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Haptic display for virtual reality: progress and challenges

Virtual Reality & Intelligent Hardware 2019年第2期1卷 136-162页

作者： Dangxiao WANG Yuan GUO Shiyi LIU Yuru ZHANG Weiliang XU Jing XIAO State Key Laboratory of Virtual Reality Technology and Systems Beihang UniversityBeijing 100083China Beijing Advanced Innovation Center for Biomedical Engineering Beihang UniversityBeijing 100083China Peng Cheng Laboratory Shenzhen 518055China Department of Mechanical Engineering University of AucklandAuckland 1142New Zealand School of Computer Science and the Robotics Engineering Program Worcester Polytechnic InstituteWorcesterMA 01609-2280USA

Immersion, interaction, and imagination are three features of virtual reality (VR). Existing VR systems possess fairly realistic visual and auditory feedbacks, and however, are poor with haptic feedback, by means of which human can perceive the physical world via abundant haptic properties. Haptic display is an interface aiming to enable bilateral signal communications between human and computer, and thus to greatly enhance the immersion and interaction of VR systems. This paper surveys the paradigm shift of haptic display occurred in the past 30 years, which is classified into three stages, including desktop haptics, surface haptics, and wearable haptics. The driving forces, key technologies and typical applications in each stage are critically reviewed. Toward the future high-fidelity VR interaction, research challenges are highlighted concerning handheld haptic device, multimodal haptic device, and high fidelity haptic rendering. In the end, the importance of understanding human haptic perception for designing effective haptic devices is addressed.

关键词： Haptic display Virtual reality Desktop haptics Surface haptics Wearable haptics Multimodal haptics

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Numerical Investigation Against Laboratory Experiment: An Overview of Damage and Wind Loads on Structural Design

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Procedia Structural Integrity 2020年 27卷 6-13页

作者： Aldias Bahatmaka Dong-Joon Kim Aditya Rio Prabowo Daewoo Shipbuilding and Marine Engineering (DSME).Co.Ltd Okpo 53305 South Korea Interdisciplinary Program of Marine Design Convergence Pukyong National University Busan 48513 South Korea Department of Naval Architecture and Marine Systems Engineering Pukyong National University Busan 48513 South Korea Department of Mechanical Engineering Universitas Sebelas Maret Surakarta 57126 Indonesia

The numerical approach is being used against experimental and solves engineering problems. In the engineering design, the structural and load analysis are a part of an important thing to show the effect of geometrical or the structure design. The main purpose is to review the influence of deckhouse height on the flow around the funnel and aft ship structure. In this review study, the fluid-structure and 3D steady RANS CFD are used to validate the result of simulations. Several aspects of the numerical approach, such as turbulence modeling, boundary conditions, inlet velocity, and pressure outlet to simulate wind load in CFD, ground surface roughness, and quantification of wind loads by computational fluid-structure and computational fluid dynamics (CFD) are summarized. A benchmarking study of the numerical approach against the experiment is emphasized. A comparative study among the numerical prediction on the wind tunnel demonstrated good agreement and satisfaction. Moreover, by numerical approach could handle the accurate results and show how the response to the ship structure that makes the dynamic interaction during wind loads events.

关键词： Fluid Structure Wind Loads Numerical Approach CFD Experimental

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First and second law analyses of wastewater cooled condenser for a refrigeration system

First and second law analyses of wastewater cooled condenser...

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作者： Karacayli, Ibrahim Altay, Lutfiye Hepbasli, Arif Air Conditioning and Refrigeration Technology Program Ege High Vocational School Ege University Bornova Izmir35100 Turkey Department of Mechanical Engineering Faculty of Engineering Ege University Bornova Izmir35100 Turkey Department of Energy Systems Engineering Faculty of Engineering Yaşar University Bornova Izmir35100 Turkey

In this study, a vapour compression refrigeration (VCR) system with a wastewater (WW) cooled condenser at a temperature range of 27-29°C was designed. The cooling capacity of the system using R134a as the refrigerant was 1.09 kW. The condenser consisted of a coaxial heat exchanger with a capacity of 1 kW. This paper dealt with energy and exergy analyses of the VCR system using WW, as a heat sink. Experiments were performed in order to evaluate the energetic and exergetic performances of the wastewater-cooled condenser (WWC) and the overall system. The convective heat transfer coefficient of WW and refrigerant in the condenser, overall heat transfer coefficient of the WWC, total amount of heat removed by WW, amount of cooling effect, coefficient of performance (COP), exergy destruction rate, and second law efficiencies of the WWC and VCR system were calculated under different WW temperatures and flowrates. Increasing volumetric flowrate of WW from 200 L/h to 400 L/h caused 4.4% improvement in COP, 12.0% reduction in exergy destruction, and 10.3% increase in exergy efficiency. © 2019 Inderscience Enterprises Ltd.

