Search results for: credit card fraud detection

Authors: Anurag Sharma, Christian W. Omlin

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Self-organizing map (SOM) is a well known data reduction technique used in data mining. Data visualization can reveal structure in data sets that is otherwise hard to detect from raw data alone. However, interpretation through visual inspection is prone to errors and can be very tedious. There are several techniques for the automatic detection of clusters of code vectors found by SOMs, but they generally do not take into account the distribution of code vectors; this may lead to unsatisfactory clustering and poor definition of cluster boundaries, particularly where the density of data points is low. In this paper, we propose the use of a generic particle swarm optimization (PSO) algorithm for finding cluster boundaries directly from the code vectors obtained from SOMs. The application of our method to unlabeled call data for a mobile phone operator demonstrates its feasibility. PSO algorithm utilizes U-matrix of SOMs to determine cluster boundaries; the results of this novel automatic method correspond well to boundary detection through visual inspection of code vectors and k-means algorithm.

Keywords: Particle swarm optimization, self-organizing maps, clustering, data mining.

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Authors: Boregowda S.B., Hemanth Kumar A.R. Babu N.V, Puttamadappa C., And H.S Mruthyunjaya

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In the past few years, the use of wireless sensor networks (WSNs) potentially increased in applications such as intrusion detection, forest fire detection, disaster management and battle field. Sensor nodes are generally battery operated low cost devices. The key challenge in the design and operation of WSNs is to prolong the network life time by reducing the energy consumption among sensor nodes. Node clustering is one of the most promising techniques for energy conservation. This paper presents a novel clustering algorithm which maximizes the network lifetime by reducing the number of communication among sensor nodes. This approach also includes new distributed cluster formation technique that enables self-organization of large number of nodes, algorithm for maintaining constant number of clusters by prior selection of cluster head and rotating the role of cluster head to evenly distribute the energy load among all sensor nodes.

Keywords: Clustering algorithms, Cluster head, Energy consumption, Sensor nodes, and Wireless sensor networks.

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Authors: Mohamed Amine Ouddan, Hassane Essafi

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Source code retrieval is of immense importance in the software engineering field. The complex tasks of retrieving and extracting information from source code documents is vital in the development cycle of the large software systems. The two main subtasks which result from these activities are code duplication prevention and plagiarism detection. In this paper, we propose a Mohamed Amine Ouddan, and Hassane Essafi source code retrieval system based on two-level fingerprint representation, respectively the structural and the semantic information within a source code. A sequence alignment technique is applied on these fingerprints in order to quantify the similarity between source code portions. The specific purpose of the system is to detect plagiarism and duplicated code between programs written in different programming languages belonging to the same class, such as C, Cµ, Java and CSharp. These four languages are supported by the actual version of the system which is designed such that it may be easily adapted for any programming language.

Keywords: Source code retrieval, plagiarism detection, clonedetection, sequence alignment.

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Authors: E. Karoui Chaabane, S. Hadouaj, K. Ghedira

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Inter-organizational Workflow (IOW) is commonly used to support the collaboration between heterogeneous and distributed business processes of different autonomous organizations in order to achieve a common goal. E-government is considered as an application field of IOW. The coordination of the different organizations is the fundamental problem in IOW and remains the major cause of failure in e-government projects. In this paper, we introduce a new coordination model for IOW that improves the collaboration between government administrations and that respects IOW requirements applied to e-government. For this purpose, we adopt a Multi-Agent approach, which deals more easily with interorganizational digital government characteristics: distribution, heterogeneity and autonomy. Our model integrates also different technologies to deal with the semantic and technologic interoperability. Moreover, it conserves the existing systems of government administrations by offering a distributed coordination based on interfaces communication. This is especially applied in developing countries, where administrations are not necessary equipped with workflow systems. The use of our coordination techniques allows an easier migration for an e-government solution and with a lower cost. To illustrate the applicability of the proposed model, we present a case study of an identity card creation in Tunisia.

Keywords: E-government, Inter-organizational workflow, Multi-agent systems, Semantic web services.

