• Journal of Navigation and Port Research
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• v.48 no.3
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• pp.164-170
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• 2024

The light buoy, a floating structure at sea, is prone to drifting due to external factors such as oceanic weather. This makes it imperative to monitor for any loss or displacement of buoys. In order to address this issue, the Ministry of Oceans and Fisheries aims to issue alerts for buoy displacement by analyzing historical buoy position data to detect patterns. However, periodic lifting inspections, which are conducted every two years, disrupt the buoy's location pattern. As a result, new patterns need to be analyzed after each inspection for location monitoring. In this study, buoy position data from various periods were analyzed using convex hull and distance-based clustering algorithms. In addition, the optimal data collection period was identified in order to accurately recognize buoy location patterns. The findings suggest that a nine-week data collection period established stable location patterns, explaining approximately 89.8% of the variance in location data. These results can improve the management of light buoys based on location patterns and aid in the effective monitoring and early detection of buoy displacement.

• Journal of the Korean Society of Radiology
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• v.81 no.1
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• pp.21-40
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• 2020

Magnetic resonance imaging (MRI) is an essential modality for the diagnosis of musculoskeletal system defects because of its higher soft-tissue contrast and spatial resolution. With the recent development of MRI-related technology, faster imaging and various image plane reconstructions are possible, enabling better assessment of three-dimensional musculoskeletal anatomy and lesions. Furthermore, the image quality, diagnostic accuracy, and acquisition time depend on the MRI protocol used. Moreover, the protocol affects the efficiency of the MRI scanner. Therefore, it is important for a radiologist to optimize the MRI protocol. In this review, we will provide guidance on patient positioning; selection of the radiofrequency coil, pulse sequences, and imaging planes; and control of MRI parameters to help optimize the MRI protocol for the six major joints of the musculoskeletal system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.37-42
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• 2024

This paper suggests polynomial time algorithm for cutwidth minimization problem that classified as NP-complete because the polynomial time algorithm to find the optimal solution has been unknown yet. To find the minimum cutwidth CW_f(G)=max_𝜈∈_VCW_f(𝜈)for given graph G=(V,E),m=｜V｜, n=｜E｜, the proposed algorithm divides neighborhood N_G[𝜈_i] of the maximum degree vertex 𝜈_i in graph G into left and right and decides the vertical cut plane with minimum number of edges pass through the vertex 𝜈_i firstly. Then, we split the left and right N_G[𝜈_i] into horizontal sections with minimum pass through edges. Secondly, the inner-section vertices are connected into line graph and the inter-section lines are connected by one line layout. Finally, we perform the optimization process in order to obtain the minimum cutwidth using vertex moving method. Though the proposed algorithm requires O(n²) time complexity, that can be obtains the optimal solutions for all of various experimental data

• Korean Journal of Clinical Laboratory Science
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• v.55 no.4
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• pp.261-268
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• 2023

[¹⁸F]Fluorocholine is a radiopharmaceutical used non-invasively in positron emission tomography to diagnose parathyroid adenoma, prostate cancer, and hepatocellular carcinoma by evaluating the choline metabolism. In this study, a radiolabeling method for [¹⁸F]fluorocholine was optimized using a solid phase extraction (SPE) cartridge. [¹⁸F]Fluorocholine was labeled in two steps using an automated synthesizer. In the first step, dibromomethane was reacted with [¹⁸F]KF/K2.2.2/K₂CO₃ to obtain the intermediate [¹⁸F]fluorobromomethane. In the second step, [¹⁸F]fluorobromomethane was passed through a Sep-Pak^Ⓡ Silica SPE cartridge to remove the impurities and then reacted with N,N-dimethylaminoethanol (DMAE) in a Sep-Pak^Ⓡ C18 SPE cartridge to label [¹⁸F]fluorocholine. The reaction conditions of [¹⁸F]fluorocholine were optimized. The synthesis yield was confirmed according to the number of silica cartridges and DMAE concentration. No statistically significant difference in the synthesis yield of [¹⁸F]fluorocholine was observed when using four or three silica cartridges (P>0.05). The labeling yield was 11.5±0.5% (N=4) when DMAE was used as its original solution. On the other hand, when diluted to 10% with dimethyl sulfoxide, the radiochemical yield increased significantly to 30.1±5.2% (N=20). In conclusion, [¹⁸F]Fluorocholine for clinical use can be synthesized stably in high yield by applying an optimized synthesis method.

