Search results for: features selection technique

Authors: Hany Alashwal, Safaai Deris, Razib M. Othman

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The protein domain structure has been widely used as the most informative sequence feature to computationally predict protein-protein interactions. However, in a recent study, a research group has reported a very high accuracy of 94% using hydrophobicity feature. Therefore, in this study we compare and verify the usefulness of protein domain structure and hydrophobicity properties as the sequence features. Using the Support Vector Machines (SVM) as the learning system, our results indicate that both features achieved accuracy of nearly 80%. Furthermore, domains structure had receiver operating characteristic (ROC) score of 0.8480 with running time of 34 seconds, while hydrophobicity had ROC score of 0.8159 with running time of 20,571 seconds (5.7 hours). These results indicate that protein-protein interaction can be predicted from domain structure with reliable accuracy and acceptable running time.

Keywords: Bioinformatics, protein-protein interactions, support vector machines, protein features.

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Authors: Maleika Heenaye- Mamode Khan , Naushad Mamode Khan, Raja K.Subramanian

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Dorsal hand vein pattern is an emerging biometric which is attracting the attention of researchers, of late. Research is being carried out on existing techniques in the hope of improving them or finding more efficient ones. In this work, Principle Component Analysis (PCA) , which is a successful method, originally applied on face biometric is being modified using Cholesky decomposition and Lanczos algorithm to extract the dorsal hand vein features. This modified technique decreases the number of computation and hence decreases the processing time. The eigenveins were successfully computed and projected onto the vein space. The system was tested on a database of 200 images and using a threshold value of 0.9 to obtain the False Acceptance Rate (FAR) and False Rejection Rate (FRR). This modified algorithm is desirable when developing biometric security system since it significantly decreases the matching time.

Keywords: Dorsal hand vein pattern, PCA, Cholesky decomposition, Lanczos algorithm.

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Authors: Abdelmalek Fermas, Adel Belouchrani, Otmane Ait Mohamed

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In Blind Source Separation (BSS) processing, taking advantage of scaling factor indetermination and based on the floatingpoint representation, we propose a scaling technique applied to the separation matrix, to avoid the saturation or the weakness in the recovered source signals. This technique performs an Automatic Gain Control (AGC) in an on-line BSS environment. We demonstrate the effectiveness of this technique by using the implementation of a division free BSS algorithm with two input, two output. This technique is computationally cheaper and efficient for a hardware implementation.

Keywords: Automatic Gain Control, Blind Source Separation, Floating-Point Representation, FPGA Implementation.

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Authors: Amira M. Attia, Karim H. Youssef, Nabil H. Abbasy

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Energy consumption schedule (ECS) technique shifts usage of loads from on peak hours and redistributes them throughout the day according to residents’ operating time preferences. This technique is used as form of indirect control from utility to improve the load curve and hence its load factor and reduce customer’s total electric bill as well. Similarly, load shifting technique achieves ECS purposes but as direct control form applied from utility. In this paper, ECS is simulated twice as optimal constrained mathematical formula, solved by using CVX program in MATLAB^® R2013b. First, it is utilized for single residential building with ten apartments to determine max allowable energy consumption per hour for each residential apartment. Then, it is used for single apartment with number of shiftable domestic devices, where operating schedule is deduced using previous simulation output results as constraints. The paper ends by giving differences between ECS technique and load shifting technique via literature and simulation. Based on results assessment, it will be shown whether using ECS or load shifting is more beneficial to both customer and utility.

Keywords: Energy consumption schedule, load shifting technique, comparison.