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Authors: Seyedehzahra Mirrahimi, Nik Lukman Nik Ibrahim, M. Surat

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This paper investigated the impact of ceiling height and window head heights variation on daylighting inside architectural teaching studio with a full width window. In architectural education, using the studio is more than normal classroom in most credit hours. Therefore, window position, size and dimension of studio have direct influence on level of daylighting. Daylighting design is a critical factor that improves student learning, concentration and behavior, in addition to these, it also reduces energy consumption. The methodology of analysis involves using Radiance in IES software under overcast and cloudy sky in Malaysia. It has been established that presentation of daylighting of architecture studio can be enhanced by changing the ceiling heights and window level, because, different ceiling heights and window head heights can contribute to different range of daylight levels.

Keywords: Ceiling height, window head height, daylighting, studio architecture, simulation.

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Authors: J. Mehena, M. C. Adhikary

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In this paper, a spatial multiple-kernel fuzzy C-means (SMKFCM) algorithm is introduced for segmentation problem. A linear combination of multiples kernels with spatial information is used in the kernel FCM (KFCM) and the updating rules for the linear coefficients of the composite kernels are derived as well. Fuzzy cmeans (FCM) based techniques have been widely used in medical image segmentation problem due to their simplicity and fast convergence. The proposed SMKFCM algorithm provides us a new flexible vehicle to fuse different pixel information in medical image segmentation and detection of MR images. To evaluate the robustness of the proposed segmentation algorithm in noisy environment, we add noise in medical brain tumor MR images and calculated the success rate and segmentation accuracy. From the experimental results it is clear that the proposed algorithm has better performance than those of other FCM based techniques for noisy medical MR images.

Keywords: Clustering, fuzzy C-means, image segmentation, MR images, multiple kernels.

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Authors: António J. R. Neves, Rui Garcia, Paulo Dias, Alina Trifan

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With the aging of the world population and the continuous growth in technology, service robots are more and more explored nowadays as alternatives to healthcare givers or personal assistants for the elderly or disabled people. Any service robot should be capable of interacting with the human companion, receive commands, navigate through the environment, either known or unknown, and recognize objects. This paper proposes an approach for object recognition based on the use of depth information and color images for a service robot. We present a study on two of the most used methods for object detection, where 3D data is used to detect the position of objects to classify that are found on horizontal surfaces. Since most of the objects of interest accessible for service robots are on these surfaces, the proposed 3D segmentation reduces the processing time and simplifies the scene for object recognition. The first approach for object recognition is based on color histograms, while the second is based on the use of the SIFT and SURF feature descriptors. We present comparative experimental results obtained with a real service robot.

Keywords: Service Robot, Object Recognition, 3D Sensors, Plane Segmentation.

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Authors: G. Ramesh, S. Sundara Vadivelu

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For several high speed networks, providing resilience against failures is an essential requirement. The main feature for designing next generation optical networks is protecting and restoring high capacity WDM networks from the failures. Quick detection, identification and restoration make networks more strong and consistent even though the failures cannot be avoided. Hence, it is necessary to develop fast, efficient and dependable fault localization or detection mechanisms. In this paper we propose a new fault localization algorithm for WDM networks which can identify the location of a failure on a failed lightpath. Our algorithm detects the failed connection and then attempts to reroute data stream through an alternate path. In addition to this, we develop an algorithm to analyze the information of the alarms generated by the components of an optical network, in the presence of a fault. It uses the alarm correlation in order to reduce the list of suspected components shown to the network operators. By our simulation results, we show that our proposed algorithms achieve less blocking probability and delay while getting higher throughput.

Keywords: Alarm correlation, blocking probability, delay, fault localization, WDM networks.

