Ra japanese的問題，透過圖書和論文來找解法和答案更準確安心。 我們找到下列訂位、菜單、價格優惠和問答集

Life-Cycle Greenhouse Gas Emissions of Commercial Buildings: An Analysis for Green-Building Implementation Using a Green Star Ra

為了解決Ra japanese的問題，作者Tran, Cuong N. N.,Tam, Vivian,Le, Khoa N. 這樣論述：

This book develops a model to evaluate and assess life-cycle greenhouse gas emissions based on typical Australian commercial building design options. It also draws comparisons between some of the many green building rating tools that have been developed worldwide to support sustainable developmen

t. These include: Leadership in Energy and Environmental Design (LEED) by the United States Green Building Council (USGBC), Building Research Establishment Environmental Assessment Method (BREEAM) by the Building Research Establishment, Comprehensive Assessment System for Building Environmental Effi

ciency (CASBEE) by the Japanese Sustainable Building Consortium, and Green Star Environmental Rating System by the Green Building Council of Australia.Life-cycle assessment (LCA), life-cycle energy consumption, and life-cycle greenhouse gas emissions form the three pillars of life-cycle studies, whi

ch have been used to evaluate environmental impacts of building construction. Assessment of the life-cycle greenhouse gas emissions of buildings is one of the significant obstacles in evaluating green building performance. This book explains the methodology for achieving points for the categories as

sociated with reduction of greenhouse gas emissions in the Australian Green Star rating system. The model for the assessment uses GaBi 8.7 platform along with Visual Basic in Microsoft Excel and shows the relationship between the building’s energy consumption and greenhouse gas emissions released du

ring the lifetime of the building. The data gathered in the book also illustrates that the green building design and specifications are becoming more popular and are being increasingly utilized in Australia. This book is important reading for anyone interested in sustainable construction, green desi

gn and buildings and LCA tools.

Ra japanese進入發燒排行的影片

豬流行性下痢病毒核酸於田間豬場的環境分布

為了解決Ra japanese的問題，作者蔣昕恆 這樣論述：

豬流行性下痢 (porcine epidemic diarrhea; PED) 引起豬隻急性嘔吐及下痢，因其在新生仔豬可造成高死亡率，故造成豬場嚴重損失，然而在台灣尚無商業化之疫苗，因此以生物安全措施預防及控制豬流行性下痢成為最根本之方法。本研究以即時定量聚合酶鏈鎖反應 (real-time quantitative polymerase chain reaction; real-time qPCR) 檢測4場PED爆發場與1場非爆發場環境中PEDV (porcine epidemic diarrhea virus; PEDV) 之病原核酸，尋找病原可能藏匿的地點，並透過問卷調查獲取有關養豬

場生物安全資料，了解養豬場生物安全等級現況，以評估試驗養豬場中可能的生物安全風險因子。本實驗共蒐集434個環境樣本，爆發場環境樣本的PEDV總體陽性率為39.2％ (149/380)，而非爆發場之所有樣本皆為陰性 (0/54)。於爆發場中，分娩舍之所有樣本，包含常在性的仔豬保溫地墊、隔門及教槽盤、母豬飲水乳頭及飼料槽、內部走廊、風扇開關、風扇葉片、水濂片、門把，可移動性的器械如：推車、注射器、畫記筆、場內工作人員之衣物、手及雨鞋，皆可檢測出PEDV核酸；且相較於未消毒的分娩舍，消毒後的分娩舍設施之檢測陽性率及病毒量皆較低。於保育舍及肉豬舍於本實驗並未檢測出PEDV核酸，但於分娩前母豬之糞便樣本

中，可檢測到病原的核酸。綜合上述，顯示於PED爆發場PEDV可能無所不在，且可能因棟舍消毒不完全，或於不完善的生物安全措施，藉由汙染區域或物品進行不同棟舍間或不同批次間的傳播。在問卷調查的結果中，多數豬場在清潔與消毒方面相對重視，但仍建議加強害蟲、害獸與鳥類的防治措施。另於實施生物安全措施後，也應進行環境監測等效果評估，以了解生物安全的實施成效。