• Journal of the Korean Institute of Gas
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• v.28 no.1
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• pp.11-18
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• 2024

If flammable liquid leaks, vapor evaporated from the pool can cause poisoning or suffocation to workers, leading to secondary accidents such as fires and explosions. To prevent such damage, ventilation facilities shall be installed when designing indoor workplaces. At this time, the behavior varies depending on the characteristics of the leaked chemical, so it is necessary to select a suitable vent location according to the material. Therefore, 3D CFD simulations were introduced to derive optimal vent position and ventilation efficiency was quantitatively evaluated by vent position. At this time, assuming a situation in which flammable liquids leak at indoor workplaces to form pools, the concentration of vapor evaporated from pools was compared to derive the optimal vent position. As a result of research on toluene with high vapor density, ventilation efficiency was confirmed to be the highest at the upper supply-lower exhaust, and it is judged that introducing it can achieve about 3.7 times ventilation effect at the same maintenance cost. Through this study, it is expected that the workplace will be able to secure workers' safety by applying simulation results and installing ventilation ports.

• Archives of Plastic Surgery
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• v.51 no.2
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• pp.234-250
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• 2024

Background The impact of diabetes on complication rates following free flap (FF), pedicled flap (PF), and amputation (AMP) procedures on the lower extremity (LE) is examined. Methods Patients who underwent LE PF, FF, and AMP procedures were identified from the 2010 to 2020 American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP®) database using Current Procedural Terminology and International Classification of Diseases-9/10 codes, excluding cases for non-LE pathologies. The cohort was divided into diabetics and nondiabetics. Univariate and adjusted multivariable logistic regression analyses were performed. Results Among 38,998 patients undergoing LE procedures, 58% were diabetic. Among diabetics, 95% underwent AMP, 5% underwent PF, and <1% underwent FF. Across all procedure types, noninsulin-dependent (NIDDM) and insulin-dependent diabetes mellitus (IDDM) were associated with significantly greater all-cause complication rates compared with absence of diabetes, and IDDM was generally higher risk than NIDDM. Among diabetics, complication rates were not significantly different across procedure types (IDDM: p = 0.5969; NIDDM: p = 0.1902). On adjusted subgroup analysis by diabetic status, flap procedures were not associated with higher odds of complications compared with amputation for IDDM and NIDDM patients. Length of stay > 30 days was statistically associated with IDDM, particularly those undergoing FF (AMP: 5%, PF: 7%, FF: 14%, p = 0.0004). Conclusion Our study highlights the importance of preoperative diabetic optimization prior to LE procedures. For diabetic patients, there were few significant differences in complication rates across procedure type, suggesting that diabetic patients are not at higher risk of complications when attempting limb salvage instead of amputation.

• Parasites, Hosts and Diseases
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• v.62 no.1
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• pp.42-52
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• 2024

Antimalarial drugs are an urgently need and crucial tool in the campaign against malaria, which can threaten public health. In this study, we examined the cytotoxicity of the 9 antimalarial compounds chemically synthesized using SKM13-2HCl. Except for SKM13-2HCl, the 5 newly synthesized compounds had a 50% cytotoxic concentration (CC₅₀) >100 μM, indicating that they would be less cytotoxic than SKM13-2HCl. Among the 5 compounds, only SAM13-2HCl outperformed SKM13-2HCl for antimalarial activity, showing a 3- and 1.3-fold greater selective index (SI) (CC₅₀/IC₅₀) than SKM13-2HCl in vitro against both chloroquine-sensitive (3D7) and chloroquine -resistant (K1) Plasmodium falciparum strains, respectively. Thus, the presence of morpholine amide may help to effectively suppress human-infectious P. falciparum parasites. However, the antimalarial activity of SAM13-2HCl was inferior to that of the SKM13-2HCl template compound in the P. berghei NK65-infected mouse model, possibly because SAM13-2HCl had a lower polarity and less efficient pharmacokinetics than SKM13-2HCl. SAM13-2HCl was more toxic in the rodent model. Consequently, SAM13-2HCl containing morpholine was selected from screening a combination of pharmacologically significant structures as being the most effective in vitro against human-infectious P. falciparum but was less efficient in vivo in a P. berghei-infected animal model when compared with SKM13-2HCl. Therefore, SAM13-2HCl containing morpholine could be considered a promising compound to treat chloroquine-resistant P. falciparum infections, although further optimization is crucial to maintain antimalarial activity while reducing toxicity in animals.

