Search results for: Image Quality

Authors: A. Golmohammadi, B. Jahandideh

Abstract:

One of the determinants of a firm-s prosperity is the customers- perceived service quality and satisfaction. While service quality is wide in scope, and consists of various dimensions, there may be differences in the relative importance of these dimensions in affecting customers- overall satisfaction of service quality. Identifying the relative rank of different dimensions of service quality is very important in that it can help managers to find out which service dimensions have a greater effect on customers- overall satisfaction. Such an insight will consequently lead to more effective resource allocation which will finally end in higher levels of customer satisfaction. This issue – despite its criticality- has not received enough attention so far. Therefore, using a sample of 240 bank customers in Iran, an artificial neural network is developed to address this gap in the literature. As customers- evaluation of service quality is a subjective process, artificial neural networks –as a brain metaphor- may appear to have a potentiality to model such a complicated process. Proposing a neural network which is able to predict the customers- overall satisfaction of service quality with a promising level of accuracy is the first contribution of this study. In addition, prioritizing the service quality dimensions in affecting customers- overall satisfaction –by using sensitivity analysis of neural network- is the second important finding of this paper.

Keywords: service quality, customer satisfaction, relative importance, artificial neural network.

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Authors: P. Guayjarernpanishkand, T. Mayureesawan

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This paper presents a comparison of average outgoing quality limit of the MCSP-2-C plan with MCSP-C when MCSP-2-C has been developed from MCSP-C. The parameters used in MCSP-2- C are: i (the clearance number), c (the acceptance number), m (the number of conforming units to be found before allowing c nonconforming units in the sampling inspection), f1 and f2 (the sampling frequency at level 1 and 2, respectively). The average outgoing quality limit (AOQL) values from two plans were compared and we found that for all sets of i, r, and c values, MCSP-2-C gives higher values than MCSP-C. For all sets of i, r, and c values, the average outgoing quality values of MCSP-C and MCSP-2-C are similar when p is low or high but is difference when p is moderate.

Keywords: average outgoing quality, average outgoing quality limit, continuous sampling plan.

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Authors: Maninder Pal

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Medical digital images usually have low resolution because of nature of their acquisition. Therefore, this paper focuses on zooming these images to obtain better level of information, required for the purpose of medical diagnosis. For this purpose, a strategy for selecting pixels in zooming operation is proposed. It is based on the principle of analog clock and utilizes a combination of point and neighborhood image processing. In this approach, the hour hand of clock covers the portion of image to be processed. For alignment, the center of clock points at middle pixel of the selected portion of image. The minute hand is longer in length, and is used to gain information about pixels of the surrounding area. This area is called neighborhood pixels region. This information is used to zoom the selected portion of the image. The proposed algorithm is implemented and its performance is evaluated for many medical images obtained from various sources such as X-ray, Computerized Tomography (CT) scan and Magnetic Resonance Imaging (MRI). However, for illustration and simplicity, the results obtained from a CT scanned image of head is presented. The performance of algorithm is evaluated in comparison to various traditional algorithms in terms of Peak signal-to-noise ratio (PSNR), maximum error, SSIM index, mutual information and processing time. From the results, the proposed algorithm is found to give better performance than traditional algorithms.

Keywords: Zooming, interpolation, medical images, resolution.

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Authors: Cesar Eduardo Hernández Curiel, Victor Hugo Benítez Baltazar, Jesús Horacio Pacheco Ramírez

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This paper is devoted to present the advances in the design of a prototype that is able to supervise the complex behavior of water quality parameters such as pH and temperature, via a real-time monitoring system. The current water quality tests that are performed in government water quality institutions in Mexico are carried out in problematic locations and they require taking manual samples. The water samples are then taken to the institution laboratory for examination. In order to automate this process, a water quality monitoring system based on wireless sensor networks is proposed. The system consists of a sensor node which contains one pH sensor, one temperature sensor, a microcontroller, and a ZigBee radio, and a base station composed by a ZigBee radio and a PC. The progress in this investigation shows the development of a water quality monitoring system. Due to recent events that affected water quality in Mexico, the main motivation of this study is to address water quality monitoring systems, so in the near future, a more robust, affordable, and reliable system can be deployed.

Keywords: pH measurement, water quality monitoring, wireless sensor networks, ZigBee.