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Authors: Chinmay Soman, Hrishikesh Pathak, Vishal Shah, Aniket Padhye, Amey Inamdar

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Phishing, or stealing of sensitive information on the web, has dealt a major blow to Internet Security in recent times. Most of the existing anti-phishing solutions fail to handle the fuzziness involved in phish detection, thus leading to a large number of false positives. This fuzziness is attributed to the use of highly flexible and at the same time, highly ambiguous HTML language. We introduce a new perspective against phishing, that tries to systematically prove, whether a given page is phished or not, using the corresponding original page as the basis of the comparison. It analyzes the layout of the pages under consideration to determine the percentage distortion between them, indicative of any form of malicious alteration. The system design represents an intelligent system, employing dynamic assessment which accurately identifies brand new phishing attacks and will prove effective in reducing the number of false positives. This framework could potentially be used as a knowledge base, in educating the internet users against phishing.

Keywords: World Wide Web, Phishing, Internet security, data mining.

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Authors: L. Hamsaveni, Navya Prakash, Suresha

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Document Image Analysis recognizes text and graphics in documents acquired as images. An approach without Optical Character Recognition (OCR) for degraded document image analysis has been adopted in this paper. The technique involves document imaging methods such as Image Fusing and Speeded Up Robust Features (SURF) Detection to identify and extract the degraded regions from a set of document images to obtain an original document with complete information. In case, degraded document image captured is skewed, it has to be straightened (deskew) to perform further process. A special format of image storing known as YCbCr is used as a tool to convert the Grayscale image to RGB image format. The presented algorithm is tested on various types of degraded documents such as printed documents, handwritten documents, old script documents and handwritten image sketches in documents. The purpose of this research is to obtain an original document for a given set of degraded documents of the same source.

Keywords: Grayscale image format, image fusing, SURF detection, YCbCr image format.

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Authors: M. Khatami Rad, N. Jamali, M. Torabizadeh, A. Noshadi

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In this paper, an artificial neural network simulator is employed to carry out diagnosis and prognosis on electric motor as rotating machinery based on predictive maintenance. Vibration data of the primary failed motor including unbalance, misalignment and bearing fault were collected for training the neural network. Neural network training was performed for a variety of inputs and the motor condition was used as the expert training information. The main purpose of applying the neural network as an expert system was to detect the type of failure and applying preventive maintenance. The advantage of this study is for machinery Industries by providing appropriate maintenance that has an essential activity to keep the production process going at all processes in the machinery industry. Proper maintenance is pivotal in order to prevent the possible failures in operating system and increase the availability and effectiveness of a system by analyzing vibration monitoring and developing expert system.

Keywords: Condition based monitoring, expert system, neural network, fault detection, vibration monitoring.

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Authors: Tyng-Rong Roan, Fuji Foo, Wenwey Hseush

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Recent development of AI and edge computing plays a critical role to capture meaningful events such as detection of an unattended bag. One of the core problems is re-identification across multiple CCTVs. Immediately following the detection of a meaningful event is to track and trace the objects related to the event. In an extensive environment, the challenge becomes severe when the number of CCTVs increases substantially, imposing difficulties in achieving high accuracy while maintaining real-time performance. The algorithm that re-identifies cross-boundary objects for extensive tracking is referred to Extensive Re-Identification, which emphasizes the issues related to the complexity behind a great number of CCTVs. The Spatial-Temporal Awareness approach challenges the conventional thinking and concept of operations which is labor intensive and time consuming. The ability to perform Extensive Re-Identification through a multi-sensory network provides the next-level insights – creating value beyond traditional risk management.

Keywords: Long-short-term memory, re-identification, security critical application, spatial-temporal awareness.

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Authors: Aziah Khamis, H. Shareef

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The purpose of planned islanding is to construct a power island during system disturbances which are commonly formed for maintenance purpose. However, in most of the cases island mode operation is not allowed. Therefore distributed generators (DGs) must sense the unplanned disconnection from the main grid. Passive technique is the most commonly used method for this purpose. However, it needs improvement in order to identify the islanding condition. In this paper an effective method for identification of islanding condition based on phase space and neural network techniques has been developed. The captured voltage waveforms at the coupling points of DGs are processed to extract the required features. For this purposed a method known as the phase space techniques is used. Based on extracted features, two neural network configuration namely radial basis function and probabilistic neural networks are trained to recognize the waveform class. According to the test result, the investigated technique can provide satisfactory identification of the islanding condition in the distribution system.

