Search results for: molecular aggregate approach.

Authors: Ramin Halavati, Mansour Jamzad, Mahdieh Soleymani

Abstract:

Persian (Farsi) script is totally cursive and each character is written in several different forms depending on its former and later characters in the word. These complexities make automatic handwriting recognition of Persian a very hard problem and there are few contributions trying to work it out. This paper presents a novel practical approach to online recognition of Persian handwriting which is based on representation of inputs and patterns with very simple visual features and comparison of these simple terms. This recognition approach is tested over a set of Persian words and the results have been quite acceptable when the possible words where unknown and they were almost all correct in cases that the words where chosen from a prespecified list.

Keywords: Image Processing, Pattern Recognition.

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Authors: Heung Seok Chae, Jaegeol Park

Abstract:

Recently, there have been an increasing interest in RFID system and RFID systems have been applied to various applications. Load balancing is a fundamental technique for providing scalability of systems by moving workload from overloaded nodes to under-loaded nodes. This paper presents an approach to adaptive load balancing for RFID middlewares. Workloads of RFID middlewares can have a considerable variation according to the location of the connected RFID readers and can abruptly change at a particular instance. The proposed approach considers those characteristics of RFID middle- wares to provide an efficient load balancing.

Keywords: RFID middleware, Adaptive load balancing.

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Authors: Mohamed Mahmoud Hasan, Hoda M. O. Mokhtar

Abstract:

With the gigantic increment in portable applications use and the spread of positioning and location-aware technologies that we are seeing today, new procedures and methodologies for location-based strategies are required. Location recommendation is one of the highly demanded location-aware applications uniquely with the wide accessibility of social network applications that are location-aware including Facebook check-ins, Foursquare, and others. In this paper, we aim to present a new methodology for location recommendation. The proposed approach coordinates customary spatial traits alongside other essential components including shortest distance, and user interests. We also present another idea namely, "activity trajectory" that represents trajectory that fulfills the set of activities that the user is intrigued to do. The approach dispatched acquaints the related distance value to select trajectory(ies) with minimum cost value (distance) and spatial-area to prune unneeded directions. The proposed calculation utilizes the idea of movement direction to prescribe most comparable N-trajectory(ies) that matches the client's required action design with least voyaging separation. To upgrade the execution of the proposed approach, parallel handling is applied through the employment of a MapReduce based approach. Experiments taking into account genuine information sets were built up and tested for assessing the proposed approach. The exhibited tests indicate how the proposed approach beets different strategies giving better precision and run time.

Keywords: Location-based recommendation, map-reduce, recommendation system, trajectory search.

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Authors: N. Z. A. Hamid, M. S. M. Noorani

Abstract:

This study is focused on the development of prediction models of the Ozone concentration time series. Prediction model is built based on chaotic approach. Firstly, the chaotic nature of the time series is detected by means of phase space plot and the Cao method. Then, the prediction model is built and the local linear approximation method is used for the forecasting purposes. Traditional prediction of autoregressive linear model is also built. Moreover, an improvement in local linear approximation method is also performed. Prediction models are applied to the hourly Ozone time series observed at the benchmark station in Malaysia. Comparison of all models through the calculation of mean absolute error, root mean squared error and correlation coefficient shows that the one with improved prediction method is the best. Thus, chaotic approach is a good approach to be used to develop a prediction model for the Ozone concentration time series.

Keywords: Chaotic approach, phase space, Cao method, local linear approximation method.

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Authors: Kyrre M Begnum, Matthew Disney

Abstract:

Virtualization and high performance computing have been discussed from a performance perspective in recent publications. We present and discuss a flexible and efficient approach to the management of virtual clusters. A virtual machine management tool is extended to function as a fabric for cluster deployment and management. We show how features such as saving the state of a running cluster can be used to avoid disruption. We also compare our approach to the traditional methods of cluster deployment and present benchmarks which illustrate the efficiency of our approach.

