Volume 12 | Issue 5

 Abstract

The industrial sector has seen significant change in recent years, moving towards efficient and cutting-edge technologies that have decreased waste production, improved product quality overall, and sped up the time it takes to make goods. Within these industrial areas, where technology has advanced to such an extent that project completion times are a fraction of what they were just a few years ago, is the wood cutting industry. It is not possible to say that this is true for devices that are between two and three decades old. These devices employ antiquated technology and procedures, which results in much reduced accuracy, imprecision, and energy consumption, needless energy, and it is quite difficult to get replacement components for the antiquated systems in the event of a malfunction. The owner of the machine is compelled by these issues to discard these outdated devices. It brings up another issue with getting rid of these computers. Modernising these devices can readily solve the solutions to these issues. The latest systems available on the market offer significantly more processing power and greater connectivity with contemporary devices, enhancing machine precision and facilitating improved operator communication to save energy and time usage. The aspects of the machines will be significantly enhanced by updating them with the aforementioned contemporary technology.

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Wood working, CNC, Multi-headed, high speed spindle, up-gradation, energy conservation.

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The semiotics of love and passion in the ancient Arabic culture; experience of Majnun Laila (Qais bin AL-Malouh) as a model.

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The semiotics of love and passion in the ancient Arabic culture; experience of Majnun Laila (Qais bin AL-Malouh) as a model.

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The psychology of adopted children is a multifaceted field that delves into various aspects of their development, adjustment, and well-being within adoptive families. Research in this area encompasses studies from developmental psychology, clinical psychology, and social psychology, shedding light on the unique experiences and challenges faced by adopted children and their families. This exploration seeks to understand how factors such as attachment, identity formation, and pre-adoption experiences shape the psychological landscape of adopted children. By examining these dynamics, researchers aim to provide insights that can inform supportive interventions and promote positive outcomes for adopted individuals.

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Adoption, Mental Health, Psychological Development, Adopted Child, Behavioural Issues

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Research on drug development is crucial for scientists and pharmaceutical companies. However, there are obstacles and difficulties that affect medication design and development, such as low efficacy, off-target delivery, time consumption, and excessive cost. Big and complex data from clinical trials, proteomics, microarray, and genomes all represent a challenge to the drug discovery process. Drug development and discovery heavily rely on artificial intelligence and machine learning technologies. Stated differently, the field has been modernized by artificial neural networks and deep learning algorithms. Peptide synthesis, structure-based virtual screening, ligand-based virtual screening, toxicity prediction, drug monitoring and release, pharmacophore modeling, quantitative structure-activity relationship, drug repositioning,polypharmacology, and physiochemical activity and other drug discovery processes have all made use of machine learning and deep learning algorithms. Additionally, by accelerating research and development procedures, AI can help lower development costs. Pharmacokinetics and toxicity of potential drugs can be predicted using machine learning algorithms, which also help with experimental design. This capacity lessens the need for extensive and expensive animal research by enabling the prioritization and optimization of lead compounds. Artificial intelligence (AI) algorithms that evaluate real-world patient data can support personalized medicine strategies, improving patient adherence and treatment outcomes. This thorough analysis examines the many uses of AI in medication development, dosage form designs for drug delivery, process optimization, testing.In conclusion, artificial intelligence (AI) in the pharmaceutical sector provides previously unattainable improvements in drug development, clinical trial design, manufacturing, and regulatory affairs. AI has the potential to revolutionize pharmaceutical research and development by speeding up procedures, improving decision-making, and increasing overall efficiency.

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Artifical intelligence ,Clinical Research , Pharmaceutical Industry

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The project titled "A Study on exploring the impact of positive work place culture on employee morale and performance." aims to investigate and analyze the extent of awareness among employees regarding leadership and management practices, growth and development opportunities, recognition and reward system, worklife balance initiative in TI Cycles Of India. This research project will employ both qualitative and quantitative research methods using statistical analysis to assess the employees knowledge regarding leadership and management practices, growth and development opportunities, recognition and reward system, worklife balance initiative . The findings of this study will not only provide valuable insights for TI Cycles Of India to enhance their policies to solve the issues faced regarding on leadership and management practices, growth and development opportunities, recognition and reward system, worklife balance initiative . Ultimately, this research endeavours to promote a more informed and equitable working environment for employees while fostering better compliance practices among organizations.

