Search results for: Accounting information quality

Authors: Chun-Ying Lee, Kun-Hsien Lee, Bor-Wei Wang

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The process of post-supercritical CO₂ electroplating uses the electrolyte solution after being mixed with supercritical CO₂ and released to atmospheric pressure. It utilizes the microbubbles that form when oversaturated CO₂ in the electrolyte returns to gaseous state, which gives the similar effect of pulsed electroplating. Under atmospheric pressure, the CO₂ bubbles gradually diffuse. Therefore, the introduction of ultrasound and/or other agitation can potentially excite the CO₂ microbubbles to achieve an electroplated surface of even higher quality. In this study, during the electroplating process, three different modes of agitation: magnetic stirrer agitation, ultrasonic agitation and a combined mode (magnetic + ultrasonic) were applied, respectively, in order to obtain an optimal surface morphology and mechanical properties for the electroplated Ni coating. It is found that the combined agitation mode at a current density of 40 A/dm² achieved the smallest grain size, lower surface roughness, and produced an electroplated Ni layer that achieved hardness of 320 HV, much higher when compared with conventional method, which were usually in the range of 160 to 300 HV. However, at the same time, the electroplating with combined agitation developed a higher internal stress of 320 MPa due to the lower current efficiency of the process and finer grain in the coating. Moreover, a new control methodology for tailoring the coating’s mechanical property through its thickness was demonstrated by the timely introduction of ultrasonic agitation during the electroplating process with post supercritical CO₂ mixed electrolyte.

Keywords: Nickel electroplating, micro-bubbles, supercritical carbon dioxide, ultrasonic agitation, magnetic stirring.

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Authors: Clark Van Dam, Gagan Mirchandani

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The Continuously Adaptive Mean-Shift (CamShift) algorithm, incorporating scene depth information is combined with the l1-minimization sparse representation based method to form a hybrid kernel and state space-based tracking algorithm. We take advantage of the increased efficiency of the former with the robustness to occlusion property of the latter. A simple interchange scheme transfers control between algorithms based upon drift and occlusion likelihood. It is quantified by the projection of target candidates onto a depth map of the 2D scene obtained with a low cost stereo vision webcam. Results are improved tracking in terms of drift over each algorithm individually, in a challenging practical outdoor multiple occlusion test case.

Keywords: CamShift, l1-minimization, particle filter, stereo vision, video tracking.

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Authors: S. V. Yendiyarov

Abstract:

Pattern discovery from time series is of fundamental importance. Particularly, when information about the structure of a pattern is not complete, an algorithm to discover specific patterns or shapes automatically from the time series data is necessary. The dynamic time warping is a technique that allows local flexibility in aligning time series. Because of this, it is widely used in many fields such as science, medicine, industry, finance and others. However, a major problem of the dynamic time warping is that it is not able to work with structural changes of a pattern. This problem arises when the structure is influenced by noise, which is a common thing in practice for almost every application. This paper addresses this problem by means of developing a novel technique called adaptive dynamic time warping.

Keywords: Pattern recognition, optimal control, quadratic programming, dynamic programming, dynamic time warping, sintering control.

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Authors: Inas E. Darwish, Alia M. Arab, Tarek A. Azeim, Teshreen M. Zeitoun, Wafaa A. Hewedy, Moemen A. Heiba, Iman S. Emara

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Inflammatory bowel disease (IBD) is a chronic relapsing-remitting condition that afflicts millions of people throughout the world and impairs their daily functions and quality of life. Treatment of IBD depends largely on 5-aminosalicylic acid (5- ASA) and corticosteroids. The present study aimed to clarify the effects of 5-aminosalicylic acid, budesonide and currcumin on 90 male albino rats against trinitrobenzene sulfonic acid (TNB) induced colitis. TNB was injected intrarectally to 50 rats. The other 40 rats served as control groups. Both 5-ASA (in a dose of 120 mg/kg) and budesonide (in a dose of 0.1 mg/kg) were administered daily for one week whereas currcumin was injected intraperitonially (in a dose of 30 mg/kg daily) for 14 days after injection of either TNB in the colitis rats (group B) or saline in control groups (group A). The study included estimation of macroscopic score index, histological examination of H&E stained sections of the colonic tissue, biochemical estimation of myeloperoxidase (MPO), nitric oxide (NO), and caspase-3 levels, in addition to studying the effect of tested drugs on colonic motility. It was found that budesonide and curcumin improved mucosal healing, reduced both NO production and caspase- 3 level. They had the best impact on the disturbed colonic motility in TNBS-model of colitis.

