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Farming profitability is something on which economy profoundly depends. This is the one reason that sickness recognition in plants assumes a critical job in farming field, as having infection in plants are very common. In the event that legitimate consideration isn't taken here, it causes genuine consequences for plants and because of which particular item quality, amount or profitability is influenced. This paper displays an algorithm for image segmentation technique which is utilized for automatic identification and classification plant leaf infections. It additionally covers review on various classification techniques that can be utilized for plant leaf ailment discovery. As the infected regions vary in length it is difficult to develop a feature vector of identical finite length representing all the sequences. A simple method to go around this issue is given by Recurrent Neural Networks (RNN). In this work we separate a feature vector through the use of Long Short-Term Memory (LSTM) recurrent neural networks. The LSTM network recursively repeats and concentrates two limited vectors whose link yields finite length vector portrayal.

BACKGROUND: In developing countries, the recent increase in computer-related work has considerably increased the occupational complaint of pain. OBJECTIVE: To examine the effects of workstation design, posture and ergonomic awareness on the prevalence of pain for a year in the upper part of the body (eyes, hands, arms, shoulders, lower back, and upper back) among IT professionals in India. METHOD: To investigate the association of risk factors with the prevalence of pain in different body parts, a newly designed online questionnaire titled “A Questionnaire based on ergonomics for IT Professionals” was developed. The psychometric properties of this questionnaire were tested. 110 computer office workers were recruited from IT companies from major cities in India. RESULTS: The confirmation of reliability and lack of redundancy of items was provided by the calculation of internal consistency (Cronbach’s alpha 0.804) and cross-validation. 60% of participants was male. Mean age was 29.73±6.09 years. The prevalence of pain for a year in the upper part of the body was 38.2%. The frequently reported pains were in the neck (22.7%), lower back area (22.7%), and eye strain (21.8%). CONCLUSION: It was identified that long working hours, excessive usage of smartphones, lack of exercise, incorrect workstation adjustments, and incorrect posture were the risk factors for the prevalence of pain.

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