Search results for: Face Recognition

Authors: Rui Antunes

Abstract:

This article presents the implementation of several different e/b-Learning collaborative activities, used to improve the students learning process in an high school Polytechnic Institution. A new learning model arises, based on a combination between face-toface and distance leaning. Learning is now becoming centered with the development of collaborative activities, and its actors (teachers and students) have to be re-socialized to a new e/b-Learning paradigm. Measuring approaches are proposed for this model and results are presented, showing prospective correlation between students learning success and the use of online collaborative activities.

Keywords: e/b-Learning, Collaborative Learning, TeachingCommunities, Web-based Courseware

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Authors: M. H. Nagrial, J. Rizk, A. Hellany

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This paper presents the design, analysis and development of permanent magnet (PM) torque couplers. These couplers employ rare-earth magnets. Based on finite element analysis and earlier analytical works both concentric and face-type synchronous type couplers have been designed and fabricated. The experimental performance has good correlation with finite element calculations.

Keywords: Finite Element Analysis, Synchronous TorqueCouplers, Permanent Magnet Torque Couplers

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Authors: S. Sarumathi, N. Shanthi

Abstract:

Due to the fast and flawless technological innovation there is a tremendous amount of data dumping all over the world in every domain such as Pattern Recognition, Machine Learning, Spatial Data Mining, Image Analysis, Fraudulent Analysis, World Wide Web etc., This issue turns to be more essential for developing several tools for data mining functionalities. The major aim of this paper is to analyze various tools which are used to build a resourceful analytical or descriptive model for handling large amount of information more efficiently and user friendly. In this survey the diverse tools are illustrated with their extensive technical paradigm, outstanding graphical interface and inbuilt multipath algorithms in which it is very useful for handling significant amount of data more indeed.

Keywords: Classification, Clustering, Data Mining, Machine learning, Visualization.

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Authors: F. Halabchi, A. Esteghamati, A. Razzaghi, A. Noori

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Nowadays, doping is an intricate dilemma. Wrestling is the nationally popular sport in Iran. Also the prevalence of doping may be high, due to its power demanding characteristics. So, we aimed to assess the knowledge and attitudes toward doping among the club wrestlers. In a cross sectional study, 426 wrestlers were studied. For this reason, a researcher made questionnaire was used. In this study, researchers selected the clubs by randomized clustered sampling and distributed the questionnaire among wrestlers. Knowledge of wrestlers in three categories of doping definitions, recognition of prohibited drugs and side effects was poor or moderate in 70.8%, 95.8% and 99.5%, respectively. Wrestlers have poor knowledge in doping. Furthermore, they believe some myths which are unfavorable. It seems necessary to design a comprehensive educational program for all of the athletes and coaches.

Keywords: Attitude, Doping, Knowledge, Wrestling

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Authors: P. Soda, G.Iannello

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In this paper we address the issue of classifying the fluorescent intensity of a sample in Indirect Immuno-Fluorescence (IIF). Since IIF is a subjective, semi-quantitative test in its very nature, we discuss a strategy to reliably label the image data set by using the diagnoses performed by different physicians. Then, we discuss image pre-processing, feature extraction and selection. Finally, we propose two ANN-based classifiers that can separate intrinsically dubious samples and whose error tolerance can be flexibly set. Measured performance shows error rates less than 1%, which candidates the method to be used in daily medical practice either to perform pre-selection of cases to be examined, or to act as a second reader.

Keywords: Artificial neural networks, computer aided diagnosis, image classification, indirect immuno-fluorescence, pattern recognition.

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Authors: R. Ebrahimpour, M. Abbasnezhad Arabi, H. Babamiri Moghaddam

Abstract:

Combining classifiers is a useful method for solving complex problems in machine learning. The ECOC (Error Correcting Output Codes) method has been widely used for designing combining classifiers with an emphasis on the diversity of classifiers. In this paper, in contrast to the standard ECOC approach in which individual classifiers are chosen homogeneously, classifiers are selected according to the complexity of the corresponding binary problem. We use SATIMAGE database (containing 6 classes) for our experiments. The recognition error rate in our proposed method is %10.37 which indicates a considerable improvement in comparison with the conventional ECOC and stack generalization methods.

Keywords: Error correcting output code, combining classifiers, neural networks.

