• Journal of Biosystems Engineering
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• v.31 no.5 s.118
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• pp.436-442
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• 2006

This research was conducted to design and develop a wired monitoring system for judging if sick or dead layers (SDL) exist in multi-tier layers battery (MLB) by machine vision, and to analyze its performance. In this study, 20 Brown Leghorn (Hi-Brown) layers aged 37 weeks old, were used as the experimental animals. The intensity of concern paid by layers on feed was over 90% during 5 minutes and 30 seconds after providing feed, and normal layers (NL) had been standing to take feed for that period. Therefore, in this study, the optimal judging time was set by this test result. The wired monitoring system developed was consisted of a driving device for carrying machine vision systems, a control program, a RS232 to RS485 convertor, an automatic positioning system, and an image capture system. An image processing algorithm was developed to find SDL in MLB by the processes of binary processing, erosion, expansion, labeling, and reckoning central coordinate of the captured images. The optimal velocity for driving unit was set up as 0.13 m/s by the test results for wired monitoring system, and the proximity switch was controlled not to be operated for 1.0 second after first image captured. The wired monitoring system developed was tested to evaluate the remote monitoring performance at lab-scale laying hen house. Results showed that its judgement success.ate on normal cage (without SDL) was 87% and that on abnormal cage (with SDL) was 90%, respectively. Therefore, it would be concluded that the wired monitoring system developed in this study was well suited to the purpose of this study.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.2
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• pp.207-215
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• 2016

The demand for spatial data service technologies is increasing lately with the development of realistic 3D spatial information services and ICT (Information and Communication Technology). Research is being conducted on the real-time provision of spatial data services through a variety of mobile and Web-based contents. Big data or cloud computing can be presented as alternatives to the construction of spatial data for the effective use of large volumes of data. In this paper, the process of building HLM (Hyper Live Map) using multi-source data to acquire stereo CCTV and other various data is presented and a big data service architecture design is proposed for the use of flexible and scalable cloud computing to handle big data created by users through such media as social network services and black boxes. The provision of spatial data services in real time using big data and cloud computing will enable us to implement navigation systems, vehicle augmented reality, real-time 3D spatial information, and single picture based positioning above the single GPS level using low-cost image-based position recognition technology in the future. Furthermore, Big Data and Cloud Computing are also used for data collection and provision in U-City and Smart-City environment as well, and the big data service architecture will provide users with information in real time.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.5
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• pp.529-534
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• 2009

In this study, we investigate the feasibility of modeling entire image strips that has been acquired from the same orbital segments. We tested sensor models based on satellite orbit and attitude with different sets(Type1 ~ Type4) of unknowns. We checked the accuracy of orbit modeling by establishing sensor models of one scene using control points extracted from the scene and by applying the models to adjacent scenes within the same orbital segments. Results indicated that modeling of individual scenes with 1st or 2nd order unknowns was recommended. We tested the accuracy of around control points, digital map using the HIST-DPW (Hanjin Information Systems & Telecommunication Digital Photogrammetric Workstation) As a result, we showed that the orbit-based sensor model is a suitable sensor model for making 1/25,000 digital map.

• 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 Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.1
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• pp.71-78
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• 2016

In the paper, we predict the number of multi-GNSS satellites and visible satellites with the navigation satellite launch plans and their nominal orbit parameters. Based on the methodology, the multi-GNSS navigation performance and DOP (Dilution of Precision) variation from 2015 to 2020 were forecasted by the Matlab simulation. To calculate the position using the multi-GNSS constellation, we determined the time-offset between the two different systems. Two different algorithms were considered for the sake of time-offset determination; that of each was applied to system level and user side. Also, the results from two algorithms were compared for evaluating each performance. For the reality, we applied the 3D map information to the simulation, which is expected to contribute for predicting the future navigation performance in urban canyon.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.2
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• pp.21-28
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• 2010

Air pollution monitoring has attracted a lot of interests because it affects directly to the human life quality. The most of the current air pollution monitoring stations use the expensive and bulky instruments and are only installed in the specific area. Therefore, it is difficult to install them to as many places as people need. In this work, we constructed a low price and small size Radio Frequency(RF) sensor system to solve this problem. This system also had the measurement range similar to the ones used in the air pollution forecast systems. This system had the sensor unit to measure the air quality, the central processing unit for air quality data acquisition, the power unit to supply the power to every units, and the RF unit for the wireless transmission and reception of the data. This system was easy to install in the field. We also added a GPS unit to track the position of the RF-sensor in real time by wireless communication. For the various measurements of the air pollution, we used CO, $O_3$, $NO_2$ sensors as gas sensors and also installed a dust sensor.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.4940-4957
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• 2019

Compared with the localization methods in the static sensor networks, node localization in dynamic sensor networks is more complicated due to the mobility of the nodes. Dynamic Sampling Localization Algorithm Based on Virtual Anchor (DSLA) is proposed in this paper to localize the unknown nodes in dynamic sensor networks. Firstly, DSLA algorithm predicts the speed and movement direction of nodes to determine a sector sampling area. Secondly, a method of calculating the sampling quantity with the size of the sampling area dynamically changing is proposed in this paper. Lastly, the virtual anchor node, i.e., the unknown node that got the preliminary possible area (PLA), assists the other unknown nodes to reduce their PLAs. The last PLA is regarded as a filtering condition to filter out the conflicting sample points quickly. In this way, the filtered sample is close to its real coordinates. The simulation results show that the DSLA algorithm can greatly improve the positioning performance when ensuring the execution time is shorter and the localization coverage rate is higher. The localization error of the DSLA algorithm can be dropped to about 20%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.5785-5804
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• 2019

The information of localization is a fundamental requirement in wireless sensor network (WSN). The method of distance vector-hop (DV-Hop), a range-free localization algorithm, can locate the ordinary nodes by utilizing the connectivity and multi-hop transmission. However, the error of the estimated distance between the beacon nodes and ordinary nodes is too large. In order to enhance the positioning precision of DV-Hop, fast triangle flip bat algorithm, which is based on curve strategy and rank transformation (FTBA-TCR) is proposed. The rank is introduced to directly select individuals in the population of each generation, which arranges all individuals according to their merits and a threshold is set to get the better solution. To test the algorithm performance, the CEC2013 test suite is used to check out the algorithm's performance. Meanwhile, there are four other algorithms are compared with the proposed algorithm. The results show that our algorithm is greater than other algorithms. And this algorithm is used to enhance the performance of DV-Hop algorithm. The results show that the proposed algorithm receives the lower average localization error and the best performance by comparing with the other algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.2C
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• pp.145-152
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• 2009

Ultra-wideband communication systems for impulse radio have merits that are possible for either high resolution ranging system or radio determination. Conventionally, in order to accomplish these functions, the rapid analog to digital convertor (ADC) is necessary to apply radio determination system operating in time domain. However, considering that low rate - wireless personal area network (LR-WPAN) aims to low-cost hardware implementation, the expensive ADC converting GHz sampling per second is not appropriate. So, this paper introduces the high resolution ranging system operating in frequency domain with using low sampling rate ADC, and a new non-coherent ranging scheme utilizing analog Frequency Modulation (FM) mode for the frequency domain transformation. To verify the superiority of the proposed ranging algorithm working in frequency domain, the suggested IEEE 802.15.4a TG channel model is used to exploit affirmative features of the proposed algorithm with conducting the simulation results.