Volume 7 | Issue 1

 Abstract

Nowadays, the primary computer device is a mobile phone. People are often requesting more resources than a mobile device can provide. To counteract this, a mobile device needs get assistance from an outside source. One of such channels is cloud computing. The emergence of mobile cloud computing and its potential development are discussed in this essay on cloud computing. It compares the ideas of mobile cloud computing and cloud computing, as well as their features, benefits, implementations, implementation issues, potential solutions, future scope, and analysis.

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Mobile Cloud Computing; Mobile Computing; Cloud Computing; Research Directions

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In this paper we present some approaches of methods in multi-objective linear programming in different field of Integer programming the basis concept of these available exact methods.

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Multi-Objective Integer Linear Programming, Optimization Techniques

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Ayurveda, which means the science of life and is a medicinal system in India, derives from the words "aye," which means life, and "veda," which means to know. In 1930, Mr. Manal founds the Himalaya Pharmaceutical Company. A few years later, his older brother Mr. Misal joined him, and the two of them began expanding the business. An trade or transaction meant to satiate human needs or wants is at the heart of marketing. In other words, marketing is an activity carried out by people to fulfil their needs and desires through an exchange process. A demand is a wish that the customer is willing to spend money for. Anything or a service that a consumer wants or seeks is considered a want. When supported by the ability to purchase, desires become demands. A needs is anything the consumer feels to keep himself alive and healthy.Thisrange offers the goodnessof naturalsolutions for daily use,withnosideeffects. Personal care products is one of the very essential and common use consumer products foreveryindividualintheirdayto daylifeirrespectiveofrichandpoor, casteandreligion, etc.,inorder to facilitatethepresentstudyfirstofallitwillbebenefitforustohaveabirdseyesinviewofHimalayaherbalmarket in Coimbatorecity.

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A REVIEW ON CUSTOMER SATISFACTION WITH HIMALAYA PRODUCTS, PREFERRING PARTICULAR CITIES

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Dysgraphia is a condition that affects writers' ability. Identification of dysgraphia at an early stage of a child's development is a difficult task. It may very easily be identified using challenging skills associated to the Dysgraphia issue. Space knowledge, copying skills, and Visual Spatial Response are some of the elements used in this review engine capacity for Dysgraphia identifiable evidence. Using an element selection technique, the factors influencing dysgraphia inability is examined EN (Elastic Net). AI tactics are used to organize the crucial provisions. On the Dysgraphia dataset, the models considered in this sequence are KNN (K-Nearest Neighbors), Naive Bayes, Decision tree, Random Forest, and SVM (Support Vector Machine). Results demonstrate the best of the Random woodland arrangement model for Dysgraphia recognizable proof.

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Dysgraphia, Learning hardships, Machine Learning.

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Credit card theft has increased as e-commerce has expanded. Banks are having a harder time identifying credit card fraud as a result of the industry's explosive growth. One of the most crucial tasks that machine learning performs in preventing credit card fraud is the identification of fraudulent purchases. Banks estimate these types of transactions using a range of machine learning techniques, building on historical data and adding special characteristics to boost prediction accuracy. The strategy for sampling the data set, the choice of variables, and the detection process are all crucial to the effectiveness of credit card fraud detection. The usefulness of decision trees, random forests, and logistic regression in identifying credit card fraud is examined in this study. A dataset of 2, 84,808 credit card transactions from a European bank collected using kaggle. It defines fraudulent transactions as "positive class" and valid purchases as "negative class," but the data set is considerably skewed, with just about 0.172% being fraudulent and the rest being legitimate because to the author's frame interpolation efforts, the dataset now contains 60% fraudulent and 40% valid transactions. The dataset is subjected to each of the three approaches, and the output code is written in the programming R. Several metrics, including as sensitivity, specificity, accuracy, and error rate, are utilized to analyze the efficacy of the approaches in relation to the aforementioned criteria. The accuracy of the logistic regression, decision tree, and random forest classifiers was 90.0, 94.3, and 95.5%, respectively. When evaluated to logistic regression and decision trees, the Random forest outperforms both.

