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Miscellaneous Contributed Journals and Academic Newsletters
by Adillah Dayana Ahmad Dali, Nurul Aswa Omar, Aida Mustapha
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Herbs are one of the high-value products in Malaysia. The term „herbs‟ has more than one definition. It is also demanding by multiple manifolds. Herbs are used in many sectors nowadays. The ability to identify variety herbs in the market is quite hard without the intervention of human experts. Unfortunately, human experts are prone to error. Herbs classification is able to assist human experts and at the same time minimizing the intervention. This research performs identification and...
Topics: Classification, Data mining, Herbs
Miscellaneous Contributed Journals and Academic Newsletters
by Mohamad Izzuddin Rahman, Noor Azah Samsudin, Aida Mustapha, Adeleke Abdullahi
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In Islam, Quran is the holy book that was revealed to the Prophet Muhammad. It functions as complete code of life for the Muslims. Remarks from Allah which contains more than 77,000 words that was passed down through Prophet Muhammad to the mankind for 23 years started in 610 ce. The Quran was divided into 114 chapters. Arabic language is the original text. The need for the Muslims across the world to find the meaning to understand the content in the Quran is necessary. Nevertheless,...
Topics: Quran Verse Classification, Text Mining
Miscellaneous Contributed Journals and Academic Newsletters
by Nur’Ain Maulat Samsudin, Cik Feresa binti Mohd Foozy, Nabilah Alias, Palaniappan Shamala, Nur Fadzilah Othman, Wan Isni Sofiah Wan Din
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YouTube has become a popular social media among the users. Due to YouTube popularity, it became a platform for spammer to distribute spam through the comments on YouTube. This has become a concern because spam can lead to phishing attack which the target can be any user that click any malicious link. Spam has its own features that can be analyzed and detected by classification. Hence, enhancement features are proposed to detect YouTube spam. In order to conduct the experiments, a YouTube Spam...
Topics: Classification, Detection, Machine learning, Spam
Miscellaneous Contributed Journals and Academic Newsletters
by Mustakim, Novia Kumala Sari, Jasril, Ismu Kusumanto, Nurul Gayatri Indah Reza
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Data mining has two main concepts of data distribution, namely supervised learning and unsupervised learning. The most easily recognizable concepts from data distribution is related to the dataset, with and without target class. Analytic Hierarchy Process (AHP) technique that carries the concept of pairwise comparison able to answer the problem related to the dataset, which is to change unsupervised to be supervised by determining eigenvalue value of each attribute and sub attribute in AHP...
Topics: AHP, Classification, Eigenvalue, Timely graduation
Miscellaneous Contributed Journals and Academic Newsletters
by Pamela Chaudhury, Hrudaya Kumar Tripathy
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Academic performance of students has been a concern worldwide. Despite efforts made by educational institutions there has been a rise in poor academic performance. In our research study we have proposed a model to pre-determine the academic performance of students using a Radial Basis Function network (RBFN) using primary data. The proposed model has been developed by using algorithms like differential evolution (DE) and teaching learning based optimization (TLBO). This model can be used by...
Topics: Academic performance, Classification, DE, RBFN, TLBO
Currently, customer's product review opinion plays an essential role in deciding the purchasing of the online product. A customer prefers to acquire the opinion of other customers by viewing their opinion during online products' reviews, blogs and social networking sites, etc. The majority of the product reviews including huge words. A few users provide the opinion; it is tough to analysis and understands the meaning of reviews. To improve user fulfillment and shopping experience, it has become...
Topics: Classification, Efficient feature extraction and classification (EFEC), Feature extraction,...
Miscellaneous Contributed Journals and Academic Newsletters
by Muhamad Addin Akmal Bin Mohd Raif, Nurlaila Ismail, Nor Azah Mohd Ali, Mohd Hezri Fazalul Rahiman, Saiful Nizam Tajuddin, Mohd Nasir Taib
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This paper presents the analysis of agarwood oil compounds quality classification by tuning quadratic kernel parameter in Support Vector Machine (SVM). The experimental work involved of agarwood oil samples from low and high qualities. The input is abundances (%) of the agarwood oil compounds and the output is the quality of the oil either high or low. The input and output data were processed by following tasks; i) data processing which covers normalization, randomization and data splitting...
