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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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Journal of Biosystems Engineering
Journal Basic Information
Journal DOI :
Korean Society for Agricultural Machinery
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Volume & Issues
Volume 38, Issue 4 - Dec 2013
Volume 38, Issue 3 - Sep 2013
Volume 38, Issue 2 - Jun 2013
Volume 38, Issue 1 - Mar 2013
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Development of a Path Generation and Tracking Algorithm for a Korean Auto-guidance Tillage Tractor
Han, Xiong-Zhe ; Kim, Hak-Jin ; Moon, Hee-Chang ; Woo, Hoon-Je ; Kim, Jung-Hun ; Kim, Young-Joo ;
Journal of Biosystems Engineering, volume 38, issue 1, 2013, Pages 1~8
DOI : 10.5307/JBE.2013.38.1.001
Purpose: Path planning and tracking algorithms applicable to various agricultural operations, such as tillage, planting, and spraying, are needed to generate steering angles for auto-guidance tractors to track a point ahead on the path. An optimal coverage path algorithm can enable a vehicle to effectively travel across a field by following a sequence of parallel paths with fixed spacing. This study proposes a path generation and tracking algorithm for an auto-guided Korean tractor with a tillage implement that generates a path with C-type turns and follows the generated path in a paddy field. A mathematical model was developed to generate a waypoint path for a tractor in a field. This waypoint path generation model was based on minimum tractor turning radius, waypoint intervals and LBOs (Limit of Boundary Offsets). At each location, the steering angle was calculated by comparing the waypoint angle and heading angle of the tractor. A path following program was developed with Labview-CVI to automatically read the waypoints and generate steering angles for the tractor to proceed to the next waypoint. A feasibility test of the developed program for real-time path tracking was performed with a mobile platform traveling on flat ground. The test results showed that the developed algorithm generated the desired path and steering angles with acceptable accuracy.
Forecasting Demand of Agricultural Tractor, Riding Type Rice Transplanter and Combine Harvester by using an ARIMA Model
Kim, Byounggap ; Shin, Seung-Yeoub ; Kim, Yu Yong ; Yum, Sunghyun ; Kim, Jinoh ;
Journal of Biosystems Engineering, volume 38, issue 1, 2013, Pages 9~17
DOI : 10.5307/JBE.2013.38.1.009
Purpose: The goal of this study was to develop a methodology for the demand forecast of tractor, riding type rice transplanter and combine harvester using an ARIMA (autoregressive integrated moving average) model, one of time series analysis methods, and to forecast their demands from 2012 to 2021 in South Korea. Methods: To forecast the demands of three kinds of machines, ARIMA models were constructed by following three stages; identification, estimation and diagnose. Time series used were supply and stock of each machine and the analysis tool was SAS 9.2 for Windows XP. Results: Six final models, supply based ones and stock based ones for each machine, were constructed from 32 tentative models identified by examining the ACF (autocorrelation function) plots and the PACF (partial autocorrelation function) plots. All demand series forecasted by the final models showed increasing trends and fluctuations with two-year period. Conclusions: Some forecast results of this study are not applicable immediately due to periodic fluctuation and large variation. However, it can be advanced by incorporating treatment of outliers or combining with another forecast methods.
Combine Harvest Scheduling Program for Rough Rice using Max-coverage Algorithm
Lee, Hyo-Jai ; Kim, Oui-Woung ; Kim, Hoon ; Han, Jae-Woong ;
Journal of Biosystems Engineering, volume 38, issue 1, 2013, Pages 18~24
DOI : 10.5307/JBE.2013.38.1.018
Purpose: This study was conducted to develop an optimal combine scheduling program using Max-Coverage algorithm which derives the maximum efficiency for a specific location in harvest seasons. Methods: The combine scheduling program was operated with information about combine specification and farmland. Four operating types (Max-Coverage algorithm type, Boustrophedon path type, max quality value type, and max area type) were selected to compare quality and working capacity. Result: The working time of Max-Coverage algorithm type was shorter than others, and the total quality value of Max-Coverage algorithm and max quality value type were higher than others. Conclusion: The developed combine scheduling program using Max-Coverage algorithm will provide optimal operation and maximum quality in a limited area and time.
