• 제목/요약/키워드: notebook computer

검색결과 112건 처리시간 0.025초

주피터 노트북에서 자동 평가 시스템의 문제 제시를 위한 방안 탐구 (Exploring how to present the problem of Automatic Assessment system in Jupyter Notebook)

  • 고학능;이영준
    • 한국컴퓨터정보학회:학술대회논문집
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    • 한국컴퓨터정보학회 2023년도 제67차 동계학술대회논문집 31권1호
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    • pp.221-222
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    • 2023
  • 본 연구에서는 주피터 노트북에서 자동 평가 시스템을 활용하기 위한 방안으로 자동 평가 시스템의 문제를 저장하고 제시하는 방안에 대해서 연구하였다. 자동 평가 시스템은 학습자가 직접 프로그래밍을 하고 바로 피드백을 받을 수 있는 장점이 있다. 주피터 노트북에서 자동 평가 시스템을 제공하는 nbgrader와 코들의 장점을 바탕으로 문제 제시 방안은 다음과 같다. 문제는 HTML 태그를 이용해 서식 있는 형태로 서버에 저장한다. 주피터 노트북에서 IPython.display 모듈의 display와 HTML 명령어를 사용하여 문제를 출력하면 코드셀 출력창에 서식 있는 HTML 문서를 출력하여 학습자에게 가독성 있게 문제를 제시할 수 있다.

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Link Voltage Adjustment Converter Employing Load Power Estimator for Notebook Computer Adaptor

  • Choi, Seong-Wook;Lee, Byoung-Hee;Lee, Keun-Wook;Ryu, Byoung-Woo;Moon, Gun-Woo
    • 전력전자학회:학술대회논문집
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    • 전력전자학회 2008년도 하계학술대회 논문집
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    • pp.348-350
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    • 2008
  • A link voltage adjustment converter employing load power estimator for notebook computer adaptor is proposed. It is consisted of the boost converter as a power factor correction stage and the LLC resonant converter as a DC/DC conversion stage with a newly introduced link voltage adjustment method employing load power estimator, which helps to reduce the transformer size and peak of output voltage ripple, maintaining high efficiency over all the load condition. Experimental results with 85W converter are given to verify the validity of the proposed circuit.

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An Advanced Correlation Algorithm between GTEM and OATS for Radiated Emission Tests

  • Lee, Ae-Kyoung
    • ETRI Journal
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    • 제17권3호
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    • pp.45-63
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    • 1995
  • This paper proposes an algorithm to improve the correlation between giga-hertz transverse electromagnetic (GTEM) cell and open area test site (OATS). It is based on the dipole modeling process of an unknown source object in a GTEM cell and on the evaluation of the approximate far field equations correlated with measured GTEM powers at output port of the GTEM cell. In this algorithm, the relative phase differences between dipole moments play an important part in modeling the test object as a set of dipoles and offer stable calculation of emission values. The radiated emission test using this algorithm requires fifteen orientations of equipment under test, but the increased orientations as compared with the previous method have little effect on the time needed for testing. Radiation from a notebook computer has been tested for statistical analysis of the correlation between GTEM data and OATS data. The emission test results of the notebook computer show that the mean, the standard deviation, and the correlation coefficient are -0.62, 1.99, and +0.85, respectively. These figures indicate that this algorithm provides improved accuracy in the measurement of electromagnetic emissions over the previous method.

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Wellness Prediction in Diabetes Mellitus Risks Via Machine Learning Classifiers

