MAJLIS HIGH TECH NATION KETENGAHKAN TEKNOLOGI MASA HADAPAN
Semalam saya telah mempengerusikan Mesyuarat Majlis High-Tech Nation yang bertujuan merangka hala tuju teknologi sedia ada dan masa hadapan yang berpotensi untuk dibangunkan di Malaysia. Majlis ini juga akan melaporkan sebarang perkembangan secara terus kepada Majlis Sains Negara yang dipengerusikan oleh Perdana Menteri.
Program dan dasar yang akan dibentuk di bawah majlis ini adalah berpandukan kepada kerangka MySTIE 10-10 serta Dasar Sains, Teknologi dan Inovasi (DSTIN) 2021-2030 yang telah saya lancarkan minggu lalu. Sebanyak 30 bidang keutamaan telah dikenal pasti menerusi rangka kerja ini dan majlis ini akan merapatkan jurang yang wujud bagi memastikan ia dapat memberi kesan maksimum kepada setiap bidang keutamaan.
Majlis ini juga akan mengambil peranan secara proaktif dalam mengetengahkan teknologi masa hadapan yang akan melonjakkan kedudukan negara sebagai peneraju teknologi.
Saya juga telah memilih untuk mengutamakan beberapa program, hala tuju dan dasar agar sesuai dengan keperluan masa kini yang mendesak.
Antara cadangan yang telah dibentangkan semalam adalah berkenaan perubatan kepersisan (precision medicine) daripada Kementerian Kesihatan Malaysia (KKM). Perubatan kepersisan berasaskan teknologi data raya ini berupaya mendiagnos serta merancang perubatan yang berkualiti dan terjamin bagi seseorang pesakit.
Selain itu, Institut Penyelidikan Hidraulik Kebangsaan Malaysia (NAHRIM) juga telah membentangkan Hala Tuju Inovasi Air Negara yang akan menjamin keselamatan air. Menerusi hala tuju ini, sebanyak lima program telah dikenal pasti iaitu sungai yang bersih, rizab margin air, sistem air pintar, pengurangan risiko bencana dan pembiayaan air.
Kementerian Sains, Teknologi dan Inovasi (MOSTI) pula telah membentangkan 9 hala tuju yang sedang dibangunkan oleh agensi-agensi di bawah kementerian. Kesemua hala tuju yang akan dibentangkan pada pertengahan 2021 ini akan memacu kerajaan untuk merangka pelaburan serta memformulasi dasar terbaik dalam pembangunan teknologi-teknologi tersebut. Pelan itu antara lain akan merangkumi: blok rantai (blockchain); nanoteknologi; robotik; hidrogen; kecerdasan buatan (AI); litar bersepadu dan bahan termaju (advanced materials)
Akademi Sains Malaysia telah membentangkan cadangan untuk menginstitusikan sebuah badan pemecut pengkomersialan teknologi (Tech-Commercialisation Accelerator) bagi mengetuai dan mengkoordinasi usaha-usaha penyelidikan beradasarkan perniagaan serta ekonomi. Penyelidikan dan pembangunan (R&D) serta sistem penyampaian ini akan dibuat berasaskan permintaan serta keperluan pasaran untuk inovasi-inovasi penganggu (disruptive innovations). Saya akan mengumumkan lebih lanjut mengenai perkara ini sedikit masa lagi.
Institut Penyelidikan Keselamatan Jalan Raya Malaysia (MIROS) telah membentangkan kertas kerja ‘Teknologi Motosikal: Penyelesaian Kepada Dilema Kemajuan Ekonomi-Keselamatan’ dan menjelaskan bahawa 66 peratus daripada kematian di jalan raya melibatkan kemalangan motosikal. Kami berharap untuk memberi insentif dalam pembangunan, pengaplikasian dan penggunaan teknologi sedia ada serta akan datang bagi memperbaiki kebolehcapaian kesemua aspek keselamatan jalan raya. Bidang yang berpotensi untuk dibangunkan termasuklah teknologi pengujian serta verifikasi, teknologi penghindaran kemalangan, teknologi mengurangkan kecederaan (dalam kemalangan), teknologi pemaduan kembali sosial (social reintegration technology-merujuk kepada teknologi respons pintar awal dan pemulihan) serta teknologi pengurusan dan perancangan strategik.
Kementerian Alam Sekitar dan Air pula telah membentangkan Hala Tuju Inovasi Teknologi Hijau Kebangsaan yang mensasarkan penggunaan teknologi hijau menjelang 2030 bagi memastikan kemampanan alam sekitar negara. Inovasi-inovasi sektoral di bawah pelan ini termasuk perolehan hijau kerajaan, teknologi grid pintar, proses perindustrian hijau, pengawasan sungai melalui Internet Segala Benda (IoT), skim Waste to Energy (WTE) and wealth, pengaplikasian bangunan hijau dan pintar, kenderaan cekap tenaga dan kenderaan elektrik, pertanian bandar serta IoT pengawasan hutan.
Akhir sekali, dalam kita mengadaptasi perubahan tingkah laku akibat COVID-19, saya telah meminta MOSTI menyediakan satu kertas kerja mengenai Inisiatif Infrastruktur dan Ekonomi Sentuhan Rendah. Ini memerlukan anjakan paradigma bukan sahaja dalam cara kita berinteraksi sesama sendiri, malahan dengan dunia secara keseluruhan. Antaranya termasuklah penggosok lantai berautonomi, robot pembantu (membawa barangan) dan sistem pengurusan sisa pintar di pasar-pasar awam. MOSTI juga telah melancarkan penggunaan robot di hospital dengan kerjasama KKM serta memulakan modul robotik, dron serta AI di ladang-ladang bersama FELDA. Beberapa inisiatif ini akan direalisasikan di bawah Sandbox Teknologi dan Inovasi Nasional (NTIS).
Kebanyakan progam, hala tuju dan dasar sedia ada selama ini telah dimajukan secara berasingan atau bersendirian oleh pelbagai kementerian dan agensi. Majlis High Tech Nation adalah permulaan baharu kepada cara kita membangun dan mengaplikasi teknologi dalam negara bagi memastikan segalanya selaras dan koheren dengan keperluan nasional.
KHAIRY JAMALUDDIN
MENTERI SAINS, TEKNOLOGI DAN INOVASI
18 DECEMBER 2020
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HIGH-TECH NATION COUNCIL WILL CHAMPION UPCOMING TECHNOLOGIES
Yesterday, I chaired the first High-Tech Nation Council meeting, which aims to give strategic direction regarding existing and upcoming technology that has the potential to be developed in Malaysia. The High-Tech Nation Council will report directly to the National Science Council, which is chaired by the Prime Minister.
The programmes, roadmaps and policies under the High-Tech Nation Council are driven by the mySTIE 10-10 and National Science, Technology and Innovation Policy 2021-2030 that I launched last week. 30 niche areas were identified under this framework, and the High-Tech Nation Council will aim to fill in any gaps we have identified to make sure that there is maximum impact in these areas.
This Council will be proactive and champion upcoming technologies that we need to embark on as a nation to position us at the forefront of what is current and what is cutting-edge.
I have chosen to prioritise some of the programmes, roadmaps and policies in line with pressing national needs.
Some of the papers presented yesterday include the Ministry of Health’s paper on precision medicine, which takes a personalised, predictive, preventive and participatory approach to medicine. This will be layered together with big-data analytics to give personalised recommendations to each person.
National Hydraulic Research Institute of Malaysia (NAHRIM) presented on the National Water Innovation Roadmap, to guarantee national water security. This involves five programmes; Clean River, Reserve Margin, Smart Water, Disaster Risk Reduction, and Water Financing.
The Ministry of Science, Technology and Innovation presented nine roadmaps that are currently being developed under our agencies. All of these roadmaps will be unveiled by the middle of 2021. These roadmaps will guide our investments and policy direction in rolling out these technologies. They will cover: blockchain, nanotechnology, robotics, hydrogen, artificial intelligence, integrated circuits and advanced materials among others.
The Academy of Sciences presented on institutionalising a Tech-Commercialisation Accelerator, to spearhead and coordinate economic-oriented research in the form of demand-driven R&D and market-driven delivery systems for disruptive innovations. I will be announcing this in due course.
The Malaysian Institute of Road Safety Research (MIROS) also presented on Motorcycle Technology: Solving a Dilemma between Economic Development and Safety. 66% of the fatalities on the road involve motorcycles. We hope to incentive the development, application and deployment of existing and future technologies to improve accessibility and all aspects of road safety. Potential areas we are looking at include testing and verification technology, crash avoidance technology, injury mitigation technology (in event of crash), social reintegration technology (which refers to smart first response and rehabilitation technology), and management and strategic planning technology.
The Ministry of Environment and Water presented the National Green Technology Innovation Roadmap, which aims to leverage green technology innovation for an environmentally sustainable Malaysia by 2030. Sectoral innovations under this roadmap include government green procurement, smart grid technology, green industrial process, IoT river monitoring, Waste to Energy and Wealth schemes, application of smart and green buildings, energy efficiency vehicles & electric vehicles, vertical & urban farming, and IoT forest monitoring.
Lastly, but not least, in line with behavioural changes due to COVID-19, I asked MOSTI to prepare a paper on Low-Touch Infrastructure and Economic Initiatives. These will require a paradigm shift in how we look interact both with each other and the world around us. Some of the low-touch initiatives we have quickly identified include autonomous floor scrubbers, autonomous power assist robots (to carry your goods) and smart waste management systems in public markets. We’ve also launched robotics in hospitals together with MOH, and robotics, drones and artificial intelligence modules in plantations together with FELDA. Some of these initiatives will be realised via the National Technology & Innovation Sandbox.
Many of these programmes, roadmaps, and policies have existed and been implemented in silos by different ministries and agencies. This is just the start of how we relook at the development and application of technology in this country, to ensure everything is in line with our national needs and part of a coherent whole.
KHAIRY JAMALUDDIN
MINISTER OF SCIENCE, TECHNOLOGY AND INNOVATION
18 DECEMBER 2020
how to improve energy efficiency 在 國立陽明交通大學電子工程學系及電子研究所 Facebook 的最讚貼文
【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).
how to improve energy efficiency 在 ITRI Taiwan Facebook 的最讚貼文
“For the power grid to be reliable, we have to improve energy efficiency and modernization.”—Dr. Edwin Liu, ITRI President.
Check out the interview on Dr. Liu’s take on the energy supply situation in Taiwan. He also shares his opinions on how “smart usage” could help with power shortage, as well as ITRI’s role in helping returning Taiwanese businesses.
#itriglobal #itritech #powergrid #energy
http://www.taipeitimes.com/…/archiv…/2019/06/16/2003717039/2
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