Search results for: cointegration techniques

Authors: H. Kelkoul, Y. Zaz

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Nowadays, the vigorous popularity of video processing techniques has resulted in an explosive growth of multimedia data illegal use. So, watermarking security has received much more attention. The purpose of this paper is to explore some watermarking techniques in order to observe their specificities and select the finest methods to apply in digital cinema domain against movie piracy by creating an invisible watermark that includes the date, time and the place where the hacking was done. We have studied three principal watermarking techniques in the frequency domain: Spread spectrum, Wavelet transform domain and finally the digital cinema watermarking transform domain. In this paper, a detailed technique is presented where embedding is performed using direct sequence spread spectrum technique in DWT transform domain. Experiment results shows that the algorithm provides high robustness and good imperceptibility.

Keywords: digital cinema, watermarking, wavelet DWT, spread spectrum, JPEG2000 MPEG4

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Authors: S. R. M. Krishna, R. Santosh Kumar, V. Kamakshi Prasad

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Machine learning techniques are applied for the analysis of the impact of mental illness on the burden of disease. It is calculated using the disability-adjusted life year (DALY). DALYs for a disease is the sum of years of life lost due to premature mortality (YLLs) + No of years of healthy life lost due to disability (YLDs). The critical analysis is done based on the Data sources, machine learning techniques and feature extraction method. The reviewing is done based on major databases. The extracted data is examined using statistical analysis and machine learning techniques were applied. The prediction of the impact of mental illness on the population using machine learning techniques is an alternative approach to the old traditional strategies, which are time-consuming and may not be reliable. The approach makes it necessary for a comprehensive adoption, innovative algorithms, and an understanding of the limitations and challenges. The obtained prediction is a way of understanding the underlying impact of mental illness on the health of the people and it enables us to get a healthy life expectancy. The growing impact of mental illness and the challenges associated with the detection and treatment of mental disorders make it necessary for us to understand the complete effect of it on the majority of the population.

Keywords: ML, DAL, YLD, YLL

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Authors: M. Sai Veerendra

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Today, money laundering (ML) poses a serious threat not only to financial institutions but also to the nation. This criminal activity is becoming more and more sophisticated and seems to have moved from the cliché of drug trafficking to financing terrorism and surely not forgetting personal gain. Most of the financial institutions internationally have been implementing anti-money laundering solutions (AML) to fight investment fraud activities. However, traditional investigative techniques consume numerous man-hours. Recently, data mining approaches have been developed and are considered as well-suited techniques for detecting ML activities. Within the scope of a collaboration project on developing a new data mining solution for AML Units in an international investment bank in Ireland, we survey recent data mining approaches for AML. In this paper, we present not only these approaches but also give an overview on the important factors in building data mining solutions for AML activities.

Keywords: data mining, clustering, money laundering, anti-money laundering solutions

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Authors: Hana Rabbouch

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In recent years, there has been considerable growth of denoising techniques mainly devoted to medical imaging. This important evolution is not only due to the progress of computing techniques, but also to the emergence of multi-resolution analysis (MRA) on both mathematical and algorithmic bases. In this paper, a comparative study is conducted between the two best-known MRA-based decomposition techniques: the Empirical Mode Decomposition (EMD) and the Discrete Wavelet Transform (DWT). The comparison is carried out in a framework of multi-scale denoising, where a Non-Local Means (NLM) filter is performed scale-by-scale to a sample of benchmark medical images. The results prove the effectiveness of the multiscaled denoising, especially when the NLM filtering is coupled with the EMD.

Keywords: medical imaging, non local means, denoising, multiscaled analysis, empirical mode decomposition, wavelets

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Authors: Lubabatu Sada Sodangu

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Malaria is a major cause of death in tropical and subtropical nations. Malaria cases are continually rising as a result of a number of factors, despite the fact that the condition is now treatable using effective methods. In this situation, quick and effective diagnostic methods are essential for the management and control of malaria. Malaria diagnosis using conventional methods is still troublesome, hence new technologies have been created and implemented to get around the drawbacks. The review describes the currently known malaria diagnostic techniques, their strengths and shortcomings.

Keywords: malaria, technique, diagnosis, Africa

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Authors: Lubabatu Sada Sodangi

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Malaria is a major cause of death in tropical and subtropical nations. Malaria cases are continually rising as a result of a number of factors, despite the fact that the condition is now treatable using effective methods. In this situation, quick and effective diagnostic methods are essential for the management and control of malaria. Malaria diagnosis using conventional methods is still troublesome; hence, new technologies have been created and implemented to get around the drawbacks. The review describes the currently known malaria diagnostic techniques, their strengths, and shortcomings.

