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Iris recognition is a biometric authentication system proving vital for ensuring security and has been employed as an important case to test the algorithms developed in pattern recognition. The unique circular shape of the iris and its time invariance makes it a versatile technique that has an accuracy that can be mathematically proven. Here in this work we propose a new segmentation technique and...
Diagnosing liver disease is the challenging task for many public health physicians. In this study, we propose the framework to diagnose the hepatitis disease. For this study the adaptive rule based induction were formulated and the adaptive rule implemented in combined Robust BoxCox Transformation (RBCT) and Neural Network (NN) methods. The performance of proposed model is compared and results are...
The rise of internet web-based application and smart phone ease access to the stock market, attracting newcomer investors. Most investors have made their decision based on information from stock investment researches published by the brokers. An automated stock recommendation system from stock investment research is introduced in this paper. The system collects several investment researches from multiple...
Since the fault prediction is an important technique to help allocating software maintenance effort, much research on fault prediction has been proposed so far. The goal of these studies is applying their prediction technique to actual software development. In this paper, we implemented a prototype fault-prone module prediction tool using a text-filtering based technique named "Fault-Prone Filtering"...
Security is an important aspect in the practical deployment of biometric authentication systems. Biometric data in its original form is irreplaceable and thus, must be protected. This often comes at the cost of reduced matching accuracy or loss of the true key-less convenience biometric authentication can offer. In this paper, we address the shortcomings of current face template protection schemes...
Dropout rates for students in correspondence and open courses are on increase. There is a need of analysis of factors causing increase in dropout rate. The discovery of hidden knowledge from the educational data system by the effective process of data mining technology to analyze factors affecting student drop out can lead to a better academic planning and management to reduce students drop out from...
Intrusion Detection System (IDS) is used to preserve the data integrity and confidentiality from attacks. In order to identify the type of attack in IDS, different methodologies like various data mining techniques exist. But some are very time consuming and laborious. Therefore we have proposed the usage of SVM (Support Vector Machine) for classification of attack from large amount of raw intrusion...
Crime analysis is one of the most important activities of the majority of the intelligent and law enforcement organizations all over the world. Generally they collect domestic and foreign crime related data (intelligence) to prevent future attacks and utilize a limited number of law enforcement resources in an optimum manner. A major challenge faced by most of the law enforcement and intelligence...
For extorting the helpful comprehension concealed in the biggest compilation of a database the data mining technology is used. There are some negative approaches occurred about the data mining technology, among which the potential privacy incursion and potential discrimination. The latter consists of irrationally considering individuals on the source of their fitting to an exact group. Data mining...
The analysis of various components of the Electroglottograph (EGG) signal, obtained after Ensemble Empirical Mode Decomposition (EEMD) is the primary objective of this paper. The ability of EEMD to detect intermittent high frequency data embedded in the data of lower frequency is exploited to segregate the Epoch locations and the Periodic nature of EGG signal. The dyadic filterbank property of EEMD...
Immense databases may contain critical instances or chunks-a small heap of records or instances which has domain specific information. These chunks of information are useful in future decision making for improving classification accuracy for labeling of critical, unlabeled instances by reducing false positives and false negatives. Classification process may be assessed based on efficiency and effectiveness...
Databases in clinical scenario have tremendous amount of data regarding patients and clinical history associated. Here, data mining plays vital role in searching for patterns within huge clinical data that could provide useful basis of knowledge for efficient and effective decision-making. Classification mechanism is widely used tool of data mining employed in healthcare applications to facilitate...
Research in student retention is traditionally survey-based, where researchers use questionnaires to collect student data to analyse and to develop student predictive model. The major issues with survey-based study are the potentially low response rates, time consuming and costly. Nevertheless, a large number of datasets that could inform the questions that students are explicitly asked in surveys...
Data reduction as a critical step in the process of data pre-processing presents a central point of interest across a wide variety of fields. Data pre-processing has a significant impact on the performance of any machine learning algorithm. In this context, we focus our research paper on investigating the data pre-processing phase of a recent evolutionary algorithm named the Dendritic Cell Algorithm...
Data stored in educational database is increasing day by day. Data mining algorithms can be used to find hidden patterns from the student's database. These patterns can be used to find academic performance of students. The main aim of this study was to determine factors that influence the student's performance. This paper proposes Generalized Sequential Pattern mining algorithm for finding frequent...
The process of finding out the frequency of citations for various journals or articles or research papers is known as citation analysis. The impact of any research paper can be found by computing the number of citations, the particular journal or paper received. Many researchers quote concepts or ideas from various papers and the final outcome of the paper in their discussion. But it does not always...
Emotion plays an important role in human computer interaction to give a human like feel. To acknowledge the importance of emotions in an artificial agent, we propose a domain independent emotion mining model (EmoXract) which extracts emotions from an unstructured data. The emotion is extracted at sentence level based upon the contextual information. Basically, we have used two corpuses: WordNet dictionary...
Proteins are the functional subunits of a cell which interact with each other to carry out biological processes. Protein interaction networks form the backbone of the research in molecular and systems biology. Although there are available methods to mine protein interactions and their detection methods from the biological literature, the accuracy of these methods is quite low. In this study, we applied...
Multi-label classification (MLC) is the task of automatically assigning an object to multiple categories. There are many important and modern applications of MLC such as text categorization (associating documents to various subjects) and functional genomics (determining the multiple biological functions of genes and proteins). MLC problems typically involve datasets that are both very large in size...
A PT X is a state-owned enterprise that provides the largest telecommunications services and network in Indonesia. By the growing challenges in the telecommunications industry, PT X must carefully take care of their customers by improving its services in order to make them satisfied and loyal. One of the effort that can be done by PT X is determining and predicting their customer's category, so that...
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