• Journal of Environmental Health Sciences
• /
• v.30 no.3
• /
• pp.245-252
• /
• 2004

Two biofilter tests were conducted under different operating conditions. Test # 1 was performed to treat VOCs generated from a paint booth. The second test was performed to treat VOCs generated from chemical manufacturing processes. The volume of biofilter media was 4.3 $m^3$. For the test # 1, the biofilter was operated for 30 days with 99.9% reduction ratio. Range of temperature of each stage of the biofilter media was measured between $34^{\circ}C$ and $73^{\circ}C$. All the temperatures of stages reduced gradually after the initial dramatic increase. For the test # 2, the biofilter experiment was conducted for 14 days. In this case, the biofilter was installed outdoor and the experiment was performed during wintertime. Therefore, temperature management for the biofilter was needed. Seven-centimeter thick fiberglass insulation and $150^{\circ}C$ steam heating were used to overcome the outside freezing cold weather during test # 2. Temperature of stage # 5 was measured the highest and that of stage # 1 was the lowest. More acclimation time and test period was needed to determine the maximum loading rate.

• Journal of Intelligence and Information Systems
• /
• v.14 no.3
• /
• pp.59-76
• /
• 2008

In this paper, we propose an agent architecture called L-CAA that is quite effective in real-time dynamic environments. L-CAA is an extension of CAA, the behavior-based agent architecture which was also developed by our research group. In order to improve adaptability to the changing environment, it is extended by adding reinforcement learning capability. To obtain stable performance, however, behavior selection and execution in the L-CAA architecture do not entirely rely on learning. In L-CAA, learning is utilized merely as a complimentary means for behavior selection and execution. Behavior selection mechanism in this architecture consists of two phases. In the first phase, the behaviors are extracted from the behavior library by checking the user-defined applicable conditions and utility of each behavior. If multiple behaviors are extracted in the first phase, the single behavior is selected to execute in the help of reinforcement learning in the second phase. That is, the behavior with the highest expected reward is selected by comparing Q values of individual behaviors updated through reinforcement learning. L-CAA can monitor the maintainable conditions of the executing behavior and stop immediately the behavior when some of the conditions fail due to dynamic change of the environment. Additionally, L-CAA can suspend and then resume the current behavior whenever it encounters a higher utility behavior. In order to analyze effectiveness of the L-CAA architecture, we implement an L-CAA-enabled agent autonomously playing in an Unreal Tournament game that is a well-known dynamic virtual environment, and then conduct several experiments using it.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2013.10a
• /
• pp.184-187
• /
• 2013

The Four Major Rivers Restoration Project of is the multi-purpose green growth project in South Korea. Some of the project was progressed by K-water and was declared complete on October 21, 2011. The Four Rivers Restoration Project of Korea was designed to be a packaged project that aims to resolve water-related problems such as floods and droughts and revitalize Korean public spaces near the water. K-water have applied the latest ICT(Information and Communication Technology) for the operating management of 4 Rivers Project facilities. We also have applied ICT for integrating drinking water production facilities. Applying these ICT, we have many experience for integrated water resources management, so we proposed. The first is that the big data collected should be analyzed for making decisions and taking actions while considering multiple viewpoints of how water should be managed. The second is that the new MMI(Man Machine Interface) program should be developed to use domestic needs and promote ease of maintenance for the integrated operation. The third is that the standardization of communication protocol is needed for seamless communication between equipments.

• Management & Information Systems Review
• /
• v.36 no.2
• /
• pp.207-221
• /
• 2017

The career management concept is changing rapidly in the career management field in recent years. It becomes very difficult to have a lifetime employment within the same firm. As there is career interruption that is pervasive phenomenon in the women's career management area, many academics and practitioners have been interested in it. The purpose of this study was to examine the influence of women's career-interruptions as the effective career strategy on career development actors and career success. To test the effects of the proactive career management of career-interrupted women, data were divided into two groups including proactive career management group and general career management group based on whether career-interruptions are voluntary or not. The results showed that the proactive development actors was significantly different depending on women's proactive career management and general career management group. First, proactive-career women were more self-directed to learn and have a significant impact on developing skills through training. Second, the career successes were not significantly different depending on and general career management group.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.31 no.2D
• /
• pp.217-225
• /
• 2011

Currently our country has very serious problems of traffic congestion and urban environment due to increasing automobile ownership. Recently, our concern about environmentally sustainable transportation and green transportation is increasing, so the government is pushing ahead the policy of bicycle using activation. So it is needed to develop a model to analyze the service level of bicycle roads more realistically. In this study, a neuro-fuzzy inference model to analyze the service level of bicycle roads was built selecting the width of bicycle roads, the number of conflicts during cycling and pedestrian volume, which have fuzzy characteristics, as input variables. The predictability of the model was evaluated comparing the surveyed and the estimated. The values of the statistics, $R^2$, MAE and MSE were 0.987, 0.142, 0.032. Therefore, It may be judged that the explainability of the model is very high. The service levels of bicyle roads estimated by the model are 1~3 steps lower than KHCM assessments. The reason may be explained that the model estimates the service level considering the width of bicycle roads and the number of conflicts simultaneously besides pedestrian volume.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.7
• /
• pp.18-25
• /
• 2014

