Technical Efficiency of Maize Production in Fluoride Affected Locales, Tamil Nadu: A Stochastic Frontier Approach

To estimate the technical efficiency of maize production among fluoride affected and non affected locales of Tamil Nadu. A multi-stage sampling method involving a combination of purposive and random sampling procedures was employed in drawing up the samples for collecting primary data. The sample size is about 120. Stochastic frontier production function is used to estimate technical efficiency of maize. The result of stochastic frontier production function indicated that FYM, Potassium, machine power, irrigation and management index have significant influence on yield of maize in less fluoride affected locale, while, seed rate, nitrogen, phosphorous, machine power and irrigation are significantly influence the yield of maize in moderately fluoride affected locale, in case of highly fluoride affected locale, seed rate, nitrogen, phosphorous, potassium and irrigation are significantly influencing the yield of maize, while, nitrogen, potassium, irrigation and management index are significantly influences the yield of maize in non affected locale. The study suggests that awareness of fluoride contamination and averting measures must be disseminated to the farmers

An Impressive Method to Get Better Peak Signal Noise Ratio (PSNR), Mean Square Error (MSE) Values Using Stationary Wavelet Transform (SWT)

Impulse noise in images is present because of bit errors in transmission or introduced during the signal acquisition stage. There are two types of impulse noise, they are salt and pepper noise and random valued noise. In our proposed method, first we apply the Stationary wavelet transform for noise added image. It will separate into four bands like LL, LH, HL and HH. The proposed algorithm replaces the noisy pixel by trimmed median value when other pixel values, 02019;s and 2552019;s are present in the selected window and when all the pixel values are 02019;s and 2552019;s then the noise pixel is replaced by mean value of all the elements present in the selected window. This proposed algorithm shows better results than the Standard median filter (MF), decision based algorithm (DBA). The proposed method performs well in removing low to medium density impulse noise with detail preservation up to a noise density of 70% and it gives better Peak signal-to-noise ratio (PSNR) and mean square error (MSE) values

Developing New Drug Antagonist for Alpha Adrenergic Receptors for Hypertension Diseases

Alpha-adrenergic receptors play a vital role in the regulation of blood pressure(BP). Hypertension referred as blood pressure above the normal range. hyper tension can cause severe complications such as stroke, coronary heart disease and kidney failure. Phentolamine is a potential antagonist for a. Alpha-adrenergic receptor. New phentolamine derivatives will be developed through FEP (Free Energy perturbation) methods. AMBER Force fields will apply for energy Calculation. Molecular modeling includes energy minimization, molecular dynamics, mounte-carlo simulations and QSAR properties will be performed for all phentolamine analogs. The interactions studies between alpha - adrenergic Receptor and Phentolamine analogs in solvent mode and protein complex mode will be performed. The best antagonist for alpha-Adrenergic Receptor will be identified

Implementing Sequential Prefixspan Algorithm by Using Static Load Balancing

Repeated series mining is well known and well studied trouble in information mining. The productivity of the formula is used in several alternative regions like chemistry, bioinformatics, and market basket analysis. A completely unique parallel algorithmic rule for mining of frequent sequences supported a static load-balancing is planned. The static load balancing is done by measure the machine time using a probabilistic algorithm. For cheap size of instance, the algorithms deliver the good speedups. The conferred approach is extremely universal: it is often used for static load-balancing of alternative pattern mining algorithms like item set/tree/graph mining algorithms

Improving Prediction Accuracy Results by Using Q-Statistic Algorithm in High Dimensional Data

Classification problems in high dimensional information with little sort of observations became furthercommon significantly in microarray information. The increasing amount of text data on internet sites affects the agglomerationanalysis. The text agglomeration could also be a positive analysis technique used for partitioning a huge amount of datainto clusters. Hence, the most necessary draw back that affects the text agglomeration technique is that the presenceuninformative and distributed choices in text documents. A broad class of boosting algorithms is known as actingcoordinate-wise gradient descent to attenuate some potential performs of the margins of a data set. This paperproposes a novel analysis live Q-statistic that comes with the soundness of the chosen feature set to boot to theprediction accuracy. Then we've a bent to propose the Booster of associate degree FS algorithm that enhances theworth of the Q-statistic of the algorithm applied

Secured Aggregation for Privacy and Efficiency in Energy in WSN

The proposed system in WSN’s have many applications in critical secured areas, mostly in military applications, since it hides data using many nodes from third parties. The existing techniques uses hop by hop based protocols which does not provide efficiency in energy, due to which it may reveals large amount of data to the adversaries. There by loses its confidentiality of data. The proposed technique is best suited to overcome the constraints of the existing system. This uses end to end encryption which aggregates the encrypted data and sends to the base station, which provide a complete security, data freshness, confidentiality. Because of the aggregation of the encrypted data it reduces the energy consumption

