that SVM had a better forecast quality (in term of MAPE) than ANN in every category of products. Moreover, another important finding was the margin difference of MAPE from these two methods was significantly high when the data was highly correlated.

Keywords: Artificial neural network (ANN), Bullwhip effect, Consumer products, Demand forecasting, Supply chain, Support vector machine (SVM).

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2173 The Impact of Online Advertising on Consumer Purchase Behavior Based on Malaysian Organizations

Authors: Naser Zourikalatehsamad, Seyed Abdorreza Payambarpour, Ibrahim Alwashali, Zahra Abdolkarimi

Abstract:

The paper aims to evaluate the effect of online advertising on consumer purchase behavior in Malaysian organizations. The paper has potential to extend and refine theory. A survey was distributed among Students of UTM university during the winter 2014 and 160 responses were collected. Regression analysis was used to test the hypothesized relationships of the model. Result shows that the predictors (cost saving factor, convenience factor and customized product or services) have positive impact on intention to continue seeking online advertising.

Keywords: Consumer purchase, convenience, customized product, cost saving, customization, flow theory, mass communication, online advertising ads, online advertising measurement, online advertising mechanism, online intelligence system, self-confidence, willingness to purchase.

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2172 Relationship between Hofstede’s Cultural Dimensions and Tourism Product Satisfaction

Authors: Thanawit Buafai, Siyathorn Khunon

Abstract:

This paper aims to explore the satisfaction levels of tourism product components on the island of Samui by studying the cultural dimension relationships of Hofsted’s classic theory. Both the six Hofsted cultural dimensions and tourism production satisfaction measures have been of interest worldwide. Therefore, the challenge of this study is to re-confirm previous research results in the ever-changing current contexts of the modern globalized business era. Self-rated questionnaires were employed to collect data from six nationalities of tourists in Samui, totaling 386 samples. The reliability of this research methodology was 0.967. Correlation was applied to analyze the relationships. The results indicate that Masculinity is significantly related to tourism destination satisfaction for every factor, while the other five cultural dimensions are related to some factors of tourism satisfaction. Surprisingly, tourist satisfaction toward the bar/restaurant factor is significantly correlated with all six cultural dimensions.

Keywords: Cultural dimensions, tourism products, Samui, Thailand.

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2171 A Green Method for Selective Spectrophotometric Determination of Hafnium(IV) with Aqueous Extract of Ficus carica Tree Leaves

Authors: A. Boveiri Monji, H. Yousefnia, M. Haji Hosseini, S. Zolghadri

Abstract:

A clean spectrophotometric method for the determination of hafnium by using a green reagent, acidic extract of Ficus carica tree leaves is developed. In 6-M hydrochloric acid, hafnium reacts with this reagent to form a yellow product. The formed product shows maximum absorbance at 421 nm with a molar absorptivity value of 0.28 × 104 l mol⁻¹ cm⁻¹, and the method was linear in the 2-11 µg ml⁻¹ concentration range. The detection limit value was found to be 0.312 µg ml⁻¹. Except zirconium and iron, the selectivity was good, and most of the ions did not show any significant spectral interference at concentrations up to several hundred times. The proposed method was green, simple, low cost, and selective.

Keywords: Spectrophotometric determination, Ficus carica tree leaves, synthetic reagents, hafnium.

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2170 Electoral Mathematics and Asymmetrical Treatment to Political Parties: The Mexican Case

Authors: Verónica Arredondo, Miguel Martínez-Panero, Teresa Peña, Victoriano Ramírez

Abstract:

The Mexican Chamber of Deputies is composed of 500 representatives: 300 of them elected by relative majority and another 200 ones elected through proportional representation in five electoral clusters (constituencies) with 40 representatives each. In this mixed-member electoral system, the seats distribution of proportional representation is not independent of the election by relative majority, as it attempts to correct representation imbalances produced in single-member districts. This two-fold structure has been maintained in the successive electoral reforms carried out along the last three decades (eight from 1986 to 2014). In all of them, the election process of 200 seats becomes complex: Formulas in the Law are difficult to understand and to be interpreted. This paper analyzes the Mexican electoral system after the electoral reform of 2014, which was applied for the first time in 2015. The research focuses on contradictions and issues of applicability, in particular situations where seats allocation is affected by ambiguity in the law and where asymmetrical treatment of political parties arises. Due to these facts, a proposal of electoral reform will be presented. It is intended to be simpler, clearer, and more enduring than the current system. Furthermore, this model is more suitable for producing electoral outcomes free of contradictions and paradoxes. This approach would allow a fair treatment of political parties and as a result an improved opportunity to exercise democracy.

Keywords: Apportionment paradoxes, biproportional representation, electoral mathematics, electoral reform, Mexican electoral system, proportional representation, political asymmetry.

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2169 Fusion Classifier for Open-Set Face Recognition with Pose Variations

Authors: Gee-Sern Jison Hsu

Abstract:

A fusion classifier composed of two modules, one made by a hidden Markov model (HMM) and the other by a support vector machine (SVM), is proposed to recognize faces with pose variations in open-set recognition settings. The HMM module captures the evolution of facial features across a subject-s face using the subject-s facial images only, without referencing to the faces of others. Because of the captured evolutionary process of facial features, the HMM module retains certain robustness against pose variations, yielding low false rejection rates (FRR) for recognizing faces across poses. This is, however, on the price of poor false acceptance rates (FAR) when recognizing other faces because it is built upon withinclass samples only. The SVM module in the proposed model is developed following a special design able to substantially diminish the FAR and further lower down the FRR. The proposed fusion classifier has been evaluated in performance using the CMU PIE database, and proven effective for open-set face recognition with pose variations. Experiments have also shown that it outperforms the face classifier made by HMM or SVM alone.

Keywords: Face recognition, open-set identification, hidden Markov model, support vector machines.

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2168 Integrating LCA into PDM for Ecodesign

Authors: H. Ostad-Ahmad-Ghorabi, T. Rahmani, D. Gerhard

Abstract:

Product Data Management (PDM) systems for Computer Aided Design (CAD) file management are widely established in design processes. This management system is indispensable for design collaboration or when design task distribution is present. It is thus surprising that engineering design curricula has not paid much attention in the education of PDM systems. This is also the case for eduction of ecodesign and environmental evaluation of products. With the rise of sustainability as a strategic aspect in companies, environmental concerns are becoming a key issue in design. This paper discusses the establishment of a PDM platform to be used among technical and vocational schools in Austria. The PDM system facilitates design collaboration among these schools. Further, it will be discussed how the PDM system has been prepared in order to facilitate environmental evaluation of parts, components and subassemblies of a product. By integrating a Business Intelligence solution, environmental Life Cycle Assessment and communication of results is enabled.

Keywords: CAD, Engineering Design, Design Education, ProductLife Cycle, Sustainability

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2167 Data Structures and Algorithms of Intelligent Web-Based System for Modular Design

Authors: Ivan C. Mustakerov, Daniela I. Borissova

Abstract:

In recent years, new product development became more and more competitive and globalized, and the designing phase is critical for the product success. The concept of modularity can provide the necessary foundation for organizations to design products that can respond rapidly to market needs. The paper describes data structures and algorithms of intelligent Web-based system for modular design taking into account modules compatibility relationship and given design requirements. The system intelligence is realized by developed algorithms for choice of modules reflecting all system restrictions and requirements. The proposed data structure and algorithms are illustrated by case study of personal computer configuration. The applicability of the proposed approach is tested through a prototype of Web-based system.

Keywords: Data structures, algorithms, intelligent web-based system, modular design.

