• The Journal of Korean Institute of Information Technology
• /
• v.16 no.11
• /
• pp.69-76
• /
• 2018

As for V2I(Vehicle-to-Infrastructure) systems with energy-constrained RSUs(Road Side Units), the previous data delivery strategies have not considered the aspect of energy usage at RSUs. A new data delivery strategy has been proposed to determine the RSU's participation in data delivery based on the probability dependent on the RSU's remaining energy, and it showed the lower data delivery time than the previous approaches. In this paper, we propose methods to analyze the number of RSUs participating in data delivery and the variations of RSUs' energy value for the consecutive data deliveries. As a numerical result, compared with the previous strategy, the probability-based data delivery strategy shows the lower number of participating RSUs and the increased average energy value of all RSUs. In addition, from the analytical results, we propose considerations for the real implementations of the similar systems.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.14 no.2
• /
• pp.377-388
• /
• 2019

The system proposed in this paper was suggested as a big data system that works in the age of artificial intelligence of the 4th Industrial Revolution. The proposed system can be a good example in terms of government 's development of new intelligent big data information system. For example, the proposed system may be introduced into the system of a department as a function of the integration of existing cinema ticket integration network or its networking. For this purpose, the proposed system transmits the user's profile to the film producer or other company, where it is provided as comparison data. Soon, the information is sent to the user-specific characteristic data and then the film-maker will be able to gauge the success of the three elements of the movie's performance, cinematic quality, and break-even point in real time, which are revealed through the movie review that the actual user feels, including the so-called 'new reinterpretation.

• International Journal of Clinical Preventive Dentistry
• /
• v.14 no.4
• /
• pp.264-270
• /
• 2018

Objective: This study performed a quantitative analysis using the real-time polymerase chain reaction technique to examine the oral microbial prevalence in adults and intended to examine the correlations between risk factors of periodontal disease and oral bacteria and correlation between oral test scores and oral microorganisms. Methods: We examined papillary marginal attached (PMA) index, modified patient hygiene performance (M-PHP) index, probing depth (PD), modified gingival index, and oral bacteria counts and surveyed 117, 20 years or older adult males and females who visited dental clinics in the Daejeon region to analyze the prevalence and oral health. Results: The prevalence was 100% for Fusobacterium nucleatum, meaning it was observed in all examined subject, 85.5% for Parvimonas micra, 76.1% for Prevotella intermedia, and 72.6% for Tannerella forsythia. The averages of P. gingivalis and T. forsythia increased as the examined subjects were older, and there was a statistically significant difference between T. forsythia and E. nodatum in relation to medical history, between P. intermedia and P. micra in relation to gender, and between P. intermedia and E. corrodens in relation to smoking (p<0.05). For a correlation between the oral test scores and oral microorganisms, P. gingivalis and F. nucleatum was highly correlated with PD (correlation coefficient of 0.51 and 0.41) (p<0.01) while P. gingivalis, P. micra, C. rectus, and E. nodatum were significantly correlated with M-PHP index, gingival index, PD, and PMA index (p<0.01, p<0.05). Conclusion: For oral health management of adults, the age, systemic disease, and smoking are closely related to oral bacteria, and P. gingivalis, T. forsythia, F. nucleatum, P. intermedia, P. micra, C. rectus, E. corrodens, and E. nodatum are considered to be the oral microorganisms that indicate periodontal health.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.9 no.1
• /
• pp.57-70
• /
• 1999

Since a hybrid firewall filters packets at a network layer along with providing gateway functionalities at an application layer, it has a better performance than an If filtering firewall. In addition, it provides both the various kinds of access control mechanisms and transparent services to users. However, the security policies of a network layer are different from those of an application layer. Thus, the user interfaces for managing a hybrid firewalls in a consistent manner are needed. In this paper, we implement a graphical user interface to provide access control mechanisms and management facilities for a hybrid firewall such as log analysis, a real-time monitor for network traffics, and the statisics on traffics. And we also propose a new rule script language for specifying access control rules. By using the script language, users can generate the various forma of access control rules which are adapted by the existing firewalls.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.1
• /
• pp.146-151
• /
• 2021

Currently, the demand for vehicles from one family is increasing in many countries at home and abroad, reducing the number of people on the vehicle and increasing the number of vehicles on the road. The multi-passenger lane system, which is available to solve the problem of traffic congestion, is being implemented. The system allows police to monitor fast-moving vehicles with their own eyes to crack down on illegal vehicles, which is less accurate and accompanied by the risk of accidents. To address these problems, applying deep learning object recognition techniques using images from road sites will solve the aforementioned problems. Therefore, in this paper, we compare and analyze the performance of existing deep learning models, select a deep learning model that can identify real-time vehicle occupants through video, and propose a vehicle occupancy detection algorithm that complements the object-ident model's problems.

• International Journal of Computer Science & Network Security
• /
• v.22 no.2
• /
• pp.406-412
• /
• 2022

Storing large amounts of data has always been a big problem from the beginning of computing history. Big Data has made huge advancements in improving business processes by finding the customers' needs using prediction models based on web and social media search. The main purpose of big data stream processing frameworks is to allow programmers to directly query the continuous stream without dealing with the lower-level mechanisms. In other words, programmers write the code to process streams using these runtime libraries (also called Stream Processing Engines). This is achieved by taking large volumes of data and analyzing them using Big Data frameworks. Streaming platforms are an emerging technology that deals with continuous streams of data. There are several streaming platforms of Big Data freely available on the Internet. However, selecting the most appropriate one is not easy for programmers. In this paper, we present a detailed description of two of the state-of-the-art and most popular streaming frameworks: Apache Ignite and Hazelcast. In addition, the performance of these frameworks is compared using selected attributes. Different types of databases are used in common to store the data. To process the data in real-time continuously, data streaming technologies are developed. With the development of today's large-scale distributed applications handling tons of data, these databases are not viable. Consequently, Big Data is introduced to store, process, and analyze data at a fast speed and also to deal with big users and data growth day by day.

