Search results for: Visual speech.

Authors: Trien V. Do, Jong-Weon Lee

Abstract:

This paper describes a 3D modeling system in Augmented Reality environment, named 3DARModeler. It can be considered a simple version of 3D Studio Max with necessary functions for a modeling system such as creating objects, applying texture, adding animation, estimating real light sources and casting shadows. The 3DARModeler introduces convenient, and effective human-computer interaction to build 3D models by combining both the traditional input method (mouse/keyboard) and the tangible input method (markers). It has the ability to align a new virtual object with the existing parts of a model. The 3DARModeler targets nontechnical users. As such, they do not need much knowledge of computer graphics and modeling techniques. All they have to do is select basic objects, customize their attributes, and put them together to build a 3D model in a simple and intuitive way as if they were doing in the real world. Using the hierarchical modeling technique, the users are able to group several basic objects to manage them as a unified, complex object. The system can also connect with other 3D systems by importing and exporting VRML/3Ds Max files. A module of speech recognition is included in the system to provide flexible user interfaces.

Keywords: 3D Modeling, Augmented Reality, GeometricModeling, Virtual Reality

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Authors: J. Jezierski, K. Janerka

Abstract:

The results of the two-phase gas-solid jet in pneumatic powder injection process analysis were presented in the paper. The researches were conducted on model set-up with high speed camera jet movement recording. Then the recorded material was analyzed to estimate main particles movement parameters. The values obtained from this direct measurement were compared to those calculated with the use of the well-known formulas for the two-phase flows (pneumatic conveying). Moreover, they were compared to experimental results previously achieved by authors. The analysis led to conclusions which to some extent changed the assumptions used even by authors, regarding the two-phase jet in pneumatic powder injection process. Additionally, the visual analysis of the recorded clips supplied data to make a more complete evaluation of the jet behavior in the lance outlet than before.

Keywords: injection lance, liquid metal, powder injection, slip velocity, two-phase jet

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Authors: D. A. Binas, M. Konidari, C. Bourgioti, L. Angela Moulopoulou, T. L. Economopoulos, G. K. Matsopoulos

Abstract:

High grade ovarian epithelial cancer (OEC) is the most fatal gynecological cancer and poor prognosis of this entity is closely related to considerable intratumoral genetic heterogeneity. By examining imaging data, it is possible to assess the heterogeneity of tumorous tissue. This study presents a methodology for aligning, segmenting and finally visualizing information from various magnetic resonance imaging series, in order to construct 3D models of heterogeneity maps from the same tumor in OEC patients. The proposed system may be used as an adjunct digital tool by health professionals for personalized medicine, as it allows for an easy visual assessment of the heterogeneity of the examined tumor.

Keywords: K-means segmentation, ovarian epithelial cancer, quantitative characteristics, registration, tumor visualization.

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Authors: Ahmet Denker, Tuğrul Adıgüzel

Abstract:

This paper presents a solution for a robotic manipulation problem. We formulate the problem as combining target identification, tracking and interception. The task in our solution is sensing a target on a conveyor belt and then intercepting robot-s end-effector at a convenient rendezvous point. We used an object recognition method which identifies the target and finds its position from visualized scene picture, then the robot system generates a solution for rendezvous problem using the target-s initial position and belt velocity . The interception of the target and the end-effector is executed at a convenient rendezvous point along the target-s calculated trajectory. Experimental results are obtained using a real platform with an industrial robot and a vision system over it.

Keywords: Object recognition, rendezvous planning, robotics.

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Authors: Raghavi Janaswamy, Saraswathi K. Vasudev

Abstract:

Music is one of the supreme arts of expressions, next to the speech itself. Its evolution over centuries has paved the way with a variety of training protocols and performing methods. Indian classical music is one of the most elaborate and refined systems with immense emphasis on the voice culture related to range, breath control, quality of the tone, flexibility and diction. Several exercises namely saraliswaram, jantaswaram, dhatuswaram, upper stayi swaram, alamkaras and varnams lay the required foundation to gain the voice culture and deeper understanding on the voice development and further on to the intricacies of the raga system. This article narrates a few of the Carnatic music training methods with an emphasis on the advanced practice methods for articulating the vocal skills, continuity in the voice, ability to produce gamakams, command in the multiple speeds of rendering with reasonable volume. The creativity on these exercises and their impact on the voice production are discussed. The articulation of the outlined conscious practice methods and vocal exercises bestow the optimum use of the natural human vocal system to not only enhance the signing quality but also to gain health benefits.

