Volume 8 | Issue 9 |

 Abstract

Facial expressions are considered to be the fastest way of communication while delivering any type of information. Facial expressions play a key role in getting an understanding of the mental views of any person. With changing time, enhancement in technology is significantly increasing day by day. In neural networks, CNN is well known for carrying out image recognition and image classification tasks. To improve human-computer interaction, it is needed to build an efficient scheme for human expression recognition. In facial expression recognition, feature extraction is the first step. This is followed by the classifier which is used to classify facial expressions. This paper aims to provide an automated facial expression recognition system which can efficiently classify and recognize the facial expression. This proposed work runs on top of a convolutional neural network, image data of human facial expressions is fed to the neural network build with the help of Keras. The proposed methodology aims to build a neural network to recognize facial expressions by using the architectural properties of pre-trained CNN architectures such as VggNet and Alexnet.

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 Keywords

Convolutional Neural Network(CNN), Facial Expression Recognition(FER), Alexnet, VGGNet

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Cardiovascular disease or heart disease is the world�s largest cause of weariness and death. Predicting cardiac disease before hand is most important in the analysis of clinical data. A large amount of data is present in health care industry ,that data can be converted into information , with the help of that information predictions can be made. Several researchers have applied data mining technique to predict heart disease. It is very important to select appropriate set of attributes and data mining algorithm to enhance predictive accuracy. This research is done to select appropriate attributes and data mining algorithms that can enhance predictive accuracy of heart disease. Different sets of attributes and classification techniques were used to develop prediction model. K-NN, Logistic Regression, Support Vector Machine,Decision Tree, Na�ve Bayes, Vote(Hybrid technique with na�ve bayes and logistic regression) and Stacking(A hybrid technique with na�ve bayes, logistic regression as base learners and support vector machine as model learner).This study shows that the cardiac disease prediction model was developed by using appropriate attributes and best results of data mining technique(stacking) got an accuracy of 85.71% in predicting cardiac disease.

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 Keywords

Data mining,Attribute selection,Classification technique,Prediction model

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The present study is based on a random sample of 180 farmers consisting of 90 KCC beneficiary and 90 non-KCC beneficiary farmers by selecting three bank branches of Punjab national bank, Regional rural bank and Co-operative bank one from each have been selected from Sirsa, Dabwali and Rania blocks of Sirsa district, respectively. The primary data were collected for the year 2014-15. This study aims to analyse the utilization pattern and adequacy of credit provided through KCC by the beneficiary farmers in Sirsa district. For examining the utilization pattern Simple percentage method was used while to examine adequacy of credit amount sanctioned under KCC scheme both method average and percentage were computed to draw meaningful inferences. The study showed that most of the part of credit provided through KCC scheme to the farmers was misutilized by them in the study area. The study also revealed that the credit provided through KCC scheme for the selected crops i.e. wheat and paddy was inadequate in the district as well as across the various categories of farmers i.e. small, medium and large. The credit gap was found positive for both of the selected crops i.e. wheat and rice. It was found higher for paddy crop as compared to wheat crop in the study area. This study also suggests that more extension staff should be deployed by authorities to the bank branches to monitor the farmers for proper utilization of the credit availed under the KCC scheme.

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 Keywords

Kisan Credit Card, Utilization Pattern, Credit Gap and Adequacy of Credit

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 Abstract

The dried flower buds of clove (Syzygium aromaticum syn Eugenia aromaticum or caryophyllata) belonging to family Myrtaceae are used as a spice worldwide. Clove has been reported to exhibit antimicrobial, anti-viral, anesthetic, insecticidal, anti-convulsant, anti-oxidative and free radical scavenging activities. Eugenol, an active component of essential oil isolated from clove has antimutagenic, anti-genotoxic and anti-inflammatory properties. It also restricts DMBA induced skin carcinogenesis in mice. Aqueous extract of clove was effective in reducing the incidence of hyperplasia, dysplasia, and carcinoma in situ in benzo[a]pyrene induced lung carcinoma in mice. However, there are no reports on the effects of clove on human cancers.

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Myrtaceae, Antimicrobial , Anesthetic ,Insectidal ,Antimutagenic,Anti-genotoxic, carcinoma.

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With economic developments the globally generated wastes area unit increasing. This international Municipal solid waste generation levels area unit someone. 3 billion tons annually and area unit expected to extend to some a pair of 2 billion tons annually by a pair of 0.25. India with a population of 1.35 billion has per capita waste generation starting from 0.12 to 5.1 weight unit per person and a mean of 0.45kg/ capita/ day. In India, the segregation of domestic waste is completed at the municipal factories, wherever vast machinery area unit used for separating useful materials. Implementation of separate bins for assortment of waste materials is completed, however it doesn't yield its purpose because of lack of awareness, cognitive content and negligence. The present system for assortment of municipal solid waste will have any suggests that to verify the correct disposal or its timely maintenance. This paper proposes an image of a municipal waste bigot, which might segregate the drop waste right away, resulting in a lot of useful paper. The sensible bin may be programmed to send data regarding the drop garbage, specified individual action may be taken. Various sensors and motors area unit interfaced with Arduino board during this system.

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Gas Sensor, IR Sensor, Relay, UART, Arduino UNO, GLCM.

