• Electronics and Telecommunications Trends
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• v.34 no.6
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• pp.51-60
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• 2019

As a way to further expand and enable the 5G ecosystem, the $3^{rd}$ Generation Partnership Project (3GPP) is considering the development of a 5G new radio (NR)-based non-terrestrial network (NTN). These NTNs are expected to provide ubiquitous 5G services to user's equipment (especially, in Internet of Things/machine-type communications (IoT/MTC) public safety, and critical communications) by extending service coverage to areas not covered by 5G terrestrial networks. To this end, this NTN is developing scenarios to provide 5G services using spaceborne vehicles, such as geosynchronous and low-Earth orbit satellites, and airborne vehicles, such as unmanned aircraft systems, including high-altitude pseudo-satellites. In addition, various technologies are being studied to satisfy new requirements not considered in 5G NR, such as long propagation delay time, large cell coverage, large Doppler effect, and base station movement. In this paper, we present the scenarios, requirements, technical issues and solutions, and standardization planning for NR-based NTN in 3GPP.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.4
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• pp.720-740
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• 2011

Wi-Fi-enabled portable devices have recently been introduced into the consumer electronics market. These devices download or upload content, from or to a host machine, such as a personal computer, a laptop, a home gateway, or a media server. This paper investigates the fairness among multiple Wi-Fi-enabled portable devices in a home network when they are simultaneously communicated with the host machine. First, we present that, a simple IEEE 802.11-based home network suffers from unfairness, and the fairness is exaggerated by the wireless link errors. This unfairness is due to the asymmetric response of the TCP to data-packet loss and to acknowledgment-packet loss, and the wireless link errors that occur in the proximity of any node; the errors affect other wireless devices through the interaction at the interface queue of the home gateway. We propose a QoS-provisioning framework in order to achieve per-device fairness and service differentiation. For this purpose, we introduce the medium access price, which denotes an aggregate value of network-wide traffic load, per-device link usage, and per-device link error rate. We implemented the proposed framework in the ns-2 simulator, and carried out a simulation study to evaluate its performance with respect to fairness, service differentiation, loss and delay. The simulation results indicate that the proposed method enforces the per-device fairness, regardless of the number of devices present and regardless of the level of wireless link errors; furthermore it achieves high link utilization with only a small amount of frame losses.

• Journal of the Korea Society of Computer and Information
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• v.22 no.12
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• pp.79-85
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• 2017

In this paper, we propose a CNN-based swimmer detection algorithm. Every year, water safety accidents have been occurred frequently, and accordingly, intelligent video surveillance systems are being developed to prevent accidents. Intelligent video surveillance system is a real-time system that detects objects which users want to do. It classifies or detects objects in real-time using algorithms such as GMM (Gaussian Mixture Model), HOG (Histogram of Oriented Gradients), and SVM (Support Vector Machine). However, HOG has a problem that it cannot accurately detect the swimmer in a complex and dynamic environment such as a beach. In other words, there are many false positives that detect swimmers as waves and false negatives that detect waves as swimmers. To solve this problem, in this paper, we propose a swimmer detection algorithm using CNN (Convolutional Neural Network), specialized for small object sizes, in order to detect dynamic objects and swimmers more accurately and efficiently in complex environment. The proposed CNN sets the size of the input image and the size of the filter used in the convolution operation according to the size of objects. In addition, the aspect ratio of the input is adjusted according to the ratio of detected objects. As a result, experimental results show that the proposed CNN-based swimmer detection method performs better than conventional techniques.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.5B
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• pp.899-912
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• 2000

PVM provides users with a single image of high performance parallel computing machine by collecting machines distributed over a network. Low communication overhead is essential to effectively run applications on PVM based platforms. In the original PVM, three times of memory copies are required for a PVM task to send a message to a remote task, which results in performance degradation. We propose a zero-copy model using global shared memory that can be accessed by PVM tasks, PVM daemon, and network interface card(NIC). In the scheme, a task packs data into global shared memory, and notify daemon that the data is ready to be sent, then daemon routes the data to a remote task to which it is sent with no virtual data copy overhead. Experimental result reveals that the message round trip time between two machines is reduced significantly in the proposed zero-copy scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.5B
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• pp.469-479
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• 2009

The GEM frame is used a mean to deliver the variable length user data and consists of the header and the payload in the G-PON system. The HEC field of header protects contents of the header and is used to maintain GEM frame synchronization at the same time. When an LCDG (Loss of GEM Channel Delineation) occurs while receiving frames, the receiver have to discard corrupted frames until acquiring the synchronization again. Accordingly, high-speed synchronization method is required to minimize the frame loss. In this paper, we suggest not only a main state machine but a sub-state machine to reduce the frame loss when undetectable errors occurred in the GEM header. Also, we provide a more efficient and fast parallel structure to detect the starting point of the header. Finally, the proposed method is implemented with the FPGA and verified by the logic analyzer.