关键词： Exergy

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Vehicle scrappage policies for transportation decarbonization

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Environmental Research: Energy 2024年第3期1卷 033002-033002页

作者： Maxwell Woody Samuel Stolper Parth Vaishnav Gregory A Keoleian Center for Sustainable Systems School for Environment and Sustainability University of Michigan Ann Arbor MI United States of America Department of Mechanical Engineering College of Engineering University of Michigan Ann Arbor MI United States of America Science Technology and Public Policy Program Ford School of Public Policy University of Michigan Ann Arbor MI United States of America School for Environment and Sustainability University of Michigan Ann Arbor MI United States of America

Vehicle electrification is one of the primary strategies being pursued for the decarbonization of the transportation sector. But to meet emissions reduction goals for that sector, the current vehicle replacement rate is insufficient. Vehicle scrappage policies can accelerate fleet turnover by providing an incentive to retire a vehicle before its natural end of life and simultaneously replace it with a more efficient or less polluting alternative. Previous scrappage programs, like the United States' Cash for Clunkers, have had limited success as decarbonization policies; however, most of these programs ended before the widespread availability of electric vehicles and did not have decarbonization as a primary policy goal. Here we explain why scrappage policies may be necessary to meet climate goals, review historic vehicle scrappage policies from a variety of countries, highlight the successes and failures of those policies, and establish policy design considerations that could help ensure that future scrappage programs are more successful than previous efforts.

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Moderating effects of out-of-hospital cardiac arrest characteristics on the association between EMS response time and survival

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Resuscitation 2021年第0期169卷 31-38页

作者： Stoesser, Clara E. Boutilier, Justin J. Sun, Christopher L.F. Brooks, Steven C. Cheskes, Sheldon Dainty, Katie N. Feldman, Michael Ko, Dennis T. Lin, Steve Morrison, Laurie J. Scales, Damon C. Chan, Timothy C.Y. Departmentof Mechanical and Industrial Engineering University of Toronto Toronto ON Canada Departmentof Industrial and Systems Engineering University of Wisconsin – Madison Madison WI United States SloanSchool of Management Massachusetts Institute of Technology Cambridge MA United States LiKa Shing Knowledge Institute St. Michael's Hospital Unity Health Toronto Toronto ON Canada Departmentsof Emergency Medicine and Public Health Sciences Queen's University Kingston ON Canada Departmentof Family and Community Medicine Division of Emergency Medicine University of Toronto Toronto ON Canada SunnybrookCenter for Prehospital Medicine Toronto ON Canada Instituteof Health Policy Management and Evaluation (IHPME) University of Toronto Toronto ON Canada NorthYork General Hospital Toronto ON Canada Institutefor Clinical Evaluation Sciences Toronto ON Canada SchulichHeart Program Sunnybrook Health Sciences Centre Toronto ON Canada Departmentof Medicine University of Toronto Toronto ON Canada Interdepartmental Division of Critical Care Medicine University of Toronto Toronto ON Canada HealthcareSystems Engineering Massachusetts General Hospital Boston MA United States

Background: Although several Utstein variables are known to independently improve survival, how they moderate the effect of emergency medical service (EMS) response times on survival is unknown. Objectives: To quantify how public location, witnessed status, bystander CPR, and bystander AED shock individually and jointly moderate the effect of EMS response time delays on OHCA survival. Methods: This retrospective cohort study was a secondary analysis of the Resuscitation Outcomes Consortium Epistry-Cardiac Arrest database (December 2005 to June 2015). We included all adult, non-traumatic, non-EMS witnessed, and EMS-treated OHCAs from eleven sites across the US and Canada. We trained a logistic regression model with standard Utstein control variables and interaction terms between EMS response time and the four aforementioned OHCA characteristics. Results: 102,216 patients were included. Three of the four characteristics – witnessed OHCAs (OR = 0.962), bystander CPR (OR = 0.968) and public location (OR = 0.980) – increased the negative effect of a one-minute delay on the odds of survival. In contrast, a bystander AED shock decreased the negative effect of a one-minute response time delay on the odds of survival (OR = 1.064). The magnitude of the effect of a one-minute delay in EMS response time on the odds of survival ranged from 1.3% to 9.8% (average: 5.3%), depending on the underlying OHCA characteristics. Conclusions: Delays in EMS response time had the largest reduction in survival odds for OHCAs that did not receive a bystander AED shock but were witnessed, occurred in public, and/or received bystander CPR. A bystander AED shock appears to be protective against a delay in EMS response time. © 2021 Elsevier B.V.

