Volume 9 | Issue 6

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Positive deviance approach, Malnutrition, Healthy practices in children, Nutritional status of children.

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In this paper, comprehensive thermodynamic analysis of an indirect fired gas turbine cogeneration system with multistage reheat system for heating and electricity proposes is reported. An exergy analysis carried out in the present study for improving and optimizing the overall performance of the system. This cogeneration system consists of a gas turbine cycle, a heat recovery steam generator cycle and a steam turbine cycle. A comparative study between no heat and multistage reheat shows that there is a significant improvement in electric power output, process heat production, fuel utilization efficiency and exergy efficiency due to reheat. It is also showing that the power to heat ratio is decreasing with the reheat because improvement in process heat generation is greater than the improvement in electric power output.

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ENERGY AND EXERGY ANALYSIS OF GAS TURBINE COGENERATION POWER PLANT.

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Carbon Nano Materials (CNMs) have many applications because of their super catalytical, mechanical, electrical, optical, thermal and strong electromagnetic wave absorption properties. In this work, CNM were synthesized from plant fiber and decorated with cobalt nanoparticles (Co-NPs). Microwave absorption efficiencies were studied in the frequency range of 2- 8 GHz having thickness ranging from 2-5 mm. The study concludes that CNMs decorated with Co-NPs exhibit excellent microwave absorption capability. The prepared sample shows strong microwave absorption of 96-99%, whereas -20 dB Reflection loss for 2-8 GHz frequency range of 4-5mm thickness having specific surface area of 648 m2.g-1.

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Microwave absorption, Cobalt nanoparticles (Co NPs), BET, Vector Network Analyzer (VNA), Ferromagnetic, paramagnetic.

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Lightweight cryptography is a new concept that refers to a method of bettering data security through using fewer resources and providing higher throughput, conservatism, and low power consumption. Every fraction second, the Internet of Things (IoT), which links billions of devices, collects an enormous amount of data. When the number of devices grows, so does the amount of data generated, and the protection of that data becomes a concern. In IoT architecture, devices are basically smaller and low-powered. Because of their complexity, traditional encryption algorithms are computationally costly and require several rounds to encrypt, effectively wasting the limited resources of IoT devices. A less complex algorithm, on the other hand, can compromise the necessary integrity. There are many lightweight cryptography algorithms available, and we use one of the symmetric encryption algorithms called Advanced Encryption Standard (AES). The speed of this algorithm is six times that of triple DES. Since all around us is automated in today's world, automation is playing an increasingly important role in human life. The term "smart home" encompasses not only the reduction of human effort but also energy conservation and time management. Home automation enables us to control household appliances such as lights, doors, fans, and air conditioners, which require a large number of energy-constrained devices that constantly interact with one another. The security of this home automation system must not be compromised. This problem of security for automated systems is often solved by using lightweight cryptographic algorithms. For this purpose, a lightweight security algorithm is proposed in our paper that is (AES).

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Internet of Things (IoT), Home Automation, LWC, AES, DES.

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This paper deals with three algorithms implementations for square root computation. Newton-Raphson's, Iterative and Binary Search Algorithm implementations are completely designed, verified and compared. The algorithms, entire systems realization and their functioning are described.

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Recent advances in Big Data has prompted health care practitioners to utilize the data available on social media to discern sentiment and emotions expression. Health Informatics and Clinical Analytics depend heavily on information gathered from diverse sources. Traditionally, a healthcare practitioner will ask a patient to fill out a questionnaire that will form the basis of diagnosing the medical condition. However, medical practitioners have access to many sources of data including the patients writings on various media. Natural Language Processing (NLP) allows researchers to gather such data and analyze it to glean the underlying meaning of such writings. The field of sentiment analysis (applied to many other domains) depend heavily on techniques utilized by NLP. This work will look into various prevalent theories underlying the NLP field and how they can be leveraged to gather users sentiments on social media. Such sentiments can be culled over a period of time thus minimizing the errors introduced by data input and other stressors. Furthermore, we look at some applications of sentiment analysis and application of NLP to mental health. The reader will also learn about the NLTK toolkit that implements various NLP theories and how they can make the data scavenging process a lot easier.

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NLP Cosine similarity tf-idf grammar correction

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The formation of crowd in small local shops is inevitable. After the pandemic, situation has changed to such an extent that avoiding the crowd in closed compact spaces would be a priority. Hence, considering this priority, crowd estimation would be of great help. Here, we present a technique for crowd estimation by monitoring the time thus preventing a crowd formation. This approach is implemented with the aid of QR Code Scanning method.

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Crowd, ML, QR scan, pandemic, compact spaces

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Air quality prediction is one of the complex tasks due to its dynamic nature, volatility, and variability in the time and space of pollutants. At the same time, being able to model, predict, and monitor the quality of air is becoming more relevant due to the observed critical impact of air pollution on the health of citizens and the environment. This paper aims to predict the monthly Air Quality Indices using ARIMA (Autoregressive Integrated Moving Average) model. Then categorize AQI into different classes. This knowledge will help us to reduce its level to a lesser than harmful range. The prediction and categorization will be based on a data set of atmospheric conditions in a specific area.