Keywords: Carnatic music, Saraliswaram, Varnam, Vocal training.

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Authors: A. Salmanpour, Sh. Mohammad Nejad

Abstract:

One of the methods for detecting the target position error in the laser tracking systems is using Four Quadrant (4Q) detectors. If the coordinates of the target center is yielded through the usual relations of the detector outputs, the results will be nonlinear, dependent on the shape, target size and its position on the detector screen. In this paper we have designed an algorithm with using neural network that coordinates of the target center in laser tracking systems is calculated by using detector outputs obtained from visual modeling. With this method, the results except from the part related to the detector intrinsic limitation, are linear and dependent from the shape and target size.

Keywords: four quadrant detector, laser tracking system, rangefinder, tracking sensor

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Authors: Preeti Kumari, Ridhi Kapoor

Abstract:

 In any communication, security is the most important issue in today’s world. In this paper, steganography is the process of hiding the important data into other data, such as text, audio, video, and image. The interest in this topic is to provide availability, confidentiality, integrity, and authenticity of data. The steganographic technique that embeds hides content with unremarkable cover media so as not to provoke eavesdropper’s suspicion or third party and hackers. In which many applications of compression, encryption, decryption, and embedding methods are used for digital image steganography. Due to compression, the nose produces in the image. To sustain noise in the image, the LSB insertion technique is used. The performance of the proposed embedding system with respect to providing security to secret message and robustness is discussed. We also demonstrate the maximum steganography capacity and visual distortion.

Keywords: Steganography, LSB, encoding, information hiding, color image.

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Authors: Maria Grazia Albanesi, Riccardo Amadeo

Abstract:

This study presents a new model of the human image quality assessment process: the aim is to highlightthe foundations of the image quality metrics proposed in literature, by identifyingthe cognitive/physiological or mathematical principles of their development and the relation with the actual human quality assessment process. The model allows to createa novel categorization of objective and subjective image quality metrics. Our work includes an overview of the most used or effectiveobjective metrics in literature, and, for each of them, we underline its main characteristics, with reference to the rationale of the proposed model and categorization. From the results of this operation, we underline a problem that affects all the presented metrics: the fact that many aspects of human biasesare not taken in account at all. We then propose a possible methodology to address this issue.

Keywords: Eye-Tracking, image quality assessment metric, MOS, quality of user experience, visual perception.

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Authors: Suresh Thokchom, Debabrata Dutta, Somnath Ghosh

Abstract:

This paper presents results of an experimental study performed to investigate effect of incorporating silica fume on physico-mechanical properties and durability of resulting fly ash geopolymers. Geopolymer specimens were prepared by activating fly ash incorporated with additional silica fume in the range of 2.5% to 5%, with a mixture of sodium hydroxide and sodium silicate solution having Na2O content of 8%. For studying durability, 10% magnesium sulphate solution was used to immerse the specimens up to a period of 15 weeks during which visual observation, weight changes and strength changes were monitored regularly. Addition of silica fume lowers performance of geopolymer pastes. However, in mortars, addition of silica fume significantly enhanced physico-mechanical properties and durability.

Keywords: Fly ash, silica fume, geopolymer, apparent porosity, sorptivity, compressive strength, durability.

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Authors: Babajide O. Ogungbesan, Rajneesh Kumar, Mohamed Sassi

Abstract:

Hydrogen sulfide (H2S) is a very toxic gas that is produced in very large quantities in the oil and gas industry. It cannot be flared to the atmosphere and Claus process based gas plants are used to recover the sulfur and convert the hydrogen to water. In this paper, we present optical characterization of an atmospheric pressure microwave plasma torch for H2S dissociation into hydrogen and sulfur. The torch is operated at 2.45 GHz with power up to 2 kW. Three different gases can simultaneously be injected in the plasma torch. Visual imaging and optical emission spectroscopy are used to characterize the plasma for varying gas flow rates and microwave power. The plasma length, emission spectra and temperature are presented. The obtained experimental results validate our earlier published simulation results of plasma torch.

Keywords: Atmospheric pressure microwave plasma, gas dissociation, optical emission spectroscopy.