Keywords: Cluster management, clusters, high-performance, virtual machines, Xen

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Authors: Liudmyla Koliechkina, Olena Dvirna

Abstract:

The statement of the multi-objective optimization problem on combinatorial configurations is formulated, and the approach to its solution is proposed. The problem is of interest as a combinatorial optimization one with many criteria, which is a model of many applied tasks. The approach to solving the multi-objective optimization problem on combinatorial configurations consists of two stages; the first is the reduction of the multi-objective problem to the single criterion based on existing multi-objective optimization methods, the second stage solves the directly replaced single criterion combinatorial optimization problem by the horizontal combinatorial method. This approach provides the optimal solution to the multi-objective optimization problem on combinatorial configurations, taking into account additional restrictions for a finite number of steps.

Keywords: Discrete set, linear combinatorial optimization, multi-objective optimization, multipermutation, Pareto solutions, partial permutation set, permutation, structural graph.

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Authors: I. Lolic, P. Soric, M. Cizmesija

Abstract:

Based on Business and Consumer Survey (BCS) data, the European Commission (EC) regularly publishes the monthly Economic Sentiment Indicator (ESI) for each EU member state. ESI is conceptualized as a leading indicator, aimed ad tracking the overall economic activity. In calculating ESI, the EC employs arbitrarily chosen weights on 15 BCS response balances. This paper raises the predictive quality of ESI by applying nonlinear programming to find such weights that maximize the correlation coefficient of ESI and year-on-year GDP growth. The obtained results show that the highest weights are assigned to the response balances of industrial sector questions, followed by questions from the retail trade sector. This comes as no surprise since the existing literature shows that the industrial production is a plausible proxy for the overall Croatian economic activity and since Croatian GDP is largely influenced by the aggregate personal consumption.

Keywords: Business and Consumer Survey, Economic Sentiment Indicator, Leading Indicator, Nonlinear Optimization with Constraints.

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Authors: Costin Pribeanu

Abstract:

The model-based approach to user interface design relies on developing separate models capturing various aspects about users, tasks, application domain, presentation and dialog structures. This paper presents a task modeling approach for user interface design and aims at exploring mappings between task, domain and presentation models. The basic idea of our approach is to identify typical configurations in task and domain models and to investigate how they relate each other. A special emphasis is put on applicationspecific functions and mappings between domain objects and operational task structures. In this respect, we will address two layers in task decomposition: a functional (planning) layer and an operational layer.

Keywords: task modeling, user interface design, unit tasks, basic tasks, operational task model.

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Authors: Yinggan Tang, Xinping Guan

Abstract:

Color image segmentation can be considered as a cluster procedure in feature space. k-means and its adaptive version, i.e. competitive learning approach are powerful tools for data clustering. But k-means and competitive learning suffer from several drawbacks such as dead-unit problem and need to pre-specify number of cluster. In this paper, we will explore to use competitive and cooperative learning approach to perform color image segmentation. In competitive and cooperative learning approach, seed points not only compete each other, but also the winner will dynamically select several nearest competitors to form a cooperative team to adapt to the input together, finally it can automatically select the correct number of cluster and avoid the dead-units problem. Experimental results show that CCL can obtain better segmentation result.

Keywords: Color image segmentation, competitive learning, cluster, k-means algorithm, competitive and cooperative learning.

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Authors: Ivan C. Mustakerov, Daniela I. Borissova

Abstract:

The paper proposes an approach for design of modular systems based on original technique for modeling and formulation of combinatorial optimization problems. The proposed approach is described on the example of personal computer configuration design. It takes into account the existing compatibility restrictions between the modules and can be extended and modified to reflect different functional and users- requirements. The developed design modeling technique is used to formulate single objective nonlinear mixedinteger optimization tasks. The practical applicability of the developed approach is numerically tested on the basis of real modules data. Solutions of the formulated optimization tasks define the optimal configuration of the system that satisfies all compatibility restrictions and user requirements.

Keywords: Constrained discrete combinatorial choice, modular systems design, optimization problem, PC configuration.

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Authors: Fei Hao, Hai Wang

Abstract:

One of research issues in social network analysis is to evaluate the position/importance of users in social networks. As the information diffusion in social network is evolving, it seems difficult to evaluate the importance of users using traditional approaches. In this paper, we propose an evaluation approach for user importance with fractal view in social networks. In this approach, the global importance (Fractal Importance) and the local importance (Topological Importance) of nodes are considered. The basic idea is that the bigger the product of fractal importance and topological importance of a node is, the more important of the node is. We devise the algorithm called TFRank corresponding to the proposed approach. Finally, we evaluate TFRank by experiments. Experimental results demonstrate our TFRank has the high correlations with PageRank algorithm and potential ranking algorithm, and it shows the effectiveness and advantages of our approach.