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AQI, ARIMA MODEL, Stationary Series.

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This study has been undertaken to investigate the self sustainable and Ecofriendly model that has been suggested to implement the Power Generation Unit from Road Transport By using the Piezoelectric Sensors, which will convert the pressure and mechanical energy from the vehicles into electrical energy and making a Prototype for the same.

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Self sustainable, Piezoelectric Sensors, Prototype.

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Business intelligence is a key factor for any manufacturer to distribute the resources strategically. processing of data to get incites is a tedious task and will take up a large resource. The dashboards that consume this processed information require the data to be in a certain form. Some dashboards require the data to be uploaded periodically. Processing data as it is produced from sources is a waste of resources and time. ETL(Extract Transform Load) provides a way of aggregating data, transforming it, and loading it to the destination. It is a process that is custom-built for every job but, the architectural structure is the same. Even if the structure is the same there are different strategies for carrying out the ETL task. The automated ETL tasks will save time and will be reliable since they are purpose-built. The standard ETL task only transforms the data and the analytics and other processes are carried out. The analytics regarding the characteristics of data will help maintain the data and access the quality of the data.

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Extract Transform Load, Extract Load Transform, Analytics Pipeline, Knime, Jenkins

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Conveyor Belt, Propeller, Collection Bin, RC Control, Review Paper

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Nivarthana, Ezhava, Chatti Udayakkal, Janthu, lunatic asylum, bureaucracy, Diwan

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Open and distance learning, perception, attitude

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The main objective of the present research is to find out the Role of the Emotional intelligence in Well-being among Students. for this investigation Purposive randomized sampling technique was employed to select the participants. Sample of 200 undergraduate subjects were taken for this study from the population which was equally classified in students having higher level of emotional intelligence 100 & students having lower level of emotional intelligence 100 from Marathwada region. Emotional Intelligence of the students is independent variable in this study. Well-being of students is dependent variables in this study. Mangal Emotional intelligence Inventory (MEII) constructed by Dr. S. K. Mangal and Dr. Shubhra Mangal in 1971 was used. To measure the level of psychological well-being of the subjects, RYYF Scale of Psychological Well-Being was used. On the basis of the results, it can be concluded that students having higher level of Emotional Intelligence exhibit higher Wellbeing than student having lower level of Emotional Intelligence. Thus, level of Emotional Intelligence increase Wellbeing of students.

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Well-Being, Emotional Intelligence

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Container object (CO), External objects (EOs), Websites, html

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Solid waste management has been a leading concern for all the developing countries.The exponentially growing population, urbanization, and economic development have led to the rising generation of municipal solid waste. For the municipalities, especially in smart cities, this becomes a major problem in nature, and it leads to many socio-economic and environmental problems.So in this paper an alternative route can be proposed to collect waste when waste generated is below a certain threshold thus reducing the distance travelled and time taken for waste collection and a review on technologies for segregation and management of solid waste.

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smart dustbin, solid waste management, optimized route, IOT & ML , smart cities

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During extensive survey of viral disease on medicinal plants of family Euphobriaceae in the summer season of 2006-07 at different districts of Eastern Uttar Pradesh (Gorakhpur, Deoria ,Kushinagar, Maharajganj), a variety of symptoms were recorded on Phyllanthus niruri plants. The infected plants showed mosaic and mottling. Yellow-green mosaic symptoms followed by yellow patches intermingled with normal green some time whole plant leaves become white and in advanced stage of infection defoliation take place. At several locations of survey areas on P. niruri where manifested with whitefly (Bemisia tabaci) were recorded. Infected plants samples were examined by electron microscopy and nested PCR by using CRv301 and CRc1152 primer pairs. The electron micrographs prepared with leaf dip method revealed the presence of geminate particles of size 20 nm in diameter. PCR products of the expected size ~870bp, were obtained from P. niruri samples. The results of the PCR investigation revealed that the Phyllanthus niruri plant showing yellow green mosaic and complete white leaves was positive for Ageratum yellow vein virus. The virus isolate was identified as Ageratum yellow vein virus of genus Begomovirus and family Geminiviridae. This is the first report of occurrence of Ageratum yellow vein virus on P. niruri from India on the basis of symptomatology, particle morphology and PCR analysis.

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Ageratum yellow vein virus, molecular detection, symptoms, Geminivirdae and PCR

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Sustainable development, Compassionate Governments, Poverty, Commonsense, Corona Virus, Covid-19, Pandemic, resilient recovery

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Effectiveness. Self-esteem, Motivational enhancement therapy, Leprosy clients, Rehabilitation center.

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Preparation of Graphene, Graphene application

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