Volume 10 | Issue 6

 Abstract

Pleurotus sajor-caju was cultivated on six agro wastes viz., ground nut straw, soybean straw, gram straw, wheat straw, sugarcane trash and sorghum stalk to determine the suitability of these agro wastes on yield, total carbohydrate, protein, fat, crude fibre and ash content. Soybean straw showed significantly highest yield (752.64 gm/kg and 75.26 % B.E.) with maximum protein content (24.95 %). Significantly maximum moisture and crude fibre content of Pleurotus was recorded on sugarcane trash i.e. 88.59 % and 7.09 %, respectively. Maximum total carbohydrate (57.72 %) was recorded on wheat straw, while maximum fat (2.95 %) and ash content (7.13 %) of Pleurotus in mushrooms cultivated on groundnut straw.

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 Keywords

Pleurotus sajor-caju, agro wastes, yield, B.E., fruiting bodies

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This research focuses on the fabrication of LM13 aluminum alloy-based Hybrid Aluminum Matrix Composites (HAMC) and the use of Artificial Neural Networks(ANN) to predict their physical properties. The objective of this study is to calculate the hardness and density of Hybrid Aluminum matrix composites (HAMC). The estimations are made using the ANN's Levenberg-Marquardt method. The stir casting technique is used to manufacture the HAMC with Graphite (Gr) and Boron carbide (B4C) reinforcement into the LM13 aluminum alloy. The L9 orthogonal array was used to see how process variables like Graphite (Gr) reinforcement, Boron carbide (B4C) reinforcement, stirring speed, and stirring time affect the outcomes. The material's Brinell hardness number (BHN) and density were explored as output characteristics. The prediction performance of the ANN was evaluated using the determination coefficient (R2) and mean square error (MSE). The average R2 and MSE are 0.9944 and 0.003963, respectively, indicate that the ANN effectively fitted the experimental response variable values. The findings are also supported by the correlation coefficient (R) of 0.99721.

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LM13 Aluminum Alloy, Hybrid composite, Stir Casting, Physical Characteristics, Artificial neural network

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Establishing a solid theoretical foundation for structured deep neural networks is greatly desired due to the successful applications of deep learning in various practical domains. This paper aims at an approximation theory of deep convolutional neural networks whose structures are induced by convolutions.The difficulty in theoretical analysis of the networks with linearly increasing widths arising from convolutions can be overcome by introducing a downsampling operator to reduce the widths. As we prove that the downsampled deep convolutional neural networks can be used to approximate ridge functions nicely, which also hints some advantages of these structured networks in terms of approximation or modeling. We also prove that the output of any multi-layer fully-connected neural network can acquire by that of a downsampled deep convolutional neural network with free parameters of the same order, which in general, the approximation ability of deep convolutional neural networks is at least as good as that of fully-connected neural networks. Finally, a theorem for approximating functions on Riemannian manifolds is unveiled, which reveals that deep convolutional neural networks can be used to learn manifold features of data.

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 Keywords

Classifier, convolutional neural networks (CNN), radiographic images, transfer learning, weld defect detection

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 Abstract

The earnest desire of an individual to be treated as equal with dignity needs no separate reiteration. Since time immemorial, there has been the depiction in numerous historiographical records of the attempts made by so called victimised individuals to assert their individuality in the society. At the heart of such attempts lies the concern of individuals to lead their loves without facing the wrath of subjugation. Novels and other critical writings have been the documentary records of female marginalisation to a great extent. However, with the advent of different waves related to the critical movement of feminism, it can well be said that there is the growing consciousness regarding the establishment of equality between both the males and the females. Numerous writers, today, have come up with notable fictions which showcase the urge of female characters to lead a life of dignity thereby validating their identity in the society. Gods, Grave and Grandmother by the notable Indian English writer, Namita Gokhale is one of the scintillating tales of the establishment of a stable identity by the leading female protagonist. Through the portrayal of the character of Gudiya, Gokhale makes it very clear that the women of the contemporary Indian culture are no longer submissive, and they are equally bold and determined with regards to their subjective positions. This paper humbly attempts at portraying the self-created pathway of Gudiya leading to her firm identity in the novel. The nature of this research is purely qualitative, and it focusses on the comprehension of the layers of meanings embedded within the text.

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 Keywords

consciousness, dignity, female, identity, text

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The novel coronavirus which was first seen in Wuhan, China has created havoc across the world. Its rapid spreading and the virulent outbreak have created a state of emergency in the world. From a public fitness standpoint, COVID-19 is a sickness of top significance, and it has become vital to barricade the virus from spreading with preventive measures like maintaining social distance and wearing a mask. This paper mainly aims to develop a system that helps monitor if people are maintaining social distancing and also detects face masks on humans. This paper makes use of the Tiny-YOLO algorithm on Raspberry Pi for real-time object detection. Although the YOLO object detector is widely regarded as one of the quickest deep learning-based object detectors, with a high Fames Per Second, it is still too slow to run on embedded devices like the Raspberry Pi. Hence, this paper uses tiny YOLO which has a small model size (< 50MB) and rapid inference speed, making it applicable for embedded deep learning devices. We could additionally be displaying the count of human beings found in a room on an LCD. Overall, this paper facilitates lessening the range of COVID-19 sufferers and makes public locations safer.

