Volume 9 | Issue 6

 Abstract

Today information sharing has become an integral part of our day-to-day life. We tend to give reviews of all the things from our day to day activities to college activities and teacher reviews. Thus, by using this vast amount of data we can apply machine learning on the data and understand the sentiment behind the information shared. By understanding the sentiments properly can help in increasing the productivity of teachers and students in an academic arena. So, in our project we are going to apply sentiment analysis on the data we get from teacher and academic feedback of students. By applying sentiment analysis on the student feedback, we will improve the teaching quality thus improving the teacher quality and increase the grade of a college or institution using machine learning. To achieve this, we will de- sign a system in combination of natural language processing, machine learning and cloud computing together. We will create a mobile application where student can place reviews or teacher feedbacks. To store these feedbacks, we will use Google Cloud. Then lexicon analysis will be applied on the data using OPEN-NLP natural language processing toolkit. The data after lexicon analysis will be used to create a training dataset with two classes positive and negative. The machine learning algorithm Support vector Machine (SVM) using the self-created training dataset to get the sentiment behind the feedback. Thus, our system will put the feedback in two categories positive and negative. So, by analysing the positive and negative we can concentrate on increasing the efficiency of teachers if needed. So, by using our system a college or institution can remove the drawbacks in teaching and increase the student and teacher relationship and interaction.

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 Keywords

Mobile Application, Student Feedback, Machine Learning, Stop Words, Sentiment Analysis, OPEN-NLP, SVM.

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This study has been undertaken to investigate the moment carrying capacity of reduced web section (RWS) in steel beam column joint with extended endplate moment connection. A reduced web section (RWS) with 5 numbers of vertical as well horizontal slits is analyzed using ANSYS 16.0. Extensive research has been carried out on steel moment frames to improve the cyclic performance of moment connections with reduced beam section (RBS). The RBS connections are conventionally known by the radial reduction as well as hole cutting of the beam flange, some researchers have proposed reduced web section (RWS) connections. The present study dedicates to the RWS connections with vertical-slits (VS), horizontal slits (HS) as a cost-effective alternative with multiple design parameters. This paper aims to obtain proper ranges for the geometric design parameters of the VS-RWS and HS-RWS connection. In this order, two full-scale specimens of the bolted extended end-plate VS-RWS, HS-RWS connection were tested under the cyclic loading to evaluate the performance of connections, and then a parametric study was carried out using the verified numerical models.

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 Keywords

Reduced beam section, Reduced web section, connection, slits, moment.

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 Abstract

In this study, an analytical approach is used to find the effect of radial clearance between hole and fastener in load transfer capability of double shear lap joint. An undersized bolt shank or over-sized hole is a deviation due to the fabrication constraints even in aerospace industry where high precision is needed. This may increase the radial clearance between bolt shank and hole in the connecting members. As a result bending of bolt shank and corresponding change in mechanics from close fit configuration to a loose fit configuration arises. This bending may cause early failure of bolt. To find the maximum allowable clearance for safe load transferring a double shear lap joint is modeled and analyzed using Ansys software by varying bolt hole diameter to find the variation of stress along fastener.

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 Keywords

Double Shear Lap Joint, Radial Clearance, Shear Bolt, Close Fit, Load Transfer Capability

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 Abstract

In Indian Society Dalit Women are most Discriminated and Deprived Section in our Caste-Based system. They have been not only victim of the structural hierarchy of caste, but also face inequality in this patriarchal society. They are not only suffering from gender discrimination but also faces economic, political and social deprivation. The main objective of this paper is to understand the political, social and psychological dimensions of Dalit women in India.

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 Keywords

Dalit women, Gender Inequality, Caste-Discrimination, Political Rights, Social Right, Psychological Rights, Constitutional Rights, Legal framework

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 Abstract

The COVID-19 has its impact in the world in a massive way, especially due to nationwide lockdowns which have brought social and economic life to a halt. There is a multi-sectorial impact of the virus as all the economic activities of nations have decelerated down. Service industries such as tourism, hospitality, and transportation have undergone substantial losses due to reduction in mobility. Owing to the coronavirus lockdown the GDP growth of India is slumping since it created major disruption across multiple sectors. The study was undertaken with the objective to study the effect of pandemic, attitude of people and how to overcome the situation. For the study a sample of 100 respondents were taken from the state of Kerala. The major findings include atmospheric air quality was increased, noise pollution was decreased due to lockdown. ANOVA test results show that different age group has difference of opinion on wearing masks and lockdown. Adequate support from the government machinery is needed to overcome the present situation. Social distancing, wearing masks can reduce the impact of Covid-19.

