• Advances in nano research
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• v.15 no.6
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• pp.533-539
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• 2023

This study aims to examine four machine learning (ML)-based models for their potential to estimate the splitting tensile strength (STS) of manufactured sand concrete (MSC). The ML models were trained and tested based on 310 experimental data points. Stone nanopowder content (SNPC), curing age (CA), and water-to-cement (W/C) ratio were also studied for their impacts on the STS of MSC. According to the results, the support vector regression (SVR) model had the highest correlation with experimental data. Still, all of the optimized ML models showed promise in estimating the STS of MSC. Both ML and laboratory results showed that MSC with 10% SNPC improved the STS of MSC.

• Journal of Biosystems Engineering
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• v.33 no.5
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• pp.355-361
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• 2008

As agricultural machinery has become larger and tillage practices have changed in recent decades, compaction as a result of wheel traffic and tillage has caused increasing concern. If strategies to manage compaction, such as deep tillage, could be applied only where needed, economic and environmental benefits would result. For such site-specific compaction management to occur, compacted areas within fields must be efficiently sensed and mapped. We previously developed an on-the-go soil strength profile sensor (SSPS) for this purpose. The SSPS measures within-field variability in soil strength at five soil depths up to 50 cm. Determining the variability structure of SSPS data is needed for site-specific field management since the variability structure determines the required intensity of data collection and is related to the delineation of compaction management zones. In this paper, soil bin data were analyzed by a spectral analysis technique to determine the variability structure of the SSPS data, and to investigate causes and implications of this variability. In the soil bin, we observed a repeating pattern due to soil fracture with an approximate 12- to 19-cm period, especially at the 10-cm depth, possibly due to cyclic development of soil fracture on this interval. These findings will facilitate interpretation of soil strength data and enhance application of the SSPS.

• Journal of Biosystems Engineering
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• v.7 no.1
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• pp.42-52
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• 1982

This study was intended to develop a cost function for the natural air in-bin drying: system which could lead to an optimization of the drying system cost. Based on the cost function developed, a series of simulated drying tests were conducted with 10-year weather data (1970~1979) for 7 different regions by applying an appropriate levels of system factors. System performance factors treated in this study were initial moisture content, airflow rate, bin diameter and grain depth. An optimization procedure to find the least cost system was developed as follows: First, the worst year of the past decade was determined in consideration of the dryiang time and maximum dry matter loss. Second, the minimum airflow rate for a fixed bin diameter and grain depth was determined. Third, the optimum grain depth was found for the minimum airflow rate with different initial moisture contents and bin diameters. The results obtained in this study are summarized as follows: 1. The optimization procedure developed in this study was able to reduce the time and efforts significantly. 2. Optimum values of drying parameters including airflow rate, grain depth, and fan size were determined for different initial moisture contents and bin diameters in each region. The results are shown in Tables 3 to 9. 3. Optimum grain depths decreased as the initial moisture content and airflow rate increased. 4. Drying time for the least cost system should be reduced with higher initial moisture content and lower drying potential to prevent grain spoilage. 5. The fixed cost was 65 to 75 percent of the total system cost and the variable cost was 25 to 35 percent. To reduce the fixed cost it is desirable to use a drying bin 2 or 3 times a year.

• Journal of Information Processing Systems
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• v.12 no.2
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• pp.322-331
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• 2016

Image compression is an essential technique for saving time and storage space for the gigantic amount of data generated by images. This paper introduces an adaptive source-mapping scheme that greatly improves bit-level lossless grayscale image compression. In the proposed mapping scheme, the frequency of occurrence of each symbol in the original image is computed. According to their corresponding frequencies, these symbols are sorted in descending order. Based on this order, each symbol is replaced by an 8-bit weighted fixed-length code. This replacement will generate an equivalent binary source with an increased length of successive identical symbols (0s or 1s). Different experiments using Lempel-Ziv lossless image compression algorithms have been conducted on the generated binary source. Results show that the newly proposed mapping scheme achieves some dramatic improvements in regards to compression ratios.

