733 research outputs found
Impact of fiscal policy shocks on the Indian economy
Impact of Fiscal Policy Shocks on the Indian Economy Swati Yadav , V.Upadhyay , Seema Sharma Abstract In this paper, we analyse the impact of fiscal shocks on the Indian economy using structural vector autoregression (SVAR) methodology. The study uses quarterly data for the period 1997Q1 to 2009Q2. Two different identification schemes have been used to assess the effects of shocks to government spending and tax revenues on output. The recursive scheme is based on the Cholesky decomposition and the second identification scheme Blanchard & Perrotti (1999) technique of using information on tax system to identify the SVAR model. We find that the impulse responses obtained from both identification schemes behave in a similar fashion but the value of multipliers differs. Also the shock to tax variable has a bigger impact on GDP than the government spending shock. In the extended four variable VAR model the effects of fiscal shocks on private consumption has been assessed using the recursive identification scheme. Findings indicate that the tax variable has larger impact on private consumption as compared to the government spending variable. In the short run the impact of expansionary fiscal shocks follow Keynesian tradition but the long run response is mixed.SVAR, Fiscal shocks, Multipliers
Detecting Sentiments from Movie Reviews by Integrating Reviewers Own Prejudice
Presently, sentiment analysis algorithms are widely used to extract positive or negative feedback scores of various objects on the basis of the text/reviews. But, an individual may have a certain degree of biasness towards a certain product/company and hence may not objectively review the object. We try to combat this biasness problem by incorporating the positive and negative bias component in the existing sentiment score of the object. This paper proposes several algorithms for a new system of implementing individual bias in the corpus of data i.e. movie reviews in this case. Each review comment has an unadjusted sentiment score associated with it. This unadjusted score is refined to give an adjusted score using the positive and negative bias score. The bias score is calculated using certain parameters, the weightage of which has been determined by conducting a survey. We lay emphasis on the degree of biasness an individual has towards or against the review parameters for the movie reviews corpus namely actor, director and genre. We equip the system with the capability to handle various scenarios like positive inclination of the user, negative inclination of the user, presence of both positive and negative inclination of the user and neutral attitude of the user by implementing the formulae we developed
DUAL BAND MIMO ANTENNA FOR LTE, 4G AND SUB–6 GHZ 5G APPLICATIONS
In this manuscript, a compact MIMO antenna for wireless application has been presented. The proposed antenna consists of the F-shaped radiator with the circular slot in the center and a rectangular ground plane on the other side of the substrate. The proposed antenna has the overall size of 48 × 48 mm2. The antenna is designed to work on two frequency bands - from 1.5 to 2.3 GHz, and 3.7 to 4.2 GHz, having the resonating frequency of 1.8 GHz and 3.9 GHz respectively. The diversity performance of the antenna is also observed by using a variety of parameters like envelop correlation coefficient (ECC), Diversity Gain (DG), Total Active Reflection Coefficient (TARC), etc. The value of ECC is 0.02, which shows good diversity performance of the antenna. In order to validate the simulated and measured results, the proposed antenna has been fabricated and shows good agreement with the each other
THE POSITIVE EFFECTS OF PRATIMARSHA NASYA W.S.R. TO SLEEP PHYSIOLOGY
Study was planned to preventively deal with sleep disturbances which are waiting to become public health problem. As much as 30% individuals among apparently healthy individuals in India suffer from occasional insomnia. Ayurveda classics offered a solution by use of Pratimarsha Nasya as daily regimen to improve sleep quality. Anu taila is best used for Nasya Karma, so was chosen as medicine for this clinical observational study. Material and methods- 28 subjects were selected randomly and every evening two drops Anu taila in each nostril was administered for 3 months. Result- Significant improvement was found on PSQI, ESS sleepiness scale as well as self developed Sukhnidra Sukhprabodham scale. For self developed sleep quality assessment scale, null scores were present in the enrolled subjects with Baseline mean + SD 0.00 + 0.00 and gradual increase across subsequent intervals. Mean + SD after Trial is 14.54 +1.97. So subjects showed significant response to Pratimarsha nasya with p value <0.0001 and Z value 4.647. Conclusion- Overall sleep quality is more improved after administration of pratimarsha nasya, different components of sleep quality considered viz. getting to sleep, quality of sleep, awake following sleep, behaviour following wakening all are positively changed. Pratimarsha nasya has such a vast positive effect on physiology of sleep that it deserves to be incorporated in daily regimen and can be called as “two drops for well-being of Urdhvajatru”
Antihyperlipidemic potential of herbals
One of the most widespread diseases in the world is Coronary Heart Disease (CHD). It is also one of the most preventable. This review explores the management of CHD through changes in dietary modifications, lifestyle, and the use of dietary supplements and botanical