Industrial Iot Application Architectures and Use Cases

為了解決Ra japanese的問題，作者Malarvizhi, Nandagopal,Annamalai, Suresh,Neeba, E. A. 這樣論述：

As the number of Internet of Things (IoT) elements grows exponentially, their interactions generate massive amount of raw, multi-structured data. The challenge this data presents is to transform this raw data to information and knowledge, which can be used by people and systems to make intelligent d

ecisions. Industrial IoT Application Architectures and Use Cases explores how artificial intelligence (AI), data analytics, and IoT technology combine to promote intelligence decision-making and automation in a range of industries. With the faster and more stable AI algorithms and approaches, knowle

dge discovery and dissemination from IoT-device data can be simplified and streamlined. An era of powerful cognitive technology is beginning due to cloud-based cognitive systems that are forming the foundation of game-changing intelligent applications. This book presents next-generation use-cases of

IoT and IoT data analytics for a variety of industrial verticals including: An Intelligent IoT framework for smart water managementAn IoT-enabled smart traffic control system for congestion control and smart traffic management An intelligent airport system for airport management and security survei

llanceAn IoT framework for healthcare to integrate and report patient information Fuzzy scheduling with IoT for tracking and monitoring hotel assets An IoT system for designing drainage systems and monitoring drainage pipes Predictive maintenance of plant equipment to decide the actual mean time to

malfunction Integrated neural networks and IoT systems for predictive equipment maintenance IoT integration in blockchain for smart waste management The book also includes a chapter on the IoT paradigm and an overview of uses cases for personal, social, and industrial applications. Dr. N. Malarvi

zhi, B.E., M.E., PhDcurrently working as the Professor in the Department of Computer Science and Engineering at Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai-62, Tamilnadu, India. She is having more than 18 years of teaching experience. She has written a book t

itled ＂Computer Architecture and Organization＂, Eswar Press, The Science and Technology Book Publisher, Chennai. She serves as a reviewer for many reputed journals. She has published numerous papers in International Conferences and Journals. Her area of interest includes Parallel and Distributed Com

puting, Grid Computing, Cloud Computing, Big Data Analytics, Internet of Things, Computer Architecture and Operating Systems. She is a life member of Computer Society of India (CSI), Indian Society for Technical Education (ISTE), IARCS and IAENG. She is a Senior Member of IEEE and IEEE Women in Engi

neering (WIE). She is a Member of Association for Computing Machinery (ACM) and The Institution of Engineering and Technology (IET).Dr. A. Suresh B.E., M.Tech., Ph.D works as the Professor & Head, Department of the Computer Science and Engineering in Nehru Institute of Engineering & Technology, Coim

batore, Tamil Nadu, India. He has been nearly two decades of experience in teaching and his areas of specializations are Data Mining, Artificial Intelligence, Image Processing, Multimedia and System Software. He has published two patent and 85 papers in International journals. He has published 5 cha

pters in the book title An Intelligent Grid Network Based on Cloud Computing Infrastructures in IGI Global Publisher. He has published more than 40 papers in National and International Conferences. He has served as a editor / reviewer for Springer, Elsevier, Wiley, Inderscience journals etc... He is

a member of ISTE, MCSI, IACSIT, IAENG, MCSTA and Global Member of Internet Society (ISOC). He has organized several National Workshop, Conferences and Technical Events. He is regularly invited to deliver lectures in various programmes for imparting skills in research methodology to students and res

earch scholars. He has published four books, in the name of Data structures & Algorithms, Computer Programming, Problem Solving and　Python　Programming and Programming in ＂C＂ in DD Publications, Excel Publications and Sri Maruthi Publisher, Chennai, respectively. He has hosted two special sessions fo

r IEEE sponsored conference in Osaka, Japan and Thailand.Dr. E. A. Neeba, currently working as an Assistant Professor in the Department of Information Technology at Rajagiri School of Engineering & Technology, Kochi, Kerala, which is affiliated to the A.P.J Abdul Kalam Technological University, Kera

la. She received her doctoral degree from Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, Tamil Nadu. She completed her Masters in Computer Science & Engineering from SRM Institute of Science and Technology, Chennai. Her research interests include Analysis of dat

a, Data Mining and Big Data, knowledge representation, and ontology, both from the theoretical perspective and their application to natural language understanding, reasoning, information visualization, and interoperability. Having a rich industrial experience of around 10 years prior to joining acad

emia, and also she has publications in around 10 SCI/ SCIE/Scopus indexed international journals and a few national journals. An active participant in various conferences and workshops on data mining, she is currently involved in several projects in this field. She was entrusted with leadership posi

