Search results for: Human Silhouette Extraction

Authors: Al-Amin Bhuiyan, Chang Hong Liu

Abstract:

This paper addresses the development of an intelligent vision system for human-robot interaction. The two novel contributions of this paper are 1) Detection of human faces and 2) Localizing the eye. The method is based on visual attributes of human skin colors and geometrical analysis of face skeleton. This paper introduces a spatial domain filtering method named ?Fuzzily skewed filter' which incorporates Fuzzy rules for deciding the gray level of pixels in the image in their neighborhoods and takes advantages of both the median and averaging filters. The effectiveness of the method has been justified over implementing the eye tracking commands to an entertainment robot, named ''AIBO''.

Keywords: Fuzzily skewed filter, human-robot interface, rmscontrast, skin color segmentation.

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Authors: Gheida J. Shahrour, Martin J. Russell

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The 3D body movement signals captured during human-human conversation include clues not only to the content of people’s communication but also to their culture and personality. This paper is concerned with automatic extraction of this information from body movement signals. For the purpose of this research, we collected a novel corpus from 27 subjects, arranged them into groups according to their culture. We arranged each group into pairs and each pair communicated with each other about different topics. A state-of-art recognition system is applied to the problems of person, culture, and topic recognition. We borrowed modeling, classification, and normalization techniques from speech recognition. We used Gaussian Mixture Modeling (GMM) as the main technique for building our three systems, obtaining 77.78%, 55.47%, and 39.06% from the person, culture, and topic recognition systems respectively. In addition, we combined the above GMM systems with Support Vector Machines (SVM) to obtain 85.42%, 62.50%, and 40.63% accuracy for person, culture, and topic recognition respectively. Although direct comparison among these three recognition systems is difficult, it seems that our person recognition system performs best for both GMM and GMM-SVM, suggesting that intersubject differences (i.e. subject’s personality traits) are a major source of variation. When removing these traits from culture and topic recognition systems using the Nuisance Attribute Projection (NAP) and the Intersession Variability Compensation (ISVC) techniques, we obtained 73.44% and 46.09% accuracy from culture and topic recognition systems respectively.

Keywords: Person Recognition, Topic Recognition, Culture Recognition, 3D Body Movement Signals, Variability Compensation.

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Authors: Y. L. Yung, Kong Mun Lo

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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: B. Arend, P. Sunnen, P. Caire

Abstract:

In a single case study, we show how a conversation analysis (CA) approach can shed light onto the sequential unfolding of human-robot interaction. Relying on video data, we are able to show that CA allows us to investigate the respective turn-taking systems of humans and a NAO robot in their dialogical dynamics, thus pointing out relevant differences. Our fine grained video analysis points out occurring breakdowns and their overcoming, when humans and a NAO-robot engage in a multimodally uttered multi-party communication during a sports guessing game. Our findings suggest that interdisciplinary work opens up the opportunity to gain new insights into the challenging issues of human robot communication in order to provide resources for developing mechanisms that enable complex human-robot interaction (HRI).

Keywords: Human-robot interaction, conversation analysis, dialogism, museum, breakdown.

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Authors: Rami N. Khushaba, Adel Al-Jumaily

Abstract:

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: Mrs.K.Kavitha, S.Arivazhagan

Abstract:

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: 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: 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: Belkacem Chikhaoui, Helene Pigot, Mathieu Beaudoin, Guillaume Pratte, Philippe Bellefeuille, Fernando Laudares

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The way music is interpreted by the human brain is a very interesting topic, but also an intricate one. Although this domain has been studied for over a century, many gray areas remain in the understanding of music. Recent advances have enabled us to perform accurate measurements of the time taken by the human brain to interpret and assimilate a sound. Cognitive computing provides tools and development environments that facilitate human cognition simulation. ACT-R is a cognitive architecture which offers an environment for implementing human cognitive tasks. This project combines our understanding of the music interpretation by a human listener and the ACT-R cognitive architecture to build SINGER, a computerized simulation for listening and recalling songs. The results are similar to human experimental data. Simulation results also show how it is easier to remember short melodies than long melodies which require more trials to be recalled correctly.

Keywords: Computational model, cognitive modeling, simulation, learning, song, music.

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Authors: Ivana Tadić, Željana Aljinović Barać, Nikolina Plazonić

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Living today in turbulent business environment forces companies to distinguish from each other, securing sustainable competitive growth and competitive advantage. The best possible solution is to invest (effort and financial resources) within companies’ different practices of human resource management (HRM), more specifically in employees’ knowledge, skills and abilities. Applying this approach companies will create enviable level of human capital securing its economic growth. Employees become human capital for their employers at the moment when they contribute with their own knowledge and abilities in creating material and non-material value of the company. The main aim of this research is to explore the relations between human capital investments and business excellence of Croatian companies. Furthermore, the differences in the level of human capital investments with regard to several companies’ characteristics (e.g. size of the company, ownership and type of the industry) are investigated.

