• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.5
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• pp.939-955
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• 2010

With the progress of IT and mobile positioning technologies, various types of location-based services (LBS) have been proposed and implemented. Finding a shortest path between two nodes is one of the most fundamental tasks in many LBS related applications. So far, there have been many research efforts on the shortest path finding problem. For instance, $A^*$ algorithm estimates neighboring nodes using a heuristic function and selects minimum cost node as the closest one to the destination. Pruning method, which is known to outperform the A* algorithm, improves its routing performance by avoiding unnecessary exploration in the search space. For pruning, shortest paths for all node pairs in a map need to be pre-computed, from which a shortest path container is generated for each edge. The container for an edge consists of all the destination nodes whose shortest path passes through the edge and possibly some unnecessary nodes. These containers are used during routing to prune unnecessary node visits. However, this method shows poor performance as the number of unnecessary nodes included in the container increases. In this paper, we focus on this problem and propose a new border line-based pruning scheme for path routing which can reduce the number of unnecessary node visits significantly. Through extensive experiments on randomly-generated, various complexity of maps, we empirically find out optimal number of border lines for clipping containers and compare its performance with other methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.3955-3971
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• 2020

Due to the significant increase in the use of autonomous car technology, it is essential to integrate this technology with high-precision digital map data containing more precise and accurate roadway information, as compared to existing conventional map resources, to ensure the safety of self-driving operations. While existing map technologies may assist vehicles in identifying their locations via Global Positioning System, it is however difficult to update the environmental changes of roadways in these maps. Roadway vision algorithms can be useful for building autonomous vehicles that can avoid accidents and detect real-time location changes. We incorporate a hybrid architectural design that combines unsupervised classification of vision data with supervised joint fusion classification to achieve a better noise-resistant algorithm. We identify, via a deep learning approach, an intelligent hybrid fusion algorithm for fusing multimodal vision feature data for roadway classifications and characterize its improvement in accuracy over unsupervised identifications using image processing and supervised vision classifiers. We analyzed over 93,000 vision frame data collected from a test vehicle in real roadways. The performance indicators of the proposed hybrid fusion algorithm are successfully evaluated for the generation of roadway digital maps for autonomous vehicles, with a recall of 0.94, precision of 0.96, and accuracy of 0.92.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.11
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• pp.3384-3389
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• 2009

There are two major problems with current National GAP system. One was false in traceability record because it was written or inputted by farmers or distributers and no other measures to check the accuracy was valid. The other was incapability of tracking back and recalling the contaminated agricultural products. For solving these matters, IT convergence model which combined information technology with agricultural experience is elaborated. In IT convergence model, video analytic system classifies every activity depending on the pre-programmed farming process and create the traceability data automatically. Also real time trace system based on USN would solve the problem of tracking back. This system transmits the present location and monitors data of agricultural products from farm to table at all times.

• Journal of the Korea institute for structural maintenance and inspection
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• v.22 no.1
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• pp.107-114
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• 2018

In this study, the damage detection method is proposed for the rotational stiffness of connections in steel moment frames by using artificial neural network(ANN). The flexural moment of columns, natural frequencies, modeshapes are used for the input layer in ANN while the damage index, that signify the damage level, is used for the output layer in ANN. The 5-story steel moment frame as an example structure is used to generate the train and test data. Total number of damage scenarios considered is 829. From the results of application, it is shown that the proposed method can accurately estimate the location and level of damages.

• Journal of Environmental Impact Assessment
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• v.23 no.4
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• pp.237-250
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• 2014

A wide range of projects for ocean renewable energy are currently in development around the world and ocean energy industries continue to receive significant support from their governments. Surrounded by sea on three sides, Korea has potentially abundant renewable ocean energy resources, which include tidal current, tidal range, offshore wind power, osmotic pressure and ocean thermal energy. Numerous ocean renewable energy projects has been developed in Korea. Nevertheless, there are some concerns that those developments often select an environmentally unsuitable location and/or there are very few existing information on those environmental effects. The purpose of this study is to improve supporting policies and regulation systems of ocean renewable energy development in Korea by reviewing and compiling government policies and environmental assessment systems related to ocean renewable energy development around the world. The study suggests several policy implications for its environmental-friendly development in Korea, including requirements of strategic environmental assessment for proactive and environmentally suitable site selection of ocean renewable energy development and continuous post-development environmental monitoring, and so on.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.5862-5887
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• 2019

In this paper, we propose a two-way relaying scheme using non-orthogonal multiple access (NOMA) technology. In this scheme, two sources transmit packets with each other under the assistance of the decode-and-forward (DF) relays, called as a TWDFNOMA protocol. The cooperative relays exploit successive interference cancellation (SIC) technique to decode sequentially the data packets from received summation signals, and then use the digital network coding (DNC) technique to encrypt received data from two sources. A max-min criterion of end-to-end signal-to-interference-plus-noise ratios (SINRs) is used to select a best relay in the proposed TWDFNOMA protocol. Outage probabilities are analyzed to achieve exact closed-form expressions and then, the system performance of the proposed TWDFNOMA protocol is evaluated by these probabilities. Simulation and analysis results discover that the system performance of the proposed TWDFNOMA protocol is improved when compared with a conventional three-timeslot two-way relaying scheme using DNC (denoted as a TWDNC protocol), a four-timeslot two-way relaying scheme without using DNC (denoted as a TWNDNC protocol) and a two-timeslot two-way relaying scheme with amplify-and-forward operations (denoted as a TWANC protocol). Particularly, the proposed TWDFNOMA protocol achieves best performances at two optimal locations of the best relay whereas the midpoint one is the optimal location of the TWDNC and TWNDNC protocols. Finally, the probability analyses are justified by executing Monte Carlo simulations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.5
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• pp.2363-2374
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• 2016

