Search results for: online extraction

Authors: Jangwon Lee, Joonsung Yoon

Abstract:

This study analyzes on the Social Network Game (SNG), ANIPANG, in order to discover its unique fun elements, so that suggest new methodologies for development of SNGs. ANIPANG is the most popular SNG in the South Korea on 2012. Recently, the game industry is paying close attention to mobile-based SNGs due to the rapid prevalence of smart-phones and social network services. However, SNGs are not online games simply. Although the fun of most online games is the victory through competition with other players or the game system, the fun of SNG is the communication through the collaboration with other players. Thus, features of users and environments of game should be considered for the game industry and for the fun of SNG to users.

Keywords: Social Network Game, Casual user, Fun, ANIPANG.

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Authors: Zullina H. Shaari, Amzairi Amar, Abdul Mutalib Embong, Hezlina Hashim

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University websites are considered as one of the brand primary touch points for multiple stakeholders, but most of them did not have great designs to create favorable impressions. Some of the elements that web designers should carefully consider are the appearance, the content, the functionality, usability and search engine optimization. However, priority should be placed on website simplicity and negative space. In terms of content, previous research suggests that universities should include reputation, learning environment, graduate career prospects, image destination, cultural integration, and virtual tour on their websites. The study examines how top 200 world ranking science and technology-based universities present their brands online and whether the websites capture the content dimensions. Content analysis of the websites revealed that the top ranking universities captured these dimensions at varying degree. Besides, the UK-based university had better priority on website simplicity and negative space compared to the Malaysian-based university.

Keywords: Science and technology programs, top-ranked universities, online brands, university websites.

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Authors: Y. L. Yung, Kong Mun Lo

Abstract:

In this study, solid phase micro-extraction (SPME) was optimized to improve the sensitivity and accuracy in formaldehyde determination for plywood panels. Further work has been carried out to compare the newly developed technique with existing method which reacts formaldehyde collected in desiccators with acetyl acetone reagent (DC-AA). In SPME, formaldehyde was first derivatized with O-(2,3,4,5,6 pentafluorobenzyl)-hydroxylamine hydrochloride (PFBHA) and analysis was then performed by gas chromatography in combination with mass spectrometry (GC-MS). SPME data subjected to various wood species gave satisfactory results, with relative standard deviations (RSDs) obtained in the range of 3.1-10.3%. It was also well correlated with DC values, giving a correlation coefficient, RSQ, of 0.959. The quantitative analysis of formaldehyde by SPME was an alternative in wood industry with great potential

Keywords: Formaldehyde, GCMS, Plywood and SPME

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Authors: Rami N. Khushaba, Adel Al-Jumaily

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The myoelectric signal (MES) is one of the Biosignals utilized in helping humans to control equipments. Recent approaches in MES classification to control prosthetic devices employing pattern recognition techniques revealed two problems, first, the classification performance of the system starts degrading when the number of motion classes to be classified increases, second, in order to solve the first problem, additional complicated methods were utilized which increase the computational cost of a multifunction myoelectric control system. In an effort to solve these problems and to achieve a feasible design for real time implementation with high overall accuracy, this paper presents a new method for feature extraction in MES recognition systems. The method works by extracting features using Wavelet Packet Transform (WPT) applied on the MES from multiple channels, and then employs Fuzzy c-means (FCM) algorithm to generate a measure that judges on features suitability for classification. Finally, Principle Component Analysis (PCA) is utilized to reduce the size of the data before computing the classification accuracy with a multilayer perceptron neural network. The proposed system produces powerful classification results (99% accuracy) by using only a small portion of the original feature set.

Keywords: Biomedical Signal Processing, Data mining andInformation Extraction, Machine Learning, Rehabilitation.

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Authors: Adriana Alexandru, Ovidiu Bica, Eleonora Tudora, Cristina Simona Alecu, Cristina-Adriana Alexandru, Ioan Covalcic

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This paper presents the results of the authors in designing, experimenting, assessing and transferring an innovative approach to energy education in secondary schools, aimed to enhance the quality of learning in terms of didactic curricula and pedagogic methods. The training is online delivered to youngsters via e-Books and portals specially designed for this purpose or by learning by doing via interactive games. An online educational methodology is available teachers.

