• Korean Journal of Optics and Photonics
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• v.31 no.6
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• pp.281-289
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• 2020

This paper reports a slim mobile lens design using a hybrid refractive/diffractive optical element. Conventionally a wide field of view (FOV) camera-lens design adopts a retrofocus type having a negative (-) lens at the forefront, so that it improves in imaging performance over the wide FOV, but with the sacrifice of longer total track length (TTL). However, we chose a telephoto type as a baseline design layout having a positive (+) lens at the forefront, to achieving slimness, based on the specification analysis of 23 reported optical designs. Following preliminary optimization of a baseline design and aberration analysis based on Zernike-polynomial decomposition, we applied a hybrid refractive/diffractive element to effectively reduce the residual chromatic spherical aberration. The optimized optical design consists of 6 optical elements, including one hybrid element. It results in a very slim telephoto ratio of 1.7, having an f-number of 2.0, FOV of 90°, effective focal length of 2.23 mm, and TTL of 3.7 mm. Compared to a comparable conventional lens design with no hybrid elements, the hybrid design improved the value of the modulation transfer function (MTF) at a spatial frequency of 180 cycles/mm from 63% to 71-73% at zero field (0 F), and about 2-3% at 0.5, 0.7, and 0.9 fields. It was also found that a design with a hybrid lens with only two diffraction zones at the stop achieved the same performance improvement.

• Journal of Service Research and Studies
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• v.11 no.1
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• pp.45-58
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• 2021

Requirements engineering can be seen as proceeding with various processes and activities such as extraction, analysis, specification, management, and verification without temporal and spatial constraints in the development environment of information systems that are becoming large and decentralized. Developing requirements well and conducting continuous evaluation and management is the shortcut to success in project management, and it is recognized as a very important matter in relation to requirements in the information system audit. When we conduct information system audit and conducting projects subject to audit, we need to improve the required engineering aspect. Therefore, this study derives inspection items suitable for the target project by referring to the audit inspection manual and audit inspection guide when conducting the current audit, and relates to the required engineering aspect among the contents of the inspection guide for each business type that is the basis for deriving the inspection items were derived for each audit point/audit area for the project management and quality assurance project type corresponding to the inspection items. The suitability of the extracted occupation items was verified through a questionnaire survey by experts.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.1-25
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• 2020

In this paper, we suggest an application system architecture which provides accurate, fast and efficient automatic gasometer reading function. The system captures gasometer image using mobile device camera, transmits the image to a cloud server on top of private LTE network, and analyzes the image to extract character information of device ID and gas usage amount by selective optical character recognition based on deep learning technology. In general, there are many types of character in an image and optical character recognition technology extracts all character information in an image. But some applications need to ignore non-of-interest types of character and only have to focus on some specific types of characters. For an example of the application, automatic gasometer reading system only need to extract device ID and gas usage amount character information from gasometer images to send bill to users. Non-of-interest character strings, such as device type, manufacturer, manufacturing date, specification and etc., are not valuable information to the application. Thus, the application have to analyze point of interest region and specific types of characters to extract valuable information only. We adopted CNN (Convolutional Neural Network) based object detection and CRNN (Convolutional Recurrent Neural Network) technology for selective optical character recognition which only analyze point of interest region for selective character information extraction. We build up 3 neural networks for the application system. The first is a convolutional neural network which detects point of interest region of gas usage amount and device ID information character strings, the second is another convolutional neural network which transforms spatial information of point of interest region to spatial sequential feature vectors, and the third is bi-directional long short term memory network which converts spatial sequential information to character strings using time-series analysis mapping from feature vectors to character strings. In this research, point of interest character strings are device ID and gas usage amount. Device ID consists of 12 arabic character strings and gas usage amount consists of 4 ~ 5 arabic character strings. All system components are implemented in Amazon Web Service Cloud with Intel Zeon E5-2686 v4 CPU and NVidia TESLA V100 GPU. The system architecture adopts master-lave processing structure for efficient and fast parallel processing coping with about 700,000 requests per day. Mobile device captures gasometer image and transmits to master process in AWS cloud. Master process runs on Intel Zeon CPU and pushes reading request from mobile device to an input queue with FIFO (First In First Out) structure. Slave process consists of 3 types of deep neural networks which conduct character recognition process and runs on NVidia GPU module. Slave process is always polling the input queue to get recognition request. If there are some requests from master process in the input queue, slave process converts the image in the input queue to device ID character string, gas usage amount character string and position information of the strings, returns the information to output queue, and switch to idle mode to poll the input queue. Master process gets final information form the output queue and delivers the information to the mobile device. We used total 27,120 gasometer images for training, validation and testing of 3 types of deep neural network. 22,985 images were used for training and validation, 4,135 images were used for testing. We randomly splitted 22,985 images with 8:2 ratio for training and validation respectively for each training epoch. 4,135 test image were categorized into 5 types (Normal, noise, reflex, scale and slant). Normal data is clean image data, noise means image with noise signal, relfex means image with light reflection in gasometer region, scale means images with small object size due to long-distance capturing and slant means images which is not horizontally flat. Final character string recognition accuracies for device ID and gas usage amount of normal data are 0.960 and 0.864 respectively.

