• 한국컴퓨터정보학회논문지
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• 제28권11호
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• pp.227-234
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• 2023

컴퓨팅 사고력의 평가는 컴퓨터과학 개념과 원리에 대한 지식의 평가로부터 시작된다. 본 연구에서는 컴퓨터과학 지식을 평가하기 위한 비버 평가 문항의 서술 방식에 따른 교사의 인식의 차이를 분석했다. 우선 평가 문항을 컴퓨터과학 용어의 포함 유무에 따라 두 가지 유형으로 분류했다. 그리고 각 유형의 문항에 대한 컴퓨팅 사고 설문지를 작성하였고, 72명의 전공 교사를 대상으로 설문을 했다. 설문 결과, 컴퓨터과학 용어가 드러난 문항이 정보 교과의 평가 문항으로 적합하다는 의견이 제시되었고 컴퓨팅 사고와 코딩 능력을 평가하는데 더 도움이 된다고 인식했다. 연구 결과를 통해 학생들의 컴퓨터과학 개념 이해와 컴퓨팅 사고력 함양을 평가하기 위해서는 어떤 서술 방식의 평가가 더 필요한지에 대해 제언했다.

• Computers and Concrete
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• 제7권3호
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• pp.249-269
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• 2010

Managing and reusing knowledge in engineering and construction sectors can lead to greater competitive advantage, improved designs, and more effective management of constructed facilities. The use of Information Technology (IT) in design and construction can exploit strategic opportunities for new ways of integration, sharing and facilitating information and knowledge in any field of engineering. The integrating of separate areas of IT can be used to bring a group of experts and specialists in any field of engineering closer together by allowing them to communicate and exchange information and expertise that facilitate knowledge capture, sharing, and reuse. A lack of an advisory management system and a need to marshal all available data in a common format has indicated the need for an integrated engineering computing environment to investigate concrete repair problems. The research described in this paper is based upon an evaluation management system (EMS) which comprising a database management system (REPCON) alongside visualisation technologies and evaluation system (ECON) is developed to produce an innovative platform which will facilitate and encourage the development of knowledge in educational, evolution and evaluation modes of concrete repair. This allows us to create assessment procedures that will allow the current condition of the concrete structure and its components to be expressed numerically using a confidence level (CL) so as to take the best course of action in the repair and maintenance management. The explained rating system, which is related to structural integrity and serviceability of the structure, allows the confidence level to be determined by visual inspection and the descriptive information and pictures taken from an available REPair of CONcrete (REPCON) database.

• Structural Monitoring and Maintenance
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• 제2권2호
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• pp.115-132
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• 2015

This paper presents a new method for seismic vulnerability assessment of buildings with reference to their operational limit state. The importance of this kind of evaluation arises from the civil protection necessity that some buildings, considered strategic for seismic emergency management, should retain their functionality also after a destructive earthquake. The method is based on the identification of experimental modal parameters from ambient vibrations measurements. The knowledge of the experimental modes allows to perform a linear spectral analysis computing the maximum structural drifts of the building caused by an assigned earthquake. Operational condition is then evaluated by comparing the maximum building drifts with the reference value assigned by the Italian Technical Code for the operational limit state. The uncertainty about the actual building seismic frequencies, typically significantly lower than the ambient ones, is explicitly taken into account through a probabilistic approach that allows to define for the building the Operational Index together with the Operational Probability Curve. The method is validated with experimental seismic data from a permanently monitored public building: by comparing the probabilistic prediction and the building experimental drifts, resulting from three weak earthquakes, the reliability of the method is confirmed. Finally an application of the method to a strategic building in Italy is presented: all the procedure, from ambient vibrations measurement, to seismic input definition, up to the computation of the Operational Probability Curve is illustrated.