tions such as the Accreditation coordinator for the college, and Head of the Quality Cell, besides organizing various national and international events.Dr. Pethuru Ra Chelliah has been working as the chief architect in the Site Reliability Engineering (SRE) Center of Excellence, Reliance Infocomm Lt

d. (RIL), Bangalore. He previously worked as a cloud infrastructure architect in the IBM Global Cloud Center of Excellence (CoE), IBM India Bangalore for four years. Prior to that, He had a long stint as TOGAF-certified enterprise architecture (EA) consultant in Wipro Consulting Services (WCS) Divis

ion. He also worked as a lead architect in the corporate research (CR) division of Robert Bosch, Bangalore. In total, He have gained more than 17 years of IT industry experience and 8 years of research experience. He obtained his PhD through CSIR-sponsored PhD degree in Anna University, Chennai and

continued the UGC-sponsored postdoctoral research in the department of Computer Science and Automation, Indian Institute of Science, Bangalore. Thereafter, He was granted a couple of international research fellowships (JSPS and JST) to work as a research scientist for 3.5 years in two leading Japane

se universities. Regarding the publications, He have published more than 30 research papers in peer-reviewed journals such as IEEE, ACM, Springer-Verlag, Inderscience, etc. He have authored 7 books thus far and He focus on some of the emerging technologies such as IoT, Cognitive Analytics, Blockchai

n, Digital Twin, Docker-enabled Containerization, Data Science, Microservices Architecture, etc. He have contributed 25 book chapters thus far for various technology books edited by highly acclaimed and accomplished professors and professionals. The CRC Press, USA had also released his first book ti

tled as ＂Cloud Enterprise Architecture＂ in the year 2012 and you can find the book details in the page http: //www.crcpress.com/product/isbn/9781466502321 He has edited and authored a book on the title＂ Cloud Infrastructures for Big Data Analytics＂ published by IGI International USA in March 2014. A

new book on the title＂ Smarter Cities: the Enabling Technologies and Tools＂ by CRC Press, USA, is to hit the market in the month of June 2015. He has collaborating with a few authors to publish a book on the title ＂High-Performance Big Data Analytics＂ to be published by Springer-Verlag in the year

2015.Dr. Jenn-Wei Lin received the M.S. degree in computer and information science from National Chiao Tung University, Hsinchu, Taiwan, in 1993, and the Ph.D. degree in electrical engineering from National Taiwan University, Taipei, Taiwan, in 1999. He was a Researcher with Chunghwa Telecom Co., Lt

d., Taoyuan, Taiwan, from 1993 to 2001. He is currently a Full Professor with the Department of Computer Science and Information Engineering, Fu Jen Catholic University, Taiwan. His current research interests include cloud computing, mobile computing and networks, distributed systems, and fault-tole

rant computing.

以台灣人體生物資料庫世代追蹤研究探討肝功能參數與新發生高血壓關聯

為了解決Ra japanese的問題，作者劉宜學 這樣論述：

之前的研究對於肝功能參數和高血壓之間的關係，其結果並不一致。此外目前的相關研究中仍缺乏大型的世代追蹤研究。因此，這項縱貫性研究旨在利用台灣人體生物資料庫的世代追蹤研究來探討肝功能參數與新發生高血壓之間的關係。在這項研究中，我們評估的肝功能參數，包括麩胺酸苯醋酸轉氨基酵素（aspartate aminotransferase, AST）、胺酸丙酮酸轉氨基酵素（alanine aminotransferase, ALT）、白蛋白(albumin)、α-胎兒蛋白（alpha-fetoprotein, AFP）、總膽紅素(total bilirubin )和麩胺轉酸脢（γ-Glutamyltrans

ferase,GGT）。本研究中共分析了21,293名沒有高血壓病史的參與者。在平均3.9年的追蹤中，有3,002名參與者患上了新發生的高血壓。在多變量分析中顯示，較高的AST（勝算比，1.004；95%信賴區間，1.001至1.007；p= 0.014），較高的ALT（勝算比，1.004；95%信賴區間，1.002至1.006；p< 0.001），較高的白蛋白（勝算比，1. 897；95%信賴區間，1.573至2.286；p < 0.001），和較高的GGT（勝算以，1.004；95%信賴區間，1.003至1.005；p < 0.001）與所有研究參與者的新發生高血壓顯著相關。在對ALT指數

≤正常值2倍（80 u/l）的參與者（n = 20,983）的次分析中，多變量分析表明，較高的ALT（勝算比，1.009；95%信賴區間，1.005至1.012；p