81,197 research outputs found
Huangdi nei jing su wen
No full text張志聰集註.綫裝.框19.9x13.8公分, 9行20字, 小字雙行同. 白口, 四周雙邊, 單黑魚尾. 版心上鐫題名,中鐫卷次, 下鐫葉次及"善成堂"第九卷分上, 下卷.內封背頁牌記鐫"光緒癸卯善成藏板"卷一卷端題名下署"錢塘張志聰隱菴集註, 同學張文啓開之參訂, 長男張兆璜玉師校正".《靈樞經》刻書風格與《素問》不同.With: 黃帝内經素問 : 九卷 / 張志聰集註.鈐"莊兆祥印"朱, 白文各一方.Xian zhuang.Kuang 19.9 x 13.8 gong fen, 9 hang 20 zi, xiao zi shuang hang tong. Bai kou, si zhou shuang bian, dan hei yu wei. Ban xin shang juan ti ming, zhong juan juan ci, xia juan ye ci ji "Shan cheng tang"Di jiu juan fen shang, xia juan.Nei feng bei ye pai ji juan "Guangxu gui mao Shan cheng cang ban"Detailed notes in vernacular field only."Ling shu jing" ke shu feng ge yu "Su wen" bu tong.Zhang Zhicong ji zhu.With: Huangdi nei jing su wen : jiu juan / Zhang Zhicong ji zhu.Qian "Zhuang Zhaoxiang yin" zhu, bai wen ge yi fang
Su Lüyi chuang zuo xuan.
No full text蘇雪林著 ; 少侯 [唐少侯] 編.書名據版權頁封面題:上海仿古書店發行散文集Su Xuelin zhu ; Shaohou [Tang Shaohou] bian.Detailed notes in vernacular field only.Detailed notes in vernacular field only.Detailed notes in vernacular field only
Full Tang in the beginning, the Tang Dynasty's "Grass" topics discussed
No full textThis paper \ue2Full Tang in the beginning, the Tang's "Grass" Poems \ue2mainly discusses the implications of the early Tang Dynasty poem "Grass". According to the background of that time and those experiences of the authors, the theme "Grass" is classified as natural grass, grass as a metaphor, nostalgia and mourning, sad parting, seclusion, women\ue2s displeasure, and homesickness. Besides, the poems will be analyzed.
The first chapter, introduction, talks about motivation and methods and then the second chapter makes a general tracing about the emergence and variety of the word "Grass".
The third chapter, gathers "Grass" poetry-related material from "Full Tang"
From different perspectives including "color", "season" and "recalling the tragic", we can understand the use case of "grass\ue2 in \ue2Full Tang". The fourth and fifth chapters, "Grass" in Tang presented in a variety of meanings involving image characterization of "grass", the space to express aesthetic or spiritual level will be explore
A history of Artificial Intelligence / Tang Su Ai
No full textThe history of Artificial Intelligence (Al) Website is a dynamic web-based one stop centre that offer comprehensive information about the history of Artificial Intelligence. It provides an efficient method of information searching and browsing with contemporary and attractive user-friendly and hypermedia-based user interface design. On the maintenance side, the information is well organized in a way that the web administrator can easily add on or modify the website effortlessly. The primary objective of the website arc to gather all the in formation related to the history of AI and provide a comprehensive source as well as a centralized repository of information to store history of AI. This is to provide a complete website that the Internet users can gain and learn more on increasingly popular field of AI. Functions that are provided by the website include searching capability that allow users to quickly locate the information the users are looking for. Users can also browse for the history of AI according to researcher, fields or in chronological order. A recent event section is provided to place all the recent events or developments of AI. Other miscellaneous sections are introduction of AI, about the website, etc. All the information on the website is created in hypermedia format. Overall, at the end of the development cycle, developing this website will be helpful and practical in promoting the ever expanding knowledge of Artificial Intelligence to the World Wide Web users
Integrated train timetabling and rolling stock rescheduling for a disturbed metro system: A hybrid deep reinforcement learning and adaptive large neighborhood search approach
No full textFor a metro line with high density and short trip time, the original train timetable and rolling stock circulation face infeasible risks under unexpected disturbances. This paper focuses on integrated train timetabling rolling stock rescheduling for a disturbed metro system to reduce the negative impact. The problem formulated as a multi-objective master model, in which required operational constraints and dispatching strategies are taken into account. To satisfy the real-time requirement, an innovative solution framework consisting of an independent rescheduling process and a cooperative rescheduling process is proposed. the independent rescheduling process, the master model is decomposed into a series of submodels in the of train service. The submodel can be transformed into a Markov Decision Process (MDP) with well-defined fundamental elements (i.e., state, action, and reward function). Based on the MDP, a hierarchical policy developed by introducing deep reinforcement learning to generate the initial solution, including the lower policy for train timetable and the higher-level policy for flexible rolling stock circulation. In the cooperative rescheduling process, the selfishness of agents that appears after the model decomposition is overcome adaptive large neighborhood search algorithm, which can improve the solution quality. Finally, two numerical experiments are conducted to demonstrate the performance of the proposed solution framework. The experimental results show that a near-optimal solution can be obtained in a short time, which is than the currently used practical rules in the automatic train supervision system, especially during peak Furthermore, the effects of different parameter settings are analyzed
Er tong xiao chuan biao xing de yi chuan he huan jing jue ding yin su
No full textTang, Man Fung.Thesis Ph.D. Chinese University of Hong Kong 2016.Includes bibliographical references.Abstracts also in Chinese.Title from PDF title page (viewed on 07, November, 2016).Tang, Man Fung
An analysis of the mode of action of carbachol on the chick biventer cervicis nerve--muscle preparation.
