• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.165-166
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• 2019

Big data analysis is the ability to collect, store, manage and analyze data from existing database management tools. Big data refers to large scale data that is generated in a digital environment, is large in size, has a short generation cycle, and includes not only numeric data but also text and image data. Big data is data that is difficult to manage and analyze in the conventional way. It has huge size, various types, fast generation and velocity. Therefore, companies in most industries are making efforts to create value through the application of Big data. In this study, we analyzed the meaning of keyword using Social Matrix, a big data analysis tool of Daum communications. Also, the theoretical implications are presented based on the analysis results.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.195-200
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• 2021

With the development of transportation and mobiles demand for tourism travel is increasing and related industries are also developing significantly. The combination of augmented reality and tourism contents one of the areas of digital media technology, is also actively being studied, and artificial intelligence is already combined with the tourism industry in various directions, enriching tourists' travel experiences. In this paper, we propose a system that scans miniature models produced by reducing tourist areas, finds the relevant tourist sites based on models learned using deep learning in advance, and provides relevant information and 3D models as AR services. Because model learning and object detection are carried out using YOLOv3 neural networks, one of various deep learning neural networks, object detection can be performed at a fast rate to provide real-time service.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2631-2649
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• 2021

Device-to-Device (D2D) communication is one of the enabling technologies for 5G networks that support proximity-based service (ProSe) for wireless network communications. This paper proposes a power control algorithm based on the Nash equilibrium and game theory to eliminate the interference between the cellular user device and D2D links. This leadsto reliable connectivity with minimal power consumption in wireless communication. The power control in D2D is modeled as a non-cooperative game. Each device is allowed to independently select and transmit its power to maximize (or minimize) user utility. The aim is to guide user devices to converge with the Nash equilibrium by establishing connectivity with network resources. The proposed algorithm with pricing factors is used for power consumption and reduces overall interference of D2Ds communication. The proposed algorithm is evaluated in terms of the energy efficiency of the average power consumption, the number of D2D communication, and the number of iterations. Besides, the algorithm has a relatively fast convergence with the Nash Equilibrium rate. It guarantees that the user devices can achieve their required Quality of Service (QoS) by adjusting the residual cost coefficient and residual energy factor. Simulation results show that the power control shows a significant reduction in power consumption that has been achieved by approximately 20% compared with algorithms in [11].

• Journal of the Korea Institute of Information Security & Cryptology
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• v.17 no.1
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• pp.33-39
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• 2007

Finite field multipliers are the basic building blocks in many applications such as error-control coding, cryptography and digital signal processing. Hence, the design of efficient dedicated finite field multiplier architectures can lead to dramatic improvement on the overall system performance. In this paper, a new bit serial structure for a multiplier with low latency in Galois field is presented. To speed up multiplication processing, we divide the product polynomial into several parts and then process them in parallel. The proposed multiplier operates standard basis of $GF(2^m)$ and is faster than bit serial ones but with lower area complexity than bit parallel ones. The most significant feature of the proposed architecture is that a trade-off between hardware complexity and delay time can be achieved.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.3
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• pp.427-432
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• 2021

In this paper, we conduct performance analysis in automatic modulation classification of unknown communication signal to identify its modulation types based on deep neural network. The modulation classification performance was verified using time domain digital sample data of the modulated signal, frequency domain data to which FFT was applied, and time and frequency domain mixed data as neural network input data. For 11 types of analog and digitally modulated signals, the modulation classification performance was verified in various SNR environments ranging from -20 to 18 dB and reason for false classification was analyzed. In addition, by checking the learning speed according to the type of input data for neural network, proposed method is effective for constructing an practical automatic modulation recognition system that require a lot of time to learn.

• The Journal of the Convergence on Culture Technology
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• v.8 no.4
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• pp.367-373
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• 2022

VANET (Vehicular Ad hoc NETwork) is one of the special cases of the ad hoc networks in which car nodes communicate with each other and/or with RSUs (Road Side Unit) in order for the drivers to receive nearby road traffic information as well as for the passengers to retrieve nearby gas price or hotel information. In case of constructing VANET over CCN, users do not need to specify a destination server address rather to input a key word such as nearby congestion in order to gather surrounding traffic congestion information. Furthermore, each car node caches its retrieved data for forwarding other nodes when requested. In addition, the data transmission is inherently multicast, which implies fast data propagation to the participating car nodes. This paper measures and evaluates the data transmission performance of the VCCN (VANET over CCN) in which nodes are equipped with diverse wireless communication channels. The simulation result indicates that 802.11a shows the best performance of the data transmission against other wireless channels. Moreover, it indicates that VCCN improves overall data transmission and provides benefit to the nodes that request the same traffic information by exploiting inherent multicast communication.