Keywords: Colitis, curcumin, nitric oxide.

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Authors: Alexandra Oliveros, Miguel Sotaquirá

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DNA microarray technology is widely used by geneticists to diagnose or treat diseases through gene expression. This technology is based on the hybridization of a tissue-s DNA sequence into a substrate and the further analysis of the image formed by the thousands of genes in the DNA as green, red or yellow spots. The process of DNA microarray image analysis involves finding the location of the spots and the quantification of the expression level of these. In this paper, a tool to perform DNA microarray image analysis is presented, including a spot addressing method based on the image projections, the spot segmentation through contour based segmentation and the extraction of relevant information due to gene expression.

Keywords: Contour segmentation, DNA microarrays, edge detection, image processing, segmentation, spot addressing.

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Authors: Miroslav H. Hristov, Velizar A. Vassilev, Georgi K. Dukendjiev

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Due to the constant development of measurement systems and the aim for computerization, unavoidable improvements are made for the main disadvantages of air gauges. With the appearance of the air-electronic measuring devices, some of their disadvantages are solved. The output electrical signal allows them to be included in the modern systems for measuring information processing and process management. Producer efforts are aimed at reducing the influence of supply pressure and measurement system setup errors. Increased accuracy requirements and preventive error measures are due to the main uses of air electronic systems - measurement of geometric dimensions in the automotive industry where they are applied as modules in measuring systems to measure geometric parameters, form, orientation and location of the elements.

Keywords: Air-electronic, geometrical parameters, improvement, measurement systems.

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Authors: Lin Cheng, Zijiang Yang

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Program synthesis is the task to automatically generate programs based on user specification. In this paper, we present a framework that synthesizes programs from flow charts that serve as accurate and intuitive specification. In order doing so, we propose a deep neural network called GRCNN that recognizes graph structure from its image. GRCNN is trained end-to-end, which can predict edge and node information of the flow chart simultaneously. Experiments show that the accuracy rate to synthesize a program is 66.4%, and the accuracy rates to recognize edge and node are 94.1% and 67.9%, respectively. On average, it takes about 60 milliseconds to synthesize a program.

Keywords: program synthesis, flow chart, specification, graph recognition, CNN.

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Authors: Arshaluys Mushkambaryan

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The purpose of this study is to explore how the emotions at the moment of conflict escalation are expressed nonverbally and how it can be detected by the parties involved in the conflicting situation. The study consists of two parts, in the first part it starts with the definition of "conflict" and "nonverbal communication". Further it includes the analysis of emotions and types of emotions, which may bring to the conflict escalation. Four types of emotions and emotion constructs are analyzed, particularly fear, anger, guilt and frustration. The second part of the study analyses the general role of nonverbal behavior in interaction and communication, which information it may give during communication to the person, who sends or receives those signals. The study finishes with the analysis of the nonverbal expression of analyzed emotions and on how it can be used during interaction.

Keywords: Conflict Escalation, Emotions, Nonverbal communication,

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Authors: N. Sefiani, C. Fikri Benbrahim, A. Boumane, K. Reklaoui

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Nowadays, the reflection on competence management is the basic for new competitive strategies. It is considered as the core of the problems of the global supply chain. It interact a variety of actors: information, physical and activities flows, etc. Even though competence management is seen as the key factor for any business success, the existing approaches demonstrate the deficiencies and limitations of the competence concept. This research has two objectives: The first is to make a contribution by focusing on the development of a competence approach, based on continuous improvement. It allows the enterprise to spot key competencies, mobilize them in order to serve its strategic objectives and to develop future competencies. The second is to propose a method to evaluate the Level of Collective Competence. The approach was confirmed through an application carried out at an automotive company.

Keywords: Competencies, approach, continuous improvement, collective competence level, performance indicator.

