🚩 New Media Artist Hsin-Chien Huang Leads "Garden Taipei/Formosa: Taiwan Grand Tour" with 22 Taiwan's VR and New Media Artworks to 2021 Ars Electronica Linz in Austria🇦🇹
2021 ARS ELECTRONICA FESTIVAL Ars Electronica has chosen “A New Digital Deal” as its annual theme, centering around the social and cultural transformations under the influence of technology from different countries. Also, it pays attention to changes of “the New Normal” due to the pandemic.
Hsin-Chien Huang, this year’s curator of the “Garden Taipei/Formosa”, resonates the theme with the “Taiwan Grand Tour”, hoping to waken our desire and ability to move freely during the journey via different kinds of media, also make more people see the marvelous results and how hard Taiwan has devoted to technology, culture, tradition, and tradition via international digital platforms. The tour will have become a window between the world and Taiwan.
The scale of this year’s exhibitions has been brought up a notch. Not only did it carry on displaying the VR and AR productions from last year, but the curator Hsin-Chien Huang has collaborated with three other, Hsiao-Yue Tsao, Billy Chang, and Chung-Hsien Chen, to call out many VR directors, new media artists, start-up companies and government institutions to join the project. There are 22 magnificent programs in total, which will be shown in categories such as “Immersive Tour”, “Animated Tour”, “New Media Tour”, “Earth Tour” and “Action Tour” respectively.
“Immersive Tour”, as the first part of the “Taiwan Grand Tour”, viewers can wander among the mountains, oceans, and rivers in the digital world, even outer space! Six scenes inspired by unique Taiwanese landscapes with cultural and biological features will be shared with the audiences, such as “The Starry Sand Beach” (Directed by Hsin-Chien Huang and Nina Barbier), “Moondream Reality-Rebirth”(Directed by Chi-Yen Chiang, Ami Wu), the shuttle VR 360 stereo video of “TAIPOWER D/S ONE.” (Directed by Ghung-I Hung and Shih-Chou Wen), “Floating Childhoods” (Directed by Hakka Public Communication Foundation and Wen-Chieh Chang), “Blue Tears EP1” (Directed by Hsiao-Yue Tsao), and “Samsara” (Directed by Hsin-Chien Huang).
In the “Animated Tour”, viewers can devote themselves to the characters via different programs. Whether it is the abstract or figurative visual style, audiences can experience anxiety and frustration all the way to happiness and growth. Getting rid of this disappointing reality, viewers shall continue the “Taiwan Grand Tour” through their imagination. This program consists of four animations: "Go Go Giwas: Sowing Dream Seeds"(Directed by Vick Wang, Yi-Feng Kao), "My grandmother is an Egg"(Directed by Wu-Ching Chang),"Inside"(Directed by Yu-Ting Hsueh), and "The Wayward Kite"(Directed by Yu-Ting Hsueh).
In the “New Media Tour” program, nine brilliant pieces created by Taiwanese artists will be shared as the relay points for the “Taiwan Grand Tour.” They use video, sound, electronic music, installation, and various new media to explore different topics, such as family, memory, city, society, landscape, and environment. We firmly believe that digital tools can also capture the warmth and emotions in reality. This program consists of nine artworks: "Surrounding Spectrum"(Directed by Hsiu-Ming Wu), "Nanyang Express II : Eternal Wandering and Tropical Pursuing"(Directed by Yi-Chi Lin), "Wave Waves"(Directed by Sio-Pang Hong), "That ・ This"(Directed by Ching-Chuan Hu), "Signal"(Directed by Chin-Hsiang Hu), "Tower of Babel by the sea"(Directed by Wei-Chung Feng), "How to explain love to an iPhone"(Directed by Jie-Huai Yang), "U+617E_v2.∞"(Directed by Jia-Hua Zhan), and "Absence in Presence"(Directed by Ning Tsai).
