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In the rapidly digitalizing world, the management of electronic waste (e-waste) has emerged as a pressing concern, especially in developing nations like India. This research introduced a dynamic e-waste collection system in rural India, leveraging the Internet of Things (IoT), strategic management, and machine learning. The pilot implementation witnessed a remarkable threefold increase in monthly e-waste collection, soaring from 150 to 420 tonnes. Furthermore, the average collection time was slashed from 10 days to just 3, while community awareness about e-waste management surged from 30% to 78%. Utilizing machine learning models like ARIMA, geospatial analysis, and Prophet, the system adeptly forecasted e-waste generation patterns, thereby optimizing collection strategies. Despite its promising results, challenges such as IoT infrastructure in remote areas and varying rural landscapes necessitate further refinements. The study not only underscores the potential of technology and strategy in addressing e-waste challenges but also highlights a scalable model that can be adapted for similar regions globally, paving the way for sustainable waste management and environmentally friendly development. [ABSTRACT FROM AUTHOR]

Computer vision and machine learning are both used in the investigation of visual image classification. Assigning an object to a category, or group of categories, that it belongs to, is the work of visually categorising an object. A two-layered system is typically used to conduct visual classification tasks. It consists of a first layer using an off-the-shelf feature extractor and detector and a second classifier layer. Convolutional neural networks have been demonstrated to surpass such hitherto employed algorithms in recent years. The ability to automatically categorise automotive damage is very desirable, especially for the auto insurance sector, given the importance of cars in today's society. Automobile inspections are a common occurrence for auto insurance providers. Such inspections are labor-intensive, manual, and occasionally flawed processes. processes that expense and annoy customers and insurance firms equally. Even while a complete automation of such manual inspection procedures may still be some time off, modern technology may make it feasible to create systems that facilitate, expedite, or improve the process. [ABSTRACT FROM AUTHOR]

This study describes an automated irrigation system based on Internet of Things (IoT) technology that intends to increase irrigation in agriculture's efficacy and efficiency. A microcontroller, a cloud-based server, and a network of soil moisture sensors make up the system. The microcontroller receives the measurements of the soil's moisture content from the sensors. If the soil moisture falls below a predetermined level, the microcontroller analyses the data and turns on the irrigation system. The server gathers and stores the sensor and microcontroller data and offers a user interface for remote monitoring and management of the irrigation system. The suggested system has a number of benefits, including less water use, higher crop yields, and better resource management. It is also adaptable and simple to modify to fit the unique requirements of various crops and environments. Overall, by enhancing efficiency and sustainability, the IoT-based automated irrigation system has the potential to alter the way agriculture is carried out. [ABSTRACT FROM AUTHOR]

This research examines the impact of chemical pre-treatment on UTWP under a hot air oven. Acid and alkali pre-treatment methods have gained popularity as cost-effective means to enhance cellulose quality. These methods eliminate lignin, disrupt cellulose's crystal structure, and reduce its hardness. By pre-treatment with four types of acids (hydrochloric, phosphoric, acetic, and sulfuric) for the first group of samples and four types of alkaline (calcium hydroxide, sodium hydroxide, potassium hydroxide, and ammonium hydroxide) for the second group. UTWP was soaked and pretreated in a hot oven at 80°C for six hours. The first group was soaked in 100 ml of dilute acid, while the second group was soaked in a 5% alkaline solution. The weight loss of samples after pre-treatment was calculated. The mass loss of UTWP after pre-treatment varied with the type of acid and alkaline. It was varied in the following order: HCl (48%) > CH3COOH (37%) > H2SO4 (35%) > H3PO4 (33%). NaOH (70%) > KOH (55%) > NH4OH (35%) > Ca(OH)2 (25%). High mass loss was observed with alkaline compared to acids except Ca(OH)2 (25%). FTIR analysis showed enhancement of critical functional groups involved in the production of high-value materials, which are present in tea waste after pre-treatment, especially in samples that treated with HCl, H3PO4, CH3COOH, Ca(OH)2, include: Carboxyl groups (-COOH), a hydroxyl group (-OH), Ester functional groups (-COO-), Aldehydes (-CHO) and ketones (-C=O) and Unsaturated organic compounds contain double bonds (-C=C-) are crucial for the production of biodiesel and other products. [ABSTRACT FROM AUTHOR]

