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Towards engineering a portable platform for laparoscopic pre-training in virtual reality with haptic feedback

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虚拟现实与智能硬件（中英文） 2024年第2期6卷 83-99页

作者： Hans-Georg ENKLER Wolfgang KUNERT Stefan PFEFFER Kai-Jonas BOCK Steffen AXT Jonas JOHANNINK Christoph REICH Furtwangen University 78120 FurtwangenGermany University Hospital and Faculty of Medicine Tuebingen 72076 TuebingenGermany

Background Laparoscopic surgery is a surgical technique in which special instruments are inserted through small incision holes inside the body.For some time,efforts have been made to improve surgical pre training through practical exercises on abstracted and reduced models.Methods The authors strive for a portable,easy to use and cost-effective Virtual Reality-based(VR)laparoscopic pre-training platform and therefore address the question of how such a system has to be designed to achieve the quality of today's gold standard using real tissue specimens.Current VR controllers are limited regarding haptic feedback.Since haptic feedback is necessary or at least beneficial for laparoscopic surgery training,the platform to be developed consists of a newly designed prototype laparoscopic VR controller with haptic feedback,a commercially available head-mounted display,a VR environment for simulating a laparoscopic surgery,and a training concept.Results To take full advantage of benefits such as repeatability and cost-effectiveness of VR-based training,the system shall not require a tissue sample for haptic feedback.It is currently calculated and visually displayed to the user in the VR environment.On the prototype controller,a first axis was provided with perceptible feedback for test purposes.Two of the prototype VR controllers can be combined to simulate a typical both-handed use case,e.g.,laparoscopic suturing.A Unity based VR prototype allows the execution of simple standard pre-trainings.Conclusions The first prototype enables full operation of a virtual laparoscopic instrument in VR.In addition,the simulation can compute simple interaction forces.Major challenges lie in a realistic real-time tissue simulation and calculation of forces for the haptic feedback.Mechanical weaknesses were identified in the first hardware prototype,which will be improved in subsequent versions.All degrees of freedom of the controller are to be provided with haptic feedback.To make forces tangible in the simulation,characteristic values

关键词： Laparoscopic surgery training Virtual reality Controller Haptic feedback Kinesthetic skills

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training Train Drivers

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ChinAfrica 2024年第2期16卷 36-37页

作者： DERRICK SILIMINA 不详

As the train engine roars,doors of the wagons gently open at 07:30 a.m.,with crew members waiting for the passengers to board before starting the journey for their next destination.An hour before the departure,Marriam... 详细信息

关键词： starting destination training

Design and Development of Small Modular Courses for“Education-training Integration”in Vocational Colleges:A Case Study

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Journal of Contemporary Educational Research 2024年第4期8卷 10-15页

作者： Zhixin Feng Meiqin Liang School of Automotive Engineering Beijing PolytechnicBeijing 100176China College of Automation Engineering Beijing PolytechnicBeijing 100176China

Vocational education plays a vital role in the development of skilled technical professionals and the advancement of the economy.However,the emphasis on campus education often neglects the importance of external training,hindering the overall development of vocational education.This study aims to address this issue by exploring the design and development of small modular courses that integrate training and education in vocational colleges,focusing on the mechanics course as a case study.The research methods employed in this study include an in-depth analysis of enterprise training needs,the development of digital teaching resources utilizing the finite element method(FEM),and the implementation of a small modular course integrating education and training.The data analysis reveals positive outcomes in terms of learners’comprehension and engagement with complex mechanics formulas through the use of stress nephograms and other digital resources.This research provides a new perspective on curriculum design and offers insights into the integration of training and education in vocational colleges.The findings underscore the significance of incorporating innovative teaching methodologies and digital resources in enhancing the quality and relevance of vocational education,ultimately contributing to the cultivation of skilled professionals and the growth of the vocational education sector.

关键词： Education-training integration Small modular courses Vocational colleges training Finite element method

Innovation and Practice of training Mode for Professional Postgraduates of Acupuncture and Tuina Based on Artificial Intelligence

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Asian Agricultural Research 2024年第3期16卷 46-48页

作者： Mingjun LIU Xiaochao GANG Zhengri CONG Junhao HU Jianfeng LIANG Chongwen ZHONG Xinyi YUAN Bing DAI Yuzhe ZHANG Lijie LI Tianyi MU Yiran HAN Chaochao HUA College of Acupuncture and Tuina Changchun University of Chinese MedicineChangchun 130117China The Third Affiliated Hospital of Changchun University of Chinese Medicine Changchun 130117China College of Special Education Changchun UniversityChangchun 130022China Department of Orthopaedics Pingyang BranchChangchun Hospital of Traditional Chinese MedicineChangchun 130000China

In view of the common problems of integrating artificial intelligence into the training of postgraduates in Acupuncture and Tuina major,this paper reviews the related research progress both at home and abroad.It puts forward the innovative reform paths for integrating artificial intelligence into postgraduate training mode of Acupuncture and Tuina major:construct the teaching staff of artificial intelligence graduate students;innovating artificial intelligence to promote the integration of classics and scientific research;constructing the ideological and political case base of artificial intelligence courses;implementing artificial intelligence platform blended teaching;building a domestic and foreign exchange platform for artificial intelligence.Through practical research in teaching,it has achieved good teaching results and played a good demonstration,leading and radiation role in similar majors in China.