• Journal of the Society of Disaster Information
• /
• v.18 no.3
• /
• pp.487-494
• /
• 2022

Purpose: This study proposes a Metaverse-based police education and training model that can efficiently improve the performance of various police activities according to changes in the environment of the times. Method: The structure of this system can generate Avatar Controller expressed using HMD and haptic technology, access the Network Interface, and educate and train individually or on a team basis through the command control module, education and training content module, and analysis module. Result: In the proposed model of this study, the command and control module was incorporated into individual or team-based education and training, enabling organic collaborative training among team members by monitoring the overall situation of terrorism or crime in real time. Conclusion: Metaverses-based individual or team-based police education and training can provide a more efficient and safe education and training environment based on immersion, interaction, and rapid judgment in various situations.

• Structural Engineering and Mechanics
• /
• v.86 no.5
• /
• pp.647-661
• /
• 2023

It is recognized that the installation of energy dissipation devices, such as the tuned mass damper (TMD), decreases the dynamic response of structures, however, the best parameters of each device persist hard to determine. Unlike many works that perform only a deterministic optimization, this work proposes a complete methodology to minimize the dynamic response of footbridges by optimizing the parameters of multiple tuned mass dampers (MTMD) taking into account uncertainties present in the parameters of the structure and also of the human excitation. For application purposes, a steel footbridge, based on a real structure, is studied. Three different scenarios for the MTMD are simulated. The proposed robust optimization problem is solved via the Circle-Inspired Optimization Algorithm (CIOA), a novel and efficient metaheuristic algorithm recently developed by the authors. The objective function is to minimize the mean maximum vertical displacement of the footbridge, whereas the design variables are the stiffness and damping constants of the MTMD. The results showed the excellent capacity of the proposed methodology, reducing the mean maximum vertical displacement by more than 36% and in a computational time about 9% less than using a classical genetic algorithm. The results obtained by the proposed methodology are also compared with results obtained through traditional TMD design methods, showing again the best performance of the proposed optimization method. Finally, an analysis of the maximum vertical acceleration showed a reduction of more than 91% for the three scenarios, leading the footbridge to acceleration values below the recommended comfort limits. Hence, the proposed methodology could be employed to optimize MTMD, improving the design of footbridges.

• International conference on construction engineering and project management
• /
• 2020.12a
• /
• pp.87-95
• /
• 2020

Generally, occupational safety and particularly construction safety is an intricate phenomenon. Industry professionals have devoted vital attention to enforcing Occupational Safety and Health (OHS) from the last three decades to enhance safety management in construction. Despite the efforts of the safety professionals and government agencies, current safety management still relies on manual inspections which are infrequent, time-consuming and prone to error. Extensive research has been carried out to deal with high fatality rates confronting by the construction industry. Sensor systems, visualization-based technologies, and tracking techniques have been deployed by researchers in the last decade. Recently in the construction industry, computer vision has attracted significant attention worldwide. However, the literature revealed the narrow scope of the computer vision technology for safety management, hence, broad scope research for safety monitoring is desired to attain a complete automatic job site monitoring. With this regard, the development of a broader scope computer vision-based risk recognition system for correlation detection between the construction entities is inevitable. For this purpose, a detailed analysis has been conducted and related rules which depict the correlations (positive and negative) between the construction entities were extracted. Deep learning supported Mask R-CNN algorithm is applied to train the model. As proof of concept, a prototype is developed based on real scenarios. The proposed approach is expected to enhance the effectiveness of safety inspection and reduce the encountered burden on safety managers. It is anticipated that this approach may enable a reduction in injuries and fatalities by implementing the exact relevant safety rules and will contribute to enhance the overall safety management and monitoring performance.

• Korean Circulation Journal
• /
• v.52 no.10
• /
• pp.755-767
• /
• 2022

Background and Objectives: Cryoballoon catheter ablation for the treatment of patients with symptomatic atrial fibrillation (AF) has been adopted globally, but there are limited multicenter reports of 12-month outcomes in the Korean patient population. This analysis evaluated the clinical performance and safety of cryoballoon ablation (CBA) according to standard-of-care practices in Korea. Methods: This evaluation of Korean patients with AF was conducted within the larger Cryo Global Registry, which is a prospective, multicenter, post-market registry. Freedom from a ≥30-second recurrence of atrial arrhythmias (after a 90-day blanking period until 12 months) and procedural safety were examined in subjects treated with CBA at 3 Korean centers. Results: Overall, 299 patients with AF (60±11 years old, 24.7% female, 50.5% paroxysmal AF) underwent CBA using the Arctic Front Advance cryoballoon. Of those, 298 were followed-up for at least 12 months. Mean procedure-, left atrial dwell- and fluoroscopy time was 76±21 minutes, 56±23 minutes, and 27±23 minutes, respectively. Freedom from AF recurrence at 12 months was 83.9% (95% confidence interval [CI], 76.9-88.9%) in the paroxysmal and 61.6% (95% CI, 53.1-69.0%) in the persistent AF cohort. Rhythm monitoring was performed on average 4.7±1.4 times during the follow-up period. Serious device- or procedure-related adverse events occurred in 2 patients (0.7%). The 12-month Kaplan-Meier estimate of freedom from repeat ablation and cardiovascular-related hospitalization was 93.8% (95% CI, 90.4-96.1%) and 89.7% (95% CI, 85.6-92.7%), respectively. Conclusions: CBA is an efficient, effective, and safe procedure for the treatment of AF patients when used according to real-world practices in Korea.