Topics: SVM, Quadratic, Agarwood oil, Classification, Oil quality
Miscellaneous Contributed Journals and Academic Newsletters
by Shazwani Samsurim, Nor Ashikin Mohamad Kamal, Marina Ismail, Norizan Mat Diah
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Massive Multiplayer Online (MMO) game is one of the famous game genres among teenagers nowadays. MMO games allow gamers to interact and play with up to thousand players. Rainbow Six Siege (RSS) belongs to MMO type of game. However, due to many operators that are available in this game, the player needs to choose the right operator to counter the enemy operator. Therefore, based on the characteristic of the selected operator, this paper attempted to predict the outcomes of the game. In our...
Topics: Classification, Games, IBK, J48, MMOG, Naïve, Bayes
Miscellaneous Contributed Journals and Academic Newsletters
by Mahanijah Md Kamal, Ahmad Nor Ikhwan Masazhar, Farah Abdul Rahman
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Disease in palm oil sector is one of the major concerns because it affects the production and economy losses to Malaysia. Diseases appear as spots on the leaf and if not treated on time, cause the growth of the palm oil tree. This work presents the use of digital image processing technique for classification oil palm leaf disease sympthoms. Chimaera and Anthracnose is the most common symtoms infected the oil palm leaf in nursery stage. Here, support vector machine (SVM) acts as a classifier...
Topics: Leaf Disease, Image Processing, Classification, Support Vector Mahine
Miscellaneous Contributed Journals and Academic Newsletters
by Logenthiran Machap, Afnizanfaizal Abdullah, Zuraini Ali Shah
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Cancer is a heterogeneity genetic disease with huge phenotypic alterations among dissimilar cancers types or even between same cancer types. Recent expansions of genome-wide profiling technologies offer a chance to explore molecular changes variations throughout advancement of cancer. Therefore, various statistical and machine learning algorithms have been designed and developed for the handling and interpretation of high-throughput microarray molecular data. Discovery of molecular subtypes...
Topics: Biological analysis, Cancer subtypes, Classification, Co-clustering, Microarray
Miscellaneous Contributed Journals and Academic Newsletters
by Rozlini Mohamed, Munirah Mohd Yusof, Noorhaniza Wahid, Norhanifah Murli, Muhaini Othman
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This paper presents Bat Algorithm and K-Means techniques for classification performance improvement. The objective of this study is to investigate efficiency of Bat Algorithm in discrete dataset and to find the optimum feature in discrete dataset. In this study, one technique that comprise the discretization technique and feature selection technique have been proposed. Our contribution is in two process of classification: pre-processing and feature selection process. First, to proposed...
Topics: Bat algorithm, Classification, Discretization, Feature selection, K-Means
Miscellaneous Contributed Journals and Academic Newsletters
by Hana Rasheid Esmaeel
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The paper attempts to apply data mining technique, to estimate the teacher performance of college of Information Engineering (COIE) In Al Nahrain University in Baghdad/Iraq, Five classifications algorithms were used to build data they are (ZeroR, SMO, Naive Bayesian, J48 and Random Forest). The analysis implemented using WEKA (3. 8. 2) Data mining software tool. Information was collected from within the variety of form using “Referendum”; it was stored in Excel file CSV format then...
Topics: Classification, Data mining, Decision tree, Teacher evaluation, Weka
Student‟s performance is the most important value of the educational institutes for their competitiveness. In order to improve the value, they need to predict student‟s performance, so they can give special treatment to the student that predicted as low performer. In this paper, we propose 3 boosting algorithms (C5.0, adaBoost.M1, and adaBoost.SAMME) to build the classifier for predicting student‟s performance. This research used 1UCI student performance datasets. There are 3 scenarios of...
Topics: adaBoost, Boosting algorithm, C5.0, Classification, Prediction, Student‟s performance
Diabetes is a fast spreading illness, which makes to worry millions of people around the globe. The people affected by type-2 diabetes are rapidly increasing and there are no effective diagnostic systems to control the diabetics. As per global health statistics, in western countries, population effected by type 2 diabetics are higher in rate and cost factor for treatment is increasing. There are no effective methods to eradicate the diabetes and it leads to carry out an investigative study on...
