Search results for: general variable neighborhood search algorithm.

Authors: Hamed.Vezvaei, Sepideh.Ordibeheshti, Mehdi.Ardjmand

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Gasoline Octane Number is the standard measure of the anti-knock properties of a motor in platforming processes, that is one of the important unit operations for oil refineries and can be determined with online measurement or use CFR (Cooperative Fuel Research) engines. Online measurements of the Octane number can be done using direct octane number analyzers, that it is too expensive, so we have to find feasible analyzer, like ANFIS estimators. ANFIS is the systems that neural network incorporated in fuzzy systems, using data automatically by learning algorithms of NNs. ANFIS constructs an input-output mapping based both on human knowledge and on generated input-output data pairs. In this research, 31 industrial data sets are used (21 data for training and the rest of the data used for generalization). Results show that, according to this simulation, hybrid method training algorithm in ANFIS has good agreements between industrial data and simulated results.

Keywords: Adaptive Neuro-Fuzzy Inference Systems, GasolineOctane Number, Soft-sensor, Catalytic Naphtha Reforming

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Authors: Sulaiman A. Alateyah, Richard M Crowder, Gary B Wills

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This paper discusses E-government, in particular the challenges that face its development and widespread adoption in Saudi Arabia. E-government can be defined based on an existing set of requirements. E-government has been implemented for a considerable time in developed countries. However, E-government services still face many challenges in their implementation and general adoption in Saudi Arabia. In addition, the literature review and the discussion identify the influential factors, such as quality of service, diffusion of innovation, computer and information literacy, culture, lack of awareness, technical infrastructure, website design, and security, that affect the citizens’ intention to adopt E-government services in Saudi Arabia. Consequently, these factors have been integrated in a new model that would influence citizen to adopt E- government services. Therefore, this research presents an integrated model for ascertaining the intention to adopt E-government services and thereby aiding governments in accessing what is required to increase adoption.

Keywords: Adoption, citizens’ intention, E-government, G2C, influential factors.

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Authors: A. Bumbová, M. Čáslavský, F. Božek, J. Dvořák

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The paper deals with the analysis of hazards and sensitivity of potential resource of emergency water supply of population in a selected region of the Czech Republic. The procedure of identification and analysis of hazards and sensitivity is carried out on the basis of a unique methodology of classifying the drinking water resources earmarked for emergency supply of population. The hazard identification is based on a general register of hazards for individual parts of hydrological structure and the elements of technological equipment. It is followed by a semi-quantitative point indexation for the activation of each identified hazard, i.e. fires of anthropogenic origin, flood and the increased radioactive background accompanied by the leak of radon. Point indexation of sensitivity has been carried out at the same time. The analysis is the basis for a risk assessment of potential resource of emergency supply of population and the subsequent classification of such resource within the system of crisis planning.

Keywords: Hazard identification, sensitivity, semi-quantitative assessment, emergency water supply, crisis situation, ground water.

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Authors: Fakhruddin Esa, Yusri Yusof

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The confirmatory of Total Quality Management (TQM) implementation is most vital in quality management. This paper focuses on employees' perceptions towards TQM implementation in a local automotive company supplier. The objectives of this study are first and foremost to determine the perception of TQM implementation among the staff, and secondly to ascertain the correlation between the variables, and lastly to identify the relative influence of the 10 TQM variables on the cost of poor quality (COPQ). The TQM implementation is perceived to be moderate. All correlation is found to be significant and five variables having positively moderate to high correlation. Out of 10 variables, quality system improvement, reward and recognition and customer focus influence the perceived COPQ. This study extended a discussion on these three variables contribution to TQM in general and the human resource development in the organization. A significant recommendation to lowering costs of internal error, such as trouble shooting and scraps are also discussed. Certain components of further research that would add value to this study have also been suggested and perhaps could be implemented at policy-level initiatives.

Keywords: Cost of poor quality, correlation, total quality management, variables.

