• Journal of KIISE:Computing Practices and Letters
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• v.6 no.2
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• pp.120-134
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• 2000

In this paper we present a Distributed Object oriented Virtual computing Environment, called DOVE which consists of autonomous distributed objects interacting with one another via method invocations based on a distributed object model. DOVE appears to a user logically as a single virtual computer for a set of heterogeneous hosts connected by a network as if objects in remote site reside in one virtual computer. By supporting efficient parallelism, heterogeneity, group communication, single global name service and fault-tolerance, it provides a transparent and easy-to-use programming environment for parallel applications. Efficient parallelism is supported by diverse remote method invocation, multiple method invocation for object group, multi-threaded architecture and synchronization schemes. Heterogeneity is achieved by automatic data arshalling and unmarshalling, and an easy-to-use and transparent programming environment is provided by stub and skeleton objects generated by DOVE IDL compiler, object life control and naming service of object manager. Autonomy of distributed objects, multi-layered architecture and decentralized approaches in hierarchical naming service and object management make DOVE more extensible and scalable. Also,fault tolerance is provided by fault detection in object using a timeout mechanism, and fault notification using asynchronous exception handling methods

• Journal of Broadcast Engineering
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• v.13 no.1
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• pp.6-16
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• 2008

An instable wireless channel condition causes more packet losses and retransmissions due to interference, fading, station mobility, and so on. Therefore video streaming service over a wireless networks is a challenging task because of the changes in the wireless channel conditions and time-constraints characteristics of the video streaming services. To provide efficient video streaming over a wireless networks, QoS-enhanced MAC protocol, IEEE 802.11e, is standardized recently. Tn this paper, we propose a new network-adaptive H.264 video streaming mechanism in the IEEE 802.11e wireless networks. To improve the quality of video streaming services, video stream has to adapt to the changes in the wireless channel conditions. The wireless channel conditions are estimated by the packet loss probability and informed to the application layer by the cross-layering. According to the wireless channel information, the video streaming application filters out the low-priority data. This adaptation mechanism efficiently uses system resources because it drops the low-priority data in advance. Therefore, our cross-layer design can provide improved video streaming services to the end-user. Through the implementation and performance evaluation, we prove that the proposed mechanism improves the QoS of the video streaming by providing the smoothed playback.

• Knowledge Management Research
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• v.22 no.4
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• pp.27-40
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• 2021

Click-Through Rate (CTR) prediction is a key function that determines the ranking of candidate items in the recommendation system and recommends high-ranking items to reduce customer information overload and achieve profit maximization through sales promotion. The fields of natural language processing and image classification are achieving remarkable growth through the use of deep neural networks. Recently, a transformer model based on an attention mechanism, differentiated from the mainstream models in the fields of natural language processing and image classification, has been proposed to achieve state-of-the-art in this field. In this study, we present a method for improving the performance of a transformer model for CTR prediction. In order to analyze the effect of discrete and categorical CTR data characteristics different from natural language and image data on performance, experiments on embedding regularization and transformer normalization are performed. According to the experimental results, it was confirmed that the prediction performance of the transformer was significantly improved when the L2 generalization was applied in the embedding process for CTR data input processing and when batch normalization was applied instead of layer normalization, which is the default regularization method, to the transformer model.

• Korean Journal of Remote Sensing
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• v.27 no.1
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• pp.33-41
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• 2011

In the information communication technology, it is world-widely apparent that trend movement from internet web to smartphone app by users demand and developers environment. So it needs kinds of appropriate technological responses from geo-spatial domain regarding this trend. However, most cases in the smartphone app are the map service and location recognition service, and uses of geo-spatial contents are somewhat on the limited level or on the prototype developing stage. In this study, app for extraction of corner point features using geo-spatial imagery and their linkage to database system are developed. Corner extraction is based on Harris algorithm, and all processing modules in database server, application server, and client interface composing app are designed and implemented based on open source. Extracted corner points are applied LOD(Level of Details) process to optimize on display panel. Additional useful function is provided that geo-spatial imagery can be superimposed with the digital map in the same area. It is expected that this app can be utilized to automatic establishment of POI (Point of Interests) or point-based land change detection purposes.

• Journal of Wetlands Research
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• v.13 no.3
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• pp.593-602
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• 2011

The estuarine area of the ecological environment had been seriously damaged by reckless developments during the past half century. The demand for management in estuarine area increased but the efficient management system did not exist. Therefore the aim of this study is to develop a GIS-based integrated DB management system by integrating the ecological environmental data of each division in estuarine area. To achieve this, the system used integrated DB. It is classified into a surveyed monitoring DB in 2010 at estuarine area of Yeongsan and GIS DB to express the spatial data. The integrated DB management system was developed using VisualBasic.NET languages and Arcobjects component for Map-based spatial analysis. Also, to improve the utilization of data, the composition of GUI(Graphical User Interface) through user needs analysis, the expression of monitoring DB, the priority of layer and the function for modular unit were defined. Ultimately the system was developed based on the defined items. GIS-based integrated DB management system can support to understand the ecological environment in estuarine area of Yeongsan river. Also it will provide the users with effective sharing and environmental management of the data. In the future study, comprehensive diagnosis for ecological environment in estuarine area and the reliable prediction need to be made by connecting modeling system.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.5
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• pp.467-474
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• 2019

