Volume 11 | Issue 5

 Abstract

Mayonnaise is a thick, white, creamy condiment prepared by emulsifying eggs, oil, lime juice, and vinegar. Globally variety of products such as burgers, sandwiches, salads, dips, sauce, pasta, and pizza served with mayonnaise as a core ingredient. This is one of the key reasons driving the market expansion, along with the expanding food and beverage (F&B) market. The growing demand of mayonnaise in market is mainly attributed to the growing working population, fast urbanization, increasing purchasing power, and higher standards of living of people. Globally, Cardiovascular diseases occurrence is growing in human being and main cause is fatty food consumption. Fat substitutes in specific quantities are possible to produce a product with a texture close to that of traditional mayonnaise. Therefore, it is a big challenge to use fat analogue with different functions to remove partial fat and remain traditionally pleasant. Tapioca Starch is a capable fat replacer which is low in calorie and can be used in many foods without fat. Hence the research is undertaken to incorporate tapioca starch as a fat replacer in mayonnaise and standardize the formulation to produce stable and acceptable low-fat mayonnaise. The oil was replaced by tapioca starch paste in mayonnaise samples and were assessed for sensorial, textural and microbial assessment. The 40% tapioca starch paste level was found to be overall acceptable. The texture and viscosity as a rheological property of formulated low-fat mayonnaise has shown similar behavior to the control variant, and the standardized mayonnaise has the advantage of higher emulsion stability and preserved the sensory characteristics over storage tenure.

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Low-fat mayonnaise, soybean oil, peroxide value, tapioca starch, mayonnaise shelf-life

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 Abstract

The increasingly worldwide problem regarding rapid economy development and a relative shortage of energy, the internal combustion engine exhaust waste heat and environmental pollution has been more emphasized heavily recently. Out of the total heat supplied to the engine in the form of fuel, approximately, 30 to 40% is converted into useful mechanical work; the remaining heat is expelled to the environment through exhaust gases and engine cooling systems, resulting in to entropy rise and serious environmental pollution, so it is required to utilized waste heat into useful work. The recovery and utilization of waste heat not only conserves fuel (fossil fuel) but also reduces the amount of waste heat and greenhouse gases damped to environment. The study shows the availability and possibility of waste heat from internal combustion engine, also describe loss of exhaust gas energy of an internal combustion engine. Possible methods to recover the waste heat from internal combustion engine and performance and emissions of the internal combustion engine. Waste heat recovery system is the best way to recover waste heat and saving the fuel.

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"Air Preheater"

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According to Theory of Magnetic Force on Current carrying Conductor [ILB & Right Hand Rule]. In presence of magnetic field and current in Conductor which is perpendicular, will give you Force but in presence of current in a loop that can not give you linear [ translation] force and centre of mass will remain at rest [it happens in motor ]. If we some how able to make a such system in which all current in wires move in one direction and it will give you Force in one direction[centre of mass will move ].This system will give you an anti-gravity effect through which lift the box and we get huge potential energy at low input electrochemical energy[battery]. This system can be used in generation of electricity even in space

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 Keywords

Index Terms - ILB[current *length in magnetic field*magnetic field ], Right Hand Rule[give you direction of current, magnetic field and force

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This study discussed the concept of e-learning and its potential impact on the education sector in Bangladesh. It highlighted the importance of technology-based learning in today's digital age and emphasizes the benefits of e-learning in providing access to quality education, particularly for those in rural areas with limited resources. This research also acknowledges the challenges faced by the education sector in Bangladesh, such as the lack of quality teachers, content, and infrastructure. The significance of the study lies in promoting e-learning as a solution to these challenges and improving the education system in Bangladesh. The objectives of the study include understanding the importance of e-learning, assessing its acceptability, and exploring its potential for knowledge improvement. The methods employed in the study involve collaboration with international partners, addressing local needs and conditions, and conducting monitoring and evaluation to ensure the effectiveness of the e-learning system. This study also contains a literature review on e-learning, discussing its definition, effectiveness, and various tools and applications. It also explores the use of e-learning in rural areas of Bangladesh, distance education, and its contributions to higher education in the country. The review further explores the use of e-learning in rural areas of Bangladesh, where inadequate educational resources and a lack of qualified teachers and healthcare providers are common challenges. It suggests that e-learning can help address these issues by providing access to quality education and healthcare through the use of ICT tools.

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ICT, E-learning, Learning Management Systems, Collaboration Tools, Distance Education.