Topics: Accuracy, Classification, Data mining, Diabetes, Self-organizing map
Miscellaneous Contributed Journals and Academic Newsletters
by Nur Ariffin Mohd Zin, Hishammuddin Asmuni, Haza Nuzly Abdul Hamed, Razib M. Othman, Shahreen Kasim, Rohayanti Hassan, Zalmiyah Zakaria, Rosfuzah Roslan
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A Recent studies have shown that the wearing of soft lens may lead to performance degradation with the increase of false reject rate. However, detecting the presence of soft lens is a non-trivial task as its texture that almost indiscernible. In this work, we proposed a classification method to identify the existence of soft lens in iris image. Our proposed method starts with segmenting the lens boundary on top of the sclera region. Then, the segmented boundary is used as features and extracted...
Topics: Contact lens classification, Local descriptor, Support Vector Machines
Miscellaneous Contributed Journals and Academic Newsletters
by Sadiq Hussain, Neama Abdulaziz Dahan, Fadl Mutaher Ba-Alwi, Najoua Ribata
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In this competitive scenario of the educational system, the higher education institutes use data mining tools and techniques for academic improvement of the student performance and to prevent drop out. The authors collected data from three colleges of Assam, India. The data consists of socio-economic, demographic as well as academic information of three hundred students with twenty-four attributes. Four classification methods, the J48, PART, Random Forest and Bayes Network Classifiers were...
Topics: Educational data mining, Classification algorithms, WEKA, Students’ academic performance
Sentiment analysis becomes very useful since the rise of social media and online review website and, thus, the requirement of analyzing their sentiment in an effective and efficient way. We can consider sentiment analysis as text classification problem with sentiment as its categories. In this study, we explore the use of Random Forest for sentiment classification in Indonesian language. We also explore the use of bag of words (BOW) features with some term weighting methods variation such as...
Topics: Random forest, Sentiment analysis, Term weighting, Text classification, TF.IDF
Miscellaneous Contributed Journals and Academic Newsletters
by A. Adeleke, N. Samsudin, A. Mustapha, S. Ahmad Khalid
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Classification of Quranic verses into predefined categories is an essential task in Quranic studies. However, in recent times, with the advancement in information technology and machine learning, several classification algorithms have been developed for the purpose of text classification tasks. Automated text classification (ATC) is a well-known technique in machine learning. It is the task of developing models that could be trained to automatically assign to each text instances a known label...
Topics: Classifiers, Feature selection, Holy Quran, Machine learning, Text classification
Software requirements with its functional and non-functional methods are the first important phase in producing a software system with free errors. The functional requirements are the visual actions that may easily evaluated from the developer and from the user, but non-functional requirements are not visual and need a lot of efforts to be evaluated. One of the main important non-functional requirements is security, which focuses on generating secure systems from strangers. Evaluating the...
Topics: Non-functional requirements, Requirements classification, Security requirements, Software...
Miscellaneous Contributed Journals and Academic Newsletters
by Haidar J. Mohamad, Seham A. Hashim, Anwar H. Al-Saleh
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The task of recognizing the shape of Arabic letters using modified algorithms discussed in this paper. The difficulty of recognizing these letters is summarized in the shape of the Arabic letter within a word from a large set of letters has a similar shape. Moreover, the shape of the letter is different depending on its position begin, middle, end within a word. Therefore, it is necessary to introduce new geometric features to categorize each letter. The suggested algorithm with 19 features is...
Topics: Arabic letter, Evaluation of classification, Feature extraction, Image categorization
Miscellaneous Contributed Journals and Academic Newsletters
by Shafaf Ibrahim, Nurnazihah Wahab, Ahmad Firdaus Ahmad Fadzil, Nur Nabilah Abu Mangshor, Zaaba Ahmad
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Rice is a staple food in most of the Asian countries. It is an important crop, and over half of the world population relies on it for food. However, paddy leaf disease can affect both the quality and quantity of paddy in agriculture production. The classification of paddy leaf disease is an important and urgent task as it destroys about 10% to 15% of production in Asia. Thus, a study on automatic classification of paddy leaf disease using image processing is presented. Feature extraction...