Communication occurs through verbal elements, which usually involve language, as well as non-verbal elements such as facial expressions, eye contact, and gestures. In particular, among these non-verbal elements, gestures are symbolic representations of physical, vocal, and emotional behaviors. This means that gestures can be signals toward a target or expressions of internal psychological processes, rather than simply movements of the body or hands. Moreover, gestures with such properties have been the focus of much research for a new interface in the NUI/NUX field. In this paper, we propose a method for recognizing the number of fingers and detecting the hand region based on the depth information and geometric features of the hand for application to an NUI/NUX. The hand region is detected by using depth information provided by the Kinect system, and the number of fingers is identified by comparing the distance between the contour and the center of the hand region. The contour is detected using the Suzuki85 algorithm, and the number of fingers is calculated by detecting the finger tips in a location at the maximum distance to compare the distances between three consecutive dots in the contour and the center point of the hand. The average recognition rate for the number of fingers is 98.6%, and the execution time is 0.065 ms for the algorithm used in the proposed method. Although this method is fast and its complexity is low, it shows a higher recognition rate and faster recognition speed than other methods. As an application example of the proposed method, this paper explains a Secret Door that recognizes a password by recognizing the number of fingers held up by a user.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.3916-3936
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• 2014

Smartphone applications like games, image processing, e-commerce and social networking are gaining exponential growth, with the ubiquity of cellular services. This demands increased computational power and storage from mobile devices with a sufficiently high bandwidth for mobile internet service. But mobile nodes are highly constrained in the processing and storage, along with the battery power, which further restrains their dependability. Adopting the unlimited storage and computing power offered by cloud servers, it is possible to overcome and turn these issues into a favorable opportunity for the growth of mobile cloud computing. As the mobile internet data traffic is predicted to grow at the rate of around 65 percent yearly, even advanced services like 3G and 4G for mobile communication will fail to accommodate such exponential growth of data. On the other hand, developers extend popular applications with high end graphics leading to smart phones, manufactured with multicore processors and graphics processing units making them unaffordable. Therefore, to address the need of resource constrained mobile nodes and bandwidth constrained cellular networks, the computations can be migrated to resourceful servers connected to cloud. The server now acts as a bridge that should enable the participating mobile nodes to offload their computations through Wi-Fi directly to the virtualized server. Our proposed model enables an on-demand service offloading with a decision support system that identifies the capabilities of the client's hardware and software resources in judging the requirements for offloading. Further, the node's location, context and security capabilities are estimated to facilitate adaptive migration.

• Journal of Broadcast Engineering
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• v.22 no.1
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• pp.78-86
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• 2017

The Internet of Things can offer disabled people the assistance and support, which is essential to achieve a good quality of life. The visually impaired people need assistance in finding locations, detecting obstacles on the way, and getting directions while moving around to reach their destination. Based on this persistent need, this paper proposes a navigation system for blind people using Internet of Things. The technologies used in our proposed system are: a smart cane containing an RFID reader and an ultrasonic sensor, a smart phone and Internet. The sensed data from the ultrasonic sensor for detecting obstacle is converted to International Standard format from ISO/IEC 23005-5 (MPEG-V Part 5). The system detects the blind person's location using the RFID tags implemented on the way. The system uses voice message in the smart phone to communicate with the blind person to lead him to his destination. The proposed system has been tested to navigate successfully in the campus.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.51 no.5
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• pp.600-605
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• 2018

The Indo-Pacific bottlenose dolphins Tursiops aduncus are the only cetacean species that can be observed visually on coastal areas of Jeju Island and regarded as one of valuable tour resources. We attempted to figure out location and timing information of the dolphin sightings collected from two major social media, Naver $Caf{\acute{e}}$ and Instagram. 142 of dolphin sighting information were derived from 2,501 dolphin related postings on Naver $Caf{\acute{e}}$ between 2004 to 2017. 292 informative postings also were found on Instagram through hashtag searching. The number of posts about dolphin sighting was not frequent until 2014. Since 13 posts were found in 2014, dramatic increase of the sighting numbers was accelerated as 38 in 2015, 93 in 2016 and 269 in 2017. 195 (45.7%) from coastal area of Daejeong-eup, south-western part of the Island, were posted. The number of dolphin sightings also high from Gujwa-eup(n=50, 11.7%), Hangyeong-myeon (n=49, 11.5%), Seongsan-eup (n=38, 8.9%) and Seogwipo-si (n=34, 8.0%). Our results show that social media data has a high potential to be used as a data source for study of distribution pattern of the dolphins.