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Authors: M. Salehi, R. Tavakkoli-Moghaddam

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Selection of a project among a set of possible alternatives is a difficult task that the decision maker (DM) has to face. In this paper, by using a fuzzy TOPSIS technique we propose a new method for a project selection problem. After reviewing four common methods of comparing investment alternatives (net present value, rate of return, benefit cost analysis and payback period) we use them as criteria in a TOPSIS technique. First we calculate the weight of each criterion by a pairwise comparison and then we utilize the improved TOPSIS assessment for the project selection.

Keywords: Fuzzy Theory, Pairwise Comparison, ProjectSelection, TOPSIS Technique.

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Authors: M. Tridi, N. Nacereddine, N. Oucief

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This paper describes a novel method for automatic estimation of the contours of weld defect in radiography images. Generally, the contour detection is the first operation which we apply in the visual recognition system. Our approach can be described as a region based maximum likelihood formulation of parametric deformable contours. This formulation provides robustness against the poor image quality, and allows simultaneous estimation of the contour parameters together with other parameters of the model. Implementation is performed by a deterministic iterative algorithm with minimal user intervention. Results testify for the very good performance of the approach especially in synthetic weld defect images.

Keywords: Contour, gaussian, likelihood, rayleigh.

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Authors: Abdenour Bourabaa, Malika Fekih, Mohamed Saighi

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A numerical investigation of the fin efficiency and temperature distribution of an annular fin under dehumidification has been presented in this paper. The non-homogeneous second order differential equation that describes the temperature distribution from the fin base to the fin tip has been solved using the central finite difference method. The effects of variations in parameters including relative humidity, air temperature, air face velocity on temperature distribution and fin efficiency are investigated and compared with those under fully dry fin conditions. Also, the effect of fin pitch on the dimensionless temperature has been studied.

Keywords: Annular fin, Dehumidification, Fin efficiency, Heat and mass transfer, Wet fin.

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Authors: Ing-Jr Ding

Abstract:

This paper presents a technical speaker adaptation method called WMLLR, which is based on maximum likelihood linear regression (MLLR). In MLLR, a linear regression-based transform which adapted the HMM mean vectors was calculated to maximize the likelihood of adaptation data. In this paper, the prior knowledge of the initial model is adequately incorporated into the adaptation. A series of speaker adaptation experiments are carried out at a 30 famous city names database to investigate the efficiency of the proposed method. Experimental results show that the WMLLR method outperforms the conventional MLLR method, especially when only few utterances from a new speaker are available for adaptation.

Keywords: hidden Markov model, maximum likelihood linearregression, speech recognition, speaker adaptation.

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Authors: Liliana Feleagă, Niculae Feleagă, Vasile Răileanu

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Although agriculture is an important part of the world economy, accounting in agriculture still has many shortcomings. The adoption of IAS 41 “Agriculture” has tried to improve this situation and increase the comparability of financial statements of entities in the agricultural sector. Although controversial, IAS 41 is the first step of a consistent transition to fair value assessment in the agricultural sector. The objective of our work is the analysis of IAS 41 and current accounting agricultural situation in Romania. Accounting regulations in Romania are in accordance with European directives and, in many respects, converged with IFRS referential. Provisions of IAS 41, however, are not reflected directly in Romanian regulations. With the increase of forest land transactions, it is expected that recognition and measurement of biological assets under IAS 41 to become a necessity.

Keywords: Accounting Agricultural, Biological Assets, Fair value, IAS 41

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Authors: Endrick Barnacin, Jean-Luc Henry, Jimmy Nagau, Jack Molinié

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Palynology is a field of interest in many disciplines due to its multiple applications: chronological dating, climatology, allergy treatment, and honey characterization. Unfortunately, the analysis of a pollen slide is a complicated and time consuming task that requires the intervention of experts in the field, which are becoming increasingly rare due to economic and social conditions. In this context, the automation of this task is urgent. In this work, we compare classical feature extraction methods (Shape, GLCM, LBP, and others) and Deep Learning (CNN and Transfer Learning) to perform a recognition task over 80 regional pollen species. It has been found that the use of Transfer Learning seems to be more precise than the other approaches.

Keywords: Image segmentation, stuck particles separation, Sobel operator, thresholding.

