| 1. |
- Bai, Hua, 1990-, et al.
(author)
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An Exploratory Study on Nepalese Teenager’s Visual Recognition and Preferences in Serious Games
- 2022
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In: Proceedings 2022 IEEE International Conference on e-Business Engineering ICEBE 2022. - : IEEE Computer Society. - 9781665492447 - 9781665492454 ; , s. 13-18
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Conference paper (peer-reviewed)abstract
- In serious game development, effective communication through both languages, sounds, and icons can be crucial for a game to have its intended impact. While this is also true for entertainment games, serious games have added layers of challenges as they are a) often played by audiences outside of the “typical” game ecosystem, and b) miscommunication can lead to players missing important lessons or even learning incorrect information. When a serious game is intended to be used in different parts of the world, however, clear visual communication gets an added layer of complexity: culturally informed symbol interpretation and visual preference. In order to examine how these might affect players’ experiences when playing serious games, this paper presents the results of a mixed-method study conducted in two schools in Nepal. The study included 10 participants, between 13-16 years old, who played a prototype of a mobile game currently in development, which has the purpose of teaching young players about food nutrition and healthy habits. After playing the prototype, they took a short survey where they were asked to identify different food types, and they were also interviewed to discuss their opinions of the game’s visual style. The results of the study indicate that, while higher fidelity images were much easier to correctly identify by the participants, the participants’ preference for visual fidelity varied to a large degree.
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| 2. |
- Li, Xiaoxia, et al.
(author)
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Review on Learning-based Methods for shop Scheduling problems
- 2022
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In: Proceedings 2022 IEEE International Conference on e-Business Engineering ICEBE 2022. - : IEEE. - 9781665492447 - 9781665492454 ; , s. 294-298
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Conference paper (peer-reviewed)abstract
- Shop scheduling is an effective way for manufacturers to improve their manufacturing performances. However, due to its complexity, it is difficult to deal with shop scheduling problems (SSP). Thus, SSP has received a lot of attention from industry and academia. Various kinds of methods have been proposed to solve SSP. Learning-based method is just one of the most representative methods for SSP. This paper focuses on reviewing the learning-based methods for SSP. Firstly, the methods for SSP are briefly introduced. Then, its description and model are provided and its classification is discussed. Next, the learning-based methods for SSP are classified according to the machine learning technique used in the methods. Based on the classification, the related work on each type of learning-based methods for SSP is summarized and further analyzed and compared with other traditional methods. Finally, the future research opportunities and challenges of the learning-based methods for SSP are summarized.
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| 3. |
- Lu, Xin, et al.
(author)
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A generic and modularized Digital twin enabled human-robot collaboration
- 2022
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In: Proceedings 2022 IEEE International Conference on e-Business Engineering ICEBE 2022. - : IEEE. - 9781665492447 - 9781665492454 ; , s. 66-73
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Conference paper (peer-reviewed)abstract
- Recently, the manufacturing paradigm shifts from mass production to mass customization, which results in urgently demands for the development of intelligent, flexible and automatic manufacturing systems for handling complex manufacturing tasks with high efficiency. The use of collaborative robots, an essential enabling technology for developing human-robot collaboration (HRC), is on the rise for human-centric intelligent automation design. An effective virtual simulation platform, which can continuously simulate and evaluate HRC performance in different working scenarios, is lacking in developing an HRC system in a sophisticated industrial arena. This paper presents a generic and modularized digital twin enabled HRC framework based on the synergy effect of human, robotic and environment-related factors to provide a flexible, compatible, re-configurable solution to ease the implementation of HRC in the real world. The feasibility of the proposed framework is validated through the practical implementation of a food packaging job, which involves a human operator and an ABB robotic arm collaboratively working together, on an industrial shop.
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| 4. |
- Shao, Bing, et al.
(author)
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Deep Learning based Coffee Beans Quality Screening
- 2022
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In: Proceedings 2022 IEEE International Conference on e-Business Engineering ICEBE 2022. - : IEEE. - 9781665492447 - 9781665492454 ; , s. 271-275
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Conference paper (peer-reviewed)abstract
- Coffee bean quality screening is a time-consuming work, and its workload increases abruptly with the rapid development of coffee beverage consumer market. In this work, a CNN-based classifier is developed to categorizing the coffee beans into sour, black, broken, moldy, shell, insect damage and good beans. The screening test results show that the screening accuracy could reach more than 90% for all other beans except for shell beans (88%). Therefore, the proposed method is feasible and promising. Moreover, a cost-effective automatic coffee bean screening system using the developed classifier is manufactured and implemented for a local company.
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