• Journal of Digital Convergence
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• v.14 no.4
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• pp.425-435
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• 2016

This paper has the aim to track down the viewers' cognitive emotion of how they are interacting with the story of Shakespeare in Love. Human minds have cognitive and emotional flows while plots, characters, and action-ideas are intertwined in the story of the film. This paper especially focused on the analysis of characters' networks with four statistical data pictures in order to schematize the storytelling architecture on how and why Shakespeare has strongly motivated to write a great star-crossed love play, Romeo and Juliet in his very young age. This paper examines that Shakespeare's subject of desire is to accomplish both a true love and a sincere play which can make the nature of love true. The desire of subject is always slipped aside into scattering with "object a." In the film of Shakespeare in Love, the "object a" is a writing process and has a product of Romeo and Juliet as well.

• Journal of Digital Contents Society
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• v.18 no.8
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• pp.1621-1626
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• 2017

This study conducts data visualization of common climax patterns of Korean blockbuster films to analyze shots and evaluate scene (subplot unit) arrangement. For this purpose, a model of editing patterns is used to analyze how many climax patterns a film contains. Moreover, a system, which automatically collects shot images and classifies shot sizes of collected data, is designed to demonstrate that a single scene is composed based on a climax pattern. As a scene is a subplot and thus its arrangement cannot fully be analyzed only by climax patterns, dialogues of starring actors are also used to identify scenes, and the result is compared with data visualization results. It detects dialogues between particular actors and visualizes dialogue formation in a network form. Such network visualization enables the arrangement of main subplots to be analyzed, and the box office performance of a film can be explained by the density of subplots. The study of two types comparison analysis is expected to contribute to planning, plotting, and producing films.

• The Transactions of the Korea Information Processing Society
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• v.4 no.2
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• pp.465-482
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• 1997

In this paper, we have studied on cinstructing code-recognition shstem by neural network according to a image process taking the DOT classification code stamped on tire surface.It happened to a few problems that characters distorted in edge by diffused reflection and two adjacent characters take the same label,even very sen- sitive to illumination ofr recognition the stamped them on tire.Thus,this paper would propose the algorithm for tire code under being cinscious of these properties and prove the algorithm drrciency with a simulation.Also,we have suggerted the MCBP network composing of multi-linked recognizers of dffcient identify the DOT code being tire classification code.The MCBP network extracts the projection balue for classifying each character's rdgion after taking out the prjection of each chracter's region on X,Y axis,processes each chracters by taking 7$\times$8 normalization.We have improved error rate 3% through the MCBP network and post-process comparing the DOT code Database. This approach has a accomplished that learming time get's improvenent at 60% and recognition rate has become to 95% from 90% than BckPropagation with including post- processing it has attained greate rates of entire of tire recoggnition at 98%.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1321-1330
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• 2023

This study attempts to address the problem of 3D pose estimation for multiple human objects through a single image generated during the character development process that can be used in augmented reality. In the existing top-down method, all objects in the image are first detected, and then each is reconstructed independently. The problem is that inconsistent results may occur due to overlap or depth order mismatch between the reconstructed objects. The goal of this study is to solve these problems and develop a single network that provides consistent 3D reconstruction of all humans in a scene. Integrating a human body model based on the SMPL parametric system into a top-down framework became an important choice. Through this, two types of collision loss based on distance field and loss that considers depth order were introduced. The first loss prevents overlap between reconstructed people, and the second loss adjusts the depth ordering of people to render occlusion inference and annotated instance segmentation consistently. This method allows depth information to be provided to the network without explicit 3D annotation of the image. Experimental results show that this study's methodology performs better than existing methods on standard 3D pose benchmarks, and the proposed losses enable more consistent reconstruction from natural images.

