Biblical Proverbs and Tamil Proverbs- A Comparison

There are more than thousands of languages that are spoken all around the world. Communication through these languages unites individuals in the society. Due to this integration, the human race has discovered various fields and achieved many improvements. There are many elements of prosperity, science, culture and civilization in human life. All these are enhanced by language. Language is a factor in the development of human race. Similarly, the development of the human race is also a factor in the development of language. Hence there is no doubt that human life and language are inextricably intertwined. The development of a language depends largely on the vocabulary it contains. These words belong to various fields related to human life. Therefore, as the human civilization and culture develops, the vocabulary of the language increases. The development of language goes hand in hand with the development of human society. This is the main reason why the languages of the people who are rich in long- term culture, civilization, religious ideas, multi- disciplinary science, etc. are rich in vocabulary. Every feature of language is determined by society. Words are formed according to the needs of a society. Words related to human culture, civilization and arts are many in the language. Apart from this, most importantly, the exchange of ideas resulting from experience is the main reason for the birth of proverbs. For these proverbs the language must be refined and enriched. Such richness is possessed by high individual classical languages. Based on this, the purpose of this article is to compare the Tamil proverbs and the proverbs in the Bible which was written in Hebrew and Greek and translated into Tamil

The impacts of corporatisation of healthcare on medical practice and professionals in Maharashtra, India

A heterogeneous private sector dominates healthcare provision in many middle-income countries. In India the contemporary period has seen this sector undergo corporatisation processes characterised by emergence of large private hospitals and the takeover of medium-sized and charitable hospitals by corporate entities. Little is known about the operations of these private providers and the effects on healthcare professions as employment shifts from practitioner-owned small and medium hospitals to larger corporate settings. This article uses data from a mixed-methods study in two large cities in Maharashtra, India, to consider the implications of these contemporary changes for the medical profession. Data were collected from semi-structured interviews with 43 respondents who have detailed knowledge of healthcare in Maharashtra, and from a witness seminar on the topic of transformation in Maharashtra’s healthcare system. Transcripts from the interviews and witness seminar were analysed thematically through a combination of deductive and inductive approaches. Our findings point to a restructuring of medical practice in Maharashtra as training shifts towards private education and employment to those corporate hospitals. The latter is fuelled by substantial personal indebtedness, dwindling appeal of government employment, reduced opportunities to work in smaller private facilities, and the perceived benefits of work in larger providers. We describe a ‘re-professionalisation’ of medicine encompassing changes in employment relations, performance targets and constraints placed on professional autonomy within the private healthcare sector, that is accompanied by trends in cost inflation, medical malpractice, and distrust in doctor-patient relationships. The accompanying ‘re-stratification’ within this part of the profession affords prestige and influence to ‘star doctors’ while eroding the status and opportunity for young and early career doctors. The research raises important questions about the role that government and medical professionals’ bodies can, and should, play in contemporary transformation of private healthcare, and the implications of these trends for health systems more broadly

ARDUINO BASED WIRELESS MOBOT

Increased connectivity and remote monitoring and control mechanisms have revolutionized the field of measurement and automation. The proposed work is to design a system which will integrate a mobile bot with Arduino, and it is also possible with LabVIEW through a gateway to run wirelessly. An autonomous robot vehicle is to travel from source to destination through the wheels which are controlled by processor. This will be helpful launch in the application where human being travel will be difficult to meet the work. The proposed system will be able to follow a path with obstacle avoiding.Further, the vehicle can be integrated with NI instruments and with LabVIEW to make it autonomous. LabVIEW is a graphical programming language gives a platform for the engineers, which is effective and scalable to focus on robotics neglecting the minute implementation details.Â

Advancing drought monitoring, prediction and management capabilities

The India-UK Water Centre (IUKWC) promotes cooperation and collaboration between the complementary priorities of NERC-MoES water security research. This State of Science Water Brief was produced as an output of the IUKWC Science Workshop on Advancing Drought Monitoring, Prediction, and Management Capabilities

Comparison of thruster configurations in attitude control systems

Several aspects concerning reaction control jet systems as used to govern the attitude of a spacecraft were considered. A thruster configuration currently in use was compared to several new configurations developed in this study. The method of determining the error signals which control the firing of the thrusters was also investigated. The current error determination procedure is explained and a new method is presented. Both of these procedures are applied to each of the thruster configurations which are developed and comparisons of the two methods are made