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 Keywords

Lockdown, Tourism, Positive Effect, Attitude.

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Recommender system (RS) has emerged to one of the most used technology in the recent years. This paper consist overview of recommender system, types of RS, problems in RS and future scope of RS. The main purpose of this paper is to spot the research trend in RS. More than 1,000 research papers, published by ACM, IEEE, Elsevier, and Springer since 2011 to the first quarter of 2020, have been considered. While learning the Recommender system several interesting finding come out which will help current and future RS researchers to assess and set their research roadmap. Furthermore, this paper also envisions the future of Recommender System which may open up new research directions in this domain.

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 Keywords

recommender system; issues; challenges; literature review; filtering approach; filtering technique; information retrieval technique; machine learning; research trends; future direction.

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 Abstract

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Pinterest, Youth

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Human coronaviruses (HCoVs) have long been considered as no significant pathogens causing common cold in healthy people. But in the 21st century, 2 highly pathogenic HcoVs which are Severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV) emerged from animal reservoirs to cause global epidemics with alarming morbidity and mortality. An other pathogenic HcoV ,2019 novel coronavirus (2019-nCoV) was discovered was seen at Wuhan, China in December 2019 and this pathogenic HcoV has caused serious illness and death. The proposed work discusses about the detailed literature review of the contribution made by different authors.

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Covid, Corona Virus, Drug, repurposing

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The conventional method for classification and tumor detection of medical resonance brain tumor images is by human inspection, where in a lot of time and effort is put in by the specialists to analyze the problem area and to come up with a conclusion regarding the spread of the tumor region and its current stage. This paper proposes a fast and robust practical tool for segmentation of solid tumors with minimal user interaction to assist clinicians and researchers in radio surgery planning and assessment of the response to the therapy and classification of tumors using probabilistic neural network. Particularly, cellular automata (CA) based seeded tumor segmentation method on magnetic resonance (MR) images, and a standardized process called seed selection, is proposed. ANN with image and data processing techniques were employed to implement an automated brain tumor classification. Decision making was performed in two stages: feature extraction using the principal component analysis and the classification using Probabilistic Neural Network (PNN). The performance of the PNN classifier was evaluated in terms of training performance and classification accuracies.

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Keywords: Cellular Automata, Magnetic Resonance, Probabilistic Neural Network (PNN)

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 Abstract

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Video Processing, Video Coding, H.264, Decoder

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ABSTRACT: INTRODUCTION: Anaemia is a condition in which the number of RBC OR OXYGEN CARRYING CAPACITY is insufficient to meet the physiological needs of the individual .It is a commonest medical disorder in pregnancy & responsible for significant high maternal and fetal mortality rate worldwide. AIM: To study socio demographic factors , maternal and fetal outcome. MATERIALS AND METHODS: This study included all antenatal women presenting in third trimester of pregnancy with Hb<7 gm/dl over a period of 2 year in the department of OBGY ,GMCH AURANGABAD.Gestational age more than 28 wks and haemoglobin less than 7 g/dl included in this study. RESULTS: A total of 200 women were studied .All women were investigated and treated with Injectable iron sucrose and adequate blood transfusion. Maternal complication in terms of CCF ,PPH,Sepsis,Lactational failure ,Surgical site infection were studied. Fetal complication in terms of LBW ,Prematurity,Neonatal sepsis were studied. CONCLUSION: The prevalence of IDA and amount of information available regarding the condition is substantial. Iron deficiency anaemia (IDA) is not a disease,but a collection of signs and symptoms that are displayed according to an insufficient amount of iron in the body.IDA prevention is dependant on the early and successful utilization of diagnostic tools and treatment options.

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 Keywords

Pregnancy, Iron deficiency anaemia, Blood transfusion, PPH

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 Abstract

Microstrip antennas have found their place in the research areas over the past few decades. The main reason for the popularity of these types of antennas is their small size and ease of fabrication. The size of these antennas depends on the frequency of operation. Therefore, as the frequency of operation increases the size of these antennas decreases significantly. This paper summarises the different types of microstrip antennas, the feeding techniques that can be used to feed the radiating element with the input electrical signal, and the various miniaturization techniques that can be implemented to make these antennas more compact.

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Antennas, Microstrip, miniaturization, patch antenna, feeding mechanisms, microstrip antenna types.

