Volume 12 | Issue 7

 Abstract

In today's society, gratitude is a well-established tradition that has been left by the ancestors who lived before us. Gratitude always carries a deep human value as it is the heart of human values that we must follow to make a harmonious human society. Gratitude is considered a feeling of appreciation a person receives from others, which could have been material or immaterial. Regardless of religious faith, gratitude is regarded as a significant human attribute. People acknowledge the goodness in their lives with gratitude, which can also be cultivated by continuously practicing it. Moreover, as per the Buddha's teachings, gratitude is considered the spiritual practice to attain the ultimate goal of human life and a manifestation of loyalty and is referred to as a sense of affection or a feeling that an act of kindness should be positively responded to by others. In this paper, the researcher aims to emphasize the Buddhist perspective of gratitude as a noble virtue in contemporary society to encourage intellectual and personal exploration of this new fertility field of study.

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Gratitude, Buddhism, Four Debts of Gratitude, Moral Value...

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The goal of this article is to design a Agri rover: An affordable agro vehicle for precision farming." India's agriculture industry has a long history of manufacturing commodities of excellent quality and serving as one of the primary economic drivers of the nation. But since most farmers run smaller farms and are poor, we need to develop a portable agricultural vehicle that is affordable for even these farmers. Furthermore, the agricultural vehicles of today are restricted to a single task, such ploughing, water/fertilizer spraying, or sowing. The battery, DC motor, pH meter and pump are the main components of the car. The gem based sunlight based charger is use to charge a battery-powered battery of 12 volts. The engine changes electrical energy over completely to mechanical energy and this energy is utilized to perform various activities like water splashing, furrowing, seed planting with the assistance of switch control instrument. This vehicle is primarily valuable for little size ranches to expand the efficiency.

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Agriculture vehicle, pump, DC motor, battery, Mechanism, Agrirover.

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ABSTRACT The aim of the study is to investigate the predominant factors correlated to the play-ing ability among college level female volleyball players in the Telangana state. To achieve the purpose of the study, 100 female volleyball players who played inter collegiate tournament from various colleges were selected as subjects. The age of the subjects ranged from 18 to 25 years. The anthro-pometric measurements, motor fitness, physiological variables and skill variables were selected as dependent variables and playing ability of female volleyball players as independent variable for this study. The dependent variables were tested with standard testing procedures. To determine the relationship between criterion variable and determinant variables Pearson product moment correlation was used. The computation of multiple regressions was also used. In multiple regres-sions, a criterion variable was predicted from a set of predictors. Step wise selection method of multiple regressions was used in this study to find out the predictor variable that has the highest correlation with the criterion variables and it is entered into the equation first. The rest variables are entered into the equation depending on the contribution of each predictor. In all the cases 0.05 level of significance was fixed to test the hypothesis.

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Key Words: Prediction, Spiking, Muscular Endurance, Shoulder Strength

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ABSTRACT Background: The present research is based on formulation of celecoxib emulgel and determines in-vitro drug release and swelling index of prepared emulgel. Material and Methods: Pure drug of celecoxib was identified by using FTIR spectroscopy and preformulation study of emulgel was performed by using various methods like determination of lamba max, drug solubility studies, melting point of pure drug etc. The present formulation is based on carbapol 934 polymer and other key ingredient and excipients which was used in preparation of anti emulgel. Result: Evaluated the prepared emulgel by their physical appearance, PH, Rheology, Swelling index, microscopic studies, Drug content, % drug release. In all formulation batch, F3 batch formulation was give satisfactory result like that drug content 95.3%, cumulative drug release 92.9 %. Conclusion: As a result, the current study's results unambiguously showed that celecoxib emulgel presents a promising alternative to the traditional dose form. Nevertheless, additional clinical research is required to evaluate the effectiveness of this technique. After taking into account everything mentioned above, it was determined that the current research study's goal could be effectively met.

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Emulgel, Celecoxib, Gel, Jelly Etc.

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This paper explores the firewall security and performance relationship for different firewall systems. The firewall is a important component of the network for safe communication. A firewall acts as a barrier that provides security by controlling security threats. Through a thorough investigation of different firewall technologies, this research aims to recognize the strengths and weaknesses of each firewall system, determining the algorithm and method of network security. This paper is a structural study of research papers which have been carried out on the different Firewall technologies. This research paper focuses on comparative analysis of different methodologies used, accuracy in packet filtration, and the comprehensive evaluation of the performance of various firewall systems.

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Firewall security, Packet filter firewalls, Kernel-based firewalls, Pre-filtering ACL, Cloud-based firewalls, Two-stage algorithm, Redial algorithm, Virtual Machine.