Keywords: Education, eLearning, Energy Efficiency, InternetMethodology, Renewable Energy Sources.

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Authors: Mrs.K.Kavitha, S.Arivazhagan

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A spatial classification technique incorporating a State of Art Feature Extraction algorithm is proposed in this paper for classifying a heterogeneous classes present in hyper spectral images. The classification accuracy can be improved if and only if both the feature extraction and classifier selection are proper. As the classes in the hyper spectral images are assumed to have different textures, textural classification is entertained. Run Length feature extraction is entailed along with the Principal Components and Independent Components. A Hyperspectral Image of Indiana Site taken by AVIRIS is inducted for the experiment. Among the original 220 bands, a subset of 120 bands is selected. Gray Level Run Length Matrix (GLRLM) is calculated for the selected forty bands. From GLRLMs the Run Length features for individual pixels are calculated. The Principle Components are calculated for other forty bands. Independent Components are calculated for next forty bands. As Principal & Independent Components have the ability to represent the textural content of pixels, they are treated as features. The summation of Run Length features, Principal Components, and Independent Components forms the Combined Features which are used for classification. SVM with Binary Hierarchical Tree is used to classify the hyper spectral image. Results are validated with ground truth and accuracies are calculated.

Keywords: Multi-class, Run Length features, PCA, ICA, classification and Support Vector Machines.

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Authors: Linda Sau-ling LAI

Abstract:

The story of Alibaba demonstrates a credible example of how a small start-up company can eventually make it big in the global economy through the Internet. This case study does not attempt to present Alibaba as a perfect formula; rather, it discusses the strategies carried out by the firm and, in the process, culls out the important lessons that can guide start-ups and aspiring entrepreneurs in the complex world of online trading. Similar to the interesting and exotic Asian cuisine that continuously evolves from the diversity of Asia-s people and their unique culture and personality, Alibaba has successfully transformed itself over the years, adapting to the changes in and demands of online businessto- business (B2B) commerce.

Keywords: Entrepreneurship, electronic commerce, leadership, business model, small and medium enterprises.

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Authors: Nebi Gedik

Abstract:

Heart disease threatens the lives of a great number of people every year around the world. Heart issues lead to many of all deaths; therefore, early diagnosis and treatment are critical. The diagnosis of heart disease is complicated due to several factors affecting health such as high blood pressure, raised cholesterol, an irregular pulse rhythm, and more. Artificial intelligence has the potential to assist in the early detection and treatment of diseases. Improving heart failure prediction is one of the primary goals of research on heart disease risk assessment. This study aims to determine the features that provide the most successful classification prediction in detecting cardiovascular disease. The performances of each feature are compared using the K-Nearest Neighbor machine learning method. The feature that gives the most successful performance has been identified.

Keywords: Cardiovascular disease, feature extraction, supervised learning, k-NN.

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Authors: Yuchih Lin, Chung-Liang Chang, Hong-Yi Cao, Sheng-Hsuan Hsiao

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Cu-mesoporous TiO2 is developed for removal acid odor cooperated with ozone assistance and online- regeneration system with/without UV irradiation (all weather) in study. The results showed that Cu-mesoporous TiO2 present the desirable adsorption efficiency of acid odor without UV irradiation, due to the larger surface area, pore sizeand the additional absorption ability provided by Cu. In the photocatalysis process, the material structure also benefits Cu-mesoporous TiO2 to perform the more outstanding efficiency on degrading acid odor. Cu also postponed the recombination of electron-hole pairs excited from TiO2 to enhance photodegradation ability. Cu-mesoporous TiO2 could gain the conspicuous increase on photocatalysis ability from ozone assistance, but without any benefit on adsorption. In addition, the online regeneration procedure could process the used Cu-mesoporous TiO2 to reinstate the adsorption ability and maintain the photodegradtion performance, depended on scrubbing, desorping acid odor and reducing Cu to metal state.

