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Full-Text Articles in Engineering
Classification Of Oil Products According To The Nomenclature Of Goods, Kurbankul Mavlankulovych Karimkulov Profesor, Azoda Abdurahmanova
Classification Of Oil Products According To The Nomenclature Of Goods, Kurbankul Mavlankulovych Karimkulov Profesor, Azoda Abdurahmanova
Technical science and innovation
The article analyzes types of vegetable oils. Simple methods of determining their quality using liquid gas chromatography have been developed. Recommendations for improving the classification of foreign economic activity based on commodity nomenclature were developed and recommended for customs operations. “Fats and oils of animal, vegetable or microbiological origin and products of their breakdown; prepared edible fats; waxes of animal or vegetable origin” was called. Animal fats, including pork, beef, sheep, goat, fish and oils of animals such as marine mammals are classified according to the Nomenclature of Foreign Economic Activities of the Republic of Uzbekistan in commodity headings 1501-1506 …
The Morphology Analysis Of Soil In Remote Sensing Image Processing, Mirzayan Mirzaaxmedovich Kamilov, Mirzaakbar Xakkulmirzayevich Hudayberdiev, Bobomurod Mamitjonovich Tojiboev
The Morphology Analysis Of Soil In Remote Sensing Image Processing, Mirzayan Mirzaaxmedovich Kamilov, Mirzaakbar Xakkulmirzayevich Hudayberdiev, Bobomurod Mamitjonovich Tojiboev
Chemical Technology, Control and Management
This article analyzed various techniques used in satellite image processing to analyze soil morphology. Analysis of soil morphology using satellite imagery plays a crucial role in soil science research, Land Management, and environmental monitoring. It provides an economical and efficient means of studying large-scale soil variability, providing information on land sustainable use, resource management and soil conservation decisions.
A Study Of Security Problems In Big Data And Their Solutions, Nozima Akhmedova
A Study Of Security Problems In Big Data And Their Solutions, Nozima Akhmedova
Chemical Technology, Control and Management
Statistical data on information security that concerns Big Data and is the most important for enterprises are provided. Based on this data, we studied problems such as the lack of big data practices and protection, the lack of techniques for protecting big data, the lack of standards for protecting big data, the lack of regulation of big data and ecosystems, security problems in Big Data, and proposed several proposals to improve the security of systems that use this technology.
Importance Of Morphological Features In Orthoptera Identification, Kamilov Mirzoyan, Alisher Khamroev, Hudayberdiev Mirzaakbar
Importance Of Morphological Features In Orthoptera Identification, Kamilov Mirzoyan, Alisher Khamroev, Hudayberdiev Mirzaakbar
Chemical Technology, Control and Management
This article analyzes the problems of implementing image recognition methods and algorithms for identifying biological objects. The Orthoptera group was chosen as a biological object. Orthoptera is a taxonomic order of insects that includes grasshoppers, crickets, locusts, and others. Approaches to the formation and identification of features of Orthoptera species and the formation of training and control samples of their samples are proposed. Estimation algorithms (ACE) were chosen as algorithmic support for identifying Orthoptera collections. ACE is based on the principle of partial priority. Approaches to the formation of a training and testing complex based on the data from the …
Two-Class Classification With Various Characteristics Based On Kernel Principal Component Analysis And Support Vector Machines, Ivanna Kristianti Timotius, Iwan Setyawan, Andreas Ardian Febrianto
Two-Class Classification With Various Characteristics Based On Kernel Principal Component Analysis And Support Vector Machines, Ivanna Kristianti Timotius, Iwan Setyawan, Andreas Ardian Febrianto
Makara Journal of Technology
Two class pattern classification problems appeared in many applications. In some applications, the characteristic of the members in a class is dissimilar. This paper proposed a classification system for this problem. The proposed system was developed based on the combination of kernel principal component analysis (KPCA) and support vector machines (SVMs). This system has been implemented in a two class face recognition problem. The average of the classification rate in this face image classification is 82.5%.