• 생태와환경
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• 제51권3호
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• pp.212-220
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• 2018

Ecological and ecosystem database is becoming very necessary to understand origins and relationship between human and nature and also to minimize disturbance caused by human activities. An ecological information portal can play important roles as a computing system to collect knowledge, distributed research findings and separated data from researchers. In this study, we designed and developed ecological information portal service (EcoBank 1.0) for collecting and providing ecological information for diverse classes of stakeholders. To reach the goal, we had reviewed related and comparable ecological database portals to design conceptual structure of EcoBank system including database management framework. Then, we developed some functions of ecosystem analysis for each stake-holders (researchers, general public and policy makers). As a result of this study, we successfully designed of EcoBank system covering the functions of Digital Object Identifier(DOI) publishing and data quality management process. Also, we (1) applied ecological indices for calculating biodiversity by administrative boundary for policy makers, (2) provided statistical information of econature map for general public and distribution characteristics of species for researchers. To make a successful establishment of EcoBank, we have to collect and build up related database and offer various and reliable ecological data consistently. We expect that the successful construction of EcoBank will help not only to accomplish sustainable development goals but also to raise the welfare of ecosystem in Korea.

• Journal of Information Processing Systems
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• 제5권2호
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• pp.69-76
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• 2009

Self healing systems are considered as cognation-enabled sub form of fault tolerance system. But our experiments that we report in this paper show that self healing systems can be used for performance optimization, configuration management, access control management and bunch of other functions. The exponential complexity that results from interaction between autonomic systems and users (software and human users) has hindered the deployment and user of intelligent systems for a while now. We show that if that exceptional complexity is converted into self-growing knowledge (policies in our case), can make up for initial development cost of building an intelligent system. In this paper, we report the application of AHSEN (Autonomic Healing-based Self management Engine) to in OKKAM Project infrastructure backbone cluster that mimics the web service based architecture of u-Zone gateway infrastructure. The 'blind' load division on per-request bases is not optimal for distributed and performance hungry infrastructure such as OKKAM. The approach adopted assesses the active threads on the virtual machine and does resource estimates for active processes. The availability of a certain server is represented through worker modules at load server. Our simulation results on the OKKAM infrastructure show that the self healing significantly improves the performance and clearly demarcates the logical ambiguities in contemporary designs of self healing infrastructures proposed for large scale computing infrastructures.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권8호
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• pp.3328-3349
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• 2020

With rapid development of ubiquitous computing and location-based services (LBSs), human trajectory data and associated activities are increasingly easily recorded. Inappropriately publishing trajectory data may leak users' privacy. Therefore, we study publishing trajectory data while preserving privacy, denoted privacy-preserving activity trajectories publishing (PPATP). We propose S-PPATP to solve this problem. S-PPATP comprises three steps: modeling, algorithm design and algorithm adjustment. During modeling, two user models describe users' behaviors: one based on a Markov chain and the other based on the hidden Markov model. We assume a potential adversary who intends to infer users' privacy, defined as a set of sensitive information. An adversary model is then proposed to define the adversary's background knowledge and inference method. Additionally, privacy requirements and a data quality metric are defined for assessment. During algorithm design, we propose two publishing algorithms corresponding to the user models and prove that both algorithms satisfy the privacy requirement. Then, we perform a comparative analysis on utility, efficiency and speedup techniques. Finally, we evaluate our algorithms through experiments on several datasets. The experiment results verify that our proposed algorithms preserve users' privay. We also test utility and discuss the privacy-utility tradeoff that real-world data publishers may face.

• International Journal of Computer Science & Network Security
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• 제22권7호
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• pp.171-180
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• 2022

In the knowledge development of online assessment in learning management systems (LMSs), many assessments are evaluated weekly in the summer training course for undergraduate students in the Faculty of Computing and Information Technology at King Abdul-Aziz University in Saudi Arabia. The number of performance assessments in the summer training course reaches 15 weeks. Many of them, however, are sent or done informally or through unreliable ways and cannot be verified by third parties. Therefore, applying the concept of digital transformation is essential. This research study reported herein used the action design research (ADR) method to build a new information technology system that could assist in the digital transformation. An electronic platform was designed, developed, implemented, and evaluated using the ADR method so that the main people involved in the summer training process (i.e., students, academic supervisors, and administrators) would have a high level of satisfaction with it. The study was conducted on 452 students, 105 academic supervisors, and 15 administrative staff and was conducted during the summer semester of 2020. All the training processes were digitally transformed and automated to control and raise the level and reliability of the training. All involved people were satisfied, thus, shifting the process to be in a digital form assist in achieving the high-level goal.