Keywords:

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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

Abstract:

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

Abstract:

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: Meng Wang, Qi-rui Han

Abstract:

Because of excellent properties, people has paid more attention to SPIHI algorithm, which is based on the traditional wavelet transformation theory, but it also has its shortcomings. Combined the progress in the present wavelet domain and the human's visual characteristics, we propose an improved algorithm based on human visual characteristics of SPIHT in the base of analysis of SPIHI algorithm. The experiment indicated that the coding speed and quality has been enhanced well compared to the original SPIHT algorithm, moreover improved the quality of the transmission cut off.

Keywords: Lifted wavelet transform, SPIHT, Human Visual Characteristics.

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Authors: Fatma Didin Sonmez, Pinar Sener

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Technology transfer by international trade and foreign direct investment is the most important positive outcome of open economy. It is widely accepted that new technology and knowledge have an important role in enhancing economic growth. Human capital is the other important factor assisting economic growth. In this study, the role of human capital in the growth process is examined in a view of new endogenous growth theory emphasizing on the technology transfer resulting from international trade. Using the panel data of 10 developed and 10 developing countries, impact of human capital and openness on the rate of economic growth of different countries is analysed. Evidence suggests the view that human capital and openness contribute to the economic growth in both developing and developed countries, but with different rates.

Keywords: economic growth, human capital, openness, technology

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Authors: Norah A. Elgibreen

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Cultural stories are political. They register cultural phenomena and their relations with the world and society in term of their existence, function, characteristics by using different context. This paper will provide a new way of rethinking which will help us to rethink the relationship between fiction and politics. It discusses the theme of human rights and it shows the relevance between art and politics by studying the civil society through a literary framework. Reasons to establish a relationship between fiction and politics are the relevant themes and universal issues among the two disciplines. Both disciplines are sets of views and ideas formulated by the human mind to explain political or cultural phenomenon. Other reasons are the complexity and depth of the author-s vision, and the need to explain the violations of human rights in a more active structure which can relate to emotional and social existence.

Keywords: dignity, human rights, politics and literature, Untouchable.

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Authors: Madina Hamiane, May Hashim Ali

Abstract:

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: Byounghyun Kim, Youngjoon Han, Hernsoo Hahn

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The purpose of this study is to find natural gait of biped robot such as human being by analyzing the COG (Center Of Gravity) trajectory of human being's gait. It is discovered that human beings gait naturally maintain the stability and use the minimum energy. This paper intends to find the natural gait pattern of biped robot using the minimum energy as well as maintaining the stability by analyzing the human's gait pattern that is measured from gait image on the sagittal plane and COG trajectory on the frontal plane. It is not possible to apply the torques of human's articulation to those of biped robot's because they have different degrees of freedom. Nonetheless, human and 5-link biped robots are similar in kinematics. For this, we generate gait pattern of the 5-link biped robot by using the GA algorithm of adaptation gait pattern which utilize the human's ZMP (Zero Moment Point) and torque of all articulation that are measured from human's gait pattern. The algorithm proposed creates biped robot's fluent gait pattern as that of human being's and to minimize energy consumption because the gait pattern of the 5-link biped robot model is modeled after consideration about the torque of human's each articulation on the sagittal plane and ZMP trajectory on the frontal plane. This paper demonstrate that the algorithm proposed is superior by evaluating 2 kinds of the 5-link biped robot applied to each gait patterns generated both in the general way using inverse kinematics and in the special way in which by considering visuality and efficiency.

Keywords: 5-link biped robot, gait pattern, COG (Center OfGravity), ZMP (Zero Moment Point).

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Authors: Md. Zahangir Alom, Mei-Lan Piao, Md. Shariful Islam, Nam Kim, Jae-Hyeung Park

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The evaluation and measurement of human body dimensions are achieved by physical anthropometry. This research was conducted in view of the importance of anthropometric indices of the face in forensic medicine, surgery, and medical imaging. The main goal of this research is to optimization of facial feature point by establishing a mathematical relationship among facial features and used optimize feature points for age classification. Since selected facial feature points are located to the area of mouth, nose, eyes and eyebrow on facial images, all desire facial feature points are extracted accurately. According this proposes method; sixteen Euclidean distances are calculated from the eighteen selected facial feature points vertically as well as horizontally. The mathematical relationships among horizontal and vertical distances are established. Moreover, it is also discovered that distances of the facial feature follows a constant ratio due to age progression. The distances between the specified features points increase with respect the age progression of a human from his or her childhood but the ratio of the distances does not change (d = 1 .618 ) . Finally, according to the proposed mathematical relationship four independent feature distances related to eight feature points are selected from sixteen distances and eighteen feature point-s respectively. These four feature distances are used for classification of age using Support Vector Machine (SVM)-Sequential Minimal Optimization (SMO) algorithm and shown around 96 % accuracy. Experiment result shows the proposed system is effective and accurate for age classification.