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2166 Body Mass Index for Australian Athletes Participating in Rugby Union, Soccer and Touch Football at the World Masters Games

Authors: Walsh Joe, Climstein Mike, Heazlewood Ian Timothy, Burke Stephen, Kettunen Jyrki, Adams Kent, DeBeliso Mark

Abstract:

Whilst there is growing evidence that activity across the lifespan is beneficial for improved health, there are also many changes involved with the aging process and subsequently the potential for reduced indices of health. Data gathered on a subsample of 535 football code athletes, aged 31-72 yrs ( = 47.4, s = ±7.1), competing at the Sydney World Masters Games (2009) demonstrated a significantly (p < 0.001), reduced classification of obesity using Body Mass Index (BMI) when compared to the general Australian population. This evidence of improved classification in one index of health (BMI < 30) for master athletes (when compared to the general population) implies there are either improved levels of this index of health due to adherence to sport or possibly the reduced BMI is advantageous and contributes to this cohort adhering (or being attracted) to masters sport. Demonstration of this proportionately under-investigated World Masters Games population having improved health over the general population is of particular interest.

Keywords: BMI, masters athlete, rugby union, soccer, touch football.

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2165 Anti-Counterfeiting Solution Employing Mobile RFID Environment

Authors: Juhan Kim, Howon Kim

Abstract:

EPC Class-1 Generation-2 UHF tags, one of Radio frequency identification or RFID tag types, is expected that most companies are planning to use it in the supply chain in the short term and in consumer packaging in the long term due to its inexpensive cost. Because of the very cost, however, its resources are extremely scarce and it is hard to have any valuable security algorithms in it. It causes security vulnerabilities, in particular cloning the tags for counterfeits. In this paper, we propose a product authentication solution for anti-counterfeiting at application level in the supply chain and mobile RFID environment. It aims to become aware of distribution of spurious products with fake RFID tags and to provide a product authentication service to general consumers with mobile RFID devices like mobile phone or PDA which has a mobile RFID reader. We will discuss anti-counterfeiting mechanisms which are required to our proposed solution and address requirements that the mechanisms should have.

Keywords: EPC, RFID, Anti-Counterfeiting, Mobile RFIDenvironment.

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2164 Determining the Criteria and their Importance Level of Calibration Supplier Selection

Authors: Ayse Gecer, Nihal Erginel

Abstract:

Quality control is the crucial step for ISO 9001 Quality System Management Standard for companies. While measuring the quality level of both raw material and semi product/product, the calibration of the measuring device is an essential requirement. Calibration suppliers are in the service sector and therefore the calibration supplier selection is becoming a worthy topic for improving service quality. This study presents the results of a questionnaire about the selection criteria of a calibration supplier. The questionnaire was applied to 103 companies and the results are discussed in this paper. The analysis was made with MINITAB 14.0 statistical programs. “Competence of documentations" and “technical capability" are defined as the prerequisites because of the ISO/IEC17025:2005 standard. Also “warranties and complaint policy", “communication", “service features", “quality" and “performance history" are defined as very important criteria for calibration supplier selection.

Keywords: Calibration, criteria of calibration supplier selection, calibration supplier selection, questionnaire

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2163 Statistics over Lyapunov Exponents for Feature Extraction: Electroencephalographic Changes Detection Case

Authors: Elif Derya UBEYLI, Inan GULER

Abstract:

A new approach based on the consideration that electroencephalogram (EEG) signals are chaotic signals was presented for automated diagnosis of electroencephalographic changes. This consideration was tested successfully using the nonlinear dynamics tools, like the computation of Lyapunov exponents. This paper presented the usage of statistics over the set of the Lyapunov exponents in order to reduce the dimensionality of the extracted feature vectors. Since classification is more accurate when the pattern is simplified through representation by important features, feature extraction and selection play an important role in classifying systems such as neural networks. Multilayer perceptron neural network (MLPNN) architectures were formulated and used as basis for detection of electroencephalographic changes. Three types of EEG signals (EEG signals recorded from healthy volunteers with eyes open, epilepsy patients in the epileptogenic zone during a seizure-free interval, and epilepsy patients during epileptic seizures) were classified. The selected Lyapunov exponents of the EEG signals were used as inputs of the MLPNN trained with Levenberg- Marquardt algorithm. The classification results confirmed that the proposed MLPNN has potential in detecting the electroencephalographic changes.

