• 제목/요약/키워드: computer error solving

검색결과 77건 처리시간 0.027초

학습자의 컴퓨터 문제해결 선호방법 분석 (Analysis of Learners' Preferences for Computer Solving Methods)

  • 박선주
    • 정보교육학회논문지
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    • 제22권1호
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    • pp.113-122
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    • 2018
  • 성공적인 학습 성과를 위해 동료 학습자간의 상호 협력 및 도움은 매우 중요한 요소이지만 학생들은 점점 혼자 해결하려는 경향이 나타나므로 학생들의 컴퓨터 문제해결 선호 방법 및 상호 관계성 등을 조사하여 이에 관한 학생들의 생각을 파악하고 학생들에게 알맞은 실습지도를 할 필요가 있다. 그러므로 본 논문에서는 K교육대학교 학생 231명을 대상으로 컴퓨터 사용 중 어려움을 겪을 때 선호하는 해결 방법 및 학생들 상호 관계성을 분석한 결과, 컴퓨터 사용 중 어려움 발생정도가 적을수록 컴퓨터 활용능력이 높을수록 학년이 올라갈수록 스스로 해결하는 방법을 선호하였다. 그리고 가족 및 친척 등 친밀도가 높은 혈연관계에게 직접 물어보는 방법과 인터넷을 활용하여 스스로 해결하는 방법에 만족도가 높았다. 또한, 학과동기생 사회연결망 분석을 통해 학과 안에서 컴퓨터 문제해결 관계망을 파악할 수 있어 동료 학습자 선정시 참고자료로 활용할 수 있으므로 개인별 맞춤형 컴퓨터 교육실습 운영에 도움을 줄 수 있을 것이다.

A Study on Coding Education for Non-Computer Majors Using Programming Error List

  • Jung, Hye-Wuk
    • International Journal of Advanced Culture Technology
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    • 제9권1호
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    • pp.203-209
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    • 2021
  • When carrying out computer programming, the process of checking and correcting errors in the source code is essential work for the completion of the program. Non-computer majors who are learning programming for the first time receive feedback from instructors to correct errors that occur when writing the source code. However, in a learning environment where the time for the learner to practice alone is long, such as an online learning environment, the learner starts to feel many difficulties in solving program errors by himself/herself. Therefore, training on how to check and correct errors after writing the program source code is necessary. In this paper, various types of errors that can occur in a Python program were described, the errors were classified into simple errors and complex errors according to the characteristics of the errors, and the distributions of errors by Python grammar category were analyzed. In addition, a coding learning process to refer error lists was designed to present a coding learning method that enables learners to solve program errors by themselves.

Bayesian smoothing under structural measurement error model with multiple covariates

  • Hwang, Jinseub;Kim, Dal Ho
    • Journal of the Korean Data and Information Science Society
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    • 제28권3호
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    • pp.709-720
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    • 2017
  • In healthcare and medical research, many important variables have a measurement error such as body mass index and laboratory data. It is also not easy to collect samples of large size because of high cost and long time required to collect the target patient satisfied with inclusion and exclusion criteria. Beside, the demand for solving a complex scientific problem has highly increased so that a semiparametric regression approach could be of substantial value solving this problem. To address the issues of measurement error, small domain and a scientific complexity, we conduct a multivariable Bayesian smoothing under structural measurement error covariate in this article. Specifically we enhance our previous model by incorporating other useful auxiliary covariates free of measurement error. For the regression spline, we use a radial basis functions with fixed knots for the measurement error covariate. We organize a fully Bayesian approach to fit the model and estimate parameters using Markov chain Monte Carlo. Simulation results represent that the method performs well. We illustrate the results using a national survey data for application.

Siamese Network의 특징맵을 이용한 객체 추적 알고리즘 (Object Tracking Algorithm using Feature Map based on Siamese Network)

  • 임수창;박성욱;김종찬;류창수
    • 한국멀티미디어학회논문지
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    • 제24권6호
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    • pp.796-804
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    • 2021
  • In computer vision, visual tracking method addresses the problem of localizing an specific object in video sequence according to the bounding box. In this paper, we propose a tracking method by introducing the feature correlation comparison into the siamese network to increase its matching identification. We propose a way to compute location of object to improve matching performance by a correlation operation, which locates parts for solving the searching problem. The higher layer in the network can extract a lot of object information. The lower layer has many location information. To reduce error rate of the object center point, we built a siamese network that extracts the distribution and location information of target objects. As a result of the experiment, the average center error rate was less than 25%.

Enhanced Second-order Implicit Constraint Enforcement for Dynamic Simulations

  • Hong, Min;Welch, Samuel W.J.;Jung, Sun-Hwa;Choi, Min-Hyung;Park, Doo-Soon
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제2권1호
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    • pp.51-62
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    • 2008
  • This paper proposes a second-order implicit constraint enforcement method which yields enhanced controllability compared to a first-order implicit constraints enforcement method. Although the proposed method requires solving a linear system twice, it yields superior accuracy from the constraints error perspective and guarantees the precise and natural movement of objects, in contrast to the first-order method. Thus, the proposed method is the most suitable for exact prediction simulations. This paper describes the numerical formulation of second-order implicit constraints enforcement. To prove its superiority, the proposed method is compared with the firstorder method using a simple two-link simulation. In this paper, there is a reasonable discussion about the comparison of constraints error and the analysis of dynamic behavior using kinetic energy and potential energy.