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Authors: Subrahmanyam Kodukula, Nurbiya Maimaiti

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There have been many variations of technologies that helped educators in teaching & learning. From the past research it is evident that Information Technology significantly increases student participation and interactivity in the classrooms. This research started with a aim to find whether adoption of Wi-Fi environment by Malaysian Higher Educational Institutions (HEI) can benefit students and staff equally. The study was carried out in HEI-s of Klang Valley, Malaysia and the data is gathered through paper based surveys. A sample size of 237 units were randomly selected from 5 higher educational institutions in the Klang Valley using the Stratified Random sampling method and from the analysis of the data, it was found that the implementation of wireless technologies in HEIs have created lot of opportunities and also challenges.

Keywords: Wired Technologies, Wireless Classroom, HEI, Dense User Environment.

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Authors: Antonis Sideris, Elias Chlis Kalogeropoulos, Konstantia Moirogiorgou

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The present study proposes a methodology for the efficient daily management of fleet vehicles and construction machinery. The application covers the area of remote monitoring of heavy-duty vehicles operation parameters, where specific sensor data are stored and examined in order to provide information about the vehicle’s health. The vehicle diagnostics allow the user to inspect whether maintenance tasks need to be performed before a fault occurs. A properly designed machine learning model is proposed for the detection of two different types of faults through classification. Cross validation is used and the accuracy of the trained model is checked with the confusion matrix.

Keywords: Fault detection, feature selection, machine learning, predictive maintenance.

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Authors: M. Anandhavalli Gauthaman

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DNA microarrays allow the measurement of expression levels for a large number of genes, perhaps all genes of an organism, within a number of different experimental samples. It is very much important to extract biologically meaningful information from this huge amount of expression data to know the current state of the cell because most cellular processes are regulated by changes in gene expression. Association rule mining techniques are helpful to find association relationship between genes. Numerous association rule mining algorithms have been developed to analyze and associate this huge amount of gene expression data. This paper focuses on some of the popular association rule mining algorithms developed to analyze gene expression data.

Keywords: DNA microarray, gene expression, association rule mining.

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Authors: N. Sathitanon, S. Pullteap

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An optical fiber Fabry-Perot interferometer (FFPI) is proposed and demonstrated for dynamic measurements in a mechanical vibrating target. A polishing metal with a low reflectance value adhered to a mechanical vibrator was excited via a function generator at various excitation frequencies. Output interference fringes were generated by modulating the reference and sensing signal at the output arm. A fringe-counting technique was used for interpreting the displacement information on the dedicated computer. The fiber interferometer has been found the capability of the displacement measurements of 1.28 μm – 96.01 μm. A commercial displacement sensor was employed as a reference sensor for investigating the measurement errors from the fiber sensor. A maximum percentage measurement error of approximately 1.59 % was obtained.

Keywords: Optical fiber sensors, dynamic displacement, fringe counting, reference displacement sensor.

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Authors: Lely A. Luengas, Pedro R. Vizcaya, Giovanni Sánchez

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In this paper, a methodology is presented to obtain the Static Alignment Model for any transtibial amputee person. The proposed methodology starts from experimental data collected on the Hospital Militar Central, Bogotá, Colombia. The effects of transtibial prosthesis malalignment on amputees were measured in terms of joint angles, center of pressure (COP) and weight distribution. Some statistical tools are used to obtain the model parameters. Mathematical predictive models of prosthetic alignment were created. The proposed models are validated in amputees and finding promising results for the prosthesis Static Alignment. Static alignment process is unique to each subject; nevertheless the proposed methodology can be used in each transtibial amputee.

Keywords: Information theory, prediction model, prosthetic alignment, transtibial prosthesis.

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Authors: I. L. Ahmad, M. Mohamed, N. A. Ab. Ghani

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This paper presents the work of signal discrimination specifically for Electrocardiogram (ECG) waveform. ECG signal is comprised of P, QRS, and T waves in each normal heart beat to describe the pattern of heart rhythms corresponds to a specific individual. Further medical diagnosis could be done to determine any heart related disease using ECG information. The emphasis on QRS Complex classification is further discussed to illustrate the importance of it. Pan-Tompkins Algorithm, a widely known technique has been adapted to realize the QRS Complex classification process. There are eight steps involved namely sampling, normalization, low pass filter, high pass filter (build a band pass filter), derivation, squaring, averaging and lastly is the QRS detection. The simulation results obtained is represented in a Graphical User Interface (GUI) developed using MATLAB.

