• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.12
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• pp.546-554
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• 2019

Typically, closed-circuit television (CCTV) monitoring is mainly used for post-processes (i.e. to provide evidence after an incident has occurred), but by using a streaming video feed, machine-based learning, and advanced image recognition techniques, current technology can be extended to respond to crimes or reports of missing persons in real time. The multi-CCTV cooperation technique developed in this study is a program model that delivers similarity information about a suspect (or moving object) extracted via CCTV at one location and sent to a monitoring agent to track the selected suspect or object when he, she, or it moves out of range to another CCTV camera. To improve the operating efficiency of local government CCTV control centers, we describe here the partial automation of a CCTV control system that currently relies upon monitoring by human agents. We envisage an integrated crime prevention service, which incorporates the cooperative CCTV network suggested in this study and that can easily be experienced by citizens in ways such as determining a precise individual location in real time and providing a crime prevention service linked to smartphones and/or crime prevention/safety information.

• Korean journal of food and cookery science
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• v.26 no.6
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• pp.677-684
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• 2010

The purpose of this study was to investigate the effects of black foods (black rice and black garlic) and the ratio of black garlic on the quality of Sulgiddeok. Pasting properties as measured by a rapid visco analyzer (RVA) were lower for black rice flour than white rice flour. Colorimetric analysis revealed that L, a, b values were dependent on the type of rice. For texture profiles, texture was associated with RVA profiles. During storage, hardness of black rice Sulgiddeok increased to a lesser degree than that of control. After observation via scanning electron microscopy (SEM), black rice Sulgiddeok showed a honeycomb-like network structure. In sensory analysis, black rice Sulgiddeok showed a tendency to prefer the control. The addition of appropriate black garlic (BG1) helped to improve the quality. In accordance with the aforementioned results, decreased retrogradation related to black rice Sulgiddeok and black foods (black rice and black garlic) could result in quality products with high nutritional value.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.1-10
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• 2021

The interest in underwater acoustic sensor networks (UWASNs), along with the rapid development of underwater industries, has increased. To operate UWASNs efficiently, it is important to adopt well-designed medium access control (MAC) protocols that prevent collisions and allow the sharing of resources between nodes efficiently. On the other hand, underwater channels suffer from a narrow bandwidth, long propagation delay, and low data rate, so existing terrestrial node pairing schemes for non orthogonal multiple access (NOMA) cannot be applied directly to underwater environments. Therefore, a multi-dimensional node pairing scheme is proposed to consider the unique underwater channel in UWASNs. Conventional NOMA schemes have considered the channel quality only in node pairing. Unlike previous schemes, the proposed scheme considers the channel gain and many other features, such as node fairness, traffic load, and the age of data packets to find the best node-pair. In addition, the sender employs a list of candidates for node-pairs rather than path loss to reduce the computational complexity. The simulation results showed that the proposed scheme outperforms the conventional scheme by considering the fairness factor with 23.8% increases in throughput, 28% decreases in latency, and 5.7% improvements in fairness at best.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.1
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• pp.15-26
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• 2013

IP-based Wireless Sensor Networks (IP-WSNs) are gaining importance for their broad range of applications in health-care, home automation, environmental monitoring, industrial control, vehicle telematics and agricultural monitoring. In all these applications, mobility in the sensor network with special attention to energy efficiency is a major issue to be addressed. Because of the energy inefficiency of networks-based mobility management protocols can be supported in IP-WSN. In this paper we propose a network based mobility supported IP-WSN protocol called Multicasting-based inter-Domain Mobility Management Scheme in Sensor-based Fast Proxy Mobile IPv6 Networks (mSFP). Based on [8,20], We present its network architecture and evaluate its performance by considering the signaling and mobility cost. Our analysis shows that the proposed scheme reduces the signaling cost, total cost, and mobility cost. With respect to the number of IP-WSN nodes, the proposed scheme reduces the signaling cost by 7% and the total cost by 3%. With respect to the number of hops, the proposed scheme reduces the signaling cost by 6.9%, the total cost by 2.5%, and the mobility cost by 1.5%. With respect to the number of IP-WSN nodes, the proposed scheme reduces the mobility cost by 1.6%.

• Korean Chemical Engineering Research
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• v.57 no.2
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• pp.274-282
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• 2019

In recent years, big data analysis has been expanded to include automatic control through reinforcement learning as well as prediction through modeling. Research on the utilization of image data is actively carried out in various industrial fields such as chemical, manufacturing, agriculture, and bio-industry. In this paper, we applied NASNet, which is an AutoML reinforced learning algorithm, to DeepU-Net neural network that modified U-Net to improve image semantic segmentation performance. We used BRATS2015 MRI data for performance verification. Simulation results show that DeepU-Net has more performance than the U-Net neural network. In order to improve the image segmentation performance, remove dropouts that are typically applied to neural networks, when the number of kernels and filters obtained through reinforcement learning in DeepU-Net was selected as a hyperparameter of neural network. The results show that the training accuracy is 0.5% and the verification accuracy is 0.3% better than DeepU-Net. The results of this study can be applied to various fields such as MRI brain imaging diagnosis, thermal imaging camera abnormality diagnosis, Nondestructive inspection diagnosis, chemical leakage monitoring, and monitoring forest fire through CCTV.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.2
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• pp.295-310
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• 2014