  • Saravanakumar M, Venkatesh;Sabibullah, M.
    • International Journal of Computer Science & Network Security
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    • 제22권4호
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    • pp.203-208
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    • 2022
  • The occurrence of Type 2 Diabetes Mellitus (T2DM) is hoarding globally. All kinds of Diabetes Mellitus is controlled to disrupt over 415 million grownups worldwide. It was the seventh prime cause of demise widespread with a measured 1.6 million deaths right prompted by diabetes during 2016. Over 90% of diabetes cases are T2DM, with the utmost persons having at smallest one other chronic condition in UK. In valuation of contemporary applications of Big Data (BD) to Diabetes Medicare by sighted its upcoming abilities, it is compulsory to transmit out a bottomless revision over foremost theoretical literatures. The long-term growth in medicine and, in explicit, in the field of "Diabetology", is powerfully encroached to a sequence of differences and inventions. The medical and healthcare data from varied bases like analysis and treatment tactics which assistances healthcare workers to guess the actual perceptions about the development of Diabetes Medicare measures accessible by them. Apache Spark extracts "Resilient Distributed Dataset (RDD)", a vital data structure distributed finished a cluster on machines. Machine Learning (ML) deals a note-worthy method for building elegant and automatic algorithms. ML library involving of communal ML algorithms like Support Vector Classification and Random Forest are investigated in this projected work by using Jupiter Notebook - Python code, where significant quantity of result (Accuracy) is carried out by the models.

BEGAN을 통해 한국인 얼굴 데이터 생성을 하는데 최적의 HyperParameter (Optimal Hyper Parameter for Korean Face Data Generation with BEGAN)

  • 조규철;김산
    • 한국컴퓨터정보학회:학술대회논문집
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    • 한국컴퓨터정보학회 2021년도 제64차 하계학술대회논문집 29권2호
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    • pp.459-460
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    • 2021
  • 본 논문에서는 BEGAN을 활용한 한국인 얼굴 데이터 생성을 위한 최적의 Hyper Parameter를 제안한다. 연구에서는 GAN의 발전된 모델인 BEGAN을 이용한다. 위의 모델을 작성하기 위하여 본 논문에서는 Anaconda 기반의 Jupyter Notebook에서 Python Tensorflow 모델을 작성하여 테스트하고, 만들어진 모델을 FID를 통해 모델의 성능을 비교한다. 본 연구에서는 제안하는 방법들을 통해서 만들어진 모델을 이용해 한국인 얼굴 데이터를 구하고, 생성된 이미지에 대한 정량적인 평가를 진행한다.

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노트북 거치대가 건강한 젊은 성인 손목관절근육의 생체역학적 특징에 미치는 영향 (Effects of a Notebook Computer Supporter on Biomechanical Characteristics in Wrist Joint Muscles of Healthy Young Adults)

  • 마성룡;송창순
    • PNF and Movement
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    • 제19권3호
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    • pp.391-399
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    • 2021
  • Purpose: As laptop use increases throughout the COVID-19 pandemic and its use outside of traditional workstations proliferates, it is imperative to expand the limited research available regarding ergonomic exposure. This study aimed to identify the effects of a laptop supporter on biomechanical characteristics in the wrist joint muscles of healthy young adults. Methods: This was a cross-sectional observational study design with thirty-four healthy young adults as participants. They conducted a typing exercise performed under two different conditions, which were with and without a notebook computer supporter. This study measured the biomechanical characteristics of the muscles of the wrist joints including the flexor carpi ulnaris (FCU), the flexor carpi radialis (FCR), the extensor carpi radialis longus (ECRL), and the extensor carpi ulnaris (ECU). Measurements were taken three times: before typing, immediately after typing for 30 minutes with a supporter, and immediately after typing for 30 minutes without a supporter. The statistical method to compare the three different measurement conditions was the repeated measures ANOVA. Results: The participants showed significantly different levels of dynamic stiffness in both the FCU before typing and immediately after 30 minutes of typing with a supporter, and showed significantly different levels of dynamic stiffness in the FCR before typing and immediately after 30 minutes of typing with a supporter. The dynamic stiffness level immediately after 30 minutes of typing without a supporter was significantly different than that immediately after 30 minutes of typing with a supporter. However, the muscle tone was not significantly different among the three different conditions. Conclusion: The results of this study revealed that a laptop supporter used to correct the eye level of the electronic screen increases the dynamic stiffness of the wrist joint flexors, so it is necessary to consider the neutral position of the wrist joint during typing.

