• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.25-30
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• 2024

Various new technologies and aiding instruments are always being introduced for the betterment of the challenged. This project focuses on aiding the mute in expressing their views and ideas in a much efficient and effective manner thereby creating their own place in this world. The proposed system focuses on using various gestures traced into texts which could in turn be transformed into speech. The gesture identification and mapping is performed by the Kinect device, which is found to cost effective and reliable. A suitable text to speech convertor is used to translate the texts generated from Kinect into a speech. The proposed system though cannot be applied to man-to-man conversation owing to the hardware complexities, but could find itself very much of use under addressing environments such as auditoriums, classrooms, etc

• Journal of information and communication convergence engineering
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• v.22 no.2
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• pp.139-144
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• 2024

In this study, four types of fall detection systems - designed with YOLOPose, principal component analysis (PCA), convolutional neural network (CNN), and long short-term memory (LSTM) architectures - were developed and compared in the detection of everyday falls. The experimental dataset encompassed seven types of activities: walking, lying, jumping, jumping in activities of daily living, falling backward, falling forward, and falling sideways. Keypoints extracted from YOLOPose were entered into the following architectures: RAW-LSTM, PCA-LSTM, RAW-PCA-LSTM, and PCA-CNN-LSTM. For the PCA architectures, the reduced input size stemming from a dimensionality reduction enhanced the operational efficiency in terms of computational time and memory at the cost of decreased accuracy. In contrast, the addition of a CNN resulted in higher complexity and lower accuracy. The RAW-LSTM architecture, which did not include either PCA or CNN, had the least number of parameters, which resulted in the best computational time and memory while also achieving the highest accuracy.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.11
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• pp.965-974
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• 2012

As the use of smart devices has become popular, the number of smart devices connected to network has increased and the amount of traffic from them has grown rapidly. The management of mobile traffic and IP address for smart devices in an enterprise network is crucial problem for efficient operation of network. The information about connection type of a terminal host to the network will be very useful for stable and efficient management of an enterprise network. Also, this information might be used to identify NAT device. In this paper, we propose a methodology to identify the connection type of a terminal host using RTT (Round-Trip-Time) value extracted from captured packets. We prove the feasibility of our proposed method in a target campus network.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.1
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• pp.25-36
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• 2021

This paper presents a topology based on packet tracer and a five-step scenario model to make it easier for students to understand the network on which VLANs are applied. Virtual LAN (VLAN), developed as an alternative solution to the Routers that distribute broadcast traffic, is a virtual local area network that logically configured regardless of the physical network. The VLAN prevents the network performance degradation resulting from the broadcast traffic by dividing the broadcast domain so that the bandwidth can be used more efficiently. In addition, it enhances the security because on communication between the devices belonging to different VLANs is impossible. The five-step scenarios in this paper presented an efficient implementation case for students to understand and validate the various functions of VLANs through ping/telnet/tracert test and simulation, after setting up each step of programming switches and routers in the virtual network.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.1
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• pp.41-49
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• 2023

A convolutional neural network (CNN) is a representative algorithm for implementing artificial neural networks. CNNs have improved on the issues of rapid increase in calculation amount and low object classification rates, which are associated with a conventional multi-layered fully-connected neural network (FNN). However, because of the rapid development of IT devices, the maximum resolution of images captured by current smartphone and tablet cameras has reached 108 million pixels (MP). Specifically, a traditional CNN algorithm requires a significant cost and time to learn and process simple, high-resolution images. Therefore, this study proposes an improved CNN algorithm for implementing an object classification learning model for simple, high-resolution images. The proposed method alters the adjacency matrix value of the pooling layer's max pooling operation for the CNN algorithm to reduce the high-resolution image learning model's creation time. This study implemented a learning model capable of processing 4, 8, and 12 MP high-resolution images for each altered matrix value. The performance evaluation result showed that the creation time of the learning model implemented with the proposed algorithm decreased by 36.26% for 12 MP images. Compared to the conventional model, the proposed learning model's object recognition accuracy and loss rate were less than 1%, which is within the acceptable error range. Practical verification is necessary through future studies by implementing a learning model with more varied image types and a larger amount of image data than those used in this study.