Keywords: TFRank, Fractal Importance, Topological Importance, Social Network

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Authors: Khalid M. Aamir, Mohammad A. Maud

Abstract:

Power Spectral Density (PSD) computed by taking the Fourier transform of auto-correlation functions (Wiener-Khintchine Theorem) gives better result, in case of noisy data, as compared to the Periodogram approach. However, the computational complexity of Wiener-Khintchine approach is more than that of the Periodogram approach. For the computation of short time Fourier transform (STFT), this problem becomes even more prominent where computation of PSD is required after every shift in the window under analysis. In this paper, recursive version of the Wiener-Khintchine theorem has been derived by using the sliding DFT approach meant for computation of STFT. The computational complexity of the proposed recursive Wiener-Khintchine algorithm, for a window size of N, is O(N).

Keywords: Power Spectral Density (PSD), Wiener-KhintchineTheorem, Periodogram, Short Time Fourier Transform (STFT), TheSliding DFT.

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Authors: Shengman Zhao, Yang Yu, Shenghui Cui

Abstract:

Using logarithmic mean Divisia decomposition technique, this paper analyzes the change in industrial energy intensity of Fujian Province in China, based on data sets of added value and energy consumption for 35 selected industrial sub-sectors from 1999 to 2009. The change in industrial energy intensity is decomposed into intensity effect and structure effect. Results show that the industrial energy intensity of Fujian Province has achieved a reduction of 51% over the past ten years. The structural change, a shift in the mix of industrial sub-sectors, made overwhelming contribution to the reduction. The impact of energy efficiency’s improvement was relatively small. However, the aggregate industrial energy intensity was very sensitive to both the changes in energy intensity and in production share of energy-intensive sub-sectors, such as production and supply of electric power, steam and hot water. Pathway to reduce industrial energy intensity for energy conservation in Fujian Province is proposed in the end.

Keywords: Decomposition analysis, energy intensity, Fujian Province, industry.

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Authors: Emma K. Sales

Abstract:

Durian is the flagship fruit of Mindanao and there is an abundance of several cultivars with many confusing identities/ names. The project was conducted to develop procedure for reliable and rapid detection and sorting of durian planting materials. Moreover, it is also aimed to establish specific genetic or DNA markers for routine testing and authentication of durian cultivars in question. The project developed molecular procedures for routine testing. SSR primers were also screened and identified for their utility in discriminating durian cultivars collected. Results of the study showed the following accomplishments: 1. Twenty (29) SSR primers were selected and identified based on their ability to discriminate durian cultivars, 2. Optimized and established standard procedure for identification and authentication of Durian cultivars 3. Genetic profile of durian is now available at Biotech Unit Our results demonstrate the relevance of using molecular techniques in evaluating and identifying durian clones. The most polymorphic primers tested in this study could be useful tools for detecting variation even at the early stage of the plant especially for commercial purposes. The process developed combines the efficiency of the microsatellites development process with the optimization of non-radioactive detection process resulting in a user-friendly protocol that can be performed in two (2) weeks and easily incorporated into laboratories about to start microsatellite development projects. This can be of great importance to extend microsatellite analyses to other crop species where minimal genetic information is currently available. With this, the University can now be a service laboratory for routine testing and authentication of durian clones.

Keywords: DNA, SSR Analysis, genotype, genetic diversity, cultivars.

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Authors: Ahmad T. Al-Taani, Abdullah M. AL-Issa

Abstract:

In this work we propose a novel Steganographic method for hiding information within the spatial domain of the gray scale image. The proposed approach works by dividing the cover into blocks of equal sizes and then embeds the message in the edge of the block depending on the number of ones in left four bits of the pixel. The proposed approach is tested on a database consists of 100 different images. Experimental results, compared with other methods, showed that the proposed approach hide more large information and gave a good visual quality stego-image that can be seen by human eyes.

Keywords: Data Embedding, Cryptography, Watermarking, Steganography, Least Significant Bit, Information Hiding.