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Telepsychology has successfully made its way into the practice of new generation of counsellors. Especially, with the pandemic acting as a catalyst in this. The studies have shown the gradual rise in intake of online counselling as a mode of providing services. Even though the effectiveness of online counselling is at a par with traditional mode of counselling. The psychotherapists and counsellors are given less treatment in this aspect of how to adopt to technology in-order-to provide counselling services. This study aimed to understand the influence of Acceptance and Use of Technology and perceived self-efficacy on the establishment of therapeutic alliance. A sample of 54 counsellors from Noida, were administered the scales UTAUT-T, CES, and WAI-SR-T. The data analysis that was undertaken was correlation and multiple regression. The study concludes that there is a positive correlation among the three variables and in multiple regression UTAUT-T was statistically significant in the influence of therapeutic alliance than Counselling self-efficacy.

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Telepsychology, Online Counselling, Self-efficacy, Acceptance of Technology, UTAUT

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ABSTRACT: Human Resource is increasingly receiving attention as critical strategic partner, assuming stunningly different, far reaching transformational roles and responsibilities. Human asset is having most important priority in the organization and it integrates all human resource policies and programmes the frame-work of the company strategy. Human resources help in transforming the lifeless factors of production into useful products. It is endowing products and services with the power of the brand. Branding involves creating mental structure and helping consumer organize their knowledge about product and services in a way that clarifies their decision making and in the process provides value to the firm.

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Human Resource Branding, Organizations.

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Due to health problems such as epidemics and any emergencies, many schools, universities and educational institutions are forced to stop using their facilities for educational purposes, so many of them have switched to virtual education. All these educational institutions have begun to choose digital tools. such as: Google Meet, Microsoft Team, and Zoom to bring classes and teach students. 24per cent were unaware or for some reason their academic performance was not improved. The main objective of this project is to create a livelihood where both teachers, teachers can monitor their students behaviour can obtain relevant data about the class.

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monitor, behaviour , facial expression , live monitoring,

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Countries promoting renewable energies encounter a variety of phenomena that can challenge the implementation of further onshore wind energy development. Those challenges can be observed in many multi-level governance systems, as exhibited in the U.S., Germany, and Mexico, where various regulatory and institutional levels must agree on goals and responsibilities. This is a challenge, as both forms of governance (top-down and bottom-up dominated) are present in wind energy planning and policy. (1) Political and market phenomena, (2) siting issues, (3) the green vs. green dilemma, and (4) social acceptance are selected challenges within the different levels of decision-making processes in wind energy implementation. (1) Political and financial factors can influence the development by implementing incentive- and market-based policies, command-and-control policies, and feed-in tariffs. However, success of these policy designs for renewable energies is based on different political environments, and their electricity markets nationally, regionally, or statewide. (2) Spatial limitations in planning are created based on limited land availability due to conflicts with other land uses such as aviation, nature reserves, residential areas, their respective buffers. (3) The "green vs. green" dilemma involves the incoherent relationship between policies promoting renewable energies with policies protection species and their environments, becoming a major point of concern during siting and operations of wind energy. (4) Lastly, while there is a general overall support for wind energy, social acceptance on a local level is influenced by institutional settings i.e. information availability, as well as public and stakeholder concerns. Involvement in decision-making as well as financial participation (e.g. community-ownership) affects public participation and acceptance. This paper goes into detail on these phenomena and discusses case studies in Europe and North America. Often, these challenges can enhance outlooks in policy and planning, posing solutions to wind energy challenges even in sensitive environments and triggering innovations such as adaptive management.

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Wind energy, OSH risks, Safety and Environments

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The paper is a study of Neuro-linguistic programming, or NLP, that is a way to improve self-expression, persuasion, and conversation by tapping into the subconscious mind. It encourages personal growth and addresses communication issues. NLP, which stands for "neurolinguistic programming," is the study of how words can help people think better. NLP is a powerful tool for healing and self-improvement, even though some scientists are skeptical about it. The paper further analyses Barack Obama's speeches, it is evident that he skillfully employs NLP techniques to connect with his audience. It explore the dimensions such as, building rapport is a key element, as he speaks in a language that resonates with listeners and acknowledges their identities. By doing so, he establishes a strong bond and ensures that each individual feels included and heard. It also highlights that style that Obama emphasizes commonalities and uses storytelling and metaphors to engage the audience, keeping their attention and fostering a sense of involvement. In conclusion, the paper asserts that Barack Obama's victory speeches showcase the effective utilization of NLP techniques. Through rapport building, connecting on a personal level, and employing storytelling, he effectively communicates his message and connects with the masses. It concludes with the observation that NLP plays a significant role in enhancing the impact and effectiveness of his speeches, allowing him to build rapport and create a strong connection with his audience.

