Disease prediction has the potential to benefit stakeholders such as the government and health insurance companies. It can identify patients at risk of disease or health conditions. Clinicians can then take appropriate measures to avoid or minimize the risk and in turn, improve quality of care and avoid potential hospital admissions. Due to the digitalization of data in each and every domain it is becoming tedious to store and analysis. So, the demand of proficient algorithms for health care data analysis is also increasing. Machine learning is a subfield of Artificial Intelligence that allows a computer system to learn from the environment, through re-iterative processes and improve itself from experience. Here we present the review work for the diseases detection using the data mining and machine learning techniques.

Conventionally, the major part of electrical power was consumed by linear loads, which carry the sinusoidal current in proportion to supply voltage. However majority of these linear loads is phase displaced with respect to the supply voltage resulting in low power factor. In recent years, the application of power electronics has grown tremendously. These power electronics systems offer highly non-linear characteristics and draw non sinusoidal current from utility, causing harmonic pollution into supply system. Increase in such non-linearity results in undesirable features such as distortion of supply voltage, low system efficiency and a poor power factor. They also cause disturbance to other consumers and interference in nearby communication networks. To overcome these problems, active power filters have been developed. In this work both PI controllers based , three-phase shunt active power filter to compensate harmonics and reactive power by nonlinear load to improve power quality is implemented for three-phase three wire systems. MATLAB simulation model has been developed to simulate the system operation. Various simulation results are presented under steady state conditions and performance.

The progressing mechanical improvement in the car business has since incited the development in ecological and vitality productivity mindfulness. Electric vehicles (EVs) are believed to be likely options for traditional inner ignition motor (ICE) vehicles as they have various favorable circumstances. In this paper, the difficulties and chances of EVs in mass market arrangement are assessed. This proposal presents a review of the various sorts of half breed electric vehicle structures and fundamental rules with respect to selection of parts. The reproduction model of a half breed electric vehicle was made for this proposal to research the effect on eco-friendliness comparable to moving obstruction coefficient and vehicle weight. Despite the fact that the model isn't intended for ideal motor activity, the outcomes demonstrate that lower moving opposition coefficient and lower vehicle weight prompts diminished fuel utilization. Proposed upgrades to the reproduction configuration are introduced in the report.

The Cloud figuring condition and its engineering can store and procedure client logical questions In this way protection safeguarding area concealing methodology with blowfish calculation over the stage is acted in the base paper which doesn't include client private area goal and in this way not gives security over the client individual personality partner with its area. A shared validation approach is acted in the proposed work, which causes clients to speak with the cloud any number of times. A shared security convention required from the cloud end to demonstrate their authenticity. Secure correspondence is exceptionally required and is acted in the proposed calculation. Safeguard the security of the information. SPYSECUREOU (Secure Documents Care Owner and User) information, which contains individual data of the client, is put away in a re-appropriated condition. Here the endorsement of the data is checked by the information proprietor or a TPA—outsider inspecting utilizing Secure Hash Algorithm (SHA2) which work alongside the Hyper Elliptic Curve Cryptosystem which is an encryption strategy for the information which utilize various stages, change, and worldview identified with information in paired structure gives high security in low calculation time. To protect the security of that information is the principal target of this thesis. The strategy likewise displays information shared proficiency in remark (Data posting) stage and getting to the stage. A further augmentation of the work can be quitting in giving productivity with the encryption model.

The disconnection of hate speech from specific pieces of the hostile language has gotten one of the fundamental issues during the investigation of detest talk in online life. Lexical disclosure strategies, as a rule, are not exactly viable, in light of the fact that they don't comprehend the two gatherings in any message containing specific words as detest as a discourse. In this proposition, swarmed detest discourse vocabularies were created to gather tweets containing terms of despising discourse additionally dimensionality decrease approach is utilized to improve the accuracy of degree. This work has characterized tweets into three classifications: those containing detest discourse, hostile language, and those not with either. We are preparing to perceive these various characterizations in a multi-class grouping. The calculation of ordered relapse by a dimensionality decrease approach has been actualized with 83% exactness, which is better than other existing calculations like 71.33% of Naïve Bayes and 80.56% of SVMs.