• Journal of Industrial Technology
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• v.25 no.B
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• pp.157-164
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• 2005

Two methods, the bin averaging method and least square method, are often used in calibrating wind turbine test sites. The objective of this work was to determine a better method to predict the wind speed at wind turbine installing point. The calibration was done at the test site on a complex terrain located in Daegwallyeong, Korea. It was performed for two different cases based on the IEC 61400-12 power performance measurement standard. The wind speeds averaged for 10 minutes ranged between 4 m/s and 16 m/s. The wind-direction bins of each meteorological mast were 10 degrees apart, and only the bins having data measured for more than 24 hours were employed for the test site calibration. For both cases, the two methods were found to yield almost same results which estimated real wind speed very closely.

• Proceedings of KOSOMES biannual meeting
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• 2017.11a
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• pp.211-211
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• 2017

• ETRI Journal
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• v.29 no.5
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• pp.703-705
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• 2007

An image fidelity assessment using the edge histogram descriptor (EHD) of MPEG-7 is presented. Neither additional data nor fragile watermarking is needed, and there is no need to access the original image as a reference. Only the EHDs of the original image and the received image are required. The peak signal-to-noise ratio (PSNR) obtained by comparing the EHD extracted from the received image and that of the original image is used to assess the noise level of the received image. Experimental results show that the PSNRs calculated from the conventional pixel-to-pixel gray level and from the proposed bin-to-bin EHD maintain a proportional relationship. This implies that the EHD can be used instead of image data for the image fidelity assessments.

• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.15-20
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• 2022

The study investigated the effects of differences in some electronic course designs on university students' Computational Thinking Skills (CTS). Towards this end, the researcher adopted the experimental research design of a quasi-experimental of two experimental groups. The first group was taught an e-course designed in a sequential pattern, and the other group's course was designed according to the holistic model. A CTSs test was prepared to collect the relevant data, and the data were analyzed statistically using these tests- Pearson correlation Mann Whitney and Alpha Cronbach. Results revealed statistically-significant differences at the level α=0.05 between the mean scores of the first and second experimental groups in favor of the latter in the CTS test. The findings gave ground to put forward some salient recommendations, including the need to expand computational thinking in universities' educational process. It also recommends urging faculty members to enhance e-courses in the educational process and provide technical support to students and faculty members.

• Proceedings of the Korea Database Society Conference
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• 2000.11a
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• pp.1-10
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• 2000

o Procurement inefficiencies - Material and Purchase Process Cost reduction o Sourcing not proactive - Lack of visibility disrupts ability to deliver o Poor collaboration impedes ability to meet demand o Communications Impeded by product content negotiation (omitted)

• The Journal of Advanced Prosthodontics
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• v.13 no.4
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• pp.226-236
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• 2021

PURPOSE. This study aimed to evaluate the effect of incorporating zirconium oxide nanoparticles (nano-ZrO₂) in polymethylmethacrylate (PMMA) denture base resin on flexural properties at different material thicknesses. MATERIALS AND METHODS. Heat polymerized acrylic resin specimens (N = 120) were fabricated and divided into 4 groups according to denture base thickness (2.5 mm, 2.0 mm, 1.5 mm, 1.0 mm). Each group was subdivided into 3 subgroups (n = 10) according to nano-ZrO₂ concentration (0%, 2.5%, and 5%). Flexural strength and elastic modulus were evaluated using a three-point bending test. One-way ANOVA, Tukey's post hoc, and two-way ANOVA were used for data analysis (α = .05). Scanning electron microscopy (SEM) was used for fracture surface analysis and nanoparticles distributions. RESULTS. Groups with 0% nano-ZrO₂ showed no significant difference in the flexural strength as thickness decreased (P = .153). The addition of nano-zirconia significantly increased the flexural strength (P < .001). The highest value was with 5% nano-ZrO₂ and 2 mm-thickness (125.4 ± 18.3 MPa), followed by 5% nano-ZrO₂ and 1.5 mm-thickness (110.3 ± 8.5 MPa). Moreover, the effect of various concentration levels on elastic modulus was statistically significant for 2 mm thickness (P = .001), but the combined effect of thickness and concentration on elastic modulus was insignificant (P = .10). CONCLUSION. Reinforcement of denture base material with nano-ZrO₂ significantly increased flexural strength and modulus of elasticity. Reducing material thickness did not decrease flexural strength when nano-ZrO₂ was incorporated. In clinical practice, when low thickness of denture base material is indicated, PMMA/nano-ZrO₂ could be used with minimum acceptable thickness of 1.5 mm.