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Almost all heavy metals and their salts have oftenly been proven as an important group of environmental pollutants becaues they are potent metabolic inhibitors. Cadmium is non essential trace element with no biological function and highly toxic to marine and fresh water aquatic life. Several studies have shown that cadmium accumulates in specific site in the body rather than being distributed evenly throughout. In this investigation an assessment of effect of the heavy metal (Cadmium) on biochemistry of blood serum has been taken as the prime consideration because blood is good patho-physiological indicator. H-fossilis (air breather) and M.seenghla (Non-air breather) were used as test animals. Both species of fishes responded differently to the same toxicant and for the same duration of exposure. In H-fossilis there was decreasing trend in glucose, total protein, Cholesterol, urea and creatinine value while in M. Seenghala only glucose and sodium exhibited -ve trends, but all other parameter showed elevation in their value as compared with the control fish.

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H. fossilis, M. Seenghala, Cadmium, Glucose, Cholestrol, total lipid, Urea, Creatinine.

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Introduction: Prosthetic valve endocarditis (PVE) and cardiac device-related infective endocarditis (CDRIE) are the most severe forms of infective endocarditis (IE), they are burdened with a heavy morbidity-mortality. Method: We present a retrospective study of a series of 35 cases of PVE and CDRIE collected in the cardiology department B at CHU IBN SINA, between January 2015 and December 2019. Objectives: Analyse, on the one hand, the epidemiological, clinical, bacteriological and anatomical characteristics of the PVE and CDRIE, and, on the other hand, the risk factors, and the therapeutic and prophylactic modalities of these forms of endocarditis. Results: The epidemiological profile of our patients was dominated by male sex with an average age of 52.8 years. Of the 35 patients, 10 had early infective endocarditis (IE) and 25 had late IE. Clinical signs were dominated by fever in 71% of patients and local signs in 76% of patients with CDRIE. All of our patients received blood cultures on the first day of admission. HC was negative in 10 patients (28%), for the other 25 (72%) we noted a slight predominance of staphylococci followed by streptococci and BGN. Echocardiography especially transesophageal was of a fundamental contribution to the diagnosis by allowing objectifying for the PVE: vegetations (10 cases, 45%), paravalvular abscesses (3 cases, 13%), dehiscence of the prosthetic valve (3 cases, 13%), and prosthetic leaks (8 cases, 36%). For CDRIE: Probe thickening in 9 patients (69%) and vegetations in 10 cases (76%). Treatment in 81% of patients with antibiotics was medical with a duration of antibiotic therapy of at least 6 weeks and medico-surgical in 18% of patients. Concerning the CDRIE treatment was based on all patients on the extraction of the infected equipment plus antibiotic therapy.4 patients had died; they were all patients with PVE. No deaths or complications were reported in patients with CDRIE. Conclusion: Through this work we insist on the need to shorten the time of diagnosis by educating patients to avoid the empirical consumption of antibiotics, the systematic realization of echocardiography especially transoesophageal and blood cultures. Due to the reserved prognosis, surgery, when indicated, should not be delayed and antibiotic prophylaxis should never be neglected.

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 Keywords

prosthetic valve endocarditis, cardiac device-related infective endocarditis

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 Abstract

Zinc oxide nanoparticles were prepared by sol-gel technique via two different approaches having by employing zinc sulphate and sodium hydroxide. In the first approach, NaOH was added dropwise with regular interval (ZnO-A) whereas in the second approach NaOH was directly mixed with ZnSO4 solution (ZnO-B). The physical properties of the synthesized nano-particles were studied by X-ray diffraction technique and scanning electron microscope to investigate the structure and morphology of the material, respectively. It was observed that the both the grown ZnO particles revealed the crystalline properties. From the Debye-Scherrer formula , the particle size of ZnO-A was found to be 10nm whereas for ZnO-B it was found to be 7.7 nm. The SEM morphology exhibited the grown particles have uniformity. The synthesized ZnO particles could be used for various opto-electronic devices.

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Debye-Scherrer Formula, sol-gel, FWHM, Whatman filter paper

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This paper examines both the long-run and short-run impact of real exchange rates and its volatility on India�s exports to United States by using autoregressive distributed lag (ARDL) bound test on quarterly data spanning from 1991Q1-2018Q4. The results of sensitivity analysis conducted by using ARDL bound testing approach confirm that India�s aggregate real exports are relatively more sensitive to the real exchange rates in the long-run but less responsive in the short-run. The empirical results failed to reject the null hypothesis of no short-run causality. The error correction term (ECT) is found to be negatively and statistically significant, which indicates the correctness of short-run shocks towards long-run equilibrium at the speed of 24 percent within a quarter.

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 Keywords

Real exchange rate, Volatility, Export, Error correction term, ARDL model.

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 Abstract

Using an IoT based ordering system, pharmacy, auto service, hotels, and customer care units can be automated. The traditional method opted for ordering items or services is done by pen and paper. This method can be time taking when there are many people in the queue. In situations like a COVID-19 pandemic, these systems can help conduct touchless shopping and social distancing in most of the businesses, including but not limited to pharmacy, restaurants, auto service, and customer care centers. This project, wireless ordering systems for touchless shopping enables users to order products or services remotely from his/her table or queue and send those orders to the concerned based on application and industry. The system consists of two sections, transmitter and receiver section. The transmitter section has the touch screen display, which takes the input from the user, and sends it to the receiver section using an RF transmitter. In the receiver section, data is displayed on the LCD screen. The order taking department can take the order from the LCD display right after the buzzer sounds.

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 Keywords

Automation, Buzzer, IoT, LCD screen, Ordering System.

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