The most widely available form of renewable bioenergy is lignocellulosic biomass. Because of its complex structure, the cellulose and hemicellulose it contains cannot undergo any more chemical modifications. Hydrolysis resistance in lignocellulosic biomass can be reduced with organosolv pre-treatment. Treating rice straw and tea waste through the soaking process with solvents offers numerous benefits and significantly affects their chemical properties. This treatment method facilitates the extraction of valuable compounds from biomass materials, enhancing their suitability for oil production via thermal pyrolysis. Acetone, ethanol, and benzene are commonly used solvents for these treatments. Acetone treatment of rice straw removes or modifies (hydroxyl groups), while ethanol treatment of tea waste retains or modifies (polyphenols and flavonoids). These modifications contribute to improved oil yields and altered compositions during thermal pyrolysis. The oils from solvent-treated rice straw and tea waste can serve as renewable fuels, bio-based lubricants, or feedstocks for producing chemicals and materials. The FTIR analysis shows improvement in many functional groups, N-H stretching, O-H stretching, C=O stretching, C=C stretching functional groups were noticed. Overall, this treatment method facilitates the extraction of valuable compounds and promotes sustainability, waste reduction, and the utilization of renewable resources. [ABSTRACT FROM AUTHOR]

This article largely focused on the effective study of a body of norms to detect the Brute Force on the inner surface of a provided guided or unguided game theory in the Financial System. One of the most fascinating areas of conceptual arithmetic is guided or unguided game theory.A focus: the idea of guided or unguided Game theory outcomes in agreement with tracking down and unguided Game theory is shown to be a Game theory design if they are linked to one another. Using guided or unguided Behavioural economics, find a key demonstration for the simple investor for the client to the financial institution. [ABSTRACT FROM AUTHOR]

This paper focused on a study to generate the sequence of Fibonacci Type Numbers using third and higher Order Linear Recurrence Relations. Also, evaluated the Constant Coefficients of their higher Order Linear Recurrence Relations. In particularly evaluated the Non degenerated values of c1,c2,c3,....cn of some Fibonacci Type numbers of rth order of linear recurrence relation Fn = c1Fn-1 + +c2Fn-2 + c3Fn-3 + c4Fn-4+ ........crFn-r, for n≥r,r ≥ 2. Also, it was focused to study repeated steps of their residues with some integer modulo 'm'. [ABSTRACT FROM AUTHOR]

Social affiliation research depends upon a plan of information sources, subordinate upon the inconvenient condition and the solicitations, which the appraisal is attempting to reply or illuminate. Easygoing social order are astoundingly outstanding these days and the comprehension of their interior structure is clearly reassuring district. Social affair appraisal has additionally been an obviously interesting point concerning the area of computational data and discovered fitting in social affiliation assessment in its easygoing organization structure. In this part, we use k-pack appraisal with different execution measures to isolate a touch of the information sources got for social affiliation assessment. Our proposed approach is needed to address the clients of easygoing organization, that won't just assistance a relationship to comprehend their outer and internal affiliations yet additionally essentially huge for the improvement of cooperation, movement and dispersal of information. [ABSTRACT FROM AUTHOR]

A virtual classroom is an online learning environment in which students and teachers collaborate using technological equipment provided by software. A virtual classroom transmits real-time teachings while also providing the same collaboration tools and level of involvement as a traditional classroom. Virtual classroom software allows students who are unable to attend in-person classes to participate. Teachers can interact with students and interact with instructional materials, view presentations and videos, and take tests in real time using the virtual classroom environment. [ABSTRACT FROM AUTHOR]

The Indian leather Goods manufacturing industry the largest industry in India accounting for above 20%of the total industrial production. Labor welfare it is an essential variable of enterprises relations because it measures one of the key contributors to know the level of fulfillment, inspiration profitability of the representative in the association. The labor welfare facility helps to persuade and hold representatives. The majority of welfare facilities are matters of sanitation and hygienic which is not given dissatisfaction among specialists are inspired by giving welfare measures. The labor welfare covers condition of well being, happiness, satisfaction, protection and advancement of HR. The study aims to find out the various labor welfare facilities to know the significant influence on the employee's satisfaction level. To assess rapport between labor welfare measures and employee satisfaction. The study used primary and secondary data collection method. The study based on descriptive research design is used for the existing problem in the organization. From this survey, the leather manufacturing industry is giving good labor welfare facilities to their employees. The study reveals that most of the labour welfare facilities are satisfactory at Leather goods manufacturing industry in Vellore District. [ABSTRACT FROM AUTHOR]

Banks are institutions that need the utmost trust of the customers. One of the best ways to link society to the company is the effective use of Corporate Social Responsibility. Corporate Social Responsibility is used by banks to change the notion that banks are institutions that are merely concerned with money matters. Banks have another lifeline through Corporate Social Responsibility, another chance to prove to the customers that they are more than just institutions concerned with money. The Indian banking industry has begun to give more importance to Corporate Social Responsibility due to the emphasis on Social responsibility by the Reserve Bank of India. This study focuses on how banks are increasing their brand preference through practicing Corporate Social Responsibility. This study has analyzed that "Actions speak louder than words"; customer preference is strongly influenced by the actions of the banks. Corporate social responsibility enhances the brand image and in turn, creates a strong brand preference in the long run. [ABSTRACT FROM AUTHOR]