Keywords: malaria, technique, diagnosis, Africa

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Authors: Mukul Anand

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Quality oriented affordable shelter for all has always been the key issue in the housing sector of our country. Homelessness is the acute form of housing need. It is a paradox that in spite of innumerable government initiated programmes for affordable housing, certain section of society is still devoid of shelter. About nineteen million (18.78 million) households grapple with housing shortage in Urban India in 2012. In Indian scenario there is major mismatch between the people for whom the houses are being built and those who need them. The prime force faced by public authorities in facilitation of quality housing for all is high cost of construction. The present paper will comprehend executable techniques for dilution of cost factor in housing the homeless. The key actors responsible for delivery of cheap housing stock such as capacity building, resource optimization, innovative low cost building material and indigenous skeleton housing system will also be incorporated in developing these techniques. Time performance, which is an important angle of above actors, will also be explored so as to increase the effectiveness of low cost housing. Along with this best practices will be taken up as case studies where both conventional techniques of housing and innovative low cost housing techniques would be cited. Transportation consists of approximately 30% of total construction budget. Thus use of alternative local solutions depending upon the region would be covered so as to highlight major components of low cost housing. Government is laid back regarding base line information on use of innovative low cost method and technique of resource optimization. Therefore, the paper would be an attempt to bring to light simpler solutions for achieving low cost housing.

Keywords: construction, cost, housing, optimization, shelter

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Authors: M. A. I Perera, C. R. Wijesinghe, A. R. Weerasinghe

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his study was conducted to review and identify the unsupervised techniques that can be employed to analyze gene expression data in order to identify better subtypes of tumors. Identifying subtypes of cancer help in improving the efficacy and reducing the toxicity of the treatments by identifying clues to find target therapeutics. Process of gene expression data analysis described under three steps as preprocessing, clustering, and cluster validation. Feature selection is important since the genomic data are high dimensional with a large number of features compared to samples. Hierarchical clustering and K Means are often used in the analysis of gene expression data. There are several cluster validation techniques used in validating the clusters. Heatmaps are an effective external validation method that allows comparing the identified classes with clinical variables and visual analysis of the classes.

Keywords: cancer subtypes, gene expression data analysis, clustering, cluster validation

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Authors: Tae-Uk Yun, Pullip Chung, Kee-Young Kwahk, Hyunchul Ahn

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Fake news is defined as the news articles that are intentionally and verifiably false, and could mislead readers. Spread of fake news may provoke anxiety, chaos, fear, or irrational decisions of the public. Thus, detecting fake news and preventing its spread has become very important issue in our society. However, due to the huge amount of fake news produced every day, it is almost impossible to identify it by a human. Under this context, researchers have tried to develop automated fake news detection using machine learning techniques over the past years. But, there have been no prior studies proposed an automated fake news detection method for Korean news to our best knowledge. In this study, we aim to detect Korean fake news using text mining and machine learning techniques. Our proposed method consists of two steps. In the first step, the news contents to be analyzed is convert to quantified values using various text mining techniques (topic modeling, TF-IDF, and so on). After that, in step 2, classifiers are trained using the values produced in step 1. As the classifiers, machine learning techniques such as logistic regression, backpropagation network, support vector machine, and deep neural network can be applied. To validate the effectiveness of the proposed method, we collected about 200 short Korean news from Seoul National University’s FactCheck. which provides with detailed analysis reports from 20 media outlets and links to source documents for each case. Using this dataset, we will identify which text features are important as well as which classifiers are effective in detecting Korean fake news.