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Authors: Ehsan Amid, Sina Rezaei Aghdam

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In this paper, a novel method for recognition of musical instruments in a polyphonic music is presented by using an embedded hidden Markov model (EHMM). EHMM is a doubly embedded HMM structure where each state of the external HMM is an independent HMM. The classification is accomplished for two different internal HMM structures where GMMs are used as likelihood estimators for the internal HMMs. The results are compared to those achieved by an artificial neural network with two hidden layers. Appropriate classification accuracies were achieved both for solo instrument performance and instrument combinations which demonstrates that the new approach outperforms the similar classification methods by means of the dynamic of the signal.

Keywords: hidden Markov model (HMM), embedded hidden Markov models (EHMM), MFCC, musical instrument.

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Authors: Sergey A. Burikov, Tatiana A. Dolenko, Kirill A. Gushchin, Sergey A. Dolenko

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The paper presents the results of clusterization by Kohonen self-organizing maps (SOM) applied for analysis of array of Raman spectra of multi-component solutions of inorganic salts, for determination of types of salts present in the solution. It is demonstrated that use of SOM is a promising method for solution of clusterization and classification problems in spectroscopy of multicomponent objects, as attributing a pattern to some cluster may be used for recognition of component composition of the object.

Keywords: Kohonen self-organizing maps, clusterization, multicomponent solutions, Raman spectroscopy.

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Authors: Ayaz Keerio, Bhargav Kumar Mitra, Philip Birch, Rupert Young, Chris Chatwin

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Preprocessing of speech signals is considered a crucial step in the development of a robust and efficient speech or speaker recognition system. In this paper, we present some popular statistical outlier-detection based strategies to segregate the silence/unvoiced part of the speech signal from the voiced portion. The proposed methods are based on the utilization of the 3 σ edit rule, and the Hampel Identifier which are compared with the conventional techniques: (i) short-time energy (STE) based methods, and (ii) distribution based methods. The results obtained after applying the proposed strategies on some test voice signals are encouraging.

Keywords: STE based methods, Mahalanobis distance, 3 edit σ rule, Hampel Identifier.

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Authors: A.Sankara Subramanian, G.Gurusamy, G.Selvakumar, P.Gnanasekar, A.Nagappan

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This paper presents an algorithm based on the wavelet decomposition, for feature extraction from the ECG signal and recognition of three types of Ventricular Arrhythmias using neural networks. A set of Discrete Wavelet Transform (DWT) coefficients, which contain the maximum information about the arrhythmias, is selected from the wavelet decomposition. After that a novel clustering algorithm based on nature inspired algorithm (Ant Colony Optimization) is developed for classifying arrhythmia types. The algorithm is applied on the ECG registrations from the MIT-BIH arrhythmia and malignant ventricular arrhythmia databases. We applied Daubechies 4 wavelet in our algorithm. The wavelet decomposition enabled us to perform the task efficiently and produced reliable results.

Keywords: Daubechies 4 Wavelet, ECG, Nature inspired algorithm, Ventricular Arrhythmias, Wavelet Decomposition.

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Authors: Pratik Dhabal Deo, Manoj P.

Abstract:

With the increasing number of social media users, the amount of video content available has also significantly increased. Currently, the number of smartphone users is at its peak, and many are increasingly using their smartphones as their main photography and recording devices. There have been a lot of developments in the field of video quality assessment in since the past years and more research on various other aspects of video and image are being done. Datasets that contain a huge number of videos from different high-end devices make it difficult to analyze the performance of the metrics on the content from most used devices even if they contain contents taken in poor lighting conditions using lower-end devices. These devices face a lot of distortions due to various factors since the spectrum of contents recorded on these devices is huge. In this paper, we have presented an analysis of the objective Video Quality Analysis (VQA) metrics on contents taken only from most used devices and their performance on them, focusing on full-reference metrics. To carry out this research, we created a custom dataset containing a total of 90 videos that have been taken from three most commonly used devices, and Android smartphone, an iOS smartphone and a Digital Single-Lens Reflex (DSLR) camera. On the videos taken on each of these devices, the six most common types of distortions that users face have been applied in addition to already existing H.264 compression based on four reference videos. These six applied distortions have three levels of degradation each. A total of the five most popular VQA metrics have been evaluated on this dataset and the highest values and the lowest values of each of the metrics on the distortions have been recorded. Finally, it is found that blur is the artifact on which most of the metrics did not perform well. Thus, in order to understand the results better the amount of blur in the data set has been calculated and an additional evaluation of the metrics was done using High Efficiency Video Coding (HEVC) codec, which is the next version of H.264 compression, on the camera that proved to be the sharpest among the devices. The results have shown that as the resolution increases, the performance of the metrics tends to become more accurate and the best performing metric among them is VQM with very few inconsistencies and inaccurate results when the compression applied is H.264, but when the compression is applied is HEVC, Structural Similarity (SSIM) metric and Video Multimethod Assessment Fusion (VMAF) have performed significantly better.