In the program “Earth Tour”, viewers will participate in a performance art called “Taste Soil”, which intends to rethink the relationship between humans and land by means of “eating.” The program brings together international eminent chefs Andre Chiang, dancer Billy Chang, new media artist Hsin-Chien Huang and Wen-Chieh Chang, fusing Taiwan’s unique traditions and customs with cuisines and dance performances via VR experience. A feast to the eyes and tastebuds awaits.
Looking back at the present time, humans need to take more efficient scientific actions in the digital world to reduce the consumption and pressure of resources and the environment and cope with the impact in the post-pandemic times. Two important technology units in Taiwan make their debut in the “Action Tour”: Miniwiz Co., Ltd. and the Taipei Urban Intelligence Center. The former is devoted to the sustainable development of materials science with digital technology and design, while the latter is the integration of big data and streaming technology to create a new technical model of urban governance. Combing these two, an answer to developing a sustainable society with digital energy is born. During the tour, a new performance art project is inspired by the digital cross-field cooperation for the first time. The Taipei Urban Intelligence Center will join hands with new media artist Chin-Hsiang Hu and the founder of Inwheel Ghung-I Hung, to create a new media artwork “The Weight of Data” by integrating both virtual and physical materials from different domains and sharing data resources.
The brilliant curatorial concept and lineup of the Taiwan Grand Tour have attracted the interest of the officials of the festival and been in the limelight. Therefore, the festival has invited three creators behind the “Earth Tour”: Andre Chiang, Billy Chang, and Hsin-Chien Huang, to an online interview called “Highlight Channel” at 18:00 on September 1 (Taiwan Time). The link will be provided by the official later on. Moreover, Miniwiz Co., Ltd. and the Taipei Urban Intelligence Center are also invited to share their ideas and experiences in an online show called “Home Delivery.”
The theme of the Garden Taipei/ Formosa is presented in a diverse form of performances by combining different fields multiply. The audience can easily follow the step of the “Taiwan Grand Tour” to explore Taiwan’s magnificent local digital creativity and illustrate a new digital landscape unitedly that only belongs to Taiwan. The 2021 Ars Electronica online exhibition will be held from September 8 to 12, 2021. Click the link below to take a sneak peek of this year’s shows.
📍ARS ELECTRONICA FESTIVAL 🔗 https://ars.electronica.art/newdigitaldeal/de/formosa-grand-tour/
📍ARS ELECTRONICA FESTIVAL “Home Delivery” 🔗 https://www.youtube.com/c/arselectronica/playlists?view=50&sort=dd&shelf_id=5
📍 Garden Taipei/Formosa: Taiwan Grand Tour 🔗 http://garden2021.metarealitylab.com/
#奧地利林茲電子藝術節
#arselectronica21 #gardentaipeiformosa
同時也有1部Youtube影片,追蹤數超過16萬的網紅夠維根Go Vegan,也在其Youtube影片中提到,這是個常見的迷思,不只一般的民眾會搞混 連專業的醫療人員都不太清楚... FB粉絲專頁:https://www.facebook.com/GoVeganTW 提倡一種新的生活態度,透過動畫宣導"動物權利"! 特別感謝"台灣素食營養學會"贊助 臺灣素食營養學會官網:http://www.twvns...
「physical data model」的推薦目錄:
- 關於physical data model 在 黃心健 Hsin-Chien Huang Facebook 的最讚貼文
- 關於physical data model 在 台灣國際醫療暨健康照護展 Medical Taiwan Facebook 的最佳解答
- 關於physical data model 在 國立陽明交通大學電子工程學系及電子研究所 Facebook 的最佳貼文
- 關於physical data model 在 夠維根Go Vegan Youtube 的最讚貼文
- 關於physical data model 在 Conceptual, Logical & Physical Data Models - YouTube 的評價
- 關於physical data model 在 database design - Enumeration class in physical data model 的評價
physical data model 在 台灣國際醫療暨健康照護展 Medical Taiwan Facebook 的最佳解答
The National Health Insurance (NHI) cards and system helped a lot in pandemic prevention like tracing travel history and distributing the amount of medical mask etc.