Keywords: fake news detection, Korean news, machine learning, text mining

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Authors: Arushi Singh, Anjana Jain, Prakash Vyavahare

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Recently, Li-Fi(light-fiedelity) has been launched based on VLC(visible light communication) technique, 100 times faster than WiFi. Now 5G mobile communication system is proposed to use VLC-OFDM as the transmission technique. The VLC system focused on visible rays, is considered for efficient spectrum use and easy intensity modulation through LEDs. The reason of high speed in VLC is LED, as they flicker incredibly fast(order of MHz). Another advantage of employing LED is-it acts as low pass filter results no out-of-band emission. The VLC system falls under the category of ‘green technology’ for utilizing LEDs. In present scenario, OFDM is used for high data-rates, interference immunity and high spectral efficiency. Inspite of the advantages OFDM suffers from large PAPR, ICI among carriers and frequency offset errors. Since, the data transmission technique used in VLC system is OFDM, the system suffers the drawbacks of OFDM as well as VLC, the non-linearity dues to non-linear characteristics of LED and PAPR of OFDM due to which the high power amplifier enters in non-linear region. The proposed paper focuses on reduction of PAPR in VLC-OFDM systems. Many techniques are applied to reduce PAPR such as-clipping-introduces distortion in the carrier; selective mapping technique-suffers wastage of bandwidth; partial transmit sequence-very complex due to exponentially increased number of sub-blocks. The paper discusses three companding techniques namely- µ-law, A-law and advance A-law companding technique. The analysis shows that the advance A-law companding techniques reduces the PAPR of the signal by adjusting the companding parameter within the range. VLC-OFDM systems are the future of the wireless communication but non-linearity in VLC-OFDM is a severe issue. The proposed paper discusses the techniques to reduce PAPR, one of the non-linearities of the system. The companding techniques mentioned in this paper provides better results without increasing the complexity of the system.

Keywords: non-linear companding techniques, peak to average power ratio (PAPR), visible light communication (VLC), VLC-OFDM

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Authors: Gayathri Nagarajan, L. D. Dhinesh Babu

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Health care is one of the prominent industries that generate voluminous data thereby finding the need of machine learning techniques with big data solutions for efficient processing and prediction. Missing data, incomplete data, real time streaming data, sensitive data, privacy, heterogeneity are few of the common challenges to be addressed for efficient processing and mining of health care data. In comparison with other applications, accuracy and fast processing are of higher importance for health care applications as they are related to the human life directly. Though there are many machine learning techniques and big data solutions used for efficient processing and prediction in health care data, different techniques and different frameworks are proved to be effective for different applications largely depending on the characteristics of the datasets. In this paper, we present a framework that uses ensemble machine learning technique gradient boosted trees for data classification in health care big data. The framework is built on Spark platform which is fast in comparison with other traditional frameworks. Unlike other works that focus on a single technique, our work presents a comparison of six different machine learning techniques along with gradient boosted trees on datasets of different characteristics. Five benchmark health care datasets are considered for experimentation, and the results of different machine learning techniques are discussed in comparison with gradient boosted trees. The metric chosen for comparison is misclassification error rate and the run time of the algorithms. The goal of this paper is to i) Compare the performance of gradient boosted trees with other machine learning techniques in Spark platform specifically for health care big data and ii) Discuss the results from the experiments conducted on datasets of different characteristics thereby drawing inference and conclusion. The experimental results show that the accuracy is largely dependent on the characteristics of the datasets for other machine learning techniques whereas gradient boosting trees yields reasonably stable results in terms of accuracy without largely depending on the dataset characteristics.

Keywords: big data analytics, ensemble machine learning, gradient boosted trees, Spark platform

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Authors: Dilip Singh Sisodia, Shrish Verma

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Spamming is the most common issue seen nowadays in the Internet especially in Online Social Networking Sites (like Facebook, Twitter, and Google+ etc.). Spam messages keep wasting Internet bandwidth and the storage space of servers. On social network sites; spammers often disguise themselves by creating fake accounts and hijacking user’s accounts for personal gains. They behave like normal user and they continue to change their spamming strategy. To prevent this, most modern spam-filtering solutions are deployed on the receiver side; they are good at filtering spam for end users. In this paper we are presenting some spamming techniques their behaviour and possible solutions. We have analyzed how Spammers enters into online social networking sites (OSNSs) and how they target it and the techniques they use for it. The five discussed techniques of spamming techniques which are clickjacking, social engineered attacks, cross site scripting, URL shortening, and drive by download. We have used elgg framework for demonstration of some of spamming threats and respective implementation of solutions.

