• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.6
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• pp.580-586
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• 2017

The establishment of big data service environment requires both cloud-based network technology and clustering technology to improve the efficiency of information access. These cloud-based networks and clustering environments can provide variety of valuable information in real-time, which can be an intensive target of attackers attempting illegal access. In particular, attackers attempting IP spoofing can analyze information of mutual trust hosts constituting clustering, and attempt to attack directly to system existing in the cluster. Therefore, it is necessary to detect and respond to illegal attacks quickly, and it is demanded that the security policy is stronger than the security system that is constructed and operated in the existing single system. In this paper, we investigate routing pattern changes and use them as detection information to enable active correspondence and efficient information service in illegal attacks at this network environment. In addition, through the step-by -step encryption based on the routing information generated during the detection process, it is possible to manage the stable service information without frequent disconnection of the information service for resetting.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.451-453
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• 2010

The world is rapidly evolving in the future society is based on intelligence. In such circumstances, USN(Ubiquitous Sensor Network) to implement the future ubiquitous(Ubiquitous) society have been highlighted as a key infrastructure. For realization of Ubiquitous computing(Ubiquitous Computing), The data recognized from each sensors must be collected on real-time and transferred to applied service so that they may be used as data for providing service to users. USN sensor data on the use for using a numerous sensor data provision service, service provider can publish its service in standardized registry for users to search and use the service registry. However, in previous studies using Web services standards WS-Eventing, and UDDI(Universal Description, Discovery, and Integration) as USR(USN Service Registry) for USN Application Service is unnecessary or insufficient. In this paper, data from sensors that provide information to service providers register their services and use the information for service users to explore and views on the registry of the system was designed and implemented.

• Journal of the Korea institute for structural maintenance and inspection
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• v.16 no.1
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• pp.120-130
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• 2012

As long span and complex bridges are constructed often recently, safety estimation became a big issue. Various types of measuring instruments are installed in case of long span bridge. New wireless technologies for long span bridges such as sending information through a gateway at the field or sending it through cables by signal processing the sensing data are applied these days. However, The case of occurred accidents related to bridge in the world have been reported that serious accidents occur due to lack of real-time proactive, intelligent action based on recognition accidents. To solve this problem in this study, the idea of "communication among things", which is the basic method of RFID/USN technology, is applied to the bridge monitoring system. A sensor node module for USN based intelligent bridge system in which sensor are utilized on the bridge and communicates interactively to prevent accidents when it captures the alert signals and urgent events, sends RF wireless signal to the nearest traffic signal to block the traffic and prevent massive accidents, is designed and tested by performing TinyOS based middleware design and sensor test free Space trans-receiving distance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.4
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• pp.34-42
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• 2017

Since existing nonintrusive appliance load monitoring (NIALM) studies assume that voltage fluctuations are negligible for load identification, and do not affect the identification results, the power factor or harmonic signals associated with voltage are generally not considered parameters for load identification, which limits the application of NIALM in the Smart Home sector. Experiments in this paper indicate that the parameters related to voltage and the characteristics of harmonics should be used to improve the accuracy and reliability of the load monitoring system. Therefore, in this paper, we propose an improved NIALM method that can efficiently analyze the types of household appliances and electrical energy usage in a home network environment. The proposed method is able to analyze the energy usage pattern by analyzing operation characteristics inherent to household appliances using harmonic characteristics of some household appliances as recognition parameters. Through the proposed method, we expect to be able to provide services to the smart grid electric power demand management market and increase the energy efficiency of home appliances actually operating in a home network.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.5
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• pp.401-415
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• 2005

Owing to the improved wireless communication technologies, it is possible to provide streaming service of multimedia with PDAs and mobile phones in addition to desktop PCs. Since mobile client devices have low computing power and low network bandwidth due to wireless network, the transcoding technology to adapt media for mobile client devices considering their characteristics is necessary. Transcoding servers transcode the source media to the target media within corresponding grades and provide QoS in real-time. In particular, an effective load balancing policy for transcoding servers is inevitable to support QoS for large scale mobile users. In this paper, the resource weighted load distribution policy is proposed for a fair load balance and a more scalable performance in cluster-based transcoding servers. Our proposed policy is based on the resource weighted table and number of maximum supported users, which are pre-computed for each pre-defined grade. We implement the proposed policy on cluster-based transcoding servers and evaluate its fair load distribution and scalable performance with the number of transcoding servers.

