• Journal of Korea Society of Industrial Information Systems
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• v.14 no.5
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• pp.19-32
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• 2009

In this paper, we design thin-client framework capable of application sharing & data access on the Internet, and apply related skills, such as X windows system, pseudo server, CODA file system, MPI(Message Passing Interface). We suggest a framework for the thin client to access data produced by working on a server optimally as well as to run server side application, even in the case of network down. Additionally, it needed to reflect all local computing changes to remote server when network is restored. To design thin client framework with these characteristics, in this paper, we apply distributed pseudo server and CODA file system to our framework, also utilize MPI for the purpose of more efficient computing & management. It allows for implementation of network independent computing environment of thin client, also provide scalable application service to numerous user through the elimination of bottleneck on caused by server overload. In this paper, we discuss the implementing method of thin client framework in detail.

• Korean Journal of Construction Engineering and Management
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• v.24 no.3
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• pp.42-51
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• 2023

Freeze and burst water meter in winter causes many social costs, such as meter replacement cost, inability of water use, and secondary damage by freezing water. The government is making efforts to modernize local waterworks, and in particular, is promoting SWM(Smart Water Management) project nationwide. In this study suggests a new freeze risk notification information service based on the temperature by IoT sensor inside the water meter box rather than outside temperature. In addition, in order to overcome the quantitative and regional limitation of IoT temperature sensors installed nationwide, and AI based temperature prediction model was developed that predicts the temperature inside water meter boxes based on data acquired from IoT temperature sensors and other information. Through the prediction model optimization process, a nationwide water meter freezing risk information service was convinced.

• The Journal of the Acoustical Society of Korea
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• v.42 no.4
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• pp.357-363
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• 2023

In underwater signal processing, separating individual signals from mixed signals has long been a challenge due to low signal quality. The common method using Short-time Fourier transform for spectrogram analysis has faced criticism for its complex parameter optimization and loss of phase data. We propose a Triple-path Recurrent Neural Network, based on the Dual-path Recurrent Neural Network's success in long time series signal processing, to handle three-dimensional tensors from multi-channel sensor input signals. By dividing input signals into short chunks and creating a 3D tensor, the method accounts for relationships within and between chunks and channels, enabling local and global feature learning. The proposed technique demonstrates improved Root Mean Square Error and Scale Invariant Signal to Noise Ratio compared to the existing method.

• Journal of Service Research and Studies
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• v.11 no.3
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• pp.55-74
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• 2021

In the global era, the tourism industry is a major profitable business, and the state and local governments are making various efforts to provide quality tourism experiences. The purpose of this study in a variety of tourism contents is to study barrier-free subway services in line with the global era, and to expand from the existing rapid, safe, and ordered transportation to the provision of high-quality comfort and all-round service experiences. This study compared and analyzed the subway service systems of Korea, China and both countries through the service design method, and presented a barrier-free subway service system to improve the user's satisfaction with the subway service system by improving the user's service experience. As a result, research results showed that 20 attractive quality attributes in 17 fields, such as convenience facilities, language issues, security equipment, and riding environment, play an important role in improving the quality and experience of subway services. In addition, through the construction of a Service Spatial Scenario, an optimized subway service system can be visualized to help understand this so that it can be used as a reference for creating a strategic application.

• Journal of radiological science and technology
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• v.47 no.1
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• pp.39-48
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• 2024

In this study, we optimized the FNLM algorithm through a simulation study and applied it to a phantom scanned by low-dose CT to evaluate whether the FNLM algorithm can be used to obtain improved image quality images. We optimized the FNLM algorithm with MASH phantom and FASH phantom, which the algorithm was applied with MATLAB, increasing the smoothing factor from 0.01 to 0.05 with increments of 0.001 and measuring COV, RMSE, and PSNR values of the phantoms. For both phantom, COV and RMSE decreased, and PSNR increased as the smoothing factor increased. Based on the above results, we optimized a smoothing factor value of 0.043 for the FNLM algorithm. Then we applied the optimized FNLM algorithm to low dose lung CT and lung CT under normal conditions. In both images, the COV decreased by 55.33 times and 5.08 times respectively, and we confirmed that the quality of the image of low dose CT applying the optimized FNLM algorithm was 5.08 times better than the image of lung CT under normal conditions. In conclusion, we found that the smoothing factor of 0.043 among the factors of the FNLM algorithm showed the best results and validated the performance by reducing the noise in the low-quality CT images due to low dose with the optimized FNLM algorithm.

• Smart Structures and Systems
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• v.33 no.2
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• pp.165-175
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• 2024

Rotating beams play a crucial role in representing complex mechanical components that are prevalent in vital sectors like energy and transportation industries. These components are susceptible to the initiation and propagation of cracks, posing a substantial risk to their structural integrity. This study presents a two-stage methodology for detecting the location and estimating the size of an open-edge transverse crack in a rotating Euler-Bernoulli beam with a uniform cross-section. Understanding the dynamic behavior of beams is vital for the effective design and evaluation of their operational performance. In this regard, modal parameters such as natural frequencies and eigenmodes are frequently employed to detect and identify damages in mechanical components. In this instance, the Frobenius method has been employed to determine the first two natural frequencies and corresponding eigenmodes associated with flapwise bending vibration. These calculations have been performed by solving the governing differential equation that describes the motion of the beam. Various parameters have been considered, such as rotational speed, beam slenderness, hub radius, and crack size and location. The effect of the crack has been replaced by a rotational spring whose stiffness represents the increase in local flexibility as a result of the damage presence. In the initial phase of the proposed methodology, a damage index utilizing the slope of the beam's eigenmode has been employed to estimate the location of the crack. After detecting the presence of damage, the size of the crack is determined using a Genetic Algorithm optimization technique. The ultimate goal of the proposed methodology is to enable the development of more suitable and reliable maintenance plans.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.7
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• pp.1726-1748
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• 2024