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Authors: Oliver Kinnane, Aidan Reilly, John Grimes, Sara Pavia, Rosanne Walker

Abstract:

Unwanted sound reflection can create acoustic discomfort and lead to problems of speech comprehensibility. Contemporary building techniques enable highly finished internal walls resulting in sound reflective surfaces. In contrast, sustainable construction materials using natural and vegetal materials, are often more porous and absorptive. Hemp shiv is used as an aggregate and when mixed with lime binder creates a low-embodied-energy concrete. Cement replacements such as ground granulated blast slag (GGBS), a byproduct of other industrial processes, are viewed as more sustainable alternatives to high-embodied-energy cement. Hemp concretes exhibit good hygrothermal performance. This has focused much research attention on them as natural and sustainable low-energy alternatives to standard concretes. A less explored benefit is the acoustic absorption capability of hemp-based concretes. This work investigates hemp-lime-GGBS concrete specifically, and shows that it exhibits high levels of sound absorption.

Keywords: Hemp, hempcrete, acoustic absorption, GGBS.

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Authors: A. Giraldo, A. Lapatka, A. Namyslak, S. Pilny, J. B. Miima

Abstract:

This paper explains how the New Jersey Institute of Technology surveying student team members designed and created an interactive GIS map, the purpose of which is to be useful to the land surveyor and engineer for project management. This was achieved by building a research and storage database that can be easily integrated into any land surveyor’s current operations through the use of ArcGIS 10, Arc Catalog, and AutoCAD. This GIS database allows for visual representation and information querying for multiple job sites, and simple access to uploaded data, which is geospatially referenced to each individual job site or project. It can also be utilized by engineers to determine design criteria, or to store important files. This cost-effective approach to a surveying map not only saves time, but saves physical storage space and paper resources.

Keywords: Data Storage, GIS, Land Surveying, Mapping.

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Authors: Giovanni Luca Masala

Abstract:

Pattern recognition is the research area of Artificial Intelligence that studies the operation and design of systems that recognize patterns in the data. Important application areas are image analysis, character recognition, fingerprint classification, speech analysis, DNA sequence identification, man and machine diagnostics, person identification and industrial inspection. The interest in improving the classification systems of data analysis is independent from the context of applications. In fact, in many studies it is often the case to have to recognize and to distinguish groups of various objects, which requires the need for valid instruments capable to perform this task. The objective of this article is to show several methodologies of Artificial Intelligence for data classification applied to biomedical patterns. In particular, this work deals with the realization of a Computer-Aided Detection system (CADe) that is able to assist the radiologist in identifying types of mammary tumor lesions. As an additional biomedical application of the classification systems, we present a study conducted on blood samples which shows how these methods may help to distinguish between carriers of Thalassemia (or Mediterranean Anaemia) and healthy subjects.

Keywords: Computer Aided Detection, mammary tumor, pattern recognition, dissimilarity

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Authors: M. Kowalski, M. Kastek, M. Szustakowski

Abstract:

Multispectral screening systems are becoming more popular because of their very interesting properties and applications. One of the most significant applications of multispectral screening systems is prevention of terrorist attacks. There are many kinds of threats and many methods of detection. Visual detection of objects hidden under clothing of a person is one of the most challenging problems of threats detection. There are various solutions of the problem; however, the most effective utilize multispectral surveillance imagers. The development of imaging devices and exploration of new spectral bands is a chance to introduce new equipment for assuring public safety. We investigate the possibility of long lasting detection of potentially dangerous objects covered with various types of clothing. In the article we present the results of comparative studies of passive imaging in three spectrums – visible, infrared and terahertz.

Keywords: Infrared, image processing, object detection, screening camera, terahertz.

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Authors: Mangesh S. Deshpande, Raghunath S. Holambe

Abstract:

Mel Frequency Cepstral Coefficient (MFCC) features are widely used as acoustic features for speech recognition as well as speaker recognition. In MFCC feature representation, the Mel frequency scale is used to get a high resolution in low frequency region, and a low resolution in high frequency region. This kind of processing is good for obtaining stable phonetic information, but not suitable for speaker features that are located in high frequency regions. The speaker individual information, which is non-uniformly distributed in the high frequencies, is equally important for speaker recognition. Based on this fact we proposed an admissible wavelet packet based filter structure for speaker identification. Multiresolution capabilities of wavelet packet transform are used to derive the new features. The proposed scheme differs from previous wavelet based works, mainly in designing the filter structure. Unlike others, the proposed filter structure does not follow Mel scale. The closed-set speaker identification experiments performed on the TIMIT database shows improved identification performance compared to other commonly used Mel scale based filter structures using wavelets.

Keywords: Speaker identification, Wavelet transform, Feature extraction, MFCC, GMM.

