• Journal of the Korea Society of Computer and Information
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• v.14 no.2
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• pp.111-118
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• 2009

Against Anomaly of GPS, there are several projects of independent satellite navigation systems like Galileo of Europe and QZSS of Japan and modernization of terrestrial navigation system like Loran. In domestic, the need of independent navigation system was proposed and DGPS signal was nominated as the possible substitute. The DGPS signal uses medium frequency, which travels through the surface and cause the additional delay rather than the speed of light according to Conductivities and elevations of the irregular terrain. The similar approach is Locan-C. Loran-C has been widely used as the maritime location system. Loran-C uses the ASF estimation method and provides more precise positioning. However there was rarely research on this area in Korea Therefore, we introduce the legacy guaranteed model of additional delay(ASF) and present the results of implementation. With the comparison of the original Monteath results and BALOR results respectively, we guarantee that the implementation is absolutely perfect. For further works, we're going to apply the ASF estimation model to Korean DGPS system with the Korean terrain data.

• Journal of Astronomy and Space Sciences
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• v.39 no.1
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• pp.1-10
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• 2022

The universe is thought to be filled with not only Standard Model (SM) matters but also dark matters. Dark matter is thought to play a major role in its construction. However, the identity of dark matter is as yet unknown, with various search methods from astrophysical observartion to particle collider experiments. Because of the cross-section that is a thousand times smaller than SM particles, dark matter research requires a large amount of data processing. Therefore, optimization and parallelization in High Performance Computing is required. Dark matter in hypothetical hidden sector is though to be connected to dark photons which carries forces similar to photons in electromagnetism. In the recent analysis, it was studied using the decays of a dark photon at collider experiments. Based on this, we studies double dark photon decays at lepton colliders. The signal channels are e⁺e^- → A'A' and e⁺e^- → A'A'γ where dark photon A' decays dimuon. These signal channels are based on the theory that dark photons only decay into heavily charged leptons, which can explain the muon magnetic momentum anomaly. We scanned the cross-section according to the dark photon mass in experiments. MadGraph5 was used to generate events based on a simplified model. Additionally, to get the maximum expected number of events for the double dark photon channel, the detector efficiency for several center of mass (CM) energy were studied using Delphes and MadAnalysis5 for performance comparison. The results of this study will contribute to the search for double dark photon channels at lepton colliders.

• Smart Structures and Systems
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• v.31 no.5
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• pp.485-500
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• 2023

Machine learning-based structural health monitoring (ML-based SHM) methods are researched extensively in the recent decade due to the availability of advanced information and sensing technology. ML methods are well-known for their pattern recognition capability for complex problems. However, the main obstacle of ML-based SHM is that it often requires pre-collected historical data for model training. In most actual scenarios, damage presence can be detected using the unsupervised learning method through anomaly detection, but to further identify the damage types would require prior knowledge or historical events as references. This creates the cold-start problem, especially for new and unobserved structures. Modal-based methods identify damages based on the changes in the structural global properties but often require dense measurements for accurate results. Therefore, a two-stage hybrid modal-machine learning damage detection scheme is proposed. The first stage detects damage presence using Principal Component Analysis-Frequency Response Function (PCA-FRF) in an unsupervised manner, whereas the second stage further identifies the damage. To solve the cold-start problem, mode shape assessment using the first mode is initiated when no trained model is available yet in the second stage. The damage identified by the modal-based method would be stored for future training. This work highlights the performance of the scheme in alleviating the cold-start issue as it transitions through different phases, starting from zero damage sample available. Results showed that single and multiple damages can be identified at an acceptable accuracy level even when training samples are limited.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.95-102
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• 2023

The emergence of Internet of Things (IoT) into our daily lives has grown rapidly. It's been integrated to our homes, cars, and cities, increasing the intelligence of devices involved in communications. Enormous amount of data is exchanged over smart devices through the internet, which raises security concerns in regards of privacy evasion. This paper is focused on the forensics and intrusion detection on one of the most common protocols in IoT environments, especially smart home environments, which is the Message Queuing Telemetry Transport (MQTT) protocol. The paper covers general IoT infrastructure, MQTT protocol and attacks conducted on it, and multiple network forensics frameworks in smart homes. Furthermore, a machine learning model is developed and tested to detect several types of attacks in an IoT network. A forensics tool (MQTTracker) is proposed to contribute to the investigation of MQTT protocol in order to provide a safer technological future in the warmth of people's homes. The MQTT-IOT-IDS2020 dataset is used to train the machine learning model. In addition, different attack detection algorithms are compared to ensure the suitable algorithm is chosen to perform accurate classification of attacks within MQTT traffic.

