• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.7
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• pp.977-985
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• 2021

The LiDAR sensor is attracting attention as a key sensor for autonomous driving vehicle. LiDAR sensor provides measured three-dimensional lengths within range using LASER. However, as much data is provided to the external system, it is difficult to process such data in an external system or processor of the vehicle. To resolve these issues, we develop integrated processing system for LiDAR sensor. The system is configured that client receives data from LiDAR sensor and processes data, server gathers data from clients and transmits integrated data in real-time. The test was carried out to ensure real-time processing of the system by changing the data acquisition, processing method and process driving method of process. As a result of the experiment, when receiving data from four LiDAR sensors, client and server process was operated using background or multi-core processing, the system response time of each client was about 13.2 ms and the server was about 12.6 ms.

• Journal of the Korea Convergence Society
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• v.9 no.11
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• pp.91-97
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• 2018

The plant factory represents one of the future agricultural systems into which ubiquitous information technology (U-IT) is incorporated, including sensor networking, and helps minimize the influence of external experimental factors that constrain the use of existing greenhouse cultivation techniques. A plant factory's automated cultivation system does not merely provide convenience for crop cultivation, but also expandability as a platform that helps build a knowledge database based on its acquired information and develop education and other application services using the database. For the expansion of plant factory services, this study designed a plant factory interworking service (PFIS) which allows plant factories to share crop growth-related information efficiently among them and performed a test on the service and its implementation.

• Steel and Composite Structures
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• v.32 no.3
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• pp.361-372
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• 2019

Tubular joints are used in the construction of offshore structures and other land-based structures because of its ease of fabrication. These joints are subjected to different environmental loadings in their lifetime. At the time of fabrication or modification of an existing offshore platform, tubular joints are usually strengthened to withstand the environmental loads. Currently, various strengthening techniques such as ring stiffeners, gusset plates are employed to strengthen new and existing tubular joints. Due to some limitations with the present practices, some new techniques need to be addressed. Many researchers used Fibre Reinforced Polymer (FRP) to strengthen tubular joints. Some of the studies were focused on axial compression of Glass Fibre Reinforced Polymer (GFRP) strengthened tubular joints and found that it was an efficient technique. Earlier, the authors had performed studies on Carbon Fibre Reinforced Polymer (CFRP) strengthened tubular joint subjected to axial compression. The study steered to the conclusion that FRP composites is an alternative strengthening technique for tubular joints. In this work, the study was focused on axial compression of Y-joint and in plane and out of plane bending of T-joints. Experimental investigations were performed on these joints, fabricated from ASTM A106 Gr. B steel. Two sets of joints were fabricated for testing, one is a reference joint and the other is a joint strengthened with CFRP. After performing the set of experiments, test results were then compared with the numerical solution in ANSYS Parametric Design Language (APDL). It was observed that the joints strengthened with CFRP were having improved strength, lesser surface displacement and ovalization when compared to the reference joint.

• Journal of Digital Convergence
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• v.17 no.9
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• pp.71-78
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• 2019

This study aims to identify good borrowers within the context of P2P lending. P2P lending is a growing platform that allows individuals to lend and borrow money from each other. Inherent in any loans is credit risk of borrowers and needs to be considered before any lending. Specifically in the context of P2P lending, traditional models fall short and thus this study aimed to rectify this as well as explore the problem of class imbalances seen within credit risk data sets. This study implemented an over-sampling technique known as Synthetic Minority Over-sampling Technique (SMOTE). To test our approach, we implemented five benchmarking classifiers such as support vector machines, logistic regression, k-nearest neighbor, random forest, and deep neural network. The data sample used was retrieved from the publicly available LendingClub dataset. The proposed SMOTE revealed significantly improved results in comparison with the benchmarking classifiers. These results should help actors engaged within P2P lending to make better informed decisions when selecting potential borrowers eliminating the higher risks present in P2P lending.

• Journal of the Korea Convergence Society
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• v.9 no.11
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• pp.45-51
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• 2018

Autonomous ship has been sportlighted as a core technology for the maritime industry in Industry 4.0 era. Autonomous ship is expeected to improve the safety, reliability, efficiency and environment significantly. For the realization of the autonomous ship, the remote control of the ship is one of the core functionality in addition to the autonomous ship control functionality in a ship. In this paper, we address a autonomous ship control system based on remote control. This paper proposes a remote control autonomous system and standardized ship-to-shore remote control protocol with for open platform. Finally, we implemented the system and tested with a real experiments with the test ship in order to demonstrate the feasibility of the proposed remote control autonomous system.

