• The Journal of the Acoustical Society of Korea
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• v.38 no.4
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• pp.450-458
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• 2019

Passive cavitation imaging method is used to observe the ultrasonic waves generated when a group of bubbles collapses. A problem with passive cavitation imaging is a low resolution and large side lobe levels. Since ultrasound signals generated by passive cavitation take the form of a pulse, the amplitude distribution of signals received across the receive channels varies depending on the direction of incidence. Both the centroid and flatness were calculated to determine weights at imaging points in order to discriminate between the main and side lobe signals from the signal amplitude distribution of the received channel data and to reduce the side lobe levels. The centroid quantifies how the channel data are distributed across the receive channel, and the flatness measures the variance of the channel data. We applied the centroid weight and the flatness to the passive cavitation image constructed using the delay-and-sum focusing and minimum variance beamforming methods to improve the image quality. Using computer simulation and experiment, we show that the application of weighting in delay-and-sum and minimum variance beamforming reduces side lobe levels.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.2
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• pp.103-108
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• 2019

Non-equilibrium molecular dynamics simulation on the thermal boundary resistance(TBR) of an aluminum(Al)/silicon(Si) interface was performed in the present study. The constant heat flux across the Si/Al interface was simulated by adding the kinetic energy in hot Si region and removing the same amount of the energy from the cold Al region. The TBR estimated from the sharp temperature drop at the interface was independent of heat flux and equal to $5.13{\pm}0.17K{\cdot}m^2/GW$ at 300K. The simulation result was experimentally confirmed by the time-domain thermoreflectance technique. A 90nm thick Al film was deposited on a Si(100) wafer using an e-beam evaporator and the TBR on the film/substrate interface was measured using the time-domain thermoreflectance technique based on a femtosecond laser system. A numerical solution of the transient heat conduction equation was obtained using the finite difference method to estimate the TBR value. Experimental results were compared to the prediction and discussions on the nanoscale thermal transport phenomena were made.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.1-10
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• 2021

The interest in underwater acoustic sensor networks (UWASNs), along with the rapid development of underwater industries, has increased. To operate UWASNs efficiently, it is important to adopt well-designed medium access control (MAC) protocols that prevent collisions and allow the sharing of resources between nodes efficiently. On the other hand, underwater channels suffer from a narrow bandwidth, long propagation delay, and low data rate, so existing terrestrial node pairing schemes for non orthogonal multiple access (NOMA) cannot be applied directly to underwater environments. Therefore, a multi-dimensional node pairing scheme is proposed to consider the unique underwater channel in UWASNs. Conventional NOMA schemes have considered the channel quality only in node pairing. Unlike previous schemes, the proposed scheme considers the channel gain and many other features, such as node fairness, traffic load, and the age of data packets to find the best node-pair. In addition, the sender employs a list of candidates for node-pairs rather than path loss to reduce the computational complexity. The simulation results showed that the proposed scheme outperforms the conventional scheme by considering the fairness factor with 23.8% increases in throughput, 28% decreases in latency, and 5.7% improvements in fairness at best.

• Applied Chemistry for Engineering
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• v.22 no.2
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• pp.138-143
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• 2011

To investigate the electromagnetic interference shielding efficiency (EMI SE) property based on heat treatment effects of carbon fibers in various temperatures, the polyacrilonitrle-based carbon fibers were prepared by electrospinning method and treated at 1073, 1323, 1873 and 2573 K. The surface morphology of carbon fibers was investigated by using FE-SEM and the carbon crystallization was studied by Raman spectroscopy based on effects of reaction temperatures. The electrical conductivity was obtained by measuring the surface resistance with four probe method on carbon crystallization. The permittivity, permeability and EMI SE were investigated by using S-parameter in the range of 800~4500 MHz. In case of carbon fibers treated at 2573 K, the improved carbon crystallization was confirmed by Raman spectrum and the enhanced electrical conductivity showing 54.7 S/cm was also observed. The permittivity was dramatically improved by factor of 4 based on effect of high reaction temperature. Eventually, the highly improved EMI SE value was obtained showing around 41.7 dB.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.2
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• pp.39-47
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• 2008

Among previous Side Channel Analysis (SCA) methods, Differential Power Analysis (DPA) based on the statistical characteristics of collected signals has been known as an efficient attack for uncovering secret key of cryptosystems. However, the attack performance of this method is affected very much by the temporal misalignment and noise of collected side channel signals. In this paper, we propose a new method to surmount the noise problem in DPA. The performance of the proposed method is then evaluated while analyzing the power consumption signals of Micro-controller chips during a DES operation. Its performance is then compared to that of the original DPA in the time and frequency domains. When we compare the experimental results with respect to the needed number of traces to uncover the secret key, our proposed method shows the performance enhancement 33% in the time domain and 50% in the frequency domain.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.12 no.6
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• pp.113-124
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• 2002