Keywords: Chaotic signal, Electroencephalogram (EEG) signals, Feature extraction/selection, Lyapunov exponents

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2162 Computer Generated Hologram for SemiFragile Watermarking with Encrypted Images

Authors: G. Schirripa Spagnolo, M. De Santis

Abstract:

The protection of the contents of digital products is referred to as content authentication. In some applications, to be able to authenticate a digital product could be extremely essential. For example, if a digital product is used as a piece of evidence in the court, its integrity could mean life or death of the accused. Generally, the problem of content authentication can be solved using semifragile digital watermarking techniques. Recently many authors have proposed Computer Generated Hologram Watermarking (CGHWatermarking) techniques. Starting from these studies, in this paper a semi-fragile Computer Generated Hologram coding technique is proposed, which is able to detect malicious tampering while tolerating some incidental distortions. The proposed technique uses as watermark an encrypted image, and it is well suitable for digital image authentication.

Keywords: Asymmetric cryptography, Semi-Fragile watermarking, Image authentication, Hologram watermark, Public- Key Cryptography, RSA.

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2161 Non-Burn Treatment of Health Care Risk Waste

Authors: Jefrey Pilusa, Tumisang Seodigeng

Abstract:

This research discusses a South African case study for the potential of utilizing refuse-derived fuel (RDF) obtained from non-burn treatment of health care risk waste (HCRW) as potential feedstock for green energy production. This specific waste stream can be destroyed via non-burn treatment technology involving high-speed mechanical shredding followed by steam or chemical injection to disinfect the final product. The RDF obtained from this process is characterised by a low moisture, low ash, and high calorific value which means it can be potentially used as high-value solid fuel. Due to the raw feed of this RDF being classified as hazardous, the final RDF has been reported to be non-infectious and can blend with other combustible wastes such as rubber and plastic for waste to energy applications. This study evaluated non-burn treatment technology as a possible solution for on-site destruction of HCRW in South African private and public health care centres. Waste generation quantities were estimated based on the number of registered patient beds, theoretical bed occupancy. Time and motion study was conducted to evaluate the logistics viability of on-site treatment. Non-burn treatment technology for HCRW is a promising option for South Africa, and successful implementation of this method depends upon the initial capital investment, operational cost and environmental permitting of such technology; there are other influencing factors such as the size of the waste stream, product off-take price as well as product demand.

Keywords: Autoclave, disposal, fuel, incineration, medical waste.

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2160 Bioactive Component in Milk and Dairy Product

Authors: Bahareh Hajirostamloo

Abstract:

Recent research has shown that milk proteins can yield bioactive peptides with opioid, mineral binding, cytomodulatory, antihypertensive, immunostimulating, antimicrobial and antioxidative activity in the human body. Bioactive peptides are encrypted in milk proteins and are only released by enzymatic hydrolysis in vivo during gastrointestinal digestion, food processing or by microbial enzymes in fermented products. At present significant research is being undertaken on the health effects of bioactive peptides. A variety of naturally formed bioactive peptides have been found in fermented dairy products, such as yoghurt, sour milk and cheese. In particular, antihypertensive peptides have been identified in fermented milks, whey and ripened cheese. Some of these peptides have been commercialized in the form of fermented milks. Bioactive peptides have the potential to be used in the formulation of health-enhancing nutraceuticals, and as potent drugs with well defined pharmacological effects.

Keywords: Milk protein, Bioactive peptides, Health effects, Dairy product.