In this exploration, the investigation of various and the best model and set of highlights to anticipate the fame of online posts, utilizing AI systems are given. The data begins from Mash able, a prominent online website, with 39644 articles with sixty condition properties and one choice characteristic. Subsequently, it is intriguing and important to utilize AI strategies to foresee the notoriety of online news stories. Different works have been done in the expectation of online news ubiquity. The prominence of news relies on different highlights like sharing of online news through social networking media, statements of guests for news, likes for news stories, and so on. Highlight choice techniques are utilized to improve execution and decrease highlights. In this examination work, include a decrease is proposed by improved molecule swarm streamlining calculation which produces effective highlights for a proficient expectation of the fame of online distributed news. A further irregular backwoods classifier is utilized to arrange the dataset into famous and disagreeable classifications. The outcome examination is performed for a paired arrangement with 32 characteristics just as 18 qualities and contrasted and existing work and discovered an upgrade of about 1% and 2% in precision individually. This exploration work is likewise reached out for the multi-classification of online news fame utilizing diminished highlights.

In the computer’s world these days cloud computing plays a very important role. It gives user facilities like a group of things such as software, platform, and infrastructure services. Virtualization is the backbone of cloud resource sharing. Security is also a main problem in the cloud. Multiple users have their perceptions related to the cloud. By using cloud computing, users can access resources anywhere by using the internet. So this technique is very useful in a user’s daily life. One of the factors for cloud computing is cloud services which were provided by the cloud (IAAS, PAAS, and SAAS). These services enable users to access infrastructure, platform, and software. Even resources are allocated to users according to their requirements. But many people think it is unsafe to use cloud resources and its services. It is unsafe to use the cloud because there is no guarantee of information which is controlled or maintained by the vendors. Some security issues are noticed in cloud computing. In this paper, we have discussed a few issues with cloud computing and the challenges of cloud computing. This paper gives an overall investigation of security on data, protection, and issues in the cloud. The paper also defines the literature review related to cloud computing issues and threats and also the various security concerns are discussed.

Social media platforms provide an inexpensive communication medium that allows anyone to quickly reach millions of users. Consequently, in these platforms, anyone can publish content, and anyone interested in the content can obtain it, representing a transformative revolution in our society. However, this same potential of social media systems brings together an important challenge—these systems provide space for discourses that are harmful to certain groups of people. This challenge manifests itself with several variations, including bullying, offensive content, and hate speech. Specifically, authorities of many countries today are rapidly recognizing hate speech as a serious problem, especially because it is hard to create barriers on the Internet to prevent the dissemination of hate across countries or minorities. In this paper, we provide the first of a kind systematic large scale measurement and analysis study of hate speech in online social media. We aim to understand the abundance of hate speech in online social media, the most common hate expressions, the effect of anonymity on hate speech, and the most hated groups across regions. This survey organizes and describes the current state of the field, providing a structured overview of previous approaches, including core algorithms, methods, and main features used.

Social media comprises interactive applications and platforms for creating, sharing, and exchange of user-generated contents. The past ten years have brought huge growth in social media, especially online social networking services, and it is changing our ways to organize and communicate. It aggregates opinions and feelings of diverse groups of people at a low cost. Mining the attributes and contents of social media allows us to discover social structure characteristics, analyze action patterns qualitatively and quantitatively, and sometimes the ability to predict future human-related events. In this paper, we firstly discuss the realms which can be predicted with current social media, then overview available predictors and techniques of prediction, and finally discuss challenges and possible future directions. Our work can help online news companies to predict news popularity before publication.

In this paper a hybrid active power filter is introduced for harmonic filtration in a transmission system with sources and loads. The harmonics which are generated by non-linear loads (diode bridge rectifier) are introduced into the source voltage and currents which could also be injected into other loads connected to the system. These harmonics are eliminated using a series active power filter which is connected to the transmission line through series transformers which eliminates harmonics in the source voltage and currents. Along with the series active power filter a passive filter is also connected to eliminate lower order harmonics, whereas the series active power filter eliminates lower order harmonics. The controller of the series active power filter is updated with fuzzy logic controller for faster Response rate to the transients caused in the proposed system. A harmonics comparative analysis is carried out on the source current with PI and fuzzy logic controllers using FFT analysis tool in MATLAB Simulink software. All the results are presented with THD values compared in a table.