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Authors: Andre Slonopas, Warren Thompson, Zona Kostic

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Obfuscation is one of the most useful tools to prevent network compromise. Previous research focused on the obfuscation of the network communications between external-facing edge devices. This work proposes the use of two edge devices, external and internal facing, which communicates via private IPv4 addresses in a software-defined pseudo-random IP hopping. This methodology does not require additional IP addresses and/or resources to implement. Statistical analyses demonstrate that the hopping surface must be at least 1e3 IP addresses in size with a broad standard deviation to minimize the possibility of coincidence of monitored and communication IPs. The probability of breaking the hopping algorithm requires a collection of at least 1e6 samples, which for large hopping surfaces will take years to collect. The probability of dropped packets is controlled via memory buffers and the frequency of hops and can be reduced to levels acceptable for video streaming. This methodology provides an impenetrable layer of security ideal for information and supervisory control and data acquisition systems.

Keywords: Moving Target Defense, cybersecurity, network security, hopping randomization, software defined network, network security theory.

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Authors: Kuo-Cheng Liu

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

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

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Authors: Mahdieh Khalilinezhad, Silvana Dellepiane, Gianni Vernazza

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The aim of this work is to build a model based on tissue characterization that is able to discriminate pathological and non-pathological regions from three-phasic CT images. With our research and based on a feature selection in different phases, we are trying to design a neural network system with an optimal neuron number in a hidden layer. Our approach consists of three steps: feature selection, feature reduction, and classification. For each region of interest (ROI), 6 distinct sets of texture features are extracted such as: first order histogram parameters, absolute gradient, run-length matrix, co-occurrence matrix, autoregressive model, and wavelet, for a total of 270 texture features. When analyzing more phases, we show that the injection of liquid cause changes to the high relevant features in each region. Our results demonstrate that for detecting HCC tumor phase 3 is the best one in most of the features that we apply to the classification algorithm. The percentage of detection between pathology and healthy classes, according to our method, relates to first order histogram parameters with accuracy of 85% in phase 1, 95% in phase 2, and 95% in phase 3.

Keywords: Feature selection, Multi-phasic liver images, Neural network, Texture analysis.

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Authors: Gizem Kodak

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The Strait of Çanakkale (Dardanelles), together with the Strait of Istanbul and the Sea of Marmara, form the Turkish Straits System. In other words, the Strait of Çanakkale is the southern gate of the system that connects the Black Sea countries with the other countries of the world. Due to the heavy maritime traffic, it is important to scientifically examine the accident characteristics in the region. In particular, the results indicated by the descriptive statistics are of critical importance in order to strengthen the safety of navigation. At this point, exploratory data analysis offers strategic outputs in terms of defining the problem and knowing the strengths and weaknesses against possible accident risk. The study aims to determine the accident characteristics in the Strait of Çanakkale with temporal and spatial analysis of historical data, using Exploratory Data Analysis (EDA) as the research method. The study's results will reveal the general characteristics of maritime accidents in the region and form the infrastructure for future studies. Therefore, the text provides a clear description of the research goals and methodology, and the study's contributions are well-defined.

Keywords: Maritime Accidents, EDA, Strait of Çanakkale, navigational safety.

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Authors: Joseph Maloba Makokha

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Idea generation is an important part of the design process, and many strategies to support this stage have been developed. As artificial intelligence (AI) gains adoption in many domains, we need to understand its role, if any, in the design process. This paper introduces the concept of a “Disruptive Interjector”, an AI system that frequently interjects with suggestions based on observing what a user does. The concept emanates from a study that was conducted with pairs of humans on one hand, and human-AI pairs on the other collaborating on idea generation by sketching. Results from a study show that participants who collaborated with, and took cues from the AI sketch suggestions generated more ideas; and also had more ideas ranked by experts as “creative” compared to two humans working together on the same tasks. It is notable that while researchers from diverse fields of engineering, psychology, art and others have explored conditions and environments that enhance people's creativity - and have provided insights on creativity in general - there still exists a gap on the role that AI can play on creativity. We attempt to narrow this gap.

Keywords: Artificial intelligence, design collaboration, creativity, human-machine collaboration, machine learning.

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Authors: Sameru Sharma, Sanjay Sharma, Derick Engles

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Multiple-input multiple-output (MIMO) systems are widely in use to improve quality, reliability of wireless transmission and increase the spectral efficiency. However in MIMO systems, multiple copies of data are received after experiencing various channel effects. The limitations on account of complexity due to number of antennas in case of conventional decoding techniques have been looked into. Accordingly we propose a modified sphere decoder (MSD-1) algorithm with lower complexity and give rise to system with high spectral efficiency. With the aim to increase signal diversity we apply rotated quadrature amplitude modulation (QAM) constellation in multi dimensional space. Finally, we propose a new architecture involving space time trellis code (STTC) concatenated with space time block code (STBC) using MSD-1 at the receiver for improving system performance. The system gains have been verified with channel state information (CSI) errors.

