• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.2
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• pp.149-155
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• 2020

The Korea Highway Traffic Authority provides statistics that analyze the causes of traffic accidents that occurred since 2015 using the Traffic Accident Analysis System (TAAS). it was reported Through TAAS that the driver's forward carelessness was the main cause of traffic accidents in 2018. As statistics on the cause of traffic accidents, 51.2 percent used mobile phones and watched DMB while driving, 14 percent did not secure safe distance, and 3.6 percent violated their duty to protect pedestrians, representing a total of 68.8 percent. In this paper, we propose a system that has improved the advanced driver assistance system ADAS (Advanced Driver Assistance Systems) by utilizing CNN (Convolutional Neural Network) among the algorithms of Deep Learning. The proposed system learns a model that classifies the movement of the driver's face and eyes using Conv2D techniques which are mainly used for Image processing, while recognizing and detecting objects around the vehicle with cameras attached to the front of the vehicle to recognize the driving environment. Then, using the learned visual steering model and driving environment data, the hazard is classified and detected in three stages, depending on the driver's view and driving environment to assist the driver with the forward and blind spots.

• Korean Security Journal
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• no.14
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• pp.549-567
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• 2007

In the post-Cold war world, the threat of terrorism is emerging as the most formidable challenge. The terrorist attacks including 9.11 World Trade Center attack have proved such challenge. It has become apparent that no country is safe from the scourage of terrorism. The region of the southeast Asia is no exception to this trend. The Bali bombing of 2002, killing about 200 innocent people, demonstrated that the threat environment had significantly altered. Today, local and regional groups such as Jemiah Islamiah can conduct terrorist operations as devastating as those carried out by Al Qaeda. As fighting terrorism is a complex multi-dimensional task, the responsibility for fighting terrorism must not rest with a single government. The burden must be shared by both the local governments and international communities. In addition, To prevent another bombing of the scale of Bali, countries in the region of southeast Asia must respond decisively. The purpose of this study is to examine the current situation on terrorism in the southeast Asia and to provide perspectives on future terrorism in this region. To foster the better understanding, historical survey on the terrorism in the region and local terrorist groups' network with the foreign terrorist organizations including Al Qaeda have been researched. Based on the result of the research, this paper provides a perspectives and evaluation on the future terrorism in the southeast Asia. It also provides an implications for our reference in the war against terrorism.

• Nuclear Engineering and Technology
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• v.52 no.11
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• pp.2452-2459
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• 2020

Neutron spectrum is essential to the safe operation of reactors. Traditional online neutron spectrum measurement methods still have room to improve accuracy for the application cases of wide energy range. From the application of artificial neural network (ANN) algorithm in spectrum unfolding, its accuracy is difficult to be improved for lacking of enough effective training data. In this paper, an adaptive deviation-resistant neutron spectrum unfolding method based on transfer learning was developed. The model of ANN was trained with thousands of neutron spectra generated with Monte Carlo transport calculation to construct a coarse-grained unfolded spectrum. In order to improve the accuracy of the unfolded spectrum, results of the previous ANN model combined with some specific eigenvalues of the current system were put into the dataset for training the deeper ANN model, and fine-grained unfolded spectrum could be achieved through the deeper ANN model. The method could realize accurate spectrum unfolding while maintaining universality, combined with detectors covering wide energy range, it could improve the accuracy of spectrum measurement methods for wide energy range. This method was verified with a fast neutron reactor BN-600. The mean square error (MSE), average relative deviation (ARD) and spectrum quality (Qs) were selected to evaluate the final results and they all demonstrated that the developed method was much more precise than traditional spectrum unfolding methods.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.2
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• pp.78-86
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• 2004

Recently GPS and mobile GIS technologies based on LBS(location based service) have played an important role as DSS(decision supporting system) for domestic forest fire extinguishment policies. In this study forest fire extinguishments information management system based on mobile GIS technique was designed to seize the exact location on wireless network so that it helps to guide the safe and efficient extinguishments affairs and provide the extinguishments environment toward ground fighting teams and the central forest government in real time. Moreover, possibly to operate this system, the foundation technologies by the name of '.gci' such as the spatial data compression method, the spatial data transmission method over wireless network and the spatial analysis interface on PDA should be mainly considered. Especially, in this study the spatial data compression method having high compression rate from 51% to 62% for each polygon, line, and point data, without the loss of data was developed.

