scholarly journals Rethinking Automotive Engineering Education – Deep Orange as a Collaborative Innovation Framework for Project-Based Learning Incorporating Real-World Case Studies

2020 ◽  
Author(s):  
Ala Qattawi ◽  
Paul Venhovens ◽  
Johnell Brooks
Keyword(s):  
Engineering Education ◽  
Case Studies ◽  
Real World ◽  
Project Based Learning ◽  
Automotive Engineering ◽  
Collaborative Innovation

Improving Mechanical Engineering Education Through Use of Case Studies

2009 ◽  
Author(s):  
Pramod Rajan ◽  
P. K. Raju ◽  
Chetan S. Sankar
Keyword(s):  
Decision Making ◽  
Engineering Education ◽  
Case Studies ◽  
Real World ◽  
Mechanical Engineering ◽  
Role Playing ◽  
Engineering Industry ◽  
Innovative Technology ◽  
Case Study Methodology

Business is increasingly conducted in a global environment, and mechanical engineering students are expected to be proficient in leadership skills as well as strong technical skills. Many authors state that instead of adding more material and more courses to the engineering curriculum, which would likely turn students away from engineering, engineering educators need to respond by opening up access to engineering with the larger world. We found that one of the effective ways of bringing real-world issues related to the areas of manufacturing and design, thermal engineering, acoustics, vibration, welding and nondestructive evaluation into classrooms is through the use of case study methodology. The Laboratory for Innovative Technology and Engineering Education (LITEE) at Auburn University has developed eighteen multimedia case studies over the past ten years. Faculty and students partnering with various industries develop these case studies. The case studies focus on real-world problems that actually occurred in the chosen industry. All the technical and business details related to the problem are provided in the case study. Through the use of information technologies we created multi-media case studies that bring real-world decision making from the engineering industry into the classrooms. The students analyze the problem in the class using role-playing, thereby simulating the decision-making scenario that occurred in the industry. The students also have an opportunity to compare their solutions to what happened in the industry. This paper describes the steps involved in developing a LITEE case study, administering this case study in engineering classrooms, and the results of evaluating the effectiveness of this method of instruction. This paper also discusses the details of different case studies related to the above-mentioned areas available through LITEE.

Project-based learning in a graduate course on home appliance engineering

2021 ◽  
pp. 002072092110134
Author(s):  
Yeon Kim ◽  
Suk Lee ◽  
Changsun Ahn
Keyword(s):  
Quantitative Analysis ◽  
Engineering Education ◽  
Graduate School ◽  
Creative Thinking ◽  
Thinking Skills ◽  
Project Based Learning ◽  
Learning Method ◽  
Graduate Course ◽  
Industrial Projects ◽  
Home Appliance

Project-based learning is one of the popular and promising approaches in engineering education. The current study reports on a curriculum that was designed and implemented by a graduate school to help students gain knowledge and creative thinking skills through collaboration between different majors during industrial projects in a graduate course on home appliance engineering. The students selected the topics, planned the project, conducted research, produced a prototype, and presented their results under the guidance of a group of advisors consisting of professors, technical advisors, and industry mentors. A quantitative analysis showed that this approach was effective in improving the students’ attitude toward engineering. Furthermore, a qualitative analysis showed that this learning method helped students learn how to communicate and present effectively, to flexibly approach projects, and to understand the practices of industrial research. Based on the findings, the current study discusses how the project-based learning helped students advance.

scholarly journals The core components of education 4.0 in higher education: Three case studies in engineering education

2021 ◽  
Vol 93 ◽  
pp. 107278
Author(s):  
Jhonattan Miranda ◽  
Christelle Navarrete ◽  
Julieta Noguez ◽  
José-Martin Molina-Espinosa ◽  
María-Soledad Ramírez-Montoya ◽  
...  
Keyword(s):  
Higher Education ◽  
Engineering Education ◽  
Case Studies ◽  
The Core ◽  
Core Components

scholarly journals Handrails through the Swamp? A Pilot to Test the Integration and Implementation Science Framework in Complex Real-World Research

2021 ◽  
Vol 13 (10) ◽  
pp. 5491
Author(s):  
Melissa Robson-Williams ◽  
Bruce Small ◽  
Roger Robson-Williams ◽  
Nick Kirk
Keyword(s):  
Pilot Study ◽  
Case Studies ◽  
Implementation Science ◽  
Real World ◽  
Environmental Problems ◽  
Environmental Research ◽  
Integrative Framework ◽  
The World ◽  
Science Framework ◽  
Real World Problems

The socio-environmental challenges the world faces are ‘swamps’: situations that are messy, complex, and uncertain. The aim of this paper is to help disciplinary scientists navigate these swamps. To achieve this, the paper evaluates an integrative framework designed for researching complex real-world problems, the Integration and Implementation Science (i2S) framework. As a pilot study, we examine seven inter and transdisciplinary agri-environmental case studies against the concepts presented in the i2S framework, and we hypothesise that considering concepts in the i2S framework during the planning and delivery of agri-environmental research will increase the usefulness of the research for next users. We found that for the types of complex, real-world research done in the case studies, increasing attention to the i2S dimensions correlated with increased usefulness for the end users. We conclude that using the i2S framework could provide handrails for researchers, to help them navigate the swamps when engaging with the complexity of socio-environmental problems.