Keywords: Channel State Information , Diversity, Multi-Antenna, Rotated Constellation, Space Time Codes.

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Authors: Nader Gharibnavaz, Hossein Yazdi

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If organizations like Mellat Bank want to identify its customer market completely to reach its specified goals, it can segment the market to offer the product package to the right segment. Our objective is to offer a segmentation model for Iran banking market in Mellat bank view. The methodology of this project is combined by “segmentation on the basis of four part-quality variables" and “segmentation on the basis of different in means". Required data are gathered from E-Systems and researcher personal observation. Finally, the research offers the organization that at first step form a four dimensional matrix with 756 segments using four variables named value-based, behavioral, activity style, and activity level, and at the second step calculate the means of profit for every cell of matrix in two distinguished work level (levels α1:normal condition and α2: high pressure condition) and compare the segments by checking two conditions that are 1- homogeneity every segment with its sub segment and 2- heterogeneity with other segments, and so it can do the necessary segmentation process. After all, the last offer (more explained by an operational example and feedback algorithm) is to test and update the model because of dynamic environment, technology, and banking system.

Keywords: market segmentation model, banking system, Mellat bank

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Authors: H. Paredes Gutiérrez, S. T. Pérez-Merchancano

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Motivated by recent experimental and theoretical developments, we investigate the influence of embedded quantum dot (EQD) of different geometries (lens, ring and pyramidal) in a double barrier heterostructure (DBH). We work with a general theory of quantum transport that accounts the tight-binding model for the spin dependent resonant tunneling in a semiconductor nanostructure, and Rashba spin orbital to study the spin orbit coupling. In this context, we use the second quantization theory for Rashba effect and the standard Green functions method. We calculate the current density as a function of the voltage without and in the presence of quantum dots. In the second case, we considered the size and shape of the quantum dot, and in the two cases, we worked considering the spin polarization affected by external electric fields. We found that the EQD generates significant changes in current when we consider different morphologies of EQD, as those described above. The first thing shown is that the current decreases significantly, such as the geometry of EQD is changed, prevailing the geometrical confinement. Likewise, we see that the current density decreases when the voltage is increased, showing that the quantum system studied here is more efficient when the morphology of the quantum dot changes.

Keywords: Quantum semiconductors, nanostructures, quantum dots, spin polarization.

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Authors: Jorge Martinez-Garcia, Ingrid Stelzner, Joerg Stelzner, Damian Gwerder, Philipp Schuetz

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Tree-ring analysis is an important part of the quality assessment and the dating of (archaeological) wood samples. It provides quantitative data about the whole anatomical ring structure, which can be used, for example, to measure the impact of the fluctuating environment on the tree growth, for the dendrochronological analysis of archaeological wooden artefacts and to estimate the wood mechanical properties. Despite advances in computer vision and edge recognition algorithms, detection and counting of annual rings are still limited to 2D datasets and performed in most cases manually, which is a time consuming, tedious task and depends strongly on the operator’s experience. This work presents an image processing approach to detect the whole 3D tree-ring structure directly from X-ray computed tomography imaging data. The approach relies on a modified Canny edge detection algorithm, which captures fully connected tree-ring edges throughout the measured image stack and is validated on X-ray computed tomography data taken from six wood species.

Keywords: Ring recognition, edge detection, X-ray computed tomography, dendrochronology.

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Authors: Cathy Smilan

Abstract:

In our current political climate of assessment and accountability initiatives we are failing to prepare our children for a participatory role in the creative economy. The field of education is increasingly falling prey to didactic methodologies which train a nation of competent test takers, foregoing the opportunity to educate students to find problems and develop multiple solutions. No where is this more evident than in the area of art education. Due to a myriad of issues including budgetary shortfalls, time constraints and a general misconception that anyone who enjoys the arts is capable of teaching the arts, our students are not developing the skills they require to become fully literate in critical thinking and creative processing. Although art integrated curriculum is increasingly being viewed as a reform strategy for motivating students by offering alternative presentation of concepts and representation of knowledge acquisition, misinformed administrators are often excluding the art teacher from the integration equation. The paper to follow addresses the problem of the need for divergent thinking and conceptualization in our schools. Furthermore, this paper explores the role of education, and specifically, art education in the development of a creatively literate citizenry.