Keywords: 3D Face Model, Face Anthropometrics, Facial Features Extraction, Feature distances, SVM-SMO

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Authors: B. Singh, A. Singh, R. C. Yadav

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Utmost care of human related issues are essentially required for sustainable growth of micro, small and medium enterprises (MSMEs) of India, as these MSMEs are contributing enormously to socio-economic development of country. In this research, aspects related to human factors and functioning of MSMEs of India were studied. The investigation, based on a survey of 84 MSMEs of India cited that the enterprises are mostly employing unskilled labor whose wages are less with poor training. In spite of reported minor accidents, attention towards safety is poorly paid. To meet-out the production target, MSMEs generally employ over-time and payment towards this overtime is sometimes missing. Hence, honest and humanitarian attention for better human resources is needed to improve the performance and competitiveness of MSMEs of India.

Keywords: Human factors, Small and medium enterprises, Working culture.

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Authors: Qais M. Yousef, Yasmeen A. Alshaer

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Over the last few years, the amount of data available on the globe has been increased rapidly. This came up with the emergence of recent concepts, such as the big data and the Internet of Things, which have furnished a suitable solution for the availability of data all over the world. However, managing this massive amount of data remains a challenge due to their large verity of types and distribution. Therefore, locating the required file particularly from the first trial turned to be a not easy task, due to the large similarities of names for different files distributed on the web. Consequently, the accuracy and speed of search have been negatively affected. This work presents a method using Electroencephalography signals to locate the files based on their contents. Giving the concept of natural mind waves processing, this work analyses the mind wave signals of different people, analyzing them and extracting their most appropriate features using multi-objective metaheuristic algorithm, and then classifying them using artificial neural network to distinguish among files with similar names. The aim of this work is to provide the ability to find the files based on their contents using human thoughts only. Implementing this approach and testing it on real people proved its ability to find the desired files accurately within noticeably shorter time and retrieve them as a first choice for the user.

Keywords: Artificial intelligence, data contents search, human active memory, mind wave, multi-objective optimization.

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Authors: Luna Shamieh

Abstract:

Various players are part of the game in an asymmetric war, all making efforts to provide human security to their own adherents. Although a fragile state is not able to provide sufficient and comprehensive services, it still provides special services and security to the elite; the insurgents as well provide services and security to their associates. The humanitarian organisations, on the other hand, provide some fundamental elements of human security, but only in the regions, they are able to access when possible (if possible). The counterinsurgents (security forces of the state and intervention forces) operate within a narrow band defined by the vision of the responsibility to protect and the perspective of the resolution of the conflict through combat; hence, the possibility to provide human security is shaken at this end. This article examines how each player provides human security from the perspective of freedom from want in order to secure basic and strategic needs, freedom from fear through providing protection against all kinds of violence, and the freedom to live in dignity. It identifies a vicious cycle caused by the intervention of the different players causing a centrifugal force that may lead to disintegration of the nation under war.

Keywords: Human security, asymmetric war, counter insurgency, fragile state, insurgency.

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Authors: Erick López-Ornelas

Abstract:

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: 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: 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: Kuppusamy Singaravelloo, Zahra Kamiab

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This study explores the mediating effects of motivation in the relationship between human values and service quality. To examine the fundamental relationships among human values, motivation, and service quality, a Structural Equation Model (SEM) with a full mediation model was adopted. The model was designed and subsequently analyzed by utilizing the Partial Least Squares (PLS) procedure on data collected from a survey that yielded 936 usable questionnaires. The survey was sent to all 117 branches of two local commercial banks (CIMB and Maybank) operating in Kuala Lumpur, Malaysia. Both banks ranked the highest in terms of asset size and market capitalization. The mediating role of motivation was examined in the relationship between four dimensions of human values and bank service quality, whereby human values initiate service quality. The results support the notion that employee motivation fully mediates the relationship between self-enhancement values and service quality in commercial banks. These results demonstrate the unpredictable role of the interaction structures of human values on bank service quality.

Keywords: Human values, service quality, mediation, motivation, commercial bank.

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

Abstract:

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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