• Journal of the Korea Society of Computer and Information
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• v.11 no.3
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• pp.117-124
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• 2006

In this paper, we propose the optimal migration path searching method including path adjustment and reassignment techniques for an efficient migration of mobile agent which has an autonomous ability for some task processing. In traditional agent system, if the various and large quantify of task processing were required from the users, it could be derive excessive network traffic and overload due to increasing the size of agent. And also, if an agent migrates from node to node according to routing schedules specified by the user at which the most of network traffic occurs, it could not actively cope with particular situations such as communication loss and node obstacles and required much cost for node traversal Therefore. this paper presents the migration method of agent which can try to adjust and reassign path to the destination automatically through the optimal path search using by network traffic perception in stead of the passive routing schedule by the user. An optimal migration path searching and adjustment methods ensure the migration reliability on distributed nodes and reduce the traversal task processing time of mobile agent by avoiding network traffic paths and node obstacles.

• Journal of the Korea Society of Computer and Information
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• v.18 no.11
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• pp.115-124
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• 2013

In this paper, we suggest a secure data dissemination by Lightweight Individual Encryption Multicast scheme over wireless sensor networks using the individual encryption method with Forward Error Correction instead of the group key encryption method. In wireless sensor networks, a sink node disseminates multicast data to the number of sensor nodes to update the up to date software such as network re-programming and here the group key encryption method is the general approach to provide a secure transmission. This group key encryption approach involves re-key management to provide a strong secure content distribution, however it is complicated to provide group key management services in wireless sensor networks due to limited resources of computing, storage, and communication. Although it is possible to control an individual node, the cost problem about individual encryption comes up and the individual encryption method is difficult to apply in multicast data transmission on wireless sensor networks. Therefore we only use 0.16% of individually encrypted packets to securely transmit data with the unicast to every node and the rest 99.84% non-encrypted encoded packets is transmitted with the multicast for network performance.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.9
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• pp.243-250
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• 2021

Recently, with the development of cloud computing, interest in database outsourcing is increasing. However, when the database is outsourced, there is a problem in that the information of the data owner is exposed to internal and external attackers. Therefore, in this paper, we propose a parallel range query processing algorithm that supports privacy protection. The proposed algorithm uses the Paillier encryption system to support data protection, query protection, and access pattern protection. To reduce the operation cost of a checking protocol (SRO) for overlapping regions in the existing algorithm, the efficiency of the SRO protocol is improved through a garbled circuit. The proposed parallel range query processing algorithm is largely composed of two steps. It consists of a parallel kd-tree search step that searches the kd-tree in parallel and safely extracts the data of the leaf node including the query, and a parallel data search step through multiple threads for retrieving the data included in the query area. On the other hand, the proposed algorithm provides high query processing performance through parallelization of secure protocols and index search. We show that the performance of the proposed parallel range query processing algorithm increases in proportion to the number of threads and the proposed algorithm shows performance improvement by about 5 times compared with the existing algorithm.

• Journal of the Korea Convergence Society
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• v.12 no.5
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• pp.127-138
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• 2021

The aim of this study is to demonstrate interaction as a describable field and tries to understand interaction from the perspective of attributes, thus building a theoretical to help interactive designer understand this field by common rule, rather than waste huge time and labor cost on iteration. Since the concept of interaction language has been brought out in 2000, there are varies of related academical studies, but all with defect such as proposed theoretical models are built on a non-uniform scale, or the analyzing perspective are mainly based on researcher's personal experience and being too unobjective. The value of this study is the clustered resource of research which mainly based on academical review. It collected 21 papers researched on interaction paradigm or interaction attributes published since 2000, extracting 19 interaction attribute models which contains 174 interaction attributes. Furthermore, these 174 attributes were re-clustered based on a more unified standard scale, and the two theoretical models summarized from it are respectively focuses on interaction control and interaction experience, both of which covered 6 independent attributes. The propose of this theoretical models and the analyzation of the cluster static will contribute on further revealing of the importance of interaction attribute, or the attention interaction attribute has been paid on. Also, in this regard, the interactive designer could reasonably allocate their energy during design process, and the future potential on various direction of interaction design could be discussed.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.3
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• pp.7-15
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• 2019