Keywords: Art Integration, Creativity, Artist/Teacher/Leaders, Educating for a Creative Economy.

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Authors: S. Montenegro, W. Hu

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The objective of this paper is to develop a neural network-based residual generator to detect the fault in the actuators for a specific communication satellite in its attitude control system (ACS). First, a dynamic multilayer perceptron network with dynamic neurons is used, those neurons correspond a second order linear Infinite Impulse Response (IIR) filter and a nonlinear activation function with adjustable parameters. Second, the parameters from the network are adjusted to minimize a performance index specified by the output estimated error, with the given input-output data collected from the specific ACS. Then, the proposed dynamic neural network is trained and applied for detecting the faults injected to the wheel, which is the main actuator in the normal mode for the communication satellite. Then the performance and capabilities of the proposed network were tested and compared with a conventional model-based observer residual, showing the differences between these two methods, and indicating the benefit of the proposed algorithm to know the real status of the momentum wheel. Finally, the application of the methods in a satellite ground station is discussed.

Keywords: Satellite, Attitude Control, Momentum Wheel, Neural Network, Fault Detection.

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Authors: Wichian Sriprachan, Chutikarn Sriviboon

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The objectives of this research were to study the management of local towns and to develop a better model of town management according to the Philosophy of Sufficiency Economy. This study utilized qualitative research, field research, as well as documentary research at the same time. A total of 10 local towns or Tambons of Supanburi province, Thailand were selected for an in-depth interview. The findings revealed that the model of local town management according to Philosophy of Sufficient Economy was in a level of “good” and the model of management has the five basic guidelines: 1) ability to manage budget information and keep it up-to-date, 2) ability to decision making according to democracy rules, 3) ability to use check and balance system, 4) ability to control, follow, and evaluation, and 5) ability to allow the general public to participate. In addition, the findings also revealed that the human resource management according to Philosophy of Sufficient Economy includes obeying laws, using proper knowledge, and having integrity in five areas: plan, recruit, select, train, and maintain human resources.  

Keywords: Management, Local Town (Tambon), Principles of Sufficiency Economy.

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Authors: Seung Hwan Park, Cheng-Sool Park, Jun Seok Kim, Youngji Yoo, Daewoong An, Jun-Geol Baek

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Depending on the big data analysis becomes important, yield prediction using data from the semiconductor process is essential. In general, yield prediction and analysis of the causes of the failure are closely related. The purpose of this study is to analyze pattern affects the final test results using a die map based clustering. Many researches have been conducted using die data from the semiconductor test process. However, analysis has limitation as the test data is less directly related to the final test results. Therefore, this study proposes a framework for analysis through clustering using more detailed data than existing die data. This study consists of three phases. In the first phase, die map is created through fail bit data in each sub-area of die. In the second phase, clustering using map data is performed. And the third stage is to find patterns that affect final test result. Finally, the proposed three steps are applied to actual industrial data and experimental results showed the potential field application.

Keywords: Die-Map Clustering, Feature Extraction, Pattern Recognition, Semiconductor Manufacturing Process.

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Authors: Ramaswamy Palaniappan

Abstract:

In this paper, several improvements are proposed to previous work of automated classification of alcoholics and nonalcoholics. In the previous paper, multiplayer-perceptron neural network classifying energy of gamma band Visual Evoked Potential (VEP) signals gave the best classification performance using 800 VEP signals from 10 alcoholics and 10 non-alcoholics. Here, the dataset is extended to include 3560 VEP signals from 102 subjects: 62 alcoholics and 40 non-alcoholics. Three modifications are introduced to improve the classification performance: i) increasing the gamma band spectral range by increasing the pass-band width of the used filter ii) the use of Multiple Signal Classification algorithm to obtain the power of the dominant frequency in gamma band VEP signals as features and iii) the use of the simple but effective knearest neighbour classifier. To validate that these two modifications do give improved performance, a 10-fold cross validation classification (CVC) scheme is used. Repeat experiments of the previously used methodology for the extended dataset are performed here and improvement from 94.49% to 98.71% in maximum averaged CVC accuracy is obtained using the modifications. This latest results show that VEP based classification of alcoholics is worth exploring further for system development.