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Employee morale, workplace culture

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A Go-kart is a small four wheeled vehicle. Go-kart, by definition, has no suspension and no differential. They are usually raced on scaled down tracks, but are sometimes driven as entertainment or as a hobby by non-professionals. Our goal is to design and fabricate an eco-friendly go-kart that offers exceptional performance, driver comfort, and safety. The primary focus is on creating a lightweight kart that delivers impressive performance. Adherence to the rulebook of Edgeline Championship is mandatory and significantly influences our objectives. The go-kart, which is propelled by a rear- wheel internal combustion engine without suspension or differential, has been designed in accordance with standard principles. All critical factors and design parameters have been taken into account, resulting in a thoroughly failure-analysed and ergonomically optimized go-kart. Comprehensive calculations have been conducted for each component, followed by 3D modelling and simulation using professional software tools. The analysis was carried out with different iterations and finally the optimum design of each part of the Go kart was done so as to obtain the optimum result.

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DESIGN, ANALYSIS AND FABRICATION OF GO-KART VEHICLE

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Advances in technology have resulted in a rise in automation across multiple industries in recent times. One such sector is the retail sector, where automation is essential for increasing productivity and simplifying processes. The creation and deployment of a centralized system for automated bill scanning and product information extraction is suggested in this research study. By automatically extracting pertinent information from scanned bills using machine learning and computer vision techniques, the system seeks to completely transform the way bills are processed in retail settings. The suggested system's architecture, including its hardware and software components, is covered in the paper. It also describes the approaches taken in bill scanning, product recognition, text extraction, and picture preprocessing. The system's accuracy and efficacy are illustrated by the presentation of the experimental findings and implementation specifics. The study concludes with a discussion of the possible uses and advantages of implementing such a system in retail environments, including increased customer satisfaction, quicker processing times, and improved accuracy.

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Automated Bill Scanning, Product Information Extraction, Machine Learning, Computer Vision, Retail Industry.

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This research study examines the critical link between financial literacy and personal financial management in the aftermath of India's COVID-19 outbreak. The study's goal is to look at how people's financial literacy skills have affected their capacity to navigate and manage their money in the face of economic challenges caused by this pandemic. The research investigates different factors such as savings behaviour, investment decisions, debt management, and overall financial well-being in the context of post-COVID-19 India using a complete review of current research as well as actual data. For this research project, we employed a primary data collecting technique to acquire real-time information for an investigation of financial literacy towards personal financial management during COVID 19 in India. We adopted the SPSS data analysis technique to check the reliability, which allowed us to locate the genuine data. According to the findings of this survey, the majority managing their own money by budgeting and savings, with some investing in stocks during the pandemic. Everyone has adequate financial literacy for personal financial management, regardless of their educational level or experience. The study concluded that, despite the challenges encountered due to the COVID-19 epidemic, individuals in India have displayed excellent financial literacy, as seen by their assertive approaches to budgeting, savings, and investing, regardless of educational background or experience. They all are aware of the government assistance and programmes offered throughout the epidemic to support the individual life cycle.

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Financial literacy, Personal financial management, COVID-19 outbreak, Savings behavior, Investment decisions, Debt management.

