• Geomechanics and Engineering
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• v.34 no.6
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• pp.697-726
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• 2023

Brittleness as an important property of rock plays a crucial role both in the failure process of intact rock and rock mass response to excavation in engineering geological and geotechnical projects. Generally, rock brittleness indices are calculated from the mechanical properties of rocks such as uniaxial compressive strength, tensile strength and modulus of elasticity. These properties are generally determined from complicated, expensive and time-consuming tests in laboratory. For this reason, in the present research, an attempt has been made to predict the rock brittleness indices from simple, inexpensive, and quick laboratory test results namely dry unit weight, porosity, slake-durability index, P-wave velocity, Schmidt rebound hardness, and point load strength index using multiple linear regression, exponential regression, support vector machine (SVM) with various kernels, generating fuzzy inference system, and regression tree ensemble (RTE) with boosting framework. So, this could be considered as an innovation for the present research. For this purpose, the number of 39 rock samples including five igneous, twenty-six sedimentary, and eight metamorphic were collected from different regions of Iran. Mineralogical, physical and mechanical properties as well as five well known rock brittleness indices (i.e., B₁, B₂, B₃, B₄, and B₅) were measured for the selected rock samples before application of the above-mentioned machine learning techniques. The performance of the developed models was evaluated based on several statistical metrics such as mean square error, relative absolute error, root relative absolute error, determination coefficients, variance account for, mean absolute percentage error and standard deviation of the error. The comparison of the obtained results revealed that among the studied methods, SVM is the most suitable one for predicting B₁, B₂ and B₅, while RTE predicts B₃ and B₄ better than other methods.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2001.05a
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• pp.186-189
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• 2001

In keeping with the needs of the times for energy and labor saving and simplifying production processes, interests has been growing in warm forging. Moreover, it is interested in increasing the material usage and production amounts. To improve the productivity and material usage, it is studied the process design of warm forging for socket. Until now, socket is manufactured by hot forging in hammer. The percentage of material usage is under $60\%$ in hammer forging. On the other han4 the percentage can be increased over $90\%$ in warm forging. To change the process from hot forging to warm forging, process designs must be performed. In this time, by using the FEM package, DEFORM-3D, we could get the shape of 1st process and minimum sealing pressure. They are very essential design data to decrease the trial and error. Practically, the overlap defect could be detected and eliminated with design modification of rib height and fillet radius. Moreover, forging load and minimum sealing pressure was defined by the 3D FEM analysis.

• Education of Primary School Mathematics
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• v.12 no.2
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• pp.117-132
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• 2009

The purpose of this study was analysis on types of strategies and errors when the sixth grade students were solving proportion problems of mathematics textbooks. For this study, proportion problems in mathematics textbooks were investigated and 17 representative problems were chosen. The 277 students of two elementary schools solved the problems. The types of strategies and errors in solving proportion problems were analyzed. The result of this study were as follows; The percentage of correct answers is high if the problems could be solved by proportional expression and the expression is in constant rate. But the percentage of correct answers is low, if the problems were expressed with non-constant rate.

• Nuclear Engineering and Technology
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• v.48 no.1
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• pp.64-71
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• 2016

Void fraction is an important parameter in the oil industry. This quantity is necessary for volume rate measurement in multiphase flows. In this study, the void fraction percentage was estimated precisely, independent of the flow regime in gas-liquid two-phase flows by using ${\gamma}-ray$ attenuation and a multilayer perceptron neural network. In all previous studies that implemented a multibeam ${\gamma}-ray$ attenuation technique to determine void fraction independent of the flow regime in two-phase flows, three or more detectors were used while in this study just two NaI detectors were used. Using fewer detectors is of advantage in industrial nuclear gauges because of reduced expense and improved simplicity. In this work, an artificial neural network is also implemented to predict the void fraction percentage independent of the flow regime. To do this, a multilayer perceptron neural network is used for developing the artificial neural network model in MATLAB. The required data for training and testing the network in three different regimes (annular, stratified, and bubbly) were obtained using an experimental setup. Using the technique developed in this work, void fraction percentages were predicted with mean relative error of <1.4%.

• Journal of the Korean Data and Information Science Society
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• v.25 no.3
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• pp.493-499
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• 2014

The Pythagorean won-loss formula postulated by James (1980) indicates the percentage of games as a function of runs scored and runs allowed. Several hundred articles have explored variations which improve RMSE by original formula and their fit to empirical data. This paper considers a variation on the formula which allows for variation of the Pythagorean exponent. We provide the most suitable optimal exponent in the Pythagorean method. We compare it with other methods, such as the Pythagenport by Davenport and Woolner, and the Pythagenpat by Smyth and Patriot. Finally, our results suggest that proposed method is superior to other tractable alternatives under criterion of RMSE.

• Agribusiness and Information Management
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• v.12 no.2
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• pp.40-54
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• 2021

Market integration and prices in pulse crops like black gram play an important role in determining the production decisions of the farmers and diversification towards high value nutritious crops. In this context, the present study explores extent of market integration and price transmission in selected major black gram markets in Andhra Pradesh using Johansen co-integration, Vector Error Correction Model and Granger causality test. The study used monthly prices data of black gram (Rs/quintal) sourced from selected markets of Srikakulam, Krishna and Kurnool spanning January, 1990 to December, 2019. The results of the study strongly buttressed the existence of co-integration and interdependence of selected black gram markets in Andhra Pradesh. However, the speed of adjustment of the prices found to be moderate in Krishna market and quite weaker in Srikakulam market and thereby prices correct a small percentage of the disequilibrium in these markets with the greatest percentage by the external and internal forces. So, it necessitates the need for future research, to investigate the influence of external and internal factors such as market infrastructure, Government policy and self-sufficient production, product characteristics and utilization towards market integration. As there exists only unidirectional causality from Krishna to Kurnool and from Krishna to Srikakulam markets, it calls for strengthening the information technology for flow of market information regularly to help the farmers for increasing their income.

