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Airline operators get much feedback from their customers which are vital for both operational and strategic planning. Social media has become one of the most popular platforms for obtaining such feedback. However, to analyze, categorize, and generate useful insight from the huge quantity of data on social media is not a trivial task. This study…

Every institution nowadays relies on their online system and framework to do businesses. Such procedures need more attention due to the massive amount of attacks that occurs. These procedures have to go first through the management team of the institution, in order to prevent exploits of the attackers. Thus, the risk management can easily control…

Face explicitly provides the direct and quick way to evaluate human soft biometric information such as race, age and gender. Race is a group of human beings who differ from human beings of other races with respect to physical or social attributes. Race identification plays a significant role in applications such as criminal judgment and…

Nowadays, process automation and smart systems have gained increasing importance in a wide variety of sectors, and robotics have a fundamental role in it. Therefore, it has attracted greater research interests; among them, Underactuated Mechanical Systems (UMS) have been the subject of many studies, due to their application capabilities in different disciplines. Nevertheless, control of…

The main assets of universities are students. The performance of students plays a vital role in producing excellent graduate students who will be the future viable leader and manpower in charge of a country’s financial and societal progress. The purpose of this research is to develop a “University Students Result Analysis and Prediction System” that…

In recent years, cyber security has been received interest from several research communities with respect to Intrusion Detection System (IDS). Cyber security is “a fast-growing field demanding a great deal of attention because of remarkable progresses in social networks, cloud and web technologies, online banking, mobile environment, smart grid, etc.” An IDS is a software…

Face recognition in low resolution images has challenges in active research because face recognition is usually implemented in high resolution images (HR). In general, research leads to a combination of pre-processing and training models. Therefore, this study aims to classify low-resolution face images using a combination of pre-processing and deep learning. In addition, this study…

Person recognition using thermal imaging, multi-biometric traits, with groups of feature filters and classifiers, is the subject of this paper. These were used to tackle the problems of biometric systems, such as a change in illumination and spoof attacks. Using a combination of, hard and soft-biometric, attributes in thermal facial images. The hard-biometric trait, of…

Anomaly detection aims at identification of suspicious items, observations or events by differing from most of the data. Intrusion Detection, Fault Detection, and Fraud Detection are some of the various applications of Anomaly Detection. The Machine learning classifier algorithms used in these applications would greatly affect the overall efficiency. This work is an extension of…

We present findings on classifying the class of executable code using convolutional, re- current neural networks by creating images from only the .text section of executables and dividing them into standard-size windows, using minimal preprocessing. We achieve up to 98.24% testing accuracy on classifying 9 types of malware, and 99.50% testing accuracy on classifying malicious…

All forms of skin cancer are becoming widespread. These forms of cancer, and melanoma in particular, are insidious and aggressive and if not treated promptly can be lethal to humans. Effective treatment of skin lesions depends strongly on the timeliness of the diagnosis: for this reason, artificial vision systems are required to play a crucial…

Improving the hand motor skills in post-stroke patients through rehabilitation based on movement intention derived signals from the brain in conjunction with robot-assistive technologies are explored. The experimental work is conducted using Electroencephalogram based Brain-Computer Interface (EEG-BCI) system and the AMADEO hand rehabilitation robotic device. Two protocols using visual-cues and then using a 2-Dimensional (2D)…

From the collection of supervised machine learning technique, an ensemble procedure is used in Random Forest. In the arena of Data mining, there is an excellent claim for machine learning techniques. Random Forest has tremendous latent of becoming a widespread technique for forthcoming classifiers as its performance has been found analogous with ensemble techniques bagging…

The increasing number of breast cancer in recent years has attracted numerous researchers’ attention. Several techniques of Computer Aided Diagnosis System have been proposed as alternative solutions to diagnose breast cancer. The flaw of simply using the naked eye to see the differences between normal and with cancer mammogram images makes the texture analysis play…

This paper proposes a computationally intelligent algorithm for extracting relevant features from a training set. An optimal subset of features is extracted from training examples of network intrusion datasets. The Support Vector Machine (SVM) algorithm is used as the cost function within the thermal equilibrium loop of the Simulated Annealing (SA) algorithm. The proposed fusion…

This paper reports on an empirical study (an extension of a pilot study) that analyses the design of icons in a German 3-D virtual art gallery interface. It evaluates the extent to which a sample of typical computer users from a range of ages, educational attainments and employments can interpret the meaning of icons from…

Feature extraction is taking a very vital and essential part of bio-signal processing. We need to choose one of two paths to identify and select features in any system. The most popular track is engineering handcrafted, which mainly depends on the user experience and the field of application. While the other path is feature learning,…

Water quality assessment and prediction is a more and more important issue. Traditional ways either take lots of time or they can only do assessments. In this research, by applying machine learning algorithm to a long period time of water attributes’ data; we can generate a decision tree so that it can predict the future…

Radio frequency Identification (RFID) is currently considered as one of the most used technologies for an automatic identification of objects or people. Based on a combination of tags and readers, RFID technology has widely been applied in various areas including supply chain, production and traffic control systems. However, despite of its numerous advantages, the technology…

In this paper, we propose a revised version of the semantic decoder for multi-label classification task in the spoken language understanding (SLU) pilot task of the Dialog State Tracking Challenge 5 (DSTC5). Our model concatenates two deep neural networks – a Convolutional Neural Network (CNN) and a Recurrent Neural Networks (RNN) – for detecting semantic…

The discovery of semantic information from complex signals is a task concerned with connecting humans’ perceptions and/or intentions with the signals content. In the case of audio signals, complex perceptions are appraised in a listener’s mind, that trigger affective responses that may be relevant for well-being and survival. In this paper we are interested in…

The increased motivation (by service providers) to offer user-centric and seamless communication services – that satisfies users’ quality of experience (QoE), has manifested a myriad of challenges in the field of wireless communication; and given the increased traffic capacity and sudden explosion of cellular devices, communication systems are constantly threatened by performance related issues –…

Command and control (C2) systems direct operators to make accurate decisions in the stressful atmosphere of the battlefield at the earliest. There are powerful tools that fuse various instant piece of information and brings summary of those in front of operators. Threat evaluation is one of the important fusion method that provides these assistance to…

Vehicle analysis is a very useful component in various real world applications. In this paper, we have developed a Vehicle Make and Model Recognition (VMMR) system using Support Vector Machine (SVM). Scale Invariant Feature Transform (SIFT) and Speed-Up Robust Transform (SURF) are used to extract local features from an image. Bag-of-Features (BoF) model is used…

The research in Neuro-Prosthetics is gaining more significance and popularity as the advancement in prosthetics control allows amputees to perform even more tasks. Indeed, the improvement of classification accuracy is a challenge in prosthetics control. In this research, a system is developed in order to improve the multiclass classification rate. Two classifiers namely Artificial Neural…