Development of an Agricultural Data Middleware to Integrate Multiple Sensor Networks for an Farm Environment Monitoring System
Kim, Joonyong ; Lee, Chungu ; Kwon, Tae-Hyung ; Park, Geonhwan ; Rhee, Joong-Yong ;
Journal of Biosystems Engineering, volume 38, issue 1, 2013, Pages 25~32
DOI : 10.5307/JBE.2013.38.1.025
Purpose: The objective of this study is to develop a data middleware for u-IT convergence in agricultural environment monitoring, which can support non-standard data interfaces and solve the compatibility problems of heterogenous sensor networks. Methods: Six factors with three different interfaces were chosen as target data among the environmental monitoring factors for crop cultivation. PostgresSQL and PostGIS were used for database and the data middleware was implemented by Python programming language. Based on hierarchical model design and key-value type table design, the data middleware was developed. For evaluation, 2,000 records of each data access interface were prepared. Results: Their execution times of File I/O interface, SQL interface and HTTP interface were 0.00951 s/record, 0.01967 s/record and 0.0401 s/record respectively. And there was no data loss. Conclusions: The data middleware integrated three heterogenous sensor networks with different data access interfaces.
A Comparison of the Effects of Worker-Related Variables on Process Efficiency in a Manufacturing System Simulation
Lee, Dongjune ; Park, Hyunjoon ; Choi, Ahnryul ; Mun, Joung H. ;
Journal of Biosystems Engineering, volume 38, issue 1, 2013, Pages 33~40
DOI : 10.5307/JBE.2013.38.1.033
Purpose: The goal of this study was to build an accurate digital factory that evaluates the performance of a factory using computer simulation. To achieve this goal, we evaluated the effect of worker-related variables on production in a simulation model using comparative analysis of two cases. Methods: The overall work process and worker-related variables were determined and used to build a simulation model. Siemens PLM Software's Plant Simulation was used to build a simulation model. Also, two simulation models were built, where the only difference was the use of the worker-related variable, and the total daily production analyzed and compared in terms of the individual process. Additionally, worker efficiency was evaluated based on worker analysis. Results: When the daily production of the two models were compared, a 0.16% error rate was observed for the model where the worker-related variables were applied and error rate was approximately 5.35% for the model where the worker-related variables were not applied. In addition, the production in the individual processes showed lower error rate in the model that included the worker-related variables than the model where the worker-related variables were not used. Also, among the total of 22 workers, only three workers satisfied the IFRS (International Financial Reporting Standards) suggested worker capacity rate (90%). Conclusions: In the daily total production and individual process production, the model that included the worker-related variables produced results that were closer to the real production values. This result indicates the importance of worker elements as input variables, in regards to building accurate simulation models. Also, as suggested in this study, the model that included the worker-related variables can be utilized to analyze in more detail actual production. The results from this study are expected to be utilized to improve the work process and worker efficiency.
A Study for the Use of Solar Energy for Agricultural Industry - Solar Drying System Using Evacuated Tubular Solar Collector and Auxiliary Heater -
Lee, Gwi Hyun ;
Journal of Biosystems Engineering, volume 38, issue 1, 2013, Pages 41~47
DOI : 10.5307/JBE.2013.38.1.041
Purpose: The objectives of this study were to construct the solar drying system with evacuated tubular solar collector and to investigate its performance in comparison with indoor and outdoor dryings. Methods: Solar drying system was constructed with using CPC (compound parabolic concentrator) evacuated tubular solar collector. Solar drying system is mainly composed of evacuated tubular solar collector with CPC reflector, storage tank, water-to-air heat exchanger, auxiliary heater, and drying chamber. Performance test of solar drying system was conducted with drying of agricultural products such as sliced radish, potato, carrot, and oyster mushroom. Drying characteristics of agricultural products in solar drying system were compared with those of indoor and outdoor ones. Results: Solar drying system showed considerable effect on reducing the half drying time for all drying samples. However, outdoor drying was more effective than indoor drying on shortening the half drying time for all of drying samples. Solar drying system and outdoor drying for oyster mushroom showed the same half drying time. Conclusions: Oyster mushroom could be dried easily under outdoor drying until MR (Moisture Ratio) was reached to about 0.2. However, solar drying system showed great effect on drying for most samples compared with indoor and outdoor dryings, when MR was less than 0.5.