Topics: Automatic classification paddy leaf disease, Feature extraction, SVM
Miscellaneous Contributed Journals and Academic Newsletters
by Hana Rasheid Esmaeel
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The paper attempts to apply data mining technique, to estimate the teacher performance of college of Information Engineering (COIE) In Al Nahrain University in Baghdad/Iraq, Five classifications algorithms were used to build data they are (ZeroR, SMO, Naive Bayesian, J48 and Random Forest). The analysis implemented using WEKA (3. 8. 2) Data mining software tool. Information was collected from within the variety of form using “Referendum”; it was stored in Excel file CSV format then...
Topics: Classification, Data mining, Decision tree, Teacher evaluation, Weka
Miscellaneous Contributed Journals and Academic Newsletters
by Haider O. Lawend, Anuar M. Muad, Aini Hussain
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This paper presents a proposed supervised classification technique namely flexible partial histogram Bayes (fPHBayes) learning algorithm. The traditional classification algorithms like neural network, support vector machine, first nearest neighbor, nearest subclass classifier and Gaussian mixture model classifier are accurate but slow when dealing with large number of instances. In additional to that these algorithms might require to be retrain when the classes changes. On the other hand,...
Topics: Classification, Histogram probability, Distribution, Machine learning, Naïve bayes, PHBayes
Miscellaneous Contributed Journals and Academic Newsletters
by Mohd Hafizul Afifi Abdullah, Muhaini Othman, Shahreen Kasim, Siti Aisyah Mohamed
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Analysing environmental events such as predicting the risk of flood is considered as a challenging task due to the dynamic behaviour of the data. One way to correctly predict the risk of such events is by gathering as much of related historical data and analyse the correlation between the features which contribute to the event occurrences. Inspired by the brain working mechanism, the spiking neural networks have proven the capability of revealing a significant association between different...
Topics: Classification, Data mining, Pattern recognition, Personalised modelling, Spiking neural networks
The use of the data mining has become wider today; it can be applied in several fields like marketing, customer relationship management, medicine, engineering, etc. It can be used also in employability, the use of data mining in this field will give opportunities and solution for decision makers in this field in order to improve the employability and propose solutions. In this paper, we propose a data mining process for employability data using classification techniques, presenting in details...
Topics: Classification, Data mining, Data mining process, Employability, Rapid Miner
Miscellaneous Contributed Journals and Academic Newsletters
by Haseeb Ali, Mohd Najib Mohd Salleh, Rohmat Saedudin, Kashif Hussain, Muhammad Faheem Mushtaq
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The imbalanced data problems in data mining are common nowadays, which occur due to skewed nature of data. These problems impact the classification process negatively in machine learning process. In such problems, classes have different ratios of specimens in which a large number of specimens belong to one class and the other class has fewer specimens that is usually an essential class, but unfortunately misclassified by many classifiers. So far, significant research is performed to address the...
Topics: Classification, Imbalanced data, Machine learning, Majority class, Minority class
Miscellaneous Contributed Journals and Academic Newsletters
by M. Ali Fauzi, Anny Yuniarti
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Due to the massive increase of user-generated web content, in particular on social media networks where anyone can give a statement freely without any limitations, the amount of hateful activities is also increasing. Social media and microblogging web services, such as Twitter, allowing to read and analyze user tweets in near real time. Twitter is a logical source of data for hate speech analysis since users of twitter are more likely to express their emotions of an event by posting some tweet....
Topics: Classifier ensemble, Hate speech, Indonesian language, Text classification, Twitter
Spectrogram features have been used to automatically classify animals based on their vocalization. Usually features are extracted and used as inputs to classifiers to distinguish between species. In this paper, a classifier based on Correlation Filters (CFs) is employed where the input features are the spectrogram image themselves. Spectrogram parameters are carefully selected based on the target dataset in order to obtain clear distinguishing images termed as call-prints. An even better...
Topics: Bio-acoustic signal, Classification, Correlation filter, Spectrogram, Time-frequency reassignment
Miscellaneous Contributed Journals and Academic Newsletters
by M.M Abdulrazzaq, Imad FT Yaseen, SA Noah, Moayad A. Fadhil
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There has been a rise in demand for digitized medical images over the last two decades. Medical images' pivotal role in surgical planning is also an essential source of information for diseases and as medical reference as well as for the purpose of research and training. Therefore, effective techniques for medical image retrieval and classification are required to provide accurate search through substantial amount of images in a timely manner. Given the amount of images that are required to...