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2159 Computer Aided Diagnostic System for Detection and Classification of a Brain Tumor through MRI Using Level Set Based Segmentation Technique and ANN Classifier

Authors: Atanu K Samanta, Asim Ali Khan

Abstract:

Due to the acquisition of huge amounts of brain tumor magnetic resonance images (MRI) in clinics, it is very difficult for radiologists to manually interpret and segment these images within a reasonable span of time. Computer-aided diagnosis (CAD) systems can enhance the diagnostic capabilities of radiologists and reduce the time required for accurate diagnosis. An intelligent computer-aided technique for automatic detection of a brain tumor through MRI is presented in this paper. The technique uses the following computational methods; the Level Set for segmentation of a brain tumor from other brain parts, extraction of features from this segmented tumor portion using gray level co-occurrence Matrix (GLCM), and the Artificial Neural Network (ANN) to classify brain tumor images according to their respective types. The entire work is carried out on 50 images having five types of brain tumor. The overall classification accuracy using this method is found to be 98% which is significantly good.

Keywords: Artificial neural network, ANN, brain tumor, computer-aided diagnostic, CAD system, gray-level co-occurrence matrix, GLCM, level set method, tumor segmentation.

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2158 The Effect of Cooperation Teaching Method on Learning of Students in Primary Schools

Authors: Fereshteh Afkari, Davood Bagheri

Abstract:

The effect of teaching method on learning assistance Dunn Review .The study, to compare the effects of collaboration on teaching mathematics learning courses, including writing, science, experimental girl students by other methods of teaching basic first paid and the amount of learning students methods have been trained to cooperate with other students with other traditional methods have been trained to compare. The survey on 100 students in Tehran that using random sampling ¬ cluster of girl students between the first primary selections was performed. Considering the topic of semi-experimental research methods used to practice the necessary information by questionnaire, examination questions by the researcher, in collaboration with teachers and view authority in this field and related courses that teach these must have been collected. Research samples to test and control groups were divided. Experimental group and control group collaboration using traditional methods of mathematics courses, including writing and experimental sciences were trained. Research results using statistical methods T is obtained in two independent groups show that, through training assistance will lead to positive results and student learning in comparison with traditional methods, will increase also led to collaboration methods increase skills to solve math lesson practice, better understanding and increased skill level of students in practical lessons such as science and has been writing.

Keywords: method of teaching, learning, collaboration

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2157 An Experimental Investigation of Factors Affecting Consumers' Reactions to Mobile APP-Based Promotions

Authors: Shu-Lu Hsu, Jeffrey C. F. Tai, Yi-Han Wang

Abstract:

The purpose of this study is to understand how consumers react to a company's promotional offers with mobile applications (APP) as premiums. This paper presents the results of an experimental study where five features of APP were involved: the cost (free/discounted) for earning APP, the relationship between APP and the promoted product, the perceived usefulness, the perceived ease of use, and the perceived playfulness of APP in the context of light foods purchase. The results support that the above features, except perceived ease of use, have substantial influences on consumers' intention to adopt the APP. Among the five features, the cost for earning APP has the most impact on the adopting intention of APP. The study also found a positive influence of adopting intention of APP on the consumer's purchase intention of the promoted product. Thus, APP-based premiums may enhance the consumer's purchase intention of a company's promoted products.

Keywords: Mobile Application, Premium, Sales Promotion, TAM.

