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The common difficulty present among the Indian farmers is that they don’t opt for the proper crop based on their soil necessities. Because of this productivity is affected. This problem of the farmers has been solved through precision agriculture. This method is characterized by a crop database collected from the farm, crop provided by agricultural experts and given to recommendation system it will use the collect data and do deep learning model as learners to recommend a crop for site specific parameter with high accuracy and efficiency. Objectives: The comprehensive objective of the model is to deliver direct advisory services to even the smallest farmer at the level of his/her smallest plot of crop, using the most accessible technologies using deep learning. It is a recommender model built using a classifier and an optimization of the classifier. Based on appropriate parameters, the system recommends crops as technology based crop recommendation system in agricultural decisions can be of great help to farmers in increasing their crop yields or cultivating suitable crops based on their land characteristics and climatic parameters. Methods: Existing MLTs (Machine Learning Techniques) have been found to be expensive and fail to scale in locally collected samples, so recent techniques of deep learning method is adopted in this work. With this motivation, historical data on crop productions and climate data is used in this work which is then pre-processed followed by predictions using a Modified DNN (Deep Neural Networks) and PSO (Particle Swarm Optimization) called PSO-MDNN for recommending crop cultivation. This work uses L2 regularizations for reducing weights in matrices assuming. Findings: This work proposed MDNN where the weight matrices are calculated with L2 regularization and PSO utilized to tune the hyper parameters of MDNN and its network structure to improve the prediction accuracy. Novelty: MDNN can produce to simpler models while working with weights that can be optimized through PSO. PSO-MDNN submodels produced from datasets and this proposed models gets adapted to data patterns if featuring datasets. This proposed work also exhibits promising outcomes in predicting crop yields using DLTs. Keywords: Crop recommendation system; Crop yield; Precision agriculture; Deep learning; Modified Deep Neural network and Particle Swam Optimization

Objectives: To introduce the technique which can ensure the accurate and reliable prediction of liver disease by adapting the deep learning technique. Methods: In this work Modified Convolutional Neural Network based Liver Disease Prediction System (MCNN-LDPS) is introduced for the accurate liver disease prediction outcome. In the proposed research work, Dimensionality reduction is carried out using Modified Principal Component Analysis. Optimal feature selection is carried out using Score based Artificial Fish Swarm Algorithm (SAFSA). In SAFSA algorithm, information gain and entropy values are taken as input values which proved accurate outcome. This research method has been analysed over Indian Liver patient dataset. Findings: The analysis of the research work proves that the proposed method MCNN-LDPS obtains better outcome in terms of increased accuracy, precision. Here comparison analysis proved that MCNN-LDPS obtains 4.05% increased accuracy, 21.23% F-measure, 4.22% precision and 34.26% recall. This research method has been compared with the existing Multi layer Perceptron Neural Network (MLPNN) for the performance analysis. Novelty: The major limitation of CNN is its inability to encode Orientational and relative spatial relationships, view angle. CNN do not encode the position and orientation of data. Lack of ability to be spatially invariant to the input data sample. This is resolved in this research work by combining the genetic algorithm with the CNN method. Keywords: Liver Disease Prediction; Feature Selection; Information Gain; Entropy; Convolutional neural network; Dimensionality Reduction

Primary open angle glaucoma is a progressive disease that is diagnosed and followed up over time on the basis of characteristic structural changes on the optic nerve head and functional changes in the visual fields with high intraocular pressure being a risk factor. Structural changes are captured with different modalities from fundus photography, optical coherence tomography (OCT) to scanning laser tomography. The relationship between function and structure is complex and provides clinically useful information at various stages in the natural history of the disease. The question today is how to integrate the structure and functional information to compliment the data to follow up the patients under care to preserve functional vision.

Glaucoma is a progressive disease and monitoring the visual function is crucial in prevention of visual disabilities that can impact quality of life. Monitoring progression helps in preserving performance of activities of daily living. Slowly progressing disease like glaucoma punctuated with inconsistent performance of visual field tests and media opacity over time shows visual function deficits that are difficult to interpret clinically. Good statistical software to monitor progression improves decision-making for therapeutic intervention since analyzing the series of visual fields is less time consuming and programmed to flag changes in the measured values which are displayed graphically.

Clinical perimetry measures the differential light sensitivity, which is a measure of the dimmest light stimulus seen by the patient against the illuminated background. Diagnostic information is enhanced by the program and strategy of the administered test that is built into the machine software. The visual function results need to be measured for reliability and reproducibility to be useful clinically for diagnostics and follow-up.