Keywords: Classification, Islanding detection, Neural network, Phase space.

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Authors: Muhammad F. Yaqub, Iqbal Gondal, Joarder Kamruzzaman

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Occurrence of a multiple-points fault in machine operations could result in exhibiting complex fault signatures, which could result in lowering fault diagnosis accuracy. In this study, a multiple-points defect model (MPDM) is proposed which can simulate fault signature-s dynamics for n-points bearing faults. Furthermore, this study identifies that in case of multiple-points fault in the rotary machine, the location of the dominant component of defect frequency shifts depending upon the relative location of the fault points which could mislead the fault diagnostic model to inaccurate detections. Analytical and experimental results are presented to characterize and validate the variation in the dominant component of defect frequency. Based on envelop detection analysis, a modification is recommended in the existing fault diagnostic models to consider the multiples of defect frequency rather than only considering the frequency spectrum at the defect frequency in order to incorporate the impact of multiple points fault.

Keywords: Envelop detection, machine defect frequency, multiple faults, machine health monitoring.

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Authors: Elia Favarelli, Enrico Testi, Andrea Giorgetti

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Autonomous structural health monitoring (SHM) of many structures and bridges became a topic of paramount importance for maintenance purposes and safety reasons. This paper proposes a set of machine learning (ML) tools to perform automatic feature selection and detection of anomalies in a bridge from vibrational data and compare different feature extraction schemes to increase the accuracy and reduce the amount of data collected. As a case study, the Z-24 bridge is considered because of the extensive database of accelerometric data in both standard and damaged conditions. The proposed framework starts from the first four fundamental frequencies extracted through operational modal analysis (OMA) and clustering, followed by time-domain filtering (tracking). The fundamental frequencies extracted are then fed to a dimensionality reduction block implemented through two different approaches: feature selection (intelligent multiplexer) that tries to estimate the most reliable frequencies based on the evaluation of some statistical features (i.e., entropy, variance, kurtosis), and feature extraction (auto-associative neural network (ANN)) that combine the fundamental frequencies to extract new damage sensitive features in a low dimensional feature space. Finally, one-class classification (OCC) algorithms perform anomaly detection, trained with standard condition points, and tested with normal and anomaly ones. In particular, principal component analysis (PCA), kernel principal component analysis (KPCA), and autoassociative neural network (ANN) are presented and their performance are compared. It is also shown that, by evaluating the correct features, the anomaly can be detected with accuracy and an F1 score greater than 95%.

Keywords: Anomaly detection, dimensionality reduction, frequencies selection, modal analysis, neural network, structural health monitoring, vibration measurement.

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Authors: Stefanos V. Fotopoulos, Harry V. Papapanagos, Fotios M. Siokis

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This paper tries to shed light on the existence of a bank lending channel (BLC) in South Eastern European countries (SEE). Based on a VAR framework we test the responsiveness of credit supply to monetary policy shocks. By compiling a new data set and using the reserve requirement ratio, among others, as the policy instrument we measure the effectiveness of the BLC and the buffering effect of the banks in the SEE countries. The results indicate that loan supply is significantly affected by shifts in monetary policy, when demand factors are controlled. Furthermore, by analyzing the effect of the Greek banks in the region we conclude that Greek banks do buffer the negative effects of monetary policy transmission. By having a significant market share of the SEE-s banking markets we argue that Greek banks influence positively the economic growth of SEE countries.

Keywords: Bank Lending Channel, Monetary Policy Transmission, Policy Buffering, South Eastern Europe

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Authors: Noor Elaiza Abdul Khalid, Noorhayati Mohamed Noor, Zamalia Mahmud, Saadiah Yahya, and Norharyati Md Ariff

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Glaucoma diagnosis involves extracting three features of the fundus image; optic cup, optic disc and vernacular. Present manual diagnosis is expensive, tedious and time consuming. A number of researches have been conducted to automate this process. However, the variability between the diagnostic capability of an automated system and ophthalmologist has yet to be established. This paper discusses the efficiency and variability between ophthalmologist opinion and digital technique; threshold. The efficiency and variability measures are based on image quality grading; poor, satisfactory or good. The images are separated into four channels; gray, red, green and blue. A scientific investigation was conducted on three ophthalmologists who graded the images based on the image quality. The images are threshold using multithresholding and graded as done by the ophthalmologist. A comparison of grade from the ophthalmologist and threshold is made. The results show there is a small variability between result of ophthalmologists and digital threshold.