关键词： Artificial intelligence (AI) Acupuncture and Tuina major Professional postgraduates training mode

Immune consequences of exercise in hypoxia:A narrative review

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Journal of Sport and Health Science 2024年第3期13卷 297-310,I0002页

作者： Johannes Burtscher Qadar Pasha Neha Chanana Gregoire P.Millet Martin Burtscher Barbara Strasser Institute of Sport Sciences University of LausanneLausanne 1015Switzerland Institute of Hypoxia Research New Delhi 110067India Department of Biochemistry Jamia HamdardNew Delhi 110062India Department of Sport Science University of InnsbruckInnsbruck 6020Austria Faculty of Medicine Sigmund Freud Private UniversityVienna 1020Austria Ludwig Boltzmann Institute for Rehabilitation Research Vienna 1100Austria

Immune outcomes are key mediators of many health benefits of exercise and are determined by exercise type,dose(frequency/duration,intensity),and individual characteristics.Similarly,reduced availability of ambient oxygen(hypoxia)modulates immune functions depending on the hypoxic dose and the individual capacity to respond to hypoxia.How combined exercise and hypoxia(e.g.,high-altitude training)sculpts immune responses is not well understood,although such combinations are becoming increasingly popular.Therefore,in this paper,we summarize the impact on immune responses of exercise and of hypoxia,both independently and together,with a focus on specialized cells in the innate and adaptive immune system.We review the regulation of the immune system by tissue oxygen levels and the overlapping and distinct immune responses related to exercise and hypoxia,then we discuss how they may be modulated by nutritional strategies.Mitochondrial,antioxidant,and anti-inflammatory mechanisms underlie many of the adaptations that can lead to improved cellular metabolism,resilience,and overall immune functions by regulating the survival,differentiation,activation,and migration of immune cells.This review shows that exercise and hypoxia can impair or complement/synergize with each other while regulating immune system functions.Appropriate acclimatization,training,and nutritional strategies can be used to avoid risks and tap into the synergistic potentials of the poorly studied immune consequences of exercising in a hypoxic state.

关键词： Altitude Exercise Hypoxia Immune response training

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The anti-inflammatory effects of exercise on autoimmune diseases:A 20-year systematic review

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Journal of Sport and Health Science 2024年第3期13卷 353-367,I0001页

作者： Beibei Luo Dao Xiang Xiaorong Ji Xuan Chen Rui Li Shuxin Zhang Yujun Meng David C.Nieman Peijie Chen School of Exercise and Health Shanghai University of SportShanghai 200438China Shanghai Key Laboratory of Human Performance Shanghai University of SportShanghai 200438China Department of Diving and Hyperbaric Medicine Naval Medical CenterShanghai 200433China National Key Laboratory of Immunity and Inflammation Naval Medical UniversityShanghai 200433China Human Performance Laboratory Appalachian State UniversityNorth Carolina Research CampusKannapolisNC 28081USA Research Institute for Doping Control Shanghai University of SportShanghai 200438China

Background:The anti-inflammatory effect of exercise may be an underlying factor in improving several autoimmune diseases.The aim of this systematic review was to examine the evidence on the role of exercise training in mitigating inflammation in adolescents and adults with autoimmune disease.Methods:PubMed,Web of Science,and Embase databases were systematically reviewed for related studies published between January 1,2003,and August 31,2023.All randomized and non-randomized controlled trials of exercise interventions with autoimmune disease study participants that evaluated inflammation-related biomarkers were included.The quality of evidence was assessed using the Tool for the assEssment of Study qualiTy and reporting in EXercise scale and Cochrane bias risk tool.Results:A total of 14,565 records were identified.After screening the titles,abstracts,and full texts,87 were eligible for the systematic review.These studies were conducted in 25 different countries and included a total of 2779 participants(patients with autoimmune disease,in exercise or control groups).Overall,the evidence suggests that inflammation-related markers such as C-reactive protein,interleukin 6,and tumor necrosis factor a were reduced by regular exercise interventions.Regular exercise interventions combined with multiple exercise modes were associated with greater benefits.Conclusion:Regular exercise training by patients with autoimmune disease exerts an anti-inflammatory influence.This systematic review provides support for the promotion and development of clinical exercise intervention programs for patients with autoimmune disease.Most patients with autoimmune disease can safely adopt moderate exercise training protocols,but changes in inflammation biomarkers will be modest at best.Acute exercise interventions are ineffective or even modestly but transiently pro-inflammatory.

