• Agricultural and Biosystems Engineering
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• v.6 no.1
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• pp.8-14
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• 2005

This study was carried out to develop a real-time grouping system of chlorophyll contents of rice crop canopy for precision agriculture. The system measured reflected light energy of a rice canopy on a paddy field from visual to near-infrared range and analyzed the collected information of chlorophyll contents of rice crop canopy with given position data. The four filters, 560 nm $({\pm}10nm)$, 650 nm $({\pm}25nm)$, 700 nm $({\pm}12nm)$, and 850 nm $({\pm}40nm)$, were used for a multiple regression to estimate the chlorophyll contents of rice crop canopy. Every $0.2m^2$ area of the open field was inspected at a distance of 1 m above the rice canopy. According to the results of verification test, the chlorophyll content grouping by a commerical chlorophyll meter (SPAD) and by the developed system showed 58.7% match for five-stage chlorophyll contents of rice crop canopy grouping and 93.5% for the $five{\pm}1-stage$ grouping. In addition, the results showed 63.0% match for three-stage grouping and 100.0% for the $three{\pm}1-stage$ grouping.

• Agricultural and Biosystems Engineering
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• v.6 no.1
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• pp.15-21
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• 2005

This study was conducted to develop a nondestructive grouping system for soil organic matter using visible (VIS) and near infrared (NIR) spectroscopic method. The artificial light was irradiated on the cut soil surface at 15 to 20 cm depths to reduce the errors of light at open field. The reflectance energy from the cut soil surface was measured to group the soil organic matter using VIS/NIR light sensor with narrow band pass filter. From reflectance spectra of soil samples, the sensitive wavelengths for measuring the soil organic matter were selected and compared to previous research results. The grouping system for soil organic matter consisted of light sensor with band pass filter measuring the reflectance energy of the cut soil surface, global positing system (GPS), analog-to-digital (AD) converter, computer and operating software. The regression models to predict the soil organic matter were developed and evaluated. From field test, the accuracies of the developed light sensor system were 81.3% for five-stage grouping of the soil organic matters and 91.0% for three-stages grouping of the soil organic matters, respectively. It could be possible to support the decision making for variable rate applications with the developed grouping system for soil organic matter in precision agriculture.

• IE interfaces
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• v.9 no.2
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• pp.39-45
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• 1996

This paper investigates the problems of grouping N products on an assembly line with an objective of maximizing the option grouping rate. Before developing a mixed model grouping algorithm, simulation studies are committed for developing operating rules and evaluating the layout production systems. A mixed model grouping algorithm is suggested and it is applied to the color selection lane in automobile production system, which reveals a high mixed model grouping rate.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.2A
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• pp.147-154
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• 2009

Antenna grouping algorithm is hybrid of beamforming and spatial multiplexing. In antenna grouping system, we partition $N_t$ transmit antennas into $N_r$ groups and use beamforming in a group, spatial multiplexing between groups. We can transmit $N_r$ data streams in the $N_t{\times}N_r$ antenna grouping system. With antenna grouping, we can achieve diversity gain through beamforming, and high spectral efficiency through spatial multiplexing. But if channel is ill-conditioned or there are some correlations between antennas, the performance of antenna grouping is seriously degraded and in that case, beamforming is the best transmit strategy. By selecting the antenna grouping mode when channel is well-conditioned and by selecting the beamforming mode when channel is ill-conditioned, we can prevent serious fluctuation of BER performance caused by varying channel condition and achieve the best BER performance. In this paper, we investigate mode selection algorithm which can select antenna grouping mode or beamforming mode. we also propose a simple mode selection criterion.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.8A
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• pp.794-804
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• 2008