• Journal of KIISE
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• v.42 no.8
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• pp.979-989
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• 2015

Machine to Machine (M2M) technology has gained attention due to the fast diffusion of Internet of Things (IoT) technologies and smart devices. Most wireless network experts believe that Bluetooth Low Energy (BLE) Communications technology in an iBeacon network has amazing advantages in terms of providing communication services at a low cost in smartphone applications. Specifically, BLE does not require any pairing process during its communication phases, so it is possible to send a message to any node without incurring additional transmissions costs if they are within the BLE communication range. However, BLE does not require any security verification during communication, so it has weak security. Therefore, a security authorization process would be necessary to obtain customer confidence. To provide security functions for iBeacon, we think that the iBeacon Message Encryption process and a Decryption (Authorization) process should be designed and implemented. We therefore propose the BLE message Authorization Mechanism based on a One Time Password Algorithm (BLE-OTP). The effectiveness of our mechanism is evaluated by conducting a performance test on an attendance system based on BLE-OTP.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.184-188
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• 2009

To interactively share High Definition (HD)-quality visualization over emerging ultra-high-speed network infrastructure, several lossless and low-delay real-time media (i.e., uncompressed HD video and audio) transport systems are being designed and prototyped. However, most of them still rely on expensive hardware components. As an effort to reduce the building cost of system, in this paper, we propose the integration of both transmitter and receiver machines into a single bi-directional transport system. After detailed bottleneck analysis and subsequent refinements of embedded software components, the proposed integration can provide Real-time Transport Protocol (RTP)-based bi-directional transport of uncompressed HD video and audio from a single machine. We also explain how to interface the Gbps-bandwidth display output of uncompressed HD media system to the networked tiled display of 10240 $\times$ 3200 super-high-resolution. Finally, to verify the feasibility of proposed integration, several prototype systems are built and evaluated by operating them in several different experiment scenarios.

• Journal of the Korean Institute of Telematics and Electronics
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• v.23 no.1
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• pp.1-9
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• 1986

This is the third part of the four-part paper describing the development of a packet-switched computer communication network named the KORNET. In this paper we describe the design and implementation of the X.25 protocol connecting packet mode data terminal equipments(PDTE's) with data circuit terminating equipments(DCE's). In the KORNET, the X.25 protocol has been implemented on the line processing module-A(LPMA) of the network node processor(NNP). In the implementation of X.25, we have divided the software module according to the service function, and have determined the the rules that interact between the modules. Each layer protocol has been developed using the technique of the finite state machine. Before the actual coding of softwares, we hafve used formal software development tools based on the specification and description language (SDL) and program design languate (PDL) recommended by the CCITT. In addition, for the efficient operation of the X.25 protocol system we have analyzed the system performance and the service scheduling method of each module. The results will also be given.

• Journal of Welding and Joining
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• v.32 no.4
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• pp.39-45
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• 2014

Today, the development of digitized information media and info-communications are bringing many changes. Due to the development of IT thechnology, we can learn wherever, whenever, regardless of time and place. Machine drawing subject is a very important in mechanical engineering course, but it's studyed only basic theory in a short period, average 1~2weeks. So that, students think that the mechanical drawing is of minor importance. Such ideas make them difficult to impove sense of space in isometric drawing and drawing skill. Therefore, in this paper, augmented reality-based contents through the system, Mechanical Drawing of education to meet the effectiveness and satisfaction, student learning can be spontaneously it was construct self-system. And, Theoretical part of the Mechanical Drawing is proposed ensure more efficient and easier training. In this paper, we were test operation for user effectualness of proposed service at Korea Polytechnics Colleges a industrial facilities management in Daegu. Target user are 66 students, and The students were divided into experimental group and comparison group. Experimental results, experimental group was able to do systematically experience many Projection Drawing and Pictorial Drawing in short schooltime. And, The test operation results showed that have the possibility to meet education effectiveness and user satisfaction in this augmented reality-based contents system.

• Structural Engineering and Mechanics
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• v.63 no.4
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• pp.429-438
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• 2017

Structural design has an imperative role in deciding the failure possibility of a Reinforced Concrete (RC) structure. Recent research works achieved the goal of predicting the structural failure of the RC structure with the assistance of machine learning techniques. Previously, the Artificial Neural Network (ANN) has been trained supported by Particle Swarm Optimization (PSO) to classify RC structures with reasonable accuracy. Though, keeping in mind the sensitivity in predicting the structural failure, more accurate models are still absent in the context of Machine Learning. Since the efficiency of multi-objective optimization over single objective optimization techniques is well established. Thus, the motivation of the current work is to employ a Multi-objective Genetic Algorithm (MOGA) to train the Neural Network (NN) based model. In the present work, the NN has been trained with MOGA to minimize the Root Mean Squared Error (RMSE) and Maximum Error (ME) toward optimizing the weight vector of the NN. The model has been tested by using a dataset consisting of 150 RC structure buildings. The proposed NN-MOGA based model has been compared with Multi-layer perceptron-feed-forward network (MLP-FFN) and NN-PSO based models in terms of several performance metrics. Experimental results suggested that the NN-MOGA has outperformed other existing well known classifiers with a reasonable improvement over them. Meanwhile, the proposed NN-MOGA achieved the superior accuracy of 93.33% and F-measure of 94.44%, which is superior to the other classifiers in the present study.