Keywords: online social networking sites, spam, attacks, internet, clickjacking / likejacking, drive-by-download, URL shortening, networking, socially engineered attacks, elgg framework

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Authors: Saurabh Kumar

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In the fiercely competitive landscape of e-commerce, understanding and mitigating customer churn has become paramount for sustainable business growth. This paper presents a thorough investigation into the application of machine learning techniques for churn prediction in e-commerce, aiming to provide actionable insights for businesses seeking to enhance customer retention strategies. We conduct a comparative study of various machine learning algorithms, including traditional statistical methods and ensemble techniques, leveraging a rich dataset sourced from Kaggle. Through rigorous evaluation, we assess the predictive performance, interpretability, and scalability of each method, elucidating their respective strengths and limitations in capturing the intricate dynamics of customer churn. We identified the XGBoost classifier to be the best performing. Our findings not only offer practical guidelines for selecting suitable modeling approaches but also contribute to the broader understanding of customer behavior in the e-commerce domain. Ultimately, this research equips businesses with the knowledge and tools necessary to proactively identify and address churn, thereby fostering long-term customer relationships and sustaining competitive advantage.

Keywords: customer churn, e-commerce, machine learning techniques, predictive performance, sustainable business growth

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Authors: Magno Enrique Mendoza Meza

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This paper deals with the comparison of three control techniques: the hysteresis on-off control (HyOOC), the hybrid on-off control (HOOC) and the simple Structured Treatment Interruptions (sSTI). These techniques are applied to the mathematical model developed by Kirschner and Webb. To compare these techniques we use a cost functional that minimize the wild-type virus population and the mutant virus population, but the main objective is to minimize the systemic cost of treatment and maximize levels of healthy CD4+ T cells. HyOOC, HOOC, and sSTI are applied to the drug therapies using a reverse transcriptase and protease inhibitors; simulations show that these controls maintain the uninfected cells in a small, bounded neighborhood of a pre-specified level. The controller HyOOC and HOOC are designed by appropriate choice of virtual equilibrium points.

Keywords: virus dynamics, on-off control, hysteresis, multi-drug therapies

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Authors: Amit Kamra, V. K. Jain, Pragya

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Mammography is widely used technique for breast cancer screening. There are various other techniques for breast cancer screening but mammography is the most reliable and effective technique. The images obtained through mammography are of low contrast which causes problem for the radiologists to interpret. Hence, a high quality image is mandatory for the processing of the image for extracting any kind of information from it. Many contrast enhancement algorithms have been developed over the years. In the present work, an efficient morphology based technique is proposed for contrast enhancement of masses in mammographic images. The proposed method is based on Multiscale Morphology and it takes into consideration the scale of the structuring element. The proposed method is compared with other state-of-the-art techniques. The experimental results show that the proposed method is better both qualitatively and quantitatively than the other standard contrast enhancement techniques.

Keywords: enhancement, mammography, multi-scale, mathematical morphology

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Authors: Simon Ibor Akpama

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The study investigated the extent to which innovative teaching-learning techniques can influence and attenuate learning difficulties among adult learners participating in different literacy education programmes in Calabar Metropolis, Cross River State, Nigeria. A quasi-experimental design was adopted to collect data from a sample size of 150 participants of the programme. The sample was drawn using the simple random sampling method. As an experimental study, the 150 participants were divided into two equal groups –the first was the experimental group while the second was the control. A pre-test was administered to the two groups which were later exposed to a post-test after treatment. Two instruments were used for data collection. The first was the guide for the Literacy Learning Difficulties Inventory (LLDI). Three hypotheses were postulated and tested as .05 level of significance using Analysis of Covariance (ANOVA) test statistics. Results of the analysis firstly showed that the two groups (treatment and control) did not differ in the pre-test regarding their literacy learning difficulties. Secondly, the result showed that for each hypothesis, innovative teaching-learning techniques significantly influenced adult learners’ (participants) literacy learning difficulties. Based on these findings, the study recommends the use of innovative teaching-learning techniques in adult literacy education centres to mitigate the learning difficulties of adult learners in literacy education programmes in Calabar Metropolis.

Keywords: teaching, learning, techniques, innovative, difficulties, programme

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Authors: Vishal V. Choudhari, Gaurao A. Dongre, S. P. Diwan

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A number of reference current generation have been developed for analysis of shunt active power filter to mitigate the load compensation. Depending upon the type of load the technique has to be chosen. In this paper, six reference current generation techniques viz. instantaneous reactive power theory(IRP), Synchronous reference frame theory(SRF), Perfect harmonic cancellation(PHC), Unity power factor method(UPF), Self-tuning filter method(STF), Predictive filtering method(PFM) are compared for different operating conditions. The harmonics are introduced because of non-linear loads in the system. These harmonics are eliminated using above techniques. The results and performance of system simulated on MATLAB/Simulink platform. The system is experimentally implemented using DS1104 card of dSPACE system.