Keywords: Digital Fundus Image, Glaucoma Detection, Multithresholding, Segmentation.

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Authors: K. Alese Boniface, K. Adu Michael

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Cybercrime is now becoming a big challenge in Nigeria apart from the traditional crime. Inability to identify perpetrators is one of the reasons for the growing menace. This paper proposes a design for monitoring internet users’ activities in order to curbing cybercrime. It requires redefining the operations of Internet Service Providers (ISPs) which will now mandate users to be authenticated before accessing the internet. In implementing this work which can be adapted to a larger scale, a virtual router application is developed and configured to mimic a real router device. A sign-up portal is developed to allow users to register with the ISP. The portal asks for identification information which will include bio-data and government issued identification data like National Identity Card number, et cetera. A unique username and password are chosen by the user to enable access to the internet which will be used to reference him to an Internet Protocol Address (IP Address) of any system he uses on the internet and thereby associating him to any criminal act related to that IP address at that particular time. Questions such as “What happen when another user knows the password and uses it to commit crime?” and other pertinent issues are addressed.

Keywords: Cybercrime, Sign-up Portal, Internet Service Provider (ISP), Internet Protocol Address (IP address).

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Authors: K. Nirmala Devi, V. Murali Bhaskaran

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The exponential growth of social media arouses much attention on public opinion information. The online forums, blogs, micro blogs are proving to be extremely valuable resources and are having bulk volume of information. However, most of the social media data is unstructured and semi structured form. So that it is more difficult to decipher automatically. Therefore, it is very much essential to understand and analyze those data for making a right decision. The online forums hotspot detection is a promising research field in the web mining and it guides to motivate the user to take right decision in right time. The proposed system consist of a novel approach to detect a hotspot forum for any given time period. It uses aging theory to find the hot terms and E-K-means for detecting the hotspot forum. Experimental results demonstrate that the proposed approach outperforms k-means for detecting the hotspot forums with the improved accuracy.

Keywords: Hotspot forums, Micro blog, Blog, Sentiment Analysis, Opinion Mining, Social media, Twitter, Web mining.

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Authors: Tawfig Eltaif, Hesham A. Bakarman, N. Alsowaidi, M. R. Mokhtar, Malek Harbawi

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Multiple User Interference (MUI) considers the primary problem in Optical Code-Division Multiple Access (OCDMA), which resulting from the overlapping among the users. In this article we aim to mitigate this problem by studying an interference cancellation scheme called successive interference cancellation (SIC) scheme. This scheme will be tested on two different detection schemes, spectral amplitude coding (SAC) and direct detection systems (DS), using partial modified prime (PMP) as the signature codes. It was found that SIC scheme based on both SAC and DS methods had a potential to suppress the intensity noise, that is to say it can mitigate MUI noise. Furthermore, SIC/DS scheme showed much lower bit error rate (BER) performance relative to SIC/SAC scheme for different magnitude of effective power. Hence, many more users can be supported by SIC/DS receiver system.

Keywords: Multiple User Interference (MUI), Optical Code-Division Multiple Access (OCDMA), Partial Modified Prime Code (PMP), Spectral Amplitude Coding (SAC), Successive Interference Cancellation (SIC).

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Authors: O. J. G. Somsen, G. P. M. Wagemakers

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Magnetic signature detection provides sensitive detection of metal objects, especially in the natural environment. Our group is developing a tabletop setup for magnetic signatures of various small and model objects. A particular issue is the separation of permanent and induced magnetization. While the latter depends only on the composition and shape of the object, the former also depends on the magnetization history. With common deperming techniques, a significant permanent signature may still remain, which confuses measurements of the induced component. We investigate a basic technique of separating the two. Measurements were done by moving the object along an aluminum rail while the three field components are recorded by a detector attached near the center. This is done first with the rail parallel to the Earth magnetic field and then with anti-parallel orientation. The reversal changes the sign of the induced- but not the permanent magnetization so that the two can be separated. Our preliminary results on a small iron block show excellent reproducibility. A considerable permanent magnetization was indeed present, resulting in a complex asymmetric signature. After separation, a much more symmetric induced signature was obtained that can be studied in detail and compared with theoretical calculations.

