Scholarly

Phenotypes of B Cells Differ in EBV-positive Burkitt-s lymphoma Derived Cell Lines

Year: 2012 Volume: 6 Issue: 12 1145 - 1148 Pages

Abstract: Epstein-Barr virus (EBV) is implicated in the pathogenesis of the endemic Burkitt-s lymphoma (BL). The EBVpositive BL-derived cell lines initially maintain the original tumor phenotype of EBV infection (latency I, LatI), but most of them drift toward a lymphoblast phenotype of EBV latency III (LatIII) during in vitro culturing. The aim of the present work was to characterize the B-cell subsets in EBV-positive BL cell lines and to verify whether a particular cell subset correlates with the type of EBV infection. The phenotype analysis of two EBV-negative and eleven EBV-positive (three of LatI and eight of LatIII) BL cell lines was performed by polychromatic flow cytomery, based on expression pattern of CD19, CD10, CD38, CD27, and CD5 markers. Two cell subsets, CD19+CD10+ and CD19+CD10-, were defined in LatIII BL cell lines. In both subsets, the CD27 and CD5 cell surface expression was detected in a proportion of the cells.

Non-Invasive Technology on a Classroom Chair for Detection of Emotions Used for the Personalization of Learning Resources

Year: 2010 Volume: 4 Issue: 6 1348 - 1354 Pages

Abstract: Emotions are related with learning processes and physiological signals can be used to detect them for the personalization of learning resources and to control the pace of instruction. A model of relevant emotions has been developed, where specific combinations of emotions and cognition processes are connected and integrated with the concept of 'flow', in order to improve learning. The cardiac pulse is a reliable signal that carries useful information about the subject-s emotional condition; it is detected using a classroom chair adapted with non invasive EMFi sensor and an acquisition system that generates a ballistocardiogram (BCG), the signal is processed by an algorithm to obtain characteristics that match a specific emotional condition. The complete chair system is presented in this work, along with a framework for the personalization of learning resources.

Generator Damage Recognition Based on Artificial Neural Network

Year: 2012 Volume: 6 Issue: 5 521 - 524 Pages

Abstract: This article simulates the wind generator set which has two fault bearing collar rail destruction and the gear box oil leak fault. The electric current signal which produced by the generator, We use Empirical Mode Decomposition (EMD) as well as Fast Fourier Transform (FFT) obtains the frequency range-s signal figure and characteristic value. The last step is use a kind of Artificial Neural Network (ANN) classifies which determination fault signal's type and reason. The ANN purpose of the automatic identification wind generator set fault..

A New Method of Combined Classifier Design Based on Fuzzy Neural Network

Year: 2007 Volume: 1 Issue: 4 693 - 698 Pages

Authors:
Kexin Jia
Youxin Lu

Abstract: To make the modulation classification system more suitable for signals in a wide range of signal to noise rate (SNR), a novel method of designing combined classifier based on fuzzy neural network (FNN) is presented in this paper. The method employs fuzzy neural network classifiers and interclass distance (ICD) to improve recognition reliability. Experimental results show that the proposed combined classifier has high recognition rate with large variation range of SNR (success rates are over 99.9% when SNR is not lower than 5dB).

Assamese Numeral Speech Recognition using Multiple Features and Cooperative LVQ -Architectures

Year: 2011 Volume: 5 Issue: 9 1265 - 1275 Pages

Abstract: A set of Artificial Neural Network (ANN) based methods for the design of an effective system of speech recognition of numerals of Assamese language captured under varied recording conditions and moods is presented here. The work is related to the formulation of several ANN models configured to use Linear Predictive Code (LPC), Principal Component Analysis (PCA) and other features to tackle mood and gender variations uttering numbers as part of an Automatic Speech Recognition (ASR) system in Assamese. The ANN models are designed using a combination of Self Organizing Map (SOM) and Multi Layer Perceptron (MLP) constituting a Learning Vector Quantization (LVQ) block trained in a cooperative environment to handle male and female speech samples of numerals of Assamese- a language spoken by a sizable population in the North-Eastern part of India. The work provides a comparative evaluation of several such combinations while subjected to handle speech samples with gender based differences captured by a microphone in four different conditions viz. noiseless, noise mixed, stressed and stress-free.

