• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.11
• /
• pp.1-6
• /
• 2019

Multicast is an efficient method for real-time transmission in many multimedia applications. It is important to recover lost packets and to manage multicast groups according to the network status in order to improve the reliability of multicast transmissions. In this paper, we propose a method that can efficiently recover lost packets in a large multicast group. In the proposed method, we create a recovery cluster (RC) using a multicast domain (MD) for recovery of lost packets. In the conventional methods, clusters send a request message for lost packets to the senders in order to recover the packets lost from many multicast applications. This increases packet delay time and overhead because of the feedback messages and retransmitted packets. In the proposed method, we improve these problems using the RC, which consists of many MDs (which have overlay multicast senders), and many cluster heads (CHs). We divide the message into blocks, and divide each block into many segments for packet recovery using the CHs. When packet loss occurs, all CHs share the segment information and recover the lost segments at the same time. Simulation results show that the proposed method could improve the packet recovery ratio by about 50% compared to the conventional methods.

• Environmental and Resource Economics Review
• /
• v.16 no.1
• /
• pp.99-127
• /
• 2007

When the margin between available capacity and demand is thin in a liberalized electricity market, prices rise steeply and system reliability is threatened. The principal response to these circumstances is often an assumption that price spikes and electricity shortages are the result of a failure to build sufficient new supplying facilities. It is, of course, often the case that additional investments in generation and network facilities would improve reliability, and such investments are often needed. But focusing on additional generation and transmission facilities for restoring balance to the grid overlooks the essential fact that reliability is a function of the relationship between supply and demand, imposing unnecessary costs on electric system. When the relationship is out of balance, the search for solutions must consider not only investments supply-side resources but also cost-effective demand-side resources such as accelerated load management, efficiency measures, and price-responsive load programs. Integrating demand resources into electricity markets can add enormous value to the electric system, widening the capacity margin, lowering costs and enhancing system reliability at the same time. This paper studies several challenges now facing electricity markets: demand-side management-especially, economic effects of demand response, potential reliability problems, market and system operation, CBP market improvements and so on. The paper concludes with a series of policy recommendations in five areas: (i) The Effects of efficient improvement to incorporate demand responses and demand-side resources into modem electricity markets, (ii) Fosteing price based demand response and (iii) improving incentive based demand response, (iv) strengthen demand response analysis and valuation, (v) integrating demand response into resource planning and adopting enabling technologies.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.9 no.4
• /
• pp.1-12
• /
• 2010

This paper deals with the transmission interval of vehicle data in smart highway where WAVE (Wireless Access for Vehicular Environments) systems have been installed for advanced road infrastructure. The vehicle data could be collected at every second, which is containing location information of the vehicle as well the vehicle speed, RPM, fuel consuming and safety data. The safety data such as DTC code, can be collected through OBD-II. These vehicle data can be used for valuable contents for processing and providing traffic information. In this paper, we propose a model to decide the collection interval of vehicle information in real time environment. This model can change the transmission interval along with special and time-variant traffic condition based on the 32 scenarios using microscopic traffic simulator, VISSIM. We have reviewed the transmission interval, communication transmission quantity and communication interval, tried to confirm about communication possibility and BPS, etc for each scenario. As results, in 2-lane from 1km highway segment, most appropriate transmission interval is 2 times over spatial basic segment considering to communication specification. In the future, if a variety of wireless technologies on the road is introduced, this paper considering not only traffic condition but also wireless network specification will be utilized the high value.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2011.10a
• /
• pp.475-478
• /
• 2011

driver for safety always check the status of their vehicle, and it is essential to understand. But if you want to know the status of the driver of the vehicle in specialist referral time and money because it costs the operator shall be paid. Today's rapidly changing IT technology with the development of the various features of your phone to check the status of the vehicle was able to do. However, the car's existing phone system, car diagnostic expertise must be learned because it will reveal the status of the vehicle do not have the expertise to not highlight the need for diagnostic. To reflect these points in smartphone users to easily use their own vehicles at a time to determine the status of a system that is required. In this paper, OBD-II protocol conversion WiFi OBD-II connector, retrieving information from the driver of the vehicle replacement cycle of consumables required vehicle inspection, vehicle problems in real-time diagnostic information to the user ease of use shows the IOS implementation in the automotive supply was implemented based on the smartphone.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.11 no.5
• /
• pp.514-520
• /
• 2018