Applying the Systems Evaluation Protocol in the real world: Six case studies

2021 ◽  
Vol 2021 (169) ◽  
pp. 65-77
Author(s):  
Jennifer Brown Urban ◽  
Miriam R. Linver ◽  
Lisa M. Chauveron ◽  
Thomas Archibald ◽  
Monica Hargraves ◽  
...  
Keyword(s):  
Case Studies ◽  
Real World ◽  
The Real ◽  
Evaluation Protocol

scholarly journals How to train your robot with deep reinforcement learning: lessons we have learned

2021 ◽  
pp. 027836492098785
Author(s):  
Julian Ibarz ◽  
Jie Tan ◽  
Chelsea Finn ◽  
Mrinal Kalakrishnan ◽  
Peter Pastor ◽  
...  
Keyword(s):  
Machine Learning ◽  
Reinforcement Learning ◽  
Case Studies ◽  
Real World ◽  
Review Article ◽  
The Real ◽  
Complex Skills ◽  
Real World Learning ◽  
Level Sensor ◽  
Embodied Agent

Deep reinforcement learning (RL) has emerged as a promising approach for autonomously acquiring complex behaviors from low-level sensor observations. Although a large portion of deep RL research has focused on applications in video games and simulated control, which does not connect with the constraints of learning in real environments, deep RL has also demonstrated promise in enabling physical robots to learn complex skills in the real world. At the same time, real-world robotics provides an appealing domain for evaluating such algorithms, as it connects directly to how humans learn: as an embodied agent in the real world. Learning to perceive and move in the real world presents numerous challenges, some of which are easier to address than others, and some of which are often not considered in RL research that focuses only on simulated domains. In this review article, we present a number of case studies involving robotic deep RL. Building off of these case studies, we discuss commonly perceived challenges in deep RL and how they have been addressed in these works. We also provide an overview of other outstanding challenges, many of which are unique to the real-world robotics setting and are not often the focus of mainstream RL research. Our goal is to provide a resource both for roboticists and machine learning researchers who are interested in furthering the progress of deep RL in the real world.

scholarly journals Exploiting Proximity-Based Mobile Apps for Large-Scale Location Privacy Probing

2018 ◽  
Vol 2018 ◽  
pp. 1-22 ◽  
Author(s):  
Shuang Zhao ◽  
Xiapu Luo ◽  
Xiaobo Ma ◽  
Bo Bai ◽  
Yankang Zhao ◽  
...  
Keyword(s):  
Social Networks ◽  
Case Studies ◽  
Real World ◽  
Emission Reduction ◽  
Large Scale ◽  
Location Privacy ◽  
Mobile Apps ◽  
Physical World ◽  
Typical Type ◽  
Location Spoofing

Proximity-based apps have been changing the way people interact with each other in the physical world. To help people extend their social networks, proximity-based nearby-stranger (NS) apps that encourage people to make friends with nearby strangers have gained popularity recently. As another typical type of proximity-based apps, some ridesharing (RS) apps allowing drivers to search nearby passengers and get their ridesharing requests also become popular due to their contribution to economy and emission reduction. In this paper, we concentrate on the location privacy of proximity-based mobile apps. By analyzing the communication mechanism, we find that many apps of this type are vulnerable to large-scale location spoofing attack (LLSA). We accordingly propose three approaches to performing LLSA. To evaluate the threat of LLSA posed to proximity-based mobile apps, we perform real-world case studies against an NS app named Weibo and an RS app called Didi. The results show that our approaches can effectively and automatically collect a huge volume of users’ locations or travel records, thereby demonstrating the severity of LLSA. We apply the LLSA approaches against nine popular proximity-based apps with millions of installations to evaluate the defense strength. We finally suggest possible countermeasures for the proposed attacks.

scholarly journals Connected health for growth hormone treatment research and clinical practice: learnings from different sources of real-world evidence (RWE)—large electronically collected datasets, surveillance studies and individual patients’ cases

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Nea Boman ◽  
Luis Fernandez-Luque ◽  
Ekaterina Koledova ◽  
Marketta Kause ◽  
Risto Lapatto
Keyword(s):  
Growth Hormone ◽  
Observational Study ◽  
Case Studies ◽  
Real World ◽  
Growth Disorders ◽  
Injection Device ◽  
Growth Outcomes ◽  
Real World Evidence ◽  
High Adherence

Abstract Background A range of factors can reduce the effectiveness of treatment prescribed for the long-term management of chronic health conditions, such as growth disorders. In particular, prescription medications may not achieve the positive outcomes expected because approximately half of patients adhere poorly to the prescribed treatment regimen. Methods Adherence to treatment has previously been assessed using relatively unreliable subjective methods, such as patient self-reporting during clinical follow-up, or counting prescriptions filled or vials returned by patients. Here, we report on a new approach, the use of electronically recorded objective evidence of date, time, and dose taken which was obtained through a comprehensive eHealth ecosystem, based around the easypod™ electromechanical auto-injection device and web-based connect software. The benefits of this eHealth approach are also illustrated here by two case studies, selected from the Finnish cohort of the easypod™ Connect Observational Study (ECOS), a 5-year, open-label, observational study that enrolled children from 24 countries who were being treated with growth hormone (GH) via the auto-injection device. Results Analyses of data from 9314 records from the easypod™ connect database showed that, at each time point studied, a significantly greater proportion of female patients had high adherence (≥ 85%) than male patients (2849/3867 [74%] vs 3879/5447 [71%]; P < 0.001). Furthermore, more of the younger patients (< 10 years for girls, < 12 years for boys) were in the high adherence range (P < 0.001). However, recursive partitioning of data from ECOS identified subgroups with lower adherence to GH treatment ‒ children who performed the majority of injections themselves at an early age (~ 8 years) and teenagers starting treatment aged ≥ 14 years. Conclusions The data and case studies presented herein illustrate the importance of adherence to GH therapy and how good growth outcomes can be achieved by following treatment as described. They also show how the device, software, and database ecosystem can complement normal clinical follow-up by providing HCPs with reliable information about patient adherence between visits and also providing researchers with real-world evidence of adherence and growth outcomes across a large population of patients with growth disorders treated with GH via the easypod™ device.

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