Keywords: mesoporous material, photocatalyst, adsorption, regeneration usage, photocatalytic ozonation

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Authors: Sudipta Nath, Arindam Dey, Abhijit Chakrabarti

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This paper presents features that characterize power quality disturbances from recorded voltage waveforms using wavelet transform. The discrete wavelet transform has been used to detect and analyze power quality disturbances. The disturbances of interest include sag, swell, outage and transient. A power system network has been simulated by Electromagnetic Transients Program. Voltage waveforms at strategic points have been obtained for analysis, which includes different power quality disturbances. Then wavelet has been chosen to perform feature extraction. The outputs of the feature extraction are the wavelet coefficients representing the power quality disturbance signal. Wavelet coefficients at different levels reveal the time localizing information about the variation of the signal.

Keywords: Power quality, detection of disturbance, wavelet transform, multiresolution signal decomposition.

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Authors: B. Medjahed, M. A. Didi, B. Guezzen

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In the present work, emulsion liquid membrane (ELM) technique was applied for the extraction of cadmium(II) present in aqueous samples. Aliquat 336 (Chloride tri-N-octylmethylammonium) was used as carrier to extract cadmium(II). The main objective of this work is to investigate the influence of various parameters affected the ELM formation and its stability and testing the performance of the prepared ELM on removal of cadmium by using synthetic solution with different concentrations. Experiments were conducted to optimize pH of the feed solution and it was found that cadmium(II) can be extracted at pH 6.5. The influence of the carrier concentration and treat ratio on the extraction process was investigated. The obtained results showed that the optimal values are respectively 3% (Aliquat 336) and a ratio (feed: emulsion) equal to 1:1.

Keywords: Cadmium, carrier, emulsion liquid membrane, surfactant.

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Authors: C. Lodato, S. Lopes

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The image segmentation method described in this paper has been developed as a pre-processing stage to be used in methodologies and tools for video/image indexing and retrieval by content. This method solves the problem of whole objects extraction from background and it produces images of single complete objects from videos or photos. The extracted images are used for calculating the object visual features necessary for both indexing and retrieval processes. The segmentation algorithm is based on the cooperation among an optical flow evaluation method, edge detection and region growing procedures. The optical flow estimator belongs to the class of differential methods. It permits to detect motions ranging from a fraction of a pixel to a few pixels per frame, achieving good results in presence of noise without the need of a filtering pre-processing stage and includes a specialised model for moving object detection. The first task of the presented method exploits the cues from motion analysis for moving areas detection. Objects and background are then refined using respectively edge detection and seeded region growing procedures. All the tasks are iteratively performed until objects and background are completely resolved. The method has been applied to a variety of indoor and outdoor scenes where objects of different type and shape are represented on variously textured background.

Keywords: Image Segmentation, Motion Detection, Object Extraction, Optical Flow

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Authors: Mark Joseph Quinto, Roan Beronilla, Guiller Damian, Eliza Camaso, Ronaldo Alberto

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Forest inventories are essential to assess the composition, structure and distribution of forest vegetation that can be used as baseline information for management decisions. Classical forest inventory is labor intensive and time-consuming and sometimes even dangerous. The use of Light Detection and Ranging (LiDAR) in forest inventory would improve and overcome these restrictions. This study was conducted to determine the possibility of using LiDAR derived data in extracting high accuracy forest biophysical parameters and as a non-destructive method for forest status analysis of San Manual, Pangasinan. Forest resources extraction was carried out using LAS tools, GIS, Envi and .bat scripts with the available LiDAR data. The process includes the generation of derivatives such as Digital Terrain Model (DTM), Canopy Height Model (CHM) and Canopy Cover Model (CCM) in .bat scripts followed by the generation of 17 composite bands to be used in the extraction of forest classification covers using ENVI 4.8 and GIS software. The Diameter in Breast Height (DBH), Above Ground Biomass (AGB) and Carbon Stock (CS) were estimated for each classified forest cover and Tree Count Extraction was carried out using GIS. Subsequently, field validation was conducted for accuracy assessment. Results showed that the forest of San Manuel has 73% Forest Cover, which is relatively much higher as compared to the 10% canopy cover requirement. On the extracted canopy height, 80% of the tree’s height ranges from 12 m to 17 m. CS of the three forest covers based on the AGB were: 20819.59 kg/20x20 m for closed broadleaf, 8609.82 kg/20x20 m for broadleaf plantation and 15545.57 kg/20x20m for open broadleaf. Average tree counts for the tree forest plantation was 413 trees/ha. As such, the forest of San Manuel has high percent forest cover and high CS.