Applications of Discrete Wavelet Analysis for Predicting Internal Quality of Cherry Tomatoes using VIS/NIR Spectroscopy
Kim, Ghiseok ; Kim, Dae-Yong ; Kim, Geon Hee ; Cho, Byoung-Kwan ;
Journal of Biosystems Engineering, volume 38, issue 1, 2013, Pages 48~54
DOI : 10.5307/JBE.2013.38.1.048
Purpose: This study evaluated the feasibility of using a discrete wavelet transform (DWT) method as a preprocessing tool for visible/near-infrared spectroscopy (VIS/NIRS) with a spectroscopic transmittance dataset for predicting the internal quality of cherry tomatoes. Methods: VIS/NIRS was used to acquire transmittance spectrum data, to which a DWT was applied to generate new variables in the wavelet domain, which replaced the original spectral signal for subsequent partial least squares (PLS) regression analysis and prediction modeling. The DWT concept and its importance are described with emphasis on the properties that make the DWT a suitable transform for analyzing spectroscopic data. Results: The
values and root mean squared errors (RMSEs) of calibration and prediction models for the firmness, sugar content, and titratable acidity of cherry tomatoes obtained by applying the DWT to a PLS regression with a set of spectra showed more enhanced results than those of each model obtained from raw data and mean normalization preprocessing through PLS regression. Conclusions: The developed DWT-incorporated PLS models using the db5 wavelet base and selected approximation coefficients indicate their feasibility as good preprocessing tools by improving the prediction of firmness and titratable acidity for cherry tomatoes with respect to
values and RMSEs.
Cell Image Processing Methods for Automatic Cell Pattern Recognition and Morphological Analysis of Mesenchymal Stem Cells - An Algorithm for Cell Classification and Adaptive Brightness Correction -
Lim, Kitaek ; Park, Soo Hyun ; Kim, Jangho ; SeonWoo, Hoon ; Choung, Pill-Hoon ; Chung, Jong Hoon ;
Journal of Biosystems Engineering, volume 38, issue 1, 2013, Pages 55~63
DOI : 10.5307/JBE.2013.38.1.055
Purpose: The present study aimed at image processing methods for automatic cell pattern recognition and morphological analysis for tissue engineering applications. The primary aim was to ascertain the novel algorithm of adaptive brightness correction from microscopic images for use as a potential image analysis. Methods: General microscopic image of cells has a minor problem which the central area is brighter than edge-area because of the light source. This may affect serious problems to threshold process for cell-number counting or cell pattern recognition. In order to compensate the problem, we processed to find the central point of brightness and give less weight-value as the distance to centroid. Results: The results presented that microscopic images through the brightness correction were performed clearer than those without brightness compensation. And the classification of mixed cells was performed as well, which is expected to be completed with pattern recognition later. Beside each detection ratio of hBMSCs and HeLa cells was 95% and 92%, respectively. Conclusions: Using this novel algorithm of adaptive brightness correction could control the easier approach to cell pattern recognition and counting cell numbers.
Prediction of Cobb-angle for Monitoring System in Adolescent Girls with Idiopathic Scoliosis using Multiple Regression Analysis
Seo, Eun Ji ; Choi, Ahnryul ; Oh, Seung Eel ; Park, Hyun Joon ; Lee, Dong Jun ; Mun, Joung H. ;
Journal of Biosystems Engineering, volume 38, issue 1, 2013, Pages 64~71
DOI : 10.5307/JBE.2013.38.1.064
Purpose: The purpose of this study was to select standing posture parameters that have a significant difference according to the severity of spinal deformity, and to develop a novel Cobb angle prediction model for adolescent girls with idiopathic scoliosis. Methods: Five normal adolescents girls with no history of musculoskeletal disorders, 13 mild scoliosis patients (Cobb angle:
), and 14 severe scoliosis patients (Cobb angle:
) participated in this study. Six infrared cameras (VICON) were used to acquire data and 35 standing parameters of scoliosis patients were extracted from previous studies. Using the ANOVA and post-hoc test, parameters that had significant differences were extracted. In addition, these standing posture parameters were utilized to develop a Cobb-angle prediction model through multiple regression analysis. Results: Twenty two of the parameters showed differences between at least two of the three groups and these parameters were used to develop the multi-linear regression model. This model showed a good agreement (
= 0.92) between the predicted and the measured Cobb angle. Also, a blind study was performed using 5 random datasets that had not been used in the model and the errors were approximately
. Conclusions: In this study, we demonstrated the possibility of clinically predicting the Cobb angle using a non-invasive technique. Also, monitoring changes in patients with a progressive disease, such as scoliosis, will make possible to have determine the appropriate treatment and rehabilitation strategies without the need for radiation exposure.