• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.843-845
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• 2003

Shortest Path Problems are among the most studied network flow optimization problems, with interesting applications in various fields. One such field is the route determination service, where various kinds of shortest path problems need to be solved in location-based service. Our research aim is to propose a route technique in real-time locationbased service (LBS) environments according to user’s route preferences such as shortest, fastest, easiest and so on. Turn costs modeling and computation are important procedures in route planning. There are major two kinds of cost parameters in route planning. One is static cost parameter which can be pre-computed such as distance and number of traffic-lane. The other is dynamic cost parameter which can be computed in run-time such as number of turns and risk of congestion. In this paper, we propose a new cost modeling method for turn costs which are traditionally attached to edges in a graph. Our proposed route determination technique also has an advantage that can provide service interoperability by implementing XML web service for the OpenLS route determination service specification. In addition to, describing the details of our shortest path algorithms, we present a location-based service system by using proposed routing algorithms.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.6
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• pp.1489-1497
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• 2018

Web application services have diversified. At the same time, research on intrusion detection is continuing due to the surge of cyber threats. Also, As a single-defense system evolves into multi-level security, we are responding to specific intrusions by correlating security events that have become vast. However, it is difficult to check the OS, service, web application type and version of the target system in real time, and intrusion detection events occurring in network-based security devices can not confirm vulnerability of the target system and success of the attack A blind spot can occur for threats that are not analyzed for problems and associativity. In this paper, we propose the validation of effectiveness for intrusion detection events using TF-IDF. The proposed scheme extracts the response traffics by mapping the response of the target system corresponding to the attack. Then, Response traffics are divided into lines and weights each line with an TF-IDF weight. we checked the valid intrusion detection events by sequentially examining the lines with high weights.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.4
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• pp.699-708
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• 2021

In this paper, a steering control and speed control algorithm was presented for autonomous driving based on two vision sensors and road speed sign board. A car speed control algorithm was developed to recognize the speed sign by using TensorFlow, a deep learning program provided by Google to the road speed sign image provided from vision sensor B, and then let the car follows the recognized speed. At the same time, a steering angle control algorithm that detects lanes by analyzing road images transmitted from vision sensor A in real time, calculates steering angles, controls the front axle through PWM control, and allows the vehicle to track the lane. To verify the effectiveness of the proposed algorithm's steering and speed control algorithms, a car's prototype based on the Python language, Raspberry Pi and OpenCV was made. In addition, accuracy could be confirmed by verifying various scenarios related to steering and speed control on the test produced track.

• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.63-74
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• 2021

Location-based services (LBSs) are expected to process a large number of spatial queries, such as shortest path and k-nearest neighbor queries that arrive simultaneously at peak periods. Deploying more LBS servers to process these simultaneous spatial queries is a potential solution. However, this significantly increases service operating costs. Recently, batch processing solutions have been proposed to process a set of queries using shareable computation. In this study, we investigate the problem of batch processing moving k-nearest neighbor (MkNN) queries in dynamic spatial networks, where the travel time of each road segment changes frequently based on the traffic conditions. LBS servers based on one-query-at-a-time processing often fail to process simultaneous MkNN queries because of the significant number of redundant computations. We aim to improve the efficiency algorithmically by processing MkNN queries in batches and reusing sharable computations. Extensive evaluation using real-world roadmaps shows the superiority of our solution compared with state-of-the-art methods.

• Journal of the Korea Society of Computer and Information
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• v.27 no.6
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• pp.117-122
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• 2022

In this paper, we developed a vehicle control terminal using IoT and low-power long-distance communication (NB-IoT) technology. This system collects information on the location and status of a parked vehicle, and transmits the vehicle status to the vehicle owner's terminal in real time with low power to prevent vehicle theft, and in the case of a vehicle in motion, When primary information about the vehicle, such as an impact, is collected and transmitted to the server, the server analyzes the relevant data to generate secondary information on traffic congestion, road damage, and safety accidents. By sending it, you can know the exact arrival time of the vehicle at its destination. This terminal device is an IoT gateway for a vehicle and can be connected to various wired and wireless sensors inside the vehicle. In addition, the data collected from vehicle maintenance, efficient operation, and vehicles can be usefully used in the private or public sector.

• Smart Media Journal
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• v.11 no.2
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• pp.70-76
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• 2022

IoT application development using a cloud server causes problems such as data transmission and reception delay, network traffic, and cost for real-time processing support in network connected hardware. To solve this problem, edge cloud-based platforms can use neuromorphic hardware to enable fast data transfer. In this paper, we propose a model optimization method for supporting spiking neural networks on FPGA hardware. We focused on auto-adjusting network model parameters optimized for neuromorphic hardware. The proposed method performs optimization to show higher performance based on user requirements for accuracy. As a result of performance analysis, it satisfies all requirements of accuracy and showed higher performance in terms of expected execution time, unlike the naive method supported by the existing open source framework.

