• Journal of Korean Neurosurgical Society
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• v.45 no.4
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• pp.209-212
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• 2009

Objective : Avascular necrosis (AVN) of the vertebral body is known as a relatively uncommon phenomenon in a vertebral compression fracture (VCF). The outstanding radiologic findings of AVN are intravertebral vacuum phenomenon with or without fluid collection. Several reports revealed that PVP or balloon kyphoplasty might be the effective treatment modalities for AVN. We also experienced excellent results when using PVP for the treatment of AVN of the vertebral body, and intend to describe the treatment's efficacy in this report. Methods : Thirty-two patients diagnosed with AVN of the vertebral body were treated with PVP. We measured the pre- and post-operative anterior body height and kyphotic angulation. The visual analogue scale (VAS) was used to determine the relief of back pain. Results : The anterior body height (pre-operative : 1.49 cm, post-operative : 2.22 cm) and kyphotic angulation (pre-operative : 14.47 degrees, post-operative : 6.57 degrees) were significantly restored (p<0.001). VAS was improved from 8.9 to 3.7. Pseudoarthrosis was corrected in all cases, which was confirmed by dynamic radiographs. Fluid collection was found in sixteen cases and was aspirated with serous nature. No organism and tumor cell were noted. Conclusion : PVP proved to be an effective procedure for the treatment of AVN of the vertebral body, which corrected dynamic instability and significantly restored the anterior body height and kyphotic angulation.

• Journal of Digital Convergence
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• v.18 no.3
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• pp.189-194
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• 2020

Recently, various clustering techniques have been studied to efficiently handle data generated by heterogeneous IoT devices. However, existing clustering techniques are not suitable for mobile IoT devices because they focus on statically dividing networks. This paper proposes a probabilistic deep learning-based dynamic clustering model for collecting and analyzing information on IoT devices using edge networks. The proposed model establishes a subnet by applying the frequency of the attribute values collected probabilistically to deep learning. The established subnets are used to group information extracted from seeds into hierarchical structures and improve the speed and accuracy of dynamic clustering for IoT devices. The performance evaluation results showed that the proposed model had an average 13.8 percent improvement in data processing time compared to the existing model, and the server's overhead was 10.5 percent lower on average than the existing model. The accuracy of extracting IoT information from servers has improved by 8.7% on average from previous models.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.6
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• pp.850-854
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• 2014

Analyzing dynamic performance between pantograph and contact wire depends on mechanical and electrical conditions such as contact force, currents, aerodynamics of pantograph and tension of overhead contact wire. For the characteristic of dynamic performance between pantograph and overhead contact wire, various evaluation systems are used to measuring of the interaction of the contact line and the pantograph. Among the various methods, the contact force and percentage of arcing are intended to prove the safety and the quality of the current collection system on the train. However, these methods are only capable of measuring on the train which are installed measurement systems. Therefore in this paper, a track-side monitoring system was implemented to measure electrical characteristics from active overhead contact wire systems in order to constantly estimate current collection performance of railway operation. In addition, a method to analyze loss of contact phenomena was proposed. According to simulation results, the proposed system was capable of measuring abnormal electrical behavior of pantograph and contact wires on the track-side. The advantage of the proposed system is possible to detect loss of contact or any other electrical abnormalities of all types of trains within sections from sub to sub without the need to install any on-board equipment on trains.

• Convergence Security Journal
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• v.23 no.2
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• pp.27-36
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• 2023

In recent years, ransomware attacks have become more organized and specialized, with the sophistication of attacks targeting specific individuals or organizations using tactics such as social engineering, spear phishing, and even machine learning, some operating as business models. In order to effectively respond to this, various researches and solutions are being developed and operated to detect and prevent attacks before they cause serious damage. In particular, honeypots can be used to minimize the risk of attack on IT systems and networks, as well as act as an early warning and advanced security monitoring tool, but in cases where ransomware does not have priority access to the decoy file, or bypasses it completely. has a disadvantage that effective ransomware response is limited. In this paper, this honeypot is optimized for the user environment to create a reliable real-time dynamic honeypot file, minimizing the possibility of an attacker bypassing the honeypot, and increasing the detection rate by preventing the attacker from recognizing that it is a honeypot file. To this end, four models, including a basic data collection model for dynamic honeypot generation, were designed (basic data collection model / user-defined model / sample statistical model / experience accumulation model), and their validity was verified.

• Industrial Engineering and Management Systems
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• v.13 no.4
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• pp.383-397
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• 2014

Reverse logistics network design issues have been popularly discussed in recent years. However, few papers in the past literature have been dedicated to incentive effect on return quantity of used products. The purpose of this study is to formulate a dynamic nonlinear programming model of reverse logistics network design with the aim of managing the used products allocation by coordinating the collection centers and recovery facilities to warrant economic efficiency. In the optimization model, a fuzzy approach is applied to interpret the relationship between the rate of return and the suggested incentives. Due to funding constraints in setting up the collection centers, this work considers these centers as multi-capacity levels, which can be opened or closed at different periods. In view of the fact that the problem is known as NP-hard, we propose a heuristic method based on tabu search procedure to solve the presented model. Finally, several dominance properties of optimal solutions are demonstrated in comparison with the results of a state-of-the-art commercial solver.