• Smart Structures and Systems
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• v.20 no.5
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• pp.549-562
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• 2017

The US railroad network carries 40% of the nation's total freight. Railroad bridges are the most critical part of the network infrastructure and, therefore, must be properly maintained for the operational safety. Railroad managers inspect bridges by measuring displacements under train crossing events to assess their structural condition and prioritize bridge management and safety decisions accordingly. The displacement of a railroad bridge under train crossings is one parameter of interest to railroad bridge owners, as it quantifies a bridge's ability to perform safely and addresses its serviceability. Railroad bridges with poor track conditions will have amplified displacements under heavy loads due to impacts between the wheels and rail joints. Under these circumstances, vehicle-track-bridge interactions could cause excessive bridge displacements, and hence, unsafe train crossings. If displacements during train crossings could be measured objectively, owners could repair or replace less safe bridges first. However, data on bridge displacements is difficult to collect in the field as a fixed point of reference is required for measurement. Accelerations can be used to estimate dynamic displacements, but to date, the pseudo-static displacements cannot be measured using reference-free sensors. This study proposes a method to estimate total transverse displacements of a railroad bridge under live train loads using acceleration and tilt data at the top of the exterior pile bent of a standard timber trestle, where train derailment due to excessive lateral movement is the main concern. Researchers used real bridge transverse displacement data under train traffic from varying bridge serviceability levels. This study explores the design of a new bridge deck-pier experimental model that simulates the vibrations of railroad bridges under traffic using a shake table for the input of train crossing data collected from the field into a laboratory model of a standard timber railroad pile bent. Reference-free sensors measured both the inclination angle and accelerations of the pile cap. Various readings are used to estimate the total displacements of the bridge using data filtering. The estimated displacements are then compared to the true responses of the model measured with displacement sensors. An average peak error of 10% and a root mean square error average of 5% resulted, concluding that this method can cost-effectively measure the total displacement of railroad bridges without a fixed reference.

• Journal of Convergence Society for SMB
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• v.3 no.2
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• pp.51-56
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• 2013

Real-time processing of sensor data network, is one of the important factors. Each node in the detected data are required to be transmitted within a certain time since the accurate processing is possible. Thus, the data nodes are successfully delivered within a specified time, it is very important to check whether the. Recently more and more accurate real-time embedded systems are reliable and haejyeoseo been able to provide sophisticated services. Because of the inherent complexity of embedded systems in the physical world and the difficulty of predicting the difficulty of a safe design constraints on the runtime violation of system as to cause unexpected causes. Each node data in time detected by the time required to be passed in the appropriate processing is possible because the data transfer time in this paper, the monitoring of the sensor network through a node are allowed to exist within the time range and transmits data to the server Analysis of the data transfer time for checking whether the system was implemented. Implementation of the data transmission time to the process for analyzing and presenting, according to the procedure suggested by the transit time required for analysis a time difference analysis method, a data collection method and a data transmission time and transmission time calculating method presented.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.2
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• pp.89-103
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• 2020

As we face an aging society, the demand for personal mobility for disabled and aged people is increasing. In fact, as of 2017, the number of electric wheelchair in the country continues to increase to 90,000. However, people with disabilities and seniors are more likely to have accidents while driving, because their judgment and coordination are inferior to normal people. One of the causes of the accident is the interference of personal vehicle steering control due to unbalanced road surface conditions. In this paper, we introduce a encoder type semantic segmentation algorithm that can recognize road conditions at high speed to prevent such accidents. To this end, more than 1,500 training data and 150 test data including road surface damage were newly secured. With the data, we proposed a deep neural network composed of encoder stages, unlike the Auto-encoding type consisting of encoder and decoder stages. Compared to the conventional method, this deep neural network has a 4.45% increase in mean accuracy, a 59.2% decrease in parameters, and an 11.9% increase in computation speed. It is expected that safe personal transportation will be come soon by utilizing such high speed algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.5B
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• pp.260-267
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• 2008