In this paper proposed a new high step up DC to AC converter is introduced controlled with PWM technique. The output three phase AC voltages is fed to three phase induction motor controlled by vector control. The converter is connected to low voltage renewable source like PVA or battery. The low voltage is stepped up to higher voltage using the proposed converter with coupled inductor and resonant switched capacitor. Because of the synchronous rectification Boost unit and multiple coupled-inductor-SC units the structure can therefore be easily extended for ultrahigh voltage gain. The power electronic switches are operated with soft switching with reduced voltage stress increasing the reliability of the converter. MOSFET power electronic switches are used to control the circuit output voltage with high switching frequency in the range of 100 kHz. This high switching frequency reduces the ripple in the DC voltage output reducing the Harmonics in the AC voltage side of the converter. The AC voltage output of the converter is controlled by vector control with speed reference in turn controlling the induction machine. The complete modelling is carried out in MATLAB Simulink environment with discrete analysis of the circuit. The graphs are plotted with respect to time and are explained using GUI environment.

The gift goal of this work is to evaluate among behavior of flat slab with waffle or grid slab the use of in high upward push buildings in unique geometry. For this evaluation there are taken 18 models of Rectangular, Pentagonal and Octagonal geometry having one of kind flooring as eight, sixteen and 24. The parametric studies include of most nodal displacement, maximum share force, storey go with the flow most beam moment and axial forces generated within the beam and column. The modelling is carried out in STAAD.pro V8i for seismic zones IV. The Plan length of rectangle geometry 16X28 m, Octagonal geometry sixteen m in diameter, and octagonal geometry 12 m in diameter is taken into consideration. The peak of floors is taken three.2 meter. Seismic loadings are taken into consideration one by one to evaluate the overall performance of all of the 18 fashions and conclusions have drawn on the high-quality framing machine. On the basis of the seismic conduct, the overall performance of the shape is checked, and then after subsequently the additional required measures and ideas for the design of shape for the development are suggested. This observe offers various information of seismic parameters like storey drift, maximum beam second seismic, conduct, base shear and most proportion pressure based totally on current literature evaluation.

In the area of high seismicity the conventional slabs are become uneconomical due increase in design requirement to tackle additional seismic loads. The use of deep beams, increased column sections etc led to costly frame work. Moreover masonry infill wall effect is not incorporated in the design of conventional slab building frames, which led to unsafe or uneconomical design. These panels are used to fill gaps between the frames of building. The flat slabs are the beamless frame having lower lateral stiffness, high storey drift, and are more flexible. But these are more susceptible to failure under seismic action. Hence to avoid the failure of flat slab structure under seismic action, some lateral resistance structural elements are used in order to increase stiffness, reduce storey drift, lateral displacement thereby improving the lateral resistance of the system. In the present study an attempt is made to analyze and study the various multi- storied reinforced concrete flat slab building frames with several percentage of infill wall considering the lateral resistance of flat slabs by evaluating parameters, subjected to seismic loading. A number of flat slab building frames are analyzed by varying the percentage of infill wall (0%, 50%, 80% and 100%) to evaluate parameters affected by the addition of infill wall in the flat slab. The results obtained by analysis are used to study and compare the effects of variable percentages of infill wall on the lateral resistance of flat slabs by varying storey height. The several parameters are compared for the lateral resistance assessment of flat slabs. The effect of masonry infill wall on flat slab frame in studied in terms of several parameters for the lateral resistance of the flat slab under seismic actions.

As the main form of information exchange, images have always played an important role in communication media, irrespective of whether mobiles or personal computers are considered. An image compression method eradicates redundant and/or unrelated information, and resourcefully encodes leftovers. Practically, it is frequently essential to toss away both non redundant information and relevant information to attain the essential compression. In any case, the ploy is discovering methods that permit important information to be resourcefully extracted and represented. In this paper we present an image compression techniques performance evaluation and shows that our proposed method gives better results than the existing techniques, the simulation works done with the matlab simulink software.

The rapid uptake of mobile devices and the rising Popularity of mobile applications and services pose unprecedented demands on mobile and wireless networking infrastructure. Upcoming 5G systems are evolving to support exploding mobile traffic volumes, real-time extraction of fine-grained analytics, and agile management of network resources, so as to maximize user experience. In this paper we resent deep neural network with support vector machine classifier and improve the performance of channel boosting in the terms of bit error rate and block error rate, Our simulated result shows better results than the previous techniques.