Keywords: Magnetic signature, data analysis, magnetization, deperming techniques.

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Authors: S. Shefali, S. M. Deshpande, S. G. Tamhankar

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Now a days, a significant part of commercial and governmental organisations like museums, cultural organizations, libraries, commercial enterprises, etc. invest intensively in new technologies for image digitization, digital libraries, image archiving and retrieval. Hence image authorization, authentication and security has become prime need. In this paper, we present a semi-fragile watermarking scheme for color images. The method converts the host image into YIQ color space followed by application of orthogonal dual domains of DCT and DWT transforms. The DCT helps to separate relevant from irrelevant image content to generate silent image features. DWT has excellent spatial localisation to help aid in spatial tamper characterisation. Thus image adaptive watermark is generated based of image features which allows the sharp detection of microscopic changes to locate modifications in the image. Further, the scheme utilises the multipurpose watermark consisting of soft authenticator watermark and chrominance watermark. Which has been proved fragile to some predefined processing like intentinal fabrication of the image or forgery and robust to other incidental attacks caused in the communication channel.

Keywords: Cryptography, Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), Watermarking.

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Authors: Ivana Šimonová

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As widely accepted, didactic multiple-choice tests are referred as a tool providing feedback easily and quickly. Despite the final test scores are corrected by a special formula and number of high plausibility distractors is taken into consideration, the results may be influenced by the random choice. The survey was held in three academic years at the Faculty of Informatics and Management, University of Hradec Kralove, Czech Republic, where the multiple-choice test scores were compared to the open-answer ones. The research sample included 567 respondents. The collected data were processed by the NCSS2007 statistic software by the method of frequency and multiple regression analysis and presented in the form of figures and tables. The results proved statistically significant differences in test scores in academic years 2 and 3, and were discussed from the point of the credit system and conditions for teaching/learning English in the Czech education system.

Keywords: ESP, higher education, multiple-choice test, open-answer test.

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Authors: Stephen Karungaru, Minoru Fukumi, Norio Akamatsu

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In this paper, we propose a morphing method by which face color images can be freely transformed. The main focus of this work is the transformation of one face image to another. This method is fully automatic in that it can morph two face images by automatically detecting all the control points necessary to perform the morph. A face detection neural network, edge detection and medium filters are employed to detect the face position and features. Five control points, for both the source and target images, are then extracted based on the facial features. Triangulation method is then used to match and warp the source image to the target image using the control points. Finally color interpolation is done using a color Gaussian model that calculates the color for each particular frame depending on the number of frames used. A real coded Genetic algorithm is used in both the image warping and color blending steps to assist in step size decisions and speed up the morphing. This method results in ''very smooth'' morphs and is fast to process.

Keywords: color transition, genetic algorithms morphing, warping

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Authors: I. Erins, J. Erina

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The aim of the present article is to determine the impact of the external and internal factors of bank performance on the profitability indicators of the CEE countries banks in the period from 2006 to 2012. On the basis of research conducted abroad on bank and macroeconomic profitability indicators, in order to obtain research results, the authors evaluated return on average assets (ROAA) and return on average equity (ROAE) indicators of the CEE countries banks. The authors analyzed profitability indicators of banks using descriptive methods, SPSS data analysis methods, as well as data correlation and linear regression analysis. The authors concluded that most internal and external indicators of bank performance have no direct influence the profitability of the banks in the CEE countries. The only exceptions are credit risk and bank size, which affect one of the measures of bank profitability – return on average equity.

Keywords: Banks, CEE countries, Profitability ROAA, ROAE.