Since the NHI Administration began issuing NHI Cards in 2004, medical personnel have been able to obtain diagnostic data of those seeking treatment simply by accessing the card.
Based on these strong foundations, the NHI Administration has begun to develop its “Virtual NHI Card” system. Once completed, it will be able to improve home healthcare and rural medical services, while making access to medical records faster and safer. In the future, people in Taiwan will have the option to use a virtual NHI Card instead of a physical one.
#HealthcareSystem #HealthInsurance #Taiwan
https://english.cw.com.tw/article/article.action?id=2927
physical data model 在 國立陽明交通大學電子工程學系及電子研究所 Facebook 的最佳貼文
【演講】2019/11/19 (二) @工四816 (智易空間),邀請到Prof. Geoffrey Li(Georgia Tech, USA)與Prof. Li-Chun Wang(NCTU, Taiwan) 演講「Deep Learning based Wireless Resource Allocation/Deep Learning in Physical Layer Communications/Machine Learning Interference Management」
IBM中心特別邀請到Prof. Geoffrey Li(Georgia Tech, USA)與Prof. Li-Chun Wang(NCTU, Taiwan)前來為我們演講,歡迎有興趣的老師與同學報名參加!
演講標題:Deep Learning based Wireless Resource Allocation/Deep Learning in Physical Layer Communications/Machine Learning Interference Management
演 講 者:Prof. Geoffrey Li與Prof. Li-Chun Wang
時 間:2019/11/19(二) 9:00 ~ 12:00
地 點:交大工程四館816 (智易空間)
活動報名網址:https://forms.gle/vUr3kYBDB2vvKtca6
報名方式:
費用:(費用含講義、午餐及茶水)
1.費用:(1) 校內學生免費,校外學生300元/人 (2) 業界人士與老師1500/人
2.人數:60人,依完成報名順序錄取(完成繳費者始完成報名程序)
※報名及繳費方式:
1.報名:請至報名網址填寫資料
2.繳費:
(1)親至交大工程四館813室完成繳費(前來繳費者請先致電)
(2)匯款資訊如下:
戶名: 曾紫玲(國泰世華銀行 竹科分行013)
帳號: 075506235774 (國泰世華銀行 竹科分行013)
匯款後請提供姓名、匯款時間以及匯款帳號後五碼以便對帳
※將於上課日發放課程繳費領據
聯絡方式:曾紫玲 Tel:03-5712121分機54599 Email:tzuling@nctu.edu.tw
Abstract:
1.Deep Learning based Wireless Resource Allocation
【Abstract】
Judicious resource allocation is critical to mitigating interference, improving network efficiency, and ultimately optimizing wireless network performance. The traditional wisdom is to explicitly formulate resource allocation as an optimization problem and then exploit mathematical programming to solve it to a certain level of optimality. However, as wireless networks become increasingly diverse and complex, such as high-mobility vehicular networks, the current design methodologies face significant challenges and thus call for rethinking of the traditional design philosophy. Meanwhile, deep learning represents a promising alternative due to its remarkable power to leverage data for problem solving. In this talk, I will present our research progress in deep learning based wireless resource allocation. Deep learning can help solve optimization problems for resource allocation or can be directly used for resource allocation. We will first present our research results in using deep learning to solve linear sum assignment problems (LSAP) and reduce the complexity of mixed integer non-linear programming (MINLP), and introduce graph embedding for wireless link scheduling. We will then discuss how to use deep reinforcement learning directly for wireless resource allocation with application in vehicular networks.
2.Deep Learning in Physical Layer Communications
【Abstract】
It has been demonstrated recently that deep learning (DL) has great potentials to break the bottleneck of the conventional communication systems. In this talk, we present our recent work in DL in physical layer communications. DL can improve the performance of each individual (traditional) block in the conventional communication systems or jointly optimize the whole transmitter or receiver. Therefore, we can categorize the applications of DL in physical layer communications into with and without block processing structures. For DL based communication systems with block structures, we present joint channel estimation and signal detection based on a fully connected deep neural network, model-drive DL for signal detection, and some experimental results. For those without block structures, we provide our recent endeavors in developing end-to-end learning communication systems with the help of deep reinforcement learning (DRL) and generative adversarial net (GAN). At the end of the talk, we provide some potential research topics in the area.