• Asia Marketing Journal
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• v.8 no.3
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• pp.75-99
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• 2006

Inje University, a nonprofit-oriented educational institution, was ranked second in the nation and first in all the local universities in the 2001 Comprehensive Evaluation of the Universities in 25 years since it was founded. In order to find out the reason for this high reputation, we had an interview with the chairman and an in-depth interview with other school authorities, interviewed the students and the residents in the community, and collected related data for the second time. We revealed that Inje University had been performing public marketing in the areas of its management philosophy, function, form, and performance. Our interview with the chairman confirmed that Inje University's management philosophy is the frontier spirits that 'contribute to the moor, attracting nobody's attention, in the name of public interest.' It was also revealed that this management philosophy made the function of the university differ from that of the others. Inje University had been focusing on forming a public network for its community, the nation, and the world, not just for its students. Furthermore, we also found out that the university had its unique separate organizations to take care of this business. An excellent on-campus network for the student and the school, a network between off-campus industries, and an international Inje exchange network had been formed. We have concluded that Inje University is a strong nonprofit-oriented hidden champion. The healing art, easily ignored but essential to human beings, and its commitment to education with all its property invested have contributed to Inje University's social status, reputation, and achievements today.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.443-450
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• 2017

Nowadays, Power Line Communication (PLC) is gaining high attention from industry and electric supply companies for the services like demand response, demand side management and Advanced Metering Infrastructure (AMI). The reliable services to consumers using PLC can be provided by utilizing an efficient PLC channel for which sophisticated channel modeling is very important. This paper presents characterization of a Low Voltage (LV) access network for Narrowband Power Line Communications (NB-PLC) using transmission line (TL) theory and a Simulink model. The TL theory analysis not only includes the constant parameters but frequency selectivity is also introduced in these parameters such as resistance, conductance and impedances. However, the proposed Simulink channel model offers an analysis and characterization of capacitive coupler, network impedance and channel transfer function for NB-PLC. Analysis of analytical and simulated results shows a close agreement of the channel transfer function. In the absence of a standardized NBPLC channel model, this research work can prove significant in improving the efficiency and accuracy of NB-PLC communication transceivers for Smart Grid communications.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.419-422
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• 2003

To improve the recognition accuracy of a developed artificial odor discrimination system for three mixture fragrance recognition, Fuzzy Similarity based Self-Organized Network inspired by Immune Algorithm (F-SONIA) is proposed. Minimum, average, and maximum values of fragrance data acquisitions are used to form triangular fuzzy numbers. Then the fuzzy similarity treasure is used to define the relationship between fragrance inputs and connection strengths of hidden units. The fuzzy similarity is defined as the maximum value of the intersection region between triangular fuzzy set of input vectors and the connection strengths of hidden units. In experiments, performances of the proposed method is compared with the conventional Self-Organized Network inspired by Immune Algorithm (SONIA), and the Fuzzy Learning Vector Quantization (FLVQ). Experiments show that F-SONIA improves recognition accuracy of SONIA by 3-9％. Comparing to the previously developed artificial odor discrimination system that used FLVQ as pattern classifier, the recognition accuracy is increased by 14-25％.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.891-894
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• 2007

This paper purports to analyze the works of elementary school teachers belonging to the educational information division, who are key players in making information-based elementary school education, to analyze any problems with the works, and to find out the best solutions to the problems under the given circumstance. Its research topics are: characteristics and current status of school network, and major structural characteristics and problems with operation of school network at N Elementary School; the works of elementary school teachers belonging to the educational information division (hereinafter referred to as "the Teachers"); the Teachers' recognition of education information and any problems with their works; and finally, countermeasures to reduce the Teachers' work load.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.35 no.10
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• pp.1019-1024
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• 2011

The gaseous fuel injection(GFI) type of LPG fuel-supply system is more advantageous than liquefied fuel injection(LFI) from the viewpoint of durability and cost reduction. However, compared with LFI types of LPG fuel-supply systems, in the GFI systems it is difficult to achieve precision fuel metering because of the compressible characteristic of the gaseous fuel. In this study, a Helmholtz resonator is proposed as an appropriate system for precision fuel metering in GFI systems, and the effects of the Helmholtz resonator on the fuel metering are simulated by the commercial flow-network-analysis package Flowmaster.