As pervious the SAR(Security Aware Routing)[10] protocol is an secure Ad Hoc network protocol that finds a secure path, it is the security routing protocol that uses the security level of nodes as the routing information. However, the SAR protocol sometimes transfers data through inefficient transmission paths because it always tries to find secure nodes for a safe transmission. Since it is a protocol based on AODV[6], it will cause transmission delay as researching of security routing path. when a node is out of the data transmission range as its battery dying or movement. Although it is possible to connection of nodes because a characteristic of the SAR protocol, the connection is not easy to reconnect when the security level of intermediate node is lower than the level requested by a source node. In this paper, we suggest the MP-SAR based on the SAR to solve the SAR protocol's problem. The MP-SAR seeks multiple secure path for maintenance of data confidentiality using the expanded secure path detection techniques based on the SAR. It can transfer data quickly and reliably by using the shortest efficient path among multiple paths. In the research result, we proved a outstanding performance of MP-SAR than the previous SAR through comparison and analysis.

• International Journal of Contents
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• v.12 no.2
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• pp.12-23
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• 2016

This paper presents a novel concept of Disaster Prevention Design (DPD) and its derived subjects and topics for the safety of folk villages in both Korea and Japan. Nowadays, design concepts are focused on 'human-oriented nature' as a whole and this tendency fits to be appropriate for disaster prevention against real dangers of a future society, which is expected to have far more complicated features. On the other hand, convergences have performed with other areas in the field of Information Communication Technology (ICT) so that we can easily find examples like 'the strategy of ICT-based convergence' of the Korean Government in 2014. Modern content designs including UI (user interface) and USN (ubiquitous sensor network) have been developed as one of the representative areas of ICT & UD (universal design) convergences. These days this novel concept of convergence is overcoming the existing limitations of the conventional design concept focused on product and/or service. First of all, from that point our deduced topic or subject would naturally be a monitoring system design of constructional structures in folk villages for safety. We offer an integrated model of maintenance and a management-monitoring scheme. Another important point of view in the research is a safety sign or sign system installed in folk villages or traditional towns and their standardization. We would draw up and submit a plan that aims to upgrade signs and sign systems applied to folk villages in Korea and Japan. According to our investigations, floods in Korea and earthquakes in Japan are the most harmful disasters of folk villages. Therefore, focusing on floods in the area of traditional towns in Korea would be natural. We present a water-level expectation model using deep learning simulation. We also apply this method to the area of 'Andong Hahoe' village which has been registered with the World Cultural Heritage of UNESCO. Folk village sites include 'Asan Oeam', 'Andong Hahoe' and 'Chonju Hanok' villages in Korea and 'Beppu Onsen' village in Japan. Traditional Streets and Markets and Safe Schools and Parks are also chosen as nearby test-beds for DPD based on ICT. Our final goal of the research is to propose and realize an integrated disaster prevention and/or safety system based on big data for both Korea and Japan.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.400-402
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• 2019

The electric point machine, which is used for the control of the turnout used to change the track of the train, is very important in the railway system. Various wired and wireless real-time monitoring systems are used to check the status of the point machine, but there is a possibility of malfunction due to sensor or network error. In this paper, a redundant monitoring system was designed that incorporates the point machine monitoring system and the CCTV camera control system to double check the operation of the point machine. In the point machine monitoring system, the operating state of the railway converter is monitored, alarmed and transmitted over the network. The CCTV camera control system, which received this information, was required to record the status of the turnout and the point machine in question and send it to the administrator. The manager of the railway line can check the conversion status of the railway through the monitoring screen for the railway line switcher first, and then confirm the switching status directly through the CCTV camera image, thereby improving the reliability of the point machine operation. It will also enable the safe and efficient operation of personnel for management. It is expected to contribute to preventing a derailment caused by a malfunction of the point machine.