关键词： Emergency medical services Out-of-hospital cardiac arrest Public health Response time

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Multi-step ahead Bitcoin Price Forecasting Based on VMD and Ensemble Learning Methods

Multi-step ahead Bitcoin Price Forecasting Based on VMD and ...

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International Joint Conference on Neural Networks (IJCNN)

作者： Ramon Gomes da Silva Matheus Henrique Dal Molin Ribeiro Naylene Fraccanabbia Viviana Cocco Mariani Leandro dos Santos Coelho Industrial & Systems Engineering Graduate Program (PPGEPS) Pontifical Catholic University of Parana (PUCPR) Curitiba Parana Brazil Department of Mathematics Federal Technological University of Parana (UTFPR) Pato Branco Parana Brazil Mechanical Engineering Graduate Program (PPGEM) Pontifical Catholic University of Parana (PUCPR) Curitiba Parana Brazil Department of Electrical Engineering Federal University of Parana (UFPR) Curitiba Parana Brazil

ISBN: (数字)9781728169262

ISBN: (纸本)9781728169279

Bitcoin is the leading currency in the cryptocurrency market capturing attention worldwide. Forecasting the Bitcoin price as accurate as possible is essential, but due to its high volatility this task is challenging. Many researchers try, through the years, to develop efficient models for predicting the Bitcoin price using several different data-driven approaches. The objective of this paper is to develop a novel decomposition-ensemble learning model that combines Variational Mode Decomposition (VMD) and Stacking-ensemble learning (STACK) with machine learning algorithms to forecast the Bitcoin price multi-step ahead. The algorithms are k-Nearest Neighbors, Support Vector Regression with Linear kernel, Feed-forward Artificial Neural Network with single-layer perceptron, Generalized Linear Model, and Cubist. Correlation matrix (CORR), principal component analysis (PCA), and Box-Cox transformation (BOXCOX) were used as data preprocessing techniques. Estimating the performance of the proposed models (namely VMD-STACK-CORR, VMD-STACK-PCA, and VMD-STACK-BOXCOX) using relative root mean square error, symmetric mean absolute percentage error, and absolute percentage error measures, defined that for one-day-ahead forecast VMD-STAK-BOXCOX model presented the better performance, and for two and three-days-ahead forecast VMD-STACK-CORR model was chosen, compared to VMD, STACK, and machine learning algorithms models' performance. Diebold-Mariano statistical test was conducted to evaluate a reduction in forecasting errors. Therefore, the proposed models (VMD-STACK-CORR, VMD-STACK-PCA, and VMD-STACK-BOXCOX) indeed forecast accurately Bitcoin price and outperformed the compared models (VMD, STACK, and machine learning models).

关键词： Predictive models Biological system modeling Data models Bitcoin Training Machine learning algorithms

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Analyzing the Implications of New Technologies to the Management of Operations – Protocol Proposal and Application Illustration

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Procedia Manufacturing 2019年 39卷 904-912页

作者： Paulo Henrique Brunheroto Cassiano Souza Beller Fernando Deschamps Manufacturing Engineering Graduate Program Department of Mechanical Engineering Federal University of Parana Curitiba PR Brazil Industrial and Systems Engineering Graduate Program Polytechnic School Pontifícia Universidade Católica do Paraná Curitiba PR Brazil