• Economic and Environmental Geology
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• v.56 no.3
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• pp.259-275
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• 2023

Pan African granitoids of Kaiama is comprised of K-feldspar rich granites, porphyritic granites, and granitic gneiss that are intruded by quartz veins and aplitic veins and dykes which trend NE-SW. In order to establish the geochemical signatures, petrogenesis, and tectonic settings of the lithological units, petrological, petrographical, and geochemical studies was carried out. Petrographic analysis reveals that the granitoids are dominantly composed of quartz, plagioclase feldspar, biotite, and k-feldspar with occasional muscovites, sericite, and opaque minerals that constitute very low proportion. Major, trace, and rare earth elements geochemical data reveal that the rocks have moderate to high silica (SiO₂=63-79.7%) and alumina (Al₂O₃=11.85-16.15) contents that correlate with the abundance of quartz, feldspars, and biotite. The rocks are calc-alkaline, peraluminous (ASI=1.0-<1.2), and S-type granitoids sourced by melting of pre-existing metasedimentary or sedimentary rocks containing Al, Na, and K oxides. They plot dominantly in the WPG and VAG fields suggesting emplacement in a post-collisional tectonic setting. On a multi-element variation diagram, the granitoids show depletion in Ba, K, P, Rb, and Ti while enrichment was observed for Th, U, Nd, Pb and Sm. Their rare-earth elements pattern is characterized by moderate fractionation ((La/Yb)_N=0.52-38.24) and pronounced negative Eu-anomaly (Eu/Eu^*=0.02-1.22) that points to the preservation of plagioclase from the source magma. Generally, the geochemical features of the granitoids show that they were derived by the partial melting of crustal rocks with some input from greywacke and pelitic materials in a typical post-collisional tectonic setting.

• Journal of Advanced Technology Convergence
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• v.2 no.4
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• pp.43-48
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• 2023

Globally, there is a collaborative effort to achieve global carbon neutrality in response to climate change. In the case of South Korea, greenhouse gas emissions are rapidly increasing, presenting an urgent situation that requires resolution. In this context, this study developed a thermal energy collection device named a 'steam trap' and created an AI model capable of predicting future electricity usage by collecting energy usage data through steam traps. The average accuracy of electricity usage prediction with this AI model was 96.7%, demonstrating high precision. Consequently, the AI model enables the prediction and management of days with high electricity consumption and identifies which facilities contribute to elevated power usage. Future research aims to optimize energy consumption efficiency through efficient equipment operation using anomaly detection in steam traps and standardizing energy management systems, with the ultimate goal of reducing greenhouse gas emissions.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.2
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• pp.217-228
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• 2024

LiDAR(Light Detection And Ranging) sensors, which play a pivotal role among cameras, RADAR(RAdio Detection And Ranging), and ultrasonic sensors for the safe operation of autonomous vehicles, can recognize and detect objects in 360 degrees. However, since LiDAR sensors use lasers to measure distance, they are vulnerable to attackers and face various security threats. In this paper, we examine several security threats against LiDAR sensors: relay, spoofing, and replay attacks, analyze the possibility and impact of physical jamming attacks, and analyze the risk these attacks pose to the reliability of autonomous driving systems. Through experiments, we show that jamming attacks can cause errors in the ranging ability of LiDAR sensors. With vehicle-to-vehicle (V2V) communication, multi-sensor fusion under development and LiDAR anomaly data detection, this work aims to provide a basic direction for countermeasures against these threats enhancing the security of autonomous vehicles, and verify the practical applicability and effectiveness of the proposed countermeasures in future research.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.20 no.1
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• pp.1-6
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• 2024

