週的問題，透過圖書和論文來找解法和答案更準確安心。 我們找到下列評價、門市、特惠價和推薦等優惠

Programming Google Cloud: Building Cloud Native Applications with Gcp

為了解決週的問題，作者Costa, Rui 這樣論述：

Companies looking to move enterprise applications to the cloud are busy weighing several options, such as the use of containers, machine learning, and serverless computing. There’s a better way. Instead of helping you fit your use case to individual technologies, this practical guide explains how

to use these technologies to fit your use case. Author Rui Costa, a learning consultant with Google, demonstrates this approach by showing you how to run your application on Google Cloud. Each chapter is dedicated to an area of technology that you need to address when planning and deploying your a

pplication. This book starts by presenting a detailed fictional use case, followed by chapters that focus on the building blocks necessary to deploy a secure enterprise application successfully. Build serverless applications with Google Cloud Functions Explore use cases for deploying a real-time mes

saging service Deploy applications to Google Kubernetes Engine (GKE) Build multiregional GKE clusters Integrate continuous integration and continuous delivery with your application Incorporate Google Cloud APIs, including speech-to-text and data loss prevention Enrich data with Google Cloud Dataflow

Secure your application with Google Cloud Identity-Aware Proxy Explore BigQuery and visualization with Looker and BigQuery SDKs

週進入發燒排行的影片

照顧者對於育兒APP使用經驗及滿意度之研究

為了解決週的問題，作者張可橙 這樣論述：

自2020年COVID-19疫情延燒至今，對家庭帶來很大的生活改變，其中除了育兒日常之外，在防疫期間家庭互動型態也正悄悄地改變。因此，為了解家長育兒實際需求以及使用相關資源是重要的趨勢。家有嬰幼兒的父母需要紀錄各種嬰幼兒的生活紀錄，以確保嬰幼兒的健康狀況及健康檢查，如何善用各項育兒資源，將嬰兒照護資訊化，家長可以即時了解子女目前的狀況。隨著資訊科技進步，智慧型手機的流行，數位工具也愈來愈行動化及便利性，因此針對嬰幼兒各項活動的APP也蓬勃發展。目前市場上育兒APP種類眾多，但深入探討實際使用與功能是否滿足照顧者需求的研究較少。為了解照顧者對於使用育兒APP相關經驗及滿意度為何？研究首先依據文

獻探討嬰幼兒相關文獻，了解行動裝置在嬰幼兒保育相關之領域應用，再將市面上手持行動裝置平台皆有上架的育兒APP，將各個的功能做比較與統整，以問卷調查方式了解照顧者對於育兒APP實際使用情形以及滿意度。本研究採用科技接受模式為研究架構，加入受試者背景變項探討各構面關係，利用SPSS統計分析方法來驗證各項研究假設。研究結果如下：探討照顧者對於育兒APP的使用經驗之現況與差異。「認知有用性」及「認知易用性」會影響「使用意願」；「使用意願」會影響「滿意度」。根據研究結論，提出相對應研究建議，供未來建置應用程式系統可以擴充功能參考，讓使用者滿意度更加提升。

A Comprehensive Guide to Measuring the Power and Energy of Modern Systems

為了解決週的問題，作者Lee, Victor,Choi, Jee Whan,Cameron, Kirk 這樣論述：

Victor Lee is a principal engineer and research scientist at Intel’s Parallel Computing Lab. His research interests include emerging applications, application analysis and auto-tuning as well as computer architecture. He is currently working on analyzing the HW/SW interactions between HPC/Big-data a

pplications and modern processor architecture and on developing innovative architecture features to improve application and processor (performance and energy) efficiency. Victor received a B.S. in Electrical Engineering from University of Washington in 1994, S.M. in Electrical Engineering and Comput

er Science from Massachusetts Institute of Technology in 1996. He joined Intel in 1997 and had worked on many Intel processors include Intel Pentium Pro, Intel Pentium 4, and Intel Itanium processors. In 2002, Victor moved to Intel Labs and spearheaded the many-core research which eventually lead to

the Intel Many Integrated Core architecture and the first Intel Xeon Phi coprocessor product. He is a senior member of IEEE. He has 30+ professional publications, 15+ granted patents and more than 30 pending patent applications worldwide. Jee Choi is a postdoctoral research at IBM TJ Watson Researc

h Center. Kirk W. Cameron is a professor of computer science and a research fellow in the College of Engineering at Virginia Tech. The central theme of his research is to improve power and performance efficiency in high performance computing (HPC) systems and applications. Prof. Cameron is a pioneer

and leading expert in Green Computing. Cameron is also the Green IT columnist for IEEE Computer, Green500 co-founder, founding member of SPECPower, EPA consultant, Uptime Institute Fellow, and co-founder of power management software startup company MiserWare. His advanced power measurement software

infrastructure for research, (PowerPack), is used by dozens of research groups around the world. His power management software, Granola, is used by hundreds of thousands of people in more than 160 countries.

使用理財機器人的行為意圖之研究

為了解決週的問題，作者林昱德 這樣論述：

本研究以探討使用者使用理財機器人之使用行為相關研究，目的為探討使用者使用因素，提供未來後續業界之參考，以及找出現階段理財機器人使用者的描述性統計分析。本研究以有使用過銀行推出之理財機器人作為研究對象，於 2022年 7月 14日於網路進行正式問卷投放，回收後進行資料分析，經過問卷後台揭露，本次問卷研究投放人數為 4765 人，回收 490 份問卷，有效得 387份，有效回收率為 78.79%。研究架構以 UTAUT2 為基礎，並加入感知風險成為新的會影響使用意圖的因素。研究結果顯示，績效預期、社群影響、促進條件、價格價值以及習慣會對行為意圖產生顯著正向影響；努力預期以及感知風險對行為意圖則是

沒有影響；行為意圖以及習慣對使用行為有顯著正向影響；促進條件對使用意圖則無影響。希冀本研究可以作為相關單位的參考依據。