• Journal of Information Processing Systems
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• v.10 no.1
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• pp.1-22
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• 2014

Recent technological advances provide the opportunity to use large amounts of multimedia data from a multitude of sensors with different modalities (e.g., video, text) for the detection and characterization of criminal activity. Their integration can compensate for sensor and modality deficiencies by using data from other available sensors and modalities. However, building such an integrated system at the scale of neighborhood and cities is challenging due to the large amount of data to be considered and the need to ensure a short response time to potential criminal activity. In this paper, we present a system that enables multi-modal data collection at scale and automates the detection of events of interest for the surveillance and reconnaissance of criminal activity. The proposed system showcases novel analytical tools that fuse multimedia data streams to automatically detect and identify specific criminal events and activities. More specifically, the system detects and analyzes series of incidents (an incident is an occurrence or artifact relevant to a criminal activity extracted from a single media stream) in the spatiotemporal domain to extract events (actual instances of criminal events) while cross-referencing multimodal media streams and incidents in time and space to provide a comprehensive view to a human operator while avoiding information overload. We present several case studies that demonstrate how the proposed system can provide law enforcement personnel with forensic and real time tools to identify and track potential criminal activity.

• The Journal of the Acoustical Society of Korea
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• v.42 no.5
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• pp.395-401
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• 2023

Sound Event Detection (SED) aims to identify not only sound category but also time interval for target sounds in an audio waveform. It is a critical technique in field of acoustic surveillance system and monitoring system. Recently, various models have introduced through Detection and Classification of Acoustic Scenes and Events (DCASE) Task 4. This paper explored how to design optimal parameters of DenseNet based model, which has led to outstanding performance in other recognition system. In experiment, DenseRNN as an SED model consists of DensNet-BC and bi-directional Gated Recurrent Units (GRU). This model is trained with Mean teacher model. With an event-based f-score, evaluation is performed depending on parameters, related to model architecture as well as model training, under the assessment protocol of DCASE task4. Experimental result shows that the performance goes up and has been saturated to near the best. Also, DenseRNN would be trained more effectively without dropout technique.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.357-358
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• 2021

Although many people watch the scene with multiple surveillance cameras, it is difficult to ensure that immediate action can be taken in the event of a crime. Therefore, there is a need for a "crime behavior detection system" that can analyze images in real time from multiple surveillance cameras installed in elevators, call immediate crime alerts, and track crime scenes and times effectively. In this paper, a study was conducted to detect violent scenes occurring in elevators using Scene Change Detection. For effective detection, an x2-color histogram combining color histogram and histogram was applied.

• Journal of the Korea Society of Computer and Information
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• v.23 no.8
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• pp.9-16
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• 2018

In this paper, a kidnapping detection scheme in which human pose estimation is used to classify accurately between kidnapping cases and normal ones is proposed. To estimate human poses from input video, human's 10 joint information is extracted by OpenPose library. In addition to the features which are used in the previous study to represent the size change rates and the regularities of human activities, the human pose estimation features which are computed from the location of detected human's joints are used as the features to distinguish kidnapping situations from the normal accompanying ones. A frame-based kidnapping detection scheme is generated according to the selection of J48 decision tree model from the comparison of several representative classification models. When a video has more frames of kidnapping situation than the threshold ratio after two people meet in the video, the proposed scheme detects and notifies the occurrence of kidnapping event. To check the feasibility of the proposed scheme, the detection accuracy of our newly proposed scheme is compared with that of the previous scheme. According to the experiment results, the proposed scheme could detect kidnapping situations more 4.73% correctly than the previous scheme.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.5
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• pp.913-919
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• 2011

In this paper, we present a new efficient event detection algorithm for sensor networks with faults. We focus on multi-attributed events, which are sets of data points that correspond to interesting or unusual patterns in the underlying phenomenon that the network monitors. Conventional algorithms cannot detect some events because they treat only their own sensor readings which can be affected easily by environmental or physical problem. Our approach exploits spatio-temporal correlation of sensor readings. Sensor nodes exchange a fault-tolerant code encoded their own readings with neighbors, organize virtual sensor readings which have spatio-temporal correlation, and determine a result for multi-attributed events from them. In the result, our proposed algorithm provides improvement of detecting multi-attributed events and reduces the number of false-negatives due to negative environmental effects.

• Investigative Magnetic Resonance Imaging
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• v.25 no.3
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• pp.193-196
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• 2021

Congenital absence of the bilateral internal carotid arteries (ICA) is a very rare occurrence. Recognition of this rare anomaly is important, when considering intracranial endovascular interventions in the event of thromboembolic events with revascularization, transsphenoidal surgery, and the surveillance and detection of associated cerebral aneurysms. We report a case of a 25-year-old man who presented with headache since 2 years ago, and was incidentally discovered to have a congenital bilateral absence of ICAs.