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Authors: Erick López-Ornelas

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As the world changes more rapidly, the demand for update information for resource management, environment monitoring, planning are increasing exponentially. Integration of Remote Sensing with GIS technology will significantly promote the ability for addressing these concerns. This paper presents an alternative way of update GIS applications using image processing and high resolution images. We show a method of high-resolution image segmentation using graphs and morphological operations, where a preprocessing step (watershed operation) is required. A morphological process is then applied using the opening and closing operations. After this segmentation we can extract significant cartographic elements such as urban areas, streets or green areas. The result of this segmentation and this extraction is then used to update GIS applications. Some examples are shown using aerial photography.

Keywords: GIS, Remote Sensing, image segmentation, feature extraction.

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Authors: J. Alamelu Mangai, Satej Wagle, V. Santhosh Kumar

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The exponential increase in the volume of medical image database has imposed new challenges to clinical routine in maintaining patient history, diagnosis, treatment and monitoring. With the advent of data mining and machine learning techniques it is possible to automate and/or assist physicians in clinical diagnosis. In this research a medical image classification framework using data mining techniques is proposed. It involves feature extraction, feature selection, feature discretization and classification. In the classification phase, the performance of the traditional kNN k nearest neighbor classifier is improved using a feature weighting scheme and a distance weighted voting instead of simple majority voting. Feature weights are calculated using the interestingness measures used in association rule mining. Experiments on the retinal fundus images show that the proposed framework improves the classification accuracy of traditional kNN from 78.57 % to 92.85 %.

Keywords: Medical Image Mining, Data Mining, Feature Weighting, Association Rule Mining, k nearest neighbor classifier.

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Authors: Y. Ni, K. Sebri

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The practical implementation of audio-video coupled speech recognition systems is mainly limited by the hardware complexity to integrate two radically different information capturing devices with good temporal synchronisation. In this paper, we propose a solution based on a smart CMOS image sensor in order to simplify the hardware integration difficulties. By using on-chip image processing, this smart sensor can calculate in real time the X/Y projections of the captured image. This on-chip projection reduces considerably the volume of the output data. This data-volume reduction permits a transmission of the condensed visual information via the same audio channel by using a stereophonic input available on most of the standard computation devices such as PC, PDA and mobile phones. A prototype called VMIKE (Visio-Microphone) has been designed and realised by using standard 0.35um CMOS technology. A preliminary experiment gives encouraged results. Its efficiency will be further investigated in a large variety of applications such as biometrics, speech recognition in noisy environments, and vocal control for military or disabled persons, etc.

Keywords: Audio-Visual Speech recognition, CMOS Smartsensor, On-Chip image processing.

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Authors: Yongseok Kwon, Woowon Jeong, Eunjin Cho, Sangkug Chung, Kyehan Rhee

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Steady streaming flow fields induced by a 500 mm bubble oscillating at 12 kHz were measured using microscopic particle image velocimetry (PIV). The accuracy of velocity measurement using a micro PIV system was checked by comparing the measured velocity fields with the theoretical velocity profiles in fully developed laminar flow. The steady streaming flow velocities were measured in the sagittal plane of the bubble attached on the wall. Measured velocity fields showed upward jet flow with two symmetric counter-rotating vortices, and the maximum streaming velocity was about 12 mm/s, which was within the velocity ranges measured by other researchers. The measured streamlines were compared with the analytical solution, and they also showed a reasonable agreement.

Keywords: Oscillating bubble, Particle-Image-Velocimetry microstreaming.

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Authors: Gurmeet Kaur, Jyoti Pruthi

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Agile Software development approaches and techniques are being considered as efficient, effective, and popular methods to the development of software. Agile software developments are useful for developing high-quality software that completes client requirements with zero defects, and in short delivery period. In agile software development methodology, quality is related to coding, which means quality, is managed through the use of approaches like refactoring, pair programming, test-driven development, behavior-driven development, acceptance test-driven development, and demand-driven development. The quality of software is measured using metrics like the number of defects during the development and improvement of the software. Usage of the above-mentioned methods or approaches reduces the possibilities of defects in developed software, and hence improves quality. This paper focuses on the study of agile-based quality methods or approaches for software development that ensures improved quality of software as well as reduced cost, and customer satisfaction.

Keywords: Agile software development, ASD, Acceptance test-driven development, ATDD, Behavior-driven development, BDD, Demand-driven development. DDD, Test-driven development, TDD.