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Authors: C. Gunavathi, K. Premalatha

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Tumor classification is a key area of research in the field of bioinformatics. Microarray technology is commonly used in the study of disease diagnosis using gene expression levels. The main drawback of gene expression data is that it contains thousands of genes and a very few samples. Feature selection methods are used to select the informative genes from the microarray. These methods considerably improve the classification accuracy. In the proposed method, Genetic Algorithm (GA) is used for effective feature selection. Informative genes are identified based on the T-Statistics, Signal-to-Noise Ratio (SNR) and F-Test values. The initial candidate solutions of GA are obtained from top-m informative genes. The classification accuracy of k-Nearest Neighbor (kNN) method is used as the fitness function for GA. In this work, kNN and Support Vector Machine (SVM) are used as the classifiers. The experimental results show that the proposed work is suitable for effective feature selection. With the help of the selected genes, GA-kNN method achieves 100% accuracy in 4 datasets and GA-SVM method achieves in 5 out of 10 datasets. The GA with kNN and SVM methods are demonstrated to be an accurate method for microarray based tumor classification.

Keywords: F-Test, Gene Expression, Genetic Algorithm, k- Nearest-Neighbor, Microarray, Signal-to-Noise Ratio, Support Vector Machine, T-statistics, Tumor Classification.

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Authors: S. Rasekhinia, S. Aghanajafizadeh, K. Eslami

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We studied the selection of nest sites by Persian ground Jay (Podoces pleskei), in a semi -desert central Iran. Habitat variables such as plant species number, height of plant species, vegetation percent and distance to water sources of nest sites were compared with randomly selected non- used sites. The results showed that the most important factors influencing nesting site selection were total vegetation percent and number of shrubs (Zgophyllum eurypterum and Atraphaxis spinosa). The mean vegetation percent of 20 area selected by Persian Ground Jay was (4.41+ 0.17), which was significantly larger than that of the non – selected area (2.08 + 0.06). The number of Zygophyllum eurypterum (1.13+ 0.01) and Atraphaxis spinosa (1.36+ 0.10) were also significantly higher compared with the control area (0.43+ 0.07) and (0.58+ 0.9) respectively.

Keywords: Persian Ground Jay, Habitat variables, Iran.

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Authors: Maryam Alimardani, Kazuo Hiraki

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This study presents a framework for development of a new generation of therapy robots that can interact with users by monitoring their physiological and mental states. Here, we focused on one of the controversial methods of therapy, hypnotherapy. Hypnosis has shown to be useful in treatment of many clinical conditions. But, even for healthy people, it can be used as an effective technique for relaxation or enhancement of memory and concentration. Our aim is to develop a robot that collects information about user’s mental and physical states using electroencephalogram (EEG) and electromyography (EMG) signals and performs costeffective hypnosis at the comfort of user’s house. The presented framework consists of three main steps: (1) Find the EEG-correlates of mind state before, during, and after hypnosis and establish a cognitive model for state changes, (2) Develop a system that can track the changes in EEG and EMG activities in real time and determines if the user is ready for suggestion, and (3) Implement our system in a humanoid robot that will talk and conduct hypnosis on users based on their mental states. This paper presents a pilot study in regard to the first stage, detection of EEG and EMG features during hypnosis.

Keywords: Hypnosis, EEG, robotherapy, brain-computer interface.

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Authors: Rahmad Wisnu Wardana, Eakachai Warinsiriruk, Sutep Joy-A-Ka

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Selecting the most suitable welding process usually depends on experiences or common application in similar companies. However, this approach generally ignores many criteria that can be affecting the suitable welding process selection. Therefore, knowledge automation through knowledge-based systems will significantly improve the decision-making process. The aims of this research propose integrated data envelopment analysis (DEA) and fuzzy credibility constrained programming approach for identifying the best welding process for stainless steel storage tank in the food and beverage industry. The proposed approach uses fuzzy concept and credibility measure to deal with uncertain data from experts' judgment. Furthermore, 12 parameters are used to determine the most appropriate welding processes among six competitive welding processes.

Keywords: Welding process selection, data envelopment analysis, fuzzy credibility constrained programming, storage tank.