Keywords: Carbon stock, forest inventory, LiDAR, tree count.

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Authors: Daniele Traversaro

Abstract:

Problem: Senior citizens have been facing a challenging reality as a result of strict public health measures designed to protect people from the COVID-19 outbreak. These include the risk of social isolation due to the inability of the elderly to integrate with technology. Never before have Information and Communication Technology (ICT) skills become essential for their everyday life. Although third-age ICT education and lifelong learning are widely supported by universities and governments, there is a lack of literature on which teaching strategy/methodology to adopt in an entirely online ICT course aimed at third-age learners. This contribution aims to present an application of the Think-Pair-Share (TPS) learning method in an ICT third-age virtual classroom with an intergenerational approach to conducting online group labs and review activities. Research Question: Is collaborative learning suitable and effective, in terms of student engagement and learning outcomes, in an online ICT course for the elderly? Methods: In the TPS strategy a problem is posed by the teacher, students have time to think about it individually, and then they work in pairs (or small groups) to solve the problem and share their ideas with the entire class. We performed four experiments in the ICT course of the University of the Third Age of Genova (University of Genova, Italy) on the Microsoft Teams platform. The study cohort consisted of 26 students over the age of 45. Data were collected through online questionnaires. Two have been proposed, one at the end of the first activity and another at the end of the course. They consisted of five and three close-ended questions, respectively. The answers were on a Likert scale (from 1 to 4) except two questions (which asked the number of correct answers given individually and in groups) and the field for free comments/suggestions. Results: Groups achieve better results than individual students (with scores greater than one order of magnitude) and most students found TPS helpful to work in groups and interact with their peers. Insights: From these early results, it appears that TPS is suitable for an online third-age ICT classroom and useful for promoting discussion and active learning. Despite this, our work has several limitations. First of all, the results highlight the need for more data to be able to perform a statistical analysis in order to determine the effectiveness of this methodology in terms of student engagement and learning outcomes as future direction.

Keywords: Collaborative learning, information technology education, lifelong learning, older adult education, think-pair-share.

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Authors: Madina Hamiane, May Hashim Ali

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This paper presents the processing and analysis of ECG signals. The study is based on wavelet transform and uses exclusively the MATLAB environment. This study includes removing Baseline wander and further de-noising through wavelet transform and metrics such as signal-to noise ratio (SNR), Peak signal-to-noise ratio (PSNR) and the mean squared error (MSE) are used to assess the efficiency of the de-noising techniques. Feature extraction is subsequently performed whereby signal features such as heart rate, rise and fall levels are extracted and the QRS complex was detected which helped in classifying the ECG signal. The classification is the last step in the analysis of the ECG signals and it is shown that these are successfully classified as Normal rhythm or Abnormal rhythm.  The final result proved the adequacy of using wavelet transform for the analysis of ECG signals.

Keywords: ECG Signal, QRS detection, thresholding, wavelet decomposition, feature extraction.

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Authors: Ammar Anwar Khan, Nissar R. Wani, Nazar Malik, Abdulrehman Al-Arainy, and Saad Alghuwainem

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Power cables are vulnerable to failure due to aging or defects that occur with the passage of time under continuous operation and loading stresses. PD detection and characterization provide information on the location, nature, form and extent of the degradation. As a result, PD monitoring has become an important part of condition based maintenance (CBM) program among power utilities. Online partial discharge (PD) localization of defect sources in power cable system is possible using the time of flight method. The information regarding the time difference between the main and reflected pulses and cable length can help in locating the partial discharge source along the cable length. However, if the length of the cable is not known and the defect source is located at the extreme ends of the cable or in the middle of the cable, then double ended measurement is required to indicate the location of PD source. Use of multiple sensors can also help in discriminating the cable PD or local/ external PD. This paper presents the experience and results from online partial discharge measurements conducted in the laboratory and the challenges in partial discharge source localization.

