Search results for: large database of image

Authors: A. Sindhuja, V. Sadasivam

Abstract:

Breast Cancer is the most common malignancy in women and the second leading cause of death for women all over the world. Earlier the detection of cancer, better the treatment. The diagnosis and treatment of the cancer rely on segmentation of Sonoelastographic images. Texture features has not considered for Sonoelastographic segmentation. Sonoelastographic images of 15 patients containing both benign and malignant tumorsare considered for experimentation.The images are enhanced to remove noise in order to improve contrast and emphasize tumor boundary. It is then decomposed into sub-bands using single level Daubechies wavelets varying from single co-efficient to six coefficients. The Grey Level Co-occurrence Matrix (GLCM), Local Binary Pattern (LBP) features are extracted and then selected by ranking it using Sequential Floating Forward Selection (SFFS) technique from each sub-band. The resultant images undergo K-Means clustering and then few post-processing steps to remove the false spots. The tumor boundary is detected from the segmented image. It is proposed that Local Binary Pattern (LBP) from the vertical coefficients of Daubechies wavelet with two coefficients is best suited for segmentation of Sonoelastographic breast images among the wavelet members using one to six coefficients for decomposition. The results are also quantified with the help of an expert radiologist. The proposed work can be used for further diagnostic process to decide if the segmented tumor is benign or malignant.

Keywords: Breast Cancer, Segmentation, Sonoelastography, Tumor Detection.

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Authors: Marinela Mircea

Abstract:

The development of information and communication technology, the increased use of the internet, as well as the effects of the recession within the last years, have lead to the increased use of cloud computing based solutions, also called on-demand solutions. These solutions offer a large number of benefits to organizations as well as challenges and risks, mainly determined by data visualization in different geographic locations on the internet. As far as the specific risks of cloud environment are concerned, data security is still considered a peak barrier in adopting cloud computing. The present study offers an approach upon ensuring the security of cloud data, oriented towards the whole data life cycle. The final part of the study focuses on the assessment of data security in the cloud, this representing the bases in determining the potential losses and the premise for subsequent improvements and continuous learning.

Keywords: cloud computing, data life cycle, data security, security assessment.

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Authors: M. Soryani, N. Rafat

Abstract:

Dealing with hundreds of features in character recognition systems is not unusual. This large number of features leads to the increase of computational workload of recognition process. There have been many methods which try to remove unnecessary or redundant features and reduce feature dimensionality. Besides because of the characteristics of Farsi scripts, it-s not possible to apply other languages algorithms to Farsi directly. In this paper some methods for feature subset selection using genetic algorithms are applied on a Farsi optical character recognition (OCR) system. Experimental results show that application of genetic algorithms (GA) to feature subset selection in a Farsi OCR results in lower computational complexity and enhanced recognition rate.

Keywords: Feature Subset Selection, Genetic Algorithms, Optical Character Recognition.

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Authors: Chiharu Okuma, Jun Murakami, Naoki Yamamoto

Abstract:

In digital signal processing it is important to approximate multi-dimensional data by the method called rank reduction, in which we reduce the rank of multi-dimensional data from higher to lower. For 2-dimennsional data, singular value decomposition (SVD) is one of the most known rank reduction techniques. Additional, outer product expansion expanded from SVD was proposed and implemented for multi-dimensional data, which has been widely applied to image processing and pattern recognition. However, the multi-dimensional outer product expansion has behavior of great computation complex and has not orthogonally between the expansion terms. Therefore we have proposed an alterative method, Third-order Orthogonal Tensor Product Expansion short for 3-OTPE. 3-OTPE uses the power method instead of nonlinear optimization method for decreasing at computing time. At the same time the group of B. D. Lathauwer proposed Higher-Order SVD (HOSVD) that is also developed with SVD extensions for multi-dimensional data. 3-OTPE and HOSVD are similarly on the rank reduction of multi-dimensional data. Using these two methods we can obtain computation results respectively, some ones are the same while some ones are slight different. In this paper, we compare 3-OTPE to HOSVD in accuracy of calculation and computing time of resolution, and clarify the difference between these two methods.

Keywords: Singular value decomposition (SVD), higher-order SVD (HOSVD), higher-order tensor, outer product expansion, power method.

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Authors: Nurcan Tugrul, Nil Baran Acarali, Seyma Kolemen, Emek Moroydor Derun, Sabriye Piskin

Abstract:

Fly ash is a significant waste that is released of thermal power plants and defined as very fine particles that are drifted upward with up taken by the flue gases due to the burning of used coal [1]. The fly-ash is capable of removing organic contaminants in consequence of high carbon content, a large surface area per unit volume and contained heavy metals. Therefore, fly ash is used as an effective coagulant and adsorbent by pelletization [2, 3]. In this study, the possibility of use of fly ash taken from Turkey like low-cost adsorbent for adsorption of zinc ions found in waste water was investigated. The fly ash taken from Turkey was pelletized with bentonite and molass to evaluate the adsorption capaticity. For this purpose; analyses such as sieve analysis, XRD, XRF, FTIR and SEM were performed. As a result, it was seen that pellets prepared from fly ash, bentonite and molass would be used for zinc adsorption.

Keywords: Fly ash, heavy metal, sieve, adsorbent.

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Authors: Vladislav A. Nazukin, Valery G. Avgustinovich, Vakhtang V. Tsatiashvili

Abstract:

The most important part of modern lean low NOx combustors is a premixer where swirlers are often used for intensification of mixing processes and further formation of required flow pattern in combustor liner. Swirling flow leads to formation of complex eddy structures causing flow perturbations. It is able to cause combustion instability. Therefore, at design phase, it is necessary to pay great attention to aerodynamics of premixers. Analysis based on unsteady CFD modeling of swirling flow in production combustor swirler showed presence of large number of different eddy structures that can be conditionally divided into three types relative to its location of origin and a propagation path. Further, features of each eddy type were subsequently defined. Comparison of calculated and experimental pressure fluctuations spectrums verified correctness of computations.

Keywords: DES simulation, swirler, vortical structures.

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Authors: M. Ouassaid, A. Nejmi, M. Cherkaoui, M. Maaroufi

Abstract:

The very nonlinear nature of the generator and system behaviour following a severe disturbance precludes the use of classical linear control technique. In this paper, a new approach of nonlinear control is proposed for transient and steady state stability analysis of a synchronous generator. The control law of the generator excitation is derived from the basis of Lyapunov stability criterion. The overall stability of the system is shown using Lyapunov technique. The application of the proposed controller to simulated generator excitation control under a large sudden fault and wide range of operating conditions demonstrates that the new control strategy is superior to conventional automatic voltage regulator (AVR), and show very promising results.

Keywords: Excitation control, Lyapunov technique, non linearcontrol, synchronous generator, transient stability, voltage regulation.

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Authors: Sérgio S. de Jesus, Edgar Leonardo Martínez, Aulus R.R. Binelli, Aline Santana, Rubens Maciel Filho

Abstract:

The speed profiles, gas holdup (e_G) and global oxygen transfer coefficient (k_La) from a stirred airlift bioreactor using water as the fluid model, was investigated by computational fluid dynamics modeling. The parameters predicted by the computer model were validated with the experimental dates. The CFD results were very close to those obtained experimentally. During the simulation it was verified a prevalent impeller effect at low speeds, propelling a large volume of fluid against the walls of the vessel, which without recirculation, results in low values of e_G and k_La; however, by increasing air velocity, the impeller effect is smaller with the air flow being greater, in the region of the riser, causing fluid recirculation, which explains the increase in e_G and k_La.

Keywords: CFD, Hydrodynamics, Mass transfer, Stirred airlift bioreactor.

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Authors: Buntheng Chhorn, WooYoung Jung

Abstract:

Large-scale swing has been used in entertainment and performance, especially in circus, for a very long time. To increase the safety of this type of structure, a thorough analysis for displacement and bearing stress was performed for an extreme condition where a full cycle swing occurs. Different masses, ranging from 40 kg to 220 kg, and velocities were applied on the swing. Then, based on the solution of differential dynamics equation, swing velocity response to harmonic force was obtained. Moreover, the resistance capacity was estimated based on ACI steel structure design guide. Subsequently, numerical analysis was performed in ABAQUS to obtain the stress on each frame of the swing. Finally, the analysis shows that the expansion of swing structure frame section was required for mass bigger than 150kg.

Keywords: Swing structure, displacement, bearing stress, dynamic loads response, finite element analysis.

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Authors: S. Sukparungsee

Abstract:

Generally, the traditional Shewhart p chart has been developed by for charting the binomial data. This chart has been developed using the normal approximation with condition as low defect level and the small to moderate sample size. In real applications, however, are away from these assumptions due to skewness in the exact distribution. In this paper, a modified Exponentially Weighted Moving Average (EWMA) control chat for detecting a change in binomial data by improving square root transformations, namely ISRT p EWMA control chart. The numerical results show that ISRT p EWMA chart is superior to ISRT p chart for small to moderate shifts, otherwise, the latter is better for large shifts.

Keywords: Number of defects, Exponentially Weighted Moving Average, Average Run Length, Square root transformations.

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Authors: M. Sedighizadeh, A. Rezazadeh

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Based on the component approach, three kinds of dynamic load models, including a single –motor model, a two-motor model and composite load model have been developed for the stability studies of Khuzestan power system. The study results are presented in this paper. Voltage instability is a dynamic phenomenon and therefore requires dynamic representation of the power system components. Industrial loads contain a large fraction of induction machines. Several models of different complexity are available for the description investigations. This study evaluates the dynamic performances of several dynamic load models in combination with the dynamics of a load changing transformer. Case study is steel industrial substation in Khuzestan power systems.

Keywords: Dynamic load, modeling, Voltage Stability.

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Authors: Bachir Chemani, Rachid Halfaoui

Abstract:

The aim of work is to define the distribution density of winding yarn on cylindrical and conical bobbins. It is known that parallel winding gives greater density and more regular distribution, but the unwinding of yarn is much more difficult for following process. The conical spool has an enormous advantage during unwinding and may contain a large amount of yarns, but the density distribution is not regular because of difference in diameters. The variation of specific density over the reel height is explained generally by the sudden change of winding speed due to direction movement variation of yarn. We determined the conditions of uniform winding and developed a calculate model to the change of the specific density of winding wire over entire spool height.

Keywords: Textile, cylindrical bobbins, conical bobbins, parallel winding, cross winding.

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Authors: A. Boudjemai, A. Zafrane, R. Hocine

Abstract:

Honeycomb sandwich panels are increasingly used in the construction of space vehicles because of their outstanding strength, stiffness and light weight properties. However, the use of honeycomb sandwich plates comes with difficulties in the design process as a result of the large number of design variables involved, including composite material design, shape and geometry. Hence, this work deals with the presentation of an optimal design of hexagonal honeycomb sandwich structures subjected to space environment. The optimization process is performed using a set of algorithms including the gravitational search algorithm (GSA). Numerical results are obtained and presented for a set of algorithms. The results obtained by the GSA algorithm are much better compared to other algorithms used in this study.

Keywords: Optimization, Gravitational search algorithm, Genetic algorithm, Honeycomb plate.

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Authors: Sujala.D.Shetty, S.Vadivel, Sakshi Vaghella

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Data mining is the process of sifting through large volumes of data, analyzing data from different perspectives and summarizing it into useful information. One of the widely used desktop applications for data mining is the Weka tool which is nothing but a collection of machine learning algorithms implemented in Java and open sourced under the General Public License (GPL). A web service is a software system designed to support interoperable machine to machine interaction over a network using SOAP messages. Unlike a desktop application, a web service is easy to upgrade, deliver and access and does not occupy any memory on the system. Keeping in mind the advantages of a web service over a desktop application, in this paper we are demonstrating how this Java based desktop data mining application can be implemented as a web service to support data mining across the internet.

Keywords: desktop application, Weka mining, web service

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Authors: Hou Youfu, Wang Daoming, Meng Qingrui

Abstract:

To reveal the temperature field distribution of disc brake in downward belt conveyor, mathematical models of heat transfer for disc brake were established combined with heat transfer theory. Then, the simulation process was stated in detail and the temperature field of disc brake under conditions of dynamic speed and dynamic braking torque was numerically simulated by using ANSYS software. Finally the distribution and variation laws of temperature field in the braking process were analyzed. Results indicate that the maximum surface temperature occurs at a time before the brake end and there exist large temperature gradients in both radial and axial directions, while it is relatively small in the circumferential direction.

Keywords: Downward belt conveyor, Disc brake, Temperature field, Numerical simulation.

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Authors: Chun-Wei Tung, Chyn Liaw, Shinn-Jang Ho, Shinn-Ying Ho

Abstract:

Protein subchloroplast locations are correlated with its functions. In contrast to the large amount of available protein sequences, the information of their locations and functions is less known. The experiment works for identification of protein locations and functions are costly and time consuming. The accurate prediction of protein subchloroplast locations can accelerate the study of functions of proteins in chloroplast. This study proposes a Random Forest based method, ChloroRF, to predict protein subchloroplast locations using interpretable physicochemical properties. In addition to high prediction accuracy, the ChloroRF is able to select important physicochemical properties. The important physicochemical properties are also analyzed to provide insights into the underlying mechanism.

Keywords: Chloroplast, Physicochemical properties, Proteinlocations, Random Forests.

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Authors: Mohamed K. Shahin, Ahmed M. Badawi, Mohamed E. M. Rasmy

Abstract:

Prior research evidenced that unimodal biometric systems have several tradeoffs like noisy data, intra-class variations, restricted degrees of freedom, non-universality, spoof attacks, and unacceptable error rates. In order for the biometric system to be more secure and to provide high performance accuracy, more than one form of biometrics are required. Hence, the need arise for multimodal biometrics using combinations of different biometric modalities. This paper introduces a multimodal biometric system (MMBS) based on fusion of whole dorsal hand geometry and fingerprints that acquires right and left (Rt/Lt) near-infra-red (NIR) dorsal hand geometry (HG) shape and (Rt/Lt) index and ring fingerprints (FP). Database of 100 volunteers were acquired using the designed prototype. The acquired images were found to have good quality for all features and patterns extraction to all modalities. HG features based on the hand shape anatomical landmarks were extracted. Robust and fast algorithms for FP minutia points feature extraction and matching were used. Feature vectors that belong to similar biometric traits were fused using feature fusion methodologies. Scores obtained from different biometric trait matchers were fused using the Min-Max transformation-based score fusion technique. Final normalized scores were merged using the sum of scores method to obtain a single decision about the personal identity based on multiple independent sources. High individuality of the fused traits and user acceptability of the designed system along with its experimental high performance biometric measures showed that this MMBS can be considered for med-high security levels biometric identification purposes.

Keywords: Unimodal, Multi-Modal, Biometric System, NIR Imaging, Dorsal Hand Geometry, Fingerprint, Whole Hands, Feature Extraction, Feature Fusion, Score Fusion

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Authors: Y. Yudin, T. Krasikova, Y. Dorozhko, N. Currle-Linde

Abstract:

Nowadays, HPC, Grid and Cloud systems are evolving very rapidly. However, the development of infrastructure solutions related to HPC is lagging behind. While the existing infrastructure is sufficient for simple cases, many computational problems have more complex requirements.Such computational experiments use different resources simultaneously to start a large number of computational jobs.These resources are heterogeneous. They have different purposes, architectures, performance and used software.Users need a convenient tool that allows to describe and to run complex computational experiments under conditions of HPC environment. This paper introduces a modularworkflow system called SEGL which makes it possible to run complex computational experiments under conditions of a real HPC organization. The system can be used in a great number of organizations, which provide HPC power. Significant requirements to this system are high efficiency and interoperability with the existing HPC infrastructure of the organization without any changes.

Keywords: HPC, Molecular Dynamics, Workflow Languages, Workflow Management.

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Authors: Mohamed Tarek Khadir, Damien Fay, Ahmed Boughrira

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Short term electricity demand forecasts are required by power utilities for efficient operation of the power grid. In a competitive market environment, suppliers and large consumers also require short term forecasts in order to estimate their energy requirements in advance. Electricity demand is influenced (among other things) by the day of the week, the time of year and special periods and/or days such as Ramadhan, all of which must be identified prior to modelling. This identification, known as day-type identification, must be included in the modelling stage either by segmenting the data and modelling each day-type separately or by including the day-type as an input. Day-type identification is the main focus of this paper. A Kohonen map is employed to identify the separate day-types in Algerian data.

Keywords: Day type identification, electricity Load, Kohonenmaps, load forecasting.

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Authors: Zukisa Nante, Wang Zenghui

Abstract:

Face recognition is the problem of identifying or recognizing individuals in an image. This paper investigates a possible method to bring a solution to this problem. The method proposes an amalgamation of Principal Component Analysis (PCA), K-Means clustering, and Convolutional Neural Network (CNN) for a face recognition system. It is trained and evaluated using the ORL dataset. This dataset consists of 400 different faces with 40 classes of 10 face images per class. Firstly, PCA enabled the usage of a smaller network. This reduces the training time of the CNN. Thus, we get rid of the redundancy and preserve the variance with a smaller number of coefficients. Secondly, the K-Means clustering model is trained using the compressed PCA obtained data which select the K-Means clustering centers with better characteristics. Lastly, the K-Means characteristics or features are an initial value of the CNN and act as input data. The accuracy and the performance of the proposed method were tested in comparison to other Face Recognition (FR) techniques namely PCA, Support Vector Machine (SVM), as well as K-Nearest Neighbour (kNN). During experimentation, the accuracy and the performance of our suggested method after 90 epochs achieved the highest performance: 99% accuracy F1-Score, 99% precision, and 99% recall in 463.934 seconds. It outperformed the PCA that obtained 97% and KNN with 84% during the conducted experiments. Therefore, this method proved to be efficient in identifying faces in the images.

Keywords: Face recognition, Principal Component Analysis, PCA, Convolutional Neural Network, CNN, Rectified Linear Unit, ReLU, feature extraction.

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Authors: M. C. Proença

Abstract:

The tools described in this paper enable the location of burned areas where took place the annihilation of natural habitats and establishes a baseline for major changes in forest ecosystems during recovery. Moreover, the result allows the follow up of the surface fuel loading, allowing the evaluation and guidance of restoration measures to remote areas by phased time planning. This case study implements the evaluation of burned areas that suffered successive wildfires in Portugal mainland during the summer of 2017, killing more than 60 people. The goal is to show that this evaluation can be done with remote sense data free of charges in a simple laptop, with open-source software, describing the not-so-simple methodology step by step, to make it accessible for local workers in the areas attained, where the availability of information is essential for the immediate planning of mitigation measures, such as restoring road access, allocate funds for the recovery of human dwellings and assess further needs for restoration of the ecological system. Wildfires also devastate forest ecosystems having a direct impact on vegetation cover and killing or driving away the animal population, besides loss of all crops in rural areas that are essential as local resources. The economic interests are also attained, as the pinewood burned becomes useless for the noblest applications, so its value decreases, and resin extraction ends for several years.

Keywords: Image processing, remote sensing, wildfires, burned areas, SENTINEL-2.

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Authors: I. Turk Cakir, A. Senol, A. T. Tasci, O. Cakir

Abstract:

We study the anomalous WWγ and WWZ couplings by calculating total cross sections of two processes at the LHeC with electron beam energy Ee=140 GeV and the proton beam energy Ep=7 TeV, and at the FCC-ep collider with the polarized electron beam energy Ee=80 GeV and the proton beam energy Ep=50 TeV. At the LHeC with electron beam polarization, we obtain the results for the difference of upper and lower bounds as (0.975, 0.118) and (0.285, 0.009) for the anomalous (Δκγ, λγ) and (Δκz, λz) couplings, respectively. As for FCC-ep collider, these bounds are obtained as (1.101, 0.065) and (0.320, 0.002) at an integrated luminosity of Lint=100 fb^-1.

Keywords: Anomalous Couplings, Future Circular Collider, Large Hadron electron Collider, W-boson and Z-boson.

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Authors: Ghulam Rasool, Nadim Asif

Abstract:

The advent of modern technology shadows its impetus repercussions on successful Legacy systems making them obsolete with time. These systems have evolved the large organizations in major problems in terms of new business requirements, response time, financial depreciation and maintenance. Major difficulty is due to constant system evolution and incomplete, inconsistent and obsolete documents which a legacy system tends to have. The myriad dimensions of these systems can only be explored by incorporating reverse engineering, in this context, is the best method to extract useful artifacts and by exploring these artifacts for reengineering existing legacy systems to meet new requirements of organizations. A case study is conducted on six different type of software systems having source code in different programming languages using the architectural recovery framework.

Keywords: Reverse Engineering, Architecture recovery, Architecture artifacts, Reengineering.

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Authors: M. Marsadek, A. Mohamed

Abstract:

Power system security analysis is the most time demanding process due to large number of possible contingencies that need to be analyzed.  In a power system, any contingency resulting in security violation such as line overload or low voltage may occur for a number of reasons at any time.  To efficiently rank a contingency, both probability and the extent of security violation must be considered so as not to underestimate the risk associated with the contingency. This paper proposed a contingency ranking method that take into account the probabilistic nature of power system and the severity of contingency by using a newly developed method based on risk factor.  The proposed technique is implemented on IEEE 24-bus system.

Keywords: Line overload, low voltage, probability, risk factor, severity.

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Authors: Wang Zijuan, Ding Wenjing, Liu Ran

Abstract:

If an unsteady heat transfer or heat impulse happens in part of the cryogenic pipeline system of large space environment simulation equipment while running in vacuum environment, it will lead to abnormal flow of the cryogenic fluid in the pipeline. When the situation gets worse, the cryogenic fluid in the pipeline will have phase change and a gas block which results in the malfunction of the cryogenic pipeline system. Referring to the structural parameter of a typical cryogenic pipeline system and the basic equation, an analytical model and a calculation model for cryogenic pipeline system can be built. The various factors which influence the thermal resistance of a cryogenic pipeline system can be analyzed and calculated by using the qualitative analysis relation deduced for thermal resistance of pipeline. The research conclusion could provide theoretical support for the design and operation of a cryogenic pipeline system

Keywords: pipeline, vacuum, vapor quality

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Authors: B. Chandra, P. Paul Varghese

Abstract:

Crypto System Identification is one of the challenging tasks in Crypt analysis. The paper discusses the possibility of employing Neural Networks for identification of Cipher Systems from cipher texts. Cascade Correlation Neural Network and Back Propagation Network have been employed for identification of Cipher Systems. Very large collection of cipher texts were generated using a Block Cipher (Enhanced RC6) and a Stream Cipher (SEAL). Promising results were obtained in terms of accuracy using both the Neural Network models but it was observed that the Cascade Correlation Neural Network Model performed better compared to Back Propagation Network.

Keywords: Back Propagation Neural Networks, CascadeCorrelation Neural Network, Crypto systems, Block Cipher, StreamCipher.

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Authors: Kai-Ti Hsu, Hui-Ling Huang, Chun-Wei Tung, Yi-Hsiung Chen, Shinn-Ying Ho

Abstract:

Bioinformatics methods for predicting the T cell coreceptor usage from the array of membrane protein of HIV-1 are investigated. In this study, we aim to propose an effective prediction method for dealing with the three-class classification problem of CXCR4 (X4), CCR5 (R5) and CCR5/CXCR4 (R5X4). We made efforts in investigating the coreceptor prediction problem as follows: 1) proposing a feature set of informative physicochemical properties which is cooperated with SVM to achieve high prediction test accuracy of 81.48%, compared with the existing method with accuracy of 70.00%; 2) establishing a large up-to-date data set by increasing the size from 159 to 1225 sequences to verify the proposed prediction method where the mean test accuracy is 88.59%, and 3) analyzing the set of 14 informative physicochemical properties to further understand the characteristics of HIV-1coreceptors.

Keywords: Coreceptor, genetic algorithm, HIV-1, SVM, physicochemical properties, prediction.

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Authors: Mohammed Gamil Montasser, Angelo Battaglia

Abstract:

Tourism is making its presence felt across the Sultanate of Oman. The story is one of the most recognized phenomena as a sustainable solid growth and is considered a remarkable outcome for any destination. The competitive situation and challenges within the tourism industry worldwide entail a better understanding of the destination position and its image to achieve Oman’s aspiration to retain its international reputation as one of the most desirable destinations in the Middle East. To access general perceptions of Oman’s attributes, their importance and their influences among U.S. tourists, an online survey was conducted with 522 American travelers who have traveled internationally, including non-visitors, virtual-visitors and visitors to Oman. This research involved a total of 36 attributes in the survey. Participants were asked to rate their agreement on how each attribute represented Oman and how important each attribute was for selecting destinations on 5- point Likert Scale. They also indicated if each attribute has a positive, neutral or negative influence on their destination selection. Descriptive statistics and importance performance analysis (IPA) were conducted. IPA illustrated U.S. tourists’ perceptions of Oman’s destination attributes and their importance in destination selection on a matrix with four quadrants, divided by actual mean value in each grid for importance (M=3.51) and performance (M=3.57). Oman tourism organizations and destination managers may use these research findings for future marketing and management efforts toward the U.S. travel market.

Keywords: Analysis of importance and performance, destination attributes, Oman’s position, U.S. tourists.

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Authors: Hazem M. El-Bakry

Abstract:

In this paper, a new technique for fast painting with different colors is presented. The idea of painting relies on applying masks with different colors to the background. Fast painting is achieved by applying these masks in the frequency domain instead of spatial (time) domain. New colors can be generated automatically as a result from the cross correlation operation. This idea was applied successfully for faster specific data (face, object, pattern, and code) detection using neural algorithms. Here, instead of performing cross correlation between the input input data (e.g., image, or a stream of sequential data) and the weights of neural networks, the cross correlation is performed between the colored masks and the background. Furthermore, this approach is developed to reduce the computation steps required by the painting operation. The principle of divide and conquer strategy is applied through background decomposition. Each background is divided into small in size subbackgrounds and then each sub-background is processed separately by using a single faster painting algorithm. Moreover, the fastest painting is achieved by using parallel processing techniques to paint the resulting sub-backgrounds using the same number of faster painting algorithms. In contrast to using only faster painting algorithm, the speed up ratio is increased with the size of the background when using faster painting algorithm and background decomposition. Simulation results show that painting in the frequency domain is faster than that in the spatial domain.

Keywords: Fast Painting, Cross Correlation, Frequency Domain, Parallel Processing

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Authors: Soma Roychowdhury

Abstract:

This paper deals with a periodic-review substitutable inventory system for a finite and an infinite number of periods. Here an upward substitution structure, a substitution of a more costly item by a less costly one, is assumed, with two products. At the beginning of each period, a stochastic demand comes for the first item only, which is quality-wise better and hence costlier. Whenever an arriving demand finds zero inventory of this product, a fraction of unsatisfied customers goes for its substitutable second item. An optimal ordering policy has been derived for each period. The results are illustrated with numerical examples. A sensitivity analysis has been done to examine how sensitive the optimal solution and the maximum profit are to the values of the discount factor, when there is a large number of periods.

Keywords: Multi-period model, inventory, random demand, upward substitution.

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