• Coupled systems mechanics
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• v.1 no.1
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• pp.59-78
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• 2012

The available analytical methods of analysis for laterally loaded piles in level ground cannot be directly applied to such piles in sloping ground. With the commercially available software, the simulation of the appropriate field condition is a challenging task, and the results are subjective. Therefore, it becomes essential to understand the process of development of a user-framed numerical formulation, which may be used easily as per the specific site conditions without depending on other indirect methods of analysis as well as on the software. In the present study, a detailed three-dimensional finite element formulation is presented for the analysis of laterally loaded piles in sloping ground developing the 18 node triangular prism elements. An application of the numerical formulation has been illustrated for the pile located at the crest of the slope and for the pile located at some edge distance from the crest. The specific examples show that at any given depth, the displacement and bending moment increase with an increase in slope of the ground, whereas they decrease with increasing edge distance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.10
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• pp.3230-3255
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• 2022

Causality mining in NLP is a significant area of interest, which benefits in many daily life applications, including decision making, business risk management, question answering, future event prediction, scenario generation, and information retrieval. Mining those causalities was a challenging and open problem for the prior non-statistical and statistical techniques using web sources that required hand-crafted linguistics patterns for feature engineering, which were subject to domain knowledge and required much human effort. Those studies overlooked implicit, ambiguous, and heterogeneous causality and focused on explicit causality mining. In contrast to statistical and non-statistical approaches, we present Bidirectional Encoder Representations from Transformers (BERT) integrated with Multi-level Feature Networks (MFN) for causality recognition, called BERT+MFN for causality recognition in noisy and informal web datasets without human-designed features. In our model, MFN consists of a three-column knowledge-oriented network (TC-KN), bi-LSTM, and Relation Network (RN) that mine causality information at the segment level. BERT captures semantic features at the word level. We perform experiments on Alternative Lexicalization (AltLexes) datasets. The experimental outcomes show that our model outperforms baseline causality and text mining techniques.

• International Journal of Contents
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• v.13 no.2
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• pp.29-34
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• 2017

Cloud computing is becoming an effective and efficient way of computing resources and computing service integration. Through centralized management of resources and services, cloud computing delivers hosted services over the internet, such that access to shared hardware, software, applications, information, and all resources is elastically provided to the consumer on-demand. The main enabling technology for cloud computing is virtualization. Virtualization software creates a temporarily simulated or extended version of computing and network resources. The objectives of virtualization are as follows: first, to fully utilize the shared resources by applying partitioning and time-sharing; second, to centralize resource management; third, to enhance cloud data center agility and provide the required scalability and elasticity for on-demand capabilities; fourth, to improve testing and running software diagnostics on different operating platforms; and fifth, to improve the portability of applications and workload migration capabilities. One of the key features of cloud computing is elasticity. It enables users to create and remove virtual computing resources dynamically according to the changing demand, but it is not easy to make a decision regarding the right amount of resources. Indeed, proper provisioning of the resources to applications is an important issue in IaaS cloud computing. Most web applications encounter large and fluctuating task requests. In predictable situations, the resources can be provisioned in advance through capacity planning techniques. But in case of unplanned and spike requests, it would be desirable to automatically scale the resources, called auto-scaling, which adjusts the resources allocated to applications based on its need at any given time. This would free the user from the burden of deciding how many resources are necessary each time. In this work, we propose an analytical and efficient VM-level scaling scheme by modeling each VM in a data center as an M/M/1 processor sharing queue. Our proposed VM-level scaling scheme is validated via a numerical experiment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.436-439
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• 2005

As mobile computers and embedded systems are becoming popular recently, we need to study how to utilize the resources such as power, space, CPU clocks, and memory efficiently. In traditional embedded system development, we were interested in resource usage based on hardware but, as software is becoming more important, we need to study how to analyze the resource usage based on software. In this research, we propose a new method called 'Instruction Level Resource Usage Analysis Method' and implement it as a resource usage analysis tool called 'I-Debugger'. I-Debugger is constructed on three layers: debugging layer which controls the execution of software on instruction level, statistic layer which gathers real-time data and convert to useful information, and analysis layer which generate useful information to specific applications. We have applied the debugger to some simple problem and found that our method is useful in developing resource efficient embedded systems.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1538-1544
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• 2021