Keywords: SAPF, power quality, THD, IRP, SRF, dSPACE module DS1104

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Authors: Keiji Komatsu，Tetsuo Sekiya, Ayumu Toyama, Atsushi Nakamura, Ikumi Toda, Shigeo Ohshio, Hiroyuki Muramatsu, Hidetoshi Saitoh

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Yttrium oxide (Y2O3) films have been successfully deposited with yttrium-ethylenediaminetetraacetic acid (EDTA･Y･H) complexes prepared by various milling techniques. The effects of the properties of the EDTA･Y･H complex on the properties of the deposited Y2O3 films have been analyzed. Seven different types of the raw EDTA･Y･H complexes were prepared by various commercial milling techniques such as ball milling, hammer milling, commercial milling, and mortar milling. The milled EDTA･Y･H complexes exhibited various particle sizes and distributions, depending on the milling method. Furthermore, we analyzed the crystal structure, morphology and elemental distribution profile of the metal oxide films deposited on stainless steel substrate with the milled EDTA･Y･H complexes. Depending on the milling technique, the flow properties of the raw powders differed. The X-ray diffraction pattern of all the samples revealed the formation of Y2O3 crystalline phase, irrespective of the milling technique. Of all the different milling techniques, the hammer milling technique is considered suitable for fabricating dense Y2O3 films.

Keywords: powder sizes and distributions, flame spray coating techniques, Yttrium oxide

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Authors: Andrew Clark

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McCauley, Bassler, and Gunaratne show that integration I(d) processes as used in economics and finance do not necessarily produce stationary increments, which are required to determine causality in both the short term and the long term. This paper follows their lead and shows I(d) aluminum cash and futures log prices at daily and weekly intervals do not have stationary increments, which means prior causality studies using I(d) processes need to be re-examined. Wavelets based on undifferenced cash and futures log prices do have stationary increments and are used along with transfer entropy (versus cointegration) to measure causality. Wavelets exhibit causality at most daily time scales out to 1 year, and weekly time scales out to 1 year and more. To determine stationarity, localized stationary wavelets are used. LSWs have the benefit, versus other means of testing for stationarity, of using multiple hypothesis tests to determine stationarity. As informational flows exist between cash and futures at daily and weekly intervals, the aluminum market is efficient. Therefore, hedges used by producers and consumers of aluminum need not have a big concern in terms of the underestimation of hedge ratios. Questions about arbitrage given efficiency are addressed in the paper.

Keywords: transfer entropy, nonstationary increments, wavelets, localized stationary wavelets, localized stationary wavelets

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Authors: Sadiq J. Abou-Loukh, Hanan M. Habbi

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This paper presents a steganography to hide the transmitted information without excite suspicious and also illustrates the level of secrecy that can be increased by using cryptography techniques. The proposed system has been implemented firstly by encrypted image file one time pad key and secondly encrypted message that hidden to perform encryption followed by image embedding. Then the new image file will be created from the original image by using four triangles operation, the new image is processed by one of two image processing techniques. The proposed two processing techniques are thresholding and differential predictive coding (DPC). Afterwards, encryption or decryption keys are generated by functional key generator. The generator key is used one time only. Encrypted text will be hidden in the places that are not used for image processing and key generation system has high embedding rate (0.1875 character/pixel) for true color image (24 bit depth).

Keywords: encryption, thresholding, differential predictive coding, four triangles operation

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Authors: Rahul Srivastava, Priti Pundir, Y. R. Sood, Rajnish Shrivastava

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For the interpretation of the signatures of sweep frequency response analysis(SFRA) of transformer different types of statistical techniques serves as an effective tool for doing either phase to phase comparison or sister unit comparison. In this paper with the discussion on SFRA several statistics techniques like cross correlation coefficient (CCF), root square error (RSQ), comparative standard deviation (CSD), Absolute difference, mean square error(MSE),Min-Max ratio(MM) are presented through several case studies. These methods require sample data size and spot frequencies of SFRA signatures that are being compared. The techniques used are based on power signal processing tools that can simplify result and limits can be created for the severity of the fault occurring in the transformer due to several short circuit forces or due to ageing. The advantages of using statistics techniques for analyzing of SFRA result are being indicated through several case studies and hence the results are obtained which determines the state of the transformer.