There have been no published recommendations for management of Low Risk Chest Pain in Emergency Departments across India. This is despite the fact that chest pain continues to be one of the most common presenting complaints in Emergency Departments. Risk stratification of patients utilizing an Accelerated Diagnostic Protocol has been shown to decrease hospitalizations by approximately 40% with a low 30 day risk of Major Adverse Cardiac Events. The Experts Group of Academic Leaders from the Indian College of Cardiology and Academic College of Emergency Experts in India partnered with Academic Experts in Emergency Medicine and Cardiology from leading Institutions in the UK and USA collaborated to study the scientific evidence and make recommendations to guide emergency physicians working in Emergency Departments across India.

Summary This study focuses on crack identification in beams from vibration measurements using principles of dynamic state estimation. The FEM is used to model the beam with cracked-beam elements that account for the presence of an edge crack under near-tip elasto-plastic conditions. The crack size and its location are treated as the variables that are identified using a particle filter algorithm. A parametric study is first carried out with synthetic measurements to numerically analyze the performance of the algorithm. Subsequently, using measurements acquired from physical experiments involving a cantilever beam subjected to arbitrary excitations, the proposed algorithm is used to identify the size and location of crack-like defects. The proposed method does not require measurements of the undamaged beam, hence, can be used for crack identification in beams for which no earlier measurements are available. Copyright © 2015 John Wiley & Sons, Ltd.

Endovascular aortic repair (EVAR) is the treatment of choice for patients with descending thoracic aortic aneurysm who are unfit for open surgery. We report a 50-year-old Asian woman who presented with a saccular symptomatic thoracic aortic aneurysm and underwent EVAR with a covered stent with prompt relief of symptoms and no residual complications at 1 year of follow up.

Background: Aortic pulse pressure is a significant marker of cardiovascular morbidity independently of mean blood pressure and pulse pressure of 60 mm Hg should be considered as the threshold at risk both in normotensives and hypertensives. Coronary perfusion is dependent on diastolic blood pressure and patients with CAD may be susceptible to the adverse effects of low diastolic blood pressure. This study conducted to examine the relation between central aortic pulse pressure and the prevalence and extent of CAD.Methods: A cross sectional, hospital-based study conducted in Sri Jayadeva Institute of Cardiovascular Sciences and Research, Bengaluru, among patients undergoing diagnostic coronary angiography.Results: Risk factors like Diabetes, Hypertension, Dyslipidemia and smoking rates were significantly higher in patients with PP of >60 mmHg (p60 mmHg, 4 patients had left main coronary artery (LMCA) disease, 20 patients had single vessel disease, 11 patients had two vessel disease and 20 patients had triple vessel disease.Conclusions: In this study it was demonstrated aortic pulse pressure of more than 60 mm Hg is associated with significant CAD.

In many patients with coronary artery disease, a low level of high-density lipoprotein cholesterol (HDL-C), rather than substantially elevated low-density lipoprotein cholesterol (LDL-C), is often the predominant lipid abnormality. Although the National Cholesterol Education Program treatment guidelines include HDL-C concentration as a major risk factor for primary prevention, the guidelines' emphasis on LDL-C as the primary target of therapy may cause uncertainty as to whether risk reduction strategies should focus on lowering LDL-C or raising HDL-C in high-risk patients with low HDL-C. Recent clinical trial evidence and epidemiologic data suggest that HDL-C should play a more important role in risk assessment, and that the definition of low HDL-C may need adjustment from the current National Cholesterol Education Program definition of35 mg/dL to perhaps40 mg/dL in men and45 mg/dL in women. Patients with low HDL-C should receive aggressive risk factor modification, and more emphasis on increasing HDL-C may be warranted in addition to lowering LDL-C. (c) 2001 by CHF, Inc.

There have been no published recommendations for the management of low-risk chest pain in emergency departments (EDs) across India. This is despite the fact that chest pain continues to be one of the most common presenting complaints in EDs. Risk stratification of patients utilizing an accelerated diagnostic protocol has been shown to decrease hospitalizations by approximately 40% with a low 30-day risk of major adverse cardiac events. The experts group of academic leaders from the Indian College of Cardiology and Academic College of Emergency Experts in India partnered with academic experts in emergency medicine and cardiology from leading institutions in the UK and USA collaborated to study the scientific evidence and make recommendations to guide emergency physicians working in EDs across India.

