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In recent years, the damage caused by botnets has increased and become a big problem. To solve this problem, we proposed a method to detect unjust C&C servers by using Hayashi's quantification theory class II. This method is able to detect unjust C&C servers, even if they are not included in a blacklist. However, it was predicted that the detection rate for this method decreases with...
Support Vector Machine (SVM) classifier with Histogram of Oriented Gradients (HOG) feature become one of the most popular techniques used for vehicle detection in recent years. And the computing time of SVM is a main obstacle to get real time implementation which is important for Advanced Driver Assistance Systems (ADAS) applications. One of the effective ways to reduce the computing complexity of...
Service computing is a popular development paradigm in information technology. The functional properties of Web services assure correct functionality of cloud applications, while the nonfunctional properties such as reliability might significantly influence the user-perceived availability evaluation. Reliability rankings provide valuable information for making optimal cloud service selection from...
A novel and robust vision-based human-machine interface system to naturally interact with computers/smart devices is proposed. The key contribution is the introduction of a Compressive Sensing technique to largely reduce the dimensionality of highly discriminative feature descriptors (computed from depth imagery), which originally have an excessive and inoperative high dimension to be applied to a...
This paper proposes an intellectual classification system to recognize normal and abnormal MRI brain images. Nowadays, decision and treatment of brain tumors is based on symptoms and radiological appearance. Magnetic resonance imaging (MRI) is a most important controlled tool for the anatomical judgment of tumors in brain. In the present investigation, various techniques were used for the classification...
Epilepsy is a global problem, and with seizures eluding even the smartest of diagnosis, a requirement for automatic detection of the same using electroencephalogram (EEG) would have a huge impact in diagnosis of the disorder. Contemporary researchers went ahead and devised a multitude of methods for automatic epilepsy detection, becoming a reason why one should find the best method out, based on accuracy,...
The continuous proliferation of more complex and various security threats leads to the conclusion that new solutions are required. Intrusion Detection Systems can be a pertinent solution because they can deal with the large data volumes of logs gathered from the multitude of systems and can even identify new types of attacks if based on anomaly detection. In this paper we propose an IDS model which...
In recent years, ICT devices such as personal computer and video camera, tablet devices have been introduced actively in the field of ball sports. As one example, before the game is also carried out analysis of the opposing team using recorded video. In this paper, we consider the method to extract the desired scenes from the game video automatically for coaching support in the rugby sports. HOG and...
Internet Relay Chat (IRC) is a commonly used tool by Open Source developers. Developers use IRC channels to discuss programming related problems, but much of the discussion is irrelevant and off-topic. Essentially if we treat IRC discussions like email messages, and apply spam filtering, we can try to filter out the spam (the off-topic discussions) from the ham (the programming discussions). Yet we...
Image-derived features (“radiomics”) are increasingly being considered for patient management in (neuro)oncology and radiotherapy. In Glioblastoma multiforme (GBM), simple features are often used by clinicians in clinical practice, such as the size of the tumor or the relative sizes of the necrosis and active tumor. First order statistics provide a limited characterization power because they do not...
Online Peer-to-Peer (P2P) lending has achieved explosive development recently, which could be beneficial to both sides of individual lending. In this study, a data mining (DM) approach to predict the performance of P2P loan before funded is proposed. Using data from the Lending Club, we explore the characteristics of loan and its applicant and use random forest to do the feature selection in the modeling...
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...
Credit risk analysis is to determine if a customer is likely to default on the financial obligation. In this paper, we will introduce sparse non-negative matrix factorization method to discovery the lower dimensional space for reducing the data dimensionality, which will contribute to good performance and fast computation in the credit risk classification performed by support vector machine. We test...
Automatic stroke recognition of badminton video footages plays an important role in the process of analyzing players and building up statistics. Yet recognizing activities from broadcast videos is a challenging task due to person dependant body postures and blurring of the fast moving body parts. We propose a robust and an accurate approach for badminton stroke recognition using dense trajectories...
In the recent years, the rapid advancement of computer networks has led to many security problems by malicious users to the modern computer systems. Hence, it is necessary to detect illegitimate users by monitoring the unusual user activities in the network. In this paper, we propose an Intrusion Detection System (IDS) which uses a genetic algorithm based feature selection approach and a Support vector...
Intrusion detection system (IDS) is of paramount importance in the present network and system security. Intrusion detection can successfully prevent many attempts to crash network and hamper web services by intruders and hackers.
We aim to develop a brain-machine interface (BMI) system that estimates user's gaze or attention on an object to pick it up in the real world. In Experiment 1 and 2 we measured steady-state visual evoked potential (SSVEP) using luminance and/or contrast modulated flickers of photographic scenes presented on a head-mounted display (HMD). We applied multiclass SVM to estimate gaze locations for every...
This paper presents a study of feature selection methods effect, using a filter approach, on the accuracy and error of supervised classification of cancer. A comparative evaluation between different selection methods: Fisher, T-Statistics, SNR and ReliefF, is carried out, using the dataset of different cancers; leukemia cancer, prostate cancer and colon cancer. The classification results using k nearest...
Feature selection from microarray data has become an ever evolving area of research. Numerous techniques have widely been applied for extraction of genes which are expressed differentially in microarray data. Some of these comprise of studies related to fold-change approach, classical t-statistics and modified t-statistics. It has been found that the gene lists returned by these methods are dissimilar...
Automatic diagnosis of electrocardiogram (ECG) signal is significant for timely and accurate diagnosis of heart diseases like arrhythmia. Several researchers have proposed different methods in last two decades. In this work we have employed a global ECG beat classification approach based on transformed features like discrete cosine transform (DCT) and discrete wavelet transform (DWT) rather than conventional...
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