• Journal of Korea Multimedia Society
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• v.12 no.8
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• pp.1099-1108
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• 2009

The study of IP address allocation in MANET can be categories into Stateful and Stateless. The one, special node monitors other nodes' IP address and allocates IF address. And the other, node generates IP address by itself. Nodes in MANET have mobility and restricted resource, so Stateless is more suitable than Stateful. But, in Stateless, node requires DAD process because of unique IP address allocation. And Dos attack can be happened in DAD precess. In this paper, we propose a security method on preventing DoS attack against DAD in MANET using one-way hash function. Since, Computation of one-way hash function is suitable for nodes' restricted resource character in MANET. And we evaluate performance using NS2 and compare with other security method which is CGA using signature.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.7
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• pp.27-35
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• 1999

Researches on the recognition of handwritten script have been conducted under the assumption that the isolated recognition units are provided as inputs. However, in practical recognition system designs, providing the isolated recognition unit is an challenge due to various writing syles. This paper proposes an approach for segmenting words from lines of unconstrained handwritten text, without help of recognition. In contrast to the conventional approaches which are based on physical gaps between connected components, clues that reflect the author's writing style, in terms of spacing, are extracted and utilized for the segmentation using a simple neural network. The clues are from character segments and include normalized heights and intervals of the segments. Effectiveness of the proposed approach compared with the conventional connected component based approaches in terms of word segmentation performance was evaluated by experiments.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.1
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• pp.17-24
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• 2020

In this paper, we present a movie rating prediction architecture based on a convolutional neural network (CNN). Our prediction architecture extends TextCNN, a popular CNN-based architecture for sentence classification, in three aspects. First, character embeddings are utilized to cover many variants of words since reviews are short and not well-written linguistically. Second, the attention mechanism (i.e., squeeze-and-excitation) is adopted to focus on important features. Third, a scoring function is proposed to convert the output of an activation function to a review score in a certain range (1-10). We evaluated our prediction architecture on a movie review dataset and achieved a low MSE (e.g., 3.3841) compared with an existing method. It showed the superiority of our movie rating prediction architecture.

• The Journal of the Korea Contents Association
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• v.3 no.4
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• pp.48-54
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• 2003

Recently it frequently occur that remote host or network device breaks down because of various traffic flooding attacks. This kind of attack is classified an one of the most serious attacks of it can be used to a need of other hackings. This research is gathering system's informations for detecting a traffic flooding attack using the SNMP MIB. We analyze the traffic characteristic applying the critical value commonly used in analytical procedure of traffic flooding attacks. As a result or this analysis, traffic flooding attacks have a special character of its on. The proposed algorithm in this paper would be more available to a previous detecting method and a previous protecting method.

• Journal of Korea Game Society
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• v.19 no.2
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• pp.23-32
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• 2019

The popularization of VR content is slow. It's because they have not created a new visual experience, that is, 'utility' beyond 'interest'. The utility of VR content starts from functional reality. And to enhanced it, realistic interaction is required. Specifically, this study presents three methods of network play, character artificial intelligence, and Haptic implementation. In order to confirm the hypothesis, we conducted all phases of VR content production from baseball to contents production, play test, and technical verification. Through the test of the user and the evaluation institution about the final product, it was evaluated that it contributed to the realization of the content realism through the realistic visual effect, the play presentation, and the impact evaluation by the vibration.

• Journal of information and communication convergence engineering
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• v.20 no.3
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• pp.166-173
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• 2022

Recently, studies have been conducted on intelligent transportation systems (ITS) that provide safety and convenience to humans. Systems that compose the ITS adopt architectures that applied the cloud computing which consists of a high-performance general-purpose processor or graphics processing unit. However, an architecture that only used the cloud computing requires a high network bandwidth and consumes much power. Therefore, applying edge computing to ITS is essential for solving these problems. In this paper, we propose an edge artificial intelligence (AI) device based ITS. Edge AI which is applicable to various systems in ITS has been applied to license plate recognition. We implemented edge AI on a field-programmable gate array (FPGA). The accuracy of the edge AI for license plate recognition was 0.94. Finally, we synthesized the edge AI logic with Magnachip/Hynix 180nm CMOS technology and the power consumption measured using the Synopsys's design compiler tool was 482.583mW.