Keywords: absolute difference (DABS), cross correlation coefficient (CCF), mean square error (MSE), min-max ratio (MM-ratio), root square error (RSQ), standard deviation (CSD), sweep frequency response analysis (SFRA)

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Authors: F. Yildiz, S. Y. Oturanc

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Advances technology in the field of photogrammetry replaces analog cameras with reflection on aircraft GPS/IMU system with a digital aerial camera. In this system, when determining the position of the camera with the GPS, camera rotations are also determined by the IMU systems. All around the world, digital aerial cameras have been used for the photogrammetry applications in the last ten years. In this way, in terms of the work done in photogrammetry it is possible to use time effectively, costs to be reduced to a minimum level, the opportunity to make fast and accurate. Geo-referencing techniques that are the cornerstone of the GPS / INS systems, photogrammetric triangulation of images required for balancing (interior and exterior orientation) brings flexibility to the process. Also geo-referencing process; needed in the application of photogrammetry targets to help to reduce the number of ground control points. In this study, the use of direct and indirect geo-referencing techniques on the accuracy of the points was investigated in the production of photogrammetric mapping.

Keywords: photogrammetry, GPS/IMU systems, geo-referecing, digital aerial camera

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Authors: Shamil Mardi Al Islam, Zaima Ahmed

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The aim of this article is to explore whether certain macroeconomic variables such as industrial index, inflation, broad money, exchange rate and deposit rate as a proxy for interest rate are interlinked with Dhaka stock price index (DSEX index) precisely after the introduction of new index by Dhaka Stock Exchange (DSE) since January 2013. Bangladesh stock market has experienced rapid growth since its inception. It might not be a very well-developed capital market as compared to its neighboring counterparts but has been a strong avenue for investment and resource mobilization. The data set considered consists of monthly observations, for a period of four years from January 2013 to June 2018. Findings from cointegration analysis suggest that DSEX and macroeconomic variables have a significant long-run relationship. VAR decomposition based on VAR estimated indicates that money supply explains a significant portion of variation of stock index whereas, inflation is found to have the least impact. Impact of industrial index is found to have a low impact compared to the exchange rate and deposit rate. Policies should there aim to increase industrial production in order to enhance stock market performance. Further reasonable money supply should be ensured by authorities to stimulate stock market performance.

Keywords: deposit rate, DSEX, industrial index, VAR

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Authors: M. S. Sukumar

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Our objective is to develop a full-fledged system for exploring and studying nature of fossils and to extend this to underwater archaeology and mineral mapping. This includes aerial surveying, imaging techniques, artefact extraction and spectrum analysing techniques. These techniques help in regular monitoring of fossils and also the sensing system. The ROV was designed to complete several tasks which simulate collecting data and samples. Given the time constraints, the ROV was engineered for efficiency and speed in performing tasks. Its other major design consideration was modularity, allowing the team to distribute the building process, to easily test systems as they were completed and troubleshoot and replace systems as necessary. Our design itself had several challenges of on-board waterproofed sensor mounting, waterproofing of motors, ROV stability criteria, camera mounting and hydrophone sound acquisition.

Keywords: remotely operated vehicle (ROV) dragonair, underwater archaeology, full-fledged system, aerial imaging and detection

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Authors: K. Y. You, Y. L. Then

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In the recent years, the hair building fiber has become popular, in other words, it is an effective method which helps people who suffer hair loss or sparse hair since the hair building fiber is capable to create a natural look of simulated hair rapidly. In the markets, there are a lot of hair fiber brands that have been designed to formulate an intense bond with hair strands and make the hair appear more voluminous instantly. However, those products have their own set of properties. Thus, in this report, some measurement techniques are proposed to identify those products. Up to five different brands of hair fiber are tested. The electrostatic and dielectric properties of the hair fibers are macroscopically tested using design DC and high-frequency microwave techniques. Besides, the hair fibers are microscopically analysis by magnifying the structures of the fiber using scanning electron microscope (SEM). From the SEM photos, the comparison of the uniformly shaped and broken rate of the hair fibers in the different bulk samples can be observed respectively.