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Authors: Wayan F. Mahmudy, Romeo M. Marian, Lee H. S. Luong

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 This paper deals with modeling and optimization of two NP-hard problems in production planning of flexible manufacturing system (FMS), part type selection problem and loading problem. The part type selection problem and the loading problem are strongly related and heavily influence the system’s efficiency and productivity. These problems have been modeled and solved simultaneously by using real coded genetic algorithms (RCGA) which uses an array of real numbers as chromosome representation. The novel proposed chromosome representation produces only feasible solutions which minimize a computational time needed by GA to push its population toward feasible search space or repair infeasible chromosomes. The proposed RCGA improves the FMS performance by considering two objectives, maximizing system throughput and maintaining the balance of the system (minimizing system unbalance). The resulted objective values are compared to the optimum values produced by branch-and-bound method. The experiments show that the proposed RCGA could reach near optimum solutions in a reasonable amount of time.

Keywords: Flexible manufacturing system, production planning, part type selection problem, loading problem, real-coded genetic algorithm.

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Authors: Olimpia Matarazzo, Fabrizio Ferrara

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In two studies we tested the hypothesis that the appropriate linguistic formulation of a deontic rule – i.e. the formulation which clarifies the monadic nature of deontic operators - should produce more correct responses than the conditional formulation in Wason selection task. We tested this assumption by presenting a prescription rule and a prohibition rule in conditional vs. proper deontic formulation. We contrasted this hypothesis with two other hypotheses derived from social contract theory and relevance theory. According to the first theory, a deontic rule expressed in terms of cost-benefit should elicit a cheater detection module, sensible to mental states attributions and thus able to discriminate intentional rule violations from accidental rule violations. We tested this prevision by distinguishing the two types of violations. According to relevance theory, performance in selection task should improve by increasing cognitive effect and decreasing cognitive effort. We tested this prevision by focusing experimental instructions on the rule vs. the action covered by the rule. In study 1, in which 480 undergraduates participated, we tested these predictions through a 2 x 2 x 2 x 2 (type of the rule x rule formulation x type of violation x experimental instructions) between-subjects design. In study 2 – carried out by means of a 2 x 2 (rule formulation x type of violation) between-subjects design - we retested the hypothesis of rule formulation vs. the cheaterdetection hypothesis through a new version of selection task in which intentional vs. accidental rule violations were better discriminated. 240 undergraduates participated in this study. Results corroborate our hypothesis and challenge the contrasting assumptions. However, they show that the conditional formulation of deontic rules produces a lower performance than what is reported in literature.

Keywords: Deontic reasoning; Evolutionary, linguistic, logical, pragmatic factors; Wason selection task

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Authors: Kari Huhtala, Iiro Jussila

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The supervisory board is assumed to use power in the governance of a firm, but the actual use of power has been scantly investigated. The research question of the paper is “How does the supervisory board use power in the selection of the board of directors”. The data stem from 11 large Finnish agricultural cooperatives. The research approach was qualitative including semi-structured interviews of the board of directors and supervisory board chairpersons. The results were analyzed and interpreted against theories of social power. As a result, the use of power is approached from two perspectives: (1) formal position-based authority and (2) informal power. Central elements of power were the mandate of the supervisory board, the role of the supervisory board, the supervisory board chair, the nomination committee, collaboration between the supervisory board and the board of directors, the role of regions and the role of the board of directors. The study contributes to the academic discussion on corporate governance in cooperatives and on the supervisory board in the context of the two-tier model. Additional research of the model in other countries and of other types of cooperatives would further academic understanding of supervisory boards.

Keywords: Board, cooperative, supervisory board, selection, director, power.

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Authors: Fawaz S. Al-Anzi, Dia AbuZeina

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Speech recognition is of an important contribution in promoting new technologies in human computer interaction. Today, there is a growing need to employ speech technology in daily life and business activities. However, speech recognition is a challenging task that requires different stages before obtaining the desired output. Among automatic speech recognition (ASR) components is the feature extraction process, which parameterizes the speech signal to produce the corresponding feature vectors. Feature extraction process aims at approximating the linguistic content that is conveyed by the input speech signal. In speech processing field, there are several methods to extract speech features, however, Mel Frequency Cepstral Coefficients (MFCC) is the popular technique. It has been long observed that the MFCC is dominantly used in the well-known recognizers such as the Carnegie Mellon University (CMU) Sphinx and the Markov Model Toolkit (HTK). Hence, this paper focuses on the MFCC method as the standard choice to identify the different speech segments in order to obtain the language phonemes for further training and decoding steps. Due to MFCC good performance, the previous studies show that the MFCC dominates the Arabic ASR research. In this paper, we demonstrate MFCC as well as the intermediate steps that are performed to get these coefficients using the HTK toolkit.

