Handbook of Dynamic Data Driven Applications Systems: Volume 1
暫譯: 動態數據驅動應用系統手冊：第一卷
Blasch, Erik P., Darema, Frederica, Ravela, Sai
- 出版商: Springer
- 出版日期: 2022-05-12
- 售價: $10,790
- 貴賓價: 9.5 折 $10,251
- 語言: 英文
- 頁數: 766
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 3030745678
- ISBN-13: 9783030745677
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相關主題
商品描述
The Handbook of Dynamic Data Driven Applications Systems establishes an authoritative reference of DDDAS, pioneered by Dr. Darema and the co-authors for researchers and practitioners developing DDDAS technologies.
Beginning with general concepts and history of the paradigm, the text provides 32 chapters by leading experts in ten application areas to enable an accurate understanding, analysis, and control of complex systems; be they natural, engineered, or societal:
The authors explain how DDDAS unifies the computational and instrumentation aspects of an application system, extends the notion of Smart Computing to span from the high-end to the real-time data acquisition and control, and manages Big Data exploitation with high-dimensional model coordination.
The Dynamically Data Driven Applications Systems (DDDAS) paradigm inspired research regarding the prediction of severe storms. Specifically, the DDDAS concept allows atmospheric observing systems, computer forecast models, and cyberinfrastructure to dynamically configure themselves in optimal ways in direct response to current or anticipated weather conditions. In so doing, all resources are used in an optimal manner to maximize the quality and timeliness of information they provide.
Kelvin Droegemeier, Regents' Professor of Meteorology at the University of Oklahoma; former Director of the White House Office of Science and Technology Policy
We may well be entering the golden age of data science, as society in general has come to appreciate the possibilities for organizational strategies that harness massive streams of data. The challenges and opportunities are even greater when the data or the underlying system are dynamic - and DDDAS is the time-tested paradigm for realizing this potential.
Sangtae Kim, Distinguished Professor of Mechanical Engineering and Distinguished Professor of Chemical Engineering at Purdue University
商品描述(中文翻譯)
《動態數據驅動應用系統手冊》建立了DDDAS的權威參考，由Dr. Darema及其共同作者為研究人員和實踐者開發DDDAS技術而開創。
本書從該範式的一般概念和歷史開始，提供了32章由十個應用領域的領先專家撰寫的內容，以便準確理解、分析和控制複雜系統，無論是自然系統、工程系統還是社會系統。
作者解釋了DDDAS如何統一應用系統的計算和儀器方面，擴展智能計算的概念，涵蓋從高端到實時數據獲取和控制，並以高維模型協調來管理大數據的利用。
動態數據驅動應用系統（DDDAS）範式啟發了有關預測嚴重風暴的研究。具體而言，DDDAS概念允許大氣觀測系統、計算預測模型和網絡基礎設施根據當前或預期的天氣條件以最佳方式動態配置自己。這樣一來，所有資源都以最佳方式使用，以最大化其提供的信息的質量和及時性。
Kelvin Droegemeier，奧克拉荷馬大學氣象學榮譽教授；前白宮科學與技術政策辦公室主任
我們可能正進入數據科學的黃金時代，因為社會普遍已經開始認識到利用大量數據流的組織策略的可能性。當數據或基礎系統是動態的時，挑戰和機會更大——而DDDAS是實現這一潛力的經得起考驗的範式。
Sangtae Kim，普渡大學機械工程榮譽教授及化學工程榮譽教授
作者簡介
Erik P. Blasch is a program officer with the Air Force Office of Scientific Research. His focus areas are in multi-domain (space, air, ground) data fusion, target tracking, pattern recognition, and robotics. He has authored 750] scientific papers, 22 patents, 30 tutorials, and 5 books. His recognitions include the Military Sensing Society Mignogna Leadership in Data Fusion Award, IEEE Aerospace and Electronics Systems Society Mimno Best Magazine Paper Award, and IEEE Russ Bioengineering Award. He was also a founding member of the International Society of Information Fusion (ISIF). His previous appointments include adjunct associate professor at Wright State University, exchange scientist at Defense Research and Development Canada, and officer in the Air Force Research Laboratory. Dr. Blasch is an associate fellow of American Institute of Aeronautics and Astronautics (AIAA), fellow of the Society of Photo-Optical and Instrumentation Engineers (SPIE) and fellow of the Institute of Electrical and Electronics Engineers (IEEE).
Dr. Frederica Darema: retired as Senior Executive Service (SES) member and Director of the Air Force Office of Scientific Research, in Arlington, Virginia, where she led the entire basic research investment for the AF and served as Research Director in the Air Force's Chief Data Office, and as Associate Deputy Assistant Secretary the Air Force Office for Science, Technology and Engineering. Prior career history includes: research staff positions at the University of Pittsburgh, Brookhaven National Laboratory, and Schlumberger-Doll; and management and executive-level positions at: the T.J.Watson IBM Research Center and the IBM Corporate Strategy Group; the National Science Foundation and the Defense Advanced Research Projects Agency; and Director of the AFOSR Directorate for Information, Math, and Life Sciences. Dr. Darema, PhD in Nuclear Physics, is a Fellow of the Institute of Electrical and Electronics Engineers (IEEE), among other professional recognitions. She pioneered the DDDAS paradigm and since 2000 has organized and led research initiatives, programs, workshops, conferences, and other forums, to foster and promote DDDAS-based science and technology advances.