关键词： Autoimmune diseases Cytokines Inflammation Physical activity training

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Non-intrusive Load Monitoring Based on Graph Total Variation for Residential Appliances

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Journal of Modern Power Systems and Clean Energy 2024年第3期12卷 947-957页

作者： Xiaoyang Ma Diwen Zheng Xiaoyong Deng Ying Wang Dawei Deng Wei Li the College of Electrical Engineering Sichuan University State Grid Chongqing Electric Power Company State Grid Sichuan Electric Power Company State Grid Hubei Electric Power Company Limited Research Institute

Non-intrusive load monitoring is a technique for monitoring the operating conditions of electrical appliances by collecting the aggregated electrical information at the household power inlet. Despite several studies on the mining of unique load characteristics, few studies have extensively considered the high computational burden and sample training. Based on lowfrequency sampling data, a non-intrusive load monitoring algorithm utilizing the graph total variation(GTV) is proposed in this study. The algorithm can effectively depict the load state without the need for prior training. First, the combined Kmeans clustering algorithm and graph signals are used to build concise and accurate graph structures as load models. The GTV representing the internal structure of the graph signal is introduced as the optimization model and solved using the augmented Lagrangian iterative algorithm. The introduction of the difference operator reduces the computing cost and addresses the inaccurate reconstruction of the graph signal. With low-frequency sampling data, the algorithm only requires a little prior data and no training, thereby reducing the computing cost. Experiments conducted using the reference energy disaggregation dataset and almanac of minutely power dataset demonstrated the stable superiority of the algorithm and its low computational burden.

关键词： Load monitoring Costs Home appliances Hidden Markov models training Kernel Clustering algorithms

SWG: an architecture for sparse weight gradient computation

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Science China(Information Sciences) 2024年第2期67卷 302-321页

作者： Weiwei WU Fengbin TU Xiangyu LI Shaojun WEI Shouyi YIN School of Integrated Circuits Tsinghua University Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology

On-device training for deep neural networks(DNN) has become a trend due to various user preferences and scenarios. The DNN training process consists of three phases, feedforward(FF), backpropagation(BP), and weight gradient(WG) update. WG takes about one-third of the computation in the whole training process. Current training accelerators usually ignore the special computation property of WG and process it in a way similar to FF/BP. Besides, the extensive data sparsity existing in WG, which brings opportunities to save computation, is not well explored. Nevertheless, exploiting the optimization opportunities would meet three underutilization problems, which are caused by(1) the mismatch between WG data dimensions and hardware parallelism,(2) the full sparsity, i.e., the sparsity of feature map(Fmap),error map(Emap), and gradient, and(3) the workload imbalance resulting from irregular sparsity. In this paper, we propose a specific architecture for sparse weight gradient(SWG) computation. The architecture is designed based on hierarchical unrolling and sparsity-aware(HUSA) dataflow to exploit the optimization opportunities of the special computation property and full data sparsity. In HUSA dataflow, the data dimensions are unrolled hierarchically on the hardware architecture. A valid-data trace(VDT) mechanism is embedded in the dataflow to avoid the underutilization caused by the two-sided input sparsity. The gradient is unrolled in PE to alleviate the underutilization induced by output sparsity while maintaining the data reuse opportunities. Besides, we design an intra-and inter-column balancer(IIBLC) to dynamically tackle the workload imbalance problem resulting from the irregular sparsity. Experimental results show that with HUSA dataflow exploiting the full sparsity, SWG achieves a speedup of 12.23× over state-of-the-art gradient computation architecture, Train Ware. SWG helps to improve the energy efficiency of the state-of-the-art training accelerator LNPU from 7.56 to 10.58 TOPS/W.

关键词： CNN training gradient computation sparsity architecture

Improved Proximal Policy Optimization Algorithm for Sequential Security-constrained Optimal Power Flow Based on Expert Knowledge and Safety Layer

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Journal of Modern Power Systems and Clean Energy 2024年第3期12卷 742-753页

作者： Yanbo Chen Qintao Du Honghai Liu Liangcheng Cheng Muhammad Shahzad Younis State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources and School of Electrical & Electronic Engineering North China Electric Power University School of Engineering Xining University Key Laboratory of Smart Operation of New Energy Power System Ministry of Education Qinghai University China Electric Power Research Institute National University of Sciences and Technology

In recent years, reinforcement learning(RL) has emerged as a solution for model-free dynamic programming problem that cannot be effectively solved by traditional optimization methods. It has gradually been applied in the fields such as economic dispatch of power systems due to its strong selflearning and self-optimizing capabilities. However, existing economic scheduling methods based on RL ignore security risks that the agent may bring during exploration, which poses a risk of issuing instructions that threaten the safe operation of power system. Therefore, we propose an improved proximal policy optimization algorithm for sequential security-constrained optimal power flow(SCOPF) based on expert knowledge and safety layer to determine active power dispatch strategy, voltage optimization scheme of the units, and charging/discharging dispatch of energy storage systems. The expert experience is introduced to improve the ability to enforce constraints such as power balance in training process while guiding agent to effectively improve the utilization rate of renewable energy. Additionally, to avoid line overload, we add a safety layer at the end of the policy network by introducing transmission constraints to avoid dangerous actions and tackle sequential SCOPF problem. Simulation results on an improved IEEE 118-bus system verify the effectiveness of the proposed algorithm.

关键词： Renewable energy sources Safety Power systems Optimization Power grids Energy storage training