The increasing adoption of new automation and information technologies are transforming production systems into cyber-physical systems (CPS). Although consulting companies have developed management frameworks to better characterize the implications of these technologies to how operations are managed, mainly focusing on new business models, efficiency, and effectiveness, the real impacts on decision areas (e.g., quality management) and performance objectives (e.g., flexibility) are still unclear. How are management systems being transformed? Are new managerial approaches emerging that address the particularities of new technologies? What are the critical success factors for conducting this transformation? To address these questions, a more systematic approach needs to be undertaken. This paper contributes to this by presenting a protocol to be used in systematic studies of the implications of the adoption of new technologies to the management of operations, and by illustrating its application to the analysis of the adoption of a cognitive vision system in an automotive manufacturer primarily deployed for improving product quality. The analysis protocol is based on Pettigrew’s dimensions of context, content, and process for change initiatives and is further subdivided into information requirements, variables to be analyzed and its potential sources of data. The case shows that the application of the protocol was able to reveal that besides expected effects on quality and productivity, new forms of interaction among workers and between workers and supervisors emerged that need further investigation. From the results of the case, future applications of the protocol are discussed.

关键词： management of operations transformation quality management cognitive vision system

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Multi-attribute optimization of sustainable aviation fuel production-process from microalgae source

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Fuel 2022年第PartC期324卷

作者： Said, Zafar Nguyen, Tuan Hai Sharma, Prabhakar Li, Changhe Ali, Hafiz Muhammad Nguyen, Van Nhanh Pham, Van Viet Ahmed, Shams Forruque Van, Dong Nguyen Truong, Thanh Hai Department of Sustainable and Renewable Energy Engineering University of Sharjah P. O. Box 27272 Sharjah United Arab Emirates U.S.-Pakistan Center for Advanced Studies in Energy (USPCAS-E) National University of Sciences and Technology (NUST) Islamabad Pakistan Faculty of Technology Dong Nai Technology University Dong Nai 76000 Viet Nam Mechanical Engineering Department Delhi Skill and Entrepreneurship University Delhi 110089 India School of Mechanical and Automotive Engineering Qingdao University of Technology Qingdao 266520 China Mechanical Engineering Department King Fahd University of Petroleum & Minerals Dhahran 31261 Saudi Arabia Interdisciplinary Research Center for Renewable Energy and Power Systems (IRC-REPS) King Fahd University of Petroleum and Minerals Dhahran 31261 Saudi Arabia Institute of Engineering HUTECH University Ho Chi Minh City Viet Nam Faculty of Marine Engineering Vietnam Maritime University Haiphong Viet Nam Science and Math Program Asian University for Women Chattogram 4000 Bangladesh University of Science and Technology The University of Danang Viet Nam PATET Research Group Ho Chi Minh City University of Transport Ho Chi Minh City Viet Nam

The aviation sector has been one of the most significant contributors to greenhouse gas (GHG) emissions;there is an urgent need to transition from traditional fossil-based jet fuel to sustainable aviation fuel to meet net-zero targets by 2030. The use of renewable aviation fuel may be regarded as the most effective option for reducing GHG emissions in the aviation sector while allowing for long-term growth. In this study, the microalgae oil was transformed to develop hydrocarbons with the boiling point range of jet fuel. Following the transesterification of algal oil fatty acids to algal oil methyl ester, fractional distillation was carried out. The Box-Behnken technique was used to design experiments for efficient resource utilization by minimizing the number of tests during transesterification. The quantitative relationship function between input (molar ratio of methanol to oil, catalyst concentration, and temperature) and % yield of methyl ester as an output of the process was developed using analysis of variance (ANOVA). The ANFIS (adaptive neuro-fuzzy inference system) was utilized to develop a prognostic model with good prediction effectiveness. MORSM (multi-objective response surface methodology) was also used to build a prediction model using correlations. A set of statistical indicators and Theil's U2 were used to examine the prediction efficacy and model uncertainty of ANFIS and MORSM. On both statistical indices and Theil's U2, the ANFIS-based model outperformed. To get the best results, the desirability approach was used to improve operating parameters. According to the desirability approach, the best operating parameters were catalyst concentration at 2.09%, methanol to oil ratio at 9.17%, and temperature at 60.49 °C, which resulted in the greatest yield of 91%. © 2022 Elsevier Ltd

关键词： Alternative fuel Jet fuel Microalgae Optimization Sustainable aviation fuel

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Dynamic Multi-criteria Classifier Selection for Illegal Tapping Detection in Oil Pipelines

Dynamic Multi-criteria Classifier Selection for Illegal Tapp...