Dr. Ravela, Ph.D. 2002, directs the Earth Signals and Systems Group (ESSG) in the Earth Atmospheric and Planetary Sciences (EAPS) department at the Massachusetts Institute of Technology. His primary interests are in statistical pattern recognition, stochastic nonlinear systems, and computational intelligence with application to earth, planets, climate, and life. Dr. Ravela has pioneered dynamic data driven observing systems for wildlife and fluids, the latter with application from the laboratory to localized atmospheric phenomena. He has advanced several DDDAS topics with new methods for application to coherent fluid dynamical regimes. Dr. Ravela proposed and co-organized the Dynamic Data Driven Environmental Systems Science Conference (DyDESS 2014, Cambridge), and then co-organized the first, second, and third general DDDAS conferences (2016 Hartford, 2017 Cambridge, 2020 MIT/Online). Dr. Ravela also teaches Machine Learning with System Dynamics and Optimization, which introduces the informative approach, a key DDDAS concept, to design Learning and Hybrid Stochastic Systems and solve inverse problems and inference.
Alex J. Aved is a senior researcher with the Air Force Research Laboratory, Information Directorate, Rome, NY, USA. His research interests include multimedia databases, stream processing (via CPU, GPU, or coprocessor), and dynamically executing models with feedback loops incorporating measurement and error data to improve the accuracy of the model. He has published over 50 papers and given numerous invited lectures. Previously he was a programmer at the University of Central Florida and database administrator and programmer at Anderson University.
作者簡介(中文翻譯)
Erik P. Blasch 是美國空軍科學研究辦公室的計畫官。他的專注領域包括多域（太空、空中、地面）數據融合、目標追蹤、模式識別和機器人技術。他已發表750篇科學論文、22項專利、30個教學課程和5本書籍。他的榮譽包括軍事感測學會的 Mignogna 數據融合領導獎、IEEE 航空與電子系統學會的 Mimno 最佳雜誌論文獎，以及 IEEE Russ 生物工程獎。他也是國際信息融合學會（ISIF）的創始成員之一。他之前的職位包括萊特州立大學的兼任副教授、加拿大國防研究與發展部的交流科學家，以及空軍研究實驗室的軍官。Blasch 博士是美國航空航天學會（AIAA）的副研究員、光學與儀器工程學會（SPIE）的會士，以及電氣與電子工程師學會（IEEE）的會士。
Frederica Darema 博士：曾擔任高級行政服務（SES）成員及位於維吉尼亞州阿靈頓的空軍科學研究辦公室主任，負責整個空軍的基礎研究投資，並擔任空軍首席數據辦公室的研究主任，以及空軍科學、技術與工程辦公室的副助理部長。她的職業歷程包括：在匹茲堡大學、布魯克海文國家實驗室和施樂博-道爾的研究人員職位；以及在 T.J. Watson IBM 研究中心和 IBM 企業策略小組、國家科學基金會和國防高級研究計畫局的管理和高層職位；以及空軍科學研究辦公室信息、數學和生命科學部門的主任。Darema 博士擁有核物理博士學位，是電氣與電子工程師學會（IEEE）的會士，並獲得其他專業認可。她開創了 DDDAS（動態數據驅動自適應系統）範式，自2000年以來組織並領導研究倡議、計畫、研討會、會議及其他論壇，以促進和推廣基於 DDDAS 的科學和技術進步。
Ravela 博士，2002年獲得博士學位，現任麻省理工學院地球大氣與行星科學系的地球信號與系統組（ESSG）主任。他的主要研究興趣包括統計模式識別、隨機非線性系統和計算智能，應用於地球、行星、氣候和生命。Ravela 博士開創了動態數據驅動的觀測系統，用於野生動物和流體的研究，後者的應用從實驗室延伸到局部大氣現象。他在幾個 DDDAS 主題上推進了新方法，應用於相干流體動力學範疇。Ravela 博士提議並共同組織了動態數據驅動環境系統科學會議（DyDESS 2014，劍橋），並共同組織了第一、第二和第三屆 DDDAS 大會（2016年哈特福德，2017年劍橋，2020年麻省理工學院/線上）。Ravela 博士還教授系統動力學和優化的機器學習課程，介紹了信息化方法，這是設計學習和混合隨機系統以及解決逆問題和推斷的關鍵 DDDAS 概念。
Alex J. Aved 是美國紐約羅馬的空軍研究實驗室信息部門的高級研究員。他的研究興趣包括多媒體數據庫、流處理（通過 CPU、GPU 或協處理器）以及動態執行模型，並結合測量和誤差數據的反饋迴路以提高模型的準確性。他已發表超過50篇論文並進行了多次受邀演講。之前，他曾在中央佛羅里達大學擔任程式設計師，並在安德森大學擔任數據庫管理員和程式設計師。
