Amit Kumar Sharma

In the agriculture development and growth, the efficient machinery and equipment plays an important role. Various research studies are involved in the implementation of the research and patents to aid the smart agriculture and authors and reviewers that machine leaning technologies are providing the best support for this growth. To explore machine learning technology and machine learning algorithms, the most of the applications are studied based on the swarm intelligence optimization. An optimized V3CFOA-RF model is built through V3CFOA. The algorithm is tested in the data set collected concerning rice pests, later analyzed and compared in detail with other existing algorithms. The research result shows that the model and algorithm proposed are not only more accurate in recognition and prediction, but also solve the time lagging problem to a degree. The model and algorithm helped realize a higher accuracy in crop pest prediction, which ensures a more stable and higher output of rice. Thus they can be employed as an important decision-making instrument in the agricultural production sector.

A recent advent has been seen in the usage of Internet of things (IoT) for autonomous devices for exchange of data. A large number of transformers are required to distribute the power over a wide area. To ensure the normal operation of transformer, live detection and fault diagnosis methods of power transformers are studied. This article presents an IoT-based approach for condition monitoring and controlling a large number of distribution transformers utilized in a power distribution network. In this article, the vibration analysis method is used to carry out the research. The results show that the accuracy of the improved diagnosis algorithm is 99.01, 100, and 100% for normal, aging, and fault transformers. The system designed in this article can effectively monitor the healthy operation of power transformers in remote and real-time. The safety, stability, and reliability of transformer operation are improved.

The analysis of the data so far available indicates that eukaryotic chromosome with splicing characteristics appeared quite early in evolution possibly parallel and not sequential to the prokaryotic system. The endosymbiotic origin of the eukaryotic cell involved a primitive undifferentiated unicellular eukaryote and a photosynthetic or non-photosynthetic microbe. Certain regulatory genes of extra-cellular organelles were transferred later through molecular hybridization to the nucleus. The evolution of multicellularity and sexual reproduction led to the origin of innumerable eukaryotic forms in the late precambrian period. This new concept of the author can account for the evolution of complex eukaryotic chromosome and harmonious functioning of extra-cellular organelles with the nucleus. The concept also explains the sudden spurt of innumerable eukaryotic fossils at the early palaeozoic era.

Nowadays, the modern management is promoted to resolve the issue of unreliable information transmission and to provide work efficiency. The basic aim of the modern management is to be more effective in the role of the school to train talents and serve the society. This article focuses on the application of data mining (DM) in the development of information management system (IMS) in universities and colleges. DM provides powerful approaches for a variety of educational areas. Due to the large amount of student information that can be used to design valuable patterns relevant to student learning behavior, research in the field of education is continuously expanding. Educational data mining can be used by educational institutions to assess student performance, assisting the institution in recognizing the student’s accomplishments. In DM, classification is a well-known technique that has been regularly used to determine student achievement. In this study, the process of DM and the application research of association rules is introduced in the development of IMS in universities and colleges. The results show that the curriculum covers the whole field and the minimum transaction support count be 2, minconf = 70%. The results also suggested that students who choose one course also tend to choose the other course. The application of DM theory in university information will greatly upsurge the data analysis capability of administrators and improve the management level.

To shorten the travel time and improve comfort, the automatic train driving system is considered to replace manual driving. In this article, an automatic control method of computer application data-processing system based on artificial intelligence is proposed. An automatic train operation (ATO) introduced the structure and function of an autopilot system (train), optimized the train running on the target curve, introduced the basic principle of fuzzy generalized predictive control (PC) algorithm, and combined with the characteristics of ATO system design the speed controller based on optimization algorithm, the target curve to make use of the designed controller to track and simulation validation. The experimental outcomes demonstrate that when the train runs to 90 s, the displacement difference reaches about 40 m, which proves that the fuzzy PC has better displacement tracking, punctual arrival, and higher stopping accuracy.

A study was carried out from October, 2020 to September, 2021to investigate the diversity of fishes and the conservation status of Chittaura Jheel (Bahraich), Uttar Pradesh. During the study period, 38 fish species belonging to 28 genera, 14 families and 7 orders have been identified. The order Cypriniformes was found the dominated order with 15 species(39.47%) followed by Siluriformes 10 species (26.31%), Perciformes 4 species (10.52%), Ophiocephaliformes 4 species (10.52%), Synbranchiformes2 species (5.26%), Osteoglossiformes 2 species (5.26%) and Clupiformes 1 species (2.63 %), The present investigation showed that the wetland, Chittaura Jheel possesses rich fish biodiversity but proper conservation measures are required to maintain sustainability and richness of the fish species diversity of that wetland of U.P. According to IUCN, 30 were enlisted as Least Concern (LC), 2 species as near endangered (NE), 3 species as near threatened (NT), 2 listed as Endangered (EN) and 1 species was listed as Vulnerable (VU). There is a need of conservation of fish diversity of this natural wetland. The pressure is increasing day by day due to increasing population, leading to loss of fish diversity hence identifying the problem and making a better management plan is the way for conservation of the fish diversity of the Chittaura Jheel, a wetland of Bahraich district of Uttar Pradesh.