3.Machine Learning Interference Management
【Abstract】
In this talk, we discuss how machine learning algorithms can address the performance issues of high-capacity ultra-dense small cells in an environment with dynamical traffic patterns and time-varying channel conditions. We introduce a bi adaptive self-organizing network (Bi-SON) to exploit the power of data-driven resource management in ultra-dense small cells (UDSC). On top of the Bi-SON framework, we further develop an affinity propagation unsupervised learning algorithm to improve energy efficiency and reduce interference of the operator deployed and the plug-and-play small cells, respectively. Finally, we discuss the opportunities and challenges of reinforcement learning and deep reinforcement learning (DRL) in more decentralized, ad-hoc, and autonomous modern networks, such as Internet of things (IoT), vehicle -to-vehicle networks, and unmanned aerial vehicle (UAV) networks.
Bio:
Dr. Geoffrey Li is a Professor with the School of Electrical and Computer Engineering at Georgia Institute of Technology. He was with AT&T Labs – Research for five years before joining Georgia Tech in 2000. His general research interests include statistical signal processing and machine learning for wireless communications. In these areas, he has published around 500 referred journal and conference papers in addition to over 40 granted patents. His publications have cited by 37,000 times and he has been listed as the World’s Most Influential Scientific Mind, also known as a Highly-Cited Researcher, by Thomson Reuters almost every year since 2001. He has been an IEEE Fellow since 2006. He received 2010 IEEE ComSoc Stephen O. Rice Prize Paper Award, 2013 IEEE VTS James Evans Avant Garde Award, 2014 IEEE VTS Jack Neubauer Memorial Award, 2017 IEEE ComSoc Award for Advances in Communication, and 2017 IEEE SPS Donald G. Fink Overview Paper Award. He also won the 2015 Distinguished Faculty Achievement Award from the School of Electrical and Computer Engineering, Georgia Tech.
Li-Chun Wang (M'96 -- SM'06 -- F'11) received Ph. D. degree from the Georgia Institute of Technology, Atlanta, in 1996. From 1996 to 2000, he was with AT&T Laboratories, where he was a Senior Technical Staff Member in the Wireless Communications Research Department. Currently, he is the Chair Professor of the Department of Electrical and Computer Engineering and the Director of Big Data Research Center of of National Chiao Tung University in Taiwan. Dr. Wang was elected to the IEEE Fellow in 2011 for his contributions to cellular architectures and radio resource management in wireless networks. He was the co-recipients of IEEE Communications Society Asia-Pacific Board Best Award (2015), Y. Z. Hsu Scientific Paper Award (2013), and IEEE Jack Neubauer Best Paper Award (1997). He won the Distinguished Research Award of Ministry of Science and Technology in Taiwan twice (2012 and 2016). He is currently the associate editor of IEEE Transaction on Cognitive Communications and Networks. His current research interests are in the areas of software-defined mobile networks, heterogeneous networks, and data-driven intelligent wireless communications. He holds 23 US patents, and have published over 300 journal and conference papers, and co-edited a book, “Key Technologies for 5G Wireless Systems,” (Cambridge University Press 2017).
physical data model 在 夠維根Go Vegan Youtube 的最讚貼文
這是個常見的迷思,不只一般的民眾會搞混
連專業的醫療人員都不太清楚...
FB粉絲專頁:https://www.facebook.com/GoVeganTW
提倡一種新的生活態度,透過動畫宣導"動物權利"!