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The increasing popularity of wearable devices like smart watches, smart phones, and wristbands has generated a need to analyze user patterns and activity relationships. This study utilizes the MHHBA Physical Activity Monitoring dataset, consisting of data from 12 different physical activities performed by 10 subjects wearing 3 inertial measurement units and a heart rate monitor. The dataset is invaluable for activity recognition, intensity estimation, and the development of algorithms for data processing, segmentation, feature extraction, and classification. To enhance accessibility, the original data has been transformed and merging all the datasets into a comprehensive CSV file. Leveraging this enriched dataset, we apply machine learning techniques to accurately predict the specific activity a user is engaged in. We employ the K-Nearest Neighbors (KNN) algorithm, Random Forest algorithm, Robust Scalar to standardize the features and Grid Search CV for best neighbors.

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MULTI-SENSOR BASED PHYSICAL ACTIVITY RECOGNITON AND CLASSIFICATION USING MACHINE LEARNING TECHNIQUES

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Bhaarat mein samaan naagarik sanhita (ucc) kaa kryanvayan ek ja?il chunauti pesh karata hai kyonki yah vividh kaanooni pra?aaliyon men saamanjasy sthaapit karanaa owr laingik samaanataa, nyaay aur vyaktigat adhikaron ke muddon ko sambodhit karana chahataa hai. UCC kaa lakshy dhaarmik aur prathaagat prathaon par aadhaarit vyaktigat kaanuunon ko sabhii naagarikon par laaguu naagarik kaanuunon ke ekal se? se badalanaa hai, chaahe unakii dhaarmik yaa saansk?tik p?sh?habhuumi kuchh bhii ho. Haalaanki, ucc ko laagu karane men shaamil vyaavahaarik chunautiyaan mahatvapuur? hain, jinmein mowjuudaa vyaktigat kaanuunon ke saath ucc ko santulit karana, dhaarmik samvedanashiilataaon kaa prabandhan karanaa owr samvaidhaanik owr raajaniitik vichaaron ko dhyaan mein rakhana shaamil hai. UCC ke saamaajik-aarthik nihitaarth bhii mahatvapuur? hain, kyonki yah samaaj ke vibhinn pahaluon, jaise vivaah, talaak, viraasat aur god lene ko prabhaavit kar sakataa hai. Bhaarat ke 22ven vidhi aayog ne haal hi mein is vishay par phir se vichaar kiyaa hai aur sudhaar aur kanooni jaagarukataa kii ja?ilataa ko dur karane ke lie vyaapak paraamarsh aur aam sahamati nirmaa? kii aavashyakataa par prakaash ?aalate hue ucc par janataa kii raay aur vichaar maange hain.

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Laingik Samanata, Samajik Nyaya, Dharmanirpekshta, Vyaktigat Kaanoon, Karyaanvayan Chunoutiyon

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Predicting genomic disorder is a significant and crucial problem in biomedical research. Multivariate diseases with high global death rates, such as cancer, dementia, diabetes, cystic fibrosis, Leigh syndrome, etc., are brought on by genome defects. Historically, theoretical and explanatory Methods for predicting genetic disorders were introduced. As technology advanced, genetic data were expanded to nearly encompass the entire genome and proteins. Subsequently, machine learning and deep learning techniques were employed to forecast disorders related to the genome. Deep learning and machine learning techniques were introduced in parallel. Numerous studies on the prediction of genomic disorders have been carried out in the past utilizing supervised, unsupervised, and semi-supervised learning techniques; the majority of these studies used genetic sequence data to predict binary problems. These techniques' prediction findings were unclear because to due to their reduced accuracy rate and binary class prediction methods that use genome sequence data but do not use the medical history of patients with genome disorders. Consequently, an advanced genomic disorder prediction model (AGDPM) was developed in this study using a huge quantity of data by utilizing XGBoost and SVM, an efficient Machine Learning architecture. When compared to the pre-trained XGBoost model, AGDPM produces the greatest results, with training and testing accuracy rates respectively. Therefore, the advanced genome disease prediction model demonstrates the capacity to process a substantial quantity of data and forecast genomic disorders effectively. genetic disease data from patients using a multi-class prediction technique. According to a number of statistical performance metrics, AGDPM has demonstrated its ability to predict single gene inheritance disorders, mitochondrial gene inheritance disorders, and multifactorial gene inheritance disorders. Therefore, biomedical research will be enhanced with the aid of AGDPM in order to forecast genetic illnesses and control excessive death rates.