DCS (Distributed Control System), the main control system of power plants, is an automated system for enhancing operational efficiency by monitoring, tuning and real-time operation. DCS is becoming more intelligent and open systems as Information technology are evolving. In addition, there are a large amount of investment to enable proactive facility management, maintenance and risk management through the predictive diagnostics. However, new upcoming weaponized malware, such as Stuxnet designed for disrupting industrial control system(ICS), become new threat to the main control system of the power plant. Even though these systems are not connected with any other outside network. The main control systems used in the power plant usually have been used for more than 10 years. Also, this system requires the extremely high availability (rapid recovery and low failure frequency). Therefore, installing updates including security patches is not easy. Even more, in some cases, installing security updates can break the warranty by the vendor's policy. If DCS is exposed a potential vulnerability, serious concerns are to be expected. In this paper, we conduct the penetration test by using NESSUS, a general-purpose vulnerability scanner under the simulated environment configured with the Ovation version 1.5. From this result, we suggest a log analysis method to detect the security infringement and react the incident effectively.

• The Korean Journal of Rheology
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• v.11 no.2
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• pp.159-167
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• 1999

Sandwich injection molding is one of the remarkable polymer processes recently developed from conventional injection molding. But it is almost impossible to do theoretical investigation that we've researched it through numerical simulation. In this paper, numerical simulation on the study of sandwich injection molding is based on Finite Element Method and FAN/Control Volume method. In addition to conventional filling parameter that can confirm skin polymer melt front, new filling parameters have been introduced to confirm core polymer melt front advancement. These filling parameters are defined in each layer which is divided to solve temperature field along the thickness direction. One can notice different filling patterns resulted from the variation of material properties such as viscosities and power-law indexes, and processing conditions such as switch-over times and wall temperatures. It gives us a better understanding of the sandwich injection molding process. And we can recognize that it's the core polymer spatial distribution after the completion of filling that is the most important key point to use this process for industrial molding process.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.1
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• pp.1-5
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• 2010

Recently emphasizing the importance of security such as national major institutions' facilities or major industrial facilities for the maintenance of security/crime prevention due to specialization of the Green Information Technology(G-IT) and Green Ubiquitous Technology(G-UT) industry fields, The Security System Building linked high technology within the government-related organization, enterprise and army the military is urgently required. This paper is about the green USN intelligent an unmanned guard MUX system that receive the signals, from alarm device within surveillance area, with various ways of communication techniques and then transmit to local control center and remote control server trough TCP/IP network. This study enables the mutual senergy effect by realizing a total solution of an unmanned guard system and also significantly contributes to the global/domestic market expansion. That can be applied to the crime prevention/security fields in the Green Ubiquitous Environment Implemented Business(survalance-Home, Gu-City, Gu-Health, etc.), and will contribute to expand companies with international competitiveness that can provide the Green Ubiquitous Vision(Gu-Vision).

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1405-1408
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• 2005

An embedded system has been applied to many fields including households and industrial sites. In the past, user interface products with simple functions were commercialized .but now user demands are increasing and the system has more various applicable fields due to a high penetration rate of the Internet. Therefore, the demand for embedded system is tend to rise In this paper, we Implementation of an embedded system for image tracking. This system is used a fixed IP for the reliable server operation on TCP/IP networks. A real time broadcasting of video image on the internet was developed by using an USB camera on the embedded Linux system. The digital camera is connected at the USB host port of the embedded board. all input images from the video camera is continuously stored as a compressed JPEG file in a directory at the Linux web-server. And each frame image data from web camera is compared for measurement of displacement Vector. That used Block matching algorithm and edge detection algorithm for past speed. And the displacement vector is used at pan/tilt motor control through RS232 serial cable. The embedded board utilized the S3C2410 MPU Which used the ARM 920T core form Samsung. The operating system was ported to embedded Linux kernel and mounted of root file system. And the stored images are sent to the client PC through the web browser. It used the network function of Linux and it developed a program with protocol of the TCP/IP.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.189-196
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• 2023

As the manufacturing paradigm shifts, various collaborative robots are creating new markets. Demand for collaborative robots is increasing in all industries for the purpose of easy operation, productivity improvement, and replacement of manpower who do simple tasks compared to existing industrial robots. However, accidents frequently occur during work caused by collaborative robots in industrial sites, threatening the safety of workers. In order to construct an industrial site through robots in a human-centered environment, the safety of workers must be guaranteed, and there is a need to develop a collaborative robot guard system that provides reliable communication without the possibility of dispatch. It is necessary to double prevent accidents that occur within the working radius of cobots and reduce the risk of safety accidents through sensors and computer vision. We build a system based on OPC UA, an international protocol for communication with various industrial equipment, and propose a collaborative robot guard system through image analysis using ultrasonic sensors and CNN (Convolution Neural Network). The proposed system evaluates the possibility of robot control in an unsafe situation for a worker.