• Convergence Security Journal
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• v.18 no.5_1
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• pp.113-120
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• 2018

Today, the development of information and communication technology is rapidly increasing the number of users of network-based service, and enables real-time information sharing among users on the Internet. There are various methods in the information sharing process, and information sharing based on portal service is generally used. However, the process of information sharing serves as a cause of illegal activities in order to amplify the social interest of the relevant stakeholders. Public opinion attack using macro function can distort normal public opinion, so security measures are urgent. Therefore, security measures are urgently needed. Macro attacks are generally defined as attacks in which illegal users acquire multiple IP or ID to manipulate public opinion on the content of a particular web page. In this paper, we analyze network path information based on traceback for macro attack of a specific user, and then detect multiple access of the user. This is a macro attack when the access path information for a specific web page and the user information are matched more than once. In addition, when multiple ID is accessed for a specific web page in the same region, it is not possible to distort the overall public opinion on a specific web page by analyzing the threshold count value.

• Korean Journal of Remote Sensing
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• v.37 no.5_2
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• pp.1307-1315
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• 2021

The Changjiang Diluted Water (CDW) spreads over the East China Sea every summer and significantly affects the sea surface salinity changes in the seas around Jeju Island and the southern coast of Korea peninsula. Sometimes its effect extends to the eastern coast of Korea peninsula through the Korea Strait. Specifically, the CDW has a significant impact on marine physics and ecology and causes damage to fisheries and aquaculture. However, due to the limited field surveys, continuous observation of the CDW in the East China Sea is practically difficult. Many studies have been conducted using satellite measurements to monitor CDW distribution in near-real time. In this study, an algorithm for estimating Sea Surface Salinity (SSS) in the East China Sea was developed using the Geostationary Ocean Color Imager (GOCI). The Multilayer Perceptron Neural Network (MPNN) method was employed for developing an algorithm, and Soil Moisture Active Passive (SMAP) SSS data was selected for the output. In the previous study, an algorithm for estimating SSS using GOCI was trained by 2016 observation data. By comparison, the train data period was extended from 2015 to 2020 to improve the algorithm performance. The validation results with the National Institute of Fisheries Science (NIFS) serial oceanographic observation data from 2011 to 2019 show 0.61 of coefficient of determination (R²) and 1.08 psu of Root Mean Square Errors (RMSE). This study was carried out to develop an algorithm for monitoring the surface salinity of the East China Sea using GOCI and is expected to contribute to the development of the algorithm for estimating SSS by using GOCI-II.

• Journal of Broadcast Engineering
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• v.23 no.6
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• pp.855-865
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• 2018

Sound event detection is one of the research areas to model human auditory cognitive characteristics by recognizing events in an environment with multiple acoustic events and determining the onset and offset time for each event. DCASE, a research group on acoustic scene classification and sound event detection, is proceeding challenges to encourage participation of researchers and to activate sound event detection research. However, the size of the dataset provided by the DCASE Challenge is relatively small compared to ImageNet, which is a representative dataset for visual object recognition, and there are not many open sources for the acoustic dataset. In this study, the sound events that can occur in indoor and outdoor are collected on a larger scale and annotated for dataset construction. Furthermore, to improve the performance of the sound event detection task, we developed a dual CNN structured sound event detection system by adding a supplementary neural network to a convolutional neural network to determine the presence of sound events. Finally, we conducted a comparative experiment with both baseline systems of the DCASE 2016 and 2017.

• Journal of Broadcast Engineering
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• v.24 no.3
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• pp.495-505
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• 2019

Typical algorithms of deep learning include CNN(Convolutional Neural Networks), which are mainly used for image recognition, and RNN(Recurrent Neural Networks), which are used mainly for speech recognition and natural language processing. Among them, CNN is able to learn from filters that generate feature maps with algorithms that automatically learn features from data, making it mainstream with excellent performance in image recognition. Since then, various algorithms such as R-CNN and others have appeared in object detection to improve performance of CNN, and algorithms such as YOLO(You Only Look Once) and SSD(Single Shot Multi-box Detector) have been proposed recently. However, since these deep learning-based detection algorithms determine the success of the detection in the still images, stable object tracking and detection in the video requires separate tracking capabilities. Therefore, this paper proposes a method of combining Kalman filters into deep learning-based detection networks for improved object tracking and detection performance in the video. The detection network used YOLO v2, which is capable of real-time processing, and the proposed method resulted in 7.7% IoU performance improvement over the existing YOLO v2 network and 20 fps processing speed in FHD images.

• 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.