• Journal of Advanced Navigation Technology
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• v.22 no.6
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• pp.675-680
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• 2018

In this paper, we propose a hand gesture recognizer using restricted coulomb energy (RCE) neural network, and present hardware implementation results for real-time learning and recognition. Since RCE-NN has a flexible network architecture and real-time learning process with low complexity, it is suitable for hand recognition applications. The 3D number dataset was created using an FPGA-based test platform and the designed hand gesture recognizer showed 98.8% recognition accuracy for the 3D number dataset. The proposed hand gesture recognizer is implemented in Intel-Altera cyclone IV FPGA and confirmed that it can be implemented with 26,702 logic elements and 258Kbit memory. In addition, real-time learning and recognition verification were performed at an operating frequency of 70MHz.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.606-608
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• 2014

The Study on the technique of applying the method USB redirection on Linux-based SPICE-GTK VDI solution for in (Virtual Desktop Infrastructure) VDI solution for Android-based USB redirection in this paper. VDI solutions are developed according to the development of many of the latest Android-based devices, but a VDI solution that supports USB redirection is limited. Also does not support USB redirection of Android to use the SPICE VDI solution. Therefore, the text presents the techniques applied to the Android-based VDI solutions applied to analyze the way USB redirection of SPICE-GTK VDI solution based on Linux. G PRO smartphone devices to install and use Linux-based VDI server to a test of the method applied in this paper, and the USB redirection applied VDI clients using a USB storage device, USB redirection is done playing files results you can check

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.267-275
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• 2021

Smart application is developed in this paper by using an android-based platform to automatically determine the human emergency state (Lifesaver) by using different technology sensors of the mobile. In practice, this Lifesaver has many applications, and it can be easily combined with other applications as well to determine the emergency of humans. For example, if an old human falls due to some medical reasons, then this application is automatically determining the human state and then calls a person from this emergency contact list. Moreover, if the car accidentally crashes due to an accident, then the Lifesaver application is also helping to call a person who is on the emergency contact list to save human life. Therefore, the main objective of this project is to develop an application that can save human life. As a result, the proposed Lifesaver application is utilized to assist the person to get immediate attention in case of absence of help in four different situations. To develop the Lifesaver system, the GPS is also integrated to get the exact location of a human in case of emergency. Moreover, the emergency list of friends and authorities is also maintained to develop this application. To test and evaluate the Lifesaver system, the 50 different human data are collected with different age groups in the range of (40-70) and the performance of the Lifesaver application is also evaluated and compared with other state-of-the-art applications. On average, the Lifesaver system is achieved 95.5% detection accuracy and the value of 91.5 based on emergency index metric, which is outperformed compared to other applications in this domain.

• Journal of Conservation Science
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• v.37 no.4
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• pp.362-369
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• 2021

In museums, exhibition content focuses mostly on cultural heritage's historical values and functions, but doing so tends to limit visitors' interest and immersion. To counter this limitation, the study developed an experiential media art exhibition fusing bronze mirrors' traditional production technology and modern conservation science. First, for the exhibition system, scientific cultural heritage contents were projected on the three-dimensional (3D) printed bronze mirror through interactions between motion recognition digital information display (DID) and the projector. Then, a scenario of 17 missions in four stages (production process, corrosion mechanism, scientific analysis and diagnosis, and conservation treatment and restoration) was prepared according to the temporal spectrum. Additionally, various media art effects and interaction technologies were developed, so visitors could understand and become immersed in bronze mirrors' scientific content. A user test was evaluated through the living lab, reflecting generally high levels of satisfaction (90.2 points). Qualitative evaluation was generally positive, with comments such as "easy to understand and useful as the esoteric science exhibition was combined with media art" (16.7%), "wonderful and interesting" (11.7%), and "firsthand experience was good" (9.2%). By combining an esoteric science exhibition centered on principles and theories with visual media art and by developing an immersive directing method to provide high-level exhibition technology, the exhibition induced visitors' active participation. This exhibition's content can become an important platform for expanding universal museum exhibitions on archaeology, history, and art into conservation science.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.5
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• pp.969-976
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• 2019

A lightweight artificial intelligence hardware has made great strides in many application areas. In general, a lightweight artificial intelligence system consist of lightweight artificial intelligence engine and preprocessor including feature selection, generation, extraction, and normalization. In order to achieve optimal performance in broad range of applications, lightweight artificial intelligence system needs to choose a good preprocessing function and set their respective hyper-parameters. This paper proposes a unified framework for a lightweight artificial intelligence system and utilization method for finding models with optimal performance to use on a given dataset. The proposed unified framework can easily generate a model combined with preprocessing functions and lightweight artificial intelligence engine. In performance evaluation using handwritten image dataset and fall detection dataset measured with inertial sensor, the proposed unified framework showed building optimal artificial intelligence models with over 90% test accuracy.