%S n Java的問題，透過圖書和論文來找解法和答案更準確安心。 我們找到下列懶人包和總整理

Python面試題目與解答：邁向高薪之路

為了解決%S n Java的問題，作者洪錦魁 這樣論述：

　　展開程式設計師的就業廣告，幾乎都是以Python語言為主流，這本書則是收集國內外各大主流公司的熱門考試主題，Leetcode考題以及筆者認為學習Python應該了解的主流觀念，全部以極詳細、超清楚的程式實例解說，期待讀者可以錄取全球著名企業獲得高薪。   　　Python工程師面試第一個主題當然是測試面試者對於Python語言的瞭解與熟悉程度，內行的面試主管可以經由面試者對於下列Python重點與特色的理解程度，可以很輕易了解面試者Python功力如何？是不是具備真正Python工程師的資格？   　　●認識Python特色 　　●跳脫Java、C/C++邏輯，從Python觀念設計

程式 　　●串列(元組)切片(slicing)、打包(packing)、解包(unpacking) 　　●認識何謂可迭代物件(iterator object) 　　●認識生成式(generator) 　　●認識字典、集合操作 　　●類別與模組 　　●正則表達式      　　面試時間通常不會太長，面試的另一個重點是考演算法，一個看似簡單的題目描述往往暗藏豐富的演算法知識，這時就是訓練讀者的邏輯與思考的能力，在這本書筆者也使用了極豐富與廣泛的演算法題目，詳細說明解題過程，至少在面試時讀者碰上類似考題可以輕鬆面對，在極短的面試時間完成解題，本書的演算法考題包含下列內容：   　　●排序與搜尋 　　

●字串 　　●陣列 　　●鏈結串列 　　●二元樹 　　●堆疊與回溯 　　●數學問題 　　●深度、廣度優先搜尋 　　●最短路徑演算法 　　●貪婪演算法 　　●動態規劃演算法     　　整本書除了內容豐富，適合Python面試工程師外，也可以增強讀者Python功力。   本書特色   　　這是國內第一本針對Python工程師考試的圖書。

%S n Java進入發燒排行的影片

強化資訊通信系統的安全機制設計之研究

為了解決%S n Java的問題，作者林㒥祥 這樣論述：

隨著資訊技術的發展，迄今資訊安全已是全球性的問題，國家對資訊基礎建設的依賴越來越重，隨著網路興起使近年來網路上不斷發生資安事件，除了嚴重影響個人及企業，對國防資訊通信系統的安全也是一大隱憂，隨著各系統介接整合，單一身分認證機制的防護不足，機敏資訊易遭竊取、偽冒或破解等重要議題，使得如何強化資訊網路安全性，已成為當前國軍重視考量之課題。為提升系統的安全性，本研究設計將區塊鏈及智能合約導入訊息交換系統，利用其不可竄改及條件執行、去中心化等特性，由智能合約管控，直至設定條件滿足後，由智能合約驗證身分並自動執行電子訊息交換，設計出適用於強化資通系統之安全機制，不僅符合機密性、完整性、不可否認性等基礎

安全需求外，並能抵禦常見之竊聽及偽冒等網路攻擊手段，更可建立運算速度快，耗費資源少之保護機制，兼顧效能、成本與安全性，有效地防杜機敏訊息失竊風險。

電腦組成與設計：硬體/軟體介面（原書第5版·RISC-V版·英文版）

為了解決%S n Java的問題，作者（美）戴維·A.帕特森 這樣論述：

本書是經典著作《計算機組成與設計》繼MIPS版、ARM版之後的最新版本，這一版專注於RISC-V，是Patterson和Hennessy的又一力作。RISC-V指令集作為開源架構，是專為雲計算、移動計算以及各類嵌入式系統等現代計算環境設計的架構。本書更加關注後PC時代發生的變革，通過實例、練習等詳細介紹最新計算模式，更新的內容還包括平板電腦、雲基礎設施以及ARM（行動計算裝置）和x86 (雲計算)體系結構。 C H A P T E R S 1 Computer Abstractions and Technology 2 1.1 Introduction 3 1.2 Eight Great

Ideas in Computer Architecture 11 1.3 Below Your Program 13 1.4 Under the Covers 16 1.5 Technologies for Building Processors and Memory 24 1.6 Performance 28 1.7 The Power Wall 40 1.8 The Sea Change: The Switch from Uniprocessors to Multiprocessors 43 1.9 Real Stuff: Benchma the Intel Core i7 46 1.

