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関連する概念動画

Indicators02:39

Indicators

Certain organic substances change color in dilute solution when the hydronium ion concentration reaches a particular value. For example, phenolphthalein is a colorless substance in any aqueous solution with a hydronium ion concentration greater than 5.0 × 10−9 M (pH < 8.3). In more basic solutions where the hydronium ion concentration is less than 5.0 × 10−9 M (pH > 8.3), it is red or pink. Substances such as phenolphthalein, which can be used to determine the pH of a solution, are called...
Introduction to Cognitive Psychology01:20

Introduction to Cognitive Psychology

Cognitive psychology is the field of psychology dedicated to examining how people think. It attempts to explain how and why we think the way we do by studying the interactions among human thinking, emotion, creativity, language, and problem-solving, as well as other cognitive processes. Cognitive psychology studies how information is processed and manipulated in remembering, thinking, and knowing.
This field emerged in the mid-20th century, following a period dominated by behaviorism, which...
Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
Guidelines and Strategies for Safe Computer Charting01:18

Guidelines and Strategies for Safe Computer Charting

The guidelines and strategies provided by the American Nurses Association (ANA) and the Canadian Nurses Association (CNA) offer essential principles for ensuring safe and secure computer charting systems in healthcare settings. Let's break down each recommendation:
Maintain Confidentiality and Security:
Statgraphics01:10

Statgraphics

Statgraphics is a comprehensive statistical software suite designed for both basic and advanced data analysis. Originating in 1980 at Princeton University under Dr. Neil W. Polhemus, it was one of the pioneering tools for statistical computing on personal computers, with its public release in 1982 marking an early milestone in data science software. Over the years, it has evolved into a robust platform for data science, offering tools for regression analysis, ANOVA, multivariate statistics,...
Control Systems: Applications01:25

Control Systems: Applications

Electrical engineering plays a pivotal role in our daily lives, with control systems at the heart of many applications, from home appliances to sophisticated space shuttles. Control systems manage and regulate the behavior of devices and processes, ensuring they function safely, correctly, and efficiently.
In modern vehicles, control systems manage various functions to enhance performance and safety. The steering wheel and accelerator are primary inputs in a car's control system. The direction...

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関連する実験動画

Updated: Jul 12, 2026

Bridging the Technology Divide in the COVID-19 Era: Using Virtual Outreach to Expose Middle and High School Students to Imaging Technology
09:55

Bridging the Technology Divide in the COVID-19 Era: Using Virtual Outreach to Expose Middle and High School Students to Imaging Technology

Published on: September 28, 2022

科学と技術のコンピューター:初期の兆候

H Gerola, R E Gomory

    Science (New York, N.Y.)
    |July 6, 1984
    PubMed
    まとめ

    コンピュータ技術は急速に進歩しており,より小さく,速く,より安価な回路により,年間20%のコンピューティングパワーを増加させると予測されています. 異なるプロフェッショナルは,この強化されたコンピューティングパワーを異なる方法で利用し,科学研究とエンジニアリングに影響を与えます.

    科学分野:

    • コンピュータサイエンス コンピュータサイエンス
    • エンジニアリング エンジニアリング
    • 科学的研究 科学的研究

    背景:

    • コンピュータ技術は,過去20年間で論理と記憶の分野で急速な進歩を遂げました.
    • 継続的な成長が期待され,回路速度,メモリ,ストレージ,プリンター,ディスプレイの大幅な改善が期待されています.
    • コンピューティングシステム能力の年間成長率は約20%と予測されています.

    研究 の 目的:

    • 急速に進歩するコンピュータ技術の進化と利用を予測する.
    • コンピューティング能力の増大が科学およびエンジニアリング活動にどのように影響するかを理解する.
    • コンピュータ技術に対する技術者の異なる反応を観察する.

    主な方法:

    • リトグラフィック技術の動向とその回路の小型化と速度への影響の分析.
    • コンピューティングシステムの将来の成長率の予測.
    • 研究室の技術スタッフのユーザー行動と技術採用パターンの観察.

    主要な成果:

    • この10年後には,CPUの速度を10倍に増やし,シングルチップのマイクロプロセッサはさらに増加すると予想されている.
    • エンジニアは,コンピューティングパワー,ディスプレイ,コミュニケーションを,比較的均等に活用します.

    さらに関連する動画

    Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction
    16:23

    Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction

    Published on: February 26, 2014

    Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
    05:30

    Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

    Published on: September 8, 2023

    関連する実験動画

    Last Updated: Jul 12, 2026

    Bridging the Technology Divide in the COVID-19 Era: Using Virtual Outreach to Expose Middle and High School Students to Imaging Technology
    09:55

    Bridging the Technology Divide in the COVID-19 Era: Using Virtual Outreach to Expose Middle and High School Students to Imaging Technology

    Published on: September 28, 2022

    Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction
    16:23

    Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction

    Published on: February 26, 2014

    Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
    05:30

    Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

    Published on: September 8, 2023

  • マネジメントはコミュニケーションを優先し,科学者はコンピューティングパワーを重視し,最も多くのデータを表示します.

    • 結論:

    • コンピュータ技術の急速な進化,特に処理能力とディスプレイの急速な進化は,科学研究とエンジニアリングに大きな影響を与えています.
    • 異なるプロフェッショナルグループ (エンジニア,経営者,科学者) は,これらの技術的進歩を独自のニーズに基づいて,異なる方法で採用し,利用しています.
    • これらのユーザー固有の採用パターンを理解することは,さまざまな技術分野におけるコンピューティングパワーの将来の統合と影響を予測するために不可欠です.