In this paper, we propose a novel method to improve FPS while maintaining the accuracy of YOLO v2 model in NVIDIA Jetson TX1. In general, in order to reduce the amount of computation, a conversion to an integer operation or reducing the depth of a network have been used. However, the accuracy of recognition can be deteriorated. So, we use methods to reduce computation and memory consumption through adjustment of the filter size and integrated computation of the network The first method is to replace the $3{\times}3$ filter with a $1{\times}1$ filter, which reduces the number of parameters to one-ninth. The second method is to reduce the amount of computation through CBR (Convolution-Add Bias-Relu) among the inference acceleration functions of TensorRT, and the last method is to reduce memory consumption by integrating repeated layers using TensorRT. For the simulation results, although the accuracy is decreased by 1% compared to the existing YOLO v2 model, the FPS has been improved from the existing 3.9 FPS to 11 FPS.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.515-523
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• 2021

An integrated underground spatial map consists of underground facilities, underground structures, and ground information, and is periodically updated. In this paper, we design and implement a system for detecting and extracting only changed ground objects to shorten the map update speed. To find the changed objects, all the objects are compared, which are included in the newly input map and the reference map in the integrated map. Since the entire process of comparing objects and generating results is classified by function, the implemented system is composed of several modules such as object comparer, changed object detector, history data manager, changed object extractor, changed type classifier, and changed object saver. We use two metrics: detection rate and extraction rate, to evaluate the performance of the system. As a result of applying the system to boreholes, ground wells, soil layers, and rock floors in Pyeongtaek, 100% of inserted, deleted, and updated objects in each layer are detected. In addition, it provides the advantage of ensuring the up-to-dateness of the reference map by downloading it whenever maps are compared. In the future, additional research is needed to confirm the stability and effectiveness of the developed system using various data to apply it to the field.

• Journal of Bio-Environment Control
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• v.33 no.1
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• pp.1-11
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• 2024

In this study, five artificial intelligence (AI) models: Inception v3, SqueezeNet (local), VGG-16, Painters, and DeepLoc were used to classify tea leaf diseases. Eight image categories were used: healthy, algal leaf spot, anthracnose, bird's eye spot, brown blight, gray blight, red leaf spot, and white spot. Software used in this study was Orange 3 which functions as a Python library for visual programming, that operates through an interface that generates workflows to visually manipulate and analyze the data. The precision of each AI model was recorded to select the ideal AI model. All models were trained using the Adam solver, rectified linear unit activation function, 100 neurons in the hidden layers, 200 maximum number of iterations in the neural network, and 0.0001 regularizations. To extend the functionality of Orange 3, new add-ons can be installed and, this study image analytics add-on was newly added which is required for image analysis. For the training model, the import image, image embedding, neural network, test and score, and confusion matrix widgets were used, whereas the import images, image embedding, predictions, and image viewer widgets were used for the prediction. Precisions of the neural networks of the five AI models (Inception v3, SqueezeNet (local), VGG-16, Painters, and DeepLoc) were 0.807, 0.901, 0.780, 0.800, and 0.771, respectively. Finally, the SqueezeNet (local) model was selected as the optimal AI model for the detection of tea diseases using tea leaf images owing to its high precision and good performance throughout the confusion matrix.

• Sim-seong Yeon-gu
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• v.32 no.1
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• pp.1-16
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• 2017

The purpose of this paper is to illustrate the nature of Objective Psyche based on island related case materials. Theoretical background starts with psychological meaning of islands, a kind affective symbol rather than cognitive image, and creation myths as the story of man's awareness of the world; Chaos as archaic identity (unconscious), islands as emergence of the ego from unconscious. In alchemical symbolism, island related to coagulatio, the operation which turns something into earth, the realm of ego. In addition, related parts of Hindu creation myths, Korean giant woman creator Sulmoonde-halmang, and legends of "Relocation of Island/Mountain" will be presented to integrate with case materials. Case A : Starts with a dream of killing a huge dragon and dead body became an island. The dragon in the water was seen as Spirit of Mercurius, the autonomous spirit, connecting of the ego with the Self. The act of killing related to Primeval being which needs to be killed to be transformed. Myths of Eskimo, The Eagle's Gift, the giant woman creator in Korea, and Marduk, the Babylonian hero will be integrated. Case B : Prior to introduce six island images in sand trays, a dream of a giant serpent (python) wound around her body will be presented to portray her situation. By relating Jung's "The Sermons to the Dead," her effort to make the solid island regarded as an act of bringing order out of original oneness (pleroma). Then stresses the importance to coagulate archetypal image Case C : A vignette of active imagination seminar where island image emerged will be described. Her endeavor of focusing on inner image related to the Hindu Creator, Cherokee creation myth, as well as Sulmoonde-halmang. As a motif of growing island, Samoan creation myth, and Legend of Mountain, Mai were incorporated. Colors in her art work regarded as expression of inner need, and importance of expressing inner feeling images as a mean to coagulate volatile emotional and spiritual content. Case D : A dream and art work of terminally ill woman; embracing the tip of the island with gushing up water will be presented. Her island and replenishing water image regard as "an immortal body," corresponds to the Philosophers' Stone for she accepted her death peacefully after the dream. Also related to "The Mercurial Fountain" in Rosarium Philosophorum, and aqua permanence, an allegory of God.