• Steel and Composite Structures
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• v.41 no.5
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• pp.761-773
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• 2021

This study presents a 3D non-linear finite element (FE) assessment of dynamic soil-structure interaction (SSI). The numerical investigation has been performed on the time domain through a Finite Element (FE) system, while considering the nonlinear behavior of soil and the multi-directional nature of genuine seismic events. Later, the FE outcomes are analyzed to the recorded in-situ free-field and structural movements, emphasizing the numerical model's great result in duplicating the observed response. In this work, the soil response is simulated using an isotropic hardening elastic-plastic hysteretic model utilizing HSsmall. It is feasible to define the non-linear cycle response from small to large strain amplitudes through this model as well as for the shift in beginning stiffness with depth that happens during cyclic loading. One of the most difficult and unexpected tasks in resolving soil-structure interaction concerns is picking an appropriate ground motion predicted across an earthquake or assessing the geometrical abnormalities in the soil waves. Furthermore, an artificial neural network (ANN) has been utilized to properly forecast the non-linear behavior of soil and its multi-directional character, which demonstrated the accuracy of the ANN based on the RMSE and R² values. The total result of this research demonstrates that complicated dynamic soil-structure interaction processes may be addressed directly by passing the significant simplifications of well-established substructure techniques.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.3904-3922
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• 2022

As a research hotspot, pedestrian detection has a wide range of applications in the field of computer vision in recent years. However, current pedestrian detection methods have problems such as insufficient detection accuracy and large models that are not suitable for large-scale deployment. In view of these problems mentioned above, a lightweight pedestrian detection and early warning method using a new model called you only look once (Yolov5) is proposed in this paper, which utilizing advantages of Yolov5s model to achieve accurate and fast pedestrian recognition. In addition, this paper also optimizes the loss function of the batch normalization (BN) layer. After sparsification, pruning and fine-tuning, got a lot of optimization, the size of the model on the edge of the computing power is lower equipment can be deployed. Finally, from the experimental data presented in this paper, under the training of the road pedestrian dataset that we collected and processed independently, the Yolov5s model has certain advantages in terms of precision and other indicators compared with traditional single shot multiBox detector (SSD) model and fast region-convolutional neural network (Fast R-CNN) model. After pruning and lightweight, the size of training model is greatly reduced without a significant reduction in accuracy, and the final precision reaches 87%, while the model size is reduced to 7,723 KB.

• Journal of Internet Computing and Services
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• v.22 no.6
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• pp.9-15
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• 2021

In ultra-dense heterogeneous networks, the amount of interference from small-cell base stations(SBS) to macro-cell user equipments (MUEs) increases significantly as the number of SBSs increases and it causes the MUEs to decrease the signal-to-interference and noise ratio(SINR) and system capacity. In this paper, we propose a small-cell based cooperative multi-point(CoMP) communication scheme that can guarantee the performance of MUEs even when the number of SBSs increases. In the proposed scheme, MUEs first find SBSs that give signal strength equal to or greater than a given SINR threshold and then they are served by different numbers of the selected SBSs using CoMP to improve the performance of MUEs. Simulation results show that the proposed small-cell based CoMP scheme outperforms other interference management or CoMP schemes in terms of the SINR and system capacity of MUEs.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.3
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• pp.83-91
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• 2022

This paper proposes a scalable hybrid P2P(peer-to-peer) cloud architecture for MMOGs(massively multiplayer online games) which includes load management schemes for each region. A game world is divided into several game regions and each game region is serviced by at least one peer(player) in this MMOG cloud environment. The load must be managed regionally to support smooth interactions among them even in the presence of a high concentration of players in a specific region. In the proposed architecture where an efficient and effective provisioning of resources is realized, it is suitable for players to interact with cloud servers effectively and it avoids bottlenecks of the current client-server MMOG architecture. This architecture also relieves a lot of computational power and network traffic, the load on the servers in the cloud by exploiting the capacity of the players. Simulation results show that the proposed hybrid P2P cloud architecture can reduce the considerable bandwidth at the server compared to the client server architecture as the available resources grow with the number of players in crowding or hotspots.

• Journal of Aerospace System Engineering
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• v.16 no.4
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• pp.109-115
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• 2022

The CNN (Convolution Neural Network) algorithm which combines a deep learning technique, and a computer vision technology, makes image classification feasible with the high-performance computing system. In this thesis, the CNN algorithm is applied to the classification problem, by using a typical deep learning framework of TensorFlow and machine learning techniques. The data set required for supervised learning is generated with the same type of bolts. some of which have undamaged threads, but others have damaged threads. The learning model with less quantity data showed good classification performance on detecting damage in a bolt image. Additionally, the model performance is reviewed by altering the quantity of convolution layers, or applying selectively the over and under fitting alleviation algorithm.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.2
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• pp.115-126
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• 2010

Modern society can be described as ubiquitous computing over the concept of information. Information technology(IT) has been developing in a way that relative technologies are integrated to each other. Especially in ubiquitous environment, medical information industry shows significant interest in the U-healthcare service area. This paper will first look into U-healthcare service environment and component of Integrated Medical Information Systems(IMIS). Secondly, it examines the basic technological factors for integrated medical information systems, which is datawarehouse, network, communication standards and technology related U-healthcare service. Finally it proposes how to implement and operate new integrated medical information system for ubiquitous health care service. The system will do point of care(POC) for customers by real time and diagnose them using their various and personal medical data. The information will be communicated back to the customers, which will improve their satisfaction.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.353-360
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• 2022