In this paper, we analyze the performance of probabilistic slotted anti-collision algorithm used in EPCglobal Class-1 Generation-2 (Gen2). To increase throughput and system efficiency, and to decrease tag identification time and collision ratio, we propose new tag anti-collision algorithms, which are FAFQ (fired adjustable flamed Q) algorithm and AAFQ (adaptive adjustable framed Q) algorithm, by using QueryAdjust command. We also propose grouping method based on Gen2 to improve the efficiency of tag identification. The simulation results show that all the proposed algorithms outperform Q algorithm, and AAFQ algorithm performs the best. That is, AAFQ has an increment of 5% of system efficiency and a decrement of 4.5% of collision ratio. For FAFQ and AAFQ algorithm, the performance of grouping method is similar to that of ungrouping method. However, for Q algorithm in Gen2, grouping method can increase throughput and system efficiency, and decrease tag identification time and collision ratio compared with ungrouping method.

• Journal of The Korean Association of Information Education
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• v.14 no.3
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• pp.291-300
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• 2010

Group-based learning is known to be an effective means to improve scholastic achievement in online learning. Therefore, there are some previous researches for the group-based learning. A lot of previous researches define factors for grouping from the characteristics of classes, teacher's decision and students' preferences and then generate a group based on the defined factors. However, many algorithms proposed by previous researches depend on a specific class and is not a general approach since there exist several differences in terms of the need of courses, learners, and teachers. Moreover it is hard to find a automatic system for group generation. This paper proposes a grouping system which automatically generate a learner group according to characteristics of various classes. the proposed system automatically generates a learner group by using basic information for a class or additional factors inputted from a user. The proposed system defines a set of rules for learner grouping which enables automatic selection of a learner grouping algorithm tailored to the characteristics of a given class. This rule based approach allows the proposed system to accommodate various learner grouping algorithms for a later use. Also we show the usability of our system by serviceability evaluation.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.37
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• pp.1-7
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• 1996

The grouping of parts into families and machines into cells poses an important problem for the improvement of productivity and quality in the design and planning of the flexible manufacturing system(FMS). This paper proposes a new algorithm of forming machine-part groups in case of the bottleneck machine problem and shows the numerical example. This algorithm could be applied to the large scale machine-part grouping problem.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.34
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• pp.123-128
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• 1995

The grouping of parts into families and machines into cells poses an important problem in the design and planning of the flexible manufacturing system(FMS). This paper proposes a new optimal algorithm of forming machine-part groups to maximize the similarity, based on branching from seed machine and bounding on a completed part. This algorithm is illustrated with numerical example. This algorithm could be applied to the generalized machine-part grouping problem.

• The Journal of Korean Association of Computer Education
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• v.8 no.4
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• pp.15-24
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• 2005

The success of cooperative learning in small groups heavily depends on how the small groups are set up. When small groups are formed, the factors such as the objectives and characteristics of the work and the capabilities and interests of the group members should be considered to maximize the interaction among the group members. However, it is not easy for teachers to manually divide their class to small groups to satisfy such conditions. In this work, we developed and implemented a student grouping system that divides the class as appropriate as possible, when given multidimensional student data and a set of conditions for forming small groups. The grouping conditions can be heterogeneous, homogeneous, and both. The grouping system can easily be used by teachers since the system can be accessed by clicking a menu button embedded into Microsoft Excel. The system has also a wide range of application areas where object grouping by various conditions is needed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.9
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• pp.2373-2384
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• 1996

Connection caching technique is widely used to reduce the overhead incurred by frequency connection establishment in distributed computing environment using connection oriented protocol. We present an efficient connection caching scheme where we divide the system into several host groups and connection between the hosts in the same group is kept prior to others. In other words it makes the connection kept longer by sharing the connection use information between hosts in the same group. Every host group consists of hosts which have heavy intercommunication. And we present performance evaluation of the effect of host grouping upon connection caching and performance comparison of various grouping in several aspects includingmeanservice request interarrival time, mean service time, group size, grouping and type of group. Simulation results show that host grouping is effective in evrey performance criterion and proper grouping of hosts enhances the performance. We also present analysis results for Markov process model of our scheme which are consistent with the simulation results.