Background: Antiepileptic drug (AED) therapy following first unprovoked seizure is controversial. Aim: To study the patients' preferences towards AED therapy following first unprovoked generalized tonic clonic seizure (GTCS). Design: Prospective cohorts with one year follow-up study. Setting: Government teaching hospital, a tertiary care center. Materials and Methods: Patient cohort included patients with first attack of unprovoked GTCS within 30 days of onset, aged between 18-60 years and with normal brain CT scan. Counseling was done for all the patients and the relatives regarding seizure recurrence, duration and adverse effects of AED therapy if preferred. Patients were encouraged to make their own decision in preferring or deferring AED with reasons. They were followed up for one year. Results: Of the 73 enrolled (54 males and 19 females) 39 (53%) preferred to go on AED therapy. The reasons for preferring AED therapy were; (a) fear of seizure recurrence, 21 (54%); (b) risky occupation, 14 (36%); and (c) fear of injury, 4 (10%). The reasons for deferring were: (a) fear of adverse effects of long-term AED therapy, 19 (56%) and (b) preferring to wait for the second attack, 15 (44%). All the patients were happy about being involved in the decision-making. Conclusion: Following first attack of unprovoked GTCS the decision regarding AED therapy may be taken by the patients and their family members after adequate counseling and such decisions have more relevance from their perspective.

Objective: To evaluates the physical growth and psychomotor development of infants born to women with epilepsy on regular Anti Epileptic Drugs (AEDs). Setting: Govt. Stanley Medical College and Hospital, Tertiary care referral centre, Chennai. Design: Open prospective cohort study with a control group. Materials and Methods: Consecutive women with epilepsy who were on regular anticonvulsants were followed up from their first trimester. Their babies were examined at birth and anthropometric measurements including anterior fontanelle size were noted. They were followed up till one year and periodically evaluated at 1st, 6th and 12th month of age. Development testing using Griffith scale was done at 2nd, 6th and 12th month. An equal number of control babies were also studied using the same scale for one year at the specified intervals. The results in both the groups were compared. Results : 30 babies were enrolled in the case and control group. The AEDs received by the mothers with epilepsy were Phenytoin, Carbamazepine, and Sodium valproate. At birth and 1st month the weight, head circumference and length of case and control babies were equal. At 6th and 12th month reduction in the above 3 parameters were noted in the case babies ( P

Aim : To study the clinical features, precipitating stressful life events and prognosis of nonepileptic attack disorder (NEAD) among married women. Design: Prospective cohort study with 1-year follow-up. Setting: A tertiary care teaching hospital. Subjects: Of the 1020 patients with epilepsy referred to the epilepsy clinic during 2002-2003, 30 were married women with NEAD. Materials and Methods: The diagnostic criteria for NEAD included normal EEG during ictal and post-ictal phase of the generalized 'attack.' The data collected included clinical characteristics, semiology of the attacks, precipitating stressful events, and co-morbid psychiatric disorders. The control group included 30 age-matched married women with generalized tonic-clonic seizures. The long-term outcome and factors influencing the outcomes were analyzed. Results: The mean duration of illness was 18 months, and the pattern of the attack was 'fall and lying still' in 53% and 'fall with generalized motor movements' in 47%. The frequency was one or more per week in 57% and occasionally in 43%. The important stressful events were matrimonial discord following illegal relationship of the husband with another woman (c2 = 9.02, P = 0.003) and constant quarrel with other family members (c2 = 5.19, P = 0.02). The prevalence of sexual abuse was low (7%). Co-morbid psychiatric disorder was observed in 70%. At the end of 1 year, 39% were free from the attack. Resolution of the stressful life events (c2 = 4.52, P = 0.03) and lower frequency of attack at the time of reporting (c2 = 3.88, P = 0.05) correlated with good outcomes. Conclusion : Among patients with NEAD in India, the major precipitating factors were matrimonial discord following illegal relationship of the husband with another woman and constant quarrel with other family members and not sexual abuse. Women with low frequency of attack at the time of reporting and the remission of the stressful events had better outcomes.

A new scheme is proposed for the detection of premature ventricular beats, which is a vital function in rhythm monitoring of cardiac patients. A transformation based on the first difference of the digitized electrocardiogram (ECG) signal is developed for the detection and delineation of QRS complexes. The method for classifying the abnormal complexes from the normal ones is based on the concepts of minimum phase and signal length. The parameters of a linear discriminant function obtained from a training feature vector set are used to classify the complexes. Results of application of the scheme to ECG of two arrhythmia patients are presented.

Homomorphic analysis and pole-zero modeling of electrocardiogram (ECG) signals are presented in this paper. Four typical ECG signals are considered and deconvolved into their minimum and maximum phase components through cepstral filtering, with a view to study the possibility of more efficient feature selection from the component signals for diagnostic purposes. The complex cepstra of the signals are linearly filtered to extract the basic wavelet and the excitation function. The ECG signals are, in general, mixed phase and hence, exponential weighting is done to aid deconvolution of the signals. The basic wavelet for normal ECG approximates the action potential of the muscle fiber of the heart and the excitation function corresponds to the excitation pattern of the heart muscles during a cardiac cycle. The ECG signals and their components are pole-zero modeled and the pole-zero pattern of the models can give a clue to classify the normal and abnormal signals. Besides, storing only the parameters of the model can result in a data reduction of more than 3:1 for normal signals sampled at a moderate 128 samples/s.