Presence service provides various information about users such as locations, status of on/offline and network access methods, and number of presence resources required by each users increases largely in mobile environment. Therefore an effective method which can reduce load of presence servers is needed. In this paper, a large scale distributed presence service system which can distribute effectively total presence system load of presence servers using message control session has been presented. This large scale distributed presence service system provides various presence information for massive volumes of users. In this study, a new message control session architecture which can dynamically distribute loads of the presence servers to multiple servers has been presented, and a new presence information data architecture for controlling load of the presence servers has been designed. In this architecture, each presence server can exchange current load level in real time to get variance of the total system load change according to user numbers, and can distribute system load to maintain load level of each server evenly. The performance of the proposed large scale distributed presence service system has been analysed by experiments. The results has been showed that average presence resource subscription processing time reduced from 42.6% to 73.6%, and average presence notification processing time reduced from 37.6% to 64.8%.

• Journal of Korea Multimedia Society
• /
• v.14 no.5
• /
• pp.658-668
• /
• 2011

Over the past decade, the improvement of communications technologies and the rapid spread of www (World Wide Web) have brought on the exponential growth of users using Internet and real time multimedia multicast services like video conferencing, tele-immersive virtual reality, and Internet games. The dense-wavelength division multiplexing (DWDM) networks have been widely accepted as a promising approach to meet the ever-increasing bandwidth demands of Internet users, especially in next generation Internet backbone networks for nation-wide or global coverage. A major challenge in the next generation Internet backbone networks based on DWDM technologies is the resolution of the multicasting RWA (Routing and Wavelength Assignment) problem; given a set of wavelengths in the DWDM network, we set up light-paths by routing and assigning a wavelength for each connection so that the multicast connections are set-upped as many as possible. Finding such optimal multicast connections has been proven to be Non-deterministic Polynomial-time-complete. In this paper, we suggest a new heuristic multicast routing and wavelength assignment method for multicast sessions called DVS-PMIPMR (Differentiated Virtual Source-based Priority Minimum Interference Path Multicast Routing algorithm). We measured the performance of the proposed algorithm in terms of number of wavelength and wavelength channel. The simulation results demonstrate that DVS-PMIPMR algorithm is superior to previous multicast routing algorithms.

• Journal of Korean Society of Rural Planning
• /
• v.24 no.4
• /
• pp.147-155
• /
• 2018

The purpose of this study was to identify vulnerable area of emergency medical care. In the existing method, the emergency medical vulnerable area is set as an area that can not reach the emergency room within 30 minutes. In this study, we set up an area that can not reach within 30 minutes including the accessibility of 119 emergency center. To accomplish this, we obtained information on emergency room and 119 emergency center through Open API and constructed road network using digital map to perform accessibility analysis. As a result, 509 emergency room are located nationwide, 78.0% of them are concentrated in the region, 1,820 emergency center are located, and 61.0% of them are located in rural areas. The average access time from the center of the village to the emergency room was analyzed as 15.3 minutes, and the average access time considering the 119 emergency center was 21.8 minutes, 6.5 minutes more. As a result of considering the accessibility of 119 emergency center, vulnerable areas increased by 2.5 times, vulnerable population increased by 2.0 times, and calculating emergency medical care vulnerable areas, which account for more than 30% of the urban unit population, it was analyzed that it increased from 17 to 34 cities As a further study, it will be necessary to continuously monitor and research the real-time traffic information, medical personnel, medical field, and ambulance information to reflect the reality and to diagnose emergency medical care in the future.