Diabetic eye screening in multi ethnic population of Malaysia: epidemiological risk factors for development of diabetic retinopathy

Background:The objective of this study is to evaluate epidemiological risk factors for development of diabetic retinopathy.Methods:The cases of type-2 diabetes mellitus attending Melaka Manipal medical college, Malaysia were retrospectively reviewed. The epidemiological characteristics of diabetic retinopathy were estimated. The cases were graded according to degree of retinopathy in to: non-diabetic retinopathy group and diabetic retinopathy. Clinical and biochemical studies were used for studying the risk factors associated with development of retinopathy.Results:The prevalence of diabetic retinopathy in the population was 21% in known diabetic subjects and was significantly higher in men than in women (21.3% vs. 14.6%) with increasing age and duration of diabetes. Ethnicity is a complex, independent risk factor for diabetic retinopathy. Sight threatening diabetic retinopathy, and clinically significant macular edema was higher in people of Malaysia (20%) when compared with Chinese (16%) and Indonesians (12%). In all, 55 percent of patients with known diabetes mellitus had never undergone an eye examination. Among patients who had undergone eye examinations, 32.8 percent had the last examination within the last one year, 49.8 percent within the last one to two years, and 17.4 percent more than two years ago.Conclusion:Diabetic retinopathy is highly prevalent in the patients with type-2 diabetes mellitus in Malaysia. Besides blood glucose, many factors are associated with the present and development of diabetic retinopathy.

UV SPECTROPHOTOMETRIC METHOD DEVELOPMENT AND VALIDATION FOR THE SIMULTANEOUS QUANTITATIVE ESTIMATION OF MEBEVERINE HYDROCHLORIDE AND CHLORDIAZEPOXIDE IN CAPSULES

Objective: To develop a simple and cheap UV spectrophotometric method for the simultaneous quantitative estimation of Mebeverine hydrochloride (135mg) and Chlordiazepoxide (5mg) in MEVA C Capsules and validate as per ICH guidelines. Methods: The optimized method uses a diluent 100% Triethylammonium phosphate buffer (pH 3.0) for the estimation of assay of Mebeverine hydrochloride and Chlordiazepoxide in Capsules which are analyzed at a detection wavelength of 260nm. Results: The developed method exhibited linearity in the range of 10-40μg/ml for Mebeverine hydrochloride and 2.5-10μg/ml for Chlordiazepoxide. The precision for Mebeverine hydrochloride and Chlordiazepoxide is exemplified by relative standard deviation of 0.499% and 1.75 respectively. Percentage Mean recovery for Mebeverine hydrochloride and Chlordiazepoxide were found to be in the range of 98â€102, during accuracy studies. The limit of detection (LOD) for Mebeverine hydrochloride and Chlordiazepoxide were found to be 321ng/ml and 3.7ng/ml respectively, while limit of quantitiation (LOQ) for Mebeverine hydrochloride and Chlordiazepoxide were found to be 973ng/ml and 11.2ng/ml respectively. Conclusion: A simple and a cheap UV spectrophotometric method was developed and validated for the simultaneous quantitative estimation of Mebeverine hydrochloride and Chlordiazepoxide in capsules as per ICH guidelines and hence it can be used for the routine analysis in various pharmaceutical industries

Development of smart Sorting and counting machine for industrial application

This work aims to implement industrial automation landscape by developing efficient systems to connect disparate machines and devices in an industrial environment. By creating an automated, centralized platform accessible via the internet, users can control and monitor all machines in the industry from one place. This work particularly focusses on the conveyor belt application in industry and the implementation of Industry 4.0 in Industries. To achieve this, Cyber-Physical Systems (CPS), Internet of Things (IoT) and Internet of Services technologies are used. These technologies enable efficient operation and monitoring of conveyor systems, ultimately leading to increased productivity, reduced downtime and increased safety. The proposed system provides real-time data for decision-making and optimization, ultimately paving the way for the future of Industry 4.0 in the conveyor belt industry. IoT and Industrial automation is the technology that can be utilized to reduce human interventions and manual overhead in the system to monitor as well as to indicate any errors in the system. Artificial Intelligence could also be used to control and monitor the industry. IoT is not a technology basically it is an ecosystem with Industry Specific Implication. In many Industries monitoring of belt conveyor application is manual with an operator, particularly for sorting application based on color, shape and size of the object. Industry 4.0 leans towards the use of sensor and internet of things to achieve these functions with no errors. This work is an effort made to realize the  use of IoT and Industry 4.0 for sorting and counting application in an industrial environment like conveyor belt applications