Keywords: Alcoholic, Multilayer-perceptron, Nearest neighbour, Gamma band, MUSIC, Visual evoked potential.

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Authors: S. Piramu Kailasam

Abstract:

This study is expected to compress true color image with compression algorithms in color spaces to provide high compression rates. The need of high compression ratio is to improve storage space. Alternative aim is to rank compression algorithms in a suitable color space. The dataset is sequence of true color images with size 128 x 128. HAAR Wavelet is one of the famous wavelet transforms, has great potential and maintains image quality of color images. HAAR wavelet Transform using Set Partitioning in Hierarchical Trees (SPIHT) algorithm with different color spaces framework is applied to compress sequence of images with angles. Embedded Zerotrees of Wavelet (EZW) is a powerful standard method to sequence data. Hence the proposed compression frame work of HAAR wavelet, xyz color space, morphological gradient and applied image with EZW compression, obtained improvement to other methods, in terms of Compression Ratio, Mean Square Error, Peak Signal Noise Ratio and Bits Per Pixel quality measures.

Keywords: Color Spaces, HAAR Wavelet, Morphological Gradient, Embedded Zerotrees Wavelet Compression.

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Authors: Jasmine Adela Mutang, Rosnah Ismail, Chua Bee Seok, Ferlis Bahari, Lailawati Madlan, Walton Wider, Rickless Das

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Public participation in recycling domestic waste is still very low in Malaysia. Only 10.5% of solid waste was recycled up to now which is far below than of in developed countries. Therefore, understanding public motivations towards recycling domestic waste are important to improve current recycling rate. Thus, this study attempts to identify what are the possible motivations and hindrances for the public to recycle. Open-ended questions format were administered to 484 people in Kota Kinabalu, Sabah, Malaysia. Two specific questions we asked to explore their general determinants and barriers in practicing recycling: “What motivates you to recycle?” and “What are the barriers you encountered in doing recycling activities?” Thematic was conducted on the open-ended questions in which themes were created with the raw comments. It was found that the underlying recycling motivations are (i) awareness’ towards the environment; (ii) benefits to the society and individual; and (iii) social influence. Non participations are influence by (i) attitudes; (ii) commitment; (iii) facilities; (iv) knowledge; (v) inconvenience; and (vi) enforcement.

Keywords: Recycling motivation, recycling barrier, sustainable, household waste.

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Authors: Alexander Y. Vaninsky

Abstract:

This paper presents a simplified version of Data Envelopment Analysis (DEA) - a conventional approach to evaluating the performance and ranking of competitive objects characterized by two groups of factors acting in opposite directions: inputs and outputs. DEA with a Perfect Object (DEA PO) augments the group of actual objects with a virtual Perfect Object - the one having greatest outputs and smallest inputs. It allows for obtaining an explicit analytical solution and making a step to an absolute efficiency. This paper develops this approach further and introduces a DEA model with Partially Perfect Objects. DEA PPO consecutively eliminates the smallest relative inputs or greatest relative outputs, and applies DEA PO to the reduced collections of indicators. The partial efficiency scores are combined to get the weighted efficiency score. The computational scheme remains simple, like that of DEA PO, but the advantage of the DEA PPO is taking into account all of the inputs and outputs for each actual object. Firm evaluation is considered as an example.

Keywords: Data Envelopment Analysis, Perfect object, Partially perfect object, Partial efficiency, Explicit solution, Simplified algorithm.

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Authors: Khosro Mohammadi

Abstract:

The grain quality of chickpea in Iran is low and instable, which may be attributed to the evolution of cultivars with a narrow genetic base making them vulnerable to biotic stresses. Four chickpea varieties from diverse geographic origins were chosen and arranged in a randomized complete block design. Mesorhizobium sp. cicer strain SW7 was added to all the chickpea seeds. Chickpea seeds were planted on October 9, 2013. Each genotype was sown 5 m in length, with 35 cm inter-row spacing, in 3 rows. Weeds were removed manually in all plots. Results showed that Analysis of variance on the studied traits showed significant differences among genotypes for N, P, K and Fe contents of chickpea, but there is not a significant difference among Ca, Zn and Mg continents of chickpea. The experimental coefficient of variation (CV) varied from 7.3 to 15.8. In general, the CV value lower than 20% is considered to be good, indicating the accuracy of conducted experiments. The highest grain N was observed in Hashem and Jam cultivars. The highest grain P was observed in Jam cultivar. Phosphorus content (mg/100g) ranged from 142.3 to 302.3 with a mean value of 221.3. The negative correlation (-0.126) was observed between the N and P of chickpea cultivars. The highest K and Fe contents were observed in Jam cultivar.