Keywords: Speech recognition, acoustic features, Mel Frequency Cepstral Coefficients.

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Authors: Nael Hirzalla

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The legality of some countries or agencies’ acts to spy on personal phone calls of the public became a hot topic to many social groups’ talks. It is believed that this act is considered an invasion to someone’s privacy. Such act may be justified if it is singling out specific cases but to spy without limits is very unacceptable. This paper discusses the needs for not only a simple and light weight technique to secure mobile voice calls but also a technique that is independent from any encryption standard or library. It then presents and tests one encrypting algorithm that is based of Frequency scrambling technique to show fair and delay-free process that can be used to protect phone calls from such spying acts.

Keywords: Frequency Scrambling, Mobile Applications, Real- Time Voice Encryption, Spying on Calls.

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Authors: R. Poonkuzhali, M. Y. Sanavullah, M. R. Gurupriya

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Opportunistic routing is used, where the network has the features like dynamic topology changes and intermittent network connectivity. In Delay tolerant network or Disruption tolerant network opportunistic forwarding technique is widely used. The key idea of opportunistic routing is selecting forwarding nodes to forward data packets and coordination among these nodes to avoid duplicate transmissions. This paper gives the analysis of pros and cons of various opportunistic routing techniques used in MANET.

Keywords: Expected Transmission Count (ETX), Opportunistic routing, Proactive Source Routing (PSR), throughput.

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Authors: Cristina G. Dascalu, Elena Mihaela Carausu, Daniela Manuc

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The medical studies often require different methods for parameters selection, as a second step of processing, after the database-s designing and filling with information. One common task is the selection of fields that act as risk factors using wellknown methods, in order to find the most relevant risk factors and to establish a possible hierarchy between them. Different methods are available in this purpose, one of the most known being the binary logistic regression. We will present the mathematical principles of this method and a practical example of using it in the analysis of the influence of 10 different psychiatric diagnostics over 4 different types of offences (in a database made from 289 psychiatric patients involved in different types of offences). Finally, we will make some observations about the relation between the risk factors hierarchy established through binary logistic regression and the individual risks, as well as the results of Chi-squared test. We will show that the hierarchy built using the binary logistic regression doesn-t agree with the direct order of risk factors, even if it was naturally to assume this hypothesis as being always true.

Keywords: Databases, risk factors, binary logisticregression, hierarchy.

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Authors: Ritsuko Kawasaki (Aiba), Takeshi Hiromatsu

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Management is required to understand all information security risks within an organization, and to make decisions on which information security risks should be treated in what level by allocating how much amount of cost. However, such decision-making is not usually easy, because various measures for risk treatment must be selected with the suitable application levels. In addition, some measures may have objectives conflicting with each other. It also makes the selection difficult. Moreover, risks generally have trends and it also should be considered in risk treatment. Therefore, this paper provides the extension of the model proposed in the previous study. The original model supports the selection of measures by applying a combination of weighted average method and goal programming method for multi-objective analysis to find an optimal solution. The extended model includes the notion of weights to the risks, and the larger weight means the priority of the risk.

Keywords: Information security risk treatment, Selection of risk measures, Risk acceptanceand Multi-objective optimization.

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Authors: A. Statkus, S. Paulikas

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With increasing number of wireless devices like laptops, Wi-Fi Web Cams, network extenders, etc., a new kind of problems appeared, mostly related to poor Wi-Fi throughput or communication problems. In this paper an investigation on wireless networks and it-s saturation in Vilnius City and its surrounding is presented, covering the main problems of wireless saturation and network load during day. Also an investigation on wireless channel selection and noise levels were made, showing the impact of neighbor AP to signal and noise levels and how it changes during the day.