• Coupled systems mechanics
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• 제12권5호
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• pp.429-444
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• 2023

The comprehension and structural modeling of masonry constructions is fundamental to safeguard the integrity of built cultural assets and intervene through adequate actions, especially in earthquake-prone regions. Despite the availability of several modeling strategies and modern computing power, modeling masonry remains a great challenge because of still demanding computational efforts, constraints in performing destructive or semi-destructive in-situ tests, and material uncertainties. This paper investigates the shear behavior of masonry walls by applying a plane-stress FE continuum model with the Modified Masonry-like Material (MMLM). Epistemic uncertainty affecting input parameters of the MMLM is considered in a probabilistic framework. After appointing a suitable probability density function to input quantities according to prior engineering knowledge, uncertainties are propagated to outputs relying on gPCE-based surrogate models to considerably speed up the forward problem-solving. The sensitivity of the response to input parameters is evaluated through the computation of Sobol' indices pointing out the parameters more worthy to be further investigated, when dealing with the seismic assessment of masonry buildings. Finally, masonry mechanical properties are calibrated in a probabilistic setting with the Bayesian approach to the inverse problem based on the available measurements obtained from the experimental load-displacement curves provided by shear compression in-situ tests.

• International Journal of Knowledge Content Development & Technology
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• 제10권4호
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• pp.29-46
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• 2020

The paper describes the quantitative and qualitative dimensions of artificial neural networks (ANN) in India in the global context. The study is based on research publications data (8260) as covered in the Scopus database during 1999-2018. ANN research in India registered 24.52% growth, averaged 11.95 citations per paper, and contributed 9.77% share to the global ANN research. ANN research is skewed as the top 10 countries account for 75.15% of global output. India ranks as the third most productive country in the world. The distribution of research by type of ANN networks reveals that Feed Forward Neural Network type accounted for the highest share (10.18% share), followed by Adaptive Weight Neural Network (5.38% share), Feed Backward Neural Network (2.54% share), etc. ANN research applications across subjects were the largest in medical science and environmental science (11.82% and 10.84% share respectively), followed by materials science, energy, chemical engineering and water resources (from 6.36% to 9.12%), etc. The Indian Institute of Technology, Kharagpur and the Indian Institute of Technology, Roorkee lead the country as the most productive organizations (with 289 and 264 papers). Besides, the Indian Institute of Technology, Kanpur (33.04 and 2.76) and Indian Institute of Technology, Madras (24.26 and 2.03) lead the country as the most impactful organizations in terms of citation per paper and relative citation index. P. Samui and T.N. Singh have been the most productive authors and G.P.S.Raghava (86.21 and 7.21) and K.P. Sudheer (84.88 and 7.1) have been the most impactful authors. Neurocomputing, International Journal of Applied Engineering Research and Applied Soft Computing topped the list of most productive journals.

• Geomechanics and Engineering
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• 제28권4호
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• pp.397-404
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• 2022

Accurate prediction of the undrained shaft resistance is essential for robust design of bored piles in undrained condition. The undrained shaft resistance is calculated using the undrained adhesion factor multiplied by the undrained cohesion of the soil. However, the available correlations to predict the undrained adhesion factor have been developed using simple regression techniques and the accuracy of these correlations has not been thoroughly assessed in previous studies. The lack of the assessment of these correlations made it difficult for geotechnical engineers to select the most accurate correlation in routine designs. Furthermore, limited attempts have been made in previous studies to use advanced data mining techniques to develop simple and accurate correlation to predict the undrained adhesion factor. This research, therefore, has been conducted to fill these gaps in knowledge by developing novel and robust correlation to predict the undrained adhesion factor. The development of the new correlation has been conducted using the multi-objective evolutionary polynomial regression analysis. The new correlation outperformed the available empirical correlations, where the new correlation scored lower mean absolute error, mean square error, root mean square error and standard deviation of measured to predicted adhesion factor, and higher mean, a20-index and coefficient of correlation. The correlation also successfully showed the influence of the undrained cohesion and the effective stress on the adhesion factor. Hence, the new correlation enhances the design accuracy and can be used by practitioner geotechnical engineers to ensure optimized designs of bored piles in undrained conditions.