Trajectory planning is vital for autonomous systems like robotics and UAVs, as it determines optimal, safe paths considering physical limitations, environmental factors, and agent interactions. Recent advancements in trajectory planning and future location prediction stem from rapid progress in machine learning and optimization algorithms. In this paper, we proposed a novel framework for Spatial-temporal transformer-based feed-forward neural networks (STTFFNs). From the traffic flow local area point of view, skip-gram model is trained on trajectory data to generate embeddings that capture the high-level features of different trajectories. These embeddings can then be used as input to a transformer-based trajectory planning model, which can generate trajectories for new objects based on the embeddings of similar trajectories in the training data. In the next step, distant regions, we embedded feedforward network is responsible for generating the distant trajectories by taking as input a set of features that represent the object's current state and historical data. One advantage of using feedforward networks for distant trajectory planning is their ability to capture long-term dependencies in the data. In the final step of forecasting for future locations, the encoder and decoder are crucial parts of the proposed technique. Spatial destinations are encoded utilizing location-based social networks(LBSN) based on visiting semantic locations. The model has been specially trained to forecast future locations using precise longitude and latitude values. Following rigorous testing on two real-world datasets, Porto and Manhattan, it was discovered that the model outperformed a prediction accuracy of 8.7% previous state-of-the-art methods.

• Radiation Oncology Journal
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• v.20 no.4
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• pp.295-302
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• 2002

Purpose : The Purpose of this study was to establish general guidelines for the treatment of patients with early glottic carcinoma (T1-2N0M0), by assessing the role of primary radiotherapy and by analyzing the tumor-related and treatment-related factors that have an influence on the treatment results. Materials and Methods : This retrospective study was composed of 80 patients who suffered from early glottic carcinoma and were treated by primary radiotherapy at Pusan National University Hospital, between August 1987 and December 1996. The distribution of patients according to T-stage was 66 for stage T1 and 14 for stage T2. All of the patients were treated with conventional radical radiotherapy using a 6MV photon beams, a total tumor dose of $60\~75.6\;Gy$ (median 68.4 Gy), administered in 5 weekly fractions of $1.8\~2.0\;Gy$. The overall radiation treatment time was from 40 to 87 days, median 51 days. All patients were followed up for at least 3 years. Univariate and multivariate analysis was done to identify the prognostic factors affecting the treatment results. Results : The five-years survival rate was $89.2\%$ for all patients, $90.2\%$ for T1 and $82.5\%$ for T2. The local control rate was $81.3\%$ for all patients, $83.3\%$ for T1 and $71.4\%$ for T2. However, when salvage operations were taken into account, the ultimate local control rate was $91.3\%,\;T1\;94.5\%,\;T2\;79.4\%$, reprosenting an increase of $8\~12\%$ in the local control rate. The voice preservation rate was $89.2\%,\;T1\;94.7\%,\;T2\;81.3\%$. Fifteen patients suffered a relapse after radiotherapy, among whom 12 patients underwent salvage surgery. We included T-stage, tumor location, total radiation dose, fraction size, field size and overall radiation treatment time as potential prognostic factors. T-stage and overall treatment time were found to be statistically significant in the univariate analysis, but in the multivariate analysis, only the over-all treatment time was found to be significant. Conclusion : The high cure and voice preservation rates obtained when using a procedure, comprising a combination of radical radiotherapy and salvage surgery, may make this the treatment of choice for patients with early glottic carcinoma. However, the prognostic factors affecting the treatment results must be kept in mind, and more accurate treatment planning and further optimization of the radiation dose are necessary.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.594-600
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• 2018

Landscape law was enacted in 2007 after the development of the Korea Planning Support System (KOPSS) in 2006. In addition, KOPSS was utilized by many local governments to improve reliability and optimization in 2010. In 2014, landscape law was fully revised, and it is likely to have a considerable impact on municipal ordinances and deliberations, which may have a considerable effect on the results of landscape reviews. This paper presents an analysis and verification of changes in the subject of deliberation by the amendment of the law and system, the method of deliberation, the composition of the scenery committee, and the introduction of KOPSS. We also propose a direction for improving the landscape deliberation system. As a result, the change of the number of deliberation items repeatedly increased and decreased due to the change of the deliberation subject and deliberation management according to the total revision of the resultant laws and institutions. In sum, it affected the deliberation decisions.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.3
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• pp.77-90
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• 2018

Software Defect Prediction (SDP) is a field of study that identifies defective modules. With insufficient local data, a company can exploit Cross-Project Defect Prediction (CPDP), a way to build a classifier using dataset collected from other companies. Most machine learning algorithms for SDP have used more than one parameter that significantly affects prediction performance depending on different values. The objective of this study is to propose a parameter selection technique to enhance the performance of CPDP. Using a Harmony Search algorithm (HS), our approach tunes parameters of cost-sensitive boosting, a method to tackle class imbalance causing the difficulty of prediction. According to distributional characteristics, parameter ranges and constraint rules between parameters are defined and applied to HS. The proposed approach is compared with three CPDP methods and a Within-Project Defect Prediction (WPDP) method over fifteen target projects. The experimental results indicate that the proposed model outperforms the other CPDP methods in the context of class imbalance. Unlike the previous researches showing high probability of false alarm or low probability of detection, our approach provides acceptable high PD and low PF while providing high overall performance. It also provides similar performance compared with WPDP.