In the past decade, the social networks platforms and micro-blogging sites such as Facebook, Twitter, Instagram and Sina Weibo have become an integral part of our day-to-day activities and is widely used all over the world by billions of users to share their views and circulate information in the form of messages, pictures, and videos. These are even used by government agencies to spread important information through their verified Facebook accounts and official Twitter handles, as it can reach a huge population within a limited time window. However, many deceptive activities like propaganda and rumor can mislead users on a daily basis. In this COVID times the fake news and rumors are very prevalent and are shared in a huge number which has created chaos in this tough time. And hence, the need of Fake News Detection it the present scenario is inevitable. In this paper, we survey the recent literature about different approaches to detect fake news over the Internet. In particular, we firstly discuss about fake news and the various terms related to it that have been considered in the literature. Secondly, we highlight the various publicly available datasets and various online tools that are available and cam debunk Fake News in real time. Thirdly, we describe fake news detection methods based on two broader areas i.e., it’s content and the social context. Finally, we provide a comparison of various techniques that are used to debunk fake news.

In recent years, the predictive model has seen an increase in volume thanks to the application of machine learning. The film business is still quite significant, as seen by the hundreds of new films that are produced each year. The likelihood of a film's commercial success can be influenced by a wide range of elements, including film critics, actors, directors, actresses, and composers, amongst others. Several writers have proposed or implemented several approaches and algorithms for forecasting the success of movies, including KNN, SVM, Naive Bayes Classifier, Logistic regression, random forest, and others. These approaches and techniques include: In this study, we give a literature review on the topic of predicting the Reviews of a movie by employing a variety of machine learning algorithms. We also make some recommendations for further research.

Hospitals and clinics are constrained to storing and analyzing medical data using traditional and manual methods. Many medical institutions have made significant efforts to overcome this limitation by combining considerable data resources with new technologies, there is still a lack of knowledge about diseases and how to treat them, despite the enormous number of data available. Machine learning and data-driven tactics can produce accurate diagnostic tools. The current study aims to identify and predict the heart disease at an early stage and saves the human life. In this paper, we used the machine learning based performance result evaluation and find the better prediction ratio for the heart disease.

The mobile ad-hoc networks is considered a group of wireless mobile nodes that are capable of communicating with each other without the use of network infrastructure or any centralized administration. A MANET have a large number of potential applications like tactical networks, emergency services, commercial and civilian environments, home and enterprise networking, education, entertainment, sensor networks, context aware servicing and coverage extension. In this paper, our proposed modified scheme “EA-DSR” simulate in network simulator 2.34. In simulation process we used 10, 20, 30 and 50 nodes. The evaluation of performance is measured by packet delivery ratio, End to end delay and packet throughput. Our proposed scheme EADSR gives good results in compare with existing DSR method.

In this paper a series voltage regulator is proposed which supports the output voltage during “sag and swell conditions” at the input. The input of the converter is single phase AC and the output is also single-phase AC with different voltage magnitude. The input voltage is modified with abnormalities like “sag and swell conditions”. The output voltage is stabilized by closed loop controller which maintains the voltage at certain level. A comparative analysis is carried out with PI and DSM-PI controllers for the generation of output voltage. Magnitude and THD comparisons are taken between these two techniques using FFT analysis tool available in MATLAB Simulink software. All the graphs of the input and conversion voltages of the converter are shown with respect to time.

A mobile ad hoc network (MANET) is a group of mobile nodes that communicate with each other without a central server or fixed infrastructure. In MANET, each node has a routing capability, but their mobility speeds are random, and due to this, it is difficult to find out the location of mobile nodes. This means that most of the energy of nodes is wasted in flooding. Energy is one of the important constraints in MANET because no source is available for battery charging if it discharges. The nodes with DREAM have a means of disseminating and collectively updating the location table entries for each other, behaving as a proactive protocol. In this paper, we propose a new Energy sustainable Location Dream Multipath Routing (EL-DMR). In this research, the AOMDV protocol is used with the location-aware Dream protocol to enhance the energy efficiency.

In this paper a fuzzy logic controller is integrated to shunt active power filter in proposed with harmonic compensation for reduction in THD. Shunt active power filter is the preeminent solution against nonlinear loads, current harmonics and power quality problems. APF topologies for harmonic compensation use numerous high-power rating components and are therefore disadvantageous. Hybrid topologies combining low-power rating APF withinductors and sets of LC PFs. The third leg of the three-phase VSI is removed by eliminating the set of power switching devices, thereby directly connecting the phase with the negative terminals of the dc-link capacitor. The proposed topology enhances the harmonic compensation capability and provides complete reactive power compensation compared with test system are analyzed using MATLAB Simulink software.

Wireless Sensor Networks (WSNs) are decentralized networks of sensors that can measure variables like temperature, wetness, humidity, and more. Applications for WSN can be found in a number of fields, including engineering, medicine, environmental monitoring, industrial automation, and military surveillance. WSN gathers data, processes it, and communicates with the base station via data transfer. Due to the extremely low battery capacity of WSN, energy efficiency is a constant problem. The life of a WSN shortens as a result of the energy consumption required to send a single piece of data from one node to another. Finding a way to lower energy consumption is thus difficult. Routing protocol then enters the picture. This paper discusses the Low Energy Adaptive Clustering Hierarchy (LEACH) routing system, which is a hierarchical-based routing mechanism that uses less energy and is regarded as the first energy-efficient routing protocol. Discussion also includes an analysis of LEACH's energy efficiency. In this paper, comparison of several energy efficiency techniques is also investigated.

The cooling fins permit the wind and air to transport the heat away from the engine. Low rate of heat transfer via cooling fins is the primary trouble in this kind of cooling. extended surfaces has its major significance in heat transfer and thermal management in internal combustion engine they plays a major role in performance of combustion engines, When fuel is burned in an engine, heat is produced. Additional heat is also generated by friction between the moving parts. Only approximately 30% of the energy released is converted into useful work while remaining 70% must be removed from the engine to prevent the parts from melting. In air-cooled I.C engine, extended surfaces called fins are provided at the periphery of engine cylinder to increase heat transfer rate. That is why the analysis of fin is important to increase the heat transfer rate. The main of aim of this work is to study various researches done in past to improve heat transfer rate of cooling fins

The huge amount of medical data generated by healthcare devices are large and complex to be analyzed by traditional methods. Data mining is used to improve the process by discovering patterns and features is large complex data. Several techniques have been presented to give accurate medical diagnose for various diseases. In this work, we present a literature work for heart disease prediction using data mining, machine learning, and classification techniques.