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Authors: Hu Haibo, Liu Yi, He Ming

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The binary phase-only filter digital watermarking embeds the phase information of the discrete Fourier transform of the image into the corresponding magnitudes for better image authentication. The paper proposed an approach of how to implement watermark embedding by quantizing the magnitude, with discussing how to regulate the quantization steps based on the frequencies of the magnitude coefficients of the embedded watermark, and how to embed the watermark at low frequency quantization. The theoretical analysis and simulation results show that algorithm flexibility, security, watermark imperceptibility and detection performance of the binary phase-only filter digital watermarking can be effectively improved with quantization based watermark embedding, and the robustness against JPEG compression will also be increased to some extent.

Keywords: binary phase-only filter, discrete Fourier transform, digital watermarking, image authentication, quantization.

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Authors: Terrence Chen, Thomas S. Huang

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In this paper, we present the region based hidden Markov random field model (RBHMRF), which encodes the characteristics of different brain regions into a probabilistic framework for brain MR image segmentation. The recently proposed TV+L1 model is used for region extraction. By utilizing different spatial characteristics in different brain regions, the RMHMRF model performs beyond the current state-of-the-art method, the hidden Markov random field model (HMRF), which uses identical spatial information throughout the whole brain. Experiments on both real and synthetic 3D MR images show that the segmentation result of the proposed method has higher accuracy compared to existing algorithms.

Keywords: Finite Gaussian mixture model, Hidden Markov random field model, image segmentation, MRI.

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Authors: Lina, Arlends Chris, Bagus Mulyawan, Agus B. Dharmawan

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Blood cell analysis plays a significant role in the diagnosis of human health. As an alternative to the traditional technique conducted by laboratory technicians, this paper presents an automatic white blood cell (leukocyte) detection system using Image Stitching and Color Overlapping Windows. The advantage of this method is to present a detection technique of white blood cells that are robust to imperfect shapes of blood cells with various image qualities. The input for this application is images from a microscope-slide translation video. The preprocessing stage is performed by stitching the input images. First, the overlapping parts of the images are determined, then stitching and blending processes of two input images are performed. Next, the Color Overlapping Windows is performed for white blood cell detection which consists of color filtering, window candidate checking, window marking, finds window overlaps, and window cropping processes. Experimental results show that this method could achieve an average of 82.12% detection accuracy of the leukocyte images.

Keywords: Color overlapping windows, image stitching, leukocyte detection.

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Authors: Saman Ghaffarian, Ilgın Gökasar

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This paper presents a new automatic vehicle detection method from very high resolution aerial images to measure traffic density. The proposed method starts by extracting road regions from image using road vector data. Then, the road image is divided into equal sections considering resolution of the images. Gradient vectors of the road image are computed from edge map of the corresponding image. Gradient vectors on the each boundary of the sections are divided where the gradient vectors significantly change their directions. Finally, number of vehicles in each section is carried out by calculating the standard deviation of the gradient vectors in each group and accepting the group as vehicle that has standard deviation above predefined threshold value. The proposed method was tested in four very high resolution aerial images acquired from Istanbul, Turkey which illustrate roads and vehicles with diverse characteristics. The results show the reliability of the proposed method in detecting vehicles by producing 86% overall F1 accuracy value.

Keywords: Aerial images, intelligent transportation systems, traffic density measurement, vehicle detection.

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Authors: Chiung-Ju Huang

Abstract:

This study utilizes the quantile regression analysis to examine the impact of governance (including democratic quality and technical quality) on happiness in 101 countries worldwide, classified as “developed countries” and “developing countries”. The empirical results show that the impact of democratic quality and technical quality on happiness is significantly positive for “developed countries”, while is insignificant for “developing countries”. The results suggest that the authorities in developed countries can enhance the level of individual happiness by means of improving the democracy quality and technical quality. However, for developing countries, promoting the quality of governance in order to enhance the level of happiness may not be effective. Policy makers in developed countries may pay more attention on increasing real GDP per capita instead of promoting the quality of governance to enhance individual happiness.

Keywords: Governance, happiness, multiple regression, quantile regression.