特別感謝"台灣素食營養學會"贊助
臺灣素食營養學會官網:http://www.twvns.org/
--------------------------------------------------------------------------------
【參考資料】
不吃肉蛋白質夠嗎?http://www.twvns.org/info/faq/25-2008-08-20-03-38-47
顛覆你的觀念!你真的知道怎麼吃蛋白質?: www.twvns.org/info/faq/266-2015-06-17-09-32-20
告訴你~痛風要吃黃豆的理由: www.twvns.org/info/faq/213-2015-04-17-07-41-12
乳癌不能吃黃豆? https://youtu.be/ie3pVBvnIEM
1. 每日蛋白質需求量:
http://www.nationalacademies.org/hmd/~/media/Files/Activity%20Files/Nutrition/DRIs/DRI_Macronutrients.pdf
2. 豆類的優點(預防疾病、營養素):
Messina V. Nutritional and health benefits of dried beans. Am J Clin Nutr. 2014 Jul;100 Suppl 1:437S-42S. doi: 10.3945/ajcn.113.071472. Epub 2014 May 28.
3. 痛風可以吃豆類:
Teng GG, Pan A, Yuan JM, Koh WP. Food Sources of Protein and Risk of Incident Gout in the Singapore Chinese Health Study. Arthritis Rheumatol. 2015 Jul;67(7):1933-42. doi: 10.1002/art.39115.
4. 美國痛風研究:
Choi HK, Atkinson K, Karlson EW, Willett W, Curhan G. Purine-rich foods, dairy and protein intake, and the risk of gout in men. N Engl J Med. 2004 Mar 11;350(11):1093-103.
Messina M, Messina VL, Chan P. Soyfoods, hyperuricemia and gout: a review of the epidemiologic and clinical data. Asia Pac J Clin Nutr. 2011;20(3):347-58.Review.
5. 日本痛風研究:
Yamakita J, Yamamoto T, Moriwaki Y, Takahashi S, Tsutsumi Z, Higashino K. Effect of Tofu (bean curd) ingestion and on uric acid metabolism in healthy and gouty subjects. Adv Exp Med Biol. 1998;431:839-42.
6. 乳癌研究:
Caan BJ, Natarajan L, Parker B et al. (2011) Soy food consumption and breast cancer prognosis. Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 20, 854-858.
Doyle C, Kushi LH, Byers T et al. (2006) Nutrition and physical activity during and after cancer treatment: an American Cancer Society guide for informed choices. CA: a cancer journal for clinicians 56, 323-353.
Guha N, Kwan ML, Quesenberry CP, Jr. et al. (2009) Soy isoflavones and risk of cancer recurrence in a cohort of breast cancer survivors: the Life After Cancer Epidemiology study. Breast cancer research and treatment 118, 395-405.
Hsieh CY, Santell RC, Haslam SZ et al. (1998) Estrogenic effects of genistein on the growth of estrogen receptor-positive human breast cancer (MCF-7) cells in vitro and in vivo. Cancer research 58, 3833-3838.
Rock CL, Doyle C, Demark-Wahnefried W et al. (2012) Nutrition and physical activity guidelines for cancer survivors. CA: a cancer journal for clinicians 62, 243-274.
Setchell KD, Brown NM, Zhao X et al. (2011) Soy isoflavone phase II metabolism differs between rodents and humans: implications for the effect on breast cancer risk. The American journal of clinical nutrition 94, 1284-1294.
Shu XO, Zheng Y, Cai H et al. (2009) Soy food intake and breast cancer survival. Jama 302, 2437-2443.
7.吃素節能減碳:
Ruini LF, Ciati R, Pratesi CA, Marino M, Principato L, Vannuzzi E. Working toward Healthy and Sustainable Diets: The "Double Pyramid Model" Developed by the Barilla Center for Food and Nutrition to Raise Awareness about the Environmental and Nutritional Impact of Foods. Front Nutr. 2015 May 4;29.

physical data model 在 Conceptual, Logical & Physical Data Models - YouTube 的推薦與評價
Learn about the 3 stages of a Data Model Design - Conceptual Data Model - Logical Data Model - Physical Data Model. ... <看更多>