Keywords: Power cables, partial discharge localization, HFCT, condition based monitoring.

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Authors: C. Ardil

Abstract:

In this study, a model, together with a software tool that implements it, has been developed to determine the performance ratings of employees in an organization operating in the information technology sector using the indicators obtained from employees' online study data. Weighted Sum (WS) Method and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method based on multidimensional decision making approach were used in the study. WS and TOPSIS methods provide multidimensional decision making (MDDM) methods that allow all dimensions to be evaluated together considering specific weights, allowing employees to objectively evaluate the problem of online performance tracking. The application of WS and TOPSIS mathematical methods, which can combine alternatives with a large number of dimensions and reach simultaneous solution, has been implemented through an online performance tracking software. In the application of WS and TOPSIS methods, objective dimension weights were calculated by using entropy information (EI) and standard deviation (SD) methods from the data obtained by employees' online performance tracking method, decision matrix was formed by using performance scores for each employee, and a single performance score was calculated for each employee. Based on the calculated performance score, employees were given a performance evaluation decision. The results of Pareto set evidence and comparative mathematical analysis validate that employees' performance preference rankings in WS and TOPSIS methods are closely related. This suggests the compatibility, applicability, and validity of the proposed method to the MDDM problems in which a large number of alternative and dimension types are taken into account. With this study, an objective, realistic, feasible and understandable mathematical method, together with a software tool that implements it has been demonstrated. This is considered to be preferable because of the subjectivity, limitations and high cost of the methods traditionally used in the measurement and performance appraisal in the information technology sector.

Keywords: Weighted sum, entropy ınformation, standard deviation, online performance tracking, performance evaluation, performance management, multidimensional decision making.

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Authors: Erick López-Ornelas

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As the world changes more rapidly, the demand for update information for resource management, environment monitoring, planning are increasing exponentially. Integration of Remote Sensing with GIS technology will significantly promote the ability for addressing these concerns. This paper presents an alternative way of update GIS applications using image processing and high resolution images. We show a method of high-resolution image segmentation using graphs and morphological operations, where a preprocessing step (watershed operation) is required. A morphological process is then applied using the opening and closing operations. After this segmentation we can extract significant cartographic elements such as urban areas, streets or green areas. The result of this segmentation and this extraction is then used to update GIS applications. Some examples are shown using aerial photography.

Keywords: GIS, Remote Sensing, image segmentation, feature extraction.

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Authors: Bernd Kiefer, Abraham Gebru Tesfay, Dietrich Klakow

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The motivation of our work is to detect different terrain types traversed by a robot based on acoustic data from the robot-terrain interaction. Different acoustic features and classifiers were investigated, such as Mel-frequency cepstral coefficient and Gamma-tone frequency cepstral coefficient for the feature extraction, and Gaussian mixture model and Feed forward neural network for the classification. We analyze the system’s performance by comparing our proposed techniques with some other features surveyed from distinct related works. We achieve precision and recall values between 87% and 100% per class, and an average accuracy at 95.2%. We also study the effect of varying audio chunk size in the application phase of the models and find only a mild impact on performance.

Keywords: Terrain classification, acoustic features, autonomous robots, feature extraction.

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Authors: Pingping Lin, Xudong Luo

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Natural language often conveys emotions of speakers. Therefore, sentiment analysis on what people say is prevalent in the field of natural language process and has great application value in many practical problems. Thus, to help people understand its application value, in this paper, we survey various applications of sentiment analysis, including the ones in online business and offline business as well as other types of its applications. In particular, we give some application examples in intelligent customer service systems in China. Besides, we compare the applications of sentiment analysis on Twitter, Weibo, Taobao and Facebook, and discuss some challenges. Finally, we point out the challenges faced in the applications of sentiment analysis and the work that is worth being studied in the future.

Keywords: Natural language processing, sentiment analysis, application, online comments.

