• Asia pacific journal of information systems
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• v.31 no.3
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• pp.277-295
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• 2021

This paper examines the features that make a YouTube channel attractive to users. Considering that drawing users' attention is challenging on this platform, where voluminous amounts of videos are available, it is crucial to identify the factors that make users intend to subscribe to a YouTube channel. In this study, we used an online survey to collect data from 1125 respondents and an SEM model using Smart PLS 3.2.8 to analyze it. The results show that integrity and familiarity with a YouTube channel are positively correlated with trust in its creator, which leads to subscribing to the YouTube channel; value and accuracy also positively affect intention to subscribe to a YouTube channel via trust in content. This study enriches the field of research about trust in the creator and trust in content.

• Journal of IKEEE
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• v.23 no.2
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• pp.508-516
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• 2019

Smart home with various IoT devices provides convenient and efficient services. However, security is important because sensitive information such as private video and audio can be collected and processed, as well as shared over the Internet. To manage such smart home IoT devices, we use blockchain technology that provides data integrity and secure management. In this paper, we utilize a PoS(Proof of Stake) method that verifies the block through the accumulated stake in the network rather than the computation power, out of the PoW(Proof of Work) block chain, in which the computation for the existing verification must be continuously performed. Among them, we propose a blockchain based system with DPoS(Delegated Proof of Stake) method to actively solve the scalability part, for security that is suitable for smart home IoT environment. We implement the proposed system with DPoS based EOSIO to show realization, and we show performance improvement in terms of transaction processing speed.

• Smart Media Journal
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• v.7 no.3
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• pp.64-71
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• 2018

Utilization of unmanned aerial vehicles (UAVs) are rapidly expanding to various fields ranging from defense, industry, entertainment and personal hobbies. Due to the increased activities of unmanned airplanes, many security problems have emerged, including flight path errors to undesired destinations, secondary threats due to exposed securities caused by the capture of unmanned airplanes in hostile countries. In this paper, we find security vulnerabilities in UAVs such as GPS spoofing, hacking captured video information, malfunction due to signal attenuation through jamming, and exposure of personal information due to image shooting. In order to solve this problem, the stability of the unstructured data is secured by setting the encryption of the video shooting information section using the virtual private network (VPN) to prevent the GPS spoofing attack. In addition, data integrity was ensured by applying personal information encryption and masking techniques to minimize the secondary damage caused by exposure of the UAV and to secure safety. It is expected that it will contribute to the safe use and stimulation of industry in the application field of UAV currently growing.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.203-205
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• 2005

A reactor protection system (RPS) plays the roles of generating the reactor trip signal and the engineered safety features (ESF) actuation signal when the monitored plant processes reach predefined limits. A Korean project group is developing a new digitalized RPS and the Cabinet Operator Module (COM) of the RPS which is used for the RPS integrity testing and monitoring by an equipment operator. A flat panel display (FPD) with a touch screen capability is provided as a main user interface for the RPS operation. To support the RPS COM user interface design, actually the FPD screen design, we developed a user interface style guide because the system designer could not properly deal with the many general human factors design guidelines. To develop the user interface style guide, various design guideline gatherings, a walk-though with a video recorder, guideline selection with respect to user interface design elements, determination of the properties of the design elements, discussion with the system designers, and a conversion of the properties into a screen design were carried out. This paper describes the process in detail and the findings in the course of the style guide development.

• Journal of the Korea Institute of Building Construction
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• v.2 no.3
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• pp.131-138
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• 2002

The objective of the study is to examine the characteristic correlations between reinforcing carbon fiber and interfacial adhesion agent since the interfacial adhesion strength between reinforcing carbon fiber and matrices is believed to be an essential element influencing the physical properties in carbon fiber reinforced cement composite using slurry method. The integrity of interfacial adhesion between reinforcing fiber and cement not only affects the quality of fiber reinforced cement composite but also influences to a large degree the physical properties of the cement composite when producing carbon fiber reinforced cement composite using slurry method. Having analyzed the physical properties 1.e., water content, tensile strength, flexural strength and flexural toughness of carbon fiber reinforced cement composite specimens, C-PAM(cation polyacrylamide) was determined to be an optimum interfacial adhesion agent. The study has also demonstrated that interfacial adhesion strength varies largely on the content and type of the reinforcing fiber. Judging from magnified view of the tensile shear cross-section using VMS(video microscope system), interfacial adhesion strength between reinforcing fiber and matrices is affected by the type of interfacial adhesion agent. According to the result of the experiments, C-PAM was determined to be an ideal interfacial adhesion agent when using carbon fiber in producing carbon fiber reinforced cement composite with the optimum content of carbon fiber being established.

• Smart Structures and Systems
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• v.6 no.9
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• pp.1025-1039
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• 2010

Measuring displacement response for civil structures is very important for assessing their performance, safety and integrity. Recently, video-based techniques that utilize low-cost high-resolution digital cameras have been developed for such an application. These techniques however have relatively low sampling frequency and the results are usually contaminated with noises. In this study, an integrated visual-inertial measurement method that combines a monocular videogrammetric displacement measurement technique and a collocated accelerometer is proposed for displacement and velocity measurement of civil engineering structures. The monocular videogrammetric technique extracts three-dimensional translation and rotation of a planar target from an image sequence recorded by one camera. The obtained displacement is then fused with acceleration measured from a collocated accelerometer using a multi-rate Kalman filter with smoothing technique. This data fusion not only can improve the accuracy and the frequency bandwidth of displacement measurement but also provide estimate for velocity. The proposed measurement technique is illustrated by a shake table test and a pedestrian bridge test. Results show that the fusion of displacement and acceleration can mitigate their respective limitations and produce more accurate displacement and velocity responses with a broader frequency bandwidth.