Due to the dense and complicated working environment, the construction industry is susceptible to many accidents. Worker's fall is a severe problem at the construction site, including falling into holes or openings because of the inadequate coverings as per the safety rules. During the construction or demolition of a building, openings and holes are formed in the floors and roofs. Many workers neglect to cover openings for ease of work while being aware of the risks of holes, openings, and gaps at heights. However, there are safety rules for worker safety; the holes and openings must be covered to prevent falls. The safety inspector typically examines it by visiting the construction site, which is time-consuming and requires safety manager efforts. Therefore, this study presented a worker-driven approach (the worker is involved in the reporting process) to facilitate safety managers by developing integrated computer vision and inertia sensors-based mobile applications to identify openings. The TensorFlow framework is used to design Convolutional Neural Network (CNN); the designed CNN is trained on a custom dataset for binary class openings and covered and deployed on an android smartphone. When an application captures an image, the device also extracts the accelerometer values to determine the inclination in parallel with the classification task of the device to predict the final output as floor (openings/ covered), wall (openings/covered), and roof (openings / covered). The proposed worker-driven approach will be extended with other case scenarios at the construction site.

• Journal of Internet of Things and Convergence
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• v.9 no.2
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• pp.55-60
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• 2023

Recently, demand for cloud computing has increased and remote access due to home work and external work has increased. In addition, a new security paradigm is required in the current situation where the need to be vigilant against not only external attacker access but also internal access such as internal employee access to work increases and various attack techniques are sophisticated. As a result, the network security model applying Zero-Trust, which has the core principle of doubting everything and not trusting it, began to attract attention in the security industry. Zero Trust Security monitors all networks, requires authentication in order to be granted access, and increases security by granting minimum access rights to access requesters. In this paper, we explain zero trust and zero trust architecture, and propose a new cloud security system for strengthening access control that overcomes the limitations of existing security systems using zero trust and blockchain and can be used by various companies.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.1135-1138
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• 2011

안드로이드 시장이 급성장함에 따라 안드로이드 기반 어플리케이션에 대한 수요가 많아지고 있다. 그로 인해 3D 그래픽적 기능을 요구하는 어플리케이션에 대한 요구도 늘어났다. 그러나 안드로이드 단말기에서는 3D 처리능력이 데스크 탑과 비교하여 성능과 서비스에 한계가 있다. 그렇기 때문에 VNC(Virtual Network Computing)를 사용하여 고성능의 그래픽을 요구하는 프로그램을 실행할 수 있게 된다. VNC 란 클라이언트에서 데스크 탑으로 접속하여 원격으로 제어하고 그 결과를 그래픽으로 확인하는 프로그램이다. 그러나 기존의 Android VNC 는 해상도가 낮고, 이미지 전송 속도가 느리기 때문에 3D 렌더링 이미지 처리가 불가능했다. 또한 Android VNC 는 인터페이스가 불편하여 입력 오류가 많아 사용이 불편했다는 단점 등이 지적되어 왔다. 본 논문에서는 이를 개선하기 위한 Android Turbo VNC 를 제안한다. Android Turbo VNC는 libjpeg-turbo 코덱을 적용하여 3D 이미지 부분에서 기존의 Android VNC 에 비하여 약 80~120%의 이미지 개선과 이미지 압축률을 4 배정도 높여 CAD 와 같은 고성능의 그래픽을 요구하는 프로그램의 사용을 가능하게 한다. 그리고 Android Turbo VNC 에서는 기존 Android VNC 의 불편한 UI 를 개선하였다. 클라우드 서버에서는 CAD, Document, Game, Video, General 총 5 가지의 프로그램을 서비스하여 그에 맞는 테마 별 UI 를 제공한다. libjpeg-turbo 코덱의 적용을 통해 Android-Turbo VNC 는 수십 장의 설계 도면을 굳이 들고 다니지 않더라도 하나의 테블릿 PC 안에서 보는 것이 가능하게 된다. 테마별 UI 중 CAD 테마는 3D CAD 를 사용하는 산업현장에서 적극적으로 활용될 것으로 기대된다.

• Journal of the Korea Society of Computer and Information
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• v.14 no.10
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• pp.101-110
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• 2009

The 6LoWPAN(IPv6 Low-power Wireless Personal Area Network) performs IPv6 header compression, TCP/UDP/IGMP header compression, packet fragmentation and re-assemble to transmit IPv6 packet over IEEE 802,15.4 MAC/PHY. However, from the point of view of security. It has the existing security threats issued by IP packet fragmenting and reassembling, and new security threats issued by 6LoWPAN packet fragmenting and reassembling would be introduced additionally. If fragmented packets are retransmitted by replay attacks frequently, sensor nodes will be confronted with the communication disruption. This paper analysis security threats introduced by 6LoWPAN fragmenting and reassembling, and proposes a re-transmission mechanism that could minimize re-transmission to be issued by replay attacks. Re-transmission procedure and fragmented packet structure based on the 6LoWPAN standard(RFC4944) are designed. We estimate also re-transmission delay of the proposed mechanism. The mechanism utilizes timestamp, nonce, and checksum to protect replay attacks. It could minimize reassemble buffer overflow, waste of computing resource, node rebooting etc., by removing packet fragmentation and reassemble unnecessary.