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International Joint Conference on Neural Networks (IJCNN)

作者： Victor Henrique Alves Ribeiro Pedro Henrique Domingues Paulo Rodrigo Cavalin Gilberto Reynoso-Meza Helon Vicente Hultmann Ayala Luís Fernando Alzuguir Azevedo Industrial and Systems Engineering Graduate Program Pontifícia Universidade Católica do Paraná Curitiba Brazil IBM Research Rio de Janeiro Brazil Department of Mechanical Engineering Pontifícia Universidade Católica do Rio de Janeiro Rio de Janeiro Brazil

ISBN: (数字)9781728169262

ISBN: (纸本)9781728169279

Illegal tapping of fuel pipelines has recently become one of the most relevant safety problems faced by the industry. Hundreds of illegal interventions have been reported around the world, causing a significant number of deaths, relevant impacts on the environment, and capital loss. Therefore, it is important to develop systems that are able to detect such scenarios at an early stage, enabling a fast counteract. To this end, machine learning algorithms can train models on available data for detecting future issues. Most recently, ensemble learning and dynamic classifier selection (DCS) techniques have been achieving promising results in supervised learning tasks. Such models are usually trained based on a single criterion. However, it is desirable to take into account both the number of false positives (FP) and false negatives (FN) for the illegal tapping detection task, since they are conflicting and both lead to financial losses and/or accidents. Therefore, this work proposes a novel DCS technique based on multiple criteria, namely overall local class-specific accuracy (OLCA), which employs multi-criteria decision making for dynamically selecting the best classifier for a new sample given the local true positive and negative ratios. A numerical experiment is conducted for assessing the generalization performance of the proposed method in an oil pipeline, with the goal of detecting illegal taping using pressure transient signals. Results show that OLCA is able to reduce the number of both FP and FN when dynamically selecting the classifiers of a baseline Random Forest ensemble.

关键词： Pipelines Leak detection Oils Decision making Feature extraction Biological system modeling Task analysis

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Interpretable Symbolic Regression for Data Science: Analysis of the 2022 Competition

arXiv

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arXiv 2023年

作者： de Franca, F.O. Virgolin, M. Kommenda, M. Majumder, M.S. Cranmer, M. Espada, G. Ingelse, L. Fonseca, A. Landajuela, M. Petersen, B. Glatt, R. Mundhenk, N. Lee, C.S. Hochhalter, J.D. Randall, D.L. Kamienny, P. Zhang, H. Dick, G. Simon, A. Burlacu, B. Kasak, Jaan Machado, Meera Wilstrup, Casper La Cava, W.G. Federal University of ABC Santo Andre Brazil Evolutionary Intelligence Group Centrum Wiskunde & Informatica Science Park 123 Amsterdam Netherlands Computational Health Informatics Program Boston Children's Hospital Harvard Medical School Boston United States University of Applied Sciences Upper Austria Hagenberg Austria Center for Computational Astrophysics Flatiron Institute Department of Astrophysical Sciences Princeton University United States LASIGE Faculdade de Ciências Universidade de Lisboa Lisboa Portugal Computational Engineering Division Lawrence Livermore National Laboratory Livermore United States University of Utah Department of Mechanical Engineering Utah United States Meta FAIR France Victoria University of Wellington School of Engineering and Computer Science New Zealand University of otago Department of Information Science New Zealand Institut für Angewandte Physik Universität Tübingen Max Planck Institute for Intelligent Systems Tübingen Germany Abzu AI Orient Plads 1 Nordhavn 2150 Denmark

Symbolic regression searches for analytic expressions that accurately describe studied phenomena. The main attraction of this approach is that it returns an interpretable model that can be insightful to users. Historically, the majority of algorithms for symbolic regression have been based on evolutionary algorithms. However, there has been a recent surge of new proposals that instead utilize approaches such as enumeration algorithms, mixed linear integer programming, neural networks, and Bayesian optimization. In order to assess how well these new approaches behave on a set of common challenges often faced in real-world data, we hosted a competition at the 2022 Genetic and Evolutionary Computation Conference consisting of different synthetic and real-world datasets which were blind to entrants. For the real-world track, we assessed interpretability in a realistic way by using a domain expert to judge the trustworthiness of candidate models. We present an in-depth analysis of the results obtained in this competition, discuss current challenges of symbolic regression algorithms and highlight possible improvements for future competitions. Copyright © 2023, The Authors. All rights reserved.

关键词： Machine learning

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