^(64)Zn and ^(67)Zn (n,α) Reactions in the MeV Neutron Energy Region

Guohui Zhang,Jiaguo Zhang,Hao Wu,Jiaming Liu,Jinxiang Chen,Yuri Gledenov,Milana Sedysheva,Gonchigdorj Khuukhenkhuu,Pavel Szalanski 한국물리학회 2011 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.59 No.23

Nuclear reactions of ^(64)Zn(n,α)^(61)Ni and ^(67)Zn(n,α)^(64)Ni are important because they are gas pro-duction reactions and zinc is a reactor constituent element with a signicant fraction. But the cross section data of these reactions are scanty because the residual nuclei ^(61)Ni and ^(64)Ni are stable and the commonly used activation method is not feasible. In the present work, differential cross sections and angleintegrated cross sections were measured for the ^(64)Zn(n,α)^(61)Ni reaction at neutron energies of 2.5, 4.0, 5.0, 5.5, and 6.0 MeV and cross sections of the ^(67)Zn(n,α)^(64)Ni reaction were measured at 4.0, 5.0, and 6.0 MeV. A twin gridded ionization chamber was employed as alpha particle detector. Experiments were performed at the 4.5 MV Van de Graaff accelerator of Peking University. Monoenergetic neutrons of 2.5 MeV were produced through the T(p, n)^3He reaction with a solid Ti-T target, and those of other energies were produced through the D(d, n)^3He reaction with a deuterium gas target. Absolute neutron fluxes were determined through the ^(238)U(n, f) reaction and a BF^3 long counter was used as the neutron flux monitor. Present results are compared with other measurements and evaluations.

Detection of Water Cloud Microphysical Properties Using Multi-scattering Polarization Lidar

Jiaming Xie,Xingyou Huang,Lingbing Bu,Hengheng Zhang,Farhan Mustafa,Chenxi Chu 한국광학회 2020 Current Optics and Photonics Vol.4 No.3

Multiscattering occurs when a laser transmits into dense atmosphere targets (e.g. fogs, smoke or clouds), which can cause depolarization effects even though the scattering particles are spherical. In addition, multiscattering effects have additional information about microphysical properties of scatterers. Thus, multiscattering can be utilized to study the microphysical properties of the liquid water cloud. In this paper, a Monte Carlo method was used to simulate multi-scattering transmission properties of Lidar signals in the cloud. The results showed the slope of the degree of linear polarization (SLDLP) can be used to invert the extinction coefficient, and then the cloud effective size (CES) and the liquid water content (LWC) may be easily obtained by using the extinction coefficient and saturation of the degree of linear polarization (SADLP). Based on calculation results, a microphysical properties inversion method for a liquid cloud was presented. An innovative multiscattering polarization Lidar (MSPL) system was constructed to measure the LWC and CES of the liquid cloud, and a new method based on the polarization splitting ratio of the Polarization Beam Splitter (PBS) was developed to calibrate the polarization channels of MSPL. By analyzing the typical observation data of MSPL observation in the northern suburbs of Nanjing, China, the LWC and CES of the liquid water cloud were obtained. Comparisons between the results from the MSPL, MODIS and the Microwave radar data showed that, the microphysical properties of liquid cloud could be retrieved by combining our MSPL and the inversion method.

Calibration of Underwater Polarization Image Based on the Radian of Distorted Curves in the Checkboard

Jiaming Wei,Qi Li,Lili Zhang 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.8

The calibration of polarization imaging system is the premise to obtain target polarization information accurately, in this paper, we propose a method of calibration based on the radian of distorted curves in the checkboard to solve the problem of losing polarization information in the underwater distorted polarization images. Firstly, we use the radian of distorted curves in the checkboard to calculate the coordinates of distortion center, and calibrate the region near the distortion center. Then we use the calibrated region to reconstruct the whole image. Finally, we combine the distorted image, the reconstructed image and the distortion model to obtain the calibration parameters. With these parameters we can get the calibrated polarization images. The experiments show that our method can calibrate the polarization image accurately, reduce the coupled error and calculate parameters independently.

Full-order and Reduced-order Observer Design for One-sided Lipschitz Nonlinear Fractional Order Systems with Unknown Input

Tao Zhang,Jiaming Tian,Shu-Ping Ma 제어·로봇·시스템학회 2018 International Journal of Control, Automation, and Vol.16 No.5

This paper studies the problem of designing the unknown input observers (UIOs) for fractional order one-sided Lipchitz nonlinear systems. By introducing a continuous frequency distributed equivalent model and using the matrix generalized inverse approach, sufficient conditions for asymptotic stability of the observer error dynamic systems are presented, which guarantee the existence of the full-order and reduced-order UIOs. All the conditions are obtained in terms of linear matrix inequality (LMI). Furthermore, we show that the obtained results can be applied to a fractional order electrical circuit with the unknown input signal. Two examples are given to demonstrate the applicability of the proposed approach.

Visual Analysis of Deep Q-network

( Dewen Seng ),( Jiaming Zhang ),( Xiaoying Shi ) 한국인터넷정보학회 2021 KSII Transactions on Internet and Information Syst Vol.15 No.3

In recent years, deep reinforcement learning (DRL) models are enjoying great interest as their success in a variety of challenging tasks. Deep Q-Network (DQN) is a widely used deep reinforcement learning model, which trains an intelligent agent that executes optimal actions while interacting with an environment. This model is well known for its ability to surpass skilled human players across many Atari 2600 games. Although DQN has achieved excellent performance in practice, there lacks a clear understanding of why the model works. In this paper, we present a visual analytics system for understanding deep Q-network in a non-blind matter. Based on the stored data generated from the training and testing process, four coordinated views are designed to expose the internal execution mechanism of DQN from different perspectives. We report the system performance and demonstrate its effectiveness through two case studies. By using our system, users can learn the relationship between states and Q-values, the function of convolutional layers, the strategies learned by DQN and the rationality of decisions made by the agent.