Crud is a corrosion deposit that forms in equipments and piping of nuclear reactor's primary systems. When crud circulates through the reactor's primary system coolant and adheres to the surface of the nuclear fuel cladding tube, it can lead to the Axial Offset Anomaly (AOA) phenomenon. This occurrence is known to potentially reduce the output of a nuclear power plant or to necessitate an early shutdown. Consequently, worldwide nuclear power plants have employed ultrasonic cleaning methods since 2000 to mitigate crud deposition, ensuring stable operation and economic efficiency. This paper details the system configuration of ultrasonic nuclear fuel cleaning equipment, outlining the function of each component. The objective is to contribute to the local domestic production of ultrasonic nuclear fuel cleaning equipment. Additionally, the paper introduces a method for accurately measuring the weight of removed crud, a crucial factor in assessing cleaning effectiveness and providing input data for the BOA code used in core safety evaluations. Accurate measurement of highly radioactive filters containing crud is essential, and weighing them underwater is a common practice. However, the buoyancy effect during underwater weighing may lead to an overestimation of the collected crud's weight. To address this issue, the paper proposes a formula correcting for buoyancy errors, enhancing measurement accuracy. This improved weight measurement method, accounting for buoyancy effects in water, is expected to facilitate the quantitative assessment of filter weights generated during chemical decontamination and system operations in nuclear power plants.

• Korean Journal of Radiology
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• v.20 no.5
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• pp.823-829
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• 2019

Objective: To summarize the high-resolution computed tomography (HRCT) and magnetic resonance imaging (HRMRI) features of duplicated internal auditory canals (DIACs). Materials and Methods: Ear HRCT data of 64813 patients with sensorineural hearing loss (SNHL), obtained between August 2009 and November 2017, were reviewed. Among these patients, 12 (13 ears) were found to have DIACs, 9 of whom underwent HRMRI. Their images were evaluated by two otoradiologists. Results: The rate of occurrence of DIAC among SNHL patients was 0.019% (12/64813). The internal auditory canals of 13 ears were divided into double canals by complete (n = 6) and incomplete (n = 7) bony septa, with varied orientations ranging from horizontal to approximately vertical. All of the anterosuperior canals extended into the facial nerve (FN) canal, except for 1, which also extended to the vestibule. The posteroinferior canals ended in the cochlea and vestibule, except for 2, which also connected to the FN canals. Magnetic resonance images revealed that 77.8% (7/9) and 22.2% (2/9) of vestibulocochlear nerves (VCNs) were aplastic and hypoplastic, respectively. Furthermore, 88.9% (8/9) of FNs were normal, except for 1, which was hypoplastic. All of the affected ears also had other ear anomalies: a narrow, bony cochlear nerve canal was the most common other anomaly, accounting for 92.3% (12/13). Malformations of other systems were not found. Conclusion: Double-canal appearance is a characteristic finding of DIAC on HRCT, and it is usually accompanied by other ear anomalies. The VCN usually appears aplastic, with a normal FN, on HRMRI.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.1
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• pp.49-63
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• 2016

In this study, we analyzed the effects of regional hydrologic variability during warm season (June-September) in South Korea due to ENSO (El $Ni{\tilde{n}}o$-Southern Oscillation) pattern changes over the Tropical Pacific Ocean (TPO). We performed composite analysis (CA) and statistical significance test by Student's t-test using observed hydrologic data (such as, precipitation and streamflow) in the 113 sub-watershed areas over the 5-Major River basin, in South Korea. As a result of this study, during the warm-pool (WP) El $Ni{\tilde{n}}o$ year shows a significant increasing tendency than normal years. Particularly, during the cold-tongue (CT) El $Ni{\tilde{n}}o$ decaying years clearly decreasing tendency compared to the normal years was appeared. In addition, the La $Ni{\tilde{n}}a$ years tended to show a slightly increasing tendency and maintain the average year state. In addition, from the result of scatter plot of the percentage anomaly of hydrologic variables during warm season, it is possible to identify the linear increasing tendency. Also the center of the scatter plot shows during the WP El $Ni{\tilde{n}}o$ year (+17.93%, +26.99%), the CT El $Ni{\tilde{n}}a$ year (-8.20%, -15.73%), and the La $Ni{\tilde{n}}a$ year (+8.89%, +15.85%), respectively. This result shows a methodology of the tele-connection based long-range water resources prediction for reducing climate forecasting uncertainty, when occurs the abnormal SSTA (such as, El $Ni{\tilde{n}}o$ and La $Ni{\tilde{n}}a$) phenomenon in the TPO region. Furthermore, it can be a useful data for water managers and end-users to support long-range water-related policy making.