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- 저자 : Zhihao Zhou (검색결과 5 건)
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Zhihao Ding,Guang-Xi Hu,Ran Liu,Ling-Li Wang,Shuyan Hu,Xing Zhou 한국물리학회 2013 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.62 No.8
Analytical models for the electric potential, threshold voltage and drain current of long-channel junctionless (JL) double-gate (DG) field-effect transistors (FET) are presented. A regional method is used to solve the Poisson equation under different gate biases, and the electric potential is obtained. With the potential model, an analytical expression for the threshold voltage is achieved. An expression for the drain current is derived from the potential model. The analytical results are compared with simulations, and excellent agreements are observed. The models accurately describe the characteristics of JLDG FETs, and they are very helpful for the design and optimization of devices.
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Influence of Injection System Parameters on Combustion Noise of a Small Power Non-Road Diesel Engine
Zhou Xinfeng,Ma Zhihao,Liu Yuna,Li Ao 한국자동차공학회 2023 International journal of automotive technology Vol.24 No.5
Combustion noise accounts for a large proportion of diesel engine noise. On the premise of not increasing the cost of diesel engine, the injection system parameters such as dynamic fuel supply advance angle and needle valve opening pressure are optimized, and the influence of the above parameters on the in-cylinder pressure, rate of pressure rise, in-cylinder pressure level (CPL) spectrum and high frequency pressure oscillation is analyzed. The study shows that reducing the dynamic fuel supply advance angle can effectively reduce the combustion noise, and appropriately increasing the needle valve opening pressure can also reduce the combustion noise. After the optimization of injection parameters, the combustion noise of the diesel engine with an electronically controlled VE pump-tube-nozzle injection system is significantly reduced compared with the prototype engine, and can reach the same level of combustion noise as the diesel engine with the common rail system without deterioration of fuel economy and emission performance. The experimental study can provide technical reference for diesel engines in the selection of injection system parameters and the optimization of combustion noise in the improvement stage.
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Minor and major circRNAs in virus and host genomes
Lou Zhihao,Zhou Rui,Su Yinghua,Liu Chun,Wenting Ruan,전체옥,Xiao Han,Chun Lin,BAOLEI JIA 한국미생물학회 2021 The journal of microbiology Vol.59 No.3
As a special type of noncoding RNA, circular RNAs (circRNAs) are prevalent in many organisms. They can serve as sponges for microRNAs and protein scaffolds, or templates for protein translation, making them linked to cellular homeostasis and disease progression. In recent years, circRNAs have been found to be abnormally expressed during the processes of viral infection and pathogenesis, and can help a virus escape the immune response of a host. Thus, they are now considered to play important functions in the invasion and development of viruses. Moreover, the potential application of circRNAs as biomarkers of viral infection or candidates for therapeutic targeting deserves consideration. This review summarizes circRNAs in the transcriptome, including their classification, production, functions, and value as biomarkers. This review paper also describes research progress on circRNAs in viral infection (mainly hepatitis B virus, HIV, and some human herpes viruses) and aims to provide new ideas for antiviral therapies targeting circRNAs.
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Solving Truss Topological Optimization via Swarm Intelligence
Bin Yang,Qilin Zhang,Zhihao Zhou 대한토목학회 2015 KSCE JOURNAL OF CIVIL ENGINEERING Vol.19 No.7
Structural topological optimization is the most general form of structural optimization and requires a less detailed description of the concept. One of the most exciting and challenging problems in this field is to find optimized layouts with minimization of compliance (maximization of stiffness) for a given total mass of the structure discretized by truss members, which cannot be well solved by evolutionary algorithms. Particle Swarm Optimization (PSO) is a new paradigm of Swarm Intelligence which is inspired by concepts from ‘Social Psychology’ and ‘Artificial Life’. PSO is particularly a preferable candidate to solve highly nonlinear, nonconvex and even discontinuous problems and has been applied to many different kinds of optimization problems. The motivation of this paper is to propose an enhanced Lbest based PSO and geometrical consistency check tightly connecting to the ground structure approach to break through in this optimization field. Through a popular benchmark test, two kinds of Modified Lbest based PSO (MLPSO) exhibited competitive performance due to improved global searching ability.
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Bin Yang,Kai-Uwe Bletzinger,Qilin Zhang,Zhihao Zhou 대한토목학회 2013 KSCE Journal of Civil Engineering Vol.17 No.6
As a comparatively new developed stochastic method - Particle Swarm Optimization (PSO), it is widely applied to various kinds of optimization problems especially of nonlinear, non-differentiable or non-concave types. In this paper, a Parallel Modified Guaranteed Converged Particle Swarm algorithm (PMGCPSO) is proposed, which is inspired by the Guaranteed Converged Particle Swarm algorithm (GCPSO) proposed by von den Bergh. Details in the algorithm implementation and properties are presented and, an analytical benchmark test and structural sizing and topological test cases are used to evaluate the performance of the proposed PSO variant, PMGCPSO exhibited competitive performance due to improved global searching ability and its corresponding parallel model indicates nice parallel efficiency.
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