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Authors: Bhed Bahadur Bista, Danda B. Rawat

Abstract:

In this paper, we investigate multihop polling and data gathering schemes in layered sensor networks in order to extend the life time of the networks. A network consists of three layers. The lowest layer contains sensors. The middle layer contains so called super nodes with higher computational power, energy supply and longer transmission range than sensor nodes. The top layer contains a sink node. A node in each layer controls a number of nodes in lower layer by polling mechanism to gather data. We will present four types of data gathering schemes: intermediate nodes do not queue data packet, queue single packet, queue multiple packets and aggregate data, to see which data gathering scheme is more energy efficient for multihop polling in layered sensor networks.

Keywords: layered sensor network, polling, data gatheringschemes.

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Authors: J. P. Dubois

Abstract:

Pulse code modulation is a widespread technique in digital communication with significant impact on existing modern and proposed future communication technologies. Its widespread utilization is due to its simplicity and attractive spectral characteristics. In this paper, we present a new approach to the spectral analysis of PCM signals using Riemann-Stieltjes integrals, which is very accurate for high bit rates. This approach can serve as a model for similar spectral analysis of other competing modulation schemes.

Keywords: Coding, discrete Fourier, power spectral density, pulse code modulation, Riemann-Stieltjes integrals.

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Authors: Keun-Chang Kwak

Abstract:

This paper is concerned with motion recognition based fuzzy WP(Wavelet Packet) feature extraction approach from Vicon physical data sets. For this purpose, we use an efficient fuzzy mutual-information-based WP transform for feature extraction. This method estimates the required mutual information using a novel approach based on fuzzy membership function. The physical action data set includes 10 normal and 10 aggressive physical actions that measure the human activity. The data have been collected from 10 subjects using the Vicon 3D tracker. The experiments consist of running, seating, and walking as physical activity motion among various activities. The experimental results revealed that the presented feature extraction approach showed good recognition performance.

Keywords: Motion recognition, fuzzy wavelet packet, Vicon physical data.

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Authors: Florin Leon, Silvia Curteanu

Abstract:

Developing complete mechanistic models for polymerization reactors is not easy, because complex reactions occur simultaneously; there is a large number of kinetic parameters involved and sometimes the chemical and physical phenomena for mixtures involving polymers are poorly understood. To overcome these difficulties, empirical models based on sampled data can be used instead, namely regression methods typical of machine learning field. They have the ability to learn the trends of a process without any knowledge about its particular physical and chemical laws. Therefore, they are useful for modeling complex processes, such as the free radical polymerization of methyl methacrylate achieved in a batch bulk process. The goal is to generate accurate predictions of monomer conversion, numerical average molecular weight and gravimetrical average molecular weight. This process is associated with non-linear gel and glass effects. For this purpose, an adaptive sampling technique is presented, which can select more samples around the regions where the values have a higher variation. Several machine learning methods are used for the modeling and their performance is compared: support vector machines, k-nearest neighbor, k-nearest neighbor and random forest, as well as an original algorithm, large margin nearest neighbor regression. The suggested method provides very good results compared to the other well-known regression algorithms.

Keywords: Adaptive sampling, batch bulk methyl methacrylate polymerization, large margin nearest neighbor regression, machine learning.

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Authors: Mohd Fairuz Iskandar Othman, Nazrulazhar Bahaman, Zulkiflee Muslim, Faizal Abdollah

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This paper discusses a curriculum approach that will give emphasis on practical portions of teaching network security subjects in information and communication technology courses. As we are well aware, the need to use a practice and application oriented approach in education is paramount. Research on active learning and cooperative groups have shown that students grasps more and have more tendency towards obtaining and realizing soft skills like leadership, communication and team work as opposed to the more traditional theory and exam based teaching and learning. While this teaching and learning paradigm is relatively new in Malaysia, it has been practiced widely in the West. This paper examines a certain approach whereby students learning wireless security are divided into and work in small and manageable groups where there will be 2 teams which consist of black hat and white hat teams. The former will try to find and expose vulnerabilities in a wireless network while the latter will try their best to prevent such attacks on their wireless networks using hardware, software, design and enforcement of security policy and etc. This paper will try to show that the approach taken plus the use of relevant and up to date software and hardware and with suitable environment setting will hopefully expose students to a more fruitful outcome in terms of understanding of concepts, theories and their motivation to learn.

