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Abstract

This article discusses the performance of an algorithm for detection of defect centers in semiconductor materials. It is based on direct parameter approximation with nonlinear regression to determine the parameters of thermal emission rate in the photocurrent waveforms. The methodology of the proposed algorithm was presented and its application procedure was described and the results of its application can be seen in measured photocurrent waveforms of a silicon crystal examined with High-Resolution Photoinduced Transient Spectroscopy (HRPITS). The performance of the presented algorithm was verified using simulated photocurrent waveforms without and with noise at the level of 10 -2. This paper presents for the first time the application of the direct approximation method using modern regression and clustering algorithms for the study of defect centers in semiconductors.
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Authors and Affiliations

Witold Kaczmarek
1
Marek Suproniuk
1
Karol Piwowarski
1
Bogdan Perka
1
Piotr Paziewski
1

  1. Institute of Electronic Systems, Department of Electronics, Military University of Technology, ul. gen. Sylwestra Kaliskiego 2, 00-908 Warszawa, Poland
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Abstract

Perceiving the spatiotemporal relationship of land use changes and groundwater resources is crucial for the effective and sustainable management of the plains. This study aims to investigate the relationship between land use changes and groundwater depth fluctuations in the forbidden plains of northern Hamedan. In the present study, the land use maps for 1989, 1997, 2005, 2013 and 2018 were extracted and categorized from Landsat satellite images and then evaluated for accuracy. In addition, groundwater depth distribution maps were prepared by kriging method for five years from piezometric data. The correlation and relationship between land use changes and groundwater depth fluctuations were determined by REGRESS methods. The findings from kriging method indicated that the intensity of groundwater decline during the last three periods of study (2005, 2013 and 2018) becomes more severe in the study area. Land use change trends indicate a sharp decline in the orchards, pasture lands, barren lands and a relative decline in the irrigated agricultural land, and consequently, increasing in non-irrigation and residential farmland. In addition, the average annual depth of groundwater level during the past 29 years decreased to 1.57 m and 0.87 m in the Kabudrahang and Razan Plains, respectively. The r value of REGRESS method during five study periods was the minimum 0.015 and maximum 0.15 in the Kabudrahang Plain and minimum 0.06 and maximum 0.15 in the Razan Plain, respectively. The results of the study indicated that climate changes cannot be considered as the reason for declining the groundwater in the study area. However, along with the relative impacts of land use changes, the role of managerial factors, the prominent example of which is the non-expert location of the Shahid Mofatteh Hydroelectric Power Station, which supplies underground water to cool the generators, should be considered. The present study can be effective in the management, planning, and policy of groundwater resources, land use location, and spatial planning in the areas facing severe water shortages, especially in the northern plains of Hamedan because this study indicates the importance of underground water in arid and semi-arid regions.

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Authors and Affiliations

Hossein Rafiemehr
Lotfali Kozegar Kaleji
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Abstract

The main source of information on the abundance of polymetallic nodules (APN) is the results of direct seafloor sampling, mainly using box corers. Due to the vast spread of nodule occurrence in the Pacific, the distances between successive sampling sites are significant. This makes it difficult to reliably estimate the nodule resources, especially in parts of the deposit with small areas corresponding to the areas scheduled for extraction in the short term (e.g. within one year). It seems justified to try to increase the accuracy of nodule resource estimates through the use of information provided by numerous photos of the ocean floor taken between sampling stations. In particular, the percentage of nodule coverage of the ocean floor (NC), the data on fraction distribution of nodules (FD) and the coverage of nodules with sediments (SC) are important here. In the presented study, three regression models were used to predict the nodule abundance from images: simple linear regression (SLR), multiple regression (MR), and general linear model (GLM). The GLM provides the most accurate prediction of nodule abundance (APN) due to the ability of this model to simultaneously take into account both quantitative variable (NC) and qualitative variables (FD, SC). The mean absolute errors of APN prediction are in the range of 1.0–1.7 kg/m2, which is 7–13% of the average nodule abundance determined for training or testing data sets. This result can be considered satisfactory for predicting the abundance in ocean floor areas covered only by photographic survey.
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Authors and Affiliations

Monika Wasilewska-Błaszczyk
1
ORCID: ORCID
Jacek Mucha
1
ORCID: ORCID

  1. AGH University of Science and Techology, Kraków, Poland
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Abstract

The main objective of the present study is enhanced of the sand moulding process through addressing the sand mould defects and failures, ultimately lead to improve production of the sand castings with well-defined of pattern profiles. The research aimed to reduce the cost and energy expenditure associated with the compaction time of the sand moulding process. Practical destructive tests were conducted to assess properties of the green sand moulds. Linear regression and multi-regression methods were employed to identify the key factors influencing the sand moulding process. The proposed experimental destructive tests and predicted regression methods facilitated measurement of the green sand properties and enabled evaluation of the effective moulding parameters, thereby enhancing the sand moulding process. Factorial design of experiments approach was employed to evaluate effect of parameters of water content and mixing time of the green sand compaction process on the mechanical properties of green sand mould namely the tensile strength, and compressive strength.
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Bibliography

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Authors and Affiliations

Dheya Abdulamer
1
ORCID: ORCID

  1. University of Technology- Iraq

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