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Authors: A. Borji, M. Hamidi

Abstract:

In this paper we examine the use of global texture analysis based approaches for the purpose of Persian font recognition in machine-printed document images. Most existing methods for font recognition make use of local typographical features and connected component analysis. However derivation of such features is not an easy task. Gabor filters are appropriate tools for texture analysis and are motivated by human visual system. Here we consider document images as textures and use Gabor filter responses for identifying the fonts. The method is content independent and involves no local feature analysis. Two different classifiers Weighted Euclidean Distance and SVM are used for the purpose of classification. Experiments on seven different type faces and four font styles show average accuracy of 85% with WED and 82% with SVM classifier over typefaces

Keywords: Persian font recognition, support vector machine, gabor filter.

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Authors: Giovanni Luca Masala

Abstract:

Pattern recognition is the research area of Artificial Intelligence that studies the operation and design of systems that recognize patterns in the data. Important application areas are image analysis, character recognition, fingerprint classification, speech analysis, DNA sequence identification, man and machine diagnostics, person identification and industrial inspection. The interest in improving the classification systems of data analysis is independent from the context of applications. In fact, in many studies it is often the case to have to recognize and to distinguish groups of various objects, which requires the need for valid instruments capable to perform this task. The objective of this article is to show several methodologies of Artificial Intelligence for data classification applied to biomedical patterns. In particular, this work deals with the realization of a Computer-Aided Detection system (CADe) that is able to assist the radiologist in identifying types of mammary tumor lesions. As an additional biomedical application of the classification systems, we present a study conducted on blood samples which shows how these methods may help to distinguish between carriers of Thalassemia (or Mediterranean Anaemia) and healthy subjects.

Keywords: Computer Aided Detection, mammary tumor, pattern recognition, thalassemia.

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Authors: Mario Gianni, Federico Nardi, Federico Ferri, Filippo Cantucci, Manuel A. Ruiz Garcia, Karthik Pushparaj, Fiora Pirri

Abstract:

In this paper, we describe a Mixed-Initiative Operational Model (MIOM) which directly intervenes on the state of the functionalities embedded into a robot for Urban Search&Rescue (USAR) domain applications. MIOM extends the reasoning capabilities of the vehicle, i.e. mapping, path planning, visual perception and trajectory tracking, with operator knowledge. Especially in USAR scenarios, this coupled initiative has the main advantage of enhancing the overall performance of a rescue mission. In-field experiments with rescue responders have been carried out to evaluate the effectiveness of this operational model.

Keywords: Actively articulated tracked vehicles, mixed-initiative planning interfeces, robot planning, urban search and rescue.

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Authors: Matjaž Divjak, Simon Zelič, Aleš Holobar

Abstract:

We present a dedicated video-based monitoring system for quantification of patient’s attention to visual feedback during robot assisted gait rehabilitation. Two different approaches for eye gaze and head pose tracking are tested and compared. Several metrics for assessment of patient’s attention are also presented. Experimental results with healthy volunteers demonstrate that unobtrusive video-based gaze tracking during the robot-assisted gait rehabilitation is possible and is sufficiently robust for quantification of patient’s attention and assessment of compliance with the rehabilitation therapy.

Keywords: Video-based attention monitoring, gaze estimation, stroke rehabilitation, user compliance.

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Authors: Niranjali Jayasuirya, Majell Backhausen

Abstract:

Water Sensitive Urban Design (WSUD) features are increasingly used to treat and manage polluted stormwater runoff in urbanised areas. It is important to monitor and evaluate the effectiveness of the infrastructure in achieving their intended performance targets after constructing and operating these features overtime. The paper presents the various methods of analysis used to assess the effectiveness of the in-situ WSUD features, such as: onsite visual inspections during operational and non operational periods, maintenance audits and periodic water quality testing. The results will contribute to a better understanding of the operational and maintenance needs of in-situ WSUD features and assist in providing recommendations to better manage life cycle performance.

Keywords: Bio-retention swales, Maintenance plan, Operational plan, Water Sensitive Urban Design, Water quality improvement.