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In alignment with the United Nations' Sustainable Development Goals (SDGs), this research explores a novel approach to promoting eco-consumer behavior through the linking of Reverse Vending Machines (RVMs) with online shopping platforms. The proposed method encourages people to minimize waste and conserve resources by giving them discounts on purchases when they recycle at RVMs. Basically, customers would get a code after buying something which they would use when recycling at specific RVM locations. They would then take a photo of their RVM receipt, with the code. Upload it for verification on the online shopping platform. This paper investigates the role of integrating RVMs in driving sustainable practices and shaping the overall sustainability of e-commerce. It also raises an issue with excessive discounts but promotes customer involvement in environmental responsibility. Multinational corporations may substitute discounts for rewarding behavior to influence customers to be proactive in engaging in environmentally friendly activities. The findings imply that the fusion of RVMs with shopping platforms might help attain more ecological awareness and boost loyalty and engagement levels among consumers. engagement, Environmental responsibility

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Reverse Vending Machines (RVMs), Eco-consumer behavior, Recycling incentives, Consumer

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-- The design and implementation of various wellknown data mining techniques in a variety of real- world applications (e.g., industry, healthcare, and bioscience) has led to their use in machine learning environments to extract meaningful information from provided data in healthcare communities, biological disciplines, and other fields. Early illness prediction, patient treatment, and community services all benefit from precise medical database analysis. Machine learning techniques have been effectively used in a variety of applications, including disease prediction. The goal of developing a classifier system utilising machine learning algorithms is to greatly assist physicians in predicting and diagnosing diseases at an early stage, which will greatly aid in solving health-related difficulties. For our study, a sample of 4920 patient records diagnosed with 41 disorders was chosen. We chose 95 out of 132 independent variables (symptoms) that are strongly associated to illnesses and improved them. The disease prediction system built utilising Machine learning techniques such as Decision Tree classifier, Random forest classifier, and Nave Bayes classifier is demonstrated in this research paper. This paper "Disease Prediction Using Django and Machine Learning" gives a comparison of the outcomes of the aforementioned algorithms.

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--Machine learning, data mining, decision tree classifier, random forest classifier, naive bayes classifier

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To secure the greatest results for upcoming entrepreneurs, educators must continually update the curriculum, processes, and educational process in view of the shifting entrepreneurial environment. The competitive higher education market offers an incentive for attracting entrepreneurs with programs that are up to date and best guarantee the development of new enterprises. The entrepreneurial climate has influenced educational program expectations. This paper reviews some of the entrepreneurial skills required to start a firm successfully and offers recommendations for innovative training strategies that take into account the evolving Indian business landscape.

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Entrepreneurship education, programs for academics, Entrepreneurial abilities

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A campus placement prediction system is developed to calculate the possibility of a student getting jobs in a company through campus placements. The model takes many parameters that can be used to get an idea about the skill level of the student. While some data are taken from the college level like academic performance, CGPA, pointers, attendance etc. others are obtained from tests conducted in the placement management system. Combining these data points, the model is to accurately predict if the student will or will not be placed in a company. Also, Data from past year students are used for training the model. We are using educational data mining by which we can get real past year's student data of that specific college.This will help the machine learning model to be more effective about the predictions of that particular college.The purpose behind this placement prediction system is to help students improve their results, and academic performance and also develop another soft skill that will help them to maximize their chance of getting placed. Such a study will help the faculties of the college to train the students accordingly and improve the placement department of their institutions. This will give an idea about how students are doing and will ensure their institution can satisfy the needs of recruiters. For this supervised machine learning especially logistic regression is better, Logistic model designing plays a key role in getting correct predictions. This process includes the selection of tuples for training data and their preknown outcome often known as real data.

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Data Mining, Campus Placement, Logistic Regression, Machine Learning, Accuracy, Prediction.

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The indiscriminate utilization of contract labour and the recent amendments in labour codes governing social security are posing serious challenges to the welfare and livelihood of workers, significantly undermining their job security and social well-being. Contract labour arrangements often lead to exploitation as workers are vulnerable to low wages, long working hours, lack of benefits, and job instability. The new labour codes, instead of safeguarding workers' rights, prioritize flexibility for employers at the expense of workers well-being, exacerbating the already prevalent inequality in society. Significant hurdles in accessing social security benefits, including health insurance, retirement plans, and maternity benefits. With the introduction of new labour codes, social security provisions are becoming even more in accessible for such workers, further compromising their financial stability and quality of life. This study aims to identify role of new labour codes comprehensively in securing contract labour, in conjunction with the recent amendments.

