Disease, Detection and Description of Plant Using CNN
Authors: Revathy B, Ritika Sudipa Lenka
Abstract
At the point when plants and harvests are experiencing vermin it influences the rural creation of the country. Normally, ranchers or specialists notice the plants with eye for location and ID of infection. Yet, this strategy is regularly time handling, costly and mistaken. Programmed location utilizing picture handling methods give quick and exact outcomes. This paper cares with a substitution way to deal with the advancement of infection acknowledgment model, upheld leaf picture arrangement, by the usage of profound convolutional networks. Propels in PC vision present an opportunity to grow and improve the act of exact plant security and broaden the market of PC vision applications inside the field of accuracy farming. This paper (project) likewise points the amateurish nursery workers and specialists who track down trouble to seek after their advantage effectively. This procedure of plant sickness location will be of incredible assistance to those individuals and they find out about the infection caused , its depiction, counteraction and therapy of it. A totally exceptional approach to preparing and subsequently the technique involved work with a quick and direct framework execution by and by. All fundamental advances needed for carrying out this sickness acknowledgment model are completely depicted all through the paper, beginning from social affair pictures to make an information base, surveyed by horticultural specialists, a profound learning system to play out the profound CNN preparing. This technique paper might be another methodology in distinguishing plant infections utilizing the profound convolutional neural organization prepared and finetuned to suit precisely to the information base of a plant's leaves that was accumulated freely for assorted plant illnesses. The development and curiosity of the created model abide its effortlessness; solid leaves and foundation pictures are in accordance with different classes, empowering the model to recognize sick leaves and sound ones or from the climate by utilizing CNN. Plants are the wellspring of food on the planet. Contaminations and sicknesses in plants are thusly a major danger, while the first normal finding is essentially performed by inspecting the plant body for the presence of visual manifestations [1]. As an option in contrast to the customarily tedious cycle, different exploration works intend to track down plausible methodologies towards securing plants. Lately, development in innovation has caused a few options in contrast to customary laborious techniques [2]. Profound learning methods are extremely effective in picture grouping issues.
Effect of Cerium Substitution on the Structural and Optical Properties of Co - Mg Mixed Nano Ferrites by Citrate Gel Auto Combustion Method
Authors: Shyamsunder Goud, N. Venkatesh, D. Ravikumar, Boda Mahipal, P. Veera Somaiah
Abstract
From citrate gel auto combustion method Ce co-doped Co-Mg mixed nano ferrites synthesized.The synthesized samples structural characterizations have been done by XRD, SEM, EDAX, FTIR, UV-VIS. Spectroscopy. From x-ray diffraction studies, reveals that synthesized samples are in crystalline nature, as well as in nano meter region, which is 13.15nm to 23.13nm. Lattice parameter andX-ray density increases with increasing Ce Concentration on Co-Mg Mixed nanoferrites. Morphology of the synthesized samples was studied using scanning electron microscope (SEM). The elemental analysis of all the Cu-Zn-Ce nano ferrite samples with different compositions was analyzed by Energy Dispersive Spectrometer (EDS). FTIR spectroscopy used to find the functional group analysis of the materials. Optical absorption behavior of the synthesized samples carried out by UV visible spectral analysis.The observed results can be explained on the basis of composition and crystal size.
Experimental Analysis of Effect of Lateral Friction on Horizontal Curve for Highways
Authors: Dipika Gupta, Dr. P. J. Gundaliya
Abstract
For the design of horizontal curve, the different factors are calculated. Friction also plays an important role while designing the horizontal curve of the road. The lateral friction which applies to the road as per the fundamental of phyiscs, always taken as constant value in the design process. Here, the finding of the conducted research project is to estimate the lateral friction factor demanded over the lateral friction supply. An experimental approach is conducted to find the value of Lateral Friction on horizontal curve. Study has gone under the different factors which are usually effecting the lateral friction such as, radius of curvature, speed of vehicle, curve inventory data, site condition as downgrade and upgrade, lateral acceleration, trajectory path of vehicle. A sensor based device is developed to identify the direct lateral friction and human behaviour while a vehicle is negotiating the horizontal curve. The data is accounted and comparison were observed between the codal provision and the output of device. Again the data is compared with and simulation software: CARSIM. The result of all the comparison were seen and concluded that the Lateral Friction Factor is inversely proportional to the speed of vehicle. With increase of speed of vehicle, the lateral friction gets reduced. This would result to take a new value of lateral friction by highway designers in real office practice while designing the horizontal curves, that would not take the constant lateral friction as always. Also the horizontal curve should be designed without at driver’s risk.
Impact of Social Media on Academic Performance of Students: A Study of Students With Reference to Dehradun City
Authors: Mr. Naveen Bhardwaj, Prof. (Dr.) Vasudha Sharma, Dr. Neeraj Karan Singh
Abstract
Social Media is performing very effective role in every body’s life and it is growing rapidly. Internet, Laptop, smart phone, Computers are very essential and play very vital role in this field. By the help of social media, anybody can connect himself, communicate, and share his or her views, information. Therefore majority of people are aware of social media like whatsApp and Facebook and they engage themselves for various purpose like entertainment, sharing information, watching movies, images and for both academic and nonacademic purpose. In fact, these social websites like whatsApp and Facebook can be good platform to exchange the information between students and even with their teachers. Many social media options are available for fulfill the need and infect people are using almost all options like whatsApp and Facebook on priority. However, using social media in excess can be harmful, wastage of time and most importantly very dangerous for the health of the users. In this paper, the researcher investigated the pros and cons of social media as far as the academic performance of the students is concerned. Based on random sampling a sample of 300 students of various colleges in Dehradun was selected. Survey has been conducted by circulating questionnaire as an instrument for data among the respondents through descriptive statistics and Chi-square test was applied in testing the hypotheses. The result concluded that exposure of social media by the students have negative effect on the academic performance of the students. Based on this study, authors recommends that students should be advised and motivate to the students to use the social media for academic purpose more. It is advisable that Students should be engaged themselves for the study purpose to the maximum extent. College and Institutions should create the online official website and page for the students to create the awareness among the students about their bright future and educate them for the benefits of getting good education. Therefore, they can utilize it for getting important information, knowledge sharing, lecture notes, e–contents and other study materials to enhance academic activities so that they occupy themselves minimum on social media (WhatsApp and Facebook) for nonacademic purpose.