Space modulation techniques (SMTs) have emerged as promising candidates for spectral- and energy-efficient wireless communication systems since they strike a good balance among error performance, power efficiency, spectrum receiver complexity. In SMTs, the information is not only conveyed by habitual M-ary signal constellations; rather, it also indices of transmit antennas. As such, antennas are harnessed in such manner that enhance transmission efficiency compared with other multiple-input...

This paper proposed a novel deep learning-based relay selection scheme in millimeter wave (mmWave) Device-to-Device (D2D) communication underlying the fifth generation (5G) cellular networks. Relay seems to be promising solution extend coverage and solve blocking problem of mmWave direct communication. In case path blocking, base station (BS)/user equipment (UE) has several candidate devices selected as relay. Despite that, conventional when is blocked, link handover from lower frequency...

Recently, the problem of automatic traffic accident recognition has appealed to machine vision community due its implications on development autonomous Intelligent Transportation Systems (ITS). In this paper, a new framework for real-time automated accidents using Histogram Flow Gradient (HFG) is proposed. This performs two major steps. First, HFG-based features are extracted from video shots. Second, logistic regression employed develop model probability occurrence an by fitting data curve....

An essential part of any activity recognition system claiming be truly real-time is the ability to perform feature extraction in real-time. We present, this paper, a quite simple and computationally tractable approach for human that based on statistical features. These features are relatively small, accordingly they easy fast calculated, further form low-dimensional space which classification can carried out robustly. On Weizmann publicly benchmark dataset, promising results (i.e. 97.8%)...

Temporal shape variations intuitively appear to provide a good cue for human activity modeling. In this paper, we lay out novel framework action recognition based on fuzzy log-polar histograms and temporal self-similarities. At first, set of reliable keypoints are extracted from video clip (i.e., snippet). The local descriptors characterizing the then obtained by using self-similarities defined histograms. Finally, SVM classifier is trained these features realize model. proposed method...

This paper introduces a novel multiple-input-multiple-output (MIMO) modulation technique named fully-generalised spatial (F-GSM). The proposed F-GSM vanquishes the pivotal criticism of conventional (SM) and generalised (GSM) techniques which constraints data rate increment to be proportionated with base-two logarithm number transmit antennas (N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">t</sub> ). logarithmical proportion regrettably, makes...

Successful blind image deconvolution algorithms require the exact estimation of Point Spread Function size, PSF. In absence any priori information about imagery system and true image, this is normally done by trial error experimentation, until an acceptable restored quality obtained. This paper, presents PSF which yields optimum for both noisy noiseless images. It based on evaluating detail energy wave packet decomposition blurred image. The minimum energies occur at size. Having accurately...

Over the past decade, automatic traffic accident recognition has become a prominent objective in area of machine vision and pattern because its immense application potential developing autonomous Intelligent Transportation Systems (ITS). In this paper, we present new framework toward real-time automated based on Histogram Flow Gradient (HFG) statistical logistic regression analysis. First, optical flow is estimated HFG constructed from video shots. Then vehicle patterns are clustered...

Electrocardiograms (ECGs) and photoplethysmography (PPG) facilitate non-invasive cardiovascular monitoring; however, the correlation between their respective waveforms, which exhibit high cycle correlation, remains underexplored.This study aims to estimate ECG signals from PPG data using an array of Deep Neural Networks (DNNs) across varied transformation feature domains, thereby making measurements a more expedient less effort-intensive alternative acquisition.A novel, subject-specific deep...

In this paper, we propose the design, operation, and implementation of an Internet Things-based hybrid structural health monitoring. This innovative system leverages capabilities both fog cloud layers in computing The architecture consists leaf nodes deployed on a target structure. These nodes, synchronously, collect acceleration signals from accelerometers attached directly to structure transmit data on-site central node via short-range communication protocol. At layer, node, applies damage...

Research in content-based image retrieval (CBIR) shows that high-level semantic concepts cannot be constantly depicted using low-level features. So the process of designing a CBIR system should take into account diminishing existing gap between visual features and concepts. In this paper, we propose new architecture for named SNNIR (splines neural network-based retrieval). makes use rapid precise model. This model employs cubic-splines activation function. By spline model, is minimized....