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Authors: Vijay Kumar Nath, Deepika Hazarika, Anil Mahanta,

Abstract:

Discrete Cosine Transform (DCT) based transform coding is very popular in image, video and speech compression due to its good energy compaction and decorrelating properties. However, at low bit rates, the reconstructed images generally suffer from visually annoying blocking artifacts as a result of coarse quantization. Lapped transform was proposed as an alternative to the DCT with reduced blocking artifacts and increased coding gain. Lapped transforms are popular for their good performance, robustness against oversmoothing and availability of fast implementation algorithms. However, there is no proper study reported in the literature regarding the statistical distributions of block Lapped Orthogonal Transform (LOT) and Lapped Biorthogonal Transform (LBT) coefficients. This study performs two goodness-of-fit tests, the Kolmogorov-Smirnov (KS) test and the 2- test, to determine the distribution that best fits the LOT and LBT coefficients. The experimental results show that the distribution of a majority of the significant AC coefficients can be modeled by the Generalized Gaussian distribution. The knowledge of the statistical distribution of transform coefficients greatly helps in the design of optimal quantizers that may lead to minimum distortion and hence achieve optimal coding efficiency.

Keywords: Lapped orthogonal transform, Lapped biorthogonal transform, Image compression, KS test,

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Authors: Shen Jian, Hu Jie, Ma Jin, Peng Ying Hong, Fang Yi, Liu Wen Hai

Abstract:

Biologically inspired design inspires inventions and new technologies in the field of engineering by mimicking functions, principles, and structures in the biological domain. To deal with the obstacles of cross-domain knowledge acquisition in the existing biologically inspired design process, functional semantic clustering based on functional feature semantic correlation and environmental constraint clustering composition based on environmental characteristic constraining adaptability are proposed. A knowledge cell clustering algorithm and the corresponding prototype system is developed. Finally, the effectiveness of the method is verified by the visual prosthetic device design.

Keywords: Knowledge based engineering, biologically inspired design, knowledge cell, knowledge clustering, knowledge acquisition.

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Authors: Yunbin Yang, Liangli He, Fengjun Wang

Abstract:

The essentiality of maintenance assessment and maintenance optimization in design stage is analyzed, and the existent problems of conventional maintenance design method are illuminated. MDMVM (Maintenance Design Method based Virtual Maintenance) is illuminated, and the process of MDMVM established, and the MDMVM architecture is given out. The key techniques of MDMVM are analyzed, and include maintenance design based KBE (Knowledge Based Engineering) and virtual maintenance based physically attribute. According to physical property, physically based modeling, visual object movement control, the simulation of operation force and maintenance sequence planning method are emphatically illuminated. Maintenance design system based virtual maintenance is established in foundation of maintenance design method.

Keywords: Digital mock-up, virtual maintenance, knowledge engineering, maintenance sequence planning.

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Authors: Tomyslav Sledevič, Artūras Serackis, Gintautas Tamulevičius, Dalius Navakauskas

Abstract:

Paper presents an comparative evaluation of features extraction algorithm for a real-time isolated word recognition system based on FPGA. The Mel-frequency cepstral, linear frequency cepstral, linear predictive and their cepstral coefficients were implemented in hardware/software design. The proposed system was investigated in speaker dependent mode for 100 different Lithuanian words. The robustness of features extraction algorithms was tested recognizing the speech records at different signal to noise rates. The experiments on clean records show highest accuracy for Mel-frequency cepstral and linear frequency cepstral coefficients. For records with 15 dB signal to noise rate the linear predictive cepstral coefficients gives best result. The hard and soft part of the system is clocked on 50 MHz and 100 MHz accordingly. For the classification purpose the pipelined dynamic time warping core was implemented. The proposed word recognition system satisfy the real-time requirements and is suitable for applications in embedded systems.

Keywords: Isolated word recognition, features extraction, MFCC, LFCC, LPCC, LPC, FPGA, DTW.

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Authors: Kasthurirangan Gopalakrishnan, Siddhartha Khaitan, Anshu Manik

Abstract:

Cluster analysis is the name given to a diverse collection of techniques that can be used to classify objects (e.g. individuals, quadrats, species etc). While Kohonen's Self-Organizing Feature Map (SOFM) or Self-Organizing Map (SOM) networks have been successfully applied as a classification tool to various problem domains, including speech recognition, image data compression, image or character recognition, robot control and medical diagnosis, its potential as a robust substitute for clustering analysis remains relatively unresearched. SOM networks combine competitive learning with dimensionality reduction by smoothing the clusters with respect to an a priori grid and provide a powerful tool for data visualization. In this paper, SOM is used for creating a toroidal mapping of two-dimensional lattice to perform cluster analysis on results of a chemical analysis of wines produced in the same region in Italy but derived from three different cultivators, referred to as the “wine recognition data" located in the University of California-Irvine database. The results are encouraging and it is believed that SOM would make an appealing and powerful decision-support system tool for clustering tasks and for data visualization.