Study of Compost Maturity during Humification Process using UV-Spectroscopy

Year: 2011 Volume: 5 Issue: 8 486 - 488 Pages

Abstract: The increments of aromatic structures are widely used to monitor the degree of humification. Compost derived from mix manures mixed with agricultural wastes was studied. The compost collected at day 0, 7, 14, 21, 28, 35, 49, 77, 91, 105, and 119 was divided into 3 stages, initial stage at day 0, thermophilic stage during day 1-48, and mature stage during day 49-119. The change of highest absorptions at wavelength range between 210-235 nm during day 0- 49 implied that small molecules such as nitrates and carboxylic occurred faster than the aromatic molecules that were found at wavelength around 280 nm. The ratio of electron-transfer band at wavelength 253 nm by the benzonoid band at wavelength 230 nm (E253/E230) also gradually increased during the fermenting period indicating the presence of O-containing functional groups. This was in agreement with the shift change from aliphatic to aromatic structures as shown by the relationship with C/N and H/C ratios (r = - 0.631 and -0.717, p< 0.05) since both were decreasing. Although the amounts of humic acid (HA) were not different much during the humification process, the UV spectral deconvolution showed better qualitative characteristics to help in determining the compost quality. From this study, the compost should be used at day 49 and should not be kept longer than 3 months otherwise the quality of HA would decline regardless of the amounts of HA that might be rising. This implied that other processes, such as mineralization had an influence on the humification process changing HA-s structure and its qualities.

Definition of Cognitive Infocommunications and an Architectural Implementation of Cognitive Infocommunications Systems

Year: 2011 Volume: 5 Issue: 10 1379 - 1383 Pages

Abstract: Cognitive Infocommunications (CogInfoCom) is a new research direction which has emerged as the synergic convergence of infocommunications and the cognitive sciences. In this paper, we provide the definition of CogInfoCom, and propose an architectural framework for the interaction-oriented design of CogInfoCom systems. We provide the outlines of an application example of the interaction-oriented architecture, and briefly discuss its main characteristics.

Automotive 3-Microphone Noise Canceller in a Frequently Moving Noise Source Environment

Year: 2007 Volume: 1 Issue: 7 1048 - 1054 Pages

Authors:
Z. Qi
T. J. Moir

Abstract: A combined three-microphone voice activity detector (VAD) and noise-canceling system is studied to enhance speech recognition in an automobile environment. A previous experiment clearly shows the ability of the composite system to cancel a single noise source outside of a defined zone. This paper investigates the performance of the composite system when there are frequently moving noise sources (noise sources are coming from different locations but are not always presented at the same time) e.g. there is other passenger speech or speech from a radio when a desired speech is presented. To work in a frequently moving noise sources environment, whilst a three-microphone voice activity detector (VAD) detects voice from a “VAD valid zone", the 3-microphone noise canceller uses a “noise canceller valid zone" defined in freespace around the users head. Therefore, a desired voice should be in the intersection of the noise canceller valid zone and VAD valid zone. Thus all noise is suppressed outside this intersection of area. Experiments are shown for a real environment e.g. all results were recorded in a car by omni-directional electret condenser microphones.

Measuring Cognitive Load - A Solution to Ease Learning of Programming

Year: 2007 Volume: 1 Issue: 2 37 - 40 Pages

Abstract: Learning programming is difficult for many learners. Some researches have found that the main difficulty relates to cognitive load. Cognitive overload happens in programming due to the nature of the subject which is intrinisicly over-bearing on the working memory. It happens due to the complexity of the subject itself. The problem is made worse by the poor instructional design methodology used in the teaching and learning process. Various efforts have been proposed to reduce the cognitive load, e.g. visualization softwares, part-program method etc. Use of many computer based systems have also been tried to tackle the problem. However, little success has been made to alleviate the problem. More has to be done to overcome this hurdle. This research attempts at understanding how cognitive load can be managed so as to reduce the problem of overloading. We propose a mechanism to measure the cognitive load during pre instruction, post instruction and in instructional stages of learning. This mechanism is used to help the instruction. As the load changes the instruction is made to adapt itself to ensure cognitive viability. This mechanism could be incorporated as a sub domain in the student model of various computer based instructional systems to facilitate the learning of programming.

Linear Instability of Wake-Shear Layers in Two-Phase Shallow Flows

Year: 2008 Volume: 2 Issue: 10 740 - 744 Pages

Abstract: Linear stability analysis of wake-shear layers in twophase shallow flows is performed in the present paper. Twodimensional shallow water equations are used in the analysis. It is assumed that the fluid contains uniformly distributed solid particles. No dynamic interaction between the carrier fluid and particles is expected in the initial moment. The stability calculations are performed for different values of the particle loading parameter and two other parameters which characterize the velocity ratio and the velocity deficit. The results show that the particle loading parameter has a stabilizing effect on the flow while the increase in the velocity ratio or in the velocity deficit destabilizes the flow.