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2156 An Approach for Reducing the Computational Complexity of LAMSTAR Intrusion Detection System using Principal Component Analysis

Authors: V. Venkatachalam, S. Selvan

Abstract:

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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2155 An Exploration of the Dimensions of Place-Making: A South African Case Study

Authors: W. J. Strydom, K. Puren

Abstract:

Place-making is viewed here as an empowering process in which people represent, improve and maintain their spatial (natural or built) environment. With the above-mentioned in mind, place-making is multi-dimensional and include a spatial dimension (including visual properties or the end product/plan), a procedural dimension during which (negotiation/discussion of ideas with all relevant stakeholders in terms of end product/plan) and a psychological dimension (inclusion of intrinsic values and meanings related to a place in the end product/plan). These three represent dimensions of place-making. The purpose of this paper is to explore these dimensions of place-making in a case study of a local community in Ikageng, Potchefstroom, North-West Province, South Africa. This case study represents an inclusive process that strives to empower a local community (forcefully relocated due to Apartheid legislation in South Africa). This case study focussed on the inclusion of participants in the decision-making process regarding their daily environment. By means of focus group discussions and a collaborative design workshop, data is generated and ultimately creates a linkage with the theoretical dimensions of place-making. This paper contributes to the field of spatial planning due to the exploration of the dimensions of place-making and the relevancy of this process on spatial planning (especially in a South African setting).

Keywords: Case study, place-making, spatial planning, spatial dimension, procedural dimension, psychological dimension.

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2154 Normalizing Flow to Augmented Posterior: Conditional Density Estimation with Interpretable Dimension Reduction for High Dimensional Data

Authors: Cheng Zeng, George Michailidis, Hitoshi Iyatomi, Leo L Duan

Abstract:

The conditional density characterizes the distribution of a response variable y given other predictor x, and plays a key role in many statistical tasks, including classification and outlier detection. Although there has been abundant work on the problem of Conditional Density Estimation (CDE) for a low-dimensional response in the presence of a high-dimensional predictor, little work has been done for a high-dimensional response such as images. The promising performance of normalizing flow (NF) neural networks in unconditional density estimation acts a motivating starting point. In this work, we extend NF neural networks when external x is present. Specifically, they use the NF to parameterize a one-to-one transform between a high-dimensional y and a latent z that comprises two components [zP , zN]. The zP component is a low-dimensional subvector obtained from the posterior distribution of an elementary predictive model for x, such as logistic/linear regression. The zN component is a high-dimensional independent Gaussian vector, which explains the variations in y not or less related to x. Unlike existing CDE methods, the proposed approach, coined Augmented Posterior CDE (AP-CDE), only requires a simple modification on the common normalizing flow framework, while significantly improving the interpretation of the latent component, since zP represents a supervised dimension reduction. In image analytics applications, AP-CDE shows good separation of x-related variations due to factors such as lighting condition and subject id, from the other random variations. Further, the experiments show that an unconditional NF neural network, based on an unsupervised model of z, such as Gaussian mixture, fails to generate interpretable results.

Keywords: Conditional density estimation, image generation, normalizing flow, supervised dimension reduction.

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2153 Pilot Study on the Impact of VLE on Mathematical Concepts Acquisition within Secondary Education in England

Authors: Aaron A. R. Nwabude

Abstract:

The research investigates the “impact of VLE on mathematical concepts acquisition of the special education needs (SENs) students at KS4 secondary education sector" in England. The overall aim of the study is to establish possible areas of difficulties to approach for above or below knowledge standard requirements for KS4 students in the acquisition and validation of basic mathematical concepts. A teaching period, in which virtual learning environment (Fronter) was used to emphasise different mathematical perception and symbolic representation was carried out and task based survey conducted to 20 special education needs students [14 actually took part]. The result shows that students were able to process information and consider images, objects and numbers within the VLE at early stages of acquisition process. They were also able to carry out perceptual tasks but with limiting process of different quotient, thus they need teacher-s guidance to connect them to symbolic representations and sometimes coach them through. The pilot study further indicates that VLE curriculum approaches for students were minutely aligned with mathematics teaching which does not emphasise the integration of VLE into the existing curriculum and current teaching practice. There was also poor alignment of vision regarding the use of VLE in realisation of the objectives of teaching mathematics by the management. On the part of teacher training, not much was done to develop teacher-s skills in the technical and pedagogical aspects of VLE that is in-use at the school. The classroom observation confirmed teaching practice will find a reliance on VLE as an enhancer of mathematical skills, providing interaction and personalisation of learning to SEN students.