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Authors: A. Sopharak, B. Uyyanonvara, S. Barman

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Microaneurysm is a key indicator of diabetic retinopathy that can potentially cause damage to retina. Early detection and automatic quantification are the keys to prevent further damage. In this paper, which focuses on automatic microaneurysm detection in images acquired through non-dilated pupils, we present a series of experiments on feature selection and automatic microaneurysm pixel classification. We found that the best feature set is a combination of 10 features: the pixel-s intensity of shade corrected image, the pixel hue, the standard deviation of shade corrected image, DoG4, the area of the candidate MA, the perimeter of the candidate MA, the eccentricity of the candidate MA, the circularity of the candidate MA, the mean intensity of the candidate MA on shade corrected image and the ratio of the major axis length and minor length of the candidate MA. The overall sensitivity, specificity, precision, and accuracy are 84.82%, 99.99%, 89.01%, and 99.99%, respectively.

Keywords: Diabetic retinopathy, microaneurysm, naive Bayes classifier

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Authors: Sherif G. Aly

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In this article, we introduce a mechanism by which the same concept of differentiated services used in network transmission can be applied to provide quality of service levels to pervasive systems applications. The classical DiffServ model, including marking and classification, assured forwarding, and expedited forwarding, are all utilized to create quality of service guarantees for various pervasive applications requiring different levels of quality of service. Through a collection of various sensors, personal devices, and data sources, the transmission of contextsensitive data can automatically occur within a pervasive system with a given quality of service level. Triggers, initiators, sources, and receivers are four entities labeled in our mechanism. An explanation of the role of each is provided, and how quality of service is guaranteed.

Keywords: Pervasive systems, quality of service, differentiated services, mobile devices.

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Authors: Michael Zimba, Darlison Nyirenda

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A novel copy-move image forgery, CMIF, detection method is proposed. The proposed method presents a new approach which relies on electrostatic field theory, EFT. Solely for the purpose of reducing the dimension of a suspicious image, the proposed algorithm firstly performs discrete wavelet transform, DWT, of the suspicious image and extracts only the approximation subband. The extracted subband is then bijectively mapped onto a virtual electrostatic field where concepts of EFT are utilized to extract robust features. The extracted features are invariant to additive noise, JPEG compression, and affine transformation. Finally, same affine transformation selection, SATS, a duplication verification method, is applied to detect duplicated regions. SATS is a better option than the common shift vector method because SATS is insensitive to affine transformation. Consequently, the proposed CMIF algorithm is not only fast but also more robust to attacks compared to the existing related CMIF algorithms. The experimental results show high detection rates, as high as 100% in some cases.

Keywords: Affine transformation, Radix sort, SATS, Virtual electrostatic field.

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Authors: D.R Prince Williams

Abstract:

In this paper, we introduce the notion θ-Euclidean k-fuzzy ideal in semirings and to study the properties of the image and pre image of a θ -Euclidean k-fuzzy ideal in a semirings under epimorphism.

Keywords: semiring, fuzzy ideal, k–fuzzy ideal, θ -Euclidean Lfuzzyideal, θ -Euclidean fuzzy k–ideal, θ -Euclidean k-fuzzy ideal.

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Authors: Nur Adilah Md Zain, Mohd Salehuddin Mohd Zahari, Mohd Hafiz Hanafiah, Muhammad Izzat Zulkifly

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This paper empirically investigates the relationship between Sabah state core tourism products and its destination image. Through a descriptive design using a quantitative method with a self-reported and self-administered questionnaire, this research surveyed the individual international tourists who had visited Sabah and experienced the state’s core tourism products. The research findings clearly indicate that Sabah, one of the states in Malaysia has a lot of valuable resources in the eyes of the international tourists. Interestingly, it was found that Sabah’s core tourism products namely unique marine resources, various nature attractions and cultural diversities have undoubtedly contributed to the state’s tourism image. Good feedbacks and the promising insights from the international tourists’ point of view offer varying consequences, repercussion, and implication to the state government and the relevant authorities. Collaboration and cooperation between all responsible authorities are therefore crucial in strengthening the “total tourism experience” among the international tourists in this state.

Keywords: Tourism core products, marine, cultural, nature, destination image, Sabah.

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Authors: Se Ho Choi, Jong Pil Yun, Boyeul Seo, YoungSu Park, Sang Woo Kim

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This paper presents a real-time defect detection algorithm for high-speed steel bar in coil. Because the target speed is very high, proposed algorithm should process quickly the large volumes of image for real-time processing. Therefore, defect detection algorithm should satisfy two conflicting requirements of reducing the processing time and improving the efficiency of defect detection. To enhance performance of detection, edge preserving method is suggested for noise reduction of target image. Finally, experiment results show that the proposed algorithm guarantees the condition of the real-time processing and accuracy of detection.

