277 research outputs found
A positron annihilation lifetime spectroscopic study of nanocrystals formation in a chalcogenide glass-ceramic
No full textJiaxiang Nie, Fang Xia, Runsheng Yu, Baoyi Wang, Zhuoxin Li, Guorong Che
Simulation of Line-Edge Roughness Effects in Silicon Nanowire MOSFETs
No full textIn this paper, the effects of nanowire (NW) lineedge roughness (LER) in gate-all-around (GAA) silicon nanowire MOSFETs (SNWTs) are investigated by 3-D statistical simulation in terms of both performance variation and mean value degradation. A physical model is developed for NW LER induced performance degradation in SNWTs for the first time. The results indicate large performance mean value degradations due to NW LER in SNWTs. However, the LER induced parameter variation is still acceptable. In addition, as the LER correlation length (Lambda) scales beyond the gate length, new distribution of performance parameters is observed, which has dual-peaks rather than single in conventional Gaussian distribution. The optimization for NW LER parameters is given for SNWT design as well.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000283778800030&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Engineering, Electrical & ElectronicPhysics, AppliedEICPCI-S(ISTP)
Positron lifetime study of the crystal evolution and defect formation processes in a scintillating glass
No full text
The crystal evolution and defect formation in scintillating glasses as a consequence of thermal annealing were studied by annihilation lifetime spectroscopy and UV‐Vis absorption spectroscopy. The annihilation lifetime spectra and UV‐Vis spectra were recorded on glass 50SiO
2
–45ZnO–5BaF
2
before and after annealing at 580°C for 16, 32, and 48 h, respectively. The results show that the three lifetime components (τ
1
, τ
2
, and τ
3
) and the corresponding intensities (
I
1
,
I
2
, and
I
3
) change systematically with increasing annealing time. This reflects the crystal evolution and defect formation in the glass matrix. The continued crystal evolution was also revealed by the UV‐Vis spectra, as the absorption edge of the material shifted to a lower energy with prolonged annealing.
Jiaxiang Nie, Runsheng Yu, Baoyi Wang, Yuwen Ou, Yurong Zhong, Zhuoxin Li, Fang Xia, and Guorong Che
Unsolved Problems in Special and General Relativity
No full textThis book includes 21 papers written by 23 authors and co-authors: Hua Di, Li Zifeng, Li Wen-Xiu, Shi Yong-Cheng, Xu Jianmin, Dong Jingfeng, Duan Zhongxiao, Fu Yuhua, Guo Kaizhe, Guo Chongwu, Guo Ying-Huan, Guo Zhen-Hua, Hu Chang-Wei, Jiang Chun-Xuan, Liu Taixiang, Tu Runsheng, Wu Fengming, Yang Shijia, Cao Shenglin, Leo G. Sapogin, V. A. Dzhanibekov, Yu. A. Ryabov, and Florentin Smarandache.
