Human posture estimation is a crucial topic in the computer vision field and has become a hotspot for research in many human behaviors related work. Human pose estimation can be understood as the human key point recognition and connection problem. The paper presents an optimized symmetric spatial transformation network designed to connect with single-person pose estimation network to propose high-quality human target frames from inaccurate human bounding boxes, and introduces parametric pose non-maximal suppression to eliminate redundant pose estimation, and applies an elimination rule to eliminate similar pose to obtain unique human pose estimation results. The exploratory outcomes demonstrate the way that the proposed technique can precisely recognize the human central issues, really work on the exactness of human posture assessment, and can adjust to the intricate scenes with thick individuals and impediment. Finally, the difficulties and possible future trends are described, and the development of the field is presented.
Abstract
The study aims to examine the relationships between cognitive absorption and E-Learning readiness in the preparatory stage. The study sample consisted of (190) students who were chosen randomly. The Researcher has developed the cognitive absorption and E-Learning readiness scales. A correlational descriptive approach was adopted. The research revealed that there is a positive statistical relationship between cognitive absorption and eLearning readiness.
This paper presents a hybrid genetic algorithm (hGA) for optimizing the maximum likelihood function ln(L(phi(1),theta(1)))of the mixed model ARMA(1,1). The presented hybrid genetic algorithm (hGA) couples two processes: the canonical genetic algorithm (cGA) composed of three main steps: selection, local recombination and mutation, with the local search algorithm represent by steepest descent algorithm (sDA) which is defined by three basic parameters: frequency, probability, and number of local search iterations. The experimental design is based on simulating the cGA, hGA, and sDA algorithms with different values of model parameters, and sample size(n). The study contains comparison among these algorithms depending on MSE value. One can conc
... Show MoreWireless sensor networks (WSNs) represent one of the key technologies in internet of things (IoTs) networks. Since WSNs have finite energy sources, there is ongoing research work to develop new strategies for minimizing power consumption or enhancing traditional techniques. In this paper, a novel Gaussian mixture models (GMMs) algorithm is proposed for mobile wireless sensor networks (MWSNs) for energy saving. Performance evaluation of the clustering process with the GMM algorithm shows a remarkable energy saving in the network of up to 92%. In addition, a comparison with another clustering strategy that uses the K-means algorithm has been made, and the developed method has outperformed K-means with superior performance, saving ener
... Show MoreThe effect of using different R -molar ratio under variable reaction conditions (acidic as well as basic environment and reaction temperature) have been studied. The overall experiments are driven with open and closed systems. The study shows that there is an optimum value for a minimum gelling time at R equal 2. The gelling time for all studied open system found to be shorter than in closed system. In acidic environment and when R value increased from 2 to 10, the gelling time of closed systems has increased four times than open systems at T=30 ?C and fourteen times when temperature reaction increased to 60 ?C. While in basic environment the influence of increasing R value was limited.
The general health of palm trees, encompassing the roots, stems, and leaves, significantly impacts palm oil production, therefore, meticulous attention is needed to achieve optimal yield. One of the challenges encountered in sustaining productive crops is the prevalence of pests and diseases afflicting oil palm plants. These diseases can detrimentally influence growth and development, leading to decreased productivity. Oil palm productivity is closely related to the conditions of its leaves, which play a vital role in photosynthesis. This research employed a comprehensive dataset of 1,230 images, consisting of 410 showing leaves, another 410 depicting bagworm infestations, and an additional 410 displaying caterpillar infestations. Furthe
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Black paint laser peening (bPLP) technique is currently applied for many engineering materials , especially for aluminum alloys due to high improvement in fatigue life and strength . Constant and variable bending fatigue tests have been performed at RT and stress ratio R= -1 . The results of the present work observed that the significance of the surface work hardening which generated high negative residual stresses in bPLP specimens .The fatigue life improvement factor (FLIF) for bPLP constant fatigue behavior was from 2.543 to 3.3 compared to untreated fatigue and the increase in fatigue strength at 107 cycle was 21% . The bPLP cumulative fatigue life behav
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