The relevance and significance of Social issues, Corporate Social Responsibility (CSR), and Customer perceived value around the world is putting pressure on all industries to be more socially responsible while also developing society as a whole. The new generation of consumers is concerned not only with the product's appearance, quality, and price but also with the company's ethical behavior. In the past, the word "corporate social responsibility" had a completely different connotation, but multinational corporations have completely redefined it today. The impact of social issues, CSR, and customer perceived value on marketing has brought about new ways to position a product and create value. From this study one can understand the importance of the role of social issues, Corporate Social Responsibility and customer's perceived value in influencing the development of novel marketing strategies which ensure sustainable practices in every business operation. [ABSTRACT FROM AUTHOR]

When we are exposed to some of the metal elements like chromium and nickel directly upon our skin surface, we become prone to its infection or allergy. So thereby, by considering the absorption of these metal ions into the skin and its interaction with the T-cells existing in the skin surface, we take into account the damage it causes and its increased level of allergy. By performing PDEs, we try to compare the responses of these metal ions with the T-cells. This modeling approach shows that with these symptoms we can relate contact dermatitis from these allergens. [ABSTRACT FROM AUTHOR]

The W3C typically describes web services as: "a piece of software that is designed to support machine-to-machine interoperability over a network. With the rapid expansion of functionally similar web services over the internet exposes a great challenge for users to identify the web service origin and integrity process. A traditional centralized web service registry drastically shifts the dynamic power of web services, by establishing a platform for service provider‟s to advertise their self-contained, self-reliable and self-governing data. Though, these centralized infrastructures do not offer easy way to explore available services for users in thenetwork, and also nor have the ability to verify their origin and history. The contribution of the paper is to address these challenges by leveraging the decentralized, immutable, tamper-proof Blockchain technology by establishing Blockchain service registry and execution via smart contract for secured semantic web service discovery. This allows users to explore the services in a network and also able to identify its service origin and integrity. Our first evaluation shows the promising results with this system paradigm in the field of web service provisioning. [ABSTRACT FROM AUTHOR]

Phenol and phenolic compounds are one of the top pollutants in environment due to their presence in various industrial effluents and their broad applications in various other fields. The results of this current study proved that isolated strain P7 is capable of degrading high capacity phenol. Optimal conditions obtained for the degradation of phenol from this strain created a solid foundation for further use of this microorganism in the treatment of phenol effluents. Studies were conducted out using Mineral Salt Agar Medium for the growth of this strain and degradation of phenol using phenol as the sole carbon and energy source for the isolated bacterial strain. The strains obtained from the phenol contaminated soil were designated as P1, P2, P3, P4, P5, P6, P7 & P8. P7 strain among these was found to be highly effective in removing phenol. Gen III biolog was used to identify the name of this P7 strain species, which is isolated from soil sample. Gen III Biolog, a phenotypic microarray identified the strain P7 as Pseudomonas Putida. Optimization studies were carried out to find out the optimum pH, temperature, inoculum volume, contact time and initial phenol concentration for the Pseudomonas Putida species. The optimum conditions obtained for maximum phenol removal were found to be pH of 7.5, temperature of 32OC, Contact time of 72hrs, phenol concentration of 200 mg/l and inoculum volume of 4v/v. The maximum biodegradation rate achieved was 93.29% from this isolated strain which indicates its potential use in the bioremediation of wastewater effluent. [ABSTRACT FROM AUTHOR]

MCDM is used to solve problems which are having a number of goals. Goal programming produces a set of solutions considering all the problems giving equal importance to each of them. Rice land has the capacity to grow different crops. Using a high level of programming different crops are produced by considering multiple goals. Here we are using the lexicographic linear goal programming (LLGP) model for recognizing the optimal compound of agriculture products in the rice land of Sirsi, Uttara Kannada district, Karnataka. Also, we used goal programming for the result and we compare both the results to get maximum benefit. [ABSTRACT FROM AUTHOR]

Solar energy is one of the key sources of green energy because it is free of emissions, pure, limitless, and plentiful. Solar power has gained tremendous interest across the globe, and one of its key duties is to produce as much solar power as possible in varying weather conditions. Photovoltaic generation's intermittent and unregulated characteristics have a major effect on power stability. To minimize these factors, the predictability of photovoltaic generation needs to be increased. As photovoltaics are increasingly evolving, the share of PV generation in the electricity trading industry is rising. However, the model's accuracy is often low in conventional modeling because of unnecessary initial data noise or inappropriate parameter configuration. The key factor analysis in this article and the K-means algorithm are clustered and the random forest (RF) algorithm. Core components and K-means are used to get the hourly points' characteristics close to the projected time points, and then the input data are filtered to mitigate interaction with the noise data. [ABSTRACT FROM AUTHOR]

