• Journal of the Korea Society for Simulation
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• v.18 no.4
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• pp.175-184
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• 2009

The distance of sensor nodes is an important factor in having influence on capability of networks in underwater acoustic sensor networks. Our proposed scheme is to establish an efficient distance to design a route of communication in underwater environment and it proposes a Level scheme that the areas divided by transmit/receive distance in network are given different levels. Our proposed scheme is pursued research to maintain a established route and maximize an energy efficiency. The established route will have fluid modification by an internal and external factors and it will construct more robust underwater sensor networks over our proposed multiple path configuration scheme.

• Journal of Ocean Engineering and Technology
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• v.34 no.6
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• pp.442-453
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• 2020

Underwater color images suffer from low visibility and color cast effects caused by light attenuation by water and floating particles. This study applied single image enhancement techniques to enhance the quality of underwater images and compared their performance with real underwater images taken in Korean waters. Dark channel prior (DCP), gradient transform, image fusion, and generative adversarial networks (GAN), such as cycleGAN and underwater GAN (UGAN), were considered for single image enhancement. Their performance was evaluated in terms of underwater image quality measure, underwater color image quality evaluation, gray-world assumption, and blur metric. The DCP saturated the underwater images to a specific greenish or bluish color tone and reduced the brightness of the background signal. The gradient transform method with two transmission maps were sensitive to the light source and highlighted the region exposed to light. Although image fusion enabled reasonable color correction, the object details were lost due to the last fusion step. CycleGAN corrected overall color tone relatively well but generated artifacts in the background. UGAN showed good visual quality and obtained the highest scores against all figures of merit (FOMs) by compensating for the colors and visibility compared to the other single enhancement methods.

• The Journal of the Acoustical Society of Korea
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• v.32 no.1
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• pp.86-94
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• 2013

In this paper, we propose a network coding scheme that is one of the most promising techniques for overcoming transmission errors in underwater acoustic communications. It is assumed that the proposed scheme operates in a Code Division Multiple Access (CDMA) network where multiple sensor nodes share the underwater acoustic channel in both the frequency and the time domains by means of orthogonal codes. The network topology deploys multi-hop transmission with relaying between multiple source nodes and one destination node via multiple relay nodes. The proposed scheme is evaluated in terms of the successful packet delivery ratio of end-to-end transactions under varying packet loss rates. A computer simulation shows that the successful delivery ratio is maintained at over 95% even when the packet loss rate reaches 50%.

• Journal of Korea Multimedia Society
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• v.14 no.12
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• pp.1572-1582
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• 2011

The rapid growth of UnderWater Acoustic Sensor Networks (UW-ASNs) has led researchers to enhance underwater MAC protocols against limitations existing in underwater environment. We propose the customized robust real-time packet inspection mechanism with addressing the problem of the search for the data packet loss and network performance quality analysis in UW-ASNs, and describe our experiences using this approach. The goal of this work is to provide a framework to assess the network real-time performance quality. We propose a customized and adaptive mechanism to detect, monitor and analyze the data packets according to the MAC protocol standards in UW-ASNs. The packet analyzing method and software we propose is easy to implement, maintain, update and enhance. We take input stream as real data packets from sniffer node in capture mode and perform fully analysis. We were interested in developing software and hardware designed tool with the same capabilities which almost all terrestrial network packet sniffers have. Experimental results confirm that the best way to achieve maximum performance requires the most adaptive algorithm. In this paper, we present and offer the proposed packet analyzer, which can be effectively used for implementing underwater MAC protocols.

• Journal of the Korea Society for Simulation
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• v.15 no.4
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• pp.79-86
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• 2006

Data transmission in poor environment like underwater has considerably serious delay rate and ewer rate. Like this environment usually has heavy fluctuation of error rate and limited wireless communication state. Therefore, mechanism using in such environment has to be efficient and simple. This paper suggests a new block ack mechanism, called the Pervasive Block ACK (PBA), which transmits aggregated ACKs. This mechanism takes effect on reducing number of traffic, decreasing overhead and delay rate in poor environment networks like underwater. Additionally, we can expect energy consumption. We verify propriety and efficiency of PBA through describing numerical result based analytical formula in this paper.

