http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
A Power Allocation Algorithm Based on Variational Inequality Problem for Cognitive Radio Networks
( Ming-yue Zhou ),( Xiao-hui Zhao ) 한국정보처리학회 2017 Journal of information processing systems Vol.13 No.2
Power allocation is an important factor for cognitive radio networks to achieve higher communication capacity and faster equilibrium. This paper considers power allocation problem to each cognitive user to maximize capacity of the cognitive systems subject to the constraints on the total power of each cognitive user and the interference levels of the primary user. Since this power control problem can be formulated as a mixed-integer nonlinear programming (NP) equivalent to variational inequality (VI) problem in convex polyhedron which can be transformed into complementary problem (CP), we utilize modified projection method to solve this CP problem instead of finding NP solution and give a power control allocation algorithm with a subcarrier allocation scheme. Simulation results show that the proposed algorithm performs well and effectively reduces the system power consumption with almost maximum capacity while achieve Nash equilibrium.
Ming Yue,Xiangmin Wu,Lie Guo,Junjie Gao 제어·로봇·시스템학회 2019 International Journal of Control, Automation, and Vol.17 No.10
In this paper, a dynamic automatic obstacle avoidance trajectory planning and tracking control framework is proposed for tractor-trailer system. Tractor-trailer is a special class of multibody and nonholonomic system, whose backward and forward operations have difference kinetic mechanisms. Because the obstacle avoidance behaviors are concerned with the two motion modes, the kinematic models including backward and forward movements are firstly derived. Secondly, a time-based quintic polynomial function is developed to plan two kinds of dynamic obstacle avoidance trajectories based on dynamics constraints and the information from on board sensors, so as to minimize the collision risk. Thirdly, a model predictive control (MPC)-based posture controller is designed, by which better tracking performance can be achieved for both forward and backward obstacle avoidance maneuvers. Lastly, the simulation results validate the effectiveness of the proposed dynamic obstacle avoidance framework and the designed methods.
Applications of a Deep Neural Network to Illustration Art Style Design of City Architectural
( Yue Wang ),( Jia-wei Zhao ),( Ming-yue Zheng ),( Ming-yu Li ),( Xue Sun ),( Hao Liu ),( Zhen Liu ) 한국정보처리학회 2024 Journal of information processing systems Vol.20 No.1
With the continuous advancement of computer technology, deep learning models have emerged as innovative tools in shaping various aspects of architectural design. Recognizing the distinctive perspective of children, which differs significantly from that of adults, this paper contends that conventional standards may not always be the most suitable approach in designing urban structures tailored for children. The primary objective of this study is to leverage neural style networks within the design process, specifically adopting the artistic viewpoint found in children's illustrations. By combining the aesthetic paradigm of urban architecture with inspiration drawn from children's aesthetic preferences, the aim is to unearth more creative and subversive aesthetics that challenge traditional norms. The selected context for exploration is the landmark buildings in Qingdao City, Shandong Province, China. Employing the neural style network, the study uses architectural elements of the chosen buildings as content images while preserving their inherent characteristics. The process involves artistic stylization inspired by classic children's illustrations and images from children's picture books. Acting as a conduit for deep learning technology, the research delves into the prospect of seamlessly integrating architectural design styles with the imaginative world of children's illustrations. The outcomes aim to provide fresh perspectives and effective support for the artistic design of contemporary urban buildings.
Ming Yue,Deng Zhihui,Tian Xianhua,Jia Yuerong,Ning Meng,Cheng Shuhua 대한신경정신의학회 2022 PSYCHIATRY INVESTIGATION Vol.19 No.10
Objective Hippocampal neuron apoptosis contributes to autism, while METTL3 has been documented to possess great potentials in neuron apoptosis. Our study probed into the role of METTL3 in neuron apoptosis in autism and to determine the underlying mechanism.Methods Bioinformatics analysis was used to analyze expressed genes in autism samples. Institute of Cancer Research mice were treated with valproic acid to develop autism models. The function of METTL3 in autism-like symptoms in mice was analyzed with behavioral tests and histological examination of their hippocampal tissues. Primary mouse hippocampal neurons were extracted for in vitro studies. Downstream factors of METTL3 were explored and validated.Results METTL3, MALAT1, and Wnt/β-catenin signaling were downregulated, while SFRP2 was upregulated in the hippocampal tissues of a mouse model of autism. METTL3 stabilized MALAT1 expression by promoting m6A modification of MALAT1. MALAT1 promoted SFRP2 methylation and led to reduced SFRP2 expression by recruiting DNMT1, DNMT3A, and DNMT3B to the promoter region of SFRP2. Furthermore, SFRP2 facilitated activation of the Wnt/β-catenin signaling. By this mechanism, METTL3 suppressed autism-like symptoms and hippocampal neuron apoptosis.Conclusion This research suggests that METTL3 can reduce autism-like symptoms and hippocampal neuron apoptosis by regulating the MALAT1/SFRP2/Wnt/β-catenin axis.
Spatial-temporal texture features for 3D human activity recognition using laser-based RGB-D videos
( Yue Ming ),( Guangchao Wang ),( Xiaopeng Hong ) 한국인터넷정보학회 2017 KSII Transactions on Internet and Information Syst Vol.11 No.3
The IR camera and laser-based IR projector provide an effective solution for real-time collection of moving targets in RGB-D videos. Different from the traditional RGB videos, the captured depth videos are not affected by the illumination variation. In this paper, we propose a novel feature extraction framework to describe human activities based on the above optical video capturing method, namely spatial-temporal texture features for 3D human activity recognition. Spatial-temporal texture feature with depth information is insensitive to illumination and occlusions, and efficient for fine-motion description. The framework of our proposed algorithm begins with video acquisition based on laser projection, video preprocessing with visual background extraction and obtains spatial-temporal key images. Then, the texture features encoded from key images are used to generate discriminative features for human activity information. The experimental results based on the different databases and practical scenarios demonstrate the effectiveness of our proposed algorithm for the large-scale data sets.
Ming Yue,Cong An,Jian-zhong Sun 제어·로봇·시스템학회 2018 International Journal of Control, Automation, and Vol.16 No.1
This study presents a robust model predictive control (MPC) strategy to handle the trajectory tracking problem for a underactuated two-wheeled inverted pendulum (WIP) vehicle, in addition to taking various physical constraints into account. To begin with, a saturated trajectory generator is proposed to produce the desired velocities by which all posture tracking errors converge to the compact sets as well as the saturation of velocities being guaranteed. In addition, a MPC approach is put up forward after the approximate feedback linearization is performed to decrease the burden of computation and increase the realtime performance of the control system. Particularly, various physical constraints can be readily assured by the presented MPC method although the equilibrium of WIP vehicle is unstable. Meanwhile, to validate the robustness and availability of the proposed approach, initial errors, pulse disturbance and random noise are introduced to test the control performance of the closed-loop system in the simulation environment. The results from both theoretical analysis and simulation show that the proposed control strategy are effective and feasible for practical implementation.