Keywords: VLE, Mathematical Concepts Acquisition, PilotStudy, SENs, KS4, Education, Teacher

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2152 A Multi-Feature Deep Learning Algorithm for Urban Traffic Classification with Limited Labeled Data

Authors: Rohan Putatunda, Aryya Gangopadhyay

Abstract:

Acoustic sensors, if embedded in smart street lights, can help in capturing the activities (car honking, sirens, events, traffic, etc.) in cities. Needless to say, the acoustic data from such scenarios are complex due to multiple audio streams originating from different events, and when decomposed to independent signals, the amount of retrieved data volume is small in quantity which is inadequate to train deep neural networks. So, in this paper, we address the two challenges: a) separating the mixed signals, and b) developing an efficient acoustic classifier under data paucity. So, to address these challenges, we propose an architecture with supervised deep learning, where the initial captured mixed acoustics data are analyzed with Fast Fourier Transformation (FFT), followed by filtering the noise from the signal, and then decomposed to independent signals by fast independent component analysis (Fast ICA). To address the challenge of data paucity, we propose a multi feature-based deep neural network with high performance that is reflected in our experiments when compared to the conventional convolutional neural network (CNN) and multi-layer perceptron (MLP).

Keywords: FFT, ICA, vehicle classification, multi-feature DNN, CNN, MLP.

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2151 Coding of DWT Coefficients using Run-length Coding and Huffman Coding for the Purpose of Color Image Compression

Authors: Varun Setia, Vinod Kumar

Abstract:

In present paper we proposed a simple and effective method to compress an image. Here we found success in size reduction of an image without much compromising with it-s quality. Here we used Haar Wavelet Transform to transform our original image and after quantization and thresholding of DWT coefficients Run length coding and Huffman coding schemes have been used to encode the image. DWT is base for quite populate JPEG 2000 technique.

Keywords: Lossy compression, DWT, quantization, Run length coding, Huffman coding, JPEG2000.

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2150 Factors of Successful Wooden Furniture Design Process

Authors: S. Choodoung, U. Smutkupt

Abstract:

This study systemizes processes and methods in wooden furniture design that contains uniqueness in function and aesthetics. The study was done by research and analysis for designer-s consideration factors that affect function and production. Therefore, the study result indicates that such factors are design process (planning for design, product specifications, concept design, product architecture, industrial design, production), design evaluation as well as wooden furniture design dependent factors i.e. art (art style; furniture history, form), functionality (the strength and durability, area place, using), material (appropriate to function, wood mechanical properties), joints, cost, safety, and social responsibility. Specifically, all aforementioned factors affect good design. Resulting from direct experience gained through user-s usage, the designer must design the wooden furniture systemically and effectively. As a result, this study selected dinning armchair as a case study with all involving factors and all design process stated in this study.

Keywords: Furniture Design, Function Design, Aesthetic, Wooden Furniture.

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2149 A Project-Orientated Training Concept to Prepare Students for Systems Engineering Activities

Authors: Elke Mackensen

Abstract:

Systems Engineering plays a key role during industrial product development of complex technical systems. The need for systems engineers in industry is growing. But there is a gap between the industrial need and the academic education. Normally the academic education is focused on the domain specific design, implementation and testing of technical systems. Necessary systems engineering expertise like knowledge about requirements analysis, product cost estimation, management or social skills are poorly taught. Thus there is the need of new academic concepts for teaching systems engineering skills. This paper presents a project-orientated training concept to prepare students from different technical degree programs for systems engineering activities. The training concept has been initially implemented and applied in the industrial engineering master program of the University of Applied Sciences Offenburg.

Keywords: Educational systems engineering training, requirements analysis, system modelling, SysML.

