صفحه محصول - پاورپوینت عناوين موضوعات تحقيقاتی ماشينها، تجهيزات و صنايع وابسته کشاورزی

پاورپوینت عناوين موضوعات تحقيقاتی ماشينها، تجهيزات و صنايع وابسته کشاورزی (pptx) 11 اسلاید

دسته بندی : پاورپوینت

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تعداد اسلاید: 11 اسلاید

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بنام خدا 1 2 عناوين موضوعات تحقيقاتی ماشينها، تجهيزات و صنايع وابسته کشاورزی 3 Biosystems Engineering (agricultural Engineering research) ASABE (Formerly ASAE) publications Canadian Biosystems Engineering CIGR eJournal (International Commission of Agricultural Engineering ) Journal of Agricultural Engineering (Germany, Landtechnik) Computers and Electronics in Agriculture Journal of Food Engineering Soil and Tillage Research Mechatronics Image & vision Computing Journal of Electrostatics Renewable Energy ليست مجلات معتبر در ماشينهاي كشاورزي و مباحث وابسته به آن 4 شبيه سازی آزمايشگاهی و عددیNumerical and Experimental simulations and modeling ماشينهای برداشت برای محصولات خاصHarvesting Machineries for Especial Crops استفاده از تجزيه و تحليل تصاوير جهت تشخيص گياهان، دسته بندی ميوه جات و تعيين درجه رسيدگیUsing Image Processing for Weed Detection and Fruits and Vegetables Sorting & Grading روشهای نوين خشک کردن محصولات کشاورزی، استفاده از انرژی خورشيدی ، ميکروويو Solar and Microwave Drying of Agricultural produces استفاده از ماشينهای بصری جهت بر آورد کيفی محصولMachine Vision System for Automatic Quality Grading of Fruit 5 استفاده از سنسور در کشاورزیBiosensor Technology in Agricultural Problems کشاورزی دقيق (مديريت موضعی در مزرعه) Precision Agriculture (Farming)/ Specific Site Management اندازه گيری خواص فيزِيکی و مکانيکی محصولات کشاورزی با تکيه بر محصولات بومی Physical & Mechanical properties of Agricultural products اندازه گيری خواص حرارتی محصولات کشاورزی با تکيه بر محصولات بومی Thermal properties of Agricultural products اندازه گيری خواص الکترو مغناطيسی محصولات کشاورزی Electromagnetic properties of Agricultural products 6 استفاده از magnetic resonance imaging (MRI)  در محصولات کشاورزی به منظور تعيين رسيدگی ميوه ها وخسارت ناشی از لهيدگی The structural and biochemical information it provides is helpful in the diagnosis of abnormalities without the possibly harmful effects of X rays or gamma rays. It is invaluable in detecting and delineating tumours and in providing images of the brain, the heart, and other soft-tissue organs. MRI may produce anxiety because the patient must often lie quietly inside a narrow tube. Another disadvantage is that it requires a longer scanning time than other computer-assisted forms of scanning, which makes it more sensitive to motion and of less value in scanning the chest or abdomen. However, MRI images provide better contrast between normal and diseased tissue than those produced by other computer-assisted technics Absorption or emission of electromagnetic radiation by electrons or atomic nuclei in response to certain magnetic fields. استفاده از Near infra-red (NIR) spectroscopy 7 تكنيك هاي مهندسي!! نانو تكنولوژي Nanotechnology الگوريتم ژنتيكي Genetic algorithm شبكه هاي عصبي Neural network 8 نانوتكنولوژي Nanotechnology is a field of applied science focused on the design, synthesis, characterization and application of materials and devices on the nanoscale. Nanotechnology is a subclassification of technology in colloidal science, biology, physics, chemistry and other scientific fields and involves the study of phenomena and manipulation of material at the nanoscale Two main approaches are used in nanotechnology: one is a "bottom-up" approach where materials and devices are built up atom by atom, the other a "top-down" approach where they are synthesized or constructed by removing existing material from larger entities. A unique aspect of nanotechnology is the vastly increased ratio of surface area to volume present in many nanoscale materials, which opens new possibilities in surface-based science, such as catalysis. This catalytic activity also opens potential risks in their interaction with biomaterials. 9 Genetic algorithm A genetic algorithm is a search technique used in computing to find true or approximate solutions to optimization and search problems, and is often abbreviated as GA. Genetic algorithms are categorized as global search heuristics. Genetic algorithms are a particular class of evolutionary algorithms that use techniques inspired by evolutionary biology such as inheritance, mutation, selection Genetic algorithms are implemented as a computer simulation in which a population of abstract representations (called chromosomes or the genotype or the genome) of candidate solutions (called individuals, creatures, or phenotypes) to an optimization problem evolves toward better solutions. Traditionally, solutions are represented in binary as strings of 0s and 1s, but other encodings are also possible. The evolution usually starts from a population of randomly generated individuals and happens in generations. In each generation, the fitness of every individual in the population is evaluated, multiple individuals are stochastically selected from the current population (based on their fitness), and modified (recombined and possibly mutated) to form a new population. The new population is then used in the next iteration of the algorithm. Genetic algorithms find application in computer science, engineering, economics,chemistry, physics, mathematics and other fields.