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This paper presents a user authentication system based on mouse movement data. An available logging tool named Recording User Input (RUI) is used to collect three types of mouse actions — Mouse Move, Point-and-Click on Left or Right mouse button and Drag-and-Drop. Collected data are divided into N-number of blocks consisting of specific number of actions. From each block seventy four features are...
The intrinsic interactions among a video's emotion tag, its content, and a user's spontaneous response while consuming the video can be leveraged to improve video emotion tagging, but this capability has not been thoroughly exploited yet. In this paper, we propose an implicit hybrid video emotion tagging approach by integrating video content and users' multiple physiological responses, which are only...
In this paper, we focus on the problem of group detection in crowd, which is a task of partitioning a set of pedestrians in a scene into small subsets called groups based on their trajectories. Most of previous methods use only a single model for representing a relationship between trajectories of pedestrians who belong to the same group. However, such relationship would vary depending on the activity...
Cloud computing is gaining significant attention, however, security is the biggest hurdle in its wide acceptance. Users of cloud services are under constant fear of data loss, security threats and availability issues. Recently, learning-based methods for security applications are gaining popularity in the literature with the advents in machine learning techniques. However, the major challenge in these...
A Regionlet model explored here provides a new object representation strategy for generic object detection, which integrates local deformation handling into object classifier learning and feature extraction. Generic object detection deals with different degrees of variations in discrete object classes with tractable computations and hence faces problems. This generates a need for representational...
Multi-label classification (MLC), allowing instances to have multiple labels, has been received a surge of interests in recent years due to its wide range of applications such as image annotation and document tagging. One of simplest ways to solve MLC problems is label-power set method (LP) that regards all possible label subsets as classes. LP validates traditional multi-classification classifiers...
Today the Remote health monitoring play significant role for the patients who suffer from high risks and chronic disorders. The patient data and verification are significant factors in transmission of patient data remotely for suggestion and take decision of further treatment. Generally it can be used for human identification through remotely monitoring a patient's through Electrocardiogram (ECG)...
Regression testing is the common task of retesting software that has been changed or extended (e.g., by new features) during software evolution. As retesting the whole program is not feasible with reasonable time and cost, usually only a subset of all test cases is executed for regression testing, e.g., by executing test cases according to test case prioritization. Although a vast amount of methods...
It's difficult to review a large number of examination surveillance videos at the same time. To reduce the workload of censors, we propose a method to analyze abnormal behaviors during examinations. This paper mainly includes two parts. Firstly, it employs a two-layer classifier with Histograms of Oriented Gradients feature to detect head-shoulder part of examinees, thus we can report the presence...
It is very difficult to implement an efficient analysis by using the customary techniques currently available; this is due to the fact that the data size has had a huge increase. Many complications were faced because of the numerous characteristics of big data; some of them include complexity, value, variability, variety, velocity, and volume. The objective of this paper is to implement classification...
A method is proposed to distinguish patients with schizophrenia from healthy controls based on data measured by functional near-infrared spectroscopy (fNIRS) during a cognitive task, which combines principal component analysis (PCA) and support vector machine (SVM). Firstly, a data reduction technique is applied prior to PCA, and then PCA is used to extract features on oxygenated hemoglobin (oxy-Hb)...
Feature extraction is playing a major role in bio signal processing. Feature identification and selection has two approaches. The common approach is engineering handcraft which is based on user experience and application area. While the other approach is feature learning that based on making the system identify and select the best features suit the application. The idea behind feature learning is...
Speech impaired people are detached from the mainstream society due to the lacking of proper communication aid. Sign language is the primary means of communication for them which normal people do not understand. In order to facilitate the conversation conversion of sign language to audio is very necessary. This paper aims at conversion of sign language to speech so that disabled people have their...
In this paper, an ECG signal classification method is presented to classify multi-lead ECG signals into normal and abnormal classes using Common Spatial Pattern (CSP) as the feature extraction algorithm. The method consists of two main stages: CSP-based feature extraction and classification. After segmenting the signal into non-overlapping segments, each segment is projected onto a CSP projection...
Continuous authentication for mobile devices using behavioral biometrics is being suggested to complement initial authentication for securing mobile devices, and the cloud services accessed through them. This area has been studied over the past few years, and low error rates were achieved; however, it was based on training and testing using support vector machine (SVM) and other non-privacy-preserving...
This paper focuses on analyzing a Spatial Pooler (SP) of Hierarchical Temporal Memory (HTM) ability for facilitating object classification in noisy video streams. In particular, we seek to determine whether employing SP as a component of the video system increases overall robustness to noise. We have implemented our own version of HTM and applied it to object recognition tasks under various testing...
Real-time human detection is a challenging task due to appearance variance, occlusion and rapidly changing content; therefore it requires efficient hardware and optimized software. This paper presents a real-time human detection scheme on a Raspberry Pi. An efficient algorithm for human detection is proposed by processing regions of interest (ROI) based upon foreground estimation. Different number...
In this paper, we try to make an author identification of two ancient Arabic religious books dating from the 6th century: The holy Quran and the Hadith. The authorship identification process is achieved through four phases which are: documents collection, text preprocessing, features extraction and classification model building. Thus, two series of experiments are undergone and commented. The first...
In this paper, we develop a projection neural network to solve the convex quadratic programming problem in support vector machine (SVM) learning. Then, we obtain a unique global solution for the proposed neural network. Furthermore, we prove that this network is completely stable and finite-time convergence. To present the feasibility and efficiency of the proposed neural network for solving the SVM...
Massive proliferation of social media has opened possibilities for perpetrator to conduct the crime of online child grooming. Because the pervasiveness of the problem scale, it may only be tamed effectively and efficiently by using an automatic grooming conversation detection system. Previously, Pranoto, Gunawan, and Soewito [1] had developed a logistic model for the purpose and the model was able...
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