Keywords: Distortion, metrics, recording, frame rate, video quality assessment.

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Authors: M. R. Bhuiyan, S. M. M. Hossain, M. Z. Islam

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Autism Spectrum Disorder (ASD) is the fastest growing serious developmental disorder characterized by social deficits, communicative difficulties, and repetitive behaviors. ASD is an emerging public health issue globally which is associated with huge financial burden to the family, community and the nation. The aim of this study was to assess the financial burden of family for the children with Autism spectrum Disorder. This cross-sectional study was carried out from July 2015 to June 2016 among 154 children with ASD to assess the financial burden of family. Data were collected by face-to-face interview with semi-structured questionnaire following systematic random sampling technique. Majority (73.4%) children were male and mean (±SD) age was 6.66 ± 2.97 years. Most (88.8%) of the children were from urban areas with average monthly family income Tk. 41785.71±23936.45. Average monthly direct cost of the children was Tk.17656.49 ± 9984.35, while indirect cost was Tk. 13462.90 ± 9713.54 and total treatment cost was Tk. 23076.62 ± 15341.09. Special education cost (Tk. 4871.00), cost of therapy (Tk. 4124.07) and travel cost (Tk. 3988.31) were the major types of direct cost, while loss of income (Tk.14570.18) was the chief indirect cost incurred by the families. The study found that majority (59.8%) of the children attended special schools were incurred Tk.20001-78700 as total treatment cost, which were statistically significant (p<0.001). Again, families with higher monthly family income incurred higher treatment cost (r=0.526, p<0.05). Difference between mean direct and indirect cost was found significant (t=4.190, df=61, p<0.001). According to the analysis of variance, mean difference of father’s educational status among direct cost (F=10.337, p<0.001) and total treatment cost (F=7.841, p<0.001), which were statistically significant. The study revealed that maximum children with ASD were under five years, three-fourth were male. According to monthly family income, maximum family were in middle class. The study recommends cost effective interventions and financial safety-net measures to reduce the financial burden of families for the children with ASD.

Keywords: Autism spectrum disorder, financial burden, direct cost, indirect cost, Special education.

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Authors: Aynaz Lotfata

Abstract:

Planning community has been long discussing emerging paradigms within the planning theory in the face of the changing conditions of the world order. The paradigm shift concept was introduced by Thomas Kuhn, in 1960, who claimed the necessity of shifting within scientific knowledge boundaries; and following him in 1970 Imre Loktas also gave priority to the emergence of multi-paradigm societies [24]. Multi-paradigm is changing our predetermined lifeworld through uncertainties. Those uncertainties are reflected in two sides, the first one is uncertainty as a concept of possibility and creativity in public sphere and the second one is uncertainty as a risk. Therefore, it is necessary to apply a resilience planning approach to be more dynamic in controlling uncertainties which have the potential to transfigure present time and space definitions. In this way, stability of system can be achieved. Uncertainty is not only an outcome of worldwide changes but also a place-specific issue, i.e. it changes from continent to continent, a country to country; a region to region. Therefore, applying strategic spatial planning with respect to resilience principle contributes to: control, grasp and internalize uncertainties through place-specific strategies. In today-s fast changing world, planning system should follow strategic spatial projects to control multi-paradigm societies with adaptability capacities. Here, we have selected two alternatives to demonstrate; these are; 1.Tehran (Iran) from the Middle East 2.Bath (United Kingdom) from Europe. The study elaborates uncertainties and particularities in their strategic spatial planning processes in a comparative manner. Through the comparison, the study aims at assessing place-specific priorities in strategic planning. The approach is to a two-way stream, where the case cities from the extreme end of the spectrum can learn from each other. The structure of this paper is to firstly compare semi-periphery (Tehran) and coreperiphery (Bath) cities, with the focus to reveal how they equip to face with uncertainties according to their geographical locations and local particularities. Secondly, the key message to address is “Each locality requires its own strategic planning approach to be resilient.--

Keywords: Adaptation, Relational Network, Socio-Spatial Strategic Resiliency, Uncertainty.