The Splitting Upwind Schemes for Spectral Action Balance Equation

Year: 2011 Volume: 5 Issue: 6 892 - 900 Pages

Abstract: The spectral action balance equation is an equation that used to simulate short-crested wind-generated waves in shallow water areas such as coastal regions and inland waters. This equation consists of two spatial dimensions, wave direction, and wave frequency which can be solved by finite difference method. When this equation with dominating convection term are discretized using central differences, stability problems occur when the grid spacing is chosen too coarse. In this paper, we introduce the splitting upwind schemes for avoiding stability problems and prove that it is consistent to the upwind scheme with same accuracy. The splitting upwind schemes was adopted to split the wave spectral action balance equation into four onedimensional problems, which for each small problem obtains the independently tridiagonal linear systems. For each smaller system can be solved by direct or iterative methods at the same time which is very fast when performed by a multi-processor computer.

Towards Cloud Computing Anatomy

Year: 2012 Volume: 6 Issue: 5 691 - 696 Pages

Abstract: Cloud Computing has recently emerged as a compelling paradigm for managing and delivering services over the internet. The rise of Cloud Computing is rapidly changing the landscape of information technology, and ultimately turning the longheld promise of utility computing into a reality. As the development of Cloud Computing paradigm is speedily progressing, concepts, and terminologies are becoming imprecise and ambiguous, as well as different technologies are interfering. Thus, it becomes crucial to clarify the key concepts and definitions. In this paper, we present the anatomy of Cloud Computing, covering its essential concepts, prominent characteristics, its affects, architectural design and key technologies. We differentiate various service and deployment models. Also, significant challenges and risks need are tackled in order to guarantee the long-term success of Cloud Computing. The aim of this paper is to provide a better understanding of the anatomy of Cloud Computing and pave the way for further research in this area.

The Role of the State towards Employability of Malaysian PWDs – Myth or Reality?

Year: 2012 Volume: 6 Issue: 6 1549 - 1554 Pages

Abstract: In this era of globalization, the role of the State in all aspects of development is widely debated. Some scholars contend the 'demise' and diminishing role of the State whilst others claim that the State is still “de facto developmental". Clearly, it is vital to ascertain which of these two contentions are reflective of the role of the State as nations ascend their development trajectories. Based on the findings of this paper, the perception that the Malaysian State plays an active and committed role towards distributing equitable educational opportunities and enhancing employability of Malaysian PWDs is actually a myth and not reality. Thus, in order to fulfill the promise of Vision 2020 to transform Malaysia into a caring and socially-inclusive society; this paper calls for a more interventionist and committed role by the Malaysian State to translate the universal rights of education and employment opportunities for PWDs from mere policy rhetoric into inclusive realities.

Autobiographical Memory and Flexible Remembering: Gender Differences

Year: 2010 Volume: 4 Issue: 6 1336 - 1342 Pages

Abstract: In this study, we examined gender differences in: (1) a flexible remembering task, that asked for episodic memory decisions at an item-specific versus category-based level, and (2) the retrieval specificity of autobiographical memory during free recall. Differences favouring women were found on both measures. Furthermore, a significant association was observed, across gender groups, between level of specificity in the autobiographical memory interview and sensitivity to gist on the flexible remembering task. These results suggest that similar cognitive processes may partially contribute to both the ability for specific autobiographical recall and the capacity for inhibition of gist-information on the flexible remembering task.

Mass Transfer Modeling of Nitrate in an Ion Exchange Selective Resin

Year: 2012 Volume: 6 Issue: 1 59 - 64 Pages

Abstract: The rate of nitrate adsorption by a nitrate selective ion exchange resin was investigated in a well-stirred batch experiments. The kinetic experimental data were simulated with diffusion models including external mass transfer, particle diffusion and chemical adsorption. Particle pore volume diffusion and particle surface diffusion were taken into consideration separately and simultaneously in the modeling. The model equations were solved numerically using the Crank-Nicholson scheme. An optimization technique was employed to optimize the model parameters. All nitrate concentration decay data were well described with the all diffusion models. The results indicated that the kinetic process is initially controlled by external mass transfer and then by particle diffusion. The external mass transfer coefficient and the coefficients of pore volume diffusion and surface diffusion in all experiments were close to each other with the average value of 8.3×10-3 cm/S for external mass transfer coefficient. In addition, the models are more sensitive to the mass transfer coefficient in comparison with particle diffusion. Moreover, it seems that surface diffusion is the dominant particle diffusion in comparison with pore volume diffusion.