• Journal of Auto-vehicle Safety Association
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• v.15 no.2
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• pp.42-48
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• 2023

In recent years, automated vehicles have garnered attention in the multidisciplinary research field, promising increased safety on the road and new opportunities for passengers. High-Definition (HD) maps have been in development for many years as they offer roadmaps with inch-perfect accuracy and high environmental fidelity, containing precise information about pedestrian crossings, traffic lights/signs, barriers, and more. Demonstrating autonomous driving requires verification of driving on actual roads, but this can be challenging, time-consuming, and costly. To overcome these obstacles, creating HD maps of real roads in a simulation and conducting virtual driving has become an alternative solution. However, existing HD maps using high-precision data are expensive and time-consuming to build, which limits their verification in various environments and on different roads. Thus, it is challenging to demonstrate autonomous driving on anything other than extremely limited roads and environments. In this paper, we propose a new and simple method for implementing HD maps that are more accessible for autonomous driving demonstrations. Our HD map combines the CARLA simulator and OpenStreetMap (OSM) data, which are both open-source, allowing for the creation of HD maps containing high-accuracy road information globally with minimal dependence. Our results show that our easily accessible HD map has an accuracy of 98.28% for longitudinal length on straight roads and 98.42% on curved roads. Moreover, the accuracy for the lateral direction for the road width represented 100% compared to the manual method reflected with the exact road data. The proposed method can contribute to the advancement of autonomous driving and enable its demonstration in diverse environments and on various roads.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.1
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• pp.1-13
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• 2019

With commercial apps popular in EU, MaaS has been emerging around the globe as a new approach to worsening urban traffic problems. In contrast, it is still mainstay in Korea simply discussing the concept and necessities of MaaS, rather than seeking for real-world solutions for the commercialization. The purpose of this research is to analyze the demand-side i1mpacts of travel time and cost changes according to MaaS adoption, and to see its commercial feasibility in Korea. The 2010 KTDB traveler's nationwide OD data is used to estimate the level of fare discount for balancing the mode shift and fare revenue changes followed by MaaS implementation. The analysis results show that MaaS leads to the increase of public transport ridership as a result of the diminishing travel cost and time, and that the time saving works more positively for ridership increase. Also, the optimum level of fare discount is estimated 2.56% without damaging the revenue. This finding reveals that MaaS impact is superior to the other single-sided public transport inventive measures since it can affect both travel cost and time reduction at the same time.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.2
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• pp.36-42
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• 2011

The current healthcare information systems field to meet the growing demand for healthcare for a variety of building systems and operation, and subsequent information on the budget continues to increase, but the current system, although the association link between the various systems made does not, with organizations with information about each of the standardization and real-time network status data do not consist of various materials, such as insufficient to provide real-time issues have been raised. This paper proposes a Integrated information system on Healthcare based on JXTA to solve problems mentioned above. Until now, in a network environment for data storage and management is the most widely used server-intensive structure, while an increase in users and traffic difficulties in data management and communications services to handle the growing number of servers increase faster than information associated with the cost savings, P2P model in terms of efficient data management has emerged as a new solution. Therefore this paper designs a platform for Integrated information system on Healthcare based on JXTA as a method to integrate health information data and services, and then proves that the new information system on healthcare based on JXTA is the suitable model.

• The KIPS Transactions:PartC
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• v.16C no.5
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• pp.661-668
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• 2009

The Extended real-time Polling Service (ErtPS) is proposed tosupport QoS of VoIP service with silence suppression which generates variable size data packets in IEEE 802.16e systems. If the silence is suppressed, VoIP should support Comfort Noise Generation (CNG) which generates comfort noise for receiver's auditory sense to notify the status of connection to the user. CNG mode in silent-period generates a data with lower bit rate at long packet transmission intervals in comparison with talk-spurt. Therefore, if the ErtPS, which is designed to support service flows that generate data packets on a periodic basis, is applied to silent-period, resources of the uplink are used inefficiently. In this paper, we proposed the Improved ErtPS algorithm for efficient resource utilization of the silent-period in VoIP traffic supporting CNG. In the proposed algorithm, the base station allocates bandwidth depending on the status of voice at the appropriate interval by havingthe user inform the changes of voice status. The Improved ErtPS utilizes the Cannel Quality Information Channel (CQICH) which is an uplink subchannel for delivering quality information of channel to the base station on a periodic basis in 802.16e systems. We evaluated the performance of proposed algorithm using OPNET simulator. We validated that proposed algorithm improves the bandwidth utilization of the uplink and packet transmission latency