Recent evidence in mental health assessment have demonstrated that facial appearance could be highly indicative of depressive disorder. While previous methods based on the analysis promise to advance clinical diagnosis disorder a more efficient and objective manner, challenges visual representation complex depression pattern prevent widespread practice automated diagnosis. In this paper, we present deep regression network termed DepressNet learn with explanation. Specifically, convolutional...

Pottery making in technology education aims to foster students' practical and creative ability. In a typical pottery class, students receive the teacher's instruction on fundamental techniques used have opportunities practice. It is meaningful construct an observation-doing-reflection process for class promote their learning experience performance. Therefore, this study, Virtual Reality (VR)-based approach was applied junior high school examine its effects creativity engagement. A total of...

Abstract Zinc powder is the key anode material for commercialization of aqueous Zn ion batteries (AZIBs), taking advantage its cost‐effectiveness and ease processing. However, they face challenges such as severe dendrite growth, side reactions, corrosion due to rough surface with high specific area. This paper proposes a low‐cost, simple, scalable method modify powder‐based anodes by incorporating nano‐Copper (NC) functional conductive agent, modified electrode denoted ZP‐NC. NC modification...

This research presents the best power management of flexible-renewable integrated energy systems (FRIESs) with smart distribution networks (SDNs) by taking nonlinear load harmonic compensation into account. A deterministic model that optimizes for three distinct goals serves as foundation proposed system. The goal is to minimize combined impact network's operational costs, losses, and voltage distortion, account their respective weights. In FRIES framework, function a constraint on operation...

Deep Convolutional Neural Networks (CNNs) have achieved remarkable success in various fields. However, training an excellent CNN is practically a trial-and-error process that consumes tremendous amount of time and computer resources. To accelerate the reduce number trials, experts need to understand what has occurred why resulting behaves as it does. current popular platforms, such TensorFlow, only provide very little general information, training/validation errors, which far from enough...

The instability of Zn anode resulting from corrosion and dendritic growth remain impeding the development aqueous zinc-ion batteries (AZIBs). In addition, desolvation on surface is sluggish, which hinders reaction kinetics fast charge/discharge behavior AZIBs. Herein, uniform deposition are realized by using a hydrophilic fumed nano-silica coating with zinc alginate (Alg) as functional binder (Alg/SiO2@Zn). Combined theoretical calculation experimental investigations show interaction between...

Deep convolutional neural networks (CNNs) have achieved remarkable success in various fields. However, training an excellent CNN is practically a trial-and-error process that consumes tremendous amount of time and computer resources. To accelerate the reduce number trials, experts need to understand what has occurred why resulting behaves as such. current popular platforms, such TensorFlow, only provide very little general information, training/validation errors, which far from enough serve...

Although face recognition has achieved good performance in attendance marking system, people need to cooperate with the camera. Human identification performs poorly surveillance videos because of deformed and occluded conditions. In this paper, we propose a new method recognize human using global local structural information. Firstly, combine pedestrian detection tracking recognition, order improve occlusion faces. Secondly, selective algorithm based on trajectory, which is used identify...

Missing data universally exists in various research fields and it results bad computational performance effcet. In order to improve the accuracy of filling missing data, a algorithm nearest neighbor based on cluster analysis is proposed by this paper. After clustering analysis,the assigns weights according categories improves calculation formula value MGNN (Mahalanobis-Gray Nearest Neighbor algorithm) algorithm.The experimental show that method higher than traditional KNN algorithm.

To establish a general and robust shot boundary detection algorithm, according to characteristics of lens conversion the ideal multiple video features fusion, algorithm is proposed based on YUV histogram, texture feature edge orientation histogram in paper. Besides, global self-adaptive threshold are combined use so as control process enhance accuracy selection. The experiment results show that can effectively realize strengthen robustness detection.

Medical image anomaly detection refers to machine learning techniques analyze and identify lesions abnormalities in them. However, medical images, samples are usually sparse, which can lead supervised not being able obtain sufficient training. While existing unsupervised is mainly based on reconstruction generation as well feature embedding, these methods do take into account the problem of data type bias during domain migration often face loose judgment boundaries. To this end, paper...

Abstract The resilience of supply chain and logistics is becoming extremely critical under unprecedented extra-ordinary situation, such as COVID-19 pandemic. International trade global are vital components the economy. Transactions within chains account for over 76% world trade. efficiency U.S. a factor supporting competitiveness economy whole. integrity security these also national concerns. Applying international standards in design operation one key solutions to improve its safety...

In this paper, we propose a fast and accurate block-matching algorithm for motion estimation of human faces via Artificial Bee Colony (ABC) optimization. The mean square error (MSE) is often used as the matching metric in block matching, which, however, has high computational cost practice. By using ABC optimization, introduce novel effective metric. We develop based on proposed to improve accuracy with lower cost. Experimental results show that our method could achieve significant...

Environmental factors have become an important factor for a manufacturing process. It includes quantity of solid wastes generated, air pollution, water catalysts flow, health and safety operators. Efforts were made in all possible stages manufacturing, one among them is environmental conscious process planning. takes into account issues with technical operational factors. parameters that effect eco-friendly planning often difficult to measure, as there it involves certain degree vagueness,...