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COVID-19, Mask detection, Social Distancing, YOLO, Raspberry Pi.

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teacher recruitment, selection, and placement, learning metrics, Filipino learners

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 Abstract

Mobility for blind and elderly people is a problem as they have to face many difficulties in their day to day life. Most commonly, stick is use by blind and elderly people as a support for their body to stand and walk. The most common disadvantage of walking stick is user should have to be in close proximity of obstacle so that he can sense the location of obstacle to avoid bumping while waggling. We proposed a new concept of walking stick which is helpful for both blinds and elderly people to move in unfamiliar environment and monitor their medical condition. In this methodology we have used different sensors mounted on a walking stick which will help a user to navigate easily indoor and outdoor along with monitoring their health. Unlike other electronic blind stick which were helpful in detecting obstacle and alert user we designed a stick having multiple feature embedded in a single stick. This stick used for detecting obstacle, pit, water on ground to some level, location of user, body temperature measurement of user and alert another person by sending message about the health issue of user or some other emergency.

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 Keywords

WHO, smart walking stick & GSM modules

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Self Help Group has a positive impact in social, political, economic and educational sphere. It is playing a vital role in developing rural areas and rural people. SHG also pay a way for obtaining a method for raising money, skill development, ending social isolation; give a feeling of personal relation, social intimacy, social confidence etc. Self Help Group is an effective strategy for the empowerment of woman in rural as well as urban areas bringing woman together from all sphere. The selected location was Ranka, East Sikkim located 16 km away from Gangtok. The study was based to focus on functioning of SHG at Phenzong, Baliman. In the survey 6 SHG namely KURSONGREEP, UJWAL, PRERNA, LOTUS, AJAMBARI and MICKEL were interviewed. All the group mainly preferred agriculture as their foremost profession due to low level of education, knowledge in agricultural production, suitable climatic condition and fertility of soil. But LOTUS also practice bakery, handloom, and vermi-compost and AJAMBARI practice poultry farming as their secondary work. The paper also tries to look upon the economic and social impact, highlight the problems persisting and suggestion and measures are also given.

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 Keywords

Performance of Self Help Group, Performance, Women Entrepreneur.

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Andragogy, English for Medical Purpose, Language Acquisition, Teaching-Learning Method

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Image is a key of digital data which is used in many studies and research work as dataset. These datasets are compromised due to distortion which is caused by the presence of noise. Occurrence of noise is found while capturing image, transmission of pictorial data over different networks, etc. Noise plays a vital role in image corruption and this noise can also exist individually with varying intensities of different noise factor or also as hybrid noise [i.e Combination of different noises]. In general, the results of denoising have a strong influence on the quality of the image processing techniques. The nature of the noise removal problem depends on the type of the noise corrupting the image. The most commonly affected noises in image are Salt and Pepper, Speckle, Gaussian and Poisson noise. To restore these degraded images, many de-noising algorithm has been developed and one among them are filtering techniques. In this research work, three filters are considered for denoising i.e. Weiner filter, Gaussian filter and Median filter. The current work is implemented on gray scale and colored [RGB] images and the evaluation of these algorithms is done by the measure of the PSNR and MSE values. In addition, we propose to use hybrid filter along with deep learning algorithm for denoising coloured images. The main purpose of using AlexNet is to train and classify the dataset. Successful training and classification of the dataset is based on the accuracy of training session of AlexNet and the accuracy of confusion matrix.

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 Keywords

Image Restoration, Hybrid Noise, Hybrid Filter, Deep Learning, AlexNet

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Industries are continuously facing fierce competition and the challenge of meeting increasing demands for higher quality products at economic costs. The success of an organization is directly related to how effective its implementation of continuous improvement (CI) is. For any manufacturing system, Total Quality Management (TQM) and Six Sigma are important CI methodologies. Effective understanding of these methodologies and their relationship will provide an industry with a competitive advantage. Many industrial organizations today are using either TQM or Six Sigma as the core for their CI efforts. There is a lot of disputes on which methodology is superior, how they relate to each other, what the common grounds are and what their differences are. As such, the relationship between TQM and Six Sigma is worth further investigation. Finally, this research Lean Six Sigma is an approach which focuses on continuous improvement of processes in order to reduce the cost due to poor quality and to make improvements in results to create value for the customers.