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Labour Law,Labour Codes,Social Security,Contractual Labour Regulations, GST, Unorganised Sector, Secondary Research, Financial Stability, Quality of Life, Ease of Doing Business.

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The Roadside Shop is an innovative startup aimed at revolutionizing the scrap collection and recycling industry in India. By leveraging modern technology, including mobile applications and a dedicated website, The Roadside Shop offers a convenient and environmentally friendly solution for households to dispose of their scrap. This initiative focuses on segregating various types of scrap materials, providing customers with the best value, and ensuring proper recycling processes. This report details the purpose, scope, and technologies involved in The Roadside Shop, alongside the background, literature review, methodology, implementation, and projected results of the project.

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o Scrap Collection o Recycling o Doorstep Service o India o Mobile App o Online Payment

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Lechate collected from the dumping site and contaminated area at different time periods indicated significant difference in chemical composition and mercury concentration. Hence, it was planned to prepare the extract by taking the solid waste from the dumping site and preparing the extract in the laboratory, now known as solid waste extract (SWE) for the experimental purpose. The solid waste extract contained 9.75 mg of Hg l -1. This prepared solid waste extract was considered equivalent to the leached chemicals leaching in rainy season and entering into neighboring ponds and crop fields and water bodies like Rushikulya River and estuary. The ATPase activity in SWE exposed fish brain, liver and muscle tissues showed 41.03%, 63.9%, and 49.6% decrease over respective control values, where the SWE exposed fish liver was more damaged than other tissues tested. Significant depression in ATPase enzyme activity may severely affect the ion transport mechanism of the exposed fish body when compared to control fish body. The exposed fishes were when transferred to SWE free medium the enzyme activity showed no recovery at all rather further depletion was noted. During recovery period the exposed brain tissue was drastically affected, might be due to mobilization and transport of more amount of residual mercury from the body tissues to the brain. The changes observed in exposed liver and muscle tissues were interesting and the observed changes were not statistically significant. Significant differences in ion content of different tissues of the exposed fish when compared to control fish clearly indicated the nature of the toxicant and effects caused by the SWE toxicant on the nervous tissue, synaptic transmission, nerve impulse generation, ionic balance and membrane transport system of the exposed fish. The exposed fishes did not recover when transferred to SWE free medium. The enzyme activity showed no recovery in liver, brain and muscle tissues but little variation during recovery was not statistically significant. Exposed liver tissues showed the highest damage when compared to brain and muscle tissues of the exposed fish, when compared to control fish tissues.

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Chlor-alkali industry, Solid waste, SWExtract, fish, Tilapia, ATPase.

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The study aimed to formulate a pure herbal shampoo and to evaluate and compare its physicochemical properties with the marketed synthetic and herbal shampoos. The herbal shampoo was formulated by adding the extracts of Acacia concinna, Sapindus mukorossi, Phyllanthus emblica, Ziziphus spina-christi and Citrus aurantifolia in different proportions to a 10% aqueous gelatin solution. Every single manufactured item like cleanser contains a destructive substance which is in charge of damage of hair. HS is the only product which used for hair washing and also used for hair remedy on hair problem. In recent study herbal HS (HS) has remarkable properties toward hairs. Greener preparation of HS made has two sections, In first section contain, herbal extract prepared by mixtue of amla, reetha, shikakai, nagarmotha, bhringaraj, brahmi, aloevera, lemon juice and some Ingredients. Herb extract (10%) take an amla, reetha, shikakai, nagatmotha, bhringaraj, brahmi all in dried form in a beaker in aqueous medium, warm up to till the beginning of boil by microwave method, sieve and put for cooling, obtained herb extract. For their transparency add some lemon squeeze in it, followed by mixing up to colourless. In second section beaker contains SLES, glycerin and CAPB everyone followed by stirring gradually, Herb extract with lemon juice in it stir gradually due to avoid foaming. Preservative methyl paraben and sodium benzoate, for pearlising impact with EGMS to it. Pour an Aloevera in it, with small concentration of cocamono in it, mockup with water in it for small proportion, increasing a thickness with cocodi, obtained product HS. The formed HS is thick semi white transparent in colour, with great foam producing ability and fluidity. The pH of HS is between 6-7 at 250C RT, formed HS is acidic in nature which is good quality. Percentage of solid contents of HS is 0.05g after dry. The cleansing action of the formed HS is All these are these characters demonstrates that the herbal HS is high quality for usable in daily life.