This study aims to analyze through empirical experiments for the effects of a 360 degree's VR travel contents on stress in the era of COVID-19, as stress has emerged as social problems due to restrictions on freedom of movement. For the empirical experiment, the hypothesis (Happiness level or Depression level or Arousal level will affect the level of stress after watching VR travel contents) was established. As a result, the depression level was adopted while the others were rejected. In order to relieve stress, it is necessary to be careful not to feel depressed, and it was found that even if we can't travel freely, we can reduce stress somewhat with VR travel contents in the untact era. In other words, the emotional state after watching VR travel contents has changed positively. It is hoped that the results of this study will be of some help to the tourism industry and VR production industry, which have been contracted.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.7
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• pp.273-282
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• 2022

Testing approaches for configurable software product lines differs significantly from a single software testing, as it requires consideration of common parts used by all member products of a product line and variable parts shared by some or a single product. Test coverage is a measure of the adequacy of testing performed. Test coverage measurements are important to evaluate the adequacy of testing at the software product line level, as there can be hundreds of member products produced from configurable software product lines. This paper proposes a method for measuring code coverage at the product line level in configurable software product lines. The proposed method tests the member products of a product line after hierarchizing member products based on the inclusion relationship of the selected features, and quantifies SPL(Software Product Line) test coverage by synthesizing the test coverage of each product. As a result of applying the proposed method to 11 configurable software product line cases, we confirmed that the proposed method could quantitatively visualize how thoroughly the SPL testing was performed to help verify the adequacy of the SPL testing. In addition, we could check whether the newly performed testing for a member product covers the newly added code parts of a feature.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3488-3500
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• 2020

At the present time, the economy continues to flourish, and private cars have become the means of choice for most people. Therefore, the license plate recognition technology has become an indispensable part of intelligent transportation, with research and application value. In recent years, the convolution neural network for image classification is an application of deep learning on image processing. This paper proposes a strategy to improve the YOLO model by studying the deep learning convolutional neural network (CNN) and related target detection methods, and combines the OpenCV and TensorFlow frameworks to achieve efficient recognition of license plate characters. The experimental results show that target detection method based on YOLO is beneficial to shorten the training process and achieve a good level of accuracy.

• Journal of Information Processing Systems
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• v.16 no.2
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• pp.301-317
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• 2020

An enterprise patch-management system (PMS) typically supplies a single point of failure (SPOF) of centralization structure. However, a Blockchain system offers features of decentralization, transaction integrity, user certification, and a smart chaincode. This study proposes a Hyperledger Fabric Blockchain-based distributed patch-management system and verifies its technological feasibility through prototyping, so that all participating users can be protected from various threats. In particular, by adopting a private chain for patch file set management, it is designed as a Blockchain system that can enhance security, log management, latest status supervision and monitoring functions. In addition, it uses a Hyperledger Fabric that owns a practical Byzantine fault tolerant consensus algorithm, and implements the functions of upload patch file set, download patch file set, and audit patch file history, which are major features of PMS, as a smart contract (chaincode), and verified this operation. The distributed ledger structure of Blockchain-based PMS can be a solution for distributor and client authentication and forgery problems, SPOF problem, and distribution record reliability problem. It not only presents an alternative to dealing with central management server loads and failures, but it also provides a higher level of security and availability.

• Structural Engineering and Mechanics
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• v.75 no.5
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• pp.607-620
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• 2020

A numerical study is carried out to assess the dynamic response and damage level of one- and two-way reinforced concrete (RC) panels subjected to explosive loads by using finite element LS-DYNA software. The precision of the numerical models is validated with the previous experimental test. The calibrated models are used to conduct a series of parametric studies to evaluate the effects of panel wall dimensions, concrete strength, and steel reinforcement ratio on the blast-resistant capacity of the panel under various magnitudes of blast load. The results are used to develop pressure-impulse (P-I) diagrams corresponding to the damage levels defined according to UFC-3-340-02 manual. Empirical equations are proposed to easily construct the P-I diagrams of RC panels that can be efficiently used to assess its safety level against blast loads.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.7
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• pp.249-258
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• 2018

The importance of software in military weapon systems is increasing, and the software structure is becoming more complicated. We therefore must thoroughly verify its reliability. In particular, the defects from the interaction of the software components that make up the weapon system are difficult to prevent only with static testing and code coverage level dynamic testing. In this paper, we classify dynamic software defect types and analyze the issues reported in the Open Source Software (OSS) used in the US department of defense weapon systems. The dynamic defects classified in this paper usually occur after integration, and it is difficult to reproduce and identify the cause. Based on this analysis, we come to the point that the software integration test must be enhanced in order to verify the reliability of the weapon system.