Keywords: Defect detection, edge preserving filter, real-time image processing, surface inspection.

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Authors: Hamed Vahdat Nejad, Hameed Reza Pourreza, Hasan Ebrahimi

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A new fuzzy filter is presented for noise reduction of images corrupted with additive noise. The filter consists of two stages. In the first stage, all the pixels of image are processed for determining noisy pixels. For this, a fuzzy rule based system associates a degree to each pixel. The degree of a pixel is a real number in the range [0,1], which denotes a probability that the pixel is not considered as a noisy pixel. In the second stage, another fuzzy rule based system is employed. It uses the output of the previous fuzzy system to perform fuzzy smoothing by weighting the contributions of neighboring pixel values. Experimental results are obtained to show the feasibility of the proposed filter. These results are also compared to other filters by numerical measure and visual inspection.

Keywords: Additive noise, Fuzzy logic, Image processing, Noise reduction.

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Authors: U. Idachaba, F. Z. Wang, A. Qi, N. Helian

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Artificial Bee Colony (ABC) algorithm is a relatively new swarm intelligence technique for clustering. It produces higher quality clusters compared to other population-based algorithms but with poor energy efficiency, cluster quality consistency and typically slower in convergence speed. Inspired by energy saving foraging behavior of natural honey bees this paper presents a Quality and Quantity Aware Artificial Bee Colony (Q2ABC) algorithm to improve quality of cluster identification, energy efficiency and convergence speed of the original ABC. To evaluate the performance of Q2ABC algorithm, experiments were conducted on a suite of ten benchmark UCI datasets. The results demonstrate Q2ABC outperformed ABC and K-means algorithm in the quality of clusters delivered.

Keywords: Artificial bee colony algorithm, clustering.

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Authors: Lorenzo Putzu, Cecilia Di Ruberto

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The counting and analysis of blood cells allows the evaluation and diagnosis of a vast number of diseases. In particular, the analysis of white blood cells (WBCs) is a topic of great interest to hematologists. Nowadays the morphological analysis of blood cells is performed manually by skilled operators. This involves numerous drawbacks, such as slowness of the analysis and a nonstandard accuracy, dependent on the operator skills. In literature there are only few examples of automated systems in order to analyze the white blood cells, most of which only partial. This paper presents a complete and fully automatic method for white blood cells identification from microscopic images. The proposed method firstly individuates white blood cells from which, subsequently, nucleus and cytoplasm are extracted. The whole work has been developed using MATLAB environment, in particular the Image Processing Toolbox.

Keywords: Automatic detection, Biomedical image processing, Segmentation, White blood cell analysis.

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Authors: Ching-hui Lin, Yen-Chieh Wen

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The main purpose of this study is to analyze the feelings of tourists for the service quality of the bikeway. In addition, this study also analyzed the causal relationship between service quality and satisfaction to visitor-s lane loyalty. In this study, the Ya Tam San bikeway visitor-s subjects, using the designated convenience sampling carried out the survey, a total of 651 questionnaires were validly. Valid questionnaires after statistical analysis, the following findings: 1. Visitor-s lane highest quality of service project: the routes through the region weather pleasant. Lane "with health and sports," the highest satisfaction various factors of service quality and satisfaction, loyal between correlations exist. 4. Guided tours of bikeways, the quality of the environment, and modeling imagery can effectively predict visitor satisfaction. 5. Quality of bikeway, public facilities, guided tours, and modeling imagery can effectively predict visitor loyalty. According to the above results, the study not only makes recommendations to the government units and the bicycle industry, also asked the research direction for future researchers.

Keywords: Service quality, satisfaction, loyal, bikeway.

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Authors: K. K. Aggarwal, Yogesh Singh, Arvinder Kaur, Ruchika Malhotra

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Importance of software quality is increasing leading to development of new sophisticated techniques, which can be used in constructing models for predicting quality attributes. One such technique is Artificial Neural Network (ANN). This paper examined the application of ANN for software quality prediction using Object- Oriented (OO) metrics. Quality estimation includes estimating maintainability of software. The dependent variable in our study was maintenance effort. The independent variables were principal components of eight OO metrics. The results showed that the Mean Absolute Relative Error (MARE) was 0.265 of ANN model. Thus we found that ANN method was useful in constructing software quality model.