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Authors: Adrien Derock, Pascal Veron

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Taking into account the link between the efficiency of a detector and the complexity of a stealth mechanism, we propose in this paper a new formalism for stealth using graph theory.

Keywords: Detection, eradication, graph, rootkit, stealth.

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Authors: Chia-Hung Lin, Mei-Sung Kang, Cong-Hui Huang, Chao-Lin Kuo

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This paper proposes fractal patterns for power quality (PQ) detection using color relational analysis (CRA) based classifier. Iterated function system (IFS) uses the non-linear interpolation in the map and uses similarity maps to construct various fractal patterns of power quality disturbances, including harmonics, voltage sag, voltage swell, voltage sag involving harmonics, voltage swell involving harmonics, and voltage interruption. The non-linear interpolation functions (NIFs) with fractal dimension (FD) make fractal patterns more distinguishing between normal and abnormal voltage signals. The classifier based on CRA discriminates the disturbance events in a power system. Compared with the wavelet neural networks, the test results will show accurate discrimination, good robustness, and faster processing time for detecting disturbing events.

Keywords: Power Quality (PQ), Color Relational Analysis(CRA), Iterated Function System (IFS), Non-linear InterpolationFunction (NIF), Fractal Dimension (FD).

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Authors: S. J. Hachar

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The goal of this paper is to provide educators an overview of international practices supporting young learners, arming us with adequate information to lead effective change. We will report on research and observations of Service Learning Projects conducted by one South Texas University. The intent of the paper is also to provide readers an overview of service learning in the preparation of teacher candidates pursuing a Bachelor of Science in Elementary Education. The objective of noting the efficiency and effectiveness of programs leading to literacy and oral fluency in a native language and second language will be discussed. This paper also highlights experiential learning for academic credit that combines community service with student learning. Six weeks of visits to a variety of community sites, making personal observations with faculty members, conducting extensive interviews with parents and key personnel at all sites will be discussed. The culminating Service Learning Expo will be reported as well.

Keywords: Elementary education, junior achievement, service learning.

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Authors: Emad S. Abouel Nasr, Abdulaziz M. El-Tamimi, Mustufa H. Abidi, Abdulrahman M. Al-Ahmari

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Virtual Assembly (VA) is one of the key technologies in advanced manufacturing field. It is a promising application of virtual reality in design and manufacturing field. It has drawn much interest from industries and research institutes in the last two decades. This paper describes a process for integrating an interactive Virtual Reality-based assembly simulation of a digital mockup with the CAD/CAM infrastructure. The necessary hardware and software preconditions for the process are explained so that it can easily be adopted by non VR experts. The article outlines how assembly simulation can improve the CAD/CAM procedures and structures; how CAD model preparations have to be carried out and which virtual environment requirements have to be fulfilled. The issue of data transfer is also explained in the paper. The other challenges and requirements like anti-aliasing and collision detection have also been explained. Finally, a VA simulation has been carried out for a ball valve assembly and a car door assembly with the help of Vizard virtual reality toolkit in a semi-immersive environment and their performance analysis has been done on different workstations to evaluate the importance of graphical processing unit (GPU) in the field of VA.

Keywords: Collision Detection, Graphical Processing Unit (GPU), Virtual Reality (VR), Virtual Assembly (VA).

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Authors: Suppara Charoenpoom

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This paper was aimed to survey the level of awareness of traditional grocery stores in Bangkok in these categories: location, service quality, risk, shopping, worthwhile, shopping satisfaction, and future shopping intention. The paper was also aimed to survey factors influencing the decision to shop at traditional grocery stores in Bangkok in the future. The findings revealed that consumers had a high level of awareness of traditional grocery stores in Bangkok. Consumers were aware that the price was higher and it was riskier to buy goods and services at traditional grocery stores but they still had a high level of preference to patronage traditional grocery stores. This was due to the reasons that there was a high level of satisfaction from the factors of the friendliness of the owner, the ability to negotiate the price, the ability to buy on credit, free delivery, and the enjoyment to meet with other customers in the same neighborhood.

Keywords: Business Management, Thai Economy, Traditional Grocery Store.

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