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Authors: Isaac Kofi Mensah, Jianing Mi, Feng Cheng

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This research paper seeks to investigate the factors determining the continuance usage of online mobile payment applications among WECHAT users in China. Technology Acceptance Model (TAM) and the Diffusion of Innovation (DOI) theory would both be applied as the theoretical foundation for this study. A developed instrument would be administered to the targeted sample of 1000 WECHAT Users in the City of Harbin, China, through an online questionnaire administration platform. Factors such as perceived usefulness, perceived ease of use, perceived service quality, social influence, trust in the internet, internet self-efficacy, relative advantage, compatibility, and complexity would be explored to determine its significant impact on the continuance intention to use mobile payment apps. This study is at the development and implementation stage. The successful completion of this research article would not only provide an insightful understanding of the factors influencing the decision of WECHAT users in China to use mobile payment applications but also enrich the e-commerce adoption literature.

Keywords: Diffusion of innovation (DOI), e-commerce, mobile payment, technology acceptance model (TAM), WECHAT.

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Authors: Seok Hong Min, Tae Kwon Ha

Abstract:

With the increasing interest on Ti alloys, the extraction process of Ti from its typical ore, TiO₂, has long been and will be important issue. As an intermediate product for the production of pigment or titanium metal sponge, tetrachloride (TiCl₄) is produced by fluidized bed using high TiO₂ feedstock. The purity of TiCl₄ after chlorination is subjected to the quality of the titanium feedstock. Since the impurities in the TiCl₄ product are reported to final products, the purification process of the crude TiCl₄ is required. The purification process includes fractional distillation and chemical treatment, which depends on the nature of the impurities present and the required quality of the final product. In this study, thermodynamic analysis on the impurity effect in the chlorination process, which is the first step of extraction of Ti from TiO₂, has been conducted. All thermodynamic calculations were performed using the FactSage thermodynamical software.

Keywords: Rutile, titanium, chlorination process, impurities, thermodynamic calculation, FactSage.

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Authors: Nabil Sultan

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A great deal has been written on Massive Open Online Courses (MOOCs) since 2012 (considered by some as the year of the MOOCs). The emergence of MOOCs caused a great deal of interest amongst academics and technology experts as well as ordinary people. Some of the authors who wrote on MOOCs perceived it as the next big thing that will disrupt education. Other authors saw it as another fad that will go away once it ran its course (as most fads often do). But MOOCs did not turn out to be a fad and it is still around. Most importantly, they evolved into something that is beginning to look like a viable business model. This paper explores this phenomenon within the theoretical frameworks of disruptive innovations and jobs to be done as developed by Clayton Christensen and his colleagues and its implications for the future of higher education (HE).

Keywords: MOOCs, disruptive innovations, higher education, jobs theory.

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Authors: P. Gnanasekar, A. Nagappan, S. Sharavanan, O. Saravanan, D. Vinodkumar, T. Elayabharathi, G. Karthik

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In this paper we present the deep study about the Bio- Medical Images and tag it with some basic extracting features (e.g. color, pixel value etc). The classification is done by using a nearest neighbor classifier with various distance measures as well as the automatic combination of classifier results. This process selects a subset of relevant features from a group of features of the image. It also helps to acquire better understanding about the image by describing which the important features are. The accuracy can be improved by increasing the number of features selected. Various types of classifications were evolved for the medical images like Support Vector Machine (SVM) which is used for classifying the Bacterial types. Ant Colony Optimization method is used for optimal results. It has high approximation capability and much faster convergence, Texture feature extraction method based on Gabor wavelets etc..

Keywords: ACO Ant Colony Optimization, Correlogram, CCM Co-Occurrence Matrix, RTS Rough-Set theory

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Authors: Ahmet Güven, Ö. Özgür Bozkurt, Oya Kalıpsız

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Number of documents being created increases at an increasing pace while most of them being in already known topics and little of them introducing new concepts. This fact has started a new era in information retrieval discipline where the requirements have their own specialties. That is digging into topics and concepts and finding out subtopics or relations between topics. Up to now IR researches were interested in retrieving documents about a general topic or clustering documents under generic subjects. However these conventional approaches can-t go deep into content of documents which makes it difficult for people to reach to right documents they were searching. So we need new ways of mining document sets where the critic point is to know much about the contents of the documents. As a solution we are proposing to enhance LSI, one of the proven IR techniques by supporting its vector space with n-gram forms of words. Positive results we have obtained are shown in two different application area of IR domain; querying a document database, clustering documents in the document database.