• Journal of information and communication convergence engineering
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• v.11 no.3
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• pp.153-166
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• 2013

A hierarchical time division multiple access (HTDMA) medium access control (MAC) protocol is proposed for clustered mobile underwater acoustic networks. HTDMA consists of two TDMA scheduling protocols (i.e., TDMA1 and TDMA2) in order to accommodate mobile underwater nodes (UNs). TDMA1 is executed among surface stations (e.g., buoys) using terrestrial wireless communication in order to share mobility information obtained from UNs which move cluster to cluster. TDMA2 is executed among UNs, which send data to their surface station as a cluster head in one cluster. By sharing mobility information, a surface station can instantaneously determine the number of time slots in a TDMA2 frame up to as many as the number of UNs which is currently residing in its cluster. This can enhance delay and channel utilization performance by avoiding the occurrence of idle time slots. We analytically investigate the delay of HTDMA, and compare it with that of wellknown contention-free and contention-based MAC protocols, which are TDMA and Slotted-ALOHA, respectively. It is shown that HTDMA remarkably decreases delay, compared with TDMA and Slotted-ALOHA.

• 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.

• Journal of Ocean Engineering and Technology
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• v.36 no.1
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• pp.32-40
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• 2022

Underwater optical images face various limitations that degrade the image quality compared with optical images taken in our atmosphere. Attenuation according to the wavelength of light and reflection by very small floating objects cause low contrast, blurry clarity, and color degradation in underwater images. We constructed an image data of the Korean sea and enhanced it by learning the characteristics of underwater images using the deep learning techniques of CycleGAN (cycle-consistent adversarial network), UGAN (underwater GAN), FUnIE-GAN (fast underwater image enhancement GAN). In addition, the underwater optical image was enhanced using the image processing technique of Image Fusion. For a quantitative performance comparison, UIQM (underwater image quality measure), which evaluates the performance of the enhancement in terms of colorfulness, sharpness, and contrast, and UCIQE (underwater color image quality evaluation), which evaluates the performance in terms of chroma, luminance, and saturation were calculated. For 100 underwater images taken in Korean seas, the average UIQMs of CycleGAN, UGAN, and FUnIE-GAN were 3.91, 3.42, and 2.66, respectively, and the average UCIQEs were measured to be 29.9, 26.77, and 22.88, respectively. The average UIQM and UCIQE of Image Fusion were 3.63 and 23.59, respectively. CycleGAN and UGAN qualitatively and quantitatively improved the image quality in various underwater environments, and FUnIE-GAN had performance differences depending on the underwater environment. Image Fusion showed good performance in terms of color correction and sharpness enhancement. It is expected that this method can be used for monitoring underwater works and the autonomous operation of unmanned vehicles by improving the visibility of underwater situations more accurately.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.63-64
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• 2007

The Underwater Wireless Sensor Networks (UWSN) consists of sensor nodes equipped with limited sensing coverages, energy resources and communication capacity. Hence, the deployment and movement algorithm is a key issue that needs to be organized in order to improve the sensing efficiency of the networks. In this paper, we use a Queen problem and Knapsack problem to prevent the reiteration phenomenon of sensors, to guarantee improvement sensing coverage and efficiency in the 3D UWSN.

• Journal of Convergence for Information Technology
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• v.10 no.6
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• pp.41-48
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• 2020

The sensor nodes in underwater IoT networks have practical limitations in power supply. Thus, the reduction of power consumption is one of the most important issues in underwater environments. In this regard, AMC(Adaptive Modulation and Coding) techniques are used by using the relation between SNR and BER. However, according to our hands-on experience, we observed that the relation between SNR and BER is not that tight in underwater environments. Therefore, we propose a deep learning based MLP classification model to reflect multiple underwater channel parameters at the same time. It correctly predicts BER with a high accuracy of 85.2%. The proposed model can choose the best parameters to have the highest throughput. Simulation results show that the throughput can be enhanced by 4.4 times higher than the conventionally measured results.