• Spatial Information Research
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• v.20 no.1
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• pp.91-103
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• 2012

Recently, there has been much interest in the middleware that can smoothly acquire and analyze Geosensor information which includes sensor readings, location, and its surrounding spatial information. In relation to development of the middleware, researchers have proposed various algorithms for energy-efficient information filtering in Geosensor networks and have proposed Geosensor web technologies which can efficiently mash up sensor readings with spatial information on the web, also. The filtering algorithms and Geosensor Web technologies have contributions on energy-efficiency and OpenAPI, however the algorithms and technologies could not support easy and rapid development of u-GIS applications that need various Geosensor networks. Therefore, we propose a new Geosensor network middleware that can dramatically reduce the time and cost required for development of u-GIS applications that integrate heterogeneous Geosensor networks. The proposed middleware has several merits of being capable of acquiring heterogeneous Geosensor information using the standard SWE and an extended SQL, optimally performing various attribute and spatial operators, and easily integrating various Geosensor networks. Finally, we clarify our middleware's distinguished features by developing a prototype that can monitor environmental information in realtime using spatial information and various sensor readings of temperature, humidity, illumination, imagery, and location.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2002.11a
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• pp.147-153
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• 2002

Due to the growth of population and industrial development at the coastal cities, there has been much increase in necessity to effective control of the wastes into the coastal water and river. The amount of disposal at those waters has been increased rapidly and it is necessary for us to track of it in order to keep the water clean. The investigation and research related to the water quality in this region have been conducted continuously but the systematic survey of the disposed wastes at the bottom was neglected and/or minor. In this study we surveyed the status of disposed waste distribution at the bottom coastal water and river from the scanned images. The intensity of sound received by the side scan sonar tow vehicle from the sea floor provides information as to the general distribution and characteristics of the superficial wastes. The port and starboard side scanned images produced from a transducer borne on a tow fish connected by tow cable to a tug boat have the area with width of 22m∼112m, and band of 44m∼224m. All data are displayed in real-time on a high-resolution color display (1280 ${\times}$ 1024 pixels) together with position information by DGPS. From the field measurement and analysis of the recorded images, we could draw the location and distribution of bottom disposals. Furthermore, we made a database system which might be fundamental for planning the waste reception and process control system.

• Journal of Animal Environmental Science
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• v.7 no.3
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• pp.155-164
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• 2001

Environmental factors such as $NH_3,\;H_2S,\;CO_2$, dust, temperature, and humidity in the animal house are a potential health hazard to humans and animals. Until now, most of measurement methods can only provide periodic results with low accuracy. A data acquisition system which can measure continuously and simultaneously $NH_3,\;H_2S,\;CO_2$, temperature, and humidity was developed and installed in two pig houses. Daily changes of environment for the pig-houses were investigated by the data acquisition system. In order to evaluate NH$_3$sensor, gas samples were obtained and NH$_3$concentrations were measured at nine positions; combinations of three positions(inlet, middle, and outlet) and three heights(0 cm, 40 cm, 150 cm). Ammonia concentration of 14.0 ~37.1 ppm for slurry pig-house is higher than that of 8.4~29.7 ppm for scraper pig-house, and there were no statistical differences among the positions. However, the concentration of $NH_3$at 150 cm was higher than thats of 0 cm and 40 cm.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.185-192
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• 2021

Various methods have been proposed to determine the defect detection of welding bead, and recently sensor data and image data inspection have been steadily announced. There are advantages that sensor data inspection is highly accurate, and two-dimensional-based image data inspection is able to determine the position of the welding bead. However, when analyzing only with sensor data, it is difficult to determine whether the welding has been performed at the correct position. On the other hand, the image data inspection does not have high accuracy due to noise and measurement errors. In this paper, we propose a method that can complement the shortcomings of each inspection method and increase its advantages to improve accuracy and speed up inspection by fusing sensor data inspection which are average current, average volt, and mixed gas data, and image data inspection methods and is implemented as software. In addition, it is intended to allow users to conveniently and intuitively analyze and grasp the results by performing analysis using a graphical user interface(GUI) and checking the data and inspection results used for the inspection. Sensor inspection is performed using the characteristics of each sensor data, and image data is inspected by applying a morphology geodesic active contour algorithm. The experimental results showed 98% accuracy, and when performing the inspection on the four image data, and sensor data the inspection time was about 1.9 seconds, indicating the performance of software that can be used as a real-time inspector in the welding process.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.9
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• pp.595-602
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• 2013

WiFi fingerprinting is well known as an effective localization technique used for indoor environments. However, this technique requires a large amount of pre-built fingerprint maps over the entire space. Moreover, due to environmental changes, these maps have to be newly built or updated periodically by experts. As a way to avoid this problem, crowd-sourced fingerprint mapping attracts many interests from researchers. This approach supports many volunteer users to share their WiFi fingerprints collected at a specific environment. Therefore, crowd-sourced fingerprinting can automatically update fingerprint maps up-to-date. In most previous systems, however, individual users were asked to enter their positions manually to build their local fingerprint maps. Moreover, the systems do not have any principled mechanism to keep fingerprint maps clean by detecting and filtering out erroneous fingerprints collected from multiple users. In this paper, we present the design of a crowd-sourced fingerprint mapping and localization(CMAL) system. The proposed system can not only automatically build and/or update WiFi fingerprint maps from fingerprint collections provided by multiple smartphone users, but also simultaneously track their positions using the up-to-date maps. The CMAL system consists of multiple clients to work on individual smartphones to collect fingerprints and a central server to maintain a database of fingerprint maps. Each client contains a particle filter-based WiFi SLAM engine, tracking the smartphone user's position and building each local fingerprint map. The server of our system adopts a Gaussian interpolation-based error filtering algorithm to maintain the integrity of fingerprint maps. Through various experiments, we show the high performance of our system.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.32 no.4
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• pp.340-355
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• 1996

