• Annual Conference of KIPS
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• 2011.04a
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• pp.353-356
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• 2011

스마트 폰의 등장과 모바일 인터넷을 제공함에 따라 휴대폰은 음성통신 수단이 아닌 웹을 통하여 서비스를 제공받는 도구 또는 각종 게임 및 응용 어플리케이션을 제공하는 놀이수단으로도 발전하였고, 이로인하여 사용량도 증가하였다. 사용량의 급증으로 인하여 모바일 광고에 대한 업계의 관심도 증가 하였지만, 한정적인 출력화면에 의하여 제한적일 수밖에 없다. 이를 보완하기 위해, 본 논문에서는 기업의 로고 광고의 효과를 극대화 할 수 있는 안드로이드 기반 로고를 인식하는 증강현실 시스템을 제안 하였고, 이를 구현 하여 실 제폰에 탑재한 후 다양한 성능 분석을 하였다. 실험결과, 그 가능성은 확인하였지만 현하드웨어 성능으로는 실시간으로 지원하기에는 역부족임을 알 수 있었다.

• International Journal of Computer Science & Network Security
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• v.23 no.6
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• pp.59-67
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• 2023

The healthcare industry continues to adopt and integrate smart technology in its operations, from medical devices to managing operations. However, the adoption curve has not been smooth, and the historical record of technology adoption in the Kingdom of Saudi Arabia reveals the existence of both known and unknown issues. This review paper is aimed to explain the influences and barriers present in the Saudi healthcare sector affecting IoT technology adoption. A comprehensive discussion of the literature illustrated that Vision 2030, the privatisation trend, transformation in disease patterns and ageing, issues in management and increasing public awareness are the key drivers that may influence the need for the medical Internet of Things (mIoT) in Saudi healthcare. However, based on the past trend, the introduction and adoption of mIoT will likely experience issues such as noncompliance from doctors and nurses due to negative beliefs, lack of knowledge and inadequate perception of effort requirements. Thus, in-depth research of the factors associated with mIoT technology adoption is suggested for a smooth transition.

• Management & Information Systems Review
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• v.37 no.1
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• pp.75-101
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• 2018

Social enterprise in Korea has faced with many problems such as small size, management capability, lack of technology and weak ability to obtain resources despite its quantitative growth, raising concern over sustainability of social enterprises. Despite such tough environment, unique feature of social enterprise, differentiated from commercial enterprise is that it has clear social mission. In addition, social enterprise has the organizational feature in that vulnerable social group of workers coexists with ordinary workers, and plays a role of helping independence of vulnerable social group. Due to this feature, successful organizational socialization of members in social enterprise is a very important feature. Based on assumption that social mission of social enterprise can be utilized as the unique competitiveness of social enterprise through vision-sharing in the organization, and may give positive effects on successful organizational socialization of organization members, this study aims to conduct empirical research on relationship between vision-sharing and organizational socialization and to explore mediation effects of organizational health as organizational environmental element in relationship between vision sharing and organizational socialization. This study was conducted on 156 employees working at social enterprises. As a result of study, first, vision sharing is found to have positive effects on organizational socialization at social enterprises. Second, vision sharing in social enterprise has positive effects on organizational health. Third, vitality and community-oriented in social enterprise are found to have mediation effects among lower elements of organizational health in relationship between vision sharing and organizational socialization. In conclusion, it is confirmed that the more visions of organization are shared, the more members recognize their organization healthy, resulting in successful organizational socialization. This study is meaningful in that it presents the plans for successful organizational socialization of members of social enterprise including vulnerable groups and that it is the empirical study on plans of social enterprise on human resource management.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.127-135
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• 2004

With the wide-spread use of multimedia technology, the demand for the image processing engineer is increasing in various fields. But there are few engineers who can develop practical applications in the image processing area. To teach practical image processing techniques, we need an integrated education environment which can efficiently present the image processing theory and, at the same time, provide interactive experiments for the theory presented. In this paper, we propose an integrated education environment for the image processing, which is called MTES. It consists of the theory presentation systems and the experiment systems. The theory presentation systems support multimedia data, web document and Microsoft Powerpoint$^{TM}$ file. It is tightly integrated with the experiment systems which are developed based on the integrated image processing algorithm development system, called Hello-Vision.n.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.1
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• pp.94-98
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• 2015

Recently, with the rapid advancement in information and computer vision technology, a CCTV system using object recognition and tracking has been studied in a variety of fields. However, it is difficult to recognize a precise object outdoors due to varying pixel values by moving background elements such as shadows, lighting change, and moving elements of the scene. In order to adapt the background outdoors, this paper presents to analyze a variety of background models and proposed background update algorithms based on the weight factor. The experimental results show that the accuracy of object detection is maintained, and the number of misrecognized objects are reduced compared to previous study by using the proposed algorithm.

• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.3
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• pp.315-327
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• 2017

In this paper, we present a method for estimating of position and velocity of a moving target by using the range and the bearing measurements from multiple sensors of aiming unit. In many cases, conventional low cost gyro sensor and a portable laser range finder(LRF) degrade the accuracy of estimation. To enhance these problems, we propose two methods. The first is background image tracking and the other is principal component analysis (PCA). The background tracking is used to assist the low cost gyro censor. And the PCA is used to cope with the problems of a portable LRF. In this paper, we prove that our method is robust with respect to low-frequency, biased and noisy inputs. We also present a comparison between our method and the extended Kalman filter(EKF).

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.318-324
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• 2000

Ultrasonic and magnetic resonance imaging systems are used to visualize the interior states of biological objects. These nondestructive methods have many advantages but too much expensive. And they do not give exact color information and may miss some details. If it is allowed to destruct some biological objects to get the interior and exterior information, constructing 3D image from the series of the sliced sectional images gives more useful information with relatively low cost. In this paper, PC based automatic 3D model generator was developed. The system was composed of three modules. One is the object handling and image acquisition module, which feeds and slices objects sequentially and maintains the paraffin cool to be in solid state and captures the sectional image consecutively. The second is the system control and interface module, which controls actuators for feeding, slicing, and image capturing. And the last is the image processing and visualization module, which processes a series of acquired sectional images and generates 3D graphic model. The handling module was composed of the gripper, which grasps and feeds the object and the cutting device, which cuts the object by moving cutting edge forward and backward. Sliced sectional images were acquired and saved in the form of bitmap file. The 3D model was generated to obtain the volumetric information using these 2D sectional image files after being segmented from the background paraffin. Once 3-D model was constructed on the computer, user could manipulate it with various transformation methods such as translation, rotation, scaling including arbitrary sectional view.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.15 no.1
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• pp.107-117
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• 2012

We estimated the potential area roof greening in Gyeonggi-do that will mitigate the heat island effect. The estimation was based on building age, roof shape, and building use which were recorded in the building register from "Sewoomteo, the Building Administration System in the Ministry of Land, Transport and Maritime Affairs. The estimated potential roof greening area in Gyeonggi-do was approximately $102.5km^2$ assuming that the buildings for residence, public, education(school), office, shopping mall are appropriate for roof greening. The area occupied by apartment buildings over six-story was 76.3% of the potential roof greening area 10.2% for individual houses, 5.9% for under five-story apartment buildings, and 3.7% for school buildings. The result indicated that it is residential buildings that we need to pay attention for roof greening, especially high-rise buildings over six-story. Greening of the whole estimated area, $102.5km^2$, in Gyeonggi-do will result in the increase of green space per capita by $8.74m^2$. This is 1.65 times greater than the area of current urban parks, and 1.97 times greater than the total area of neighborhood parks, children's parks, and pocket parks. Greening of the estimated roof area will increase green coverage of urban area by twice, adding to current green coverage of the urban areas, 11.3%, in 10 major cities. In particular, the effect of roof greening would be remarkable in inceasing the green space of Anyang City, Gwangmyeong City, and Guri City where neighborhood park area falls short.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.9
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• pp.1088-1095
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• 2019

The information and communication technology that is being developed recently has been greatly influencing the automobile market. In recent years, devices equipped with IT technology have been installed for the safety and convenience of the driver. However, it has the advantage of increased convenience as well as the disadvantage of increasing traffic accidents due to driver's distraction. In order to prevent such accidents, it is necessary to develop safety systems of various types and ways. In this paper implements a platform that can recognize LDWS and FCWS and PDWS by using a single camera without using radar sensor and camera fusion and stereo camera method using two or more sensors, and proposes to study multi-function driving safety platform using a single camera by analyzing recognition rate evaluation and validity on a vehicle.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3708-3728
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• 2021

Indian herbal plants are used in agriculture and in the food, cosmetics, and pharmaceutical industries. Laboratory-based tests are routinely used to identify and classify similar herb species by analyzing their internal cell structures. In this paper, we have applied computer vision techniques to do the same. The original leaf image was preprocessed using the Chan-Vese active contour segmentation algorithm to efface the background from the image by setting the contraction bias as (v) -1 and smoothing factor (µ) as 0.5, and bringing the initial contour close to the image boundary. Thereafter the segmented grayscale image was fed to a leaky capacitance fired neuron model (LCFN), which differentiates between similar herbs by combining different groups of pixels in the leaf image. The LFCN's decay constant (f), decay constant (g) and threshold (h) parameters were empirically assigned as 0.7, 0.6 and h=18 to generate the 1D feature vector. The LCFN time sequence identified the internal leaf structure at different iterations. Our proposed framework was tested against newly collected herbal species of natural images, geometrically variant images in terms of size, orientation and position. The 1D sequence and shape features of aloe, betel, Indian borage, bittergourd, grape, insulin herb, guava, mango, nilavembu, nithiyakalyani, sweet basil and pomegranate were fed into the 5-fold Bayesian regularization neural network (BRNN), K-nearest neighbors (KNN), support vector machine (SVM), and ensemble classifier to obtain the highest classification accuracy of 91.19%.