Keywords: Cultivar, genotype, nitrogen, nutrient, yield.

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Authors: Nikhil, Bestamin Özkaya, Ari Visa, Chiu-Yue Lin, Jaakko A. Puhakka, Olli Yli-Harja

Abstract:

The performance of a sucrose-based H2 production in a completely stirred tank reactor (CSTR) was modeled by neural network back-propagation (BP) algorithm. The H2 production was monitored over a period of 450 days at 35±1 ºC. The proposed model predicts H2 production rates based on hydraulic retention time (HRT), recycle ratio, sucrose concentration and degradation, biomass concentrations, pH, alkalinity, oxidation-reduction potential (ORP), acids and alcohols concentrations. Artificial neural networks (ANNs) have an ability to capture non-linear information very efficiently. In this study, a predictive controller was proposed for management and operation of large scale H2-fermenting systems. The relevant control strategies can be activated by this method. BP based ANNs modeling results was very successful and an excellent match was obtained between the measured and the predicted rates. The efficient H2 production and system control can be provided by predictive control method combined with the robust BP based ANN modeling tool.

Keywords: Back-propagation, biohydrogen, bioprocessmodeling, neural networks.

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Authors: Jonghyun Park, Toan Nguyen Dinh, Gueesang Lee

Abstract:

In this paper, we present a novel approach to accurately detect text regions including shop name in signboard images with complex background for mobile system applications. The proposed method is based on the combination of text detection using edge profile and region segmentation using fuzzy c-means method. In the first step, we perform an elaborate canny edge operator to extract all possible object edges. Then, edge profile analysis with vertical and horizontal direction is performed on these edge pixels to detect potential text region existing shop name in a signboard. The edge profile and geometrical characteristics of each object contour are carefully examined to construct candidate text regions and classify the main text region from background. Finally, the fuzzy c-means algorithm is performed to segment and detected binarize text region. Experimental results show that our proposed method is robust in text detection with respect to different character size and color and can provide reliable text binarization result.

Keywords: Text detection, edge profile, signboard image, fuzzy clustering.

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Authors: Pelin Yildiz

Abstract:

The aim of this study is to emphasize the opportunities in space design under the aspect of HCI as performance areas. HCI is a multidisciplinary approach that could be identified in many different areas. The aesthetical reflections of HCI by virtual reality in space design are the high-tech solutions of the new innovations as computational facilities by artistic features. The method of this paper is to identify the subject in 3 main parts. In the first part a general approach and definition of interactivity on the basis of space design; in the second part the concept of multimedia interactive theater by some chosen samples from the world and interactive design aspects; in the third part the samples from Turkey will be identified by stage designing principles. In the results it could be declared that the multimedia database is the virtual approach of theatre stage designing regarding interactive means by computational facilities according to aesthetical aspects. HCI is mostly identified in theatre stages as computational intelligence under the affect of interactivity.

Keywords: Computational intelligence, interactive space, multimedia theatre, virtual reality.

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Authors: Parvinder Singh Sandhu, Dalwinder Singh Salaria, Hardeep Singh

Abstract:

Software Reusability is primary attribute of software quality. There are metrics for identifying the quality of reusable components but the function that makes use of these metrics to find reusability of software components is still not clear. These metrics if identified in the design phase or even in the coding phase can help us to reduce the rework by improving quality of reuse of the component and hence improve the productivity due to probabilistic increase in the reuse level. In this paper, we have devised the framework of metrics that uses McCabe-s Cyclometric Complexity Measure for Complexity measurement, Regularity Metric, Halstead Software Science Indicator for Volume indication, Reuse Frequency metric and Coupling Metric values of the software component as input attributes and calculated reusability of the software component. Here, comparative analysis of the fuzzy, Neuro-fuzzy and Fuzzy-GA approaches is performed to evaluate the reusability of software components and Fuzzy-GA results outperform the other used approaches. The developed reusability model has produced high precision results as expected by the human experts.