In order to suggest the useful information of fishing ground, a data base system on 32bit personal computer was constructed and handled by using the catch data of Korean tuna long-line, catch by species, fishing time and place, fish price and etc. mainly from 1975 to 1992. The results obtained are as follows ; In the fishing ground displaying catch rate, the catch rate has reduced as time passed, and this penomenon was more evident in Indian. And yellowfin have high catch tate in the Western Pacific of low latitute region, bigeye tuna have in the Eastern. The region of high catch rate of bigeye tuna was moved from the Indian and the Atlantic to the Pacific. The patterns of catch numbers of yellowfin and bigeye tuna appeared nearly same that, having nothing to do with catch numbers in all oceans. The region of least catch was the Northwestern Pacific, the regions of most catch were the Western Indian and the Pacific of low latitute. As to simulation of fishing ground estimation, there were economical grounds in the Western Pacific of low latitute region, the Eastern Pacific of this, the Western Indian, the Eastern Indian, and the Atlantic, in order.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.3
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• pp.461-467
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• 2019

Advances in location-aware and IoT (Internet of Things) technology increase the rapid generation of massive movement data. Knowledge discovery from massive movement data helps us to understand the urban flow and traffic management. This paper proposes a method to analyze frequent origin-destination sequence patterns from irregular spatiotemporal taxi pick-up locations. The proposed method starts by conducting cluster analysis and then run a frequent sequence pattern analysis based on identified clusters as a base unit. The experimental data is Seoul taxi trajectory data between 7 a.m. and 9 a.m. during one week. The experimental results present that significant frequent sequence patterns occur within Gangnam. The significant frequent sequence patterns of different regions are identified between Gangnam and Seoul City Hall area. Further, this study uses administrative boundaries as a base unit. The results based on administrative boundaries fails to detect the frequent sequence patterns between different regions. The proposed method can be applied to decrease not only taxis' empty-loaded rate, but also improve urban flow management.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.10
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• pp.493-498
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• 2017

Capsule endoscopy is specialized for the observation of small intestine that is difficult to access by general endoscopy. The diagnostic procedure through capsule endoscopy consists of three stages: examination of indicant, endoscopy, and diagnosis. At this time, key information needed for diagnosis includes indicant, lesions, and suspected disease information. In this paper, these information are defined as semantic features and the extracting process is defined as semantic-based analysis. It is performed in whole capsule endoscopy. First, several symptoms of patient are checked before capsule endoscopy to get some information on suspected disease. Next, capsule endoscopy is performed by checking the suspected diseases. Finally, diagnosis is concluded by using supporting information. At this time, some association are used to conclude diagnosis. For example, there are the disease association between the symptom and the disease to identify the expected disease, and the anatomical association between the location of the lesion and supporting information. However, existing knowledge models such as MST and CEST only lists the simple term related to endoscopy and cannot consider such semantic associations. Therefore, in this paper, we propose association-based knowledge model for supporting diagnosis of capsule endoscopy. The proposed model is divided into two; a disease model and anatomical model of small intestine, interesting area(organs) of capsule endoscopy. It can effectively support diagnosis by providing key information for capsule endoscopy.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.4
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• pp.413-422
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• 2012

After development of GPS in the 1960's, the United States released SA(Selective Availability) in 2000 and then the GPS has become commercialized to the present. The result of repeatedly developed GPS observation, the GPS real-time observation methods is RTK which basically always needs two base stations and has a fault of the accuracy decreasing as the distance between a mobile station and a receiver is increasing. Because of these weakness, VRS method has come out. VRS(Virtual Reference Station) generates the imaginary point near mobile station from several observatory datum of GPS, sets the accurate location of mobile station, thus shows high reliability and mobility. Now, the cadastral datum point is used with azimuth, repetition, and graphical traversing method for traverse network. The result of measurement indicates many problems because of different accomplishment interval given point, restrictions on the length of the conductor, many errors on the observations. So, this study did comparative analysis of the cadastral datum points through VRS method by Continuously Operating Reference Station. Through the above comparative analysis, The comparative result between surveyed result with repetition method through total station observed Cadastral Control Points and surveyed result with VRS-RTK has shown that average error of x-axis is -0.08m, average error of y-axis, +0.07m and average distance error is +0.11m.

• Korean Journal of Plant Resources
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• v.33 no.1
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• pp.1-14
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• 2020

This study was conducted to analyze community structure and species composition of Pinus densiflora for. erecta Stand in Mt. Cheonchuk (653 m). Field survey was carried out from June to September in 2013. 74 plots (20×20 m) were set up, 5 herb layer plots (3×3 m) were constructed for each plot, and there, Diameter at Breast Heigh t(DBH), height, environmental factor, annual growth were measured. Vascular plants were surveyed as following; 66 family, 165 genus, 211 species, 2 sub species, 29 variety, 6 form 248 taxa. Results of cluster analysis for P. densiflora for. erecta forest, 3 communities were divided into; Quercus mongolica (P-1), Quercus variabilis (P-2) and Quercus aliena-Stephanandra incisa (P-3). There were significant environmental factors that organic layer, annual growth, CEC, total total nitrogen, organic matter and pH for each community. As a result of DCA, P-1 and P-2 were distributed large range of environmental factors but relatively limited in P-3. Distributions of herb layer were affected by sand, cation exchange capacity, silt and total nitrogen. Results of MRPP test for herb layer communities, it was significantly analyzed (A=0.003, P<0.008). Species diversity index was highly recorded in P-3 and influenced by cation exchange capacity, total nitrogen, annual growth in consequence of NMS analysis.