Keywords: ECG, Pan Tompkins Algorithm, QRS Complex, Simulation

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Authors: D. H. Kim, Y. H. Kim, T. Kim

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A new method identifies coupled fluid-structure system with a reduced set of state variables is presented. Assuming that the structural model is known a priori either from an analysis or a test and using linear transformations between structural and aeroelastic states, it is possible to deduce aerodynamic information from sampled time histories of the aeroelastic system. More specifically given a finite set of structural modes the method extracts generalized aerodynamic force matrix corresponding to these mode shapes. Once the aerodynamic forces are known, an aeroelastic reduced-order model can be constructed in discrete-time, state-space format by coupling the structural model and the aerodynamic system. The resulting reduced-order model is suitable for constant Mach, varying density analysis.

Keywords: ROM (Reduced-Order Model), aero elasticity, AGARD 445.6 wing.

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Authors: Dong Hoon Lim

Abstract:

A series of microarray experiments produces observations of differential expression for thousands of genes across multiple conditions. Principal component analysis(PCA) has been widely used in multivariate data analysis to reduce the dimensionality of the data in order to simplify subsequent analysis and allow for summarization of the data in a parsimonious manner. PCA, which can be implemented via a singular value decomposition(SVD), is useful for analysis of microarray data. For application of PCA using SVD we use the DNA microarray data for the small round blue cell tumors(SRBCT) of childhood by Khan et al.(2001). To decide the number of components which account for sufficient amount of information we draw scree plot. Biplot, a graphic display associated with PCA, reveals important features that exhibit relationship between variables and also the relationship of variables with observations.

Keywords: Principal component analysis, singular value decomposition, microarray data, SRBCT

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Authors: Cherdvong Saengsupavanich

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Dredging activities inevitably cause sediment dispersion. In certain locations, where there are important ecological areas such as mangroves or coral reefs, carefully planning the dredging can significantly reduce negative impacts. This article utilizes the dredging at Phuket port, Thailand, as a case study to demonstrate how computer simulations can be helpful to protect existing coral reefs. A software package named MIKE21 was applied. Necessary information required by the simulations was gathered. After calibrating and verifying the model, various dredging scenario were simulated to predict spoil movement. The simulation results were used as guidance to setting up an environmental measure. Finally, the recommendation to dredge during flood tide with silt curtains installed was made.

Keywords: Coastal simulation, Dredging, Environmentalprotection, Port. Coastal engineering, Thailand

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Authors: Najwa Alsayed Omar

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With the increasing popularity of the Internet, online reading has become an essential source for EFL readers. Using strategies to comprehend information on online reading texts play a crucial role in students’ academic success. Metacognitive reading strategies are effective factors that enhance EFL learners reading comprehension. This study aimed at exploring the use of online metacognitive reading strategies by postgraduate Libyan EFL students. Quantitative data was collected using the Survey of Online Reading Strategies (OSORS). The findings revealed that the participants were moderate users of metacognitive online reading strategies. Problem solving strategies were the most frequently reported used strategies, while support reading strategies were the least. The five most and least frequently reported strategies were identified. Based on the findings, some future research recommendations were presented.

Keywords: Metacognitive strategies, Online reading, Online reading strategies, Postgraduate students.

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Authors: Daniel I. Morariu, Lucian N. Vintan, Volker Tresp

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Text categorization is the problem of classifying text documents into a set of predefined classes. After a preprocessing step, the documents are typically represented as large sparse vectors. When training classifiers on large collections of documents, both the time and memory restrictions can be quite prohibitive. This justifies the application of feature selection methods to reduce the dimensionality of the document-representation vector. In this paper, we present three feature selection methods: Information Gain, Support Vector Machine feature selection called (SVM_FS) and Genetic Algorithm with SVM (called GA_SVM). We show that the best results were obtained with GA_SVM method for a relatively small dimension of the feature vector.

Keywords: Feature Selection, Learning with Kernels, Support Vector Machine, Genetic Algorithm, and Classification.