열간압연용 롤 정밀 측정시스템 개발 (Development of Precise Measuring System for Hot Strip Mill's Rolls)

  • 이성진;이영진
    • 한국공작기계학회:학술대회논문집
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    • 한국공작기계학회 2002년도 춘계학술대회 논문집
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    • pp.614-618
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    • 2002
  • In hot strip mills, Portable Roll Scanner (the portable roll surface temperature and profile measuring device) can be used to calibrate on-line Process models for strip crown and flatness by measuring the thermal expansion and wear profile of the rolls. And the surface temperature measurement can be used to optimize the roll cooling system. Portable Roll Scanner consists of the measuring device, which has two contact inductive distance transducers for roll profile measurement and one infrared Pyrometer for surface temperature measurement, and computer-based controller that is equipped with the measuring device. By the wireless data communication, the data is transferred to the memory of notebook for further analysis. After roll extraction from mills, Portable Roll Scanner measure the roll profile and surface temperature simultaneously along the work roll face and display the results in the TFT color monitor of notebook. Portable Roll Scanner is useful at mill-side and roll grinding shop.

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Development of Digital Stethoscope Diagnosis System for Cardiac Disorders

  • Park, Kyi-Hwan;Jiang, Zhongwei
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2001년도 ICCAS
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    • pp.107.3-107
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    • 2001
  • This paper is concerned with the development of a simple digital stethoscope system for diagnosis of cardiac disorders. This system consists of an electronic stethoscope, IC sound recorder and a notebook computer. The cardiac sound is easily acquired by the electronic stethoscope and then recorded in IC memory stick so that the digital cardiac signal can be simply transmitted to the computer for signal display, disease diagnosis, and personal history record. A software is built with functions displaying the sound graphically and replaying the sound clearly. Further, a neural network recognition system for automatic diagnosis of cardiac disorders is also added to the software.

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휴대폰을 이용한 m-learning 구현 (Utilizing Mobile Phones for m-Iearning)

  • 이겸직;류상훈
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2006년도 추계학술발표대회
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    • pp.641-644
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    • 2006
  • e-learning에서 m-learning으로 진행함에 따라 기존에 사용하던 PDA, Notebook 이 아닌 일반 사용자들이 대부분 가지고 있는 휴대폰을 학습도구로 이용, 다양한 형식의 e-learning contents를 m-learning contents로 변환 활용하기 위하여 화면 capture 기법을 활용하고 무선통신망을 배제하고 유선통신망을 이용하여 서비스 할 수 있는 모델을 제시한다.

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Heart Disease Prediction Using Decision Tree With Kaggle Dataset

  • Noh, Young-Dan;Cho, Kyu-Cheol
    • 한국컴퓨터정보학회논문지
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    • 제27권5호
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    • pp.21-28
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    • 2022
  • 심혈관질환은 심장질환과 혈관질환 등 순환기계통에 생기는 모든 질병을 통칭한다. 심혈관질환은 2019년 사망의 1/3을 차지하는 전 세계 사망의 주요 원인이며, 사망자는 계속 증가하고 있다. 이와 같은 질병을 인공지능을 활용해 환자의 데이터로 미리 예측이 가능하다면 질병을 조기에 발견해 치료할 수 있을 것이다. 본 연구에서는 심혈관질환 중 하나인 심장질환을 예측하는 모델들을 생성하였으며 Accuracy, Precision, Recall의 측정값을 지표로 하여 모델들의 성능을 비교한다. 또한 Decision Tree의 성능을 향상시키는 방법에 대해 기술한다. 본 연구에서는 macOS Big Sur환경에서 Jupyter Notebook으로 Python을 사용해 scikit-learn, Keras, TensorFlow 라이브러리를 이용하여 실험을 진행하였다. 연구에 사용된 모델은 Decision Tree, KNN(K-Nearest Neighbor), SVM(Support Vector Machine), DNN(Deep Neural Network)으로 총 4가지 모델을 생성하였다. 모델들의 성능 비교 결과 Decision Tree 성능이 가장 높은 것으로 나타났다. 본 연구에서는 노드의 특성배치를 변경하고 트리의 최대 깊이를 3으로 지정한 Decision Tree를 사용하였을 때 가장 성능이 높은 것으로 나타났으므로 노드의 특성 배치 변경과 트리의 최대 깊이를 설정한 Decision Tree를 사용하는 것을 권장한다.