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Herb Extract, Greener preparation, Cocodi, Cocamono, Herbal HS (HS), Microwave method.

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With the increasing popularity of location-based social networks (LBSNs) and the abundance of food related content shared by users, there is a growing interest in developing eatery spot recommendation systems that leverage LBSN data. This research paper proposes a system (ESRS) that utilizes LBSN data to recommend personalized dining options to users based on their location, preferences, and. The ESRS employs a hybrid recommendation approach, combining collaborative filtering techniques with geographical proximity analysis and user feedback to enhance the dining experience of users. The ESRS not only enhances the dining experience for users but also benefits local businesses by increasing foot traffic and customer engagement. The user feedback mechanisms are integrated to gather real time inputs and improve the recommendation accuracy over time. The system aims to address the challenges of information overload and decision fatigue faced by users when choosing dining venues, ultimately enhancing user satisfaction and engagement in the dining experience.

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Recommender system, collaborative filtering, user feedback, location based social network

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The work presented here deals with formulation and evaluation of herbal antidiabetic capsule containing dried powder of Momordica Charantia Fruit. Medicinal plants are commonly known for their therapeutic value and free from side effects. Keeping this in view, the development of antidiabetic drug from the natural plants being a major thrust area has drawn the attention of the researchers in the field of natural product research because synthetic drugs may cause unwanted side effects. But the lack of complete evaluation for herbal formulations is the most important challenges faced. So, the quality control evaluation is necessary to ensure the quality of the herbal formulations. Hence the present study was aimed to formulate the herbal capsules using the dried powder of Momordica Charantia fruits and evaluated the pharmaceutical quality of herbal capsules formulated. The evaluation parameters include weight variation, disintegration time and uniformity of weight tests. The herbal capsules formulated were achieved the criteria within permitted range for conventional dosage forms as per pharmacopoeial standards. The findings suggested that the formulated herbal capsules of dried powder of Momordica Charantia fruits have passed through all the evaluation parameters .

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Bitter gourd, Diabetes Mellitus , Herbal Capsule, Evaluation.

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Resazurin Microtitre Assay, KAARA SODA SATHU PARPAM (KSSP), UTI, Drug resistant, Ancient, Potential, Siddha medicine.

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This article represented to the cave temples at Bhairava cona. That rock caves during the time of the Pallavas and Telugu Cholas in the Nallamalla forests between Nellore and Prakasam districts. Similar ones are found in our Andhra Pradesh Vijayawada and Visakhapatnam. But the caves here were built by Mahadevavarma and later kings during the Pallava period. Most of the rock treasures here are close to the Pallava structures in the Tamil Nadu region

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Bhairava Kona , Trimurth, gatekeepers, Nandiswara Vigneswara and Chandiwara the Pallava period. J. Dubrail, Raja Poreri,chitrakantha, Veerakanta,Chitrakantha" Trichinapolai, Dhalavanur, Mandagapattu, Dindi, Mundi, Brahma Sutra lingas.Shani Nagalingam, respectively.Rudranadeswaralingam,.Rama Lingam, Naga Lingam , Bhargaleswaralingam,Sri Saila Mallikarjuna Lingam,Vakshaghathalingam,Ashtakal Prachanda Bhairava Lingam

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