Keywords: hair fiber, electrostatic, dielectric properties, broken rate, microwave techniques

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Authors: Rashid Mahmood

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The network as a service (NaaS) usage has been well-known from the last few years in the many applications, like mission critical applications. In the NaaS, prevention method is not adequate as the security concerned, so the detection method should be added to the security issues in NaaS. The authentication and encryption are considered the first solution of the NaaS problem whereas now these are not sufficient as NaaS use is increasing. In this paper, we are going to present the concept of intrusion detection and then survey some of major intrusion detection techniques in NaaS and aim to compare in some important fields.

Keywords: IDS, cloud, naas, detection

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Authors: Asmaa M. Hussein, Amr Wassal, Ahmed Farouk Al-Sadek, A. F. Abd El-Rahman

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In this study, a multivariate analysis of potato spectroscopic data was presented to detect the presence of brown rot disease or not. Near-Infrared (NIR) spectroscopy (1,350-2,500 nm) combined with multivariate analysis was used as a rapid, non-destructive technique for the detection of brown rot disease in potatoes. Spectral measurements were performed in 565 samples, which were chosen randomly at the infection place in the potato slice. In this study, 254 infected and 311 uninfected (brown rot-free) samples were analyzed using different advanced statistical analysis techniques. The discrimination performance of different multivariate analysis techniques, including classification, pre-processing, and dimension reduction, were compared. Applying a random forest algorithm classifier with different pre-processing techniques to raw spectra had the best performance as the total classification accuracy of 98.7% was achieved in discriminating infected potatoes from control.

Keywords: Brown rot disease, NIR spectroscopy, potato, random forest

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Authors: Asia Majeed

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The learning of mathematics in science, engineering and social science programs can be enhanced through practical problem-solving techniques. The instructors can design their lessons with some strategies to improve students’ educational needs and accomplishments in mathematics classrooms. The use of technology in class problem solving and application sessions can enhance deep understanding of mathematics among students. As mathematician, we believe in subject specific and content-driven teaching methods. Through technology the relationship between the physical problems and the mathematical models can be analyzed. This paper is about selective use of technology in mathematics classrooms and helpful to others mathematics instructors who wishes to improve their traditional teaching techniques to improve students’ attitude in learning mathematics. These techniques corpus can be used in teaching large mathematics classes in science, technology, engineering, and social science.

Keywords: attitude in learning mathematics, mathematics, non-mathematics undergraduate students, technology

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Authors: T. Garba, Y. Y. Babanyara, T. O. Quddus, A. K. Mukatari

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Human activities make environmental parameters in order to keep on changing globally. While some changes are necessary and beneficial to flora and fauna, others have serious consequences threatening the survival of their natural habitat if these changes are not properly monitored and mitigated. In-situ assessments are characterized by many challenges due to the absence of time series data and sometimes areas to be observed or monitored are inaccessible. Satellites Remote Sensing provide us with the digital images of same geographic areas within a pre-defined interval. This makes it possible to monitor and detect changes of environmental phenomena. This paper, therefore, reviewed the commonly use changes detection techniques globally such as image differencing, image rationing, image regression, vegetation index difference, change vector analysis, principal components analysis, multidate classification, post-classification comparison, and visual interpretation. The paper concludes by suggesting the use of more than one technique.

Keywords: environmental phenomena, change detection, monitor, techniques

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Authors: L. Al-Mulla, B. M. Thomas, N. R. Bhat, M. K. Suleiman, P. George

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Mangroves are halophytic shrubs habituated in the intertidal zones in the tropics and subtropics, forming a complex and highly dynamic coastal ecosystem. Historical evidence indicating the existence followed by the extinction of mangrove in Kuwait; hence, continuous projects have been established to reintroduce this plant to the marine ecosystem. One of the major challenges in establishing large-scale mangrove plantations in Kuwait is the very high rate of seedling mortality, which should ideally be less than 20%. This study was conducted at three selected locations in the Kuwait bay during 2016-2017, to evaluate the effect of four planting techniques on mangrove seedling establishment. Coir-pillow planting technique, comp-mat planting technique, and anchored container planting technique were compared with the conventional planting method. The study revealed that the planting techniques significantly affected the establishment of mangrove seedlings in the initial stages of growth. Location-specific difference in seedling establishment was also observed during the course of the study. However, irrespective of the planting techniques employed, high seedling mortality was observed in all the planting locations towards the end of the study; which may be attributed to the physicochemical characteristics of the mudflats selected.

Keywords: Avicennia marina (Forsk.) Vierh, coastal pollution, heavy metal accumulation, marine ecosystem, sedimentation, tidal inundation

Procedia PDF Downloads 152