Cloud computing markets are rapidly growing as cost savings and business innovation are being carried out through ICT worldwide. In line with this paradigm, the nation is striving to introduce cloud computing in various areas, including the public sector and defense sector, through various research. In the defense sector, DIDC was established in 2015 by integrating military, naval, air and military computing centers, and it provides cloud services in the form of IaaS to some systems in the center. In DIDC and various future cloud defense systems, It is an important issue to ensure availability in cloud defense systems in the defense sector because system failures such as network delays and system resource failures are directly linked to the results of battlefields. However, ensuring the highest levels of availability for all systems in the defense cloud can be inefficient, and the efficiency that can be gained from deploying a cloud system can be reduced. In this paper, we classify and define the level of availability of defense cloud systems step by step, and propose the strategy of introducing Erasure coding and failure acceptance systems, and disaster recovery system technology according to each level of availability acquisition.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.568-573
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• 2018

UAV(Unmanned Aerial Vehicle) is widely used in space information construction, agriculture, fisheries, weather observation, communication, and entertainment fields because they are cheaper and easier to operate than manned aircraft. In particular, UAV have attracted much attention due to the speed and cost of data acquisition in the field of spatial information construction. However, ortho image images produced using UAVs are distorted in buildings and forests. It is necessary to solve these problems in order to utilize the geospatial information field. In this study, fixed wing, rotary wing, vertical take off and landing type UAV were used to detect distortions of ortho image of UAV under various conditions, and various object areas such as construction site, urban area, and forest area were captured and analysed. Through the research, it was found that the redundancy of the unmanned aerial vehicle image is the biggest factor of the distortion phenomenon, and the higher the flight altitude, the less the distortion phenomenon. We also proposed a method to reduce distortion of orthoimage by lowering the resolution of original image using DTM (Digital Terrain Model) to improve distortion. Future high-quality unmanned aerial vehicles without distortions will contribute greatly to the application of UAV in the field of precision surveying.

• Journal of Platform Technology
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• v.6 no.4
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• pp.59-68
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• 2018

The objective of this study is to develop an embedded antenna structure with NFC and WPC composite functions. By selecting stable materials, the optimal component ratio of the polymer sheet was determined. The low cost embedded winding method compared to the existing FPCB was devised. During the winding process, characterization and process technology were developed. We also fabricated a ferrite mold to process the WPC grooves and developed the process technology for optimizing the WPC antenna. The following conclusions were obtained. (1) Optimum composition ratio was derived as Fe 87.5%, Si 7%, Al 5.5% and selected as the final material. (2) Optimal sheet conditions were derived from the experimental evaluation method and the experimental design method through the combination test of the optimized sheet and the conventional mass production FPCB. (3) According to coil diameter and inner diameter, Q value fluctuation, resistance value and efficiency fluctuation are obtained. Therefore, the most suitable coil condition is selected and Rx matching is performed. (4) The EMV load modulation test and the cognitive distance test of the polymer sheet and the ferrite sheet showed that the recognition distance of the polymer sheet at 1k and 4K was 32-33 mm and the recognition distance of the ferrite sheet at the same condition was 30-31 mm.