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neuro-linguistic programming, metaphors, subconscious mind, rapport building

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In today's world the credit card fraud is the biggest issue and now there is need to combat against the credit card fraud. "credit card fraud is the process of cleaning dirty money, thereby making the source of funds no longer identifiable." On daily basis, the financial transactions are made on huge amount in global market and hence detecting credit card fraud activity is challenging task. As earlier (Anti- credit card fraud Suite) is introduced to detect the suspicious activities but it is applicable only on individual transaction not for other bank account transaction. To Overcomes issues of we propose Machine learning method using 'Structural Similarity', to identify common attributes and behaviour with other bank account transaction. Detection of credit card fraud transaction from large volume dataset is difficult, so we propose case reduction methods to reduces the input dataset and then find pair of transaction with other bank account with common attributes and behaviour.

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Fraud Detection, Credit Card, SVM, Decision Tree, Machine Learning.

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Waste Tyre rubber is one of the most significant environmental hazards worldwide because of the increase in auto mobile production, there is a need to properly dispose the vast amounts of used rubber tyres. Due to the rapid growth in automobile industry. The disposal of waste tyres has facing major problems in India. The growing problem of waste tyre disposal in India can be solved if new recycling routes can be found. It is estimated that 1.2 billions of waste tyre rubber produced globally in a year.

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Rubber Tyre Waste, Materials Required, Methodology, Test on Fresh Concrete.

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This paper is commonly discussing about the battery validation used during electric vehicles regarding bulge, dilate, flatten, etc. The paper is motivated by the fire incidents occur due to explosion of battery. However, the nearby challenge is to eradicatethermal runway process. Numerous of these factors come in the form of thin partitions that are relatively fragile, and if they come punctured or pierced a spark may do and start a fire. In contrast, thermal and electrodynamic characteristics of lithium-ion battery performance will be identified. Using an STM32 controller, the recommended circuitry is a research aimed at optimising the battery management system's parameter validation. This paper presents the results of a battery simulation analysis for protection of battery by constant monitoring battery voltage, current and temperature instantly as in real-time life health to improve battery effectiveness under typical condition.

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battery , battery explosion ,

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This review article provides an overview of the advances in herbal treatments for cancer. The article summarizes the latest research on the use of herbal medicines in cancer treatment, including their mechanisms of action, efficacy, and safety. It covers a range of herbs commonly used in cancer treatment, such as turmeric, green tea, and ginseng. The article also discusses the potential benefits of herbal medicine as an adjunct to conventional cancer treatment and the challenges in integrating herbal medicine into cancer care. The review concludes by highlighting the need for further research to better understand the role of herbal medicine in cancer treatment and improve patient outcomes.Herbal medicines have been used for centuries in traditional medicine systems for their therapeutic properties, including anti-cancer effects. In recent years, there has been growing interest in the use of herbal medicine as an adjunct or alternative therapy to conventional cancer treatments, such as chemotherapy and radiotherapy. Advances in scientific research have helped to elucidate the mechanisms of action of herbal medicines and validate their anti-cancer effects. This review article discusses some of the most promising herbal medicines for cancer treatment, including curcumin from turmeric, epigallocatechin-3-gallate (EGCG) from green tea, ginsenosides from ginseng, and resveratrol from grapes. It also explores the challenges in studying herbal medicine in cancer treatment, such as variability in the quality and composition of herbal products, and the need for standardized clinical trials to evaluate their efficacy and safety.The review also highlights the potential benefits of using herbal medicine in cancer treatment, such as reducing the side effects of conventional treatments, improving quality of life, and enhancing the body's immune response to cancer. However, it emphasizes that herbal medicine should not be used as a substitute for conventional cancer treatments, but rather as a complementary therapy that can work in synergy with conventional treatments to improve patient outcomes.

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Diet; Herbs; Spices; Cancer prevention

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Women have been victimized in the patriarchal and caste-based society on a greater level. Their unheard and untold stories of atrocities and traumas are brought to the mass by Meena Kandasamy. She is a writer with a lot of aggression and a lot of rebellion, and her uncontrolled emotions for the subjugated community gets highly reflected in her writings. Ms Militancy (2010) is a violent as well as powerful poetry collection by Meena Kandasamy where she explores the social reality of our society and problematizes the camouflaged dissemination of power through her intensely inquisitive poetry. The paper intends to study how Ms Militancy in Dalit literature becomes a strong resistant narrative through the resurrection of the humiliated, tortured, and exploited groups in society. Meena Kandasamy's war of resistance is against institutional patriarchy and the caste-based Brahmanical Hindu society.

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Keywords: Dalit literature, patriarchy, Brahmanical Hindu society, voiceless.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

To Optimize the Mechanical Properties of Hybrid Composite Material. To Manufacture epoxy based composites with different weight % fiber.