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EFFECTIVE DETECTION OF CREDIT CARD FRAUD USING LOGISTIC REGRESSION, DECISION TREE AND MACHINE LEARNING TECHNIQUES

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Wireless Sensor Networks are usually composed of a lot of distributed sensor nodes that organize themselves into a multi-hop wireless network. Several of the main problems in wireless sensor networks are actually energy usage, lack of authentication data integrity as well as instability of load link between sensor nodes which brings down the acceptance of the sensor network. The latest communications in wireless sensor networks (WSNs) have a lot of new energy-efficient protocols especially designed, in which energy recognition is actually an important concern. Inside WSNs, many small sensor nodes are utilized as a good means of data collecting in a variety of environments. Since the sensor nodes run on the battery of power that is restricted, it's an excellent demanding goal to develop an energy-efficient routing protocol, which may lessen the delay while providing long span and high energy efficiency of network lifetime. Our proposed item is actually improved from LEACH protocol by adapting node scheduling program (active and sleep) in heterogeneous and homogeneous node topologies of WSNs, which yield better performance in energy saving and then improved network lifetime. The work carried out is presented in this thesis will be based on simulations of newly designed routing protocols, from the key routing protocol of clustering based hierarchical, routing protocol namely called LEACH (Low Energy Adaptive Clustering Hierarchy). Simulations allow for more aspects to be evaluated and more parameter values to be investigated, than what would be possible using real applications in real wireless sensor networks. Nevertheless, the accuracy of every simulation is dependent on the accuracy of the simulation models used in the developed routing protocols

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Leach Algorithm, Energy Efficient Routing, Wireless Sensor Networks, energy efficiency etc.

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 Abstract

Sarv Skihsa Abhiyan

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Sarv Skihsa Abhiyan

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In past few years, the world has experienced a high rise in the market of poultry industry. This industry has added a non degradable feather waste to the environment on very large scale. This feather is even not degraded by the enzymes such as Trypsin and Pepsin and has become a global issue. Use of microorganisms in feather degradation is a trending and eco-friendly solution. The ultimate aim of the current study was to degrade feather using keratinolytic bacteria. Bacteria were isolated and screened from the soil samples collected from the dumping yards of chicken shops, poultry farm and feather waste collected areas. Total 68 different bacterial isolates were isolated and checked for their potential to degrade feather waste. Among them isolate C1B is gram positive, rod shaped, endospore forming bacterial species , morphological and biochemical identification showed that isolate C1B was Bacillus species. It was found that the bacterium had the efficiency of degrading 84.5% of feather within 72h. The bacteria used feather keratin as a principal source of carbon, nitrogen, sulphur and energy. The present study would highlight the degradation of feather waste using bacteria.

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Poultry Industry, Feather Waste, Waste Degradation, Bacteria, Keratin.

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Machine learning, Heart Disease, Decision Tree, Naive Bayes, Neural Network, Deep Learning and SVM.

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We humans are known for maintaining cleanliness may it be our home or the vehicle we travel in. As we know the number of vehicles worldwide increasing day by day hence keeping the vehicles clean have become a big issue. People often tend to give their vehicles outside for cleaning; therefore spending a lot of money and some in order to save money, people exhaust their time and energy cleaning the vehicle themselves. We live in a period where all the works are made to be done by a machine either automatic or remote controlled. The already existing automatic car washer is very costly and takes huge place for a family to install for their personal use. Hence we have come up with a solution of a car washer which is remote controlled and are affordable for family use, which can be parked in the corner of a parking when not in use. This project is about reducing size and cost of the machine that is used for washing vehicle. The machine is remote controlled hence contains transmitter and receiver. For the movement of the machines motors and wheels are used. For the better cleaning the water is directly connected to the tap by the help of pipe and using pump and pressure gun the water is then sprayed. The glass washer and car washing liquid is stored in a container and is sprayed as and when required using a motor and drip technique. The arm is rotated using motors. The wheels of the vehicle are also taken into consideration and there is a separate brush which is used for the cleaning of the wheel. Safety of the car and the operator and the machine is also taken into consideration and hence sensors are used which when detects the machine too close to the vehicle which may cause any harm to the vehicle then it gives out an alarm to warn the operator. Aurdino is used for some of the operations to be performed under some cases and waterproofing of the devices is very important in order to avoid electrical shortage and loose connection, tight packing is given priority.

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Car Washer, Aurdino, Sensors

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This comprehensive review critically analyses the complex correlation between DC microgrids and the incorporation of Distributed Generation (DG). It offers a full evaluation of fundamental principles, advanced control strategies, technology advancements, and practical implementations in real-world scenarios. This research examines the ability of Direct Current (DC) microgrids to effectively integrate and optimize various DG sources within the context of a paradigm shift towards decentralized energy solutions. The paper critically examines the obstacles and opportunities associated with renewable energy systems and different DG technologies. It provides essential insights for researchers, engineers, and politicians who are involved in the complex process of integrating distributed energy into existing systems. This review serves as a crucial resource that contributes to the understanding of DG in DC microgrids. It plays a significant role in developing conversations surrounding energy solutions that are both resilient and sustainable.This paper not only discusses the difficulties related to the integration of DG, but also emphasizes practical examples that demonstrate the flexibility and effectiveness of DC microgrid designs. This study serves as a crucial resource for stakeholders who aim to use the potential of DC microgrids, since it encompasses a comprehensive analysis of power electronics, energy storage, and sophisticated control systems. By combining critical evaluation with practical implementation, this review offers valuable insights and guidance in the field. The complete investigation plays a significant role in advancing the integration of DG, which is essential for creating a resilient and sustainable energy environment. It provides basic information that is needed for achieving effective integration. This review paper provides a comprehensive examination of the integration of DG within DC microgrids. From laying the groundwork with fundamental principles to scrutinizing challenges, technological advancements, and practical applications, this review aims to offer a holistic understanding of the dynamic landscape where DC microgrids intersect with distributed energy generation.