• The Journal of the Convergence on Culture Technology
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• v.5 no.3
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• pp.125-130
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• 2019

This research is about alternative measure of main components for sprinkler system like automatic wet pipe sprinkler system, dry pipe sprinkler system, pre-action sprinkler system, vacuum sprinkler system, deluge sprinkler system, and so on. By replacing the alarm check valve, dry valve, pre-operated valve, and deluge open valve with a solenoid valve, it be can be simplifed the various processes of the manufacturing process into one process, it creates an environment in which one standardized product can be produced simultaneously on a single machine. Therefore, it could improve the price competitiveness of products, reduce the maintenance cost, and help the adaptability of new sprinkler systems in the future. There is a benefit when it comes to apply to sprinkler system. Only replace the valve which is used to control primary and secondary valve such as wet, dry, pre operated, vacuum, deluge system valve. Other components such as retarding chambers, automatic air compressors, accelerators or adjusters, supervisory panels, vacuum pumps, and manual starters can be used as they are, so they can be easily applied to existing sprinkler system. It is needed to legal and institutional study for solenoid valve applied sprinkler system to commercialize.

• Journal of Navigation and Port Research
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• v.43 no.1
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• pp.42-48
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• 2019

The significance of PNT information in the fourth industrial revolution is viewed differently in relation to the past. Autonomous vehicles, autonomous vessels, smart grids, and national infrastructure require sustainable and reliable services in addition to their high precision service. Satellite navigation system, which is the most representative system for providing PNT information, receive signals from satellites outside the earth so signal reception power is low and signal structures for civilian use are open to the public. Therefore, it is vulnerable to intentional and unintentional interference or hacking. Satellite navigation systems, which can easily acquire high performance of PNT information at low cost, require alternatives due to its vulnerability to the hacking. This paper proposed R-Mode (Ranging Mode) technology that utilizes currently operated navigation and communication infrastructure in terms of Signals of OPportunity (SoOP). For this, the Nationwide Differential Global Navigation Satellite System (NDGNSS), which currently gives a service of Medium Frequency (MF) navigation signal broadcasting, was used to validate the feasibility of a backup infrastructure in domestic maritime areas through simulation analysis.

• Journal of Korean Neurosurgical Society
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• v.62 no.4
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• pp.442-449
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• 2019

Objective : Bone mineral density (BMD) is an important consideration during fusion surgery. Although dual X-ray absorptiometry is considered as the gold standard for assessing BMD, quantitative computed tomography (QCT) provides more accurate data in spine osteoporosis. However, QCT has the disadvantage of additional radiation hazard and cost. The present study was to demonstrate the utility of artificial intelligence and machine learning algorithm for assessing osteoporosis using Hounsfield units (HU) of preoperative lumbar CT coupling with data of QCT. Methods : We reviewed 70 patients undergoing both QCT and conventional lumbar CT for spine surgery. The T-scores of 198 lumbar vertebra was assessed in QCT and the HU of vertebral body at the same level were measured in conventional CT by the picture archiving and communication system (PACS) system. A multiple regression algorithm was applied to predict the T-score using three independent variables (age, sex, and HU of vertebral body on conventional CT) coupling with T-score of QCT. Next, a logistic regression algorithm was applied to predict osteoporotic or non-osteoporotic vertebra. The Tensor flow and Python were used as the machine learning tools. The Tensor flow user interface developed in our institute was used for easy code generation. Results : The predictive model with multiple regression algorithm estimated similar T-scores with data of QCT. HU demonstrates the similar results as QCT without the discordance in only one non-osteoporotic vertebra that indicated osteoporosis. From the training set, the predictive model classified the lumbar vertebra into two groups (osteoporotic vs. non-osteoporotic spine) with 88.0% accuracy. In a test set of 40 vertebrae, classification accuracy was 92.5% when the learning rate was 0.0001 (precision, 0.939; recall, 0.969; F1 score, 0.954; area under the curve, 0.900). Conclusion : This study is a simple machine learning model applicable in the spine research field. The machine learning model can predict the T-score and osteoporotic vertebrae solely by measuring the HU of conventional CT, and this would help spine surgeons not to under-estimate the osteoporotic spine preoperatively. If applied to a bigger data set, we believe the predictive accuracy of our model will further increase. We propose that machine learning is an important modality of the medical research field.