Volume 9 | Issue 6 |

 Abstract

Plant disease is ongoing challenge for smallholder formers, which threatens income and food security. The recent revolution smartphone penetration and computer vision models has created an opportunity for image classification in agriculture. Convolutional Neural Networks(CNN) algorithm is considered state-of-the-art in image recognition and offer the ability to provide a prompt and definite diagnosis. It analyze the data of leaf image and send the output as either it is good leaf it shows healthy and disease leaf shows the name of the disease.

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 Keywords

deep learning, classification, CNN algorithm, disease identification

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Rural south Tamilnadu students who step into their colleges are found to be in lower level in their second language English. The researcher intended to prove this condition and conducted a diagnostic test in writing skill to the first year under graduation students.340 first year students from various departments participated in this study. A qualitative study is made to analyse the inter lingual and intra lingual skills developed by both English Medium and Tamil medium students. Inter lingual and intra lingual errors are identified, analysed and categorized. It is found that the Tamil medium students, even after 12 years of English language acquaintance, still suffer from mother tongue influence and have committed a lot of inter and intra lingual errors. Those students could not construct correct English sentences. The students who have studied in English medium have improved their proficiency level than the Tamil medium students. This study is significant and will be useful for the teachers to know the level of the students so that they can give them the suitable remedial measures and assist the students towards successful English language learning.

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 Keywords

Second language learning, Inter lingual skill, Intra lingual skill, error analysis, Mother tongue influence, Medium of instruction

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Stock price forecasting is a popular and important topic in financial and academic studies. Share Market is an untidy place for predicting since there are no significant rules to estimate or predict the price of share in the share market. Many methods like technical analysis, fundamental analysis, time series analysis and statistical analysis, etc. are all used to attempt to predict the price in the share market but none of these methods are proved as a consistently acceptable prediction tool. In this project we attempt to implement Network approach to LSTM based predict stock market prices. The aim is to predict the future value of the financial stocks of a company. The recent trend in stock market prediction technologies is the use of machine learning which makes predictions based on the values of current stock market indices by training on their previous values. Machine learning itself employs different models to make prediction easier and authentic. The project focuses on the use of Regression and LSTM based Machine learning to predict stock values. Factors considered are open, close, low, high and volume.

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 Keywords

Backpropagation, Hydropower, NEPSE, LSTM, Nepal Stock Exchange, Structured Query Language, Application Programming Interfac

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Solar cell, MPPT System, efficiency, PV Systems

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Mental Health of an individual is determined by not only the absence of mental illness, but also, how one feels about self and adjusts to life events. COVID-19 is the largest outbreak of uncommon pneumonia since the severe acute respiratory syndrome (SARS) which out broke in 2003. This pandemic not only affecting our physical health but have a huge impact on the mental health of all the age range people - child to old. This paper focus on the idea regarding how society and the authorities must thrive to provide extra care for safeguarding the mental health along with physical health of these classes.

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 Keywords

Mental Health, Covid - 19, Children, Elderly people, Health Workers

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Antenatal exercises aim at improving the physical and psychological well-being of an expected mother for labor and preventing pregnancy-induced pathologies by various physical means. Health professionals who care for pregnant women should discuss potential health benefits and harms of exercise. Although most pregnant women do not meet minimal exercise recommendations, there are a growing number of physically active women who wish to continue training throughout pregnancy. During the first trimester, pregnancy brings certain changes in the body for example: morning sickness, fatigue or low energy levels, nausea and increased secretion of the relaxin hormone. Exercise helps to overcome these changes and improves the mood and energy level of the mother. Healthy pregnant women should exercise for at least 150 min per week or 20-30 min everyday in moderate to vigorous aerobic intensity.

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 Keywords

Antenatal, pregnancy, hormone, prenatal, stretching

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Abstract Introduction:Thalassemia, a hereditary autosomal recessive disorder, imposes a major public health burden in an area known as thalassemia belt. Thalassemia belt extends from Mediterranean region to middle east and south east Asia. To avert the fiscal and social burden on health system, countries have devised and adopted preventive strategies. Although, WHO developed and disseminated a preventive strategy for prevention of hemoglobinopathies, including thalassemia, countries must adjust it according to the prevailing sociocultural determinants within countries. Objectives: This study aims to investigate acceptance of the preventive measures for thalassemia i.e. premarital counselling, prenatal diagnosis and abortion in existing body of literature. Furthermore, it seeks barriers towards successful implementation of these preventive approaches. Methodology:Online search engines (Google scholar and PubMed) were used for exploring related studies that meets the inclusion criteria. Studies conducted from 2000 onwards were illegible for the study. Result: With strictly following PRISMA methodology, 11 studies were included for the full-text reading from the total of 4097 articles. The results of studies varied widely; for instance, the acceptance of premarital counseling ranged from about 59% to 84% by different studies that had been investigated fully. Similarly, Acceptance of prenatal diagnosis was reported from 100% to as low as 74% by studies conducted in India. Conclusion: With the variations in the results of studies conducted in this area, further investigations are crucial to reflect the true acceptance of each of preventive approach. This will contribute in successful development of strategies that can halt the raising trend of thalassemia in India effectively.

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Key words: Thalassemia prevention, premarital counselling, prenatal diagnosis, Thalassemia parents.

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 Abstract

ABSTRACT Nowadays circular polarization is very important in the antenna design industry as it gives much more flexibility to the angle between transmitting & receiving antennas. Also it enhances weather penetration and mobility. It is widely used in commercial and militarily applications. In this project a broadband circularly polarized monopole antenna is designed and simulated using Ansys HFSS Software. This circular microstrip patch antenna with a asymmetrical slot at the centre resonates at 2.4GHz frequency. The slot is added to obtain the proper axial ratio. The antenna is designed on an FR4 substrate with dielectric constant ?r = 4.4. The height of the substrate is 1.6mm. Coaxial cable (or) probe feed is used for excitation. From simulation, the antenna characteristics such as return loss, radiation pattern and axial ratio are studied. The designed circular patch antenna shows return loss value of -15.16 dB at the designed frequency. The antenna gain is equal to 1.52 dB. The axial ratio is 0.57 dB (less than 3dB), which satisfies the required criteria for circular polarization

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Keywords: Circular polarization,Monopole Antenna,Axial ratio, Coaxial feed.

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Given two individuals and their casual association incorporates, our obligation is to expect which one is more influential. In our endeavor, we accumulate planning tests from Kaggle reliant upon human judgment. We use a couple of unmistakable models to make estimates, as Logistic Regression, SVM, Naive Bayes and. We similarly use some partner procedures like cross endorsement, incorporate assurance and data preprocessing. In the results region, we consider the shows of different models and give examination and thoughts to future works. We do different learning models using python

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 Keywords

SVM, NR, RF algorithm, Social network Dataset Process, Prediction

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Abstract - A problem faced in major metropolitan areas, is the search for parking space. In this paper, we proposed a novel way for automatic parking lot detection. In our approach, we first extract features by generating detection patches and building Gaussian ground model from input video frames. Then this model is used to train an eight-class multi-SVM classifier. Finally, the classification is optimized globally via applying Markov Random Field. Current systems detecting vacant parking spaces are either very expensive due to their hardware requirements or do not provide a detailed occupancy map. While several sensor types feature individual parking space surveillance, their installation and maintenance costs are relatively high. The system developed in this research group has minimal hardware requirements, which makes it less expensive and easy to install. At the same time, our video-based approach offers flexibility regarding information usage and site of operation.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Reduce time to parking. Easy to access parking areas

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Creative Commons Attribution 4.0 and The Open Definition