Keywords: Artificial neural networks, cluster analysis, Kohonen maps, wine recognition.

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Authors: Ashwag O. Maghraby, Nida N. Khan, Hosnia A. Ahmed, Ghufran N. Brohi, Hind F. Assouli, Jawaher S. Melibari

Abstract:

The Arabic language is one of the most important languages. Learning it is so important for many people around the world because of its religious and economic importance and the real challenge lies in practicing it without grammatical or syntactical mistakes. This research focused on detecting and correcting the syntactic mistakes of Arabic syntax according to their position in the sentence and focused on two of the main syntactical rules in Arabic: Dual and Plural. It analyzes each sentence in the text, using Stanford CoreNLP morphological analyzer and machine-learning approach in order to detect the syntactical mistakes and then correct it. A prototype of the proposed system was implemented and evaluated. It uses support vector machine (SVM) algorithm to detect Arabic grammatical errors and correct them using the rule-based approach. The prototype system has a far accuracy 81%. In general, it shows a set of useful grammatical suggestions that the user may forget about while writing due to lack of familiarity with grammar or as a result of the speed of writing such as alerting the user when using a plural term to indicate one person.

Keywords: Arabic Language acquisition and learning, natural language processing, morphological analyzer, part-of-speech.

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Authors: Francisco Guimarães, Mauro Figueiredo, José Rodrigues

Abstract:

Cities are spaces of memory with several zones (parts of cities) with their own history and cultural events. Today, cities are also marked by a form of intangible cultural heritage like street art, which creates a visual culture based on the process of reflection about the city and the world. To link these realities and create a personal user interaction with this cultural heritage it is important to capture the story and aesthetics, and find alternatives to immerse the user in these spaces of memory. To that end, this article presents a project which combines Augmented Reality technologies and concepts of Transmedia Storytelling applied to Lisbon City, using Street Art artifacts as markers in a framework of digital media-art.

Keywords: Cultural heritage, urban art, street art, augmented reality, transmedia storytelling, digital media-art, socio-museology.

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Authors: S. Souli, Z. Lachiri

Abstract:

In this paper we propose a robust environmental sound classification approach, based on spectrograms features driven from log-Gabor filters. This approach includes two methods. In the first methods, the spectrograms are passed through an appropriate log-Gabor filter banks and the outputs are averaged and underwent an optimal feature selection procedure based on a mutual information criteria. The second method uses the same steps but applied only to three patches extracted from each spectrogram.

To investigate the accuracy of the proposed methods, we conduct experiments using a large database containing 10 environmental sound classes. The classification results based on Multiclass Support Vector Machines show that the second method is the most efficient with an average classification accuracy of 89.62 %.

Keywords: Environmental sounds, Log-Gabor filters, Spectrogram, SVM Multiclass, Visual features.

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Authors: Watcharawalee Lertlum, Borworn Papasratorn

Abstract:

Conventional WBL is effective for meaningful student, because rote student learn by repeating without thinking or trying to understand. It is impossible to have full benefit from conventional WBL. Understanding of rote student-s intention and what influences it becomes important. Poorly designed user interface will discourage rote student-s cultivation and intention to use WBL. Thus, user interface design is an important factor especially when WBL is used as comprehensive replacement of conventional teaching. This research proposes the influencing factors that can enhance student-s intention to use the system. The enhanced TAM is used for evaluating the proposed factors. The research result points out that factors influencing rote student-s intention are Perceived Usefulness of Homepage Content Structure, Perceived User Friendly Interface, Perceived Hedonic Component, and Perceived (homepage) Visual Attractiveness.

Keywords: E-learning, Web-Based learning, Intention to use, Rote student, Influencing.

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Authors: Najam Aziz, Nasru Minallah, Ahmad Junaid, Kashaf Gul

Abstract:

Landcover classification using automated classification techniques, while employing remotely sensed multi-spectral imagery, is one of the promising areas of research. Different land conditions at different time are captured through satellite and monitored by applying different classification algorithms in specific environment. In this paper, a SPOT-5 image provided by SUPARCO has been studied and classified in Environment for Visual Interpretation (ENVI), a tool widely used in remote sensing. Then, Artificial Neural Network (ANN) classification technique is used to detect the land cover changes in Abbottabad district. Obtained results are compared with a pixel based Distance classifier. The results show that ANN gives the better overall accuracy of 99.20% and Kappa coefficient value of 0.98 over the Mahalanobis Distance Classifier.

Keywords: Landcover classification, artificial neural network, remote sensing, SPOT-5.

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