Keywords: Curriculum approach, wireless networks, wirelesssecurity.

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Authors: Kasthurirangan Gopalakrishnan, Naga Shashidhar

Abstract:

The mechanical properties of granular solids are dependent on the flow of stresses from one particle to another through inter-particle contact. Although some experimental methods have been used to study the inter-particle contacts in the past, preliminary work with these techniques indicated that they do not have the necessary resolution to distinguish between those contacts that transmit the load and those that do not, especially for systems with a wide distribution of particle sizes. In this research, computer simulations are used to study the nature and distribution of contacts in a compact with wide particle size distribution, representative of aggregate size distribution used in asphalt pavement construction. The packing fraction, the mean number of contacts and the distribution of contacts were studied for different scenarios. A methodology to distinguish and compute the fraction of load-bearing particles and the fraction of space-filling particles (particles that do not transmit any force) is needed for further investigation.

Keywords: Computer simulation, three-dimensional particlepacking, coordination number, asphalt concrete, aggregates.

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Authors: Mohamed Abdel Fattah, Fuji Ren

Abstract:

This work proposes an approach to address automatic text summarization. This approach is a trainable summarizer, which takes into account several features, including sentence position, positive keyword, negative keyword, sentence centrality, sentence resemblance to the title, sentence inclusion of name entity, sentence inclusion of numerical data, sentence relative length, Bushy path of the sentence and aggregated similarity for each sentence to generate summaries. First we investigate the effect of each sentence feature on the summarization task. Then we use all features score function to train genetic algorithm (GA) and mathematical regression (MR) models to obtain a suitable combination of feature weights. The proposed approach performance is measured at several compression rates on a data corpus composed of 100 English religious articles. The results of the proposed approach are promising.

Keywords: Automatic Summarization, Genetic Algorithm, Mathematical Regression, Text Features.

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Authors: D. Fodorean, D.C. Popa, F. Jurca, M. Ruba

Abstract:

the paper presents the optimization results for several electrical machines dedicated for powered electric wheel-chairs. The optimization, using the Hook-Jeeves algorithm, was employed based on a design approach which takes into consideration the road conditions. Also, through numerical simulations (based on finite element method), the analytical approach was validated. The optimization approach gave satisfactory results and the best suited variant was chosen for the motorization of the wheel-chair.

Keywords: electrical machines, numerical validation, optimization, electric wheel chair.

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Authors: Mehran Yazdi, Kazem Gheysari

Abstract:

In this paper, we propose an approach for the classification of fingerprint databases. It is based on the fact that a fingerprint image is composed of regular texture regions that can be successfully represented by co-occurrence matrices. So, we first extract the features based on certain characteristics of the cooccurrence matrix and then we use these features to train a neural network for classifying fingerprints into four common classes. The obtained results compared with the existing approaches demonstrate the superior performance of our proposed approach.

Keywords: Biometrics, fingerprint classification, gray level cooccurrence matrix, regular texture representation.

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Authors: Mahamed G.H. Omran, Andries P Engelbrecht, Ayed Salman

Abstract:

A new dynamic clustering approach (DCPSO), based on Particle Swarm Optimization, is proposed. This approach is applied to unsupervised image classification. The proposed approach automatically determines the "optimum" number of clusters and simultaneously clusters the data set with minimal user interference. The algorithm starts by partitioning the data set into a relatively large number of clusters to reduce the effects of initial conditions. Using binary particle swarm optimization the "best" number of clusters is selected. The centers of the chosen clusters is then refined via the Kmeans clustering algorithm. The experiments conducted show that the proposed approach generally found the "optimum" number of clusters on the tested images.

Keywords: Clustering Validation, Particle Swarm Optimization, Unsupervised Clustering, Unsupervised Image Classification.

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Authors: Costin Pribeanu

Abstract:

The model-based approach to user interface design relies on developing separate models that are capturing various aspects about users, tasks, application domain, presentation and dialog representations. This paper presents a task modeling approach for user interface design and aims at exploring the mappings between task, domain and presentation models. The basic idea of our approach is to identify typical configurations in task and domain models and to investigate how they relate each other. A special emphasis is put on application-specific functions and mappings between domain objects and operational task structures. In this respect, we will distinguish between three layers in the task decomposition: a functional layer, a planning layer, and an operational layer.