EVALUATION OF SUPPLEMENTING HERBAL PRODUCT TO SOWS FOR IMPROVING LITTER WEIGHT AND REDUCING PIGLET MORTALITY

Objective: To examine the impact of the herbal product in improving litter weight, reducing piglet mortality and increasing milk production in sows.Methods: 20 sows which were in their late gestation period were randomly divided into two groups (n=10). Group T0 sows served as no treatment control group, and T1 group sows were supplemented with herbal galactagogue premix, Payapro (M/S Ayurvet Ltd., Baddi) administered for 5 d prior to farrowing and & 10 d post farrowing.Results: The analyses of result revealed that the postpartum milk yield (Approximately for 2 mo) was found to be increased in Payapro supplemented group (166 liters) in comparison to control group (103.5 liters). A significant reduction in mortality in Payapro supplemented group was evident at the time of weaning. Mean piglet weight was improved in the treatment group by 38.8%. Average litter size was also more in Payapro supplemented group (8.6) than the control group (7.7).Conclusion: Payapro premix can enhance the sow productivity in terms of milk production and number of. pigs produced per litter.Keywords: Galactogogue, Mean piglet weight, Average mortalityÂ

Mean platelet volume in patients with type 2 diabetes mellitus and its correlation across varying levels of albuminuria and HBA1c levels.

Diabetes mellitus is a syndrome of altered carbohydrate metabolism characterised by deficiency of endogenous insulin production or defect in insulin secretion or peripheral resistance to insulin actio

DRUNK & DRIVE DETERRENCE SYSTEM USING PIC18F542 MICRO CONTROLLER

An innovative low cost ‘Drunk & Drive Deterrence System’ is designed and implemented by tracking a vehicle with drunk drive from any location at any time. The system made good use of a popular technology that combines a smart phone application with a microcontroller. The in-vehicle device works using Global Positioning System (GPS) and Global System for Mobile Communication (GSM) technology for tracking the intended vehicles. A PIC18F542 microcontroller used to control the Sensors, GPS and GSM modules. The drunken state of the driver is detected by an onboard alcohol detector. The GSM module is used to transmit an ALERT and update the vehicle location to the designated android mobile of law enforcing agency.  The Google Maps API have been used to display the vehicle location on the map in the Smartphone application. Thus, the developed facility enables the law enforcing agency to track the vehicle with drunken driver easily using their android based mobile phones

Congestion Management Using an Optimized Deep Convolution Neural Network in Deregulated Environment

The technical issue of congestion, which is predominantly found in deregulated power systems, is caused by the failure of transmission networks to satisfy load power demands. This failure is primarily caused due to an increase in loads or loss of transmission lines or generators in modern restructured power networks. This work introduces a CM approach using Deep Convolution Neural Network (DCNN) for minimizing congestion and supporting Independent System Operators (ISOs). The purpose of the work is to generate enhanced prediction outputs for congestion management with reduced error values. These objectives were achieved through the actual power rescheduling of generators. The proposed work adopts DCNN which is optimized using an Improved Lion Algorithm (LA) and aids in providing significant outcomes for congestion management with reduced error. By implementing customized IEEE 57-bus, IEEE 30-bus, and IEEE 118-bus test systems, the suggested approach has been successfully verified for its performance on test systems of varied sizes. This analysis incorporates restrictions such as line loads, bus voltage influence, generator, line limits, etc. The most important results for the test system indicating convergence profile, congestion cost, and change in real-power and voltage magnitude are obtained by the simulation in MATLAB, and on the basis of the obtained simulation outcomes, it is evident that the proposed Improved Lion Algorithm optimized Deep Convolution Neural Network displays phenomenal computation performance in minimizing congestion losses at minimum congestion costs. When compared to several contemporary optimization techniques, the suggested technique performs better in terms of congestion cost and losses by generating improved prediction outputs with reduced errors

Imminent Rift Assortment Algorithm for Elevated Facet Data Using Wanton Collecting

Feature subset clustering is a powerful technique to reduce the dimensionality of feature vectors for text classification. In this paper, we propose a similarity-based self-constructing algorithm for feature clustering with the help of K-Means strategy. The words in the feature vector of a document set are grouped into clusters, based on similarity test. Words that are similar to each other are grouped into the same cluster, and make a head to each cluster data sets. By the FAST algorithm, the derived membership functions match closely with and describe properly the real distribution of the training data. Besides, the user need not specify the number of extracted features in advance, and trial-and-error for determining the appropriate number of extracted features can then be avoided. Experimental results show that our FAST algorithm implementation can run faster and obtain better-extracted features than other methods