• Smart Structures and Systems
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• v.28 no.6
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• pp.799-810
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• 2021

When monitoring the structural integrity of a bridge using data collected through accelerometers, identifying the profile of the load exerted on the bridge from the vehicles passing over it becomes a crucial task. In this study, the speed and location of vehicles on the deck of a bridge is reconfigured using real-time video to implicitly associate the load applied to the bridge with the response from the bridge sensors to develop an image-based deep learning network model. Instead of directly measuring the load that a moving vehicle exerts on the bridge, the intention in the proposed method is to replace the correlation between the movement of vehicles from CCTV images and the corresponding response by the bridge with a neural network model. Given the framework of an input-output-based system identification, CCTV images secured from the bridge and the acceleration measurements from a cantilevered beam are combined during the process of training the neural network model. Since in reality, structural damage cannot be induced in a bridge, the focus of the study is on identifying local changes in parameters by adding mass to a cantilevered beam in the laboratory. The study successfully identified the change in the material parameters in the beam by using the deep-learning neural network model. Also, the method correctly predicted the acceleration response of the beam. The proposed approach can be extended to the structural health monitoring of actual bridges, and its sensitivity to damage can also be improved through optimization of the network training.

• Geomechanics and Engineering
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• v.22 no.2
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• pp.133-142
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• 2020

The evolution of the mining-induced fracture network formed during longwall top coal caving (LTCC) has a great influence on the gas drainage, roof control, top coal recovery ratio and engineering safety of aquifers. To reveal the evolution of the mining-induced stress and fracture network formed during LTCC, the fracture network in front of the working face was observed by borehole video experiments. A discrete element model was established by the universal discrete element code (UDEC) to explore the local stress distribution. The regression relationship between the fractal dimension of the fracture network and mining stress was established. The results revealed the following: (1) The mining disturbance had the most severe impact on the borehole depth range between approximately 10 m and 25 m. (2) The distribution of fractures was related to the lithology and its integrity. The coal seam was mainly microfractures, which formed a complex fracture network. The hard rock stratum was mainly included longitudinal cracks and separated fissures. (3) Through a numerical simulation, the stress distribution in front of the mining face and the development of the fracturing of the overlying rock were obtained. There was a quadratic relationship between the fractal dimension of the fractures and the mining stress. The results obtained herein will provide a reference for engineering projects under similar geological conditions.

• Journal of the Korea Society of Computer and Information
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• v.13 no.1
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• pp.253-260
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• 2008

This paper is based on the ubiquitous network of telematics technology, equipped with a black box to the car by a unique address given to IPv6. The driver's black box at startup and operation of certification, and the car's driving record handling video signals in real-time sensor signals handling to analyze the records. Through the recorded data is encrypted transmission, and the Ubiquitous network of base stations, roadside sensors through seamless mobility and location tracking data to be generated. This is a file of Transportation Traffic Operations Center as a unique address IPv6 records stored in the database. The car is equipped with a black box used on the road go to Criminal cases, the code automotive black boxes recovered from the addresses and IPv6, traffic records stored in a database to compare the data integrity verification and authentication via secure. This material liability in the courtroom and the judge Forensic data are evidence of the recognition as a highly secure. convenient and knowledge in the information society will contribute to human life.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.89-89
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• 2022

Soybean (Glycine max (L.) Merr.) is a representative food resource. To preserve the integrity of soybean, it is necessary to protect soybean yield and seed quality from threats of various pests and diseases. Riptortus pedestris is a well-known insect pest that causes the greatest loss of soybean yield in South Korea. This pest not only directly reduces yields but also causes disorders and diseases in plant growth. Unfortunately, no resistant soybean resources have been reported. Therefore, it is necessary to identify the distribution and movement of Riptortus pedestris at an early stage to reduce the damage caused by insect pests. Conventionally, the human eye has performed the diagnosis of agronomic traits related to pest outbreaks. However, due to human vision's subjectivity and impermanence, it is time-consuming, requires the assistance of specialists, and is labor-intensive. Therefore, the responses and behavior patterns of Riptortus pedestris to the scent of mixture R were visualized with a 3D model through the perspective of artificial intelligence. The movement patterns of Riptortus pedestris was analyzed by using time-series image data. In addition, classification was performed through visual analysis based on a deep learning model. In the object tracking, implemented using the YOLO series model, the path of the movement of pests shows a negative reaction to a mixture Rina video scene. As a result of 3D modeling using the x, y, and z-axis of the tracked objects, 80% of the subjects showed behavioral patterns consistent with the treatment of mixture R. In addition, these studies are being conducted in the soybean field and it will be possible to preserve the yield of soybeans through the application of a pest control platform to the early stage of soybeans.