Study on Seismic Response Characteristics and Design Parameters of Composite Isolation System for Rural Buildings

Kang Yuan,Jiaming Zhang,Junlin Guo,Wan Tian 대한토목학회 2019 KSCE Journal of Civil Engineering Vol.23 No.4

The seismic capacity of rural buildings is low and effective execution of the traditional seismic measures is difficult. Therefore, a new type of composite isolation system, which is suitable for rural buildings in frozen earth regions, is proposed in this work. The design parameters and dynamic response characteristics of this system under rare earthquakes were investigated via systematic dynamic elastic-plastic time-history analyses performed on four different types of models. These models were established by the finite element software ABAQUS, and a composite isolation structure, sliding isolation structure, sand cushion isolation structure, and traditional masonry structure were considered. Afterward, the seismic response characteristics and design parameters of the composite isolation system were obtained by comparing the dynamic response analysis results (acceleration, displacement, and bottom shearing force) of each model. The best isolation effect was realized for the composite isolation system, where the seismic energy can be effectively absorbed and the impact of frost heaving on buildings can be eliminated. Furthermore, this effect will improve with decreasing friction coefficient of the sliding layer and increasing seismic intensity. Based on the preset isolation rate of 40%, the design values of the friction coefficient were determined to be 0.1–0.35, which are appropriate for high-seismic-intensity regions.

Optimization design of graphene with adjustable hydrophilic properties by finite elements analysis

Shixun Sun,Jiaming Song,Naiyu Cui,Xinyue Lu,Xuehan Li,Heng Zhang,Heng Bo Jiang 대한치과재료학회 2021 대한치과기재학회 학술대회 Vol.2021 No.4

Joint Optimization of Time-Slot Allocation and Traffic Steering for Large-Scale Deterministic Networks

Wu, Wenhao,Zhang, Xiaoning,Pan, Jiaming,Zhou, Yihui 한국통신학회 2023 Journal of communications and networks Vol.25 No.6

Recently, time-sensitive services have expanded from traditional industrial control systems to more scenarios. Some time-sensitive applications, such as remote surgery, autonomous driving, Augmented Reality (AR), etc., require deterministic end-to-end delay and jitter in data transmission. Deterministic Network (DetNet) is proposed as a promising technology for providing deterministic service in Wide Area Networks (WAN). DetNet guarantees deterministic end-to-end delay and jitter by specifying a certain routing path and transmission time-slots for time-sensitive flows. However, how to efficiently steer time-sensitive flows while jointly allocating transmission time-slots is still an open problem. Existing flow scheduling algorithms are limited in the scenarios of Local Area Networks (LAN), and do not consider the impact of propagation delay in large-scale networks. To this end, we study the joint optimization of time-slot allocation and traffic steering, while considering the propagation delay of WAN links. Our objective is to maximize the number of successfully deployed time-sensitive flows under the constraints of required end-to-end delay. Accordingly, we formulate the studied problem as an Integer Linear Programming (ILP) model. Since it is proved to be an NP-hard problem, we design a heuristic algorithm named Genetic-based Deterministic Network Traffic Scheduling (GDNTS). The solution with the largest number of deployed time-sensitive flows can be obtained from the evolution of chromosomes in GDNTS. Compared with the benchmark algorithms, extensive simulation results show that GDNTS improves the deployed time sensitive flows number by 22.85% in average.

Multi-scale Nano/Micro Fiber Scaffolds with Different Topological Morphologies

Jianyong Feng,Ruixiang Xu,Jiaming Zhao,Lingxiao Zhang 한국섬유공학회 2022 Fibers and polymers Vol.23 No.4

The multi-scale fiber and topological morphologies had been shown to influence cell mitogenesis and chemotaxis,direct cell differentiation, and induce constructive host tissue remodeling responses. To simulate multi-layer meshworkarchitecture of extracellular matrix and regulate cell behavior, we prepared different topological scaffolds, such as 3Dprinting fiber scaffolds, poly(lactic acid) (PLA) electrospun fiber scaffolds, 3D printing/knitted fabric composite scaffolds,and PLA electrospinning/knitted fabric composite scaffolds. The surface morphology, pore diameter, thickness, stress-straincurve, electrical current, and other properties were studied. The aim is to prepare multi-scale nano/micro fiber scaffolds withdifferent topological morphologies and properties that can provide structural and mechanical support for potential tissueengineering applications.

Unidirectional sensitive flexible sensor for bending measurements

Li Mengmeng,Liang Jiaming,Min Zhang 한국물리학회 2021 Current Applied Physics Vol.23 No.-

The measurement of bending direction and bending angles is essential in the multiaxial servo-controlled system, especially for collaborative robots. However, most flexible sensors developed for bending measurements cannot distinguish bending directions due to their sensitivity to both positive and negative bending. Also, these sensors usually exhibit simultaneous response to normal pressure, which results in additional calibration. Here, a unidirectional-sensitive flexible capacitive sensor is proposed. A simple asymmetric pyramidal microstructure was designed to create uneven responses to positive and negative bending and minimum response to normal pressure based on the fringe effect. The fabricated sensor shows a relative capacitance change of nearly 0.9 in the sensitive direction and only 0.05 in the other direction as the sensor bends from flat to the curvature radius of 10 mm. Also, the sensor shows negligible sensitivity even under a normal pressure force as high as 16 N, either in planar or bending condition.