Keywords: IEEE 802.11b/g/n, wireless saturation, client activity, channel selection.

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Authors: Maha Sharkas, Dahlia R. ElShafie, Nadder Hamdy

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Image watermarking has proven to be quite an efficient tool for the purpose of copyright protection and authentication over the last few years. In this paper, a novel image watermarking technique in the wavelet domain is suggested and tested. To achieve more security and robustness, the proposed techniques relies on using two nested watermarks that are embedded into the image to be watermarked. A primary watermark in form of a PN sequence is first embedded into an image (the secondary watermark) before being embedded into the host image. The technique is implemented using Daubechies mother wavelets where an arbitrary embedding factor α is introduced to improve the invisibility and robustness. The proposed technique has been applied on several gray scale images where a PSNR of about 60 dB was achieved.

Keywords: Image watermarking, Multimedia Security, Wavelets, Image Processing.

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Authors: Zeinab Zeinalpour-Tabrizi, Faeze Asdaghi, Mahmooh Fathy, Mohammad Reza Jahed-Motlagh

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Shot boundary detection is a fundamental step for the organization of large video data. In this paper, we propose a new method for video gradual shots detection and classification, using advantages of fractal analysis and AIS-based classifier. Proposed features are “vertical intercept" and “fractal dimension" of each frame of videos which are computed using Fourier transform coefficients. We also used a classifier based on Clonal Selection Algorithm. We have carried out our solution and assessed it according to the TRECVID2006 benchmark dataset.

Keywords: shot boundary detection, gradual shots, fractal analysis, artificial immune system, choose Clooney.

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Authors: Adel Aloraini

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Financial forecasting using machine learning techniques has received great efforts in the last decide . In this ongoing work, we show how machine learning of graphical models will be able to infer a visualized causal interactions between different banks in the Saudi equities market. One important discovery from such learned causal graphs is how companies influence each other and to what extend. In this work, a set of graphical models named Gaussian graphical models with developed ensemble penalized feature selection methods that combine ; filtering method, wrapper method and a regularizer will be shown. A comparison between these different developed ensemble combinations will also be shown. The best ensemble method will be used to infer the causal relationships between banks in Saudi equities market.

Keywords: Causal interactions , banks, feature selection, regularizere,

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Authors: Vesna Kirandziska, Nevena Ackovska, Ana Madevska Bogdanova

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The problem of emotion recognition is a challenging problem. It is still an open problem from the aspect of both intelligent systems and psychology. In this paper, both voice features and facial features are used for building an emotion recognition system. A Support Vector Machine classifiers are built by using raw data from video recordings. In this paper, the results obtained for the emotion recognition are given, and a discussion about the validity and the expressiveness of different emotions is presented. A comparison between the classifiers build from facial data only, voice data only and from the combination of both data is made here. The need for a better combination of the information from facial expression and voice data is argued.

Keywords: Emotion recognition, facial recognition, signal processing, machine learning.

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Authors: K.Sowmyan, A.Siddarth, D.Menaka

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Several methods have been proposed for color image compression but the reconstructed image had very low signal to noise ratio which made it inefficient. This paper describes a lossy compression technique for color images which overcomes the drawbacks. The technique works on spatial domain where the pixel values of RGB planes of the input color image is mapped onto two dimensional planes. The proposed technique produced better results than JPEG2000, 2DPCA and a comparative study is reported based on the image quality measures such as PSNR and MSE.Experiments on real time images are shown that compare this methodology with previous ones and demonstrate its advantages.

Keywords: Color Image compression, spatial domain, planereduction, root mean square, image restoration

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Authors: R. P. Mahapatra, Jitendra Singh

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This paper proposes a new technique for improving the efficiency of software testing, which is based on a conventional attempt to reduce test cases that have to be tested for any given software. The approach utilizes the advantage of Regression Testing where fewer test cases would lessen time consumption of the testing as a whole. The technique also offers a means to perform test case generation automatically. Compared to one of the techniques in the literature where the tester has no option but to perform the test case generation manually, the proposed technique provides a better option. As for the test cases reduction, the technique uses simple algebraic conditions to assign fixed values to variables (Maximum, minimum and constant variables). By doing this, the variables values would be limited within a definite range, resulting in fewer numbers of possible test cases to process. The technique can also be used in program loops and arrays.