Keywords: task modeling, user interface design, unit tasks, basic tasks, operational task model

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Authors: Anurag Jain, Rajneesh Kumar

Abstract:

Cloud computing is the outcome of rapid growth of internet. Due to elastic nature of cloud computing and unpredictable behavior of user, load balancing is the major issue in cloud computing paradigm. An efficient load balancing technique can improve the performance in terms of efficient resource utilization and higher customer satisfaction. Load balancing can be implemented through task scheduling, resource allocation and task migration. Various parameters to analyze the performance of load balancing approach are response time, cost, data processing time and throughput. This paper demonstrates a two level load balancer approach by combining join idle queue and join shortest queue approach. Authors have used cloud analyst simulator to test proposed two level load balancer approach. The results are analyzed and compared with the existing algorithms and as observed, proposed work is one step ahead of existing techniques.

Keywords: Cloud Analyst, Cloud Computing, Join Idle Queue, Join Shortest Queue, Load balancing, Task Scheduling.

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Authors: Abder-Rahman Ali, Antoine Vacavant, Manuel Grand-Brochier, Adélaïde Albouy-Kissi, Jean-Yves Boire

Abstract:

In this paper, we present a new segmentation approach for liver lesions in regions of interest within MRI (Magnetic Resonance Imaging). This approach, based on a two-cluster Fuzzy CMeans methodology, considers the parameter variable compactness to handle uncertainty. Fine boundaries are detected by a local recursive merging of ambiguous pixels with a sequential forward floating selection with Zernike moments. The method has been tested on both synthetic and real images. When applied on synthetic images, the proposed approach provides good performance, segmentations obtained are accurate, their shape is consistent with the ground truth, and the extracted information is reliable. The results obtained on MR images confirm such observations. Our approach allows, even for difficult cases of MR images, to extract a segmentation with good performance in terms of accuracy and shape, which implies that the geometry of the tumor is preserved for further clinical activities (such as automatic extraction of pharmaco-kinetics properties, lesion characterization, etc.).

Keywords: Defuzzification, floating search, fuzzy clustering, Zernike moments.

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Authors: Ghalem Belalem, Yahya Slimani

Abstract:

Large scale systems such as computational Grid is a distributed computing infrastructure that can provide globally available network resources. The evolution of information processing systems in Data Grid is characterized by a strong decentralization of data in several fields whose objective is to ensure the availability and the reliability of the data in the reason to provide a fault tolerance and scalability, which cannot be possible only with the use of the techniques of replication. Unfortunately the use of these techniques has a height cost, because it is necessary to maintain consistency between the distributed data. Nevertheless, to agree to live with certain imperfections can improve the performance of the system by improving competition. In this paper, we propose a multi-layer protocol combining the pessimistic and optimistic approaches conceived for the data consistency maintenance in large scale systems. Our approach is based on a hierarchical representation model with tree layers, whose objective is with double vocation, because it initially makes it possible to reduce response times compared to completely pessimistic approach and it the second time to improve the quality of service compared to an optimistic approach.

Keywords: Data Grid, replication, consistency, optimistic approach, pessimistic approach.

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Authors: R. K. Chaurasiya, N. D. Londhe, S. Ghosh

Abstract:

The study of the electrical signals produced by neural activities of human brain is called Electroencephalography. In this paper, we propose an automatic and efficient EEG signal classification approach. The proposed approach is used to classify the EEG signal into two classes: epileptic seizure or not. In the proposed approach, we start with extracting the features by applying Discrete Wavelet Transform (DWT) in order to decompose the EEG signals into sub-bands. These features, extracted from details and approximation coefficients of DWT sub-bands, are used as input to Principal Component Analysis (PCA). The classification is based on reducing the feature dimension using PCA and deriving the supportvectors using Support Vector Machine (SVM). The experimental are performed on real and standard dataset. A very high level of classification accuracy is obtained in the result of classification.

Keywords: Discrete Wavelet Transform, Electroencephalogram, Pattern Recognition, Principal Component Analysis, Support Vector Machine.

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