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Authors: Sebastien Harasse, Laurent Bonnaud, Michel Desvignes

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Counting people from a video stream in a noisy environment is a challenging task. This project aims at developing a counting system for transport vehicles, integrated in a video surveillance product. This article presents a method for the detection and tracking of multiple faces in a video by using a model of first and second order local moments. An iterative process is used to estimate the position and shape of multiple faces in images, and to track them. the trajectories are then processed to count people entering and leaving the vehicle.

Keywords: face detection, tracking, counting, local statistics

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Authors: Ntokozo Mthembu

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Access to relevant health indicates people’s likelihood of survival, including craft of indigenous healing and its related practitioners- izinyanga. However, the emergence of a dreaded novel corona virus - COVID-19 that has engulfed almost the whole world has necessitated the need to revisit the state of traditional healers in South Africa. This circumstance tended to expose the reality of social settings in various social structures and related policies including the manner coloniality reveal its ugly head when it comes treatment between western and African based therapeutic practices in this country. In attempting to gain a better understanding of such experiences, primary and secondary sources were consulted when collecting data that perusal of various literature in this instance including face-to-face interviews with traditional healers working on the street of Tshwane Municipality in South Africa. Preliminary findings revealed that the emergence of this deadly virus coincided with the moment when the government agenda was focussed on fulfilment of its promise of addressing the past inequity practices, including the transformation of medical sector. This scenario can be witnessed by the manner in which government and related agencies such as health department keeps on undermining indigenous healing practice irrespective of its historical record in terms of healing profession and fighting various diseases before times of father of medicine, Imhotep. Based on these preliminary findings, it is recommended that the government should hasten the incorporation of African knowledge systems especially medicine to offer alternatives and diverse to assess the underutilised indigenous African therapeutic approach and relevant skills that could be useful in combating ailments such as COVID 19. Perhaps, the plural medical systems should be recognized and related policies are formulated to guarantee mutual respect among citizens and the incorporation of healing practices in South African health sector, Africa and in the broader global community.

Keywords: Indigenous healing practice, inyanga, COVID-19, therapeutic, urban, experience.

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Authors: Randa Boukhris Trabelsi, Alima Damak Masmoudi, Dorra Sellami Masmoudi

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Nowadays, hand vein recognition has attracted more attentions in identification biometrics systems. Generally, hand vein image is acquired with low contrast and irregular illumination. Accordingly, if you have a good preprocessing of hand vein image, we can easy extracted the feature extraction even with simple binarization. In this paper, a proposed approach is processed to improve the quality of hand vein image. First, a brief survey on existing methods of enhancement is investigated. Then a Radon Like features method is applied to preprocessing hand vein image. Finally, experiments results show that the proposed method give the better effective and reliable in improving hand vein images.

Keywords: Hand Vein, Enhancement, Contrast, RLF, SDME

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Authors: Preeti Yadav, Dandeswar Bisoyi, Debkumar Chakrabarti

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Mascots provide memories to viewers, and numerous promotional campaigns with different appearances, continue to trigger viewers and capture their interest. This study investigates the effect of Indian food mascot designs and influence on enhancing communication; thereby, building long-term brand recognition by the consumers. This paper presents a descriptive approach to Indian food mascot design as an advertising tool, and its research adopts a quantitative methodology. The study confirms that mascots have an ability to communicate a message in an effective manner; all though they are simple in terms of design and fashion trend, they have the capability to build positive reactions.

Keywords: Food mascot, brand recognitions, advertising, humour.

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Authors: H. Nagendra, Vinod Kumar, S. Mukherjee

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In this study, the potential benefits of playing action video game among congenitally deaf and dumb subjects is reported in terms of EEG ratio indices. The frontal and occipital lobes are associated with development of motor skills, cognition, and visual information processing and color recognition. The sixteen hours of First-Person shooter action video game play resulted in the increase of the ratios β/(α+θ) and β/θ in frontal and occipital lobes. This can be attributed to the enhancement of certain aspect of cognition among deaf and dumb subjects.

Keywords: Cognitive enhancement, video games, EEG band powers, Deaf and Dumb subjects.

