Volume 10 | Issue 6 |

 Abstract

Abstract The purpose of this research study was to determine the specific abilities of students with autism and their peer learners that may contribute to the achievement of peer-mediated intervention strategies. Autism students and peer learners were co-ordinationed based on skill level, age, and preferences; the autism students participated in a different of activities throughout a week-long day inclusive education set-up. Peer learners were taught how to interact with autism students, and what social behavioral methods to use and technicians were trained to facilitate these interactions. Current qualitative case study research was designed to determine patterns across the co-ordinationed pairs. Existing research study has endeavored to explore some research objectives to fulfill the target of study and has espoused a purposive sampling technique for the selection of respondents. Eleven case study pairs were selected based upon attendance at inclusive education set-up and set-up was held on a TEPSE & HEPSN Centre campus in Jodhpur District, Rajasthan Findings indicate that peer learners specific abilities and the specific abilities of the autism student contribute to the achievement of a peer learning intervention.

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Key-words: Peer Learning, Students, Mild Autism and Qualitative Case Study

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ABSTRACT The most common and serious metabolic disorder nowadays is diabetes. More than 300 million people of the world having this disease and the number is still go on increasing at a rapid rate. Long-term use of insulin and other oral hypoglycemic agents will cause many side effects and complications with heart diseases. Also diabetics are highly prone to different types of microbial infections due to low immunity. To avoid such problems herbal drugs has greater importance, Instead of using these types of allopathic formulations. According to World Health Organization, in developing countries, 80% of the population has still depended on traditional or folk medicines for prevention or treatment of diseases, because of their affordable price, clinically effectiveness and relatively low side effects than modern drugs. This review aims to focus the significance of herbal folk medicinal plants traditionally used in the prevention and treatment of diabetes mellitus in Indian Medicine.

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Keywords : Folk medicine, Herbal medicine , Medicinal plants, Traditional plants, Diabetes

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Data assumes a significant part in each period of work in the present advanced time. Data should be safe since it can modify. Portrayal and capacity of data will be addressed in heterogeneous organization. There are chances of assault on information which is crucial for specific association. With quick expansion in cybercrime, assailants act perniciously to change those data. Be that as it may, it's incredibly affecting scientific proof which is expected for provenance. In this manner, it's expected to keep up the forensic evidence since it goes through different stages during scientific examination. during this methodology, there's a legal chain during which produced report goes through different levels or delegates like pathology lab, forensic slab, police and so on to make the straightforward framework with changelessness of measurable confirmations, blockchain technology innovation is more appropriate.

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Forensic evidence, Blockchain Technology

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The corollas of Solanum flowers are blue-purple, yellow or white and they stand out against the anthers' brilliant yellow cones. The present study focuses on the biochemicals and pigments analysis of fresh flower of Solanum species (S. lycopersion L., S. melongena L., S. nigrum L., S. torvum Sw. and S. trilobatum L.). Solanum lycopersicum L. (Tomato) flower is small, yellow, star shape, aromatic odour, sweet taste, pubescent odour with smooth texture. Solanum melongena L. (Brinjal) flower is medium size, violet or pale blue, star shape, pungent, bitter taste with smooth texture. Solanum nigrum L. (Black nightshades) flower is minute, white, star shape, musk odour, sour tasting with smooth texture. Solanum torvum Sw. (Turkey berry) flower is medium size, pale white, tubular, star shape, pungent, odour, bitter tasting with smooth texture. Solanum trilobatum L. (Climbing brinjal) flower is a large, violet, star shape, aromatic odour, sour taste with smooth texture. The macroscopic characters such as description of theplant, colour, odour, taste, nature, texture were studiedfor morphological investigation. Preliminary screening result shows that the present of phenolic compounds, tannin, saponins and terpenoids in all five flowers. Flavonoids are absent in S. lycopersicum, S. melongena. Resin is absent in S. melongena. Presence of quinone in all flowers. Cartenoids and anthroquinone are absent in S. nigrum and S. torvum. Anthocyanin is present in S. nigrum and S. torvum. According to the results of the quantitative pigments analysis, the greatest absorbance peak was visible in the spectra of white flowers at 620 nm, yellow flowers at 570 nm and purple flowers at 490 nm.

