Ground-based active optical sensors (GBAOS) have been successfully used in agriculture to predict crop yield potential (YP) early in the season and to improvise N rates for optimal crop yield. However, the models were found weak or inconsistent due to environmental variation especially rainfall. The objectives of the study were to evaluate if GBAOS could predict YP across multiple locations, soil types, cultivation systems, and rainfall differences. This study was carried from 2011 to 2013 on corn (Zea mays L.) in North Dakota, and in 2017 in potatoes in Maine. Six N rates were used on 50 sites in North Dakota and 12 N rates on two sites, one dryland and one irrigated, in Maine. Two active GBAOS used for this study were GreenSeeker and Holland Scientific Crop Circle Sensor ACS 470 (HSCCACS-470) and 430 (HSCCACS-430). Rainfall data, with or without including crop height, improved the YP models in term of reliability and consistency. The polynomial model was relatively better compared to the exponential model. A significant difference in the relationship between sensor reading multiplied by rainfall data and crop yield was observed in terms of soil type, clay and medium textured, and cultivation system, conventional and no-till, respectively, in the North Dakota corn study. The two potato sites in Maine, irrigated and dryland, performed differently in terms of total yield and rainfall data helped to improve sensor YP models. In conclusion, this study strongly advocates the use of rainfall data while using sensor-based N calculator algorithms.
New designs of solar using ray tracing program, have been presented for improved the performance and the out put power of the silicon solar cell, as well as reducing the cost of system working by solar energy. Two dimensional solar concentrator (Fresnel lenses) and three dimensional concentrators (parabola dish and cassegrain) were used as concentrator for photovoltaic applications (CPV). The results show that the performance efficiency and out power for crystalline silicon solar cells are improved.
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The utilization of sugarcane molasses (SCM), a byproduct of sugar refining, offers a promising bio-based alternative to conventional chemical admixtures in cementitious systems. This study investigates the effects of SCM at five dosage levels, 0.25%, 0.50%, 0.75%, 1.00%, and 1.25% by weight of cement, on cement mortar performance across fresh, mechanical, thermal, durability, and density criteria. A comprehensive experimental methodology was employed, including flow table testing, compressive strength (7, 14, and 28 days) and flexural strength measurements, embedded thermal sensors for real-time hydration monitoring, water absorption and chloride ion penetration tests, as well as 28-day density determination. Results revealed clear
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The spectral response of the Si solar cell does not coincidence with the sun irradiance spectrum, so the efficiency of the Si solar cell is not high. To improve the Si solar cell one try to make use of most region of the sun spectrum by using dyes which absorb un useful wavelengths and radiate at useful region of spectrum (by stock shift). Fluorescence's dye is used as luminescent concentrator to increase the efficiency of the solar cell. The results show that the performance efficiency and out power for crystalline silicon solar cells are improved.
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The research deals with A very important two subjects, computer aided process planning (CAPP) and Quality of product with its dimintions which identified by the producer organization, the goal of the research is to Highlight and know the role of the CAPP technology to improve quality of the product of (rotor) in the engines factory in the general company for electrical industries, The research depends case study style by the direct visits of researcher to the work location to apply the operational paths generated by specialized computer program designed by researcher, and research divides into four axes, the first regard to the general structure of the research, the second to the theoretical review, the t
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يدور هذا البحث حول خواص البولي ايثيلين (PE) باستخدام اللاكتام مع مركبات أكسيد النانو المعدنية المستخرجة من نبات (القرنفل) وهي براعم زهرة شجرة القرنفل كمثبت وعامل اختزال . حيث يستقر أكسيد النانو ويغطي البوليمر الطبيعي. الهدف من الدراسة هو أن أكسيد النانو يؤدي أفضل ترابط للمركبات المحضرة ، بسبب زيادة مساحة السطح ، وبالتالي القدرة على الارتباط بالبوليمر المحضر. والقدرة على الثبات الإلكتروني بسبب كثرة الروابط
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Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo
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Metoclopramide (MCP) ion selective electrodes based on metoclopramide-phosphotungstic acid (MCP-PT) ion pair complex in PVC matrix membrane were constructed. The plasticizers used were tri-butyl phosphate (TBP), di-octyl phenyl phosphonate (DOPP), di-butyl phthalate (DBPH), di-octyl phthalate (DOP), di-butyl phosphate (DBP), bis 2-ethyl hexyl phosphate (BEHP). The sensors based on TBP, DOPP, DBPH and DOP display a fast, stable and linear response with slopes 59.9, 57.7, 57.4, 55.3 mV/decade respectively at pH ranged 2-6. The linear concentration range between 1.0×10-5 – 1.0×10-2 M with detection limit 3.0×10-6 and 4.0×10-6 M for electrodes using TBP, DOPP and DBPH while e
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