• Journal of KIISE:Information Networking
• /
• v.30 no.2
• /
• pp.179-188
• /
• 2003

Advances in wireless networking technology has engendered a new paradigm of computing, called mobile computing, in which users carrying portable devices have access to a shared infrastructure independent of their physical locations. Wireless communication has some restraints such as disconnection, low bandwidth, a variation of available bandwidth, network heterogeneity, security risk, small storage, and low power. Power adaptation routing scheme overcome the shortage of power by adjusting the output power, was proposed. Existing power saving routing algorithm has some minor effect such as seceding from shortest path to minimize the power consumption, and number of nodes that Participate in routing than optimal because it select a next node with considering only consuming power. This paper supplements the weak point in the existing power saving routing algorithm as considering the gradual approach to final destination and the number of optimal nodes that participate in routing.

• Journal of KIISE:Computer Systems and Theory
• /
• v.34 no.5_6
• /
• pp.238-248
• /
• 2007

As the demand of employing various PC software on mobile embedded devices which have limited storages has been increased, software streaming services are needed. However it takes too much time to launch software on them because it is transferred through wireless networks. To address this problem, prefetch algorithms are needed. We examined 'Last successor (LS)' algorithm and PPM-based prefetch algorithm as prefetch algorithms for software streaming services. We present 'Probability-base Multi Successor (PMS)' algorithm which is contrived through analyzing evaluations of previous algorithms and characteristics of software streaming services. While LS has one successor per each block, PMS has N successors based on probability which is calculated by PPM-based prefetch algorithm. The hit rate of PMS is similar to that of PPM-base prefetch algorithm and the space overhead is similar to that of LS. We can get good efficiency at the point of memory usage when PMS is applied to software streaming services.

• Tunnel and Underground Space
• /
• v.25 no.4
• /
• pp.373-382
• /
• 2015

This study presents a method to calculate carbon dioxide emissions of diesel vehicles operated in an underground mine using Geographic Information Systems (GIS). An underground limestone mine in Korea was selected as the study area. A GIS database was constructed to represent the haulage roads as a 3D vector network. The speed of dump trucks at each haulage road was investigated to determine the carbon dioxide emission factor. The amount of carbon dioxide emissions related to the truck's haulage work could be calculated by considering the carbon dioxide emission factor at each haulage road and the haulage distance determined by GIS-based optimal route analysis. Because diesel vehicles are widely utilized in the mining industry, the method proposed in this study can be used and further improved to calculate the amount of carbon dioxide emissions in mining sites.

• Journal of Korean Society of Transportation
• /
• v.26 no.2
• /
• pp.135-145
• /
• 2008

As a fundamental input to the travel demand forecasting, OD has been always a concern in obtaining the accurate link traffic volume. Numerous methods were applied thus far without a complete success. Some existing OD estimation techniques generally extract regular samples and expand those sample into population. These methods, however, leaves some to be desired in terms of accuracy. To complement such problems, research on estimating OD using additional information such as link traffic volume as well as sample link use rate have been accomplished. In this paper, a new approach for estimating static origin-destination (OD) using probe vehicle has been proposed. More specifically, this paper tried to search an effective sample rate which varies over time and space. In a sample test network study, the traffic volume error rate of each link was set as objective function in solving the problem. As a key result the MAE (mean absolute error) between expanded OD and actual OD was identified as about 5.28%. The developed methodology could be applied with similar cases. Some limitations and future research agenda have also been discussed.

• Journal of Advanced Navigation Technology
• /
• v.13 no.2
• /
• pp.238-243
• /
• 2009

Now, the production process systems are largely based on automatic system using the wired network. The production process systems using wired network has disadvantage that it is expensive when the installed and replaced equipment. The each equipment happens to repair cost for control and management in production processes. And the replaced equipment has also the additional expense and breaks production process. These problems are solved through wireless communication between the industrial equipments. So, we propose wireless production process system based on IEEE 802.15.4 technology. It solves a complicated space and stops by replaced equipment in the factory. Then we simulated and analyzed IEEE 802.15.4 for Industrial Equipment based on Wireless Network.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.12 no.1
• /
• pp.351-356
• /
• 2011

In this paper, we design a pet location tracking and remote monitoring system that uses ultrasonic, temperature, humidity and illumination sensors to study behavioral patterns and habits. Using ultrasonic waves to calculate distances, a WSN(Wireless Sensor Network) was constructed to transmit data at pet's location, such as temperature, humidity and illumination, to a sink mote. Data received by the system are stored in the database in real time to trace pet's location. Interference among transmitting motes was eliminated by sequentially transmitting RF beacons using sink mote's beacon as the reference signal. Experiments were performed with the laboratory prototype of a pet animal monitoring system implemented for this study. The system analyzes locations of a pet and displays movement patterns, areas of movement, temperature, humidity and illumination using a GUI (graphical user interface).

• Journal of KIISE:Information Networking
• /
• v.37 no.2
• /
• pp.142-149
• /
• 2010

In this paper, we propose to modify the IEEE 802.16 MAC protocol in order to allow the coexistence of IEEE 802.11 and IEEE 802.16 wireless networks in shared bands. Our suggested protocol enables 802.16 WMAN to control WLAN devices for the coexistence. That is, in the downlink subframes(BS to SS), SS(Subscriber Station) prohibits WLAN to transmit by using CTS(Clear to Send) in order to protect it's burst. In the uplink subframes(SS to BS), on the other hand, BS(Base Station) sends CTS to block WLAN's communications. Our proposals enables the coexistence between WLAN and WMAN, and simulation results show that our protocols enhance the throughput of the entire system.

• Tunnel and Underground Space
• /
• v.13 no.6
• /
• pp.434-443
• /
• 2003

In this study, it was purposed to develop the new method for the prediction of pollutant concentration in road tunnels. The new method was the use of artificial neural network with the back-propagation algorithm which can model the non-linear system of tunnel environment. This network system was separated into two parts as the visibility and the CO concentration. For this study, data was collected from two highway road tunnels on Yeongdong Expressway. The tunnels have two lanes with one-way direction and adopt the longitudinal ventilation system. The actually measured data from the tunnels was used to develop the neural network system for the prediction of pollutant concentration. The output results from the newly developed neural network system were analysed and compared with the calculated values by PIARC method. Results showed that the prediction accuracy by the neural network system was approximately five times better than the one by PIARC method. In addition, the system predicted much more accurately at the situation where the drivers have to be stayed for a while in tunnels caused by the low velocity of vehicles.

• Journal of the Economic Geographical Society of Korea
• /
• v.9 no.3
• /
• pp.273-296
• /
• 2006

The purpose of this paper is to investigate the formation and characteristics of Gwangju photonics agglomeration as a new agglomeration with a new industry. Data used in this study are locally investigatedfirm related data and the result of questionnaire surveys. Major findings are as follows. First, in the viewpoint of policy, national government suggested the whole policy frameworks and financial support for the strategic industrial development. Regional government picked up and fostered the strategic industry. The initial support of the national government and role of regional government triggered the initial development of the agglomeration. Second, in the spatial perspective, Gwangju photonics agglomeration is based on the externalities of knowledge and technology as well as the input-output network within value chains of production. There is a possibility that Gwangju photonics agglomeration will be developed as an innovation cluster of knowledge-based economy in the future beyond a mere production base of photonics.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.26 no.3
• /
• pp.233-238
• /
• 2016

In this paper, we propose the algorithms of processing the uncertainty data using data fusion for the next generation intrusion detection. In the next generation intrusion detection, a lot of data are collected by many of network sensors to discover knowledge from generating information in cyber space. It is necessary the data fusion process to extract knowledge from collected sensors data. In this paper, we have proposed method to represent the uncertainty data, by classifying where is a confidence interval in interval of uncertainty data through feature analysis of different data using inference method with Dempster-Shafer Evidence Theory. In this paper, we have implemented a detection experiment that is classified by the confidence interval using IRIS plant Data Set for anomaly detection of uncertainty data. As a result, we found that it is possible to classify data by confidence interval.