Proposals for a password-based authenticated key exchange protocol that have been published so far almost concentrated on the provable security. But in a real environment such as mobile one, efficiency is a critical issue as security. In this paper we discuss the efficiency of PAK which is secure in the random oracle model ［l］. Among 4 hash functions in PAK the instantiation for $H_1$, which outputs a verifier of the password, has most important effect on the computational efficiency. We analyze two different methods for $H_1$ suggested in ［1］ and we show that $H_{lq}$ has merits in transforming to EC or XTR variants as well as in the efficiency. As an efficient variant. we propose PAK2-EC and PAK2-XTR which do not require any additional step converting a hash output into a point of elliptic curve or XTR subgroup when compared to the previous work on the PAK［2］. Finally we compare PAK2 with the password-based authenticated key exchange protocols such as SPEKE, SRP, and AMP.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.13 no.1
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• pp.19-26
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• 2003

Recently, the number of internet service companies is increasing and so is the number of malicious attackers. Damage such as distrust about credit and instability of the service by these attacks may influence us fatally as it makes companies image failing down. One of the frequent and fatal attacks is DoS(Denial-of-Service). Because the attacker performs IP spoofing for hiding his location in DoS attack it is hard to get an exact location of the attacker from source IP address only. and even if the system recovers from the attack successfully, if attack origin has not been identified, we have to consider the possibility that there may be another attack again in near future by the same attacker. This study suggests to find the attack origin through MAC address marking of the attack origin. It is based on an IP trace algorithm, called Marking Algorithm. It modifies the Martins Algorithm so that we can convey the MAC address of the intervening routers, and as a result it can trace the exact IP address of the original attacker. To improve the detection time, our algorithm also contains a technique to improve the packet arrival rate. By adjusting marking probability according to the distance from the packet origin we were able to decrease the number of needed packets to traceback the IP address.

• Journal of radiological science and technology
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• v.28 no.4
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• pp.317-325
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• 2005

The recent medical treatment guidelines and the development of information technology make hospitals reduce the expense in surrounding environment and it requires improving the quality of medical treatment of the hospital. That is, with the new guidelines and technology, hospital business escapes simple fee calculation and insurance claim center. Moreover, MIS(Medical Information System), PACS(Picture Archiving and Communications System), OCS(Order Communicating System), EMR(Electronic Medical Record), DSS(Decision Support System) are also developing. Medical Information System is evolved toward integration of medical IT and situation si changing with increasing high speed in the ICT convergence. These changes and development of ubiquitous environment require fundamental change of medical information system. Mobile medical information system refers to construct wireless system of hospital which has constructed in existing environment. Through RFID development in existing system, anyone can log on easily to Internet whenever and wherever. RFID is one of the technologies for Automatic Identification and Data Capture(AIDC). It is the core technology to implement Automatic processing system. This paper provides a comprehensive basic review of RFID model in Korea and suggests the evolution direction for further advanced RFID application services. In addition, designed and implemented DB server's agent program and Client program of Mobile application that recognized RFID tag and patient data in the ubiquitous environments. This system implemented medical information system that performed patient data based EMR, HIS, PACS DB environments, and so reduced delay time of requisition, medical treatment, lab.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.12
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• pp.291-306
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• 2020

Nowadays, Data-Network-AI (DNA)-based intelligent services and applications have become a reality to provide a new dimension of services that improve the quality of life and productivity of businesses. Artificial intelligence (AI) can enhance the value of IoT data (data collected by IoT devices). The internet of things (IoT) promotes the learning and intelligence capability of AI. To extract insights from massive volume IoT data in real-time using deep learning, processing capability needs to happen in the IoT end devices where data is generated. However, deep learning requires a significant number of computational resources that may not be available at the IoT end devices. Such problems have been addressed by transporting bulks of data from the IoT end devices to the cloud datacenters for processing. But transferring IoT big data to the cloud incurs prohibitively high transmission delay and privacy issues which are a major concern. Edge computing, where distributed computing nodes are placed close to the IoT end devices, is a viable solution to meet the high computation and low-latency requirements and to preserve the privacy of users. This paper provides a comprehensive review of the current state of leveraging deep learning within edge computing to unleash the potential of IoT big data generated from IoT end devices. We believe that the revision will have a contribution to the development of DNA-based intelligent services and applications. It describes the different distributed training and inference architectures of deep learning models across multiple nodes of the edge computing platform. It also provides the different privacy-preserving approaches of deep learning on the edge computing environment and the various application domains where deep learning on the network edge can be useful. Finally, it discusses open issues and challenges leveraging deep learning within edge computing.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.6
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• pp.235-242
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• 2021

In this work, we develop a Korean dependency parser based on a stack-pointer network that consists of a pointer network and an internal stack. The parser has an encoder and decoder and builds a dependency tree for an input sentence in a depth-first manner. The encoder of the parser encodes an input sentence, and the decoder selects a child for the word at the top of the stack at each step. Since the parser has the internal stack where a search path is stored, the parser can utilize information of previously derived subtrees when selecting a child node. Previous studies used only a grandparent and the most recently visited sibling without considering a subtree structure. In this paper, we introduce graph attention networks that can represent a previously derived subtree. Then we modify our parser based on the stack-pointer network to utilize subtree information produced by the graph attention networks. After training the dependency parser using Sejong and Everyone's corpus, we evaluate the parser's performance. Experimental results show that the proposed parser achieves better performance than the previous approaches at sentence-level accuracies when adopting 2-depth graph attention networks.