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Authors: Eiad Yafi, M. A. Alam, Ranjit Biswas

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Knowledge Discovery of Databases (KDD) is the process of extracting previously unknown but useful and significant information from large massive volume of databases. Data Mining is a stage in the entire process of KDD which applies an algorithm to extract interesting patterns. Usually, such algorithms generate huge volume of patterns. These patterns have to be evaluated by using interestingness measures to reflect the user requirements. Interestingness is defined in different ways, (i) Objective measures (ii) Subjective measures. Objective measures such as support and confidence extract meaningful patterns based on the structure of the patterns, while subjective measures such as unexpectedness and novelty reflect the user perspective. In this report, we try to brief the more widely spread and successful subjective measures and propose a new subjective measure of interestingness, i.e. shocking.

Keywords: Shocking rules (SHR).

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Authors: A. Bouzid, R. Chadli

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Fritillaria oranensis (Liliaceae) was described in 1874 by pomel from Algeria. Plant samples have been collected from the mount of Tessala (Sidi-Bel-Abbes). The morphological features of various organs of the plant are described in detail. In the morphological part of the study, features of various organs of the plants such as stem and leaf were determined and illustrated. Ecological studies provide information about the physical and chemical structure of soil types in Tessala Mountain. The aim of this original investigation is to put forth ecological and anatomical features of these species for the first time, but at the same time given detailed account of the morphological characteristics of the stem and leaf of Fritillaria oranensis.

Keywords: Anatomy, ecology, Liliaceae, morphology, Fritillaria oranensis Pomel.

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Authors: Daniel Morariu, Lucian N. Vintan, Volker Tresp

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Text categorization is the problem of classifying text documents into a set of predefined classes. After a preprocessing step, the documents are typically represented as large sparse vectors. When training classifiers on large collections of documents, both the time and memory restrictions can be quite prohibitive. This justifies the application of feature selection methods to reduce the dimensionality of the document-representation vector. In this paper, three feature selection methods are evaluated: Random Selection, Information Gain (IG) and Support Vector Machine feature selection (called SVM_FS). We show that the best results were obtained with SVM_FS method for a relatively small dimension of the feature vector. Also we present a novel method to better correlate SVM kernel-s parameters (Polynomial or Gaussian kernel).

Keywords: Feature Selection, Learning with Kernels, SupportVector Machine, and Classification.

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Authors: Susmita Ghosh, Bhaskar Bhowmick

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Market is an important factor for start-ups to look into during decision-making in product development and related areas. Emerging country markets are more uncertain in terms of information availability and institutional supports. The literature review of market uncertainty reveals the need for identifying factors representing the market uncertainty. This paper identifies factors for market uncertainty using Exploratory Factor Analysis (EFA) and confirmed the number of factor retention using an alternative factor retention criterion ‘Parallel Analysis’. 500 entrepreneurs, engaged in start-ups from all over India participated in the study. This paper concludes with the factor structure of ‘market uncertainty’ having dimensions of uncertainty in industry orientation, uncertainty in customer orientation and uncertainty in marketing orientation.

Keywords: Uncertainty, market, orientation, competitor, demand.

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Authors: Ardhendu Behera, Denis Lalanne, Rolf Ingold

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This paper proposes a method, combining color and layout features, for identifying documents captured from low-resolution 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. Our identification method first uses the color information in the documents 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 of the search space.

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

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Authors: M. Bastanfard, B. Jalaeian, S. Jafari

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Sonogram images of normal and lymphocyte thyroid tissues have considerable overlap which makes it difficult to interpret and distinguish. Classification from sonogram images of thyroid gland is tackled in semiautomatic way. While making manual diagnosis from images, some relevant information need not to be recognized by human visual system. Quantitative image analysis could be helpful to manual diagnostic process so far done by physician. Two classes are considered: normal tissue and chronic lymphocyte thyroid (Hashimoto's Thyroid). Data structure is analyzed using K-nearest-neighbors classification. This paper is mentioned that unlike the wavelet sub bands' energy, histograms and Haralick features are not appropriate to distinguish between normal tissue and Hashimoto's thyroid.

Keywords: Sonogram, thyroid, Haralick feature, wavelet.