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Solanum species, Flowers, Morphology, Biochemicals, Pigments, Colorimeter

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Monitoring the quantity and quality of urban vegetation accurately aids regional greening efforts and enhances knowledge of vegetation's environmental impact. Building shadows and synthetic materials, on the other hand, can severely obscure vegetation estimations. Furthermore, vegetation indices (VIs) quickly saturate in high biomass settings, making vegetation quality assessments more challenging. Plant Indices (VIs) are the most effective and simple ways for computing both the qualitative and quantitative assessments of aspects like vegetation cover, vigor, and boom dynamics, among other things, derived from remote sensing-based canopies. The indices are being used enormously inside RS for a variety of objectives, including the usage of exceptional airborne and satellite television for computer systems, as well as the use of Unmanned Aerial Vehicles (UAVs). For now, there is no unifying mathematical equation that defines all the VIs due to complexity of many mild spectra combinations, equipment, platforms, and resolutions that are being used. As a result, customized algorithms based on unique mathematical expressions that are combined see mild radiation from vegetation, normally inexperienced spectra region, and nonvisible spectra to achieve proxy quantifications of the vegetation surface have been developed and tested for a variety of applications. Optimization VIs are typically adjusted to specific software requirements in real-world applications, and they are frequently utilized in tandem with excellent validation equipment and methods on the ground. The current study discusses spectral features in plants and describes the development of VIs, as well as the advantages and risks of developing unique indices. In agricultural improvement analytics, vegetation indices are a critical metric. Information precision and miles-away management are two primary motivators for employing vegetation indices in remote sensing, which are just two of the technology's many advantages.

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Vegetation indices, dataset, NDVI, NDWI, spectral indices, reflectance

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Cloud computing is predicted to vary the way information technology (IT) is employed and managed better cost efficiency, faster innovation, faster time-tomarket, and therefore the ability to scale Application on Demand (Leighton, 2009). per Gartner, while the hype grew rapidly Released from 2008 and onwards, it's clear that the cloud computing model has undergone a serious change. And the benefits will be significant (Gartner HypeCycle, 2012). However, because cloud Computing is emerging and rapidly evolving conceptual and real, legal/contractual, Financial, quality of service, interoperability, security, and privacy issues are still significant challenges. In this paper, we describe the varied services and deployment models of cloud computing and identify the key ones. challenges. Specifically, we discuss three serious challenges: regulatory, security, and privacy issues in cloud computing.

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Cloud Computing, Security Metrics, Security Threats, Security Measurement Frameworks

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It is critical now for supply authorities to provide consumers with clean, reliable, and continuous power. There are no. interruptions in power quality such as voltage sag, swell, or harmonics due to the growing number of consumers and use of advanced power electronic devices. Hence Different power electronic devices have been utilized to maintain power quality. Also Because of a scarcity of nonrenewable energy sources, the world is shifting toward renewable energy sources. However, using nonrenewable energy sources has its own set of benefits and drawbacks. To maintain acceptable power quality in this project, we deployed a unified power quality conditioner in conjunction with a solar PV array. The UPQC is a series and shunt compensator that performs multiple tasks to improve power quality. The grid side power quality concerns, such as voltage sag and swell, are compensated by the series converter, which also keeps the load voltage constant. It also controls the voltage of the PCC. The current harmonics caused by a nonlinear load are compensated by a shunt compensator. It gets its energy from a photovoltaic array. A Synchronous Reference Frame (SRF) control based on a moving average filter is used to generate the reference signal. The system proposed in this paper provides benefits in clean power generation and also improves the power quality of the distribution system. The performance of the system under various conditions was tested by simulation in MATLAB simulation software using a non-linear load. In this document, the system was tested for different conditions such as voltage fluctuations, sags, and swells.

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Power Quality, Photovoltaic System, Unified Power Flow Controller, and Voltage Fluctuation

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Keywords: Hesitant bipolar, Hesitant Bipolar Intuitionistic Fuzzy, Entropy, TOPSIS, GRA techniques.

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Diabetic Retinopathy is one of the major causes of blindness around the world. This disease affects those people who suffer from diabetes and mainly aged diabetes patients. Many hospitals around the world try their best to conduct research and prevent blindness caused due to diabetic retinopathy. Being able to detect diabetic retinopathy before it is too advanced is one of the major aims of this project. In this work, we will try to detect whether a patient has reached the stage of diabetic retinopathy or not. In accordance with this, we will use deep learning neural networks to classify the images of eyes of patients. Medical imaging analysis using deep learning and neural networks is gaining popularity because of its effectiveness and positive results. In this project, we will train a neural network on the retina images taken using fundus photography. After the training the neural network will be able to classify whether a patient has diabetic retinopathy or not and to what extent. The successful completion of this project may help many medical practitioners carry out the eye examination of diabetes patients in an easy and effective manner. The detection of diabetic retinopathy will also become more accurate and less time consuming. This will lead to better treatment and also a reduction in cost as physical examination of the retina images by technicians will be minimal.

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Deep learning, neural networks, image classification, medical imaging, diabetic retinopathy, medical imaging analysis, machine learning.

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