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2148 Parkinsons Disease Classification using Neural Network and Feature Selection

Authors: Anchana Khemphila, Veera Boonjing

Abstract:

In this study, the Multi-Layer Perceptron (MLP)with Back-Propagation learning algorithm are used to classify to effective diagnosis Parkinsons disease(PD).It-s a challenging problem for medical community.Typically characterized by tremor, PD occurs due to the loss of dopamine in the brains thalamic region that results in involuntary or oscillatory movement in the body. A feature selection algorithm along with biomedical test values to diagnose Parkinson disease.Clinical diagnosis is done mostly by doctor-s expertise and experience.But still cases are reported of wrong diagnosis and treatment. Patients are asked to take number of tests for diagnosis.In many cases,not all the tests contribute towards effective diagnosis of a disease.Our work is to classify the presence of Parkinson disease with reduced number of attributes.Original,22 attributes are involved in classify.We use Information Gain to determine the attributes which reduced the number of attributes which is need to be taken from patients.The Artificial neural networks is used to classify the diagnosis of patients.Twenty-Two attributes are reduced to sixteen attributes.The accuracy is in training data set is 82.051% and in the validation data set is 83.333%.

Keywords: Data mining, classification, Parkinson disease, artificial neural networks, feature selection, information gain.

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2147 Frames about Nanotechnology Agenda in Turkish Media, 2005-2009

Authors: Ebru Belkıs Kamanlıoğlu, Cem Güzeloğlu

Abstract:

As the new industrial revolution advances in the nanotechnology have been followed with interest throughout the world and also in Turkey. Media has an important role in conveying these advances to public, rising public awareness and creating attitudes related to nanotechnology. As well as representing how a subject is treated, media frames determine how public think about this subject. In literature definite frames related to nanoscience and nanotechnology such as process, regulation, conflict and risks were mentioned in studies focusing different countries. So how nanotechnology news is treated by which frames and in which news categories in Turkey as a one of developing countries? In this study examining different variables about nanotechnology that affect public attitudes such as category, frame, story tone, source in Turkish media via framing analysis developed in agenda setting studies was aimed. In the analysis data between 2005 and 2009 obtained from the first five national newspapers with wide circulation in Turkey will be used. In this study the direction of the media about nanotechnology, in which frames nanotechnologic advances brought to agenda were reported as news, and sectoral, legal, economic and social scenes reflected by these frames to public related to nanotechnology in Turkey were planned.

Keywords: Agenda, frames, media, nanotechnology, Turkey.

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2146 The Perception on 21st Century Skills of Nursing Instructors and Nursing Students at Boromarajonani College of Nursing, Chonburi

Authors: Kamolrat Turner, Somporn Rakkwamsuk, Ladda Leungratanamart

Abstract:

The aim of this descriptive study was to determine the perception of 21st century skills among nursing professors and nursing students at Boromarajonani College of Nursing, Chonburi. A total of 38 nursing professors and 75 second year nursing students took part in the study. Data were collected by 21st century skills questionnaires comprised of 63 items. Descriptive statistics were used to describe the findings. The results have shown that the overall mean scores of the perception of nursing professors on 21st century skills were at a high level. The highest mean scores were recorded for computing and ICT literacy, and career and leaning skills. The lowest mean scores were recorded for reading and writing and mathematics. The overall mean scores on perception of nursing students on 21st century skills were at a high level. The highest mean scores were recorded for computer and ICT literacy, for which the highest item mean scores were recorded for competency on computer programs. The lowest mean scores were recorded for the reading, writing, and mathematics components, in which the highest item mean score was reading Thai correctly, and the lowest item mean score was English reading and translate to other correctly. The findings from this study have shown that the perceptions of nursing professors were consistent with those of nursing students. Moreover, any activities aiming to raise capacity on English reading and translate information to others should be taken into the consideration.

Keywords: 21st century skills, perception, nursing instructor, nursing student.

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