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Citrus are one in every of the foremost wide cultivated fruit crops. Citrus fruits are made supply of essential vitamins, minerals, ?bers and bioactive phytochemicals, like alkaloids, carotenoids, gas compounds and polyphenolics. The by-products derived from citrus wastes ar thought of to be associate degree economic and renewable supply for valuable compounds which might be utilized in pharmaceutical, neutraceutical, food and cosmetic industries. The review presents an in depth description on the recent advances with stress on the citrus derived neutraceuticals as potential supply for numerous biological properties and physiological roles, like anti-carcinogenicity, anti-mutagenicity, anti-allergenicity, anti-ageing activitiy, and natural moreover as vital constituent in artificial antioxidants. A comprehensive description on the citrus derived food and drinks more over as alimentary feed for animals has additionally been enclosed.

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Neutraceuticals, Citrus fruits, Citrus Waste, Phytochemicals, Anti-oxidants, Supplements.

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 Abstract

Many working families locate far away from their place of work because of the low or affordable housing but this also results in increasing transportation cost and also increase in the commute time. However, for such families the transportation cost is sometimes equal to their housing cost or sometimes it is even greater. But affordability for these people is not just about transportation cost. Households of limited resources have fewer choices in both where they can travel to and where they can actually afford to live and survive. Key words: Affordability, Transportation, Survival.

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Key words: Affordability, Transportation, Survival.

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Multiple-Input and Multiple-Output or MIMO has become an essential element of wireless communication standards including the use of multiple antennas at the transmitter and the receiver. In modern usage, MIMO refers to a practical technique for sending and receiving more than one data signal simultaneously over the same radio channel by exploiting multipath propagation. the use of orthogonal frequency division multiplexing to encode the channels that's responsible for the increase in data capacity.The narrowband MIMO performance is used to enhancechannelestimation in wireless MIMO ad hoc systems. In this paper we develop a model of MIMO ad hoc and measure the performance the network using the maximum likelihood (ML) estimator to formulate the channel model and measures the bit error rate (BER) in terms of signal to noise ratio (SNR) considering the Rayleigh fading channel with different number of receiver combination. Finally, we simulate a network implementing the Alamouti coding scheme and results are shown for the channel estimation.

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MIMO,Maximum Likelihood Channel Estimation,Alamouti Coding,fading channel.

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 Abstract

recent years, various methods for source code classification using deep learning have been proposed. In these methods, the source code classification is performed by letting the neural network learn the source code's token sequence, etc. In that case, it is necessary to select the appropriate neural network or source code representation because the learning efficiency decreases when neural networks and source code representations that are not effective for source code classification are used for learning. However, it is not clear which neural networks or combinations of source code representations are effective for realizing high-precision source code classification methods. In this study, we compare the source code classification method using deep learning. First, we selected 3 neural networks that are widely used in existing research. Next, we compared the accuracy of a total of 6 source code classification methods in which the neural network trained the token sequence or abstract syntax tree of the source code. As a result, it was confirmed that the recursive neural network which learned the token sequence of the source code has the highest accuracy. In addition; we compared the source code classification accuracy of deep learning and non-deep learning methods, and confirmed that the classification accuracy of deep learning methods is high.

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Deep learning, Source code classification, Forward propagation Neural network, Recursive Neural network, Graph Convolution network, BoW.

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 Abstract

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Keywords: Deep Learning, Natural Language, Detection Models, predict, binary

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Creative Commons Attribution 4.0 and The Open Definition

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cyber-crime, Globalized

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 Abstract

Malaria is the deadliest disease in the earth and big hectic work for the health department. The traditional way of diagnosing malaria is by schematic examining blood smears of human beings for parasite-infected red blood cells under the microscope by lab or qualified technicians. This process is inefficient and the diagnosis depends on the experience and well knowledgeable person needed for the examination. Deep Learning algorithms have been applied to malaria blood smears for diagnosis before. Design propose system a new and highly robust deep learning model based on a convolutional neural network (CNN) which automatically classifies and predicts infected cells in thin blood smears on standard microscope slides. Testing on a small dataset of images gathered from a different source achieves similar performance, suggesting the model may generalize to different imaging conditions. The system achieves higher recall than existing non-deep approaches, and its accuracy, recall and precision of the highest performing CNN approach.

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CNN,Deep Learn,Maleria

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Swarm Robotics, LoRaWAN, Indoor Positioning System

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Creative Commons Attribution 4.0 and The Open Definition