Project Awakesure: Intelligent Drowsiness Detection Using Eye Tracking
Being sleepy or drowsy is referred to as being drowsy. A person who is sleepy may feel exhausted or lethargic and struggle to stay awake. People who are sleepy tend to be less attentive and may even nod off, though they can still be awakened. An increasing number of vocations nowadays call for sustained focus. In order for drivers to respond quickly to unexpected incidents, they must maintain a watchful eye on the road. Many road incidents are directly caused by tired drivers. In order to drastically lower the frequency of fatigue-related auto accidents, it is crucial to develop technologies that can identify and alert a driver to a poor psychophysical state. However, there are many challenges in developing systems that can quickly and accurately recognize a driver's signs of fatigue. Using vision-based technology is one technological option for implementing driver fatigue monitoring systems. The available driver drowsiness detection systems are described in this article. Here, we are assessing the driver's level of sleepiness utilizing his visual system. The automated system for preventing accidents and monitoring sleepy drivers developed for this study is based on detecting variations in the length of eye blinks. Our recommended technique makes use of the eyes' postulated horizontal symmetry property to identify visual changes in eye positions. Our novel approach precisely positions a standard webcam in front of the driver's seat to identify eye blinks. It will identify the eyeballs based on a specific EAR (Eye Aspect Ratio)
Comparison of ease of insertion, visibility of strings and continuation rate of post-partum intrauterine copper device insertion by long inserter versus with the help of Kelly’s forceps
Background: The objective of the study was to compare ease of insertion, visibility of strings and continuation rate of post-partum intrauterine copper devices (PPIUCD) insertion by long inserter versus with the help of Kelly’s forceps.Methods: 100 women were enrolled in our study which was conducted in department of obstetrics and gynecology, Subharti medical college and Chattrapati Shivaji Subharti hospital (CSSH), Meerut over a period of 2 years between November 2018 and August 2020. In study comparison was done on insertion technique of PPIUCD.Results: High fundal placement was achieved with long inserter. There was no perforation and decreased infection rate among the users with no increase in incidence of side effects and expulsion. Among 50 insertion, 1 woman (2%) had partial expulsion, 2 women (4%) had complete expulsion and 1 woman (2%) got PPIUCD removed on request. Providers reported 100% easier technique. 96% satisfaction among the users.Conclusions: The dedicated long inserter PPIUCD was found to be safe, with high acceptability among the participants and providers. Study revealed the reduced risk of infection and expulsion, providers also reported increased convenience in insertion compared to standard PPIUCD insertion techniques
Peer-to-Peer File Sharing WebApp: Enhancing Data Security and Privacy through Peer-to-Peer File Transfer in a Web Application
Peer-to-peer (P2P) networking has emerged as a promising technology that enables distributed systems to operate in a decentralized manner. P2P networks are based on a model where each node in the network can act as both a client and a server, thereby enabling data and resource sharing without relying on centralized servers. The P2P model has gained considerable attention in recent years due to its potential to provide a scalable, fault-tolerant, and resilient architecture for various applications such as file sharing, content distribution, and social networks.In recent years, researchers have also proposed hybrid architectures that combine the benefits of both structured and unstructured P2P networks. For example, the Distributed Hash Table (DHT) is a popular hybrid architecture that provides efficient lookup and search algorithms while maintaining the flexibility and adaptability of the unstructured network.To demonstrate the feasibility of P2P systems, several prototypes have been developed, such as the BitTorrent file-sharing protocol and the Skype voice-over-IP (VoIP) service. These prototypes have demonstrated the potential of P2P systems for large-scale applications and have paved the way for the development of new P2P-based systems
MACHINE LEARNING ASSISTED OPTIMIZATION AND ITS APPLICATION TO HYBRID DIELECTRIC RESONATOR ANTENNA DESIGN
Machine learning assisted optimization (MLAO) has become very important for improving the antenna design process because it consumes much less time than the traditional methods. These models' accountability can be checked by the accuracy metrics, which tell about the correctness of the predicted result. Machine learning (ML) methods, such as Gaussian Process Regression, Artificial Neural Networks (ANNs), and Support Vector Machine (SVM), are used to simulate the antenna model to predict the reflection coefficient faster. This paper presents the optimization of Hybrid Dielectric Resonator Antenna (DRA) using machine learning models. Several regression models are applied to the dataset for optimization, and the best results are obtained using a random forest regression model with the accuracy of 97%. Additionally, the effectiveness of machine learning based antenna design is demonstrated through comparison with conventional design methods
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