• Journal of Radiation Protection and Research
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• v.47 no.3
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• pp.111-133
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• 2022

The exciting advancement related to the "modeling of digital human" in terms of a computational phantom for radiation dose calculations has to do with the latest hype related to deep learning. The advent of deep learning or artificial intelligence (AI) technology involving convolutional neural networks has brought an unprecedented level of innovation to the field of organ segmentation. In addition, graphics processing units (GPUs) are utilized as boosters for both real-time Monte Carlo simulations and AI-based image segmentation applications. These advancements provide the feasibility of creating three-dimensional (3D) geometric details of the human anatomy from tomographic imaging and performing Monte Carlo radiation transport simulations using increasingly fast and inexpensive computers. This review first introduces the history of three types of computational human phantoms: stylized medical internal radiation dosimetry (MIRD) phantoms, voxelized tomographic phantoms, and boundary representation (BREP) deformable phantoms. Then, the development of a person-specific phantom is demonstrated by introducing AI-based organ autosegmentation technology. Next, a new development in GPU-based Monte Carlo radiation dose calculations is introduced. Examples of applying computational phantoms and a new Monte Carlo code named ARCHER (Accelerated Radiation-transport Computations in Heterogeneous EnviRonments) to problems in radiation protection, imaging, and radiotherapy are presented from research projects performed by students at the Rensselaer Polytechnic Institute (RPI) and University of Science and Technology of China (USTC). Finally, this review discusses challenges and future research opportunities. We found that, owing to the latest computer hardware and AI technology, computational human body models are moving closer to real human anatomy structures for accurate radiation dose calculations.

• Journal of Korea Trade
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• v.23 no.8
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• pp.89-109
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• 2019

Purpose - We perform an empirical analysis of the effects of global consumer culture positioning (GCCP) in TV advertisements on consumer's brand evaluations (perceived quality, perceived price, and brand prestige) and attitude toward brand. Also, we analyze the moderating roles of consumer characteristics (ethnocentrism and level of product knowledge) in those effects. Design/methodology - This research is based on a survey of 210 randomly-selected university students in Seoul, Korea. The participants in the survey were shown a total of 8 TV advertisements of consumer goods of nondurable goods (fast food and carbonated drinks), and durable goods (sports shoes and digital camera), which included two advertisements for each product where one uses GCCP strategy while another uses LCCP strategy. We estimate the structural model using the AMOS 18.0 computer program. Findings - We find that GCCP has more positive effects on consumers' brand evaluations and attitude toward brand than LCCP in TV advertising. We also find that GCCP has stronger effects on brand evaluation and attitude toward brand in consumers with weak ethnocentrism and in those with a low level of product knowledge. Practical implications - Using GCCP in an advertisement is an effective way of improving consumer's evaluation of the brand and attitude toward the brand mainly when cosmopolitan consumers and consumers with low knowledge levels are segmented as targets. Originality/value - The study contributes to identify how and for what consumer groups' global brand positioning strategies in TV advertisements affect consumers' brand evaluations and their attitudes toward brands.

• Physical Therapy Korea
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• v.29 no.1
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• pp.48-53
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• 2022

Background: The gastrocnemius tightness can easily occur. Gastrocnemius tightness results in gait disturbance. Thus, various interventions have been used to release a tight gastrocnemius muscle and improve gait performance. Moreover, focal muscle vibration (FMV) has recently been extensively researched in terms of tight muscle release and muscle performance. However, no study has investigated the effects of FMV application on medial gastrocnemius architectural changes. Objects: In this study, we aimed to investigate the effects of FMV on medial gastrocnemius architecture in persons with limited ankle dorsiflexion. Methods: Thirty one persons with <10° of passive ankle dorsiflexion participated in this study. We excluded persons with acute ankle injury within six months prior to study onset, a history of ankle fracture, leg length discrepancy greater than 2 cm, no history of neurological dysfunction, or trauma affecting the lower limb. The specifications of the FMV motor were as follows: a fixed frequency (fast wave: 150 Hz) and low amplitude (0.3-0.5 mm peak to peak) of vibration; the motor was used to release the medial gastrocnemius for 15 minutes. Each participant completed three trials for 10 days; a 30-second rest period was provided between each trial. Medial gastrocnemius architectural parameters [muscle thickness (MT), fiber bundle length (FBL), and pennation angle (PA)] were measured via ultrasonography. Results: MT significantly decreased after FMV application (p < 0.05). FBL significantly increased from its baseline value after FMV application (p < 0.05). PA significantly decreased from its baseline value after FMV application (p < 0.05). Conclusion: FMV application may be advantageous in reducing medial gastrocnemius excitability following a decrease in the amount of contractile tissue. Furthermore, FMV application can be used as a stretching method to alter medial gastrocnemius architecture.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.54-57
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• 1998

As the physical layer on telecommunication network is replaced fiber optic lines, it is increased the need of systematic maintenance for fiber optic lines. Korea Telecom has developed FLOMS in order to establish maintenance processes for optical fiber lines. FLOMS has functions which manages optical facilities and tests optical fiber lines automatically. As a resuls, this system can check and/or report a fault. Operator, who is reponsible for management of optical fiber lines, can test the characteristics of optical fiber lines remotely using FLOMS. As interpoerable with Digital Transmission Management System, FLOMS provides efficient management for optical fiber lines. This system improves the work process to find fault location fast, detect the degradation of fiber quality, and make database of optical facilities efficiently.