• Korean Journal of Clinical Pharmacy
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• v.32 no.3
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• pp.226-237
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• 2022

Background: Monoclonal antibodies for the treatment of patients with different types of cancer, such as cetuximab, have been widely used for the past 10 years in oncology. Although drug information package insert contains some representative adverse events which were observed in the clinical trials for drug approval, the overall adverse event patterns on the real-world cetuximab use were less investigated. Also, there have been no published papers that deal with the full spectrums of adverse drug events of cetuximab using national-wide drug safety surveillance systems. Methods: In this study, we detected new adverse event signals of cetuximab in the Korea Adverse Event Reporting System (KAERS) by utilizing proportional reporting ratios, reporting odds ratios, and information components indices. Results: The KAERS database included 869,819 spontaneous adverse event reports, among which 2,116 reports contained cetuximab. We compared the labels of cetuximab among the United States, European Union, Australia, Japan, and Korea to compare the current labeling information and newly detected signals of our study. Some of the signals including hyperkeratosis, tenesmus, folliculitis, esophagitis, neuralgia, disseminated intravascular coagulopathy, and skin/throat tightness were not labeled in the five countries. Conclusion: We identified new signals that were not known at the time of market approval.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1123-1140
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• 2019

Many Internet of Things (IoT) applications involving bursty traffic have emerged recently with event detection. A power management scheme qualified for uplink bursty traffic (PM-UBT) is proposed by distinguishing between bursty and general uplink traffic patterns in the IEEE 802.11 standard to balance energy consumption and uplink latency, especially for stations with limited power and constrained buffer size. The proposed PM-UBT allows a station to transmit an uplink bursty frame immediately regardless of the state. Only when the sleep timer expires can the station send uplink general traffic and receive all downlink frames from the access point. The optimization problem (OP) for PM-UBT is power consumption minimization under a constrained buffer size at the station. This OP can be solved effectively by the bisection method, which demonstrates a performance similar to that of exhaustive search but with less computational complexity. Simulation results show that when the frame arrival rate in a station is between 5 and 100 frame/second, PM-UBT can save approximately 5 mW to 30 mW of power compared with an existing power management scheme. Therefore, the proposed power management strategy can be used efficiently for delay-intolerant uplink traffic in event-driven IoT applications, such as health status monitoring and environmental surveillance.

• Korean Journal of Remote Sensing
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• v.36 no.2_2
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• pp.379-399
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• 2020

The detection of illegal ship is one of the key factors in building a marine surveillance system. Effective marine surveillance requires the means for continuous monitoring over a wide area. In this study, the possibility of ship detection monitoring based on satellite SAR, HF radar, UAV and AIS integration was investigated. Considering the characteristics of time and spatial resolution for each platform, the ship monitoring scenario consisted of a regular surveillance system using HFR data and AIS data, and an event monitoring system using satellites and UAVs. The regular surveillance system still has limitations in detecting a small ship and accuracy due to the low spatial resolution of HF radar data. However, the event monitoring system using satellite SAR data effectively detects illegal ships using AIS data, and the ship speed and heading direction estimated from SAR images or ship tracking information using HF radar data can be used as the main information for the transition to UAV monitoring. For the validation of monitoring scenario, a comprehensive field experiment was conducted from June 25 to June 26, 2019, at the west side of Hongwon Port in Seocheon. KOMPSAT-5 SAR images, UAV data, HF radar data and AIS data were successfully collected and analyzed by applying each developed algorithm. The developed system will be the basis for the regular and event ship monitoring scenarios as well as the visualization of data and analysis results collected from multiple platforms.

• Journal of Radiation Protection and Research
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• v.44 no.3
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• pp.118-126
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• 2019

Background: Government conducts environmental radioactivity surveillance for verification purpose around nuclear facilities based on the Nuclear Safety Law and issues a surveillance report every year. This study aims to evaluate the short and the long-term fluctuation of radionuclides detected above MDC and their origins using concentration ratios between these radionuclides. Materials and Methods: Sample media for verification surveillance are air, rainwater, groundwater, soil, and milk for terrestrial samples, and seawater, marine sediment, fish, and seaweed for marine samples. Gamma-emitting radionuclides including $^{137}Cs$, $^{90}Sr$, Pu, $^3H$, and $^{14}C$ are evaluated in these samples. Results and Discussion: According to the result of the environmental radioactivity verification surveillance in the vicinity of nuclear power facilities in 2017, the anthropogenic radionuclides were not detected in most of the environmental samples except for the detection of a trace level of $^{137}Cs$, $^{90}Sr$, Pu, and $^{131}I$ in some samples. Radioactivity concentration ratios between the anthropogenic radionuclides ($^{137}Cs/^{90}Sr$, $^{137}Cs/^{239+240}Pu$, $^{90}Sr/^{239+240}Pu$) were similar to those reported in the environmental samples, which were affected by the global fallout of the past nuclear weapon test, and Pu atomic ratios ($^{240}Pu/^{239}Pu$) in the terrestrial sample and marine sample showed significant differences due to the different input pathway and the Pu source. Radioactive iodine ($^{131}I$) was detected at the range of < $5.6-190mBq{\cdot}kg-fresh^{-1}$ in the gulfweed and sea trumpet collected from the area of Kori and Wolsong intake and discharge. A high level of $^3H$ was observed in the air (Sangbong: $0.688{\pm}0.841Bq{\cdot}m^{-3}$) and the precipitation (Meteorology Post: $199{\pm}126Bq{\cdot}L^{-1}$) samples of the Wolsong nuclear power plant (NPP). $^3H$ concentration in the precipitation and pine needle samples showed typical variation pattern with the distance and the wind direction from the stack due to the gaseous release of $^3H$ in Wolsong NPP. Conclusion: Except for the detection of a trace level of $^{137}Cs$, $^{90}Sr$, Pu, and $^{131}I$ in some samples, anthropogenic radionuclides were below MDC in most of the environmental samples. Overall, no unusual radionuclides and abnormal concentration were detected in the 2017's surveillance result for verification. This research will be available in the assessment of environment around nuclear facilities in the event of radioactive material release.