Keywords: Software Reusability, Software Metrics, Neural Networks, Genetic Algorithm, Fuzzy Logic.

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Authors: Yingjie Zhang, Ming Li, Ying Zhang, Jing Zhang, Zuolei Hu

Abstract:

In the actual start-up process of DC motors, the DC drive system often faces a conflict between energy consumption and acceleration performance. To resolve the conflict, this paper proposes a comprehensive performance index that energy consumption index is added on the basis of classical control performance index in the DC motor starting process. Taking the comprehensive performance index as the cost function, particle swarm optimization algorithm is designed to optimize the comprehensive performance. Then it conducts simulations on the optimization of the comprehensive performance of the DC motor on condition that the weight coefficient of the energy consumption index should be properly designed. The simulation results show that as the weight of energy consumption increased, the energy efficiency was significantly improved at the expense of a slight sacrifice of fastness indicators with the comprehensive performance index method. The energy efficiency was increased from 63.18% to 68.48% and the response time reduced from 0.2875s to 0.1736s simultaneously compared with traditional proportion integrals differential controller in energy saving.

Keywords: Comprehensive performance index, energy consumption, acceleration performance, particle swarm optimal control.

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Authors: Kamil R. Aida-zade, Jamaladdin Z. Hasanov

Abstract:

An approach is offered for more precise definition of base lines- borders in handwritten cursive text and general problems of handwritten text segmentation have also been analyzed. An offered method tries to solve problems arose in handwritten recognition with specific slant or in other words, where the letters of the words are not on the same vertical line. As an informative features, some recognition systems use ascending and descending parts of the letters, found after the word-s baseline detection. In such recognition systems, problems in baseline detection, impacts the quality of the recognition and decreases the rate of the recognition. Despite other methods, here borders are found by small pieces containing segmentation elements and defined as a set of linear functions. In this method, separate borders for top and bottom border lines are found. At the end of the paper, as a result, azerbaijani cursive handwritten texts written in Latin alphabet by different authors has been analyzed.

Keywords: Azeri, azerbaijani, latin, segmentation, cursive, HWR, handwritten, recognition, baseline, ascender, descender, symbols.

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Authors: Wen-Hsiang Lai, Nguyen Quang Vinh

Abstract:

In order to explore the relationship of promotion activities, destination attribute and destination image of Vietnam and find possible solutions, this study uses decision system analysis (DSA) method to develop flowcharts based on three rounds of expert interviews. The interviews were conducted with the experts who were confirmed to directly participate or influence on the decision making that drives the promotion of Vietnam tourism process. This study identifies three models and describes specific decisions on promotion activities, destination attributes and destination images. This study finally derives a general model for promoting the Tourism Industrial Service Network (TISN) in Vietnam. This study finds that the coordination with all sectors and industries of tourism to facilitate favorable condition and improving destination attributes in linking with the efficient promotion activities is highly recommended in order to make visitors satisfied and improve the destination image.

Keywords: Destination attributes, Destination image, Decision system analysis, Tourism promotion

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Authors: M. A. Hasan, M. R. Islam, R. A. Tarefder

Abstract:

This study investigates how the site specific traffic data differs from the Mechanistic Empirical Pavement Design Software default values. Two Weigh-in-Motion (WIM) stations were installed in Interstate-40 (I-40) and Interstate-25 (I-25) to developed site specific data. A computer program named WIM Data Analysis Software (WIMDAS) was developed using Microsoft C-Sharp (.Net) for quality checking and processing of raw WIM data. A complete year data from November 2013 to October 2014 was analyzed using the developed WIM Data Analysis Program. After that, the vehicle class distribution, directional distribution, lane distribution, monthly adjustment factor, hourly distribution, axle load spectra, average number of axle per vehicle, axle spacing, lateral wander distribution, and wheelbase distribution were calculated. Then a comparative study was done between measured data and AASHTOWare default values. It was found that the measured general traffic inputs for I-40 and I-25 significantly differ from the default values.

Keywords: AASHTOWare, Traffic, Weigh-in-Motion, Axle load Distribution.

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