• Korean Chemical Engineering Research
• /
• v.59 no.2
• /
• pp.209-218
• /
• 2021

First principle-based modeling studies have been performed to improve the heat exchange efficiency of ORV and optimize operation, but the heat transfer coefficient of ORV is an irregular system according to time and location, and it undergoes a complex modeling process. In this study, FNN, LSTM, and AutoML-based modeling were performed to confirm the effectiveness of data-based modeling for complex systems. The prediction accuracy indicated high performance in the order of LSTM > AutoML > FNN in MSE. The performance of AutoML, an automatic design method for machine learning models, was superior to developed FNN, and the total time required for model development was 1/15 compared to LSTM, showing the possibility of using AutoML. The prediction of NG and seawater discharged temperatures using LSTM and AutoML showed an error of less than 0.5K. Using the predictive model, real-time optimization of the amount of LNG vaporized that can be processed using ORV in winter is performed, confirming that up to 23.5% of LNG can be additionally processed, and an ORV optimal operation guideline based on the developed dynamic prediction model was presented.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.16 no.4
• /
• pp.69-81
• /
• 2006

The Computer Forensics is a research area that finds the malicious users by collecting and analyzing the intrusion or infringement evidence of computer crimes such as hacking. Many researches about Computer Forensics have been done so far. But those researches have focussed on how to collect the forensic evidence for both analysis and poofs after receiving the intrusion or infringement reports of hosts from computer users or network administrators. In this paper, we describe how to collect the forensic evidence of good quality from observable and protective hosts at the time of infringement occurrence by malicious users. By correlating the event logs of Intrusion Detection Systems(IDSes) and hosts with the configuration information of hosts periodically, we calculate the value of infringement severity that implies the real infringement possibility of the hosts. Based on this severity value, we selectively collect the evidence for proofs at the time of infringement occurrence. As a result, we show that we can minimize the information damage of the evidence for both analysis and proofs, and reduce the amount of data which are used to analyze the degree of infringement severity.

• International conference on construction engineering and project management
• /
• 2024.07a
• /
• pp.1307-1307
• /
• 2024

Recent research on heavy equipment has been conducted for the purposes of enhanced safety, productivity improvement, and carbon neutrality at construction sites. A sensor-based approach is being explored to monitor the location and movements of heavy equipment in real time. However, it poses significant challenges in terms of time and cost as multiple sensors should be installed on numerous heavy equipment at construction sites. In addition, there is a limitation in identifying the collaboration or interference between two or more heavy equipment. In light of this, a vision-based deep learning approach is being actively conducted to effectively respond to various working conditions and dynamic environments. To enhance the performance of a vision-based activity recognition model, it is essential to secure a sufficient amount of training datasets (i.e., video datasets collected from actual construction sites). However, due to safety and security issues at construction sites, there are limitations in adequately collecting training dataset under various situations and environmental conditions. In addition, the videos feature a sequence of multiple activities of heavy equipment, making it challenging to clearly distinguish the boundaries between preceding and subsequent activities. To address these challenges, this study proposed a domain adaptation in vision-based transfer learning for automated excavator activity recognition utilizing 3D ResNet (residual deep neural network). Particularly, this study aimed to identify the optimal depth of 3D ResNet (i.e., the number of layers of the feature extractor) suitable for domain adaptation via fine-tuning process. To achieve this, this study sought to evaluate the activity recognition performance of five 3D ResNet models with 18, 34, 50, 101, and 152 layers, which used two consecutive videos with multiple activities (5 mins, 33 secs and 10 mins, 6 secs) collected from actual construction sites. First, pretrained weights from large-scale datasets (i.e., Kinetic-700 and Moment in Time (MiT)) in other domains (e.g., humans, animals, natural phenomena) were utilized. Second, five 3D ResNet models were fine-tuned using a customized dataset (14,185 clips, 60,606 secs). As an evaluation index for activity recognition model, the F1 score showed 0.881, 0.689, 0.74, 0.684, and 0.569 for the five 3D ResNet models, with the 18-layer model performing the best. This result indicated that the activity recognition models with fewer layers could be advantageous in deriving the optimal weights for the target domain (i.e., excavator activities) when fine-tuning with a limited dataset. Consequently, this study identified the optimal depth of 3D ResNet that can maintain a reliable performance in dynamic and complex construction sites, even with a limited dataset. The proposed approach is expected to contribute to the development of decision-support systems capable of systematically managing enhanced safety, productivity improvement, and carbon neutrality in the construction industry.