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In order to detect the health status of high-speed railway, various studies have been examined by Acoustic Emission (AE) method. However, little work has been done on studying the relationship between rail status and features of AE signals, and this relationship can be used to establish a detection criterion for rail health monitoring. This paper presents a methodology on rail health monitoring by...
High false alarm rates and execution times are among the key issues in host-based anomaly detection systems. In this paper, we investigate the use of trace abstraction techniques for reducing the execution time of anomaly detectors while keeping the same accuracy. The key idea is to represent system call traces as traces of kernel module interactions and use the resulting abstract traces as input...
Echo state neural networks (ESNs) provide an efficient classification technique for spatiotemporal signals. The feedback connections in the ESN topology enable feature extraction of both spatial and temporal components in time series data. This property has been used in several application domains such as image and video analysis, anomaly detection, and speech recognition. In this research, we explore...
The development of social media, especially Twitter is growing rapidly. Twitter is usually used to comment on a product, a person or even a television program. The written comments by Twitter users can reach hundred thousand or even millions every day. By using the comments obtained from Twitter, it can complement a television program assessment that usually done by using rating, which only represented...
The unsupervised learning of Self Organizing Map (SOM) is an effective computational tool in data mining exploration processes. It provides topology preserved data mapping from high-dimensional input space into low-dimensional representation such as two-dimensional map. The visualization and classification of clustered data even with good topological preservation between input and output spaces however...
The Internet has brought enormous benefits to mankind, but it could be many potential risks. Internet crimes are growing rapidly, phishing is one of the new type of online crime. Phishing site is a fake-site aimed to steal personal information such as password, banking account and credit card information, etc. Most of these phishing pages look similar to the real pages in terms of interface and uniform...
Early detection of cataract considered as an important solution to prevent the increasing number of cataract in developing country, especially in Indonesia. A cataract will be a serious public health problem as a leading cause of blindness if there is a delay in handling it. In this paper, we discuss about the performing high accuracy of the system for cataract detection using statistical texture...
When enterprises outsource maintenance of IT systems to service providers, thorough knowledge acquisition is critical to the success of the engagement. Program comprehension contributes significantly to acquiring knowledge of the IT systems. It is a common practice to execute test scripts to identify critical scenarios in the system and then trace these as flows in the programs. Instead of executing...
The explosive growth of Internet commerce has made phishers who may attempt to create phishing sites aimed to steal personal information such as password, banking account and credit card account details, etc. Most of these phishing pages look similar to the real pages in terms of interface and uniform resource locator (URL) address. Many techniques have been proposed to identify phishing sites. However,...
Institutions hassles to accommodate a large of student that couldn't passed in normal study period. Some of them pending the study period because couldn't passed TPB in two semesters. If many students didn't graduated on time, it would be a lot of difficulties involved by institutions. The impact of these problems such as human resources, supplying classroom and operational costs. This research tries...
Odometer is an instrument that functions to measure the vehicle mileage and is usually used for periodic inspection of vehicle lubricant replacement. For companies that have a large number of vehicles (for example banks, travel agencies, etc.), vehicle lubricant replacement is an important thing to do, because if it is not maintained well it may cause fatal damage to the vehicle and can even endanger...
This study presents a small part of the major study, involved in categorizing EEG calmness. The kNN classifier was used to classify EEG features named as asymmetry index (AsI) which was extracted during relaxed state and non-relaxed state. Results from the previous study showed that the EEG behaviour during both states appear to have more than two groups. The group of four EEG behaviours and three...
Financial time series forecasting is regarded as one of the most challenging applications of time series forecasting. Many researchers have been focusing on this topic due to the potential of yielding significant profits on the invested money in a short time frame. Believing in the predictability of stock markets, traders have been using Technical Analysis tools for a very long time to analyze and...
Intrusion detection system (IDS) research field has grown tremendously in the past decade. Improving the detection rate of user to root (U2R) attack classes is an open research problem. Current IDS uses all data features to detect intrusions. Some of the features may be redundant to the detection process. The purpose of this empirical study is to identify important features to improve the detection...
The widespread use of wireless communications, Internet, and mobile technology offers the opportunity of supplying new generation of decision support commonly known as Mobile Decision Support Systems (MDSS). This paper describes research towards evaluation of such systems. Our view is that the end user will benefit if provided with a better Quality of MDSS. We propose a quality model taking into account...
In this paper, non-intrusive load monitoring using a single point sensing and wavelet-based classification is presented and applied to a test system feeding two dynamic and two static three-phase loads. The features in the three-phase voltage and current signals are extracted by wavelet transform to decompose the original signals. The energy of the obtained wavelet coefficients at the detail levels...
Alternate Test has demonstrated in the last decade that advanced machine-learning tools can leverage the accuracy gap between functional test and indirect, or model-based, test. If a regression approach is taken, a model should be trained for each specification. The advantage is that the results are interpreted just like performance measurements but the drawback is that accuracy is required over the...
This paper investigates the development of a knowledge base (KB) of logical functions, that can be used to do reasoning, from the consolidation of training examples of those logical functions. The work is based on the L2R (Learning to Reason) framework. A L2R agent only needs to answer knowledge queries that are relevant to its environment in a Probably Approximately Correct sense. We develop an L2R...
Face detection has become a fundamental task in computer vision and pattern recognition applications. This paper describes a system for face detection using data mining approach. The proposed face detection method is a two phase process comprising of training and detection phase. In the training phase, training image is transformed into an edge and non-edge image. Maximal Frequent Itemset Algorithm...
The abundant spectral and spatial information in the hyperspectral images (HSI) are largely used in the field of remote sensing. Though there are highly sophisticated sensors to capture the hyperspectral imagery, they suffer from issues like hyperspectral noise and spectral mixing. The major challenges encountered in this field, demands the use of preprocessing techniques prior to hyperspectral image...
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