• Journal of Construction Engineering and Project Management
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• v.8 no.1
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• pp.10-21
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• 2018

Many construction projects involve a plethora of safety-related problems that can cause loss of productivity, diminished revenue, time overruns, and legal challenges. Incorporating data collection and analytics methods can help overcome the root causes of many such problems. However, in a dynamic construction workplace collecting data from a large number of resources is not a trivial task and can be costly, while many contractors lack the motivation to incorporate technology in their activities. In this research, an Android-based mobile application, Preemptive Construction Site Safety (PCS2) is developed and tested for real-time location tracking, trajectory prediction, and prevention of potential collisions between workers and site hazards. PCS2 uses ubiquitous mobile technology (smartphones) for positional data collection, and a robust trajectory prediction technique that couples hidden Markov model (HMM) with risk-taking behavior modeling. The effectiveness of PCS2 is evaluated in field experiments where impending collisions are predicted and safety alerts are generated with enough lead time for the user. With further improvement in interface design and underlying mathematical models, PCS2 will have practical benefits in large scale multi-agent construction worksites by significantly reducing the likelihood of proximity-related accidents between workers and equipment.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.893-903
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• 2022

Recently, computer vision (CV)-based safety monitoring (i.e., object detection) system has been widely researched in the construction industry. Sufficient and high-quality data collection is required to detect objects accurately. Such data collection is significant for detecting small objects or images from different camera angles. Although several previous studies proposed novel data augmentation and synthetic data generation approaches, it is still not thoroughly addressed (i.e., limited accuracy) in the dynamic construction work environment. In this study, we proposed a game engine-driven synthetic data generation model to enhance the accuracy of the CV-based object detection model, mainly targeting small objects. In the virtual 3D environment, we generated synthetic data to complement training images by altering the virtual camera angles. The main contribution of this paper is to confirm whether synthetic data generated in the game engine can improve the accuracy of the CV-based object detection model.

• Journal of the Korea Society of Computer and Information
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• v.25 no.11
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• pp.123-129
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• 2020

Recently, cybercrime has become increasingly difficult to track by applying new technologies such as virtualization technology and distribution tracking avoidance. etc. Therefore, there is a limit to the technology of tracking distributors based on malicious code information through static and dynamic analysis methods. In addition, in the field of cyber investigation, it is more important to track down malicious code distributors than to analyze malicious codes themselves. Accordingly, in this paper, we propose a next-generation malicious code information collection architecture to efficiently track down malicious code distributors by converging traditional analysis methods and recent information collection methods such as OSINT and Intelligence. The architecture we propose in this paper is based on the differences between the existing malicious code analysis system and the investigation point's analysis system, which relates the necessary elemental technologies from the perspective of cybercrime. Thus, the proposed architecture could be a key approach to tracking distributors in cyber criminal investigations.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.7
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• pp.827-833
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• 2011

In this study, a simulation model to estimate the current-collection performance of a high-speed train was developed by using a commercial finite element analysis software, SAMCEF. A three-dimensional springDdamperDmass model of a pantograph was created, and its reliability was validated by comparing the receptance of the model to that of the actual pantograph. The wave propagation speed of the catenary model was compared with the analytical wave propagation speed of the catenary system presented in the UIC 799 OR standard. The length of the droppers was controlled, and the pre-sag of the contact wire due to gravity was considered. The catenary and the pantograph were connected by using a contact element, and the contact force variation when the pantograph was moved at velocities of 300 km/h and 370 km/h was obtained. The average, standard deviation, maximum, and minimum values of the contact force were analyzed, and the effectiveness of the developed simulation model was examined.

• The Transactions of the Korea Information Processing Society
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• v.7 no.11S
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• pp.3732-3838
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• 2000

As the Internet sites and users have rapidly been increased, the development for search engines has also been accelerated to satisfy users' expectations. As the result, not only the action of collecting documents through many search engines gave hosts workload, but also regular updating all the information is needed since information is newly added. With the circumstances, the necessity of the technology to collect massive information in hosts has been increased for the speed which is a basic requisite of search systems, and for more accurate collection of documents. Also, the role of search engines grows bigger for Internet users' various demands and flexible process through World Wide Web. In this paper, we design and implement a robot agent and a remote control system which doesn't give an excessive workload on a target server and makes the collection of documents done in a short period by considering an average workload rate on the target server and the rate of the workload that a robot experience in collection time, after we compare and analyze the existing Robot Agent Systems and supplement their weak points.