• 한국공간정보시스템학회:학술대회논문집
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• 2004.12a
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• pp.169-181
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• 2004

SK Telecom has already constructed GIMS system as the base common framework of LBS/GIS service system based on OGC(OpenGIS Consortium)'s international standard for the first mobile vector map service in 2002, But as service content appears more complex, renovation has been needed to satisfy multi-purpose, multi-function and maximum efficiency as requirements have been increased. This research is for preparation ion of GML3-based platform to upgrade service from GML2 based GIMS system. And with this, it will be possible for variety of application services to provide location and geographic data easily and freely. In GML 3.0, it has been selected animation, event handling, resource for style mapping, topology specification for 3D and telematics services for mobile LBS multimedia service. And the schema and transfer protocol has been developed and organized to optimize data transfer to MS(Mobile Stat ion) Upgrade to GML 3.0-based GIMS system has provided innovative framework in the view of not only construction but also service which has been implemented and applied to previous research and system. Also GIMS channel interface has been implemented to simplify access to GIMS system, and service component of GIMS internals, WFS and WMS, has gotten enhanded and expanded function.

• Korean Journal of Heritage: History & Science
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• v.49 no.2
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• pp.56-69
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• 2016

Flame resistant treatment has been applied since 1973 for fire prevention in historical wooden buildings, but several problems, such as whitening and discoloration are constantly occurring in some Dancheong, in spite of evaluation criteria. It is supposed that these phenomena are caused by the stability issue of flame retardant, Dancheong production methods, the residue of chemicals, which were applied in the past, building location environments, etc., but no evaluation and cause inspection has been performed. Therefore, this study aims to verify the effect of flame retardant on Dancheong by producing Pseudo-samples and setting spatial and temporal environment conditions. Pseudo-samples of Dancheong were produced using three methods; the method specified in the Standard Specification of Properties; the method, which is generally used in the site and the traditional method. For different environment conditions of pseudo-samples, the areas were classified into a coastal area and an inland area and the places were classified into a sunny place and a wetland. After applying a flame retardant, annual variations were inspected for 12 months and change aspects were observed through scan and regular observation. In annual variation inspection, various variations like whitening, decolorization, dissolution and exfoliation were found and especially, whitening was most dominant. When the effect of flame retardant depending on the production methods was analyzed, whitening occurred in all the three production methods. It is supposed that this is because calcium(Ca) was contained in the coloring material of each production method and it reacted with phosphorous(P) of flame retardant. When the effect of flame retardant depending on the environment conditions was analyzed, whitening occurred more in the coastal area than in the inland area and it reduced in the building in a sunny place, which was constructed using the traditional method. It is supposed that this results from the humidity change and the difference of glue used in each production method. In conclusion, for using a flame retardant containing phosphorous(P), there is a need to check if calcium components including Oyster Shell White were used in Dancheong in advance and to conduct various preliminary studies on place conditions and Dancheong construction conditions.