* 組織一般到特殊，更重要的到次重要的技術信息 (PART A)
* 助研究思考及寫作的背景音樂 (316)
* 國外專家訪問行程之安排 (國外專家訪問) (有效撰寫專業英文電子郵件) (7 of 9)
* 工程英文假設描述 (50) (下)
Academic publishing news 學術出版新聞
組織一般到特殊，更重要的到次重要的技術信息 (PART A)
Alan Hovhaness (1911年3月8日－2000年6月21日），亞美尼亞-蘇格蘭裔美國作曲家，20世紀最多產的古典音樂作曲家之一。
We were pleased to hear from Professor Chang (National Taiwan University) concerning your willingness to serve as a speaker at the Combustibility of Building Materials Symposium.
The meeting will be held April 25-26, 1994 at the National Central Library, Taipei. What the speaker can hopefully prepare We hope that you can give two lectures, which will be at 13:20-14:05 and 15:10-15:55 (4/25/94), respectively. Please fax us your curriculum vitae, lecture topics, and half-page abstracts before January 31, 1994. Also, please send us the complete papers before March 1, 1994.
Please fax and send all your materials (i.e., abstracts, papers and curriculum vitae) to us at FAX No. 035 123456 so that we will have sufficient time for translation and printing. Our correspondence address is included in the above fax heading. Thanks in advance for your cooperation.
The sponsors will provide roundtrip airfare and transportation from Japan to the conference site, as well as hotel accommodations and living expenses for seven days (4/23-4/29). We have already faxed the informal invitation. A formal invitation letter with a complete program will be sent out by Dr. Johnsee Lee, the General Director of UCL, ITRI. Please do not hesitate to contact me if you have any questions.
工程英文假設描述 (50) (下)
* 工程目標 : 工程提案的目標 ?
* 達成目標的方法 : 你的計劃中達成目標的步驟?
* 希望的結果 : 希望的結果你希望達成的結果?
* 領域的貢獻 : 你的提案對相關工程領域的貢獻?
工程計劃目標 An efficient affective modeling scheme can be developed that incorporates fuzzy emotional measurement of users. An evolutionary learning algorithm can also be developed to model and learn emotions from users. 達成目標的方法 To do so, a user behavior video corpus can be constructed. Appropriate member functions of the fuzzy-logic model can then be completed by analyzing the corpus. Next, events and emotional states can be mapped, and inductive learning algorithms can be used to understand the context of events and emotional states. The context consists of patterns of events, associations among objects, and expectations. Moreover, affective modeling can be adapted using a learning classifier systems approach. 希望的結果 As anticipated, the proposed affective modeling scheme can increase the accuracy of emotional recognition in educational game problems by 10%. Additionally, inductive learning algorithms can facilitate semi-automatic learning of how events and emotional states are related, thus reducing human efforts by 30%. Moreover, adaptations to new environments can be performed as well. 領域的貢獻 Importantly, the proposed scheme can contribute to efforts to further enhance HCI to be affect-sensitive HCI by facilitating affective senses with computers. The affective computing scheme can reduce the intrusiveness of HCI, possibly making individuals more receptive to HCI applications given their more natural interactions. Corporations could learn more about their employees through affective computers, with this knowledge used to maximize work productivity. For instance, affective computers can help to determine when employees are not completely focused on completing their tasks or determining the most productive situations for each individual. Additionally, affective computing can enhance customer services, e.g., enhanced call-center services, phone-free access or data mining. Such efforts can help to monitor consumer reactions towards television advertisements through facial-recognition networked software embedded in televisions; such knowledge can ultimately enhance marketing campaigns. Given the vast array of human emotions, the proposed affective modeling scheme can also provide a valuable reference for efforts underway to model the emotions of users.