To increase wireless capacity, the concurrent use of multiple wireless interfaces on different frequency bands, called aggregation, can be considered. In this paper, we focus on aggregation of multiple Wi-Fi interfaces with packet-level traffic spreading between the interfaces. Two aggregation schemes, link bonding and multipath TCP (MPTCP), are tested and compared in a dualband Wi-Fi radio system with their Linux implementation. Various test conditions such as traffic types, network delay, locations, interface failures and configuration parameters are considered. Experimental results show that aggregation increases throughput performance significantly over the use of a single interface. Link bonding achieves lower throughput than MPTCP due to duplicate TCP acknowledgements (ACKs) resulting from packet reordering and filtering such duplicate ACKs out is considered as a possible solution. However, link bonding is fast responsive to links' status changes such as a link failure. It is shown that different combinations of interface weights for packet spread in link bonding result in different throughput performance, envisioning a spatio-temporal adaptation of the weights. We also develop a mathematical model of power consumption and compare the power efficiency of the schemes applying different power consumption profiles.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.1
• /
• pp.96-107
• /
• 2015

VANET technologies provide real-time traffic information for mitigating traffic jam and preventing traffic accidents, as well as in-vehicle infotainment service through Telematics/Intelligent Transportation System (ITS). Due to the rapid increasement of various requirements, the vehicle communication with a limited resource and the fixed frame architecture of the conventional techniques is limited to provide an efficient communication service. Therefore, a new flexible operation depending on the surrounding situation information is required that needs an adaptive design of the network architecture and protocol for efficiently predicting, distributing and sharing the context-aware information. In this paper, Vehicle-to-Infrastructure (V2I) based on communication between vehicle and a Road Side Units (RSU) and Vehicle-to-Vehicle (V2V) based on communication between vehicles are effectively combined in a new MAC architecture and V2I and V2V vehicles collaborate in management. As a result, many vehicles and RSU can use more efficiently the resource and send data rapidly. The simulation results show that the proposed method can achieve high resource utilization in accordance. Also we can find out the optimal transmission relay time and 2nd relay vehicle selection probability value to spread out V2V/V2I collaborative schedule message rapidly.

• The KIPS Transactions:PartC
• /
• v.16C no.2
• /
• pp.151-164
• /
• 2009

The importance of sensor networks as a base of ubiquitous computing realization is being highlighted, and espicially the security is recognized as an important research isuue, because of their characteristics.Several efforts are underway to provide security services in sensor networks, but most of them are preventive approaches based on cryptography. However, sensor nodes are extremely vulnerable to capture or key compromise. To ensure the security of the network, it is critical to develop security Intrusion Detection System (IDS) that can survive malicious attacks from "insiders" who have access to keying materials or the full control of some nodes, taking their charateristics into consideration. In this perper, we design a distributed and adaptive IDS architecture on sensor networks, respecting both of energy efficiency and IDS efficiency. Utilizing a modified HEED algorithm, a clustering algorithm, distributed IDS nodes (dIDS) are selected according to node's residual energy and degree. Then the monitoring results of dIDSswith detection codes are transferred to dIDSs in next round, in order to perform consecutive and integrated IDS process and urgent report are sent through high priority messages. With the simulation we show that the superiorities of our architecture in the the efficiency, overhead, and detection capability view, in comparison with a recent existent research, adaptive IDS.

• Journal of KIISE:Computing Practices and Letters
• /
• v.16 no.3
• /
• pp.301-315
• /
• 2010

Recently, competition between companies has intensified and so has the necessity of creating a new business value inventions has increased. A numbers of Business organizations are beginning to realize the importance of business process management. Processes however can often not go the way they were initially designed or non-efficient performance process model could be designed. This can be due to a lack of cooperation and understanding between business analysts and system developers. To solve this problem, business process mining which can be used as the basis of the business process re-engineering has been recognized to an important concept. Current process mining research has only focused their attention on extracting workflow-based process model from competed process logs. Thus there have a limitations in expressing various forms of business processes. The disadvantage in this method is process discovering time and log scanning time in itself take a considerable amount of time. This is due to the re-scanning of the process logs with each new update. In this paper, we will presents a modified FP-Tree algorithm for FP-Tree based business processes, which are used for association analysis in data mining. Our modified algorithm supports the discovery of the appropriate level of process model according to the user's need without re-scanning the entire process logs during updated.

• Journal of Korean Society of Transportation
• /
• v.27 no.5
• /
• pp.97-111
• /
• 2009

Image-based traffic information collection systems have entered widespread adoption and use in many countries since these systems are not only capable of replacing existing loop-based detectors which have limitations in management and administration, but are also capable of providing and managing a wide variety of traffic related information. In addition, these systems are expanding rapidly in terms of purpose and scope of use. Currently, the utilization of image processing technology in the field of traffic accident management is limited to installing surveillance cameras on locations where traffic accidents are expected to occur and digitalizing of recorded data. Accurately recording the sequence of situations around a traffic accident in a signal intersection and then objectively and clearly analyzing how such accident occurred is more urgent and important than anything else in resolving a traffic accident. Therefore, in this research, we intend to present a technology capable of overcoming problems in which advanced existing technologies exhibited limitations in handling real-time due to large data capacity such as object separation of vehicles and tracking, which pose difficulties due to environmental diversities and changes at a signal intersection with complex traffic situations, as pointed out by many past researches while presenting and implementing an active and environmentally adaptive methodology capable of effectively reducing false detection situations which frequently occur even with the Gaussian complex model analytical method which has been considered the best among well-known environmental obstacle reduction methods. To prove that the technology developed by this research has performance advantage over existing automatic traffic accident recording systems, a test was performed by entering image data from an actually operating crossroad online in real-time. The test results were compared with the performance of other existing technologies.