• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.63 no.2
• /
• pp.81-88
• /
• 2014

In this paper, an implementation of concurrent backoff delay process on a single chip with IEEE 802.15.4 hardware and 8051 processor core that can be used for analyzing the interference on IEEE 802.15.4 channels due to WiFi traffics is studied. The backoff delay process of IEEE 802.15.4 CSMA-CA algorithm is explained. The characteristics of random number generator, timer, and CCA register included in the single chip are described with their control procedure in order to implement the process. A concurrent backoff delay process to evaluate multiple IEEE 802.15.4 channels is proposed, and a method to service the associated tasks at sequentially ordered backoff delay events occurring on the channels is explained. For the implementation of the concurrent backoff delay process on a single chip IEEE 802.15.4 hardware, the elements for the single channel backoff delay process and their control procedure are used to be extended to multiple channels with little modification. The medium access delay on each channel, which is available after execution of the concurrent backoff delay process, is displayed on the LCD of an IEEE 802.15.4 channel analyzer. The experimental results show that we can easily identify the interference on IEEE 802.15.4 channels caused by WiFi traffics in comparison with the way displaying measured channel powers.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.24 no.9 s.180
• /
• pp.2361-2370
• /
• 2000

The introduction of inexpensive cylinder pressure sensors provides new opportunities for precise engine control. This paper presents a control strategy of spark advance based upon cylinder pressure of spark ignition engines. A location of peak pressure(LPP) is the major parameter for controlling the spark timing, and also the UP is estimated, using a multi-layer feedforward neural network, which needs only five pressure sensor output voltage samples at -40˚, -20˚, 0˚, 20˚, 40˚ after top dead center. The neural network plays an important role in mitigating the A/D conversion load of an electronic engine controller by increasing the sampling interval from 10 crank angle(CA) to 20˚ CA. A proposed control algorithm does not need a sensor calibration and pegging(bias calculation) procedure because the neural network estimates the UP from the raw sensor output voltage. The estimated LPP can be regarded as a good index for combustion phasing, and can also be used as an MBT control parameter. The feasibility of this methodology is closely examined through steady and transient engine operations to control individual cylinder spark advance. The experimental results have revealed a favorable agreement of individual cylinder optimal combustion phasing.

• Journal of the Korea Society of Computer and Information
• /
• v.10 no.4 s.36
• /
• pp.249-257
• /
• 2005

A Markov model for the IEEE 802.11 standard which is the most widely deployed wireless LAN protocol, is designed and the channel throughput is evaluated. The DCF of 802.11, which is based on CSMA/CA protocol, coordinates transmissions onto the shared communication channel. In this paper, under a finite load traffic condition and the assumption of packet loss after the final backoff stage. We present an algorithm to find the transmission probability and derive the formula for the channel throughput. The proposed model is validated through simulation and is compared with the case without packet losses.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.18 no.3
• /
• pp.429-436
• /
• 2008

Nowadays fires must be detected rapidly Abstract, and by connecting the detector's distribution, sender, transponder, receiver and others can be connected. Mechanical systems are implemented in today's buildings. However, this kind of constructing method has some disadvantages, that is, if fire happens somewhere, we cannot judge where the fires happen, and it is also difficult to judge what extent the fires reach. In order to overcome the disadvantages, in this paper, according to the tendency of combining the Ubiquitous and Intelligent Network, we propose a type of system by using the method of comparing the differences of the existed systems. The proposed system is designed to perceive the fires rapidly and confirm the fire place and fire scale correctly.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.12 no.3
• /
• pp.87-94
• /
• 2002

This study presents an MSB(Most Significant Bit) Int multiplier using cellular automata, along with a new MSB first multiplication algorithm over GF($2^m$). The proposed architecture has the advantage of high regularity and a reduced latency based on combining the characteristics of a PBCA(Periodic Boundary Cellular Automata) and with the property of irreducible AOP(All One Polynomial). The proposed multiplier can be used in the effectual hardware design of exponentiation architecture for public-key cryptosystem.

• Journal of Ecology and Environment
• /
• v.31 no.3
• /
• pp.233-241
• /
• 2008

Functional feeding groups (FFGs) of benthic macroinvertebrates are guilds of invertebrate taxa that obtain food in similar ways, regardless of their taxonomic affinities. They can represent a heterogeneous assemblage of benthic fauna and may indicate disturbances of their habitats. The proportion of different groups can change in response to disturbances that affect the food base of the system, thereby offering a means of assessing disruption of ecosystem functioning. In this study, we used benthic macroinvertebrate communities collected at 650 sites of 23 different water types in the province of Overijssel, The Netherlands. Physical and chemical environmental factors were measured at each sampling site. Each taxon was assigned to its corresponding FFG based on its food resources. A multilayer perceptron (MLP) using a backpropagation algorithm, a supervised artificial neural network, was applied to evaluate the influence of environmental variables to the FFGs of benthic macroinvertebrates through a sensitivity analysis. In the evaluation of input variables, the sensitivity analysis with partial derivatives demonstrates the relative importance of influential environmental variables on the FFG, showing that different variables influence the FFG in various ways. Collector-filterers and shredders were mainly influenced by $Ca^{2+}$ and width of the streams, and scrapers were influenced mostly with $Ca^{2+}$ and depth, and predators were by depth and pH. $Ca^{2+}$ and depth displayed relatively high influence on all four FFGs, while some variables such as pH, %gravel, %silt, and %bank affected specific groups. This approach can help to characterize community structure and to ecologically assess target ecosystems.

• Journal of Environmental Health Sciences
• /
• v.41 no.2
• /
• pp.90-101
• /
• 2015

Objective: This study was conducted to develop a chemical oxygen demand (COD) regression model using water quality monitoring data (January, 2014) obtained from the Han River auto-monitoring stations. Methods: Surface water quality data at 198 sampling stations along the six major areas were assembled and analyzed to determine the spatial distribution and clustering of monitoring stations based on 18 WQPs and regression modeling using selected parameters. Statistical techniques, including combined genetic algorithm-multiple linear regression (GA-MLR), cluster analysis (CA) and principal component analysis (PCA) were used to build a COD model using water quality data. Results: A best GA-MLR model facilitated computing the WQPs for a 5-descriptor COD model with satisfactory statistical results ($r^2=92.64$,$Q{^2}_{LOO}=91.45$,$Q{^2}_{Ext}=88.17$). This approach includes variable selection of the WQPs in order to find the most important factors affecting water quality. Additionally, ordination techniques like PCA and CA were used to classify monitoring stations. The biplot based on the first two principal components (PCs) of the PCA model identified three distinct groups of stations, but also differs with respect to the correlation with WQPs, which enables better interpretation of the water quality characteristics at particular stations as of January 2014. Conclusion: This data analysis procedure appears to provide an efficient means of modelling water quality by interpreting and defining its most essential variables, such as TOC and BOD. The water parameters selected in a COD model as most important in contributing to environmental health and water pollution can be utilized for the application of water quality management strategies. At present, the river is under threat of anthropogenic disturbances during festival periods, especially at upstream areas.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.10 no.2
• /
• pp.1-8
• /
• 2011

Traffic congestion is a source of significant economic and social costs in urban areas. Intelligent Transportation Systems (ITS) are a promising means to help alleviate congestion by utilizing advanced sensing, computing, and communication technologies. This paper proposes and investigates a basic and advanced ITS framework Advanced Traveler Information System (ATIS) using wireless Vehicle to Roadside (Centralized ATIS model: CA model) and Vehicle to Vehicle (DeCentralized ATIS model: DCA model) communication and assuming an ideal communication environment in the typical $6{\times}6$ urban grid traffic network. Results of this study indicate that an ATIS using wireless communication can save travel time given varying combinations of system characteristics: traffic flow, communication radio range, and penetration ratio. Also, all tested metrics of the CA and DCA models indicate that the system performance of both models is almost identical regardless of varying traffic demand and penetration ratios. Therefore, DCA model can be a reasonable alternative to the fixed infrastructure based ATIS model (CA model).

• Journal of Korea Spatial Information System Society
• /
• v.12 no.1
• /
• pp.76-84
• /
• 2010

Many pedestrian simulation models for micro-scale spaces as building indoor areas have been proposed for the last decade and two models - social force model and floor field model - are getting attention. Among these, CA-based floor field model is viewed more favourable for computer simulations than computationally complex social force model. However, Kirchner's floor field model has limitations in capturing the differences in dynamic values of different agents and this study proposes an enhanced algorithm. This study improved the floor field model in order for an agent to be able to exclude the influences of its own dynamic values by changing the data structure, and, also modified the initial dynamic value problem in order to fit more realistic environment. In the simulations, real 3D building data stored in a spatial DBMS were used considering future integration with indoor localization sensors and real time applications.

• Spatial Information Research
• /
• v.16 no.2
• /
• pp.157-171
• /
• 2008

With emerging technologies on wireless networks and mobile computing environment, a number of researches have been carried out for ubiquitous computing. An important functional requirement of ubiquitous computing is to handle location data with ease. With the increase of accidents in large complex buildings. move attention is being paid to indoor spaces and evacuation. However, most currently used evacuation-related applications are simulation based on hypothetical data. Also, since they use non-georeferenced CAD data, it is not easy to integrate them with indoor positioning devices. With the recent progress of indoor positioning systems, the simulators can be enhanced to real-time evacuation systems. As a preliminary stage to make such systems possible, this study proposes using a georeferenced data and evacuation simulation. This study used GIS data and Cellular Automata theory an the algorithm for the movement of the evacuee.