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DC Microgrid, DG, Renewable Energy, Power Electronics, Energy Storage, Control Strategies, Integration Challenges.

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Speech processing has witnessed significant advancements in recent years, with probabilistic models playing a pivotal role in enhancing various tasks, including speech recognition, synthesis, and understanding. This paper presents a comprehensive review of recent trends in speech processing, focusing on the application of probabilistic models. We explore the theoretical foundations, methodologies, and practical implementations of probabilistic models in speech processing tasks. Additionally, we discuss the challenges, emerging trends, and future directions in this rapidly evolving field.

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A Novel and Realistic Review on Recent Trends in Speech Processing Using Probabilistic Models

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Mangroves are halophytic species and help stabilise the coasts and river lines, protecting them from tides, waves, and heavy wind. It also functions as a breeding and feeding ground for several aquatic species. India represents the world's 5% mangrove forest cover. The River Tirur originates from the Athavanad village and flows into the Arabian Sea through the coastal town of Ponnani. The main threat to mangrove forests is anthropogenic activities compared to natural phenomena. The majority of these ecosystems are converted into farmlands, resorts, aquaculture, and other building activities. A transect measuring 8Km (4Km from urban and 4 Km from the suburban area) was selected to study the mangrove diversity and existing threats to the mangrove forests of the river Tirur. A 100m line transect was laid in each of the 1 Km for studying vegetation. A total of 8 species were identified and 286 individuals recorded. In the urban area, we could locate two species, namely Sonniratia caseolans (n=1) and Avicennia officinalis (n=23). In the rural area, we identified 6 species, of which the species Sonniratia caseolans (189) and Bruguiera gymnorrhiza (36) were observed in high numbers. The least recorded species were Bruguiera sexangula (n=5) and Kandella candel (n=6). The study revealed the highest density of Sonniratia caseolans and Avicennia officinalis. The local residents reported that, over a period of time, the mangrove forest patches have undergone a considerable decrease. Residents are aware of the important functions of the mangrove ecosystem, and the identified services are prevention from soil erosion, supporting bird diversity, providing fodder for cattle, and protection from heavy wind. The identified threats to the mangrove forest were river beautification activities, encroachment along the riverside, and the Koottayi regulator cum bridge.

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Mangorve species, diversity, environmental awareness, conservation

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In recent decades, consumers and producers have voiced concerns about the effects of products on the environment. Products that are thought to be "green" or environmentally friendly, such as low-power (energy-efficient) electrical appliances, organic foods, lead-free paints, recyclable paper, and phosphate-free detergents, have drawn the attention of both consumers and manufacturers. The significance of the Green Marketing Concept is also being recognized by marketers in India. While there has been a lot of global research on green marketing, there hasn't been much scholarly study done in India on customer perceptions and preferences. An overview of environmental issues is given in this research, along with information on consumers' green values, awareness of environmental issues, and green habits and products. Consumers place a high value on green products, research has provided useful insights for green product marketers and indicates the necessity to create marketing communication campaigns supporting green products. This study supports the idea that customer preference and purchase decisions are positively influenced by general green values, consumer awareness of green practices and products, and consumer perceptions of the seriousness of marketing firms' commitment to green marketing.

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green marketing, consumer preferences, green products, marketing communication campaign

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The market for eco-friendly cosmetics has grown significantly in the last few years. Concurrently, there has been a rise in scholarly interest in the topic. However, the information is inconsistent overall. Despite the growing corpus of literature, no thorough compilation and integration of empirical research examining the variables associated with green cosmetics purchase behaviour (GCPB) has been carried out. This study makes an effort to close this gap. We conducted this systematic review. The elements of the theory of planned behaviour that were most commonly demonstrated as determinants were attitude, subjective norms, and perceived behavioural control. Then came the "marketing mix, consumer consciousness issues, consumer values, brand-related attributes, experience and knowledge, self-efficacy, and perceived barriers". Consequently, this research will aid in the understanding of the knowledge barrier by academics. Moreover, the findings of this review will help marketers frame their marketing strategies for promoting green cosmetic products.