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ADVANCE GENOME DISORDER PREDICTION MODEL EMPOWERED WITH MACHINE LEARNING

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The drama Aurat,was first published in 1937 in its native Urdulanguage.Tutun Mukherjee and A.Z. Manzartranslated Auratinto Englishas Woman and published it in the book "Staging Resistance: Plays by Women in Translation" in 2005.The drama provides a profound understanding of the circumstances prevailing in the Muslim community. It is a significant piece of literature that explores the complex dynamics of gender oppression and the gradual awakening of female consciousness.It holds a significant place in Rasheed Jahan`s oeuvre because it not only talks about a women's pitiable condition but it goes a step further and shows her taking a stand which was quite unusual for that era. Through a close analysis of key moments and textual lines, this article examines center character Fatima's journey and transformation and its implications for gender discourse.

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Keywords: Rashid Jahan, 'Woman', Muslim community, Patriarchy, female consciousness.

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Alzheimer's disease (AD) poses a significant global health challenge with limited therapeutic options. Acetyl cholinesterase (Ache) inhibitors represent a cornerstone in AD treatment by enhancing cholinergic neurotransmission. Through in silico techniques, such as molecular docking and molecular dynamics simulations, a library of quinazoline derivatives was screened against the active site of AChE to predict binding affinities and interactions. Structural modifications were systematically explored to optimize inhibitor binding and pharmacokinetic properties. The computational results identified several promising candidates demonstrating potent inhibitory activity against Ache. These compounds exhibited favourable interactions within the enzyme's catalytic site, suggesting their potential efficacy in enhancing cholinergic neurotransmission.

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Alzheimer's disease, neurotransmission, pharmacokinetic, enzyme's catalytic site

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In the present study water sample of Kishore Sagar Lake,Kota from three different sites i.e Near KST Boating Ramp(S1), Near Bhagwan Mahaveer Children's Park(S2), Near Shree Tejaji Maharaj Temple(S3) has been physicochemically evaluated for its suitability for domestic and irrigation purposes. In Physical and Chemical Parameters Such as Temperature, turbidity, pH, T.D.S., Alkalinity, Total hardness, Chloride, Nitrate, Dissolve Oxygen, and B.O.D., were analyzed in the laboratory.The Physico Chemical parameters of water were determined as per standard methods of APHA (2012). The results indicate that the lake water quality is suitable and safe for domestic and irrigation purposes.

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Physicochemical parameters, Kishore Sagar Lake

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Skills were developed in response to the demands of the twenty-first century, which led to a paradigm shift away from traditional teaching methods and towards M-learning in higher education. Students are using their mobile devices for instructional purposes more and more. The purpose of this inquiry is to determine the attitudes of students towards mobile learning by administering a survey. A survey was conducted by research students at the College of Arts, Science, and Commerce, emphasising their perceptions of mobile learning. Online surveys were used to collect the data, and 175 valid answers were chosen for the study. The findings of this study could potentially provide investigators with some understanding of present advances in mobile learning research. In order to improve teaching strategies and learning outcomes in higher education institutions, the current research examines a study on m-learning using mobile devices to determine students' opinions in various dimensions of mobile techniques and perceive the viability of mobile technologies for academic and social purposes.

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Attitude, Mobile Learning, M-learning, Higher Education

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The present era is considered to be a period of the technology- revolution. Information technology is playing a crucial role in bringing this change worldwide. The technological change in this competitive scenario has instigated innovation in products and services. In this respect, the Indian economy has witnessed a prodigious change in its currency from the barter system to the digital payment system. This cash crunch persuaded people to embrace the idea of "My bank, My Money, My Wallet". E-wallet is one of the types of electronic payment systems being widely used these days. This study is centric to customers' perception towards digital wallet, also known as e-wallet with particular emphasis on the twin cities i.e. Hyderabad and Secunderabad. For data collection, structured questionnaires were prepared and distributed to the respondents. It is an empirical study that explains customer's perception towards e-wallet based on their gender, age, occupation, and educational qualification.

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Information technology, Digital Payment System, Customer's Perception, E-Wallet

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Teaching strategies are very important to make classroom instruction very effective and fruitful. In the case of instruction on the Bengali language at the primary level, there are many approaches. But instruction of Bengali language through Group Interactive Strategy and Expository Teaching Strategy may provide an effective output as a result it can be estimated the effectiveness of an instructional strategy for the development of Basic skills in Bengali language. In the Expository teaching approach, students get a narrative about a subject as well as they observe the subject matter through effective demonstration and meaningful learning programs. In Group interactive strategy students can learn the language by interacting among themselves guided by the teacher to minimize the ambiguity in language skills. In teaching new vocabulary, and grammar in Bengali along with prose and poetry and four basic skills of language, an Expository teaching strategy can be used by putting logical descriptions and the inner meaning of prose and poetry in the syllabus. Hence in this paper, the author intends to present the analysis of models and the nature of outcomes by conducting a pilot experiment with two teaching strategies in teaching the Bengali language at the primary level.

