Search results for " processing"
showing 10 items of 7549 documents
A critical review on the implementation of static data sampling techniques to detect network attacks
2021
International audience; Given that the Internet traffic speed and volume are growing at a rapid pace, monitoring the network in a real-time manner has introduced several issues in terms of computing and storage capabilities. Fast processing of traffic data and early warnings on the detected attacks are required while maintaining a single pass over the traffic measurements. To palliate these problems, one can reduce the amount of traffic to be processed by using a sampling technique and detect the attacks based on the sampled traffic. Different parameters have an impact on the efficiency of this process, mainly, the applied sampling policy and sampling ratio. In this paper, we investigate th…
Talent identification in soccer using a one-class support vector machine
2019
Abstract Identifying potential future elite athletes is important in many sporting events. The successful identification of potential future elite athletes at an early age would help to provide high-quality coaching and training environments in which to optimize their development. However, a large variety of different skills and qualities are needed to succeed in elite sports, making talent identification generally a complex and multifaceted problem. Due to the rarity of elite athletes, datasets are inherently imbalanced, making classical statistical inference difficult. Therefore, we approach talent identification as an anomaly detection problem. We trained a nonlinear one-class support ve…
Robust Light Field Watermarking by 4D Wavelet Transform
2020
Unlike common 2D images, the light field representation of a scene delivers spatial and angular description which is of paramount importance for 3D reconstruction. Despite the numerous methods proposed for 2D image watermarking, such methods do not address the angular information of the light field. Hence the exploitation of such methods may cause severe destruction of the angular information. In this paper, we propose a novel method for light field watermarking with extensive consideration of the spatial and angular information. Considering the 4D innate of the light field, the proposed method incorporates 4D wavelet for the purpose of watermarking and converts the heavily-correlated chann…
On achieving intelligent traffic-aware consolidation of virtual machines in a data center using Learning Automata
2018
Unlike the computational mechanisms of the past many decades, that involved individual (extremely powerful) computers or clusters of machines, cloud computing (CC) is becoming increasingly pertinent and popular. Computing resources such as CPU and storage are becoming cheaper, and the servers themselves are becoming more powerful. This enables clouds to host more virtual machines (VMs). A natural consequence ofthis is that many modern-day data centers experience very high internaltraffic within the data centers themselves. This is, of course, due to the occurrence of servers that belong to the same tenant, communicating between themselves. The problem is accentuated when the VM deployment t…
A Machine Learning Approach for Fall Detection and Daily Living Activity Recognition
2019
The number of older people in western countries is constantly increasing. Most of them prefer to live independently and are susceptible to fall incidents. Falls often lead to serious or even fatal injuries which are the leading cause of death for elderlies. To address this problem, it is essential to develop robust fall detection systems. In this context, we develop a machine learning framework for fall detection and daily living activity recognition. We use acceleration and angular velocity data from two public databases to recognize seven different activities, including falls and activities of daily living. From the acceleration and angular velocity data, we extract time- and frequency-do…
WiWeHAR: Multimodal Human Activity Recognition Using Wi-Fi and Wearable Sensing Modalities
2020
Robust and accurate human activity recognition (HAR) systems are essential to many human-centric services within active assisted living and healthcare facilities. Traditional HAR systems mostly leverage a single sensing modality (e.g., either wearable, vision, or radio frequency sensing) combined with machine learning techniques to recognize human activities. Such unimodal HAR systems do not cope well with real-time changes in the environment. To overcome this limitation, new HAR systems that incorporate multiple sensing modalities are needed. Multiple diverse sensors can provide more accurate and complete information resulting in better recognition of the performed activities. This article…
A Machine Learning Approach for Fall Detection Based on the Instantaneous Doppler Frequency
2019
Modern societies are facing an ageing problem that is accompanied by increasing healthcare costs. A major share of this ever-increasing cost is due to fall-related injuries, which urges the development of fall detection systems. In this context, this paper paves the way for the development of radio-frequency-based fall detection systems, which do not require the user to wear any device and can detect falls without compromising the user's privacy. For the design of such systems, we present an activity simulator that generates the complex path gain of indoor channels in the presence of one person performing three different activities: slow fall, fast fall, and walking. We have developed a mac…
Face Inpainting via Nested Generative Adversarial Networks
2019
Face inpainting aims to repaired damaged images caused by occlusion or cover. In recent years, deep learning based approaches have shown promising results for the challenging task of image inpainting. However, there are still limitation in reconstructing reasonable structures because of over-smoothed and/or blurred results. The distorted structures or blurred textures are inconsistent with surrounding areas and require further post-processing to blend the results. In this paper, we present a novel generative model-based approach, which consisted by nested two Generative Adversarial Networks (GAN), the sub-confrontation GAN in generator and parent-confrontation GAN. The sub-confrontation GAN…
The HPC Certification Forum: Toward a Globally Acknowledged HPC Certification
2020
The goal of the HPC Certification Forum is to categorize, define, and examine competencies expected from proficient HPC practitioners. The community-led forum is working toward establishing a globally acknowledged HPC certification process, a process that engages with HPC centers to identify gaps in users’ knowledge, and with users to identify the skills required to perform their tasks. In this article, we introduce the forum and summarize the progress made over the last two years. The release of the first officially supported certificate is planned for the second half of 2020.
Multilevel assessment of mental stress via network physiology paradigm using consumer wearable devices
2019
Mental stress is a physiological condition that has a strong negative impact on the quality of life, affecting both the physical and the mental health. For such a reason, accurate measurements of stress level can be helpful to provide mechanisms for prevention and treatment. This paper proposes a procedure for the classification of different mental stress levels by using physiological signals provided by low invasive wearable devices. 17 healthy volunteers participated in this study. Three different mental states were elicited in them: a resting condition, a stressful cognitive state, and a sustained attention task. The acquired physiological signals were: a one lead electrocardiogram (ECG)…