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Green cosmetics; Purchase Behavior Systematic Review; Sustainability, E-WOM.

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ukVdksa ds eaph; izLrqrhdj.k esa laxhr ds fofHkuu :iksa dk iz;ksx

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Analyzing the evolution of women's rights within the Indian judicial system over the past two centuries presents a multifaceted and intricate narrative. The journey of women's rights in India has been marked by several milestones, setbacks, and incremental progress. In this article, we will embark on a detailed exploration of the legal landscape pertaining to women's rights in the Indian judicial system from the colonial era to the present day.

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The evaluation of women's rights in the Indian judicial system over the past 200 years.

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Ladakh, nestled in the Himalayas, faces escalating climate change impacts, necessitating an in-depth understanding of local perceptions and adaptive strategies. This study explores Ladakh's socio-cultural dynamics, livelihood impacts, and adaptive responses to climate change. Employing a mixed-methods approach, including interviews, surveys, and observation, the research unveils a diverse array of local perceptions. Some attribute weather changes to natural variability, while others express concerns about increasing temperatures and glacial retreat. These impacts reverberate across livelihoods, notably agriculture and pastoralism, prompting resilience and adaptability through traditional practices, modern technologies, and community-based initiatives. Ladakh experiences a cold desert climate characterized by extreme temperatures and sparse vegetation. Home to diverse ethnic groups, Ladakh's cultural heritage faces threats from climate change-induced glacier retreat and erratic precipitation, impacting water security, agriculture, and ecosystems. The findings underscore the intricate interplay of socio-cultural, ecological, and economic factors shaping Ladakh's response to climate change. Despite challenges, communities exhibit resilience, drawing upon traditional wisdom and innovative practices. Notably, perceptions of natural variability and recognition of anthropogenic influences underscore nuanced understandings of climate dynamics. Adaptive strategies encompass traditional practices, technological innovations, and community-based initiatives, reflecting a multifaceted approach to building resilience. This research offers comprehensive insights into Ladakh's local perceptions, livelihood impacts, and adaptive capacities, informing targeted interventions and policy frameworks. By recognizing and leveraging local knowledge systems, stakeholders can collaboratively address the complex challenges posed by climate change in Ladakh and beyond.

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Ladakh; climate change; local perceptions; socio-cultural dynamics; livelihood impacts; adaptive strategies

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This research paper provides an in-depth analysis of fiscal and monetary policies in India, with a focus on the prevailing economic conditions. Against the backdrop of global economic uncertainties and domestic challenges, this paper examines the roles, objectives, and effectiveness of fiscal and monetary policies in promoting economic stability, growth, and development in India. Simultaneously, the evaluation of monetary policy under the purview of the Reserve Bank of India (RBI) is examined. The RBI's monetary policy framework, guided by the objective of maintaining inflation within a target range while supporting growth, is analyzed in depth. The adoption of inflation targeting, coupled with forward-looking communication strategies, has enhanced the effectiveness and credibility of monetary policy. However, challenges such as volatile global financial conditions and transmission mechanisms pose significant hurdles to the efficacy of monetary policy transmission in India. Furthermore, it evaluates the policy response to emerging challenges and offers insights into the future trajectory of fiscal and monetary policies in India.

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Fiscal Policy, Monetary Policy, Economic Stability, India

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The idea of visual education is not new. It appears that over long centuries outstanding teachers have tried to devise ways to make concepts clearer to their pupils through the use of various devices. It is said that 2500 years ago the Greek mathematician Pythagoras drew geometric figures in the sand when making his demonstrations. History suggests that the basic condition which strongly encourages study and experimentation in visual aids was one which was the danger of what William James called it "Empty Verbalism" concepts; to have meaning for the learners must be grounded in his personal experience. Many students of Educational method are convinced that the most serious problem of all formal teaching from Kindergarten through college is the avoidance of meaningless verbalisation. The avoidance of excessive verbalism was a basic consideration in the pedagogical theories of Johann Amos Comenius (1592-1670). Comenius was greatly disturbed by the prevailing methods and materials of instruction in use in his day. He was convinced that improvement in Teaching and learning would necessitate more emphasis on sense experience, in order that the formal teaching would be grounded in the experience of children and would thus be meaningful to them. This conviction led him to prepare one of the most famous text book ever written for children, ORBIS PICTUS (meaning the world in pictures). This book contained numerous pictures of scenes from everyday life of the times accompanied by textual material for children to read. In his book Comenius gave the following directions to the teachers and parents who were to use the materials with children.

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Visual Instructional Devices

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