Image-object extraction is one of the most important parts in image processing. Object technique extracting objects from pre-processed such a way that within - class similarity maximized and between minimized. In this paper, new method grey scale static images using Fast Discrete Curvelet Transform (FDCT) via wrapping function proposed. The motivation curvelet transform proposed due to approximate properties high directional sensitivity transform. An imaginary component coefficients extract...

Real-time feature extraction is a key component for any action recognition system that claims to be truly real-time. In this paper we present conceptually simple and computationally efficient method real-time human activity based on statistical features. Such features are very cheap compute form relatively low dimensional space in which classification can carried out robustly. On the Weizmann dataset, proposed achieves encouraging results with an average rate up 97.8%. These good agreement...

A reliable model for human skin is a significant need wide range of computer vision applications ranging from face detection, gesture analysis, content-based image retrieval systems, searching and filtering content on the web, to various interaction domains. In this paper, robust neural recognition first presented. Then, fully automated network based system recognizing naked people in color images proposed. The proposed makes use fast precise model, called Multi-level Sigmoidal Neural...

Temporal invariant shape moments intuitively seem to provide an important visual cue human activity recognition in video sequences. In this paper, SVM based method for is introduced. With method, the feature extraction carried out on a small number of computationally-cheap moments. When tested popular KTH action dataset, obtained results are promising and compare favorably with that reported literature. Furthermore our proposed achieves real-time performance, thus can latency guarantees...

Despite their high stability and compactness, chord-length features have received little attention in activity recognition literature. In this paper, we present an SVM approach for recognition, based on shape features. The main contribution of the paper is two-fold. We first show how a compact computationally-efficient descriptor constructed using 1-D functions. Secondly, unfold to use fuzzy membership functions partition action snippets into number temporal states. When tested KTH benchmark...

Recently the indexed modulation (IM) technique in conjunction with multi-carrier gains an increasing attention. It conveys additional information on subcarrier indices by activating specific subcarriers frequency domain besides conventional amplitude-phase of activated subcarriers. Orthogonal division multiplexing (OFDM) IM (OFDM-IM) is deeply compared classical OFDM. leads to attractive trade-off between spectral efficiency (SE) and energy (EE). In this paper, concept combinatorial...

Over the past few years, dynamic spectrum access has been gaining an increasing attention as a solution to scarcity problem. In this paper, primary user detection technique based on Maximum A Posteriori estimation is proposed for networks. technique, set of secondary users acting sensing nodes send their individual decisions about existence central fusion center. The center uses received data form codeword then, applies maximum posteriori rule make final decision regarding presence user....

One of the greatest challenges facing physical layer design internet things (IoT) resides in imposed constraint very low power consumption. Recently, new modulation scheme termed OFDM with sparse index (OFDM-SIM) has been introduced as an energy efficient multicarrier (MCS). Although its high efficiency (EE) and spectral (SE), OFDM-SIM cannot fulfill IoT requirements owing to PAPR. In this regard, enhanced is proposed paper MCS for communications. particular, a novel clipping-compressive...

Retrieving human actions from video databases is a paramount but challenging task in computer vision. In this work, we develop such framework for robustly recognizing sequences. The contribution of the paper twofold. First reliable neural model, Multi-level Sigmoidal Neural Network (MSNN) as classifier action recognition presented. Second unfold how temporal shape variations can be accurately captured based on both self-similarities and fuzzy log-polar histograms. When method evaluated...

The low power consumption merit of the multi-input multi-output constant envelope modulation (MIMO-CEM) system nominated it to be a favorable candidate design PHY layer smart devices that support internet things (IoT) technology. Thanks CEM, MIMO-CEM efficiently overcomes high peak-to-average ratio (PAPR) in transmitter side (TX). Hence, an efficient class C or D amplifier (PA) is used TX instead inefficient A PA. Furthermore, depending on (CE) property received signal, resolution 1-bit...