The rate of death in heart failure patients keeps increasing, but the causes of death are always uncertain. Even though heart failure is a diverse syndrome classified by ejection fraction, the relationship among both ejection fraction and death rates is significant but elusive. According to health cardiology report, Patients with heart failure and reduced ejection fraction have greater risk of dying, compared with heart failure patients and preserved ejection fraction. However, the factors influencing the death rate of heart failure patients remains a challenging task for the doctors and researchers. With this motivation, this paper attempts to analyze the important features that influences the mortality rate of the patients. The Heart Failure dataset from UCI data warehouse repository is subjected for analyzing the heart failure patients. The dataset is preprocessed with data cleaning process and missing values. The preprocessed dataset is applied to all the classifiers and the performance of the mortality grading is analyzed before and after feature scaling. The raw dataset with entire 12 features are applied to Ada Boost, Random Forest, Extra Tree and Gradient Boost classifier to extract the top six important features to increase the accuracy performance. The feature importance dataset is then applied to all the classifier and the performance is analyzed in terms of accuracy, precision, recall, FScore and Run Time. The implementation results shows that random forest classifier is showing the accuracy of 89% after feature scaling and the random forest classifier with the feature importance of Gradient Boost classifier shows the accuracy of 97%. [ABSTRACT FROM AUTHOR]

Precise and early diagnosis is crucial for the cancer patients to get optimal care. Tools available to predict cancer in advance remains deficient and also there are considerable false positive rates. In order to avoid this, the proposed work focuses on Clinical Data analysis and Image analysis of Ultra sound images to predict cancer at initial stages. In this analysis, Adaptive Randomized Tree (ART) uses clinical data such as percentage of unbound Prostate Specific Antigen (PSA), bound PSA, age, PSA density and PSA velocity and intensity extracted from Ultra sound images as metrics to predict carcinoma. Hence ART has a better prognostic performance than other diagnostic indicators for prostate cancer. This gives the preliminary evidence that ART can be used as an effective diagnosis tool for other type of cancers with appropriate metrics. [ABSTRACT FROM AUTHOR]

In this research, we will look at interstitial lung disease (ILD), which is an inflammation and fibrotic respiratory illness that mostly damages the cells and area around the lungs' air sacs known as the interstitium. There are around group of 200 diseases belonging to this category. This disease affects the other compartments of lungs, the airways known as alveoli, the blood vessels and the outside lining of lung known as pleura. This disease is characterized by respiratory symptoms, chest radiographic abnormalities, pulmonary fibrosis and fibrosis results from chronic inflammation. The lung biopsies with predominance of fibrosis results in poor prognosis comparatively than inflammation. Many studies reported that 80.9 per 1, 00,000 men and 62.7 per1, 00,000 women was diagnosed with this disease every year. There is no established treatment that prolongs life for patients with these diseases. It is critical to do accurate diagnosis in order tohave significantly dissimilar treatment choices and a improved prognosis. [ABSTRACT FROM AUTHOR]

In the past few decades, IoT (Internet of Things) based m-healthcare applications are arising to provide real time services in the fast world. These applications save people's lives by getting regular updates about health conditions of them for their easy lifestyle. Cloud based health care framework are provide better outcomes when compared to conventional methodologies. Nowadays Incorporating IoT devices in clinical environments plays major role in handling huge volume of medical data. Researchers thus sought to automate the process of detecting and diagnosis diseases using could computing technology. Accordingly, number of explores has been proposed an infection forecast and analysis framework in cloud based IoT utilizing distinctive secure ML (Machine Learning) calculations. This paper reviews the existing heart disease classification research frameworks with its pros and cons. Here, totally twenty-five papers are analyzed. In addition, this study gives an elaborate idea about disease prediction and diagnosis system. [ABSTRACT FROM AUTHOR]

Approximate computing can lessen the style complicacy with a rise in overall performance and power performance for error-tolerant programs like multimedia and additionally sign managing which can tolerate mistake, precise computing units don't appear like continuously wanted. They will virtually get replaced with their approximate equivalents. The Approximation of multipliers by using a state-of-the-art layout method segment upon partial products is emerging as gift differing risk terms. A High performance approximate redundant binary multiplier is designed and implemented. A new booth multiplier (using conventional modified booth algorithm) design is implemented using 4:2 & 5:2 compressors. In the existing approximate redundant binary multiplier (ARBM), the summation of partial products is accomplished in levels using a 4:2 compressor. 4:2 compressor involves a majority of levels for the summation of partial products. The More the number of levels, the greater the delay so the pace of the multiplier is diminished. In the Proposed high-performance approximate redundant binary multiplier-I(ARBM-1), we use a higher-order compressor, i.e., 5:2 compressor is used to overcome this issue, the number of levels can be reduced. Then comparison in terms of power, delay & area of ARBM with ARBM-1 is done using the Xilinx tool. [ABSTRACT FROM AUTHOR]