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To Optimize the Mechanical Properties of Hybrid Composite Material. To Manufacture epoxy based composites with different weight % fiber.

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Because of the intricacy, unconventionality, and nonlinearity of monetary frameworks, it is challenging to anticipate stock costs precisely. The PCC-BLS structure, a stock expense deciding multi-pointer feature decision method considering the Pearson connection coefficient (PCC) and Broad Learning System (BLS), was presented in this brief. PCC chose the initial stock price, technical indicators, and financial indicators as input characteristics from a list of 35 options. Second, a BLS was trained with these filtered input characteristics and information features were quickly extracted. The proposed strategy's performance was evaluated using four stocks that are either listed on the Shanghai Stock Exchange or the Shenzhen Stock Exchange. In addition, the forecasting results were compared to those of the Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), Broad Learning System (BLS), Random Forest (RF), Gradient Boosting Decision Tree (GBDT), Multi-layer Perceptron (MLP), and Support Vector Regression (SVR). The highest modelfitting capability was demonstrated by the proposed model, which outperformed all other algorithms in this brief.

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Broad learning system, machine learning, Pearson correlation coefficient, time series forecasting, complex system.

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The present study examined the relationship between workplace procrastination, work load and work performance among working individuals in India; the difference in procrastination, work load and work performance between males and females along with understanding the impact of procrastination on work load and work performance. The data was collected in hybrid mode within the age group of 20- 40 years from 202 working individuals employed in IT sector and involved in software development domain, residing in India using Procrastination at Workplace scale, Quantitative Workload Inventory and Individual Work performance Questionnaire. Statistical analysis of correlation, independent sample t test and linear regression was done to test the hypothesis. The results indicated that the variables, procrastination, workload and work performance were correlated to each other; independent variable procrastination influenced the dependent variables work load and work performance; and these variables do not have difference among males and females and different age bracket. Implications, limitations and future suggestions of the study were also stated.

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Workplace Procrastination, Work load, Work performance, Working Individuals

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An approach to accurately acknowledge various Yoga pose Assess deep learning algorithms has been presented during this work. During system, our purpose to access a Yoga pose assessment technique using pose detection to assist the self-learning of Yoga. The system first detects a Yoga pose using multi human joint parts detection only with laptop camera. During this system, we have a tendency to additionally propose AN improved formula to calculate scores which will of all poses. Our application is evaluated on completely different Yoga poses. A hybrid Machine learning model is proposed using Logistic Regression algorithm for Yoga recognition on real-time videos, where Logistic regression is used to extract features from key-points of each frame obtained from Open-Pose. LR algorithm would be trained on a labelled dataset of correct and incorrect yoga poses, and its output could be used to provide real-time feedback to the practitioner.

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Logistic Regression, Anaconda navigator platform, Deep Learning , Yoga Pose detection, etc.

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The issue of work-related stress has become increasingly prevalent, as it not only affects the health and well-being of employees but also impacts the productivity of organizations. To delve deeper into this problem, a study was conducted to examine how work-related stress influences job performance and which gender is more susceptible to its effects. The research design implemented a quantitative approach, with a sample size of 100 individuals (50 men and 50 women) selected from a reputable technology company based in Mumbai. The results indicated that work-related stress has an adverse effect on job performance, with male and female employees experiencing a similar impact. These findings underscore the importance of addressing work-related stress to enhance job performance and prevent negative consequences

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work-related stress, job performance, gender

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Cryptocurrency becomes more popular and merchant accept it, it is playing an increasingly vital role in reshaping the financial system. While many people are forming investments in Cryptocurrency, the vital features, distrust, the predictability of Cryptocurrency are quiet basically unknown, which dramatically risk the investments. It's a business to strain to conclude the procurators that impact the value formation. Here we apply advanced artificial intelligence frameworks of completely connected Artificial Neural Network (ANN) and Long Short Term Memory (LSTM) periodical Neural Network to analyze the price dynamics of Bitcoin, Ethereum, and Ripple. We find that ANN tends to calculate more on long- term chronicle while LSTM tends to calculate more on short- term dynamics, which indicate the effectiveness of LSTM to exploit useful data hidden in literal memory is stronger than ANN. still, given enough historical data ANN can attain an analogous accurateness equated with LSTM. This reverie provides a unique demo that Cryptocurrency market price is predictable. Still, the explanation of the predictability could differ depending on the complexion of the detailed machine- learning model.

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Artificial Intelligence, ANN, LSTM, Block Chain.

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Creative Commons Attribution 4.0 and The Open Definition