Keywords: Software Testing, Test Case Generation, Test CaseReduction

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Authors: C. Ardil

Abstract:

This article presents a multiple criteria evaluation for a trainer aircraft selection problem using "preference analysis for reference ideal solution (PARIS)” approach. The available relevant literature points to the use of multiple criteria decision making analysis (MCDMA) methods for the problem of trainer aircraft selection, which often involves conflicting multiple criteria. Therefore, this MCDMA study aims to propose a robust systematic integrated framework focusing on the trainer aircraft selection problem. For this purpose, an integrated preference analysis approach based the mean weight and entropy weight procedures with PARIS, and TOPSIS was used for a MCDMA compensating solution. In this study, six trainer aircraft alternatives were evaluated according to six technical decision criteria, and data were collected from the current relevant literature. As a result, the King Air C90GTi alternative was identified as the most suitable trainer aircraft alternative. In order to verify the stability and accuracy of the results obtained, comparisons were made with existing MCDMA methods during the sensitivity and validity analysis process.The results of the application were further validated by applying the comparative analysis-based PARIS, and TOPSIS method. The proposed integrated MCDMA systematic structure is also expected to address the issues encountered in the aircraft selection process. Finally, the analysis results obtained show that the proposed MCDMA method is an effective and accurate tool that can help analysts make better decisions.

Keywords: aircraft, trainer aircraft selection, multiple criteria decision making, multiple criteria decision making analysis, mean weight, entropy weight, MCDMA, PARIS, TOPSIS

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Authors: R. B. Ibrahim, M. S. Argungu, I. M. Mungadi

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It is obvious in this present time, internet has become an indispensable part of human life since its inception. The Internet has provided diverse opportunities to make life so easy for human beings, through the adoption of various channels. Among these channels are email, internet banking, video conferencing, and the like. Email is one of the easiest means of communication hugely accepted among individuals and organizations globally. But over decades the security integrity of this platform has been challenged with malicious activities like Phishing. Email phishing is designed by phishers to fool the recipient into handing over sensitive personal information such as passwords, credit card numbers, account credentials, social security numbers, etc. This activity has caused a lot of financial damage to email users globally which has resulted in bankruptcy, sudden death of victims, and other health-related sicknesses. Although many methods have been proposed to detect email phishing, in this research, the results of multiple machine-learning methods for predicting email phishing have been compared with the use of filter-wrapper feature selection. It is worth noting that all three models performed substantially but one outperformed the other. The dataset used for these models is obtained from Kaggle online data repository, while three classifiers: decision tree, Naïve Bayes, and Logistic regression are ensemble (Bagging) respectively. Results from the study show that the Decision Tree (CART) bagging ensemble recorded the highest accuracy of 98.13% using PEF (Phishing Essential Features). This result further demonstrates the dependability of the proposed model.

Keywords: Ensemble, hybrid, filter-wrapper, phishing.

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Authors: Asma Rabaoui, Zied Lachiri, Noureddine Ellouze

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Discrimination between different classes of environmental sounds is the goal of our work. The use of a sound recognition system can offer concrete potentialities for surveillance and security applications. The first paper contribution to this research field is represented by a thorough investigation of the applicability of state-of-the-art audio features in the domain of environmental sound recognition. Additionally, a set of novel features obtained by combining the basic parameters is introduced. The quality of the features investigated is evaluated by a HMM-based classifier to which a great interest was done. In fact, we propose to use a Multi-Style training system based on HMMs: one recognizer is trained on a database including different levels of background noises and is used as a universal recognizer for every environment. In order to enhance the system robustness by reducing the environmental variability, we explore different adaptation algorithms including Maximum Likelihood Linear Regression (MLLR), Maximum A Posteriori (MAP) and the MAP/MLLR algorithm that combines MAP and MLLR. Experimental evaluation shows that a rather good recognition rate can be reached, even under important noise degradation conditions when the system is fed by the convenient set of features.