No full textA data-driven mixed-integer linear programming approach for real-time rescheduling of urban rail transit under rolling stock faults
No full textUrban rail transit operations are susceptible to unexpected disturbances or disruptions, with rolling stock faults being a particularly common cause. Therefore, this paper focuses on the integrated rescheduling of the train timetable and rolling stock circulation in an urban rail transit line under rolling stock faults. Three typical scenarios arising from such faults are studied simultaneously, i.e., delay, out-of-service, and rescue. Taking general key practical constraints and scenario-specific constraints into account, multi-objective mathematical models are formulated for each scenario to optimize various dispatching measures, such as retiming, cancellation, short-turning, and backup rolling stock utilization. For computational tractability, the proposed models are transformed into equivalent mixed-integer linear programming (MILP) reformulations using some linearization techniques. In order to satisfy the real-time requirements of train rescheduling, a data-driven approach is developed to accelerate the solving process by fixing some decision variables in advance. Specifically, the prediction of binary variable values is treated as a classification task. After creating a dataset including different rolling stock faults and their respective optimal solutions generated by GUROBI, the correlations between optimal solutions and instance features are extracted through supervised learning based on the multilayer perceptron. By generalizing the extracted correlations to unseen instances, high-quality solutions can be found in a short time. Finally, numerical experiments are carried out based on the Beijing Yizhuang Metro Line. Compared to directly solving the original model using GUROBI, the proposed solution approach can reduce the average computation time by up to 91.49% with an average optimality gap of only 0.77%
Cooperative train control during the power supply shortage in metro system: A multi-agent reinforcement learning approach
No full textIn metro system, the fault of traction power supply system may cause the power supply shortage around the failure substation. In this case, the dispatching measure should be immediately taken to reduce the impacts of disruption on the train operation. To deal with this real-time traffic management problem, a cooperative control approach is proposed in this paper. In this approach, the time to apply tractive force and the level of force are simultaneously adjusted for all the operated trains, to maximize the maintained line capacity when considering the power supply capacity. Compared with the existing train timetable rescheduling approach, cooperative control is more flexible to get a better train regulation solution. To solve the challenges for developing the cooperative control model (i.e., undetermined number and dynamically changing of controlled objects), an imaginary section method is newly developed to transform the original problem into an equivalent cooperative control problem with fixed controlled objects. Then, the mathematical models for the transformed problem are constructed by using the space–time–speed network methodology. According to the formulated model, a Decentralized-Markov Decision Process (Dec-MDP) framework is designed as the basis of the applied algorithm. Next, a Collaboration Mechanism Based-Independent Deep Q-Network (CMB-IDQN) algorithm is proposed to solve the cooperative control problem. Compared with classical IDQN algorithm, a credit assignment method based on the collaboration mechanism among trains is novelly considered in the designed multi-agent reinforcement learning algorithm. Finally, the effectiveness of the proposed cooperative control approach is verified by two case studies. When solving the cooperative control problem, the performance by using CMB-IDQN algorithm can be increased by up to 13.0% and 16.8% compared with other two classical reinforcement learning algorithms (i.e., DQN and IDQN), respectively. Compared with two train timetable rescheduling measures during the power supply shortage, the cooperative control approach can improve the solution quality by more than 180.4% and 17.4%, respectively
Mysteries of the Tang dynasty
No full textMysteries of the Tang Dynasty is an interactive pop-up book, accompanied by a collaborative craft activity, for children aged between 3 and 9. It aims to make learning Chinese history more fun and appealing, given the “boring” reputation of history as a subject, thus increasing the accessibility to such information for this young audience. Through engaging with the contents of this book with family and friends, children will able to glean new knowledge about Chinese history, while also having their curiosity and interest about this topic piqued.Bachelor of Fine Arts in Design Ar
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