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The designing based on Adaboost algorithm not only achieved the nighttime pedestrian detection module of auxiliary driving system, but also realized the system optimization on issues of low detection speed and precision. In this design, variable step length and partition scanning track methods are used to improve the detection speed and variance normalization approach was applied to eliminate the...
Computer Aided Diagnosis (CAD) is one of the trusted methods in the field of medicine. CAD system assists the doctors for the diagnosis of diseases in higher degree of perfection within a short period of time. Now CAD is the most preferable method for the initial diagnosis of cancer using X-ray, CT, mammogram or MRI images. CAD works as an intermediate in between the radiologist and the input images...
Masqueraders are people who use somebody else's computer account. Masquerade attacks are serious in nature in the case of an insider, who can cause considerable damage to an organization. The insider attack detection problem remains one of the more important research areas requiring new insights to alleviate against this threat. Detection of these attacks is done by monitoring significant changes...
A EEG signal-based emotion recognition system was designed. The system was developed to operate as a user-independent system, based on MAPL (minority affective picture library), EEG-signal database obtained from multiple ethnic objections. The system consisted of preprocessing, feature extraction and pattern classification stages. Preprocessing and feature extraction methods were devised so that emotion-specific...
k nearest neighbor algorithm is a widely used classifier. It benefits from distances among features to classify the data. Classifiers based on distance metrics are affected from irrelevant or redundant features. Especially, it is valid for big datasets. So, some of features can be weighted with higher coefficients to reduce the effect of irrelevant or redundant features. We suggest adaptive weighted...
Traffic management measures like one-way street results in the misalignment of upward and downward traveling routes of public transit, which was rarely taken into account by researches on transit shortest path. In this paper, the concept of Abnormal Station is proposed, after which an analysis of its characteristic is made in depth. Then, an algorithm that can effectively handle the matter of Abnormal...
It is shown in the literature that network address translation devices have become a convenient way to hide the source of malicious behaviors. In this research, we explore how far we can push a machine learning (ML) approach to identify such behaviors using only network flows. We evaluate our proposed approach on different traffic data sets against passive fingerprinting approaches and show that the...
Finding anomalous behavior of user in networks is crucial, in analysis of such behavior to identify the real user is very complicated. Classification is one technique for identifying the anomalous behavior. The anomaly detection rate can be improved by ensemble the different classifiers. Empirically, ensembles tend to yield better results when there is a significant diversity among the models. The...
Classification techniques based on Artificial Intelligence are computational tools that have been applied to detection of intrusions (IDS) with encouraging results. They are able to solve problems related to information security in an efficient way. The intrusion detection implies the use of huge amount of information. For this reason heuristic methodologies have been proposed. In this paper, decision...
In cybercrime, the evaluation results of the weight of digital evidence are directly influencing the cognizance of the relevant case, further influencing the judgment of the case. Now, it lacks a universally accepted standard to evaluate the weight of digital evidence. Furthermore, the result of the evaluation will be easily influenced by experts. A system, which is based on Naive Bayesian Classification,...
Carrying out effective and sustainable agriculture product has become an important issue in recent years. Agricultural production has to keep up with an ever-increasing population. A key to this is the usage of modern techniques (for precision agriculture) to take advantage of the quality in the market. The paper reviews various quality evaluation and grading techniques of Oryza Sativa L. (rice) in...
For any successful launch of product, it should be properly reviewed. This is done by conducting a meeting in which various participants give their opinions, and depending upon those opinions decision is made. Firstly, it was given by Anvil tool, which was difficult to analyze. Also, commands such as propose, acknowledgement, negative response do not have a predefined notion which can differentiate...
This paper presents a learning algorithm for adaptive network intrusion detection based on clustering and naïve Bayesian classifier, which induces a hybridization of unsupervised and supervised learning processes. The proposed approach scales up the balance detection rates for different types of network intrusions, and keeps the false positives at acceptable level in network intrusion detection....
Internet has changed the way of communication, which has become more and more concentrated on emails. Emails, text messages and online messenger chatting have become part and parcel of our lives. Out of all these communications, emails are more prone to exploitation. Thus, various email providers employ algorithms to filter emails based on spam and ham. In this research paper, our prime aim is to...
Cluster is bunch of similar items. Unsupervised classification of patterns into clusters is known as clustering. It is useful in knowledge discovery in data. Clustering is able to deal with different data types. Fuzzy rules are used for data intelligence illustration purpose. User gets highly interpretable discovered clusters using fuzzy rules. To generate accurate fuzzy rules triangular membership...
Exponential increase in the number of web pages in the World Wide Web poses a great challenge in information filtering and also makes topic focused crawling a time consuming process in searching for relevant information. We propose an URL based web page classification method that does not need either the web page content or its link structure. In the proposed approach, character n-gram based features...
The classification performance of previous IG algorithm may decline obviously because of the maldistribution of classes and features, due to which an improved text feature selection method UDsIG is proposed. First, we select features by classes to reduce the impact on feature selection when the classes are unevenly distributed. After that, we use feature equilibrium of distribution to decrease the...
In mammography computer-aided diagnosis, the automatic extraction of interesting region is one of the most difficult problems. This paper presents a method based on two-dimensional principal component analysis (2DPCA) to extract the region of interest (ROI) automatically. First, preprocess the mammograms, then, extract mammography features by 2DPCA method and edge-detection algorithm. Finally, extract...
Feature selection plays an important role in text classification, and contributes directly to the accuracy of the classification. In order to correct the defects, such as mutual information-Based feature selection method tends to select rare words and those words from small samples as features, and negative MI value. This paper proposes a new improved feature evaluation function for automatic text...
Data rates on Internet links keep increasing with the deployment of optical technology. Packets coming into highspeed networks need to be classified quickly. Different packet classification schemes have been developed but they require a number of memory accesses as classification is complex and memory is slow. We follow the approach of providing support with fast memory, as cache, in computer systems,...
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