• Advanced Industrial SCIence
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• v.3 no.1
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• pp.23-29
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• 2024

In this scholarly investigation, the focus is placed on the transformative potential of edge computing in enhancing Intelligent Transportation Systems (ITS) for the facilitation of autonomous driving. The intrinsic capability of edge computing to process voluminous datasets locally and in a real-time manner is identified as paramount in meeting the exigent requirements of autonomous vehicles, encompassing expedited decision-making processes and the bolstering of safety protocols. This inquiry delves into the synergy between edge computing and extant ITS infrastructures, elucidating the manner in which localized data processing can substantially diminish latency, thereby augmenting the responsiveness of autonomous vehicles. Further, the study scrutinizes the deployment of edge servers, an array of sensors, and Vehicle-to-Everything (V2X) communication technologies, positing these elements as constituents of a robust framework designed to support instantaneous traffic management, collision avoidance mechanisms, and the dynamic optimization of vehicular routes. Moreover, this research addresses the principal challenges encountered in the incorporation of edge computing within ITS, including issues related to security, the integration of data, and the scalability of systems. It proffers insights into viable solutions and delineates directions for future scholarly inquiry.

• Smart Media Journal
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• v.13 no.4
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• pp.33-48
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• 2024

With the advent of 5G, characterized by Enhanced Mobile Broadband (eMBB), Ultra-Reliable Low Latency Communications (URLLC), and Massive Machine Type Communications (mMTC), efficient network management and service provision are becoming increasingly critical. This paper proposes a novel approach to address key challenges of 5G networks, namely ultra-high speed, ultra-low latency, and ultra-reliability, while dynamically optimizing network slicing and resource allocation using machine learning (ML) and deep learning (DL) techniques. The proposed methodology utilizes prediction models for network traffic and resource allocation, and employs Federated Learning (FL) techniques to simultaneously optimize network bandwidth, latency, and enhance privacy and security. Specifically, this paper extensively covers the implementation methods of various algorithms and models such as Random Forest and LSTM, thereby presenting methodologies for the automation and intelligence of 5G network operations. Finally, the performance enhancement effects achievable by applying ML and DL to 5G networks are validated through performance evaluation and analysis, and solutions for network slicing and resource management optimization are proposed for various industrial applications.

• Geophysics and Geophysical Exploration
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• v.27 no.2
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• pp.91-107
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• 2024

Single-channel seismic exploration has proven effective in delineating subsurface geological structures using small-scale survey systems. The seismic data acquired through zero- or near-offset methods directly capture subsurface features along the vertical axis, facilitating the construction of corresponding seismic sections. However, substantial noise in single-channel seismic data hampers precise interpretation because of the low signal-to-noise ratio. This study introduces a novel approach that integrate noise reduction and signal enhancement via matrix rank optimization to address this issue. Unlike conventional rank-reduction methods, which retain selected singular values to mitigate random noise, our method optimizes the entire singular value spectrum, thus effectively tackling both random and erratic noises commonly found in environments with low signal-to-noise ratio. Additionally, to enhance the horizontal continuity of seismic events and mitigate signal loss during noise reduction, we introduced an adaptive weighting factor computed from the eigenimage of the seismic section. To access the robustness of the proposed method, we conducted numerical experiments using single-channel Sparker seismic data from the Chukchi Plateau in the Arctic Ocean. The results demonstrated that the seismic sections had significantly improved signal-to-noise ratios and minimal signal loss. These advancements hold promise for enhancing single-channel and high-resolution seismic surveys and aiding in the identification of marine development and submarine geological hazards in domestic coastal areas.