Chewing behavior and Bolus Properties as Affected by Different Rice Types

Year: 2012 Volume: 6 Issue: 1 40 - 45 Pages

Abstract: The study aimed to investigate the effect of rice types on chewing behaviours (chewing time, number of chews, and portion size) and bolus properties (bolus moisture content, solid loss, and particle size distribution (PSD)) in human subjects. Five cooked rice types including brown rice (BR), white rice (WR), parboiled white rice (PR), high amylose white rice (HR) and waxy white rice (WXR) were chewed by six subjects. The chewing behaviours were recorded and the food boluses were collected during mastication. Rice typeswere found to significantly influence all chewing parameters evaluated. The WXR and BR showed the most pronounced differences compared with other rice types. The initial moisture content of un-chewed WXR was lowest (43.39%) whereas those of other rice types were ranged from 66.86 to 70.33%. The bolus obtained from chewing the WXR contained lowest moisture content (56.43%) whilst its solid loss (22.03%) was not significant different from those of all rice types. In PSD evaluation using Mastersizer S, the diameter of particles measured was ranged between 4 to 3500 μm. The particle size of food bolus from BR, HR, and WXR contained much finer particles than those of WR and PR.

Classification of Initial Stripe Height Patterns using Radial Basis Function Neural Network for Proportional Gain Prediction

Year: 2011 Volume: 5 Issue: 4 393 - 395 Pages

Abstract: This paper aims to improve a fine lapping process of hard disk drive (HDD) lapping machines by removing materials from each slider together with controlling the strip height (SH) variation to minimum value. The standard deviation is the key parameter to evaluate the strip height variation, hence it is minimized. In this paper, a design of experiment (DOE) with factorial analysis by twoway analysis of variance (ANOVA) is adopted to obtain a statistically information. The statistics results reveal that initial stripe height patterns affect the final SH variation. Therefore, initial SH classification using a radial basis function neural network is implemented to achieve the proportional gain prediction.

Optimizing Feature Selection for Recognizing Handwritten Arabic Characters

Year: 2007 Volume: 1 Issue: 4 1137 - 1140 Pages

Abstract: Recognition of characters greatly depends upon the features used. Several features of the handwritten Arabic characters are selected and discussed. An off-line recognition system based on the selected features was built. The system was trained and tested with realistic samples of handwritten Arabic characters. Evaluation of the importance and accuracy of the selected features is made. The recognition based on the selected features give average accuracies of 88% and 70% for the numbers and letters, respectively. Further improvements are achieved by using feature weights based on insights gained from the accuracies of individual features.

Deep Learning and Virtual Environment

Year: 2012 Volume: 6 Issue: 11 3268 - 3274 Pages

Abstract: While computers are known to facilitate lower levels of learning, such as rote memorization of facts, measurable through electronically administered and graded multiple-choice questions, yes/no, and true/false answers, the imparting and measurement of higher-level cognitive skills is more vexing. These require more open-ended delivery and answers, and may be more problematic in an entirely virtual environment, notwithstanding the advances in technologies such as wikis, blogs, discussion boards, etc. As with the integration of all technology, merit is based more on the instructional design of the course than on the technology employed in, and of, itself. With this in mind, this study examined the perceptions of online students in an introductory Computer Information Systems course regarding the fostering of various higher-order thinking and team-building skills as a result of the activities, resources and technologies (ART) used in the course.

Evolutionary Training of Hybrid Systems of Recurrent Neural Networks and Hidden Markov Models

Year: 2008 Volume: 2 Issue: 3 891 - 896 Pages

Abstract: We present a hybrid architecture of recurrent neural networks (RNNs) inspired by hidden Markov models (HMMs). We train the hybrid architecture using genetic algorithms to learn and represent dynamical systems. We train the hybrid architecture on a set of deterministic finite-state automata strings and observe the generalization performance of the hybrid architecture when presented with a new set of strings which were not present in the training data set. In this way, we show that the hybrid system of HMM and RNN can learn and represent deterministic finite-state automata. We ran experiments with different sets of population sizes in the genetic algorithm; we also ran experiments to find out which weight initializations were best for training the hybrid architecture. The results show that the hybrid architecture of recurrent neural networks inspired by hidden Markov models can train and represent dynamical systems. The best training and generalization performance is achieved when the hybrid architecture is initialized with random real weight values of range -15 to 15.

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