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Authors: Mana Tarjoman, Shaghayegh Zarei

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Using efficient classification methods is necessary for automatic fingerprint recognition system. This paper introduces a new structural approach to fingerprint classification by using the directional image of fingerprints to increase the number of subclasses. In this method, the directional image of fingerprints is segmented into regions consisting of pixels with the same direction. Afterwards the relational graph to the segmented image is constructed and according to it, the super graph including prominent information of this graph is formed. Ultimately we apply a matching technique to compare obtained graph with the model graphs in order to classify fingerprints by using cost function. Increasing the number of subclasses with acceptable accuracy in classification and faster processing in fingerprints recognition, makes this system superior.

Keywords: Classification, Directional image, Fingerprint, Graph, Super graph.

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Authors: Amon Lasomboon

Abstract:

Since the world printing industry has to confront globalization with a constant change, the Thai printing industry, as a small but increasingly significant part of the world printing industry, cannot inevitably escape but has to encounter with the similar change and also the need to revamp its production processes, designs and technology to make them more appealing to both international and domestic market. The essential question is what is the Thai competitive edge in the printing industry in changing environment? This research is aimed to study the Thai level of competitive edge in terms of marketing, technology, environment friendly, and the level of satisfaction of the process of using printing machines. To access the extent to which is the trends in competitiveness of Thai printing industry, both quantitative and qualitative study were conducted. The quantitative analysis was restricted to 100 respondents. The qualitative analysis was restricted to a focus group of 10 individuals from various backgrounds in the Thai printing industry. The findings from the quantitative analysis revealed that the overall mean scores are 4.53, 4.10, and 3.50 for the competitiveness of marketing, the competitiveness of technology, and the competitiveness of being environment friendly respectively. However, the level of satisfaction for the process of using machines has a mean score only 3.20. The findings from the qualitative analysis have revealed that target customers have increasingly reordered due to their contentment in both low prices and the acceptable quality of the products. Moreover, the Thai printing industry has a tendency to convert to ambient green technology which is friendly to the environment. The Thai printing industry is choosing to produce or substitute with products that are less damaging to the environment. It is also found that the Thai printing industry has been transformed into a very competitive industry which bargaining power rests on consumers who have a variety of choices.

Keywords: Competitiveness, Printing Industry

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Authors: Y. Boutiche, N. Ramou, M. Ben Gharsallah

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This paper is devoted to present and discuss a model that allows a local segmentation by using statistical information of a given image. It is based on Chan-Vese model, curve evolution, partial differential equations and binary level sets method. The proposed model uses the piecewise constant approximation of Chan-Vese model to compute Signed Pressure Force (SPF) function, this one attracts the curve to the true object(s)-s boundaries. The implemented model is used to extract weld defects from weld radiographic images in the aim to calculate the perimeter and surfaces of those weld defects; encouraged resultants are obtained on synthetic and real radiographic images.

Keywords: Active contour, Chan-Vese Model, local segmentation, weld radiographic images.

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Authors: Ayşin Sev, Görkem Aslan

Abstract:

Sustainable tall buildings that provide comfortable, healthy and efficient indoor environments are clearly desirable as the densification of living and working space for the world’s increasing population proceeds. For environmental concerns, these buildings must also be energy efficient. One component of these tasks is the provision of indoor air quality and thermal comfort, which can be enhanced with natural ventilation by the supply of fresh air. Working spaces can only be naturally ventilated with connections to the outdoors utilizing operable windows, double facades, ventilation stacks, balconies, patios, terraces and skygardens. Large amounts of fresh air can be provided to the indoor spaces without mechanical air-conditioning systems, which are widely employed in contemporary tall buildings. This paper tends to present the concept of natural ventilation for sustainable tall office buildings in order to achieve healthy and comfortable working spaces, as well as energy efficient environments. Initially the historical evolution of ventilation strategies for tall buildings is presented, beginning with natural ventilation and continuing with the introduction of mechanical airconditioning systems. Then the emergence of natural ventilation due to the health and environmental concerns in tall buildings is handled, and the strategies for implementing this strategy are revealed. In the next section, a number of case studies that utilize this strategy are investigated. Finally, how tall office buildings can benefit from this strategy is discussed.

Keywords: Tall office building, natural ventilation, energy efficiency, double-skin façade, stack ventilation, air conditioning.

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