The editors hope that all these papers will contribute to the advance of scholarly research on several aspects of Special and General Relativity. This book is suitable for students and scholars interested in studies of physics
Impact of Temporal Transistor Variations on Circuit Reliability
No full textWith the ever-increasing importance of temporal transistor variations during circuit run time and aging, this paper focuses on impacts of the two major temporal effects: the Bias Temperature Instability (BTI) and Random Telegraph Noise (RTN), illustrating their scaling trend, challenges, and potential solutions for future design robustness.EICPCI-S(ISTP)[email protected]; [email protected]
Effects of conservation policies on forest cover change in panda habitat regions, China
No full textTo restore forests and protect remaining natural forests, in 1998 the Chinese government initiated two nationwide conservation policies, the Natural Forest Conservation Program (NFCP) and the Grain-To-Green Program (GTGP). This study evaluated the effects of conservation policies and other potential driving forces on forest-cover change in 108 townships located in the Qinling Mountains and Sichuan Giant Panda Sanctuary (both known giant panda habitat regions) between 2001 and 2008. Forest-cover change was evaluated using land-cover products derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). Most townships in both regions showed either stable or increased forest cover. An Ordinary Least Square (OLS) regression model was applied to identify potential driving forces of this forest-cover change. The model suggests that conservation policies had significantly positive effects on forest cover, while population density, percentage of agricultural population, road density, and initial forest cover (i.e., in 2001) had significantly negative effects. This study helps to clarify not only the patterns of forest-cover change after conservation policy implementation, but also to identify the impacts of potential driving forces of forest-cover change, at township level. This information could be, in turn, useful in the development of future giant panda habitat restoration projects.Thesis (M.S.)--Michigan State University. Department of Fisheries and Wildlife, 2010Includes bibliographical references (pages 45-58
Impacts of diameter-dependent annealing on S/D extension random dopant fluctuations in silicon nanowire MOSFETs
No full textIn this paper, the impacts of diameter-dependent annealing (DDA) effect on nanowire S/D extension random dopant fluctuations (SDE-RDF) in silicon nanowire MOSFETs (SNWTs) are investigated, in terms of electrostatic properties, source/drain series resistance (RSD), and driving current. The SDE-RDF induced variations of threshold voltage (Vth) and DIBL in SNWTs with different diameters are found to be modest and decrease as the diameters down-scale. However, SDE-RDF induced RSD variation in SNWTs is enhanced by abnormal DDA effects, which aggravates the drive current variations with the downscaling of SNWT diameter. The results also show that Vth is the dominant factor in ON/OFF current ratio variation while RSD dominates that of ON current. The tradeoff between RSD and Vth dominant current variations is discussed to give some guidelines for SDE-RDF-aware design in SNWTs. ?2010 IEEE.EI
Research on Congestion Pricing in a Multiple-Operator Autonomous-Mobility-on-Demand System
No full textThe performance of multiple AMoD operators under congestion pricing strategies remains unexplored. We propose two congestion pricing strategies: Link-based congestion pricing strategy and Delay-based congestion pricing strategy to regulate AMoD services. We aim to demonstrate the effectiveness of such strategies using an agent-based modeling framework in a case study of the city of Hague, the Netherlands. Simulation results suggest that congestion pricing strategies could effectively reduce congestion, and congestion could be significantly reduced even if pricing strategies are in place in a limited area. Moreover, we found that the delay-based pricing scheme is more flexible and more capable of reducing congestion. It is recommended that some road sections may be tolled to reduce delays. Passengers, however, will have to accept higher fares because of the additional congestion fee (as we hypothesized), and the impact needs to be further investigated in future research.Civil Engineerin
Enhanced meta learning for few-shot learning, and recommendation system
No full textMeta-learning tries to leverage information from similar learning tasks. In the commonly-used bilevel optimization formulation, the shared parameter is learned in the outer loop by minimizing the average loss over all tasks. However, the converged solution may be compromised in that it only focuses on optimizing on a small subset of tasks. To alleviate this problem, we consider meta-learning as a multi-objective optimization (MOO) problem, in which each task is an objective. However, existing MOO solvers need to access all the objectives’ gradients in each iteration, and cannot scale to the huge number of tasks in typical meta-learning settings. To alleviate this problem, we propose a scalable gradient-based solver with the use of mini-batch. We provide theoretical guarantees on the Pareto optimality or Pareto stationarity of the converged solution. Empirical studies on various machine learning settings demonstrate that the proposed method is efficient, and achieves better performance than the baselines, particularly on improving the performance of the poorly-performing tasks and thus alleviating the compromising phenomenon. Moreover, we introduce a Meta Prompt Learning (MPL) method tailored for online recommendation systems. This method leverages a meta prompt to capture useful information from historical data efficiently. The key contributions of the MPL method include a bi-level optimization strategy to retain essential information, a multi-step gradient descent approximation for solution finding, and a comprehensive regret analysis of the system’s performance. Our experiments on datasets such as Tmall, Taobao, and Avazu demonstrate that MPL outperforms state-of-the-art models with lower memory usage and training time.</p
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