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Authors: Geoffrey Sinha

Abstract:

This paper is primarily addressed to teachers who stand on the threshold of bringing technology and new media into their classrooms. Technology and new media, such as smart phones and tablets have changed the face of communication in general and of language teaching more specifically. New media has widespread appeal among young people in particular, so it is in the teacher’s best interests to bring new media into their lessons. It is the author’s firm belief that technology will never replace the teacher, but it is without question that the twenty-first century teacher must employ technology and new media in some form, or run the risk of failure. The level that one chooses to incorporate new media within their class is entirely in their hands.

Keywords: New media, social media, technology, education.

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Authors: Mehran Yazdi, Mehdi Seyfi, Amirhossein Rafati, Meghdad Asadi

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Detection and tracking of the lip contour is an important issue in speechreading. While there are solutions for lip tracking once a good contour initialization in the first frame is available, the problem of finding such a good initialization is not yet solved automatically, but done manually. We have developed a new tracking solution for lip contour detection using only few landmarks (15 to 25) and applying the well known Active Shape Models (ASM). The proposed method is a new LMS-like adaptive scheme based on an Auto regressive (AR) model that has been fit on the landmark variations in successive video frames. Moreover, we propose an extra motion compensation model to address more general cases in lip tracking. Computer simulations demonstrate a fair match between the true and the estimated spatial pixels. Significant improvements related to the well known LMS approach has been obtained via a defined Frobenius norm index.

Keywords: Lip contour, Tracking, LMS-Like

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Authors: Jason Zalev, Reza Sedaghat

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This paper describes a complex energy signal model that is isomorphic with digital human fingerprint images. By using signal models, the problem of fingerprint matching is transformed into the signal processing problem of finding a correlation between two complex signals that differ by phase-rotation and time-scaling. A technique for minutiae matching that is independent of image translation, rotation and linear-scaling, and is resistant to missing minutiae is proposed. The method was tested using random data points. The results show that for matching prints the scaling and rotation angles are closely estimated and a stronger match will have a higher correlation.

Keywords: Affine Invariant, Fingerprint Recognition, Matching, Minutiae.

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Authors: Daesung Moon, Woo-Yong Choi, Kiyoung Moon

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Fuzzy fingerprint vault is a recently developed cryptographic construct based on the polynomial reconstruction problem to secure critical data with the fingerprint data. However, the previous researches are not applicable to the fingerprint having a few minutiae since they use a fixed degree of the polynomial without considering the number of fingerprint minutiae. To solve this problem, we use an adaptive degree of the polynomial considering the number of minutiae extracted from each user. Also, we apply multiple polynomials to avoid the possible degradation of the security of a simple solution(i.e., using a low-degree polynomial). Based on the experimental results, our method can make the possible attack difficult 2192 times more than using a low-degree polynomial as well as verify the users having a few minutiae.

Keywords: Fuzzy vault, fingerprint recognition multiple polynomials.

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Authors: Khaled N. El-Hashmi, Omar K.Gnieber

Abstract:

The clinical laboratory has received considerable recognition globally due to the rapid development of advanced technology, economic demands and its role in a patient’s treatment cycle. Although various cross-domain experiments and practices with respect to clinical laboratory projects are ready for the full swing, the customer needs are still ambiguous and debatable. The purpose of this study is to apply Kano’s model and customer satisfaction matrix to categorize service quality attributes in order to see how well these attributes are able to satisfy customer needs. The result reveals that ten of the 26 service quality attributes have greater impacts on highly increasing customer’s satisfaction and should be taken in consideration firstly.

Keywords: Clinical laboratory, Customer satisfaction matrix, Kano’s Model, Quality Attributes, Voice of Customer.

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Authors: Mahboubeh Molaei

Abstract:

Transferring information developed by other peoples is an ordinary event that happens during daily conversations, for example when employees sea each other in the organization, or when they are having lunch together, or attending a meeting, they use to talk about their experience, and discuss about their current projects, and talk about their successes over some specific problems. Despite the potential value of leveraging organizational memory and expertise by using OMS and ER, still small organizations haven-t been able to capitalize on its promised value. Each organization has its internal knowledge management system, in some of organizations the system face the lack of expert people to save their experience in the repository and in another hand on some other organizations there are lots of expert people but the organization doesn-t have the maximum use of their knowledge.

Keywords: Knowledge, knowledge management.

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