This paper presents a novel approach to overcome the difficulty and complexity in detecting and predicting social networking phishing website. We proposed an intelligent resilient and effective model that is based on using A New Class Based Associative Classification Algorithm which is an advanced and efficient approach than all other association and classification Data Mining algorithms. This ...

This paper describes a target detection system on road environments based on Support Vector Machine (SVM) and monocular vision. The final goal is to provide pedestrian-to-car and car-to-car time gap. The challenge is to use a single camera as input, in order to achieve a low cost final system that meets the requirements needed to undertake serial production in automotive industry. The basic fea...

Nowadays digital transactions play a vital role in money transaction processes. Last 5 years statistical report portrays the growth of internet especially credit card and unified payments interface. Mean time increasing numerous banking threats fraud rates also growing significantly. Data engineering techniques provide ultra supports to detect forgery problems online offline mode transactions. ...

In this paper an intelligent classifier was development, in which information provided from MRI and FDG-PET images are combined in order to obtain an automatic classifier. In the first step was to develop a classification method to tag simultaneously MR and FDG-PET images as either normal or with the Alzheimer’s disease (AD). With the methodology obtained, and using similar features, the next s...

Automatic classification of modulation type in detected signals is an intermediate step between signal detection and demodulation, and is also an essential task for an intelligent receiver in various civil and military applications. In this paper, we propose a semi-supervised online passive-aggressive classifier that uses self-training approach for AWGN channels with unknown or variable signal ...

Road condition monitoring through real-time intelligent systems has become more and more significant due to heavy road transportation. Road conditions can be roughly divided into normal and anomaly segments. The number of former should be much larger than the latter for a useable road. Based on the nature of road condition monitoring, anomaly detection is applied, especially for pothole detecti...

Behavior-based artificial intelligent system is to derive the complicated behaviors by selecting appropriate one from a set of basic behaviors. Many robot systems have used behavior-based systems since the 1980’s. In this paper, we propose new method to create the sequences of behaviors appropriate to the changing environments by adding the function of learning with Learning Classifier System t...

It is widely acknowledged that learners experience a variety of emotions while interacting with Intelligent Tutoring Systems (ITS), hence, detecting and responding to emotions might improve learning outcomes. This study uses machine learning techniques to detect learners’ affective states from multichannel physiological signals (heart activity, respiration, facial muscle activity, and skin cond...

A multi-module architecture to detect, track and classify objects in semi-structured outdoor scenarios for intelligent vehicles is proposed in this paper. In order to fulfill this task it was used the information provided by a laser range finder (LRF) and a monocular camera. The detection and tracking phases are performed in the LRF space, and the object classification methods work both in lase...

High attrition rates in massive open online courses (MOOCs) have motivated growing interest in the automatic detection of student “stopout”. Stopout classifiers can be used to orchestrate an intervention before students quit, and to survey students dynamically about why they ceased participation. In this paper we expand on existing stop-out detection research by (1) exploring important elements...