Topics: X-ray medical image, SVM, K-NN, Feature Extraction, Classification
Miscellaneous Contributed Journals and Academic Newsletters
by Siti Fairuz Nurr Sadikan, Azizul Azhar Ramli, Mohd Farhan Md. Fudzee, Siti Sapura Jailani, Mohd Ali Mohd Isa, Prasanna Ramakrisnan, Roslani Embi
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A Web server log files contain an entire record of the user’s browsing history such as referrer, date and time access, path, operating system (OS), browser and IP address. User navigation pattern discovery involves learning of user’s browsing behaviour to gain the pattern from web server log file. This paper emphasizes on identifying user navigation pattern from web server log file data of iLearn portal. The study implements the framework for user navigation including phases of acquisition...
Topics: Classification, Navigational pattern modelling clustering, Server log files, Web usage mining
Miscellaneous Contributed Journals and Academic Newsletters
by Sai Siong Jun, Hafiz Rashidi Ramli, Azura Che Soh, Noor Ain Kamsani, Raja Kamil Raja Ahmad, Siti Anom Ahmad, Asnor Juraiza Ishak
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Falls are dangerous and contribute to over 80% of injury-related hospitalization especially amongst the elderly. Hence, fall detection is important for preventing severe injuries and accidental deaths. Meanwhile, recognizing human activity is important for monitoring health status and quality of life as it can be applied in geriatric care and healthcare in general. This research presents the development of a fall detection and human activity recognition system using Threshold Based Method (TBM)...
Topics: Activity recognition, Classification, Fall detection, Neural network, Threshold based method
Miscellaneous Contributed Journals and Academic Newsletters
by Mehdi Ramezanifard, B. S. Mousavi
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Since image classification is a complex process that may be affected by many factors, it is a challenging problem of computer vision. This study reports a fuzzy system to semantic image classification. As it is a complex task, various information of digital image, including: three color space components and two Zernike moments with different order are gathered and utilized as an input of fuzzy inference system to materialize a robust rotation/lighting condition and size invariant image...
Topics: Fuzzy inference system, Genetic algorithm, Image classification, Zernike moments
Miscellaneous Contributed Journals and Academic Newsletters
by Mohd Hanafi Ahmad Hijazi, Leong Qi Yang, Rayner Alfred, Hairulnizam Mahdin, Razali Yaakob
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Tuberculosis (TB) is one of the deadliest infectious disease in the world. TB is caused by a type of tubercle bacillus called Mycobacterium Tuberculosis. Early detection of TB is pivotal to decrease the morbidity and mortality. TB is diagnosed by using the chest x-ray and a sputum test. Challenges for radiologists are to avoid confused and misdiagnose TB and lung cancer because they mimic each other. Semi-automated TB detection using machine learning found in the literature requires...
Topics: Deep learning, Ensemble, Image classification, Medical image analysis, Tuberculosis detection
Miscellaneous Contributed Journals and Academic Newsletters
by Nur Syaza Izzati Mohd Rafei, Rohayanti Hassan, RD Rohmat Saedudin, Anis Farihan Mat Raffei, Zalmiyah Zakaria, Shahreen Kasim
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The amount of digital biomedical literature grows that make most of the researchers facing the difficulties to manage and retrieve the required information from the Internet because this task is very challenging. The application of text classification on biomedical literature is one of the solutions in order to solve problem that have been faced by researchers but managing the high dimensionality of data being a common issue on text classification. Therefore, the aim of this research is to...
Topics: Feature selection, Information gain, Pearson correlation, Support vector machine, Text...
Miscellaneous Contributed Journals and Academic Newsletters
by N. N. S. Abdul Rahman, N.M. Saad, A. R. Abdullah, M. R. M. Hassan, M. S. S. M. Basir, N. S. M. Noor
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The requirement of product quality inspection in industries for product standardized leads to a development of the quality inspection system. The problem is related to a manual inspection that is done by a human as an inspector. This paper presents an automated real-time vision quality inspection monitoring system as a problem solver to a manual inspection that is tedious and time-consuming task as well as reducing cost especially in small and medium enterprise industries (SME). For the...
Topics: Color classification, Image processing, Level analysis, Quadratic distance classifier, Visual...