The Error of the Method of Angular Sections of Microwave Sounding of Natural Environments in the System of Geoecological Monitoring

  • Fedoseeva, E.V.;Kuzichkin, O. R.
    • International Journal of Computer Science & Network Security
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    • 제21권6호
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    • pp.47-53
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    • 2021
  • The article deals with the problems of application of microwave methods in systems of geoecological monitoring of natural environments and resources of the agro-industrial complex. It is noted that the methods of microwave radiometry make it possible, by the power of the measured intrinsic radio-thermal radiation of the atmosphere, when solving inverse problems using empirical and semi-empirical models, to determine such parameters of the atmosphere as thermodynamic temperature, humidity, water content, moisture content, precipitation intensity, and the presence of different fractions of clouds.In addition to assessing the meteorological parameters of the atmosphere and the geophysical parameters of the underlying surface based on the data of microwave radiometric measurements, it is possible to promptly detect and study pollution of both the atmosphere and the earth's surface. A technique has been developed for the analysis of sources of measurement error and their numerical evaluation, because they have a significant effect on the accuracy of solving inverse problems of reconstructing the values of the physical parameters of the probed media.To analyze the degree of influence of the limited spatial selectivity of the antenna of the microwave radiometric system on the measurement error, we calculated the relative measurement error of the ratio of radio brightness contrasts in two angular directions. It has been determined that in the system of geoecological monitoring of natural environments, the effect of background noise is maximal with small changes in the radiobrightness temperature during angular scanning and high sensitivity of the receiving equipment.

A STUDY ON THE EFFECTIVE ALGORITHMS BASED ON THE WEGMANN'S METHOD

  • Song, Eun-Jee
    • Journal of applied mathematics & informatics
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    • 제20권1_2호
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    • pp.595-602
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    • 2006
  • Determinations of conformal map from the unit disk onto a Jordan region are reduced to solve the Theodorsen equation which is an integral equation for the boundary correspondence function. Among numerical conformal maps the Wegmann's method is well known as a Newton efficient one for solving Theodorsen equation. However this method has not so wide class of convergence. We proposed as an improved method for convergence by applying a low frequency filter to the Wegmann's method. In this paper, we investigate error analysis and propose an automatic algorithm based on this analysis.

문제해결력 향상을 위한 과제 중심 스크래치 프로그래밍 학습 프로그램 (A Task Centered Scratch Programming Learning Program for Enhancing Learners' Problem Solving Abilities)

  • 이은경
    • 컴퓨터교육학회논문지
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    • 제12권6호
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    • pp.1-9
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    • 2009
  • 프로그래밍 학습은 현대사회가 요구하는 복잡한 문제해결력 향상에 도움이 되지만, 학습자에게 과도한 인지적 부담을 줄 수 있다. 따라서 인지적 부담을 감소시키기 위한 프로그래밍 도구의 선택 및 학습 효과를 최대화하기 교수 학습 전략이 요구된다. 본 연구에서는 중학생의 문제해결력 향상을 위한 과제 중심 스크래치 프로그래밍 학습 프로그램을 개발하고 해당 프로그램이 학습자의 문제해결력에 미치는 영향을 분석하였다. 연구결과, 과제 중심 스크래치 프로그래밍 학습을 수행한 집단이 일반적인 스크래치 프로그래밍 학습과 비주얼 베이식 프로그래밍 학습을 실시한 집단에 비해 문제해결력이 유의하게 향상되었다. 특히 오류를 발견하고 수정하는 능력인 문제점 해결 영역에서 유의한 차이를 더 크게 드러났다.

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Kalman Filtering with Optimally Scheduled Measurements in Bandwidth Limited Communication Media

  • Pasand, Mohammad Mahdi Share;Montazeri, Mohsen
    • ETRI Journal
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    • 제39권1호
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    • pp.13-20
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    • 2017
  • A method is proposed for scheduling sensor accesses to the shared network in a networked control system. The proposed method determines the access order in which the sensors are granted medium access through minimization of the state estimation error covariance. Solving the problem by evaluating the error covariance for each possible ordered set of sensors is not practical for large systems. Therefore, a convex optimization problem is proposed, which yields approximate yet acceptable results. A state estimator is designed for the augmented system resulting from the incorporation of the optimally chosen communication sequence in the plant dynamics. A car suspension system simulation is conducted to test the proposed method. The results show promising improvement in the state estimation performance by reducing the estimation error norm compared to round-robin scheduling.

ResNet-Based Simulations for a Heat-Transfer Model Involving an Imperfect Contact

  • Guangxing, Wang;Gwanghyun, Jo;Seong-Yoon, Shin
    • Journal of information and communication convergence engineering
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    • 제20권4호
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    • pp.303-308
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    • 2022
  • Simulating the heat transfer in a composite material is an important topic in material science. Difficulties arise from the fact that adjacent materials cannot match perfectly, resulting in discontinuity in the temperature variables. Although there have been several numerical methods for solving the heat-transfer problem in imperfect contact conditions, the methods known so far are complicated to implement, and the computational times are non-negligible. In this study, we developed a ResNet-type deep neural network for simulating a heat transfer model in a composite material. To train the neural network, we generated datasets by numerically solving the heat-transfer equations with Kapitza thermal resistance conditions. Because datasets involve various configurations of composite materials, our neural networks are robust to the shapes of material-material interfaces. Our algorithm can predict the thermal behavior in real time once the networks are trained. The performance of the proposed neural networks is documented, where the root mean square error (RMSE) and mean absolute error (MAE) are below 2.47E-6, and 7.00E-4, respectively.