Keywords: Software quality, Measurement, Metrics, Artificial neural network, Coupling, Cohesion, Inheritance, Principal component analysis.

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Authors: Sudipta Nath, Arindam Dey, Abhijit Chakrabarti

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This paper presents features that characterize power quality disturbances from recorded voltage waveforms using wavelet transform. The discrete wavelet transform has been used to detect and analyze power quality disturbances. The disturbances of interest include sag, swell, outage and transient. A power system network has been simulated by Electromagnetic Transients Program. Voltage waveforms at strategic points have been obtained for analysis, which includes different power quality disturbances. Then wavelet has been chosen to perform feature extraction. The outputs of the feature extraction are the wavelet coefficients representing the power quality disturbance signal. Wavelet coefficients at different levels reveal the time localizing information about the variation of the signal.

Keywords: Power quality, detection of disturbance, wavelet transform, multiresolution signal decomposition.

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Authors: Akhil Kumar Arya, Jagdeep Singh Lather, Lillie Dewan

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In this paper is to evaluate audio and speech quality with the help of Digital Audio Watermarking Technique under the different types of attacks (signal impairments) like Gaussian Noise, Compression Error and Jittering Effect. Further attacks are considered as Hostile Environment. Audio and Speech Quality Evaluation is an important research topic. The traditional way for speech quality evaluation is using subjective tests. They are reliable, but very expensive, time consuming, and cannot be used in certain applications such as online monitoring. Objective models, based on human perception, were developed to predict the results of subjective tests. The existing objective methods require either the original speech or complicated computation model, which makes some applications of quality evaluation impossible.

Keywords: Digital Watermarking, DCT, Speech Quality, Attacks.

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Authors: Kang Chia Yang, Hushairi HJ Zen, Nur Ikhmar@Najemeen Binti Ayob

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Power quality is used to describe the degree of consistency of electrical energy expected from generation source to point of use. The term power quality refers to a wide variety of electromagnetic phenomena that characterize the voltage and current at a given time and at a given location on the power system. Power quality problems can be defined as problem that results in failure of customer equipments, which manifests itself as an economic burden to users, or produces negative impacts on the environment. Voltage stability, power factor, harmonics pollution, reactive power and load unbalance are some of the factors that affect the consistency or the quality level. This research proposal proposes to investigate and analyze the causes and effects of power quality to homes and industries in Sarawak. The increasing application of electronics equipment used in the industries and homes has caused a big impact on the power quality. Many electrical devices are now interconnected to the power network and it can be observed that if the power quality of the network is good, then any loads connected to it will run smoothly and efficiently. On the other hand, if the power quality of the network is bad, then loads connected to it will fail or may cause damage to the equipments and reduced its lifetime. The outcome of this research will enable better and novel solutions of poor power quality to small industries and reduce damage of electrical devices and products in the industries.

Keywords: Power quality, power network, voltage dip.

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Authors: C. R. Balamurugan, P. Vijayakumar, P. Kiruba, S. Arun Kanna, E. R. Hariprasath, C. Anu Priya

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This paper studies in details about the need of quadcopter in various fields especially in the place of remote area where the road transportation facility is very less. It is used to monitor and collect data in a specific region. The movement of this quadcopter is controlled by the Raspberry Pi. FPV camera is used for capturing the image and will transmit the image to the receiver which can be monitored using an android smart phone. This is mainly used for surveillance purpose and hidden activities can be captured.

Keywords: FPV camera, A2212 brushless direct current motor, Raspberry Pi, lithium polymer battery.

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Authors: Najib Ahmad Marzuki, Che Su Mustaffa, Johana Johari, Nur Hafizza Rahaman

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The purpose of this paper is to examine the effects and relationship of stress and social support towards the quality of life among flood victims in Malaysia. A total of 764 respondents took part in the survey via convenience sampling. The Depression, Anxiety and Stress scale (DASS) was utilized to measure stress while The Multidimensional Scale of Perceived Social Support was used to measure social support. To measure quality of life, the combination of WHO Quality of Life – BREF (WHOQOL-BREF) and The Impact of Event Scale – Revised (IES-R) were utilized. The findings of this study indicate that there were significant correlations between variables in the study. The findings showed a significant negative relation between stress and quality of life; and significant positive correlations between support from family as well as support from friends with quality of life. Stress and support from family were found to be significant predictors that influence the quality of life among flood victims.

Keywords: Stress, social support, quality of life, flood victims.

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