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Teaching strategy, Group Interactive Strategy, Expository Strategy, Steps of model, Basic skills of language.

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Education has now witnessed enigmatic changes with the arrival of rapidly developing technology in all possible ways. From the introduction of primitive technology like teaching machines or basic instructional technology to today's artificial intelligence, technology is set to transform the futuristic notion of education across the world. India, being an emerging hub of world education is now most likely to adopt Artificial Intelligence as a part of teaching learning and curriculum transaction. Teachers are the most crucial stakeholders and have the sheer responsibility of adopting Artificial Intelligence into their teaching-learning practices through AI-integrated curricula or professional development mechanisms. This paper will cover 435 relevant studies based on publishing years, publishing mode, type of documents, and index type to formulate a systematic review of using artificial intelligence in Continuous professional development. This systematic Bibliographic review will eventually show the current scenario, scopes, and challenges of integrating Artificial Intelligence in the professional development mechanism of teachers at different levels.

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Artificial Intelligence, Teacher Education, Continuous Professional Development, Systematic Bibliographic reviews

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As more and more DNA sequences are becoming available day by day, storing and transmitting them may require a huge amount of space. This paper introduces a new DNA sequence compression programme which is based on Huffman Technique of compression routine. DNA and RNA sequences can be considered as tests over a four letter alphabet, namely {a,t,g and c} ( note that t is replaced with u in the case of the RNA). For complete genomes, these texts can be very long. Huffman's code also fails badly on DNA sequences both in the static and adaptive model, because there are only four kind symbols in DNA sequences and the probabilities of occurrence of the symbols are not very different[1]. Huffman coding is known to compress not very efficiently [2].This program is developed mainly to merge with dynamic Look up Table method, where sixty eight kind symbols are present. This merge techniques are developed to increase the compression rate/bases. This algorithm can approach a compression rate of 2.1 bits /base and even lower. This compression rate is defined as the compressed file size divided by base number[3]. This algorithm can approach a compression ratio is better than other method. The definition of the compression ratio is the same as in [4] i.e.,1- (|O|/2| I|), where |I| is number of bases in the input DNA sequence and |O| is the length (number of bits) of the output sequence. Compression of these genome sequences will help us increase the efficiency of their use. We use Huffman coding to encode the nucleotide genome sequence , a greedy algorithm that constructs an optimal prefix code called a Huffman code. The algorithm builds the tree T corresponding to the optimal code in a bottom-up manner. It begins with a set of |c| leaves and perform |c|-1 "merging" operations to create the final tree. The total running time of Huffman on the set of n characters is O( n log n). We tested the program on standard benchmark data used in[4]. The greatest advantage of this progrmme is fast execution, small memory occupation and easy implementation. Since this program have been written both in the C language, (Windows platform, and TC compiler) and MATLAB, it is possible to run in other microcomputers with small changes (depending on platform and Compiler used). The program runs on the IBM personal computer, requires 512K, without additional hardware except for disk drives and printer. The execution is quite fast, all the operations are carried out in fraction of seconds, depending on the required task and on the sequence length.

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Huffman algorithm, Biology and genetics, Data Compression

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Thyroid is an essential endocrine gland. Thyroid hormones controls body's fundamental metabolic rate, currently hypothyroidism possessing a measure challenge to medical fraternity in developing as well as developed country. Hypothyroidism is the common clinical condition of thyroid hormone deficiency and if left untreated, can lead to serious adverse health effect on multiple organ systems. Primary hypothyroidism is defined as elevated thyroid stimulating hormone (TSH) concentration in combination with free thyroxin (T4) concentration below the reference range. Hypothyroidism usually associated with the symptoms like weight gain, face puffiness, fatigue, hair loss, constipation. In the conventional system there is no permanent solution for this disease. Hence there is an urgent need for safe and effective alternate solutions where ayurveda can play vital role to resolve the issues. As per classics, Punarnavadi kwatha is one of the potent herbal preparation which acts on sarvanga shopha (~anasarca), Pandu, Udara etc. Though, Punarnavadi kwatha is not indicated directly in hypothyroidism but based on clinical presentation in hypothyroidism like mixed edema, Pandu which are the indications of Punarnavadi kwatha. Hence same medicine used in hypothyroidism associated with these symptoms.

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Hypothyroidism, Thyroid stimulating hormone (TSH), Srotoshodhana, Punarnavadi kwatha

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ABSTRACT Dadru, commonly known as fungal skin infections, presents a significant challenge in dermatological practