Search results for: Ensemble Based Threshold Accepting
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 11449

Search results for: Ensemble Based Threshold Accepting

11239 Fault Detection and Isolation in Attitude Control Subsystem of Spacecraft Formation Flying Using Extended Kalman Filters

Authors: S. Ghasemi, K. Khorasani

Abstract:

In this paper, the problem of fault detection and isolation in the attitude control subsystem of spacecraft formation flying is considered. In order to design the fault detection method, an extended Kalman filter is utilized which is a nonlinear stochastic state estimation method. Three fault detection architectures, namely, centralized, decentralized, and semi-decentralized are designed based on the extended Kalman filters. Moreover, the residual generation and threshold selection techniques are proposed for these architectures.

Keywords: Formation flight of satellites, extended Kalman filter, fault detection and isolation, actuator fault.

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11238 An Optimal Control Method for Reconstruction of Topography in Dam-Break Flows

Authors: Alia Alghosoun, Nabil El Moçayd, Mohammed Seaid

Abstract:

Modeling dam-break flows over non-flat beds requires an accurate representation of the topography which is the main source of uncertainty in the model. Therefore, developing robust and accurate techniques for reconstructing topography in this class of problems would reduce the uncertainty in the flow system. In many hydraulic applications, experimental techniques have been widely used to measure the bed topography. In practice, experimental work in hydraulics may be very demanding in both time and cost. Meanwhile, computational hydraulics have served as an alternative for laboratory and field experiments. Unlike the forward problem, the inverse problem is used to identify the bed parameters from the given experimental data. In this case, the shallow water equations used for modeling the hydraulics need to be rearranged in a way that the model parameters can be evaluated from measured data. However, this approach is not always possible and it suffers from stability restrictions. In the present work, we propose an adaptive optimal control technique to numerically identify the underlying bed topography from a given set of free-surface observation data. In this approach, a minimization function is defined to iteratively determine the model parameters. The proposed technique can be interpreted as a fractional-stage scheme. In the first stage, the forward problem is solved to determine the measurable parameters from known data. In the second stage, the adaptive control Ensemble Kalman Filter is implemented to combine the optimality of observation data in order to obtain the accurate estimation of the topography. The main features of this method are on one hand, the ability to solve for different complex geometries with no need for any rearrangements in the original model to rewrite it in an explicit form. On the other hand, its achievement of strong stability for simulations of flows in different regimes containing shocks or discontinuities over any geometry. Numerical results are presented for a dam-break flow problem over non-flat bed using different solvers for the shallow water equations. The robustness of the proposed method is investigated using different numbers of loops, sensitivity parameters, initial samples and location of observations. The obtained results demonstrate high reliability and accuracy of the proposed techniques.

Keywords: Optimal control, ensemble Kalman Filter, topography reconstruction, data assimilation, shallow water equations.

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11237 Just-In-Time Implementation Status in the Middle East Industry

Authors: Rami H. Fouad

Abstract:

The purpose of this study is to identify and evaluate the scale of implementation of Just-In-Time (JIT) in the different industrial sectors in the Middle East. This study analyzes the empirical data collected by a questionnaire survey distributed to companies in three main industrial sectors in the Middle East, which are: food, chemicals and fabrics. The following main hypotheses is formulated and tested: (The requirements of JIT application differ according to the type of industrial sector).Descriptive statistics and Box plot analysis were used to examine the hypotheses. This study indicates a reasonable evidence for accepting the main hypotheses. It reveals that there is no standard way to adopt JIT as a production system. But each industrial sector should concentrate in the investment on critical requirements that differ according to the nature and strategy of production followed in that sector.

Keywords: Just-In-Time, JIT, Questionnaire, Types of Industrial Sectors.

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11236 Watermarking Scheme for Color Images using Wavelet Transform based Texture Properties and Secret Sharing

Authors: Nagaraj V. Dharwadkar, B.B.Amberker

Abstract:

In this paper, a new secure watermarking scheme for color image is proposed. It splits the watermark into two shares using (2, 2)- threshold Visual Cryptography Scheme (V CS) with Adaptive Order Dithering technique and embeds one share into high textured subband of Luminance channel of the color image. The other share is used as the key and is available only with the super-user or the author of the image. In this scheme only the super-user can reveal the original watermark. The proposed scheme is dynamic in the sense that to maintain the perceptual similarity between the original and the watermarked image the selected subband coefficients are modified by varying the watermark scaling factor. The experimental results demonstrate the effectiveness of the proposed scheme. Further, the proposed scheme is able to resist all common attacks even with strong amplitude.

Keywords: VCS, Dithering, HVS, DWT.

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11235 Detecting Abnormal ECG Signals Utilising Wavelet Transform and Standard Deviation

Authors: Dejan Stantic, Jun Jo

Abstract:

ECG contains very important clinical information about the cardiac activities of the heart. Often the ECG signal needs to be captured for a long period of time in order to identify abnormalities in certain situations. Such signal apart of a large volume often is characterised by low quality due to the noise and other influences. In order to extract features in the ECG signal with time-varying characteristics at first need to be preprocessed with the best parameters. Also, it is useful to identify specific parts of the long lasting signal which have certain abnormalities and to direct the practitioner to those parts of the signal. In this work we present a method based on wavelet transform, standard deviation and variable threshold which achieves 100% accuracy in identifying the ECG signal peaks and heartbeat as well as identifying the standard deviation, providing a quick reference to abnormalities.

Keywords: Electrocardiogram-ECG, Arrhythmia, Signal Processing, Wavelet Transform, Standard Deviation

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11234 Bright–Dark Pulses in Nonlinear Polarisation Rotation Based Erbium-Doped Fiber Laser

Authors: R. Z. R. R. Rosdin, N. M. Ali, S. W. Harun, H. Arof

Abstract:

We have experimentally demonstrated bright-dark pulses in a nonlinear polarization rotation (NPR) based mode-locked Erbium-doped fiber laser (EDFL) with a long cavity configuration. Bright–dark pulses could be achieved when the laser works in the passively mode-locking regime and the net group velocity dispersion is quite anomalous. The EDFL starts to generate a bright pulse train with degenerated dark pulse at the mode-locking threshold pump power of 35.09 mW by manipulating the polarization states of the laser oscillation modes using a polarization controller (PC). A split bright–dark pulse is generated when further increasing the pump power up to 37.95 mW. Stable bright pulses with no obvious evidence of a dark pulse can also be generated when further adjusting PC and increasing the pump power up to 52.19 mW. At higher pump power of 54.96 mW, a new form of bright-dark pulse emission was successfully identified with the repetition rate of 29 kHz. The bright and dark pulses have a duration of 795.5 ns and 640 ns, respectively.

Keywords: Erbium-doped fiber laser, Nonlinear polarization rotation, bright-dark pulse.

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11233 Analysis and Evaluation of the Public Responses to Traffic Congestion Pricing Schemes in Urban Streets

Authors: Saeed Sayyad Hagh Shomar

Abstract:

Traffic congestion pricing in urban streets is one of the most suitable options for solving the traffic problems and environment pollutions in the cities of the country. Unlike its acceptable outcomes, there are problems concerning the necessity to pay by the mass. Regarding the fact that public response in order to succeed in this strategy is so influential, studying their response and behavior to get the feedback and improve the strategies is of great importance. In this study, a questionnaire was used to examine the public reactions to the traffic congestion pricing schemes at the center of Tehran metropolis and the factors involved in people’s decision making in accepting or rejecting the congestion pricing schemes were assessed based on the data obtained from the questionnaire as well as the international experiences. Then, by analyzing and comparing the schemes, guidelines to reduce public objections to them are discussed. The results of reviewing and evaluating the public reactions show that all the pros and cons must be considered to guarantee the success of these projects. Consequently, with targeted public education and consciousness-raising advertisements, prior to initiating a scheme and ensuring the mechanism of the implementation after the start of the project, the initial opposition is reduced and, with the gradual emergence of the real and tangible benefits of its implementation, users’ satisfaction will increase.

Keywords: Demand management, international experiences, traffic congestion pricing, public acceptance, public objection.

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11232 A Rule-based Approach for Anomaly Detection in Subscriber Usage Pattern

Authors: Rupesh K. Gopal, Saroj K. Meher

Abstract:

In this report we present a rule-based approach to detect anomalous telephone calls. The method described here uses subscriber usage CDR (call detail record) data sampled over two observation periods: study period and test period. The study period contains call records of customers- non-anomalous behaviour. Customers are first grouped according to their similar usage behaviour (like, average number of local calls per week, etc). For customers in each group, we develop a probabilistic model to describe their usage. Next, we use maximum likelihood estimation (MLE) to estimate the parameters of the calling behaviour. Then we determine thresholds by calculating acceptable change within a group. MLE is used on the data in the test period to estimate the parameters of the calling behaviour. These parameters are compared against thresholds. Any deviation beyond the threshold is used to raise an alarm. This method has the advantage of identifying local anomalies as compared to techniques which identify global anomalies. The method is tested for 90 days of study data and 10 days of test data of telecom customers. For medium to large deviations in the data in test window, the method is able to identify 90% of anomalous usage with less than 1% false alarm rate.

Keywords: Subscription fraud, fraud detection, anomalydetection, maximum likelihood estimation, rule based systems.

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11231 Improving Flash Flood Forecasting with a Bayesian Probabilistic Approach: A Case Study on the Posina Basin in Italy

Authors: Zviad Ghadua, Biswa Bhattacharya

Abstract:

The Flash Flood Guidance (FFG) provides the rainfall amount of a given duration necessary to cause flooding. The approach is based on the development of rainfall-runoff curves, which helps us to find out the rainfall amount that would cause flooding. An alternative approach, mostly experimented with Italian Alpine catchments, is based on determining threshold discharges from past events and on finding whether or not an oncoming flood has its magnitude more than some critical discharge thresholds found beforehand. Both approaches suffer from large uncertainties in forecasting flash floods as, due to the simplistic approach followed, the same rainfall amount may or may not cause flooding. This uncertainty leads to the question whether a probabilistic model is preferable over a deterministic one in forecasting flash floods. We propose the use of a Bayesian probabilistic approach in flash flood forecasting. A prior probability of flooding is derived based on historical data. Additional information, such as antecedent moisture condition (AMC) and rainfall amount over any rainfall thresholds are used in computing the likelihood of observing these conditions given a flash flood has occurred. Finally, the posterior probability of flooding is computed using the prior probability and the likelihood. The variation of the computed posterior probability with rainfall amount and AMC presents the suitability of the approach in decision making in an uncertain environment. The methodology has been applied to the Posina basin in Italy. From the promising results obtained, we can conclude that the Bayesian approach in flash flood forecasting provides more realistic forecasting over the FFG.

Keywords: Flash flood, Bayesian, flash flood guidance, FFG, forecasting, Posina.

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11230 Efficient Signal Detection Using QRD-M Based On Channel Condition in MIMO-OFDM System

Authors: Jae-Jeong Kim, Ki-Ro Kim, Hyoung-Kyu Song

Abstract:

In this paper, we propose an efficient signal detector that switches M parameter of QRD-M detection scheme is proposed for MIMO-OFDM system. The proposed detection scheme calculates the threshold by 1-norm condition number and then switches M parameter of QRD-M detection scheme according to channel information. If channel condition is bad, the parameter M is set to high value to increase the accuracy of detection. If channel condition is good, the parameter M is set to low value to reduce complexity of detection. Therefore, the proposed detection scheme has better tradeoff between BER performance and complexity than the conventional detection scheme. The simulation result shows that the complexity of proposed detection scheme is lower than QRD-M detection scheme with similar BER performance.

Keywords: MIMO-OFDM, QRD-M, Channel condition.

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11229 Skin Detection using Histogram depend on the Mean Shift Algorithm

Authors: Soo- Young Ye, Ki-Gon Nam, Ki-Won Byun

Abstract:

In this paper, we were introduces a skin detection method using a histogram approximation based on the mean shift algorithm. The proposed method applies the mean shift procedure to a histogram of a skin map of the input image, generated by comparison with standard skin colors in the CbCr color space, and divides the background from the skin region by selecting the maximum value according to brightness level. The proposed method detects the skin region using the mean shift procedure to determine a maximum value that becomes the dividing point, rather than using a manually selected threshold value, as in existing techniques. Even when skin color is contaminated by illumination, the procedure can accurately segment the skin region and the background region. The proposed method may be useful in detecting facial regions as a pretreatment for face recognition in various types of illumination.

Keywords: Skin region detection, mean shift, histogram approximation.

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11228 Improved Segmentation of Speckled Images Using an Arithmetic-to-Geometric Mean Ratio Kernel

Authors: J. Daba, J. Dubois

Abstract:

In this work, we improve a previously developed segmentation scheme aimed at extracting edge information from speckled images using a maximum likelihood edge detector. The scheme was based on finding a threshold for the probability density function of a new kernel defined as the arithmetic mean-to-geometric mean ratio field over a circular neighborhood set and, in a general context, is founded on a likelihood random field model (LRFM). The segmentation algorithm was applied to discriminated speckle areas obtained using simple elliptic discriminant functions based on measures of the signal-to-noise ratio with fractional order moments. A rigorous stochastic analysis was used to derive an exact expression for the cumulative density function of the probability density function of the random field. Based on this, an accurate probability of error was derived and the performance of the scheme was analysed. The improved segmentation scheme performed well for both simulated and real images and showed superior results to those previously obtained using the original LRFM scheme and standard edge detection methods. In particular, the false alarm probability was markedly lower than that of the original LRFM method with oversegmentation artifacts virtually eliminated. The importance of this work lies in the development of a stochastic-based segmentation, allowing an accurate quantification of the probability of false detection. Non visual quantification and misclassification in medical ultrasound speckled images is relatively new and is of interest to clinicians.

Keywords: Discriminant function, false alarm, segmentation, signal-to-noise ratio, skewness, speckle.

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11227 An Efficient Approach to Mining Frequent Itemsets on Data Streams

Authors: Sara Ansari, Mohammad Hadi Sadreddini

Abstract:

The increasing importance of data stream arising in a wide range of advanced applications has led to the extensive study of mining frequent patterns. Mining data streams poses many new challenges amongst which are the one-scan nature, the unbounded memory requirement and the high arrival rate of data streams. In this paper, we propose a new approach for mining itemsets on data stream. Our approach SFIDS has been developed based on FIDS algorithm. The main attempts were to keep some advantages of the previous approach and resolve some of its drawbacks, and consequently to improve run time and memory consumption. Our approach has the following advantages: using a data structure similar to lattice for keeping frequent itemsets, separating regions from each other with deleting common nodes that results in a decrease in search space, memory consumption and run time; and Finally, considering CPU constraint, with increasing arrival rate of data that result in overloading system, SFIDS automatically detect this situation and discard some of unprocessing data. We guarantee that error of results is bounded to user pre-specified threshold, based on a probability technique. Final results show that SFIDS algorithm could attain about 50% run time improvement than FIDS approach.

Keywords: Data stream, frequent itemset, stream mining.

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11226 Temperature Variation Effects on I-V Characteristics of Cu-Phthalocyanine based OFET

Authors: Q. Zafar, R. Akram, Kh.S. Karimov, T.A. Khan, M. Farooq, M.M. Tahir

Abstract:

In this study we present the effect of elevated temperatures from 300K to 400K on the electrical properties of copper Phthalocyanine (CuPc) based organic field effect transistors (OFET). Thin films of organic semiconductor CuPc (40nm) and semitransparent Al (20nm) were deposited in sequence, by vacuum evaporation on a glass substrate with previously deposited Ag source and drain electrodes with a gap of 40 μm. Under resistive mode of operation, where gate was suspended it was observed that drain current of this organic field effect transistor (OFET) show an increase with temperature. While in grounded gate condition metal (aluminum) – semiconductor (Copper Phthalocyanine) Schottky junction dominated the output characteristics and device showed switching effect from low to high conduction states like Zener diode at higher bias voltages. This threshold voltage for switching effect has been found to be inversely proportional to temperature and shows an abrupt decrease after knee temperature of 360K. Change in dynamic resistance (Rd = dV/dI) with respect to temperature was observed to be -1%/K.

Keywords: Copper Phthalocyanine, Metal-Semiconductor Schottky Junction, Organic Field Effect Transistor, Switching effect, Temperature Sensor

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11225 Hybrid Hierarchical Routing Protocol for WSN Lifetime Maximization

Authors: H. Aoudia, Y. Touati, E. H. Teguig, A. Ali Cherif

Abstract:

Conceiving and developing routing protocols for wireless sensor networks requires considerations on constraints such as network lifetime and energy consumption. In this paper, we propose a hybrid hierarchical routing protocol named HHRP combining both clustering mechanism and multipath optimization taking into account residual energy and RSSI measures. HHRP consists of classifying dynamically nodes into clusters where coordinators nodes with extra privileges are able to manipulate messages, aggregate data and ensure transmission between nodes according to TDMA and CDMA schedules. The reconfiguration of the network is carried out dynamically based on a threshold value which is associated with the number of nodes belonging to the smallest cluster. To show the effectiveness of the proposed approach HHRP, a comparative study with LEACH protocol is illustrated in simulations.

Keywords: Routing protocols, energy optimization, clustering.

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11224 A Distributed Mobile Agent Based on Intrusion Detection System for MANET

Authors: Maad Kamal Al-Anni

Abstract:

This study is about an algorithmic dependence of Artificial Neural Network on Multilayer Perceptron (MPL) pertaining to the classification and clustering presentations for Mobile Adhoc Network vulnerabilities. Moreover, mobile ad hoc network (MANET) is ubiquitous intelligent internetworking devices in which it has the ability to detect their environment using an autonomous system of mobile nodes that are connected via wireless links. Security affairs are the most important subject in MANET due to the easy penetrative scenarios occurred in such an auto configuration network. One of the powerful techniques used for inspecting the network packets is Intrusion Detection System (IDS); in this article, we are going to show the effectiveness of artificial neural networks used as a machine learning along with stochastic approach (information gain) to classify the malicious behaviors in simulated network with respect to different IDS techniques. The monitoring agent is responsible for detection inference engine, the audit data is collected from collecting agent by simulating the node attack and contrasted outputs with normal behaviors of the framework, whenever. In the event that there is any deviation from the ordinary behaviors then the monitoring agent is considered this event as an attack , in this article we are going to demonstrate the  signature-based IDS approach in a MANET by implementing the back propagation algorithm over ensemble-based Traffic Table (TT), thus the signature of malicious behaviors or undesirable activities are often significantly prognosticated and efficiently figured out, by increasing the parametric set-up of Back propagation algorithm during the experimental results which empirically shown its effectiveness  for the ratio of detection index up to 98.6 percentage. Consequently it is proved in empirical results in this article, the performance matrices are also being included in this article with Xgraph screen show by different through puts like Packet Delivery Ratio (PDR), Through Put(TP), and Average Delay(AD).

Keywords: Mobile ad hoc network, MANET, intrusion detection system, back propagation algorithm, neural networks, traffic table, multilayer perceptron, feed-forward back-propagation, network simulator 2.

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11223 Aircraft Automatic Collision Avoidance Using Spiral Geometric Approach

Authors: M. Orefice, V. Di Vito

Abstract:

This paper provides a description of a Collision Avoidance algorithm that has been developed starting from the mathematical modeling of the flight of insects, in terms of spirals and conchospirals geometric paths. It is able to calculate a proper avoidance manoeuver aimed to prevent the infringement of a predefined distance threshold between ownship and the considered intruder, while minimizing the ownship trajectory deviation from the original path and in compliance with the aircraft performance limitations and dynamic constraints. The algorithm is designed in order to be suitable for real-time applications, so that it can be considered for the implementation in the most recent airborne automatic collision avoidance systems using the traffic data received through an ADS-B IN device. The presented approach is able to take into account the rules-of-the-air, due to the possibility to select, through specifically designed decision making logic based on the consideration of the encounter geometry, the direction of the calculated collision avoidance manoeuver that allows complying with the rules-of-the-air, as for instance the fundamental right of way rule. In the paper, the proposed collision avoidance algorithm is presented and its preliminary design and software implementation is described. The applicability of this method has been proved through preliminary simulation tests performed in a 2D environment considering single intruder encounter geometries, as reported and discussed in the paper.

Keywords: collision avoidance, RPAS, spiral geometry, ADS-B based application

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11222 Temperature Effect on the Mechanical Properties of Pd3Rh and PdRh3 Ordered Alloys

Authors: J. Davoodi , J. Moradi

Abstract:

The aim of this research was to calculate the mechanical properties of Pd3Rh and PdRh3 ordered alloys. The molecular dynamics (MD) simulation technique was used to obtain temperature dependence of the energy, the Yong modulus, the shear modulus, the bulk modulus, Poisson-s ratio and the elastic stiffness constants at the isobaric-isothermal (NPT) ensemble in the range of 100-325 K. The interatomic potential energy and force on atoms were calculated by Quantum Sutton-Chen (Q-SC) many body potential. Our MD simulation results show the effect of temperature on the cohesive energy and mechanical properties of Pd3Rh as well as PdRh3 alloys. Our computed results show good agreement with the experimental results where they have been available.

Keywords: Pd-Rh alloy; Mechanical properties; Moleculardynamics simulation

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11221 Optimization of Fuzzy Cluster Nodes in Cellular Multimedia Networks

Authors: J. D. Mallapur, Supriya H., Santosh B. K., Tej H.

Abstract:

The cellular network is one of the emerging areas of communication, in which the mobile nodes act as member for one base station. The cluster based communication is now an emerging area of wireless cellular multimedia networks. The cluster renders fast communication and also a convenient way to work with connectivity. In our scheme we have proposed an optimization technique for the fuzzy cluster nodes, by categorizing the group members into three categories like long refreshable member, medium refreshable member and short refreshable member. By considering long refreshable nodes as static nodes, we compute the new membership values for the other nodes in the cluster. We compare their previous and present membership value with the threshold value to categorize them into three different members. By which, we optimize the nodes in the fuzzy clusters. The simulation results show that there is reduction in the cluster computational time and iterational time after optimization.

Keywords: Clusters, fuzzy and optimization.

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11220 Liver Lesion Extraction with Fuzzy Thresholding in Contrast Enhanced Ultrasound Images

Authors: Abder-Rahman Ali, Adélaïde Albouy-Kissi, Manuel Grand-Brochier, Viviane Ladan-Marcus, Christine Hoeffl, Claude Marcus, Antoine Vacavant, Jean-Yves Boire

Abstract:

In this paper, we present a new segmentation approach for focal liver lesions in contrast enhanced ultrasound imaging. This approach, based on a two-cluster Fuzzy C-Means methodology, considers type-II fuzzy sets to handle uncertainty due to the image modality (presence of speckle noise, low contrast, etc.), and to calculate the optimum inter-cluster threshold. Fine boundaries are detected by a local recursive merging of ambiguous pixels. The method has been tested on a representative database. Compared to both Otsu and type-I Fuzzy C-Means techniques, the proposed method significantly reduces the segmentation errors.

Keywords: Defuzzification, fuzzy clustering, image segmentation, type-II fuzzy sets.

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11219 Marketing and Commercial Activities Offered on Websites of European Union Banks

Authors: Mario Spremić, Natalija Kokolek, Božidar Jaković, Jurica Šimurina

Abstract:

This paper deals with various questions related to functionality and providing banking services in the European union on the Internet. Due to the fact that we live in the information technologies era, the Internet become a new space for doing economic and business activities in all areas, and especially important in banking. Accepting the busy tempo of life, in the past several years electronic banking has become necessity and a must for most users of banking services. On a sample of 300 web sites of the banks operating in European Union (EU) we conduct the research on the functionality of e-banking services offered through banks web sites with the key objective to reveal to what extent the information technologies are used in their business operations. Characteristics of EU banks websites will be examined and compared to the basic groups of business activities on the web. Also some recommendations for the successful bank web sites will be provided.

Keywords: Electronic banking, electronic business, European Union banks, internet.

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11218 Integration of Support Vector Machine and Bayesian Neural Network for Data Mining and Classification

Authors: Essam Al-Daoud

Abstract:

Several combinations of the preprocessing algorithms, feature selection techniques and classifiers can be applied to the data classification tasks. This study introduces a new accurate classifier, the proposed classifier consist from four components: Signal-to- Noise as a feature selection technique, support vector machine, Bayesian neural network and AdaBoost as an ensemble algorithm. To verify the effectiveness of the proposed classifier, seven well known classifiers are applied to four datasets. The experiments show that using the suggested classifier enhances the classification rates for all datasets.

Keywords: AdaBoost, Bayesian neural network, Signal-to-Noise, support vector machine, MCMC.

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11217 Novelty as a Measure of Interestingness in Knowledge Discovery

Authors: Vasudha Bhatnagar, Ahmed Sultan Al-Hegami, Naveen Kumar

Abstract:

Rule Discovery is an important technique for mining knowledge from large databases. Use of objective measures for discovering interesting rules leads to another data mining problem, although of reduced complexity. Data mining researchers have studied subjective measures of interestingness to reduce the volume of discovered rules to ultimately improve the overall efficiency of KDD process. In this paper we study novelty of the discovered rules as a subjective measure of interestingness. We propose a hybrid approach based on both objective and subjective measures to quantify novelty of the discovered rules in terms of their deviations from the known rules (knowledge). We analyze the types of deviation that can arise between two rules and categorize the discovered rules according to the user specified threshold. We implement the proposed framework and experiment with some public datasets. The experimental results are promising.

Keywords: Knowledge Discovery in Databases (KDD), Interestingness, Subjective Measures, Novelty Index.

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11216 Object Tracking using MACH filter and Optical Flow in Cluttered Scenes and Variable Lighting Conditions

Authors: Waqar Shahid Qureshi, Abu-Baqar Nisar Alvi

Abstract:

Vision based tracking problem is solved through a combination of optical flow, MACH filter and log r-θ mapping. Optical flow is used for detecting regions of movement in video frames acquired under variable lighting conditions. The region of movement is segmented and then searched for the target. A template is used for target recognition on the segmented regions for detecting the region of interest. The template is trained offline on a sequence of target images that are created using the MACH filter and log r-θ mapping. The template is applied on areas of movement in successive frames and strong correlation is seen for in-class targets. Correlation peaks above a certain threshold indicate the presence of target and the target is tracked over successive frames.

Keywords: Correlation filters, optical flow, log r-θ mapping.

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11215 Molecular Dynamics Simulation of Thermal Properties of Au3Ni Nanowire

Authors: J. Davoodi, F. Katouzi

Abstract:

The aim of this research was to calculate the thermal properties of Au3Ni Nanowire. The molecular dynamics (MD) simulation technique was used to obtain the effect of radius size on the energy, the melting temperature and the latent heat of fusion at the isobaric-isothermal (NPT) ensemble. The Quantum Sutton-Chen (Q-SC) many body interatomic potentials energy have been used for Gold (Au) and Nickel (Ni) elements and a mixing rule has been devised to obtain the parameters of these potentials for nanowire stats. Our MD simulation results show the melting temperature and latent heat of fusion increase upon increasing diameter of nanowire. Moreover, the cohesive energy decreased with increasing diameter of nanowire.

Keywords: Au3Ni Nanowire, Thermal properties, Molecular dynamics simulation

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11214 Hierarchies Based On the Number of Cooperating Systems of Finite Automata on Four-Dimensional Input Tapes

Authors: Makoto Sakamoto, Yasuo Uchida, Makoto Nagatomo, Takao Ito, Tsunehiro Yoshinaga, Satoshi Ikeda, Masahiro Yokomichi, Hiroshi Furutani

Abstract:

In theoretical computer science, the Turing machine has played a number of important roles in understanding and exploiting basic concepts and mechanisms in computing and information processing [20]. It is a simple mathematical model of computers [9]. After that, M.Blum and C.Hewitt first proposed two-dimensional automata as a computational model of two-dimensional pattern processing, and investigated their pattern recognition abilities in 1967 [7]. Since then, a lot of researchers in this field have been investigating many properties about automata on a two- or three-dimensional tape. On the other hand, the question of whether processing fourdimensional digital patterns is much more difficult than two- or threedimensional ones is of great interest from the theoretical and practical standpoints. Thus, the study of four-dimensional automata as a computasional model of four-dimensional pattern processing has been meaningful [8]-[19],[21]. This paper introduces a cooperating system of four-dimensional finite automata as one model of four-dimensional automata. A cooperating system of four-dimensional finite automata consists of a finite number of four-dimensional finite automata and a four-dimensional input tape where these finite automata work independently (in parallel). Those finite automata whose input heads scan the same cell of the input tape can communicate with each other, that is, every finite automaton is allowed to know the internal states of other finite automata on the same cell it is scanning at the moment. In this paper, we mainly investigate some accepting powers of a cooperating system of eight- or seven-way four-dimensional finite automata. The seven-way four-dimensional finite automaton is an eight-way four-dimensional finite automaton whose input head can move east, west, south, north, up, down, or in the fu-ture, but not in the past on a four-dimensional input tape.

Keywords: computational complexity, cooperating system, finite automaton, four-dimension, hierarchy, multihead.

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11213 The Qualitative Methodology Exposure and Experiences of Journal Reviewers: A Qualitative Exploration

Authors: Salomé Elizabeth Scholtz

Abstract:

Reviewers are the gatekeepers of knowledge dissemination and promote the scientific validity of the research. However, authors often receive questionable feedback on qualitative manuscripts. Thus, this qualitative descriptive study sought to explore the qualitative knowledge and experiences of reviewers of psychology journals. A purposive and snowball sample (n = 27) of psychology journal reviewers completed an online questionnaire, and data were analysed using thematic analysis. Reviewers felt their postgraduate education, reading, and the process of reviewing qualitative articles equipped them to review qualitative manuscripts. Less than half of the reviewer’s published articles were qualitative and male reviewers published more than females. Despite not expecting authors to have the same level of research skills, reviewers still experienced authors as unskilled and biased, creating difficulty in accepting and reviewing qualitative articles. The applicability of the qualitative method and recommendations in preparing qualitative manuscripts for reviewing are reported.

Keywords: Journal reviewers, psychology, qualitative research, research method, research skills.

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11212 A Distributed Approach to Extract High Utility Itemsets from XML Data

Authors: S. Kannimuthu, K. Premalatha

Abstract:

This paper investigates a new data mining capability that entails mining of High Utility Itemsets (HUI) in a distributed environment. Existing research in data mining deals with only presence or absence of an items and do not consider the semantic measures like weight or cost of the items. Thus, HUI mining algorithm has evolved. HUI mining is the one kind of utility mining concept, aims to identify itemsets whose utility satisfies a given threshold. Although, the approach of mining HUIs in a distributed environment and mining of the same from XML data have not explored yet. In this work, a novel approach is proposed to mine HUIs from the XML based data in a distributed environment. This work utilizes Service Oriented Computing (SOC) paradigm which provides Knowledge as a Service (KaaS). The interesting patterns are provided via the web services with the help of knowledge server to answer the queries of the consumers. The performance of the approach is evaluated on various databases using execution time and memory consumption.

Keywords: Data mining, Knowledge as a Service, service oriented computing, utility mining.

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11211 Hospitality Management to Welcome Foreign Guests in the Japanese Lodging Industry

Authors: Shunichiro Morishita

Abstract:

This study examines the factors for attracting foreign guests in the Japanese lodging industry and discusses some measures taken for accepting foreign guests. It reviews three different accommodation providers acclaimed highly by foreign guests, Yamashiroya, Sawanoya and Fuji-Hakone Guest House, and identifies their characteristics. The common points for attracting foreign guests were: 1) making the best use of the old facilities, 2) multilingual signs, guidance and websites, 3) necessary and sufficient communication in English, 4) events and opportunities to experience Japanese culture, 5) omotenashi, warm and homely Japanese hospitality. These findings indicate that foreign guests’ dissatisfaction level can be decreased through internationalization utilizing ICT and by offering multilingual support. On the other hand, their satisfaction level can be increased by encouraging interaction with other guests and local Japanese people, providing events and opportunities to experience Japanese culture and omotenashi, home-style Japanese hospitality.

Keywords: Hospitality management, foreign guests, Japanese lodging industry, Omotenashi.

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11210 Coding Considerations for Standalone Molecular Dynamics Simulations of Atomistic Structures

Authors: R. O. Ocaya, J. J. Terblans

Abstract:

The laws of Newtonian mechanics allow ab-initio molecular dynamics to model and simulate particle trajectories in material science by defining a differentiable potential function. This paper discusses some considerations for the coding of ab-initio programs for simulation on a standalone computer and illustrates the approach by C language codes in the context of embedded metallic atoms in the face-centred cubic structure. The algorithms use velocity-time integration to determine particle parameter evolution for up to several thousands of particles in a thermodynamical ensemble. Such functions are reusable and can be placed in a redistributable header library file. While there are both commercial and free packages available, their heuristic nature prevents dissection. In addition, developing own codes has the obvious advantage of teaching techniques applicable to new problems.

Keywords: C-language, molecular dynamics, simulation, embedded atom method.

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