Keywords: Sounds recognition, HMM classifier, Multi-style training, Environmental Adaptation, Feature combinations.

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Authors: N. B. Mahesh Kumar, K. Premalatha

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The inherent skin patterns created at the joints in the finger exterior are referred as finger knuckle-print. It is exploited to identify a person in a unique manner because the finger knuckle print is greatly affluent in textures. In biometric system, the region of interest is utilized for the feature extraction algorithm. In this paper, local and global features are extracted separately. Fast Discrete Orthonormal Stockwell Transform is exploited to extract the local features. Global feature is attained by escalating the size of Fast Discrete Orthonormal Stockwell Transform to infinity. Two features are fused to increase the recognition accuracy. A matching distance is calculated for both the features individually. Then two distances are merged mutually to acquire the final matching distance. The proposed scheme gives the better performance in terms of equal error rate and correct recognition rate.

Keywords: Hamming distance, Instantaneous phase, Region of Interest, Recognition accuracy.

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Authors: P. V. V. Rama Rao, M. V. Srikanth, S. Dileep Kumar Varma

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With advances in solid-state power electronic devices and microprocessors, various pulse-width-modulation (PWM) techniques have been developed for industrial applications. This paper presents the comparison of two different PWM techniques, the sinusoidal PWM (SPWM) technique and the space-vector PWM (SVPWM) technique applied to two level VSI for micro grid applications. These two methods are compared by discussing their ease of implementation and by analyzing the output harmonic spectra of various output voltages (line-to-neutral voltages, and line-to-line voltages) and their total harmonic distortion (THD). The SVPWM technique in the under-modulation region can increase the fundamental output voltage by 15.5% over the SPWM technique.

Keywords: SPWM, SVPWM, VSI, Modulation Index.

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Authors: Farshideh Einsele, Rolf Ingold

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Current OCR technology does not allow to accurately recognizing small text images, such as those found in web images. Our goal is to investigate new approaches to recognize very low resolution text images containing antialiased character shapes. This paper presents a preliminary study on the variability of such characters and the feasibility to discriminate them by using geometrical features. In a first stage we analyze the distribution of these features. In a second stage we present a study on the discriminative power for recognizing isolated characters, using various rendering methods and font properties. Finally we present interesting results of our evaluation tests leading to our conclusion and future focus.

Keywords: World Wide Web, document analysis, pattern recognition, Optical Character Recognition.

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Authors: C. Ardil

Abstract:

This paper introduces the concept of neutral sets (NSs) and explores various operations on NSs, along with their associated properties. The foundation of the Neutral Set framework lies in ontological neutrality and the principles of logic, including the Law of Non-Contradiction. By encompassing components for possibility, indeterminacy, and necessity, the NS framework provides a flexible representation of truth, uncertainty, and necessity, accommodating diverse ontological perspectives without presupposing specific existential commitments. The inclusion of Possibility acknowledges the spectrum of potential states or propositions, promoting neutrality by accommodating various viewpoints. Indeterminacy reflects the inherent uncertainty in understanding reality, refraining from making definitive ontological commitments in uncertain situations. Necessity captures propositions that must hold true under all circumstances, aligning with the principle of logical consistency and implicitly supporting the Law of Non-Contradiction. Subsequently, a neutral set-TOPSIS approach is applied in the maintenance strategy selection problem, demonstrating the practical applicability of the NS framework. The paper further explores uncertainty relations and presents the fundamental preliminaries of NS theory, emphasizing its role in fostering ontological neutrality and logical coherence in reasoning.

Keywords: Uncertainty sets, neutral sets, maintenance strategy selection multiple criteria decision-making analysis, MCDM, uncertainty decision analysis, distance function, multiple attribute, decision making, selection method, uncertainty, TOPSIS

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