Keywords: Document clustering, Information Extraction, Information Retrieval, LSI, n-gram.

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Authors: Hendry Muljadi, Hideaki Takeda, Koichi Ando

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A manufacturing feature can be defined simply as a geometric shape and its manufacturing information to create the shape. In a feature-based process planning system, feature library that consists of pre-defined manufacturing features and the manufacturing information to create the shape of the features, plays an important role in the extraction of manufacturing features with their proper manufacturing information. However, to manage the manufacturing information flexibly, it is important to build a feature library that can be easily modified. In this paper, the implementation of Semantic Wiki for the development of the feature library is proposed.

Keywords: Manufacturing feature, feature library, feature ontology, process planning, Wiki, MediaWiki, Semantic Wiki.

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Authors: Kuan-Chou Chen, Keh-Wen “Carin” Chuang

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This paper demonstrates a model of an e-Learning system based on nowadays learning theory and distant education practice. The relationships in the model are designed to be simple and functional and do not necessarily represent any particular e- Learning environments. It is meant to be a generic e-Learning system model with implications for any distant education course instructional design. It allows online instructors to move away from the discrepancy between the courses and body of knowledge. The interrelationships of four primary sectors that are at the e-Learning system are presented in this paper. This integrated model includes [1] pedagogy, [2] technology, [3] teaching, and [4] learning. There are interactions within each of these sectors depicted by system loop map.

Keywords: e-Learning system, online courses instructionaldesign, integrated model, interrelationships.

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Authors: C. S. Sastry, Saurabh Jain, Ashish Mishra

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Image retrieval is a topic where scientific interest is currently high. The important steps associated with image retrieval system are the extraction of discriminative features and a feasible similarity metric for retrieving the database images that are similar in content with the search image. Gabor filtering is a widely adopted technique for feature extraction from the texture images. The recently proposed sparsity promoting l1-norm minimization technique finds the sparsest solution of an under-determined system of linear equations. In the present paper, the l1-norm minimization technique as a similarity metric is used in image retrieval. It is demonstrated through simulation results that the l1-norm minimization technique provides a promising alternative to existing similarity metrics. In particular, the cases where the l1-norm minimization technique works better than the Euclidean distance metric are singled out.

Keywords: l1-norm minimization, content based retrieval, modified Gabor function.

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Authors: Mario Kubek, Herwig Unger

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Due to the large amount of information in the World Wide Web (WWW, web) and the lengthy and usually linearly ordered result lists of web search engines that do not indicate semantic relationships between their entries, the search for topically similar and related documents can become a tedious task. Especially, the process of formulating queries with proper terms representing specific information needs requires much effort from the user. This problem gets even bigger when the user's knowledge on a subject and its technical terms is not sufficient enough to do so. This article presents the new and interactive search application DocAnalyser that addresses this problem by enabling users to find similar and related web documents based on automatic query formulation and state-ofthe- art search word extraction. Additionally, this tool can be used to track topics across semantically connected web documents.

Keywords: DocAnalyser, interactive web search, search word extraction, query formulation, source topic detection, topic tracking.

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Authors: Mahdi Shaneh, Azizollah Taheri

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The goal of this project is to design a system to recognition voice commands. Most of voice recognition systems contain two main modules as follow “feature extraction" and “feature matching". In this project, MFCC algorithm is used to simulate feature extraction module. Using this algorithm, the cepstral coefficients are calculated on mel frequency scale. VQ (vector quantization) method will be used for reduction of amount of data to decrease computation time. In the feature matching stage Euclidean distance is applied as similarity criterion. Because of high accuracy of used algorithms, the accuracy of this voice command system is high. Using these algorithms, by at least 5 times repetition for each command, in a single training session, and then twice in each testing session zero error rate in recognition of commands is achieved.

Keywords: MFCC, Vector quantization, Vocal tract, Voicecommand.

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