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 Keywords

Six Sigma, SQC, TQM

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Juvenile Justice is a component of criminal law that reduces criminal liability based on the assumption that a juvenile lacks the capacity to act maliciously. The conception of juvenile justice arose from the notion that the challenges of juvenile delinquency and kids in unusual settings could not be resolved through standard criminal justice methods. India's juvenile justice system is at a critical crossroads in its history. With all of these big adjustments, there is growing worry that the system has gone from its objective of rehabilitation and reformation. This essay examines the issues that the Juvenile Justice System is facing, which are eroding its legitimacy, and proposes plausible alternatives. The author contends that, while India's current juvenile justice system can be traced back to colonial rule with many improvisations, it lacks vitality and does not address the reality of exacerbated criminal tendencies among the young. The author makes a few recommendations that will help bring about change and fulfil the expanding needs of today's world. The rate of crime in our society is soaring at a breakneck pace. While the necessary law is in place, it is at the implementation phase that the majority of things fail. There is a loud voice within society advocating for strict rules, and the time has come to address them in order to ensure greater justice and a more effective juvenile justice system.

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 Keywords

Juvenile Justice System, Criminal law, Crime, Reformation, Rehabilitation, Reforms

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 Abstract

By lessening misfortune alteration costs, enhancements within the To begin with Take note of Misfortune and the speed with which claims are inspected and assessed might spare a lot of cash within the vehicle protections claims prepare. Car harm is consequently distinguished and classified utilizing progressed picture examination and design acknowledgment innovation. A method that compares before-and-after-accident car pictures to naturally identify the harmed location.

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Convolution Neural Organize, Profound Learning, Picture classification, R-CNN, and protest location

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The objective of drug repurposing is identification of potential drugs and surveilling their in vivo efficacy and effectiveness against a disease. Drug repurposing is associated with several advantages. The risk of failure is low as it uses the drugs which are already been approved. It uses the drugs which has less unknown harmful adverse effects. Since it uses the drugs which have passed all pre-clinical trials and safety standards, the time span of drug development is reduced significantly. Drug repurposing requires less financial investment when compared to the discovery of new drug. It reduces the time frame for drug development as the drugs have passed all the pre-clinical trials and safety norms.

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Covid, Corona Virus, Drug Repurposing, Graph Neural Networks

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Indexing Techniques, Map and Reduce functions, Join Operation, Hive, Hadoop

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Speech Emotion Recognition is a momentum research subject in light of its emotion handling. In this paper, we have done a short study on Speech Emotion Analysis alongside Emotion Acknowledgment. The initial segment of the paper is enhanced with a basic depiction. This paper incorporates the investigation of various kinds of emotions, elements to recognize those emotions and different classifiers to characterize them appropriately. Emotional speech databases, which are utilized in emotional speech recognition, are also analyzed critically. The Hidden Markov Model and Support Vector Machine were used in this study to discern human emotion through voice.

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 Keywords

Speech Emotion Recognition, Feature Extraction, Recurrent Neural Networks, SVM, MFCC (Mel Frequency Cepstral Coefficient), LPCC (Linear Prediction Cepstral Coefficients), LPC (Linear Prediction Coefficients), Classifier, GMM (Gaussian Mixture Model), HMM (Hidden Markov Model), KNN (K-Nearest Neighbors), MLP (Multi Layer Perceptron), RNN (Recurrent Neural Network), MSF (Modulation Spectral Features), adaboost algorithm

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Financial Independency, Women Home Makers, Salary for Home Makers

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Creative Commons Attribution 4.0 and The Open Definition

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Fire Detection, RGB and HSV Color Model, OpenCV, NumPy

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Groundwater quality must be assessed since it determines whether or not it may be used for drinking. Water for drinking, cooking, land farming and other purposes should be free of physical and chemical impurities. Groundwater is the primary source of drinking water. The physicochemical and biological examination of groundwater was used to determine the appropriateness of the water for consumption. The groundwater is polluted as a result of human and industrial activity. This is a significant issue nowadays. As a result, water quality analysis is critical for maintaining and improving the natural ecosystem. The factor analysis approaches are used to analyze groundwater quality data sets acquired from the CGWB, Gandhinagar in India in this study. The data were normalized and submitted to factor extraction in order to make it easier to comprehend and identify the characteristics that cause the most variability in water quality. The goal is to determine the reciprocal connections among the various water quality metrics in order to identify the key variables that influence reservoir water quality as well as the variations between them. The water quality index (WQI) is a useful and unique rating that depicts the total state of water quality in a single term and aids in the selection of appropriate treatment techniques to address the concerns.

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groundwater, water parameters, water quality standards, multivariate analysis, India

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 Abstract

The tolerancing concept is essential in part design process. It describes a relation between the many stages of the design and manufacturing activities. In this paper, tolerance models were developed to estimate required tolerance gap of selected assembly parts using python programming. The Monte Carlo Method is selected and using Uniform and Normal Distributions for finding required tolerance gap for given assembly.

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 Keywords

Part tolerance, Tolerance gap, Monte Carlo Method, Python.

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