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Nowadays, owing to the growth of quantity of data, the data mining techniques have been required on web exceedingly for extracting information from the data. Classification of text in data mining is very important and has been a hot issue on the topic. Especially, ontological taxonomy classification is important for more intelligent information reasoning. As it relates to data distribution of classes...
Advanced driver assistance systems are required to detect latent hazards posed by surrounding vehicles and generate an appropriate response to enhance safety. Lane changes constitute potentially risky maneuvers, as drivers involved encounter latent hazards due to surrounding vehicles. A careful study of lane change behavior is therefore essential in identifying potential abnormalities that may lead...
Cross section area (CSA) of spinal canal has been an important indicator for lumbar spinal stenosis (LSS), which remains the leading preoperative diagnosis for adults older than 65 years. Until recently, the machine learning algorithms had been investigated in [5–7] for an automatic classification system. The automatic classification system exploited the luminance of cerebrospinal fluid (CSF) as the...
Cardiovascular risk prediction is a vital aspect of personalized health care. In this study, retinal vascular function is assessed in asymptomatic participants who are classified into risk groups based on Framingham Risk Score. Feature selection, oversampling and state-of-the-art classification methods are applied to provide a sound individual risk prediction based on Retinal Vessel Analysis (RVA)...
Emotion recognition is an integral part of affective computing. An affective brain-computer-interface (BCI) can benefit the user in a number of applications. In most existing studies, EEG (electroencephalograph)-based emotion recognition is explored in a classificatory manner. In this manner, human emotions are discretized by a set of emotion labels. However, human emotions are more of a continuous...
With the emergence of large datasets in real-time applications as network intrusion detection, systems classification have gained more attention due to the importance of these applications and the increasing generation of these network traffic information. The proliferation of Internet and networking applications, coupled with the widespread availability of system hacks and viruses have increased...
This paper proposes a method of predicting future medical examination measurements given the past values. The medical examinations considered in this paper are blood sugar level, low and high blood pressures, and cholesterol level. This paper uses a specific type of artificial neural networks, radial-basis function network (RBFN), to approximate mapping from the past medical measurements to that of...
The semiconductor counterfeiting has become a serious problem. Several Physical Unclonable Functions (PUFs), which utilizes the variation when manufacturing, are proposed as a countermeasure for imitation electronics. An arbiter PUF is one of the most popular PUFs. The operation of an arbiter PUF can be expressed by using a delay model. An arbiter PUF is reported to be attacked by forcing them to...
In this paper, we propose a tourism category classification method based on estimation of reliable decision. The proposed method performs tourism category classification using location, visual, and textual tag features obtained from tourism images in image sharing services. As the biggest contribution of this paper, the proposed method performs successful classification based on two classification...
Hadoop distributed file system (HDFS) is a major distributed file system for commodity clusters and cloud computing. Its extensive scalability and replica fault tolerance scheme makes it well suited for data-intensive application. Due to the tremendous growth of data, many computation-centric applications also become data-intensive. However, they are not optimal on HDFS, which leaves plenty of space...
In this paper, we presented a comparison between different approaches of person re-identification in camera network based on the-state-of-the-art. We studied the different descriptors of objects for identifying people and existing classifier at the re-identification step. We seek to develop video surveillance systems online in controlled areas and improve their reliability and their processing time...
Feature-based opinion mining for product review is the field of study that analyzes user's attitude towards product attributes, which has been witnessed a booming interest in the last one and half decades, due to its importance to business and society as a whole. This paper proposed a POS patterns matching method to identify feature words, opinion bearing words, as well as negative words based on...
Shape features are widely used in image target recognition due to their useful property of translation, rotation and scaling invariance. In this paper, low order Hu moments and other four shape features are combined together to classify different kinds of knives and guns with the support vector machine in the application of millimeter wave security imaging. Experimental results show that the combined...
Support vector regression (SVR) has become one of the most promising methods for function approximation and regression estimation. However, SVR has a time complexity of O(N3) and a space complexity of O(N2). When dealing with very large sizes of training sets, SVR takes a lot computational time. To solve this problem, a method called heuristic sample reduction (HSR) is proposed for obtaining a reduced...
Now-a-days Variable Frequency Drives (VFDs) became popular due to the advantage of energy saving. Earlier, DC motors were used in variable speed applications which require good dynamic response, even though they have problems related to commutation. With the advancement in power electronics, dynamic response is no more a problem with induction motor. This paper demonstrates three speed control methods...
In recent years, decision fusion techniques have been widely applied in many studies to combine information from different sensor data to achieve higher accuracy in information extraction than that could be achieved by the use of single sensor data alone. So far, most of the decision fusion techniques developed for the remote sensing applications have the drawback of assuming conditional independence...
Classification between foggy and non-foggy images is a primitive step for automation in traffic activity and industries. The existing techniques provide low accuracy and needs validation over both synthetic and natural database. Foggy images are identified and classified based on their optical characteristics for vision enhancement and to make them more efficient for further processing. In proposed...
Opinion Mining is an area in Natural Language Processing that is becoming increasingly popular due to its ability to reduce the time and effort involved in manually inspecting and determining the opinion of a text. However, most of the research work carried out in opinion mining predominantly focuses on the English language. In this paper, a novel approach to opinion mining in the Konkani language...
Whenever an intrusion happens, privacy and security of the system are compromised. In order to detect different types of attacks that happen in a network, Intrusion Detection System (IDS) plays a crucial role in Network security. IDS is designed in order to classify the activities of the system into abnormal and normal. Machine learning based Intrusion Detection is gaining attention in recent years...
Electrocardiogram (ECG) is the most reliable and low-cost diagnostic tool to evaluate the patients with cardiac arrhythmias. Manual diagnosis of arrhythmia beats is very tedious due to the nonlinear and complex nature of ECG. The current paper, describes pattern recognition and machine learning-based approach for computer-aided detection of five classes of ECG arrhythmia beats using Discrete Cosine...
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