Miscellaneous Contributed Journals and Academic Newsletters
by Maryam Nuser, Enas Al-Horani
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The number of digital medical documents is increasing continuously; several medical websites share a lot of unclassified articles. These articles have very long texts that should be read to determine the topic of each document. The classification of these documents is important so researchers can use these documents easily and the effort and time in reading and searching for a specific topic will be reduced. Therefore, an automatic way to extract latent topics from these text documents is...
Topics: Classification, Latent dirichlet allocation, Medical documents, Mining health data, Topic modeling
Miscellaneous Contributed Journals and Academic Newsletters
by Mohd Hanafi Ahmad Hijazi, Leong Qi Yang, Rayner Alfred, Hairulnizam Mahdin, Razali Yaakob
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Tuberculosis (TB) is one of the deadliest infectious disease in the world. TB is caused by a type of tubercle bacillus called Mycobacterium Tuberculosis. Early detection of TB is pivotal to decrease the morbidity and mortality. TB is diagnosed by using the chest x-ray and a sputum test. Challenges for radiologists are to avoid confused and misdiagnose TB and lung cancer because they mimic each other. Semi-automated TB detection using machine learning found in the literature requires...
Topics: Deep learning, Ensemble, Image classification, Medical image analysis, Tuberculosis detection
Miscellaneous Contributed Journals and Academic Newsletters
by Mohammed Amine Ihedrane, Seddik Bri
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This study presents the conception, simulation, realisation and characterisation of a patch antenna for Wi-Fi. The antenna is designed at the frequency of 2.45 GHz; the dielectric substrate used is FR4_epoxy which has a dielectric permittivity of 4.4.this patch antenna is used to estimate the direction of arrival (DOA) using 2-D Multiple Signal Classification (2-D MUSIC) the case of the proposed uniform circular arrays (UCA). The comparison between Uniform circular arrays and Uniform Linear...
Topics: Direction of arrival, Multiple signal classification, Uniform circular array, Uniform linear array
Miscellaneous Contributed Journals and Academic Newsletters
by Lilik J. Awalin, Fatini, M. N. Abdullah, L.T. Tay, M. Fairuz Ab. Hamid, Bazilah Ismail
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This research introduces the appropriate input pattern of Fuzzy Logic design for fault type classification of Single Line to Ground Fault at distribution network. The proposed design is solely using Fuzzy Logic as the research technique with input data from PSCAD simulation. PSCAD software simulate the circuit configuration for fault disturbance at the distribution network. The research technique was applied with multiples input values of voltage and current that extracted from the PSCAD...
Topics: Distribution network, Fault resistance, Fault type classification, Fuzzy logic, Single line to...
These days it has become a common practice for business organizations and individuals to make use of social media for sharing the opinions about the products or the services. Consumers are also ready to share their views on certain products or commodities. Thus huge amount of unstructured social media data gets generated day by day. Gradually heap of text data will be formed in many areas like automated business, education, health care, and show business and so on. Opinion mining also referred...
Topics: ANN, Ensemble model, Feature selection, Opinion mining, Reviews, Sentiment classification, SVM
Miscellaneous Contributed Journals and Academic Newsletters
by Dawlat Mustafa Sulaiman, Adnan Mohsin Abdulazeez, Habibollah Haron
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Today, finger vein recognition has a lot of attention as a promising approach of biometric identification framework and still does not meet the challenges of the researchers on this filed. To solve this problem, we propose s double stage of feature extraction schemes based localized finger fine image detection. We propose Globalized Features Pattern Map Indication (GFPMI) to extract the globalized finger vein line features basede on using two generated vein image datasets: original gray level...
Topics: Classification, Finger vein, Glcm features, Gray scale texture features, Identification,...
Miscellaneous Contributed Journals and Academic Newsletters
by D. Dhanalakshmi, Anna Saro Vijendran
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The main objective of this research is to improve the predictive accuracy of classification in ordinal multiclass imbalanced scenario. The methodology attempts to uplift the classifier performance through synthesizing sophisticated objects of immature classes. A novel Adaptive Data Structure based Oversampling algorithm is proposed to create synthetic objects and Extreme Learning Machine for Ordinal Regression (ELMOP) classifier is adopted to validate our work. The proposed method generating...
Topics: Adaptive data structur, Average accuracy, Extreme learning machine for ordinal regression,...