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.71-78
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• 2022

Electronic measuring devices have an important role in agricultural projects and in various fields. Electronic measuring devices play a vital role in controlling and saving soil information. They are designed to measure the temperature, acidity and moisture of the soil. In this paper, a new methodology to manage irrigation and soil fertility using an electronic system is proposed. This is designed to operate the electronic irrigation and adds inorganic fertilizers automatically. This paper also explains the concept of remote management and control of agricultural projects using electronic soil measurement devices. The proposed methodology is aimed at managing the electronic irrigation process, reading the moisture percentage, elements of soil and controlling the addition of inorganic fertilizers. The system also helps in sending alert messages to the user when an error occurs in measuring the percentage of soil moisture specified for crop and a warning message when change happens to the fertility of soil as many workers find difficulty in daily checking of soil and operating agricultural machines such as irrigation machine and soil fertilizing machine, especially in large projects.

• Journal of Distribution Science
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• v.12 no.2
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• pp.59-71
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• 2014

Purpose - In recent years, many firms have attempted various approaches to cope with the continual increase of aviation transportation. The previous research into freight charge forecasting models has focused on regression analyses using a few influence factors to calculate the future price. However, these approaches have limitations that make them difficult to apply into practice: They cannot respond promptly to small price changes and their predictive power is relatively low. Therefore, the current study proposes a freight charge-forecasting model using time series data instead a regression approach. The main purposes of this study can thus be summarized as follows. First, a proper model for freight charge using the autoregressive integrated moving average (ARIMA) model, which is mainly used for time series forecast, is presented. Second, a modified ARIMA model for freight charge prediction and the standard process of determining freight charge based on the model is presented. Third, a straightforward freight charge prediction model for practitioners to apply and utilize is presented. Research design, data, and methodology - To develop a new freight charge model, this study proposes the ARIMAC(p,q) model, which applies time difference constantly to address the correlation coefficient (autocorrelation function and partial autocorrelation function) problem as it appears in the ARIMA(p,q) model and materialize an error-adjusted ARIMAC(p,q). Cargo Account Settlement Systems (CASS) data from the International Air Transport Association (IATA) are used to predict the air freight charge. In the modeling, freight charge data for 72 months (from January 2006 to December 2011) are used for the training set, and a prediction interval of 23 months (from January 2012 to November 2013) is used for the validation set. The freight charge from November 2012 to November 2013 is predicted for three routes - Los Angeles, Miami, and Vienna - and the accuracy of the prediction interval is analyzed using mean absolute percentage error (MAPE). Results - The result of the proposed model shows better accuracy of prediction because the MAPE of the error-adjusted ARIMAC model is 10% and the MAPE of ARIMAC is 11.2% for the L.A. route. For the Miami route, the proposed model also shows slightly better accuracy in that the MAPE of the error-adjusted ARIMAC model is 3.5%, while that of ARIMAC is 3.7%. However, for the Vienna route, the accuracy of ARIMAC is better because the MAPE of ARIMAC is 14.5% and the MAPE of the error-adjusted ARIMAC model is 15.7%. Conclusions - The accuracy of the error-adjusted ARIMAC model appears better when a route's freight charge variance is large, and the accuracy of ARIMA is better when the freight charge variance is small or has a trend of ascent or descent. From the results, it can be concluded that the ARIMAC model, which uses moving averages, has less predictive power for small price changes, while the error-adjusted ARIMAC model, which uses error correction, has the advantage of being able to respond to price changes quickly.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.1
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• pp.43-48
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• 2010

Proctor test A or D method of compaction is the most common laboratory test for investigation of subgrade soil characteristics, however, compression type using roller is used in the field. The differences between laboratory and field compaction have considerable error as application to subgrade soil properties of laboratory test. The investigation of compacted soil is carried into effect to solve the problem. The gyratory compactor which is made to reproduce the field density of asphalt mixture, coming from traffic loads, has an advance to compact it similar to arrangement of field aggregate particles. This gyratory compactor has several problems of investigation of compacted soil, because it has designed to make initial asphalt specimens. The main objectives of this research are grasping problems when compacted soil test using the gyratory compactor and showing solutions. It has made a comparative study of difference of the percentage of water content and weight, which are before and after compaction, about the pressure of compaction, frequency of compaction and speed of compaction. And it also has investigated finding maximum percentage of water content which not occur change of percentage of water content after compaction and searching how has an effect on drawing compaction curve.

• Anatomy and Cell Biology
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• v.57 no.2
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• pp.271-277
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• 2024

Human dentition is unique to individuals and helps in identification of individuals in forensic odontology. This study proposes to study the manually ground sections of single rooted teeth using digital methods for dental age estimation. To assess the dentinal translucency from the scanned digital images of manually ground section of teeth using commercially available image edition software. Corroborating the root dentinal translucency length and region of interest (ROI) of translucency zone in pixels (as a marker of dental age) with the chronological age of the subject, as stratified by different age groups. Twenty single-rooted extracted teeth from 20 patients each from 6 groups divided as per age. Manual sectioning of the teeth followed by scanning the sections was done. Root area in pixels and ROI of translucency zone were measured. From the observed values, translucency length percentage (TLP) and percentage of ROI in pixels (TPP) was calculated and tabulated. Pearson's correlation coefficients were obtained for age with TLP and TPP. Positive correlation existed between age and TLP and also between age and TPP. With the obtained data, multilinear regression equations for specific age groups based on 10-year intervals were derived. By a step-down analysis method, age was estimated with an average error of around ±7.9 years. This study gives a novel method for age-estimation that can be applied in real-time forensic sciences.