10 Fallacies and Pitfalls 49 1.11 Concluding Remarks 52 1.12 Historical Perspective and Further Reading 54 1.13 Exercises 54 2 Instructions: Language of the Computer 60 2.1 Introduction 62 2.2 Operations of the Computer Hardware 63 2.3 Operands of the Computer Hardware 67 2.4 Signed and Unsigned Nu

mbers 74 2.5 Representing Instructions in the Computer 81 2.6 Logical Operations 89 2.7 Instructions for M Decisions 92 2.8 Supporting Procedures in Computer Hardware 98 2.9 Communicating with People 108 2.10 RISC-V Addressing for Wide Immediates and Addresses 113 2.11 Parallelism and Instructions:

Synchronization 121 2.12 Translating and Starting a Program 124 2.13 A C Sort Example to Put it All Together 133 2.14 Arrays versus Pointers 141 2.15 Advanced Material: Compiling C and Interpreting Java 144 2.16 Real Stuff: MIPS Instructions 145 2.17 Real Stuff: x86 Instructions 146 2.18 Real Stuff:

The Rest of the RISC-V Instruction Set 155 2.19 Fallacies and Pitfalls 157 2.20 Concluding Remarks 159 2.21 Historical Perspective and Further Reading 162 2.22 Exercises 162 3 Arithmetic for Computers 172 3.1 Introduction 174 3.2 Addition and Subtraction 174 3.3 Multiplication 177 3.4 Division 183

3.5 Floating Point 191 3.6 Parallelism and Computer Arithmetic: Subword Parallelism 216 3.7 Real Stuff: Streaming SIMD Extensions and Advanced Vector Extensions in x86 217 3.8 Going Faster: Subword Parallelism and Matrix Multiply 218 3.9 Fallacies and Pitfalls 222 3.10 Concluding Remarks 225 3.11 H

istorical Perspective and Further Reading 227 3.12 Exercises 227 4 The Processor 234 4.1 Introduction 236 4.2 Logic Design Conventions 240 4.3 Building a Datapath 243 4.4 A Simple Implementation Scheme 251 4.5 An Overview of Pipelining 262 4.6 Pipelined Datapath and Control 276 4.7 Data Hazards: Fo

rwarding versus Stalling 294 4.8 Control Hazards 307 4.9 Exceptions 315 4.10 Parallelism via Instructions 321 4.11 Real Stuff: The ARM Cortex-A53 and Intel Core i7 Pipelines 334 4.12 Going Faster: Instruction-Level Parallelism and Matrix Multiply 342 4.13 Advanced Topic: An Introduction to Digital D

esign Using a Hardware Design Language to Describe and Model a Pipeline and More Pipelining Illustrations 345 4.14 Fallacies and Pitfalls 345 4.15 Concluding Remarks 346 4.16 Historical Perspective and Further Reading 347 4.17 Exercises 347 5 Large and Fast: Exploiting Memory Hierarchy 364 5.1 Intr

oduction 366 5.2 Memory Technologies 370 5.3 The Basics of Caches 375 5.4 Measuring and Improving Cache Performance 390 5.5 Dependable Memory Hierarchy 410 5.6 Virtual Machines 416 5.7 Virtual Memory 419 5.8 A Common Framework for Memory Hierarchy 443 5.9 Using a Finite-State Machine to Control a Si

mple Cache 449 5.10 Parallelism and Memory Hierarchy: Cache Coherence 454 5.11 Parallelism and Memory Hierarchy: Redundant Arrays of Inexpensive Disks 458 5.12 Advanced Material: Implementing Cache Controllers 459 5.13 Real Stuff: The ARM Cortex-A53 and Intel Core i7 Memory Hierarchies 459 5.14 Real

Stuff: The Rest of the RISC-V System and Special Instructions 464 5.15 Going Faster: Cache Blo and Matrix Multiply 465 5.16 Fallacies and Pitfalls 468 5.17 Concluding Remarks 472 5.18 Historical Perspective and Further Reading 473 5.19 Exercises 473 6 Parallel Processors from Client to Cloud 490 6

.1 Introduction 492 6.2 The Difficulty of Creating Parallel Processing Programs 494 6.3 SISD, MIMD, SIMD, SPMD, and Vector 499 6.4 Hardware Multithreading 506 6.5 Multicore and Other Shared Memory Multiprocessors 509 6.6 Introduction to Graphics Processing Units 514 6.7 Clusters, Warehouse Scale Com

puters, and Other Message-Passing Multiprocessors 521 6.8 Introduction to Multiprocessor Network Topologies 526 6.9 Communicating to the Outside World: Cluster Netwo 529 6.10 Multiprocessor Benchmarks and Performance Models 530 6.11 Real Stuff: Benchma and Rooflines of the Intel Core i7 960 and the

NVIDIA Tesla GPU 540 6.12 Going Faster: Multiple Processors and Matrix Multiply 545 6.13 Fallacies and Pitfalls 548 6.14 Concluding Remarks 550 6.15 Historical Perspective and Further Reading 553 6.16 Exercises 553 A P P E N D I X The most beautiful thing we can experience is the mysterious. It

is the source of all true art and science. Albert Einstein, What I Believe, 1930 About This Book We believe that learning in computer science and engineering should reflect the current state of the field, as well as introduce the principles that are shaping computing. We also feel that readers

in every specialty of computing need to appreciate the organizational paradigms that determine the capabilities, performance, energy, and, ultimately, the success of computer systems. Modern computer technology requires professionals of every computing specialty to understand both hardware and so

ftware. The interaction between hardware and software at a variety of levels also offers a framework for understanding the fundamentals of computing. Whether your primary interest is hardware or software, computer science or electrical engineering, the central ideas in computer organization and desi

gn are the same. Thus, our emphasis in this book is to show the relationship between hardware and software and to focus on the concepts that are the basis for current computers. The recent switch from uniprocessor to multicore microprocessors confirmed the soundness of this perspective, given sinc

e the first edition. While programmers could ignore the advice and rely on computer architects, compiler writers, and silicon engineers to make their programs run faster or be more energy-efficient without change, that era is over. For programs to run faster, they must become parallel. While the goa

l of many researchers is to make it possible for programmers to be unaware of the underlying parallel nature of the hardware they are programming, it will take many years to realize this vision. Our view is that for at least the next decade, most programmers are going to have to understand the hardw

are/software interface if they want programs to run efficiently on parallel computers. The audience for this book includes those with little experience in assembly language or logic design who need to understand basic computer organization as well as readers with backgrounds in assembly language a

nd/or logic design who want to learn how to design a computer or understand how a system works and why it performs as it does. About the Other Book Some readers may be familiar with Computer Architecture: A Quantitative Approach, popularly known as Hennessy and Patterson. (This book in turn is o

ften called Patterson and Hennessy.) Our motivation in writing the earlier book was to describe the principles of computer architecture using solid engineering fundamentals and quantitative cost/performance tradeoffs. We used an approach that combined examples and measurements, based on commercial s

ystems, to create realistic design experiences. Our goal was to demonstrate that computer architecture could be learned using quantitative methodologies instead of a descriptive approach. It was intended for the serious computing professional who wanted a detailed understanding of computers. A maj

ority of the readers for this book do not plan to become computer architects. The performance and energy efficiency of future software systems will be dramatically affected, however, by how well software designers understand the basic hardware techniques at work in a system. Thus, compiler writers,

operating system designers, database programmers, and most other software engineers need a firm grounding in the principles presented in this book. Similarly, hardware designers must understand clearly the effects of their work on software applications. Thus, we knew that this book had to be much

more than a subset of the material in Computer Architecture, and the material was extensively revised to match the different audience. We were so happy with the result that the subsequent editions of Computer Architecture were revised to remove most of the introductory material; hence, there is much

less overlap today than with the first editions of both books. Why RISC-V for This Edition? The choice of instruction set architecture is

基於距離都卜勒影像之跌倒偵測系統的設計與實現

為了解決%S n Java的問題，作者徐偉倫 這樣論述：

由於近年來深度學習技術的發展及普及，生活中許多的研究與發明，漸漸朝向人工智慧的方向發展，逐漸影響人們的日常體驗與生活，不論是在工商、金融、治安甚至是軍事及教育等等所有都能看到相關應用的出現，根據台灣衛福部統計處資料，在2019年跌倒事故傷害而過世的人竟然位居排行第二，故居家照護等相關應用也成了AI技術的一個重要議題，而跌倒偵測便是此次論文的研究重點。有別於市售的穿戴式裝置如蘋果手錶和項鍊式緊急通報跌倒偵測器，利用設備的陀螺移、三軸加速度計或ECG心電圖等技術來判斷，為了避免人員發生意外時未配戴裝置很引發憾事，我們參考了攝影機影像辨識的技術，在特定場域裝設裝置判斷人員有無跌倒狀況，但礙於隱私權

問題，會讓人有所顧慮，所以我們選擇了在場域架設雷達裝置來發展我們的跌倒偵測系統。透過頻率調變連續波雷達(FMCW)，收集其回傳的原始資料(Raw data)，進行計算，產出範圍都卜勒圖(Range Doppler Image)及長時間間格的都卜勒直方圖(Long Time Interval Range Doppler Histogram)，觀察其資料特徵，對圖片及影像進行資料分析及編輯，並撰寫輔助工具，完成資料的收集及標籤(Label)，最後則是設計觸發(Trigger)模型，辨識圖片距離及速度變化量明顯的圖形，結合根據資料型態所自定義的的演算法完成觸發的判斷，再將有觸發的情形結合都卜勒長方圖

丟至下一層基於雙向長短時記憶循環神經網路(Bi-directional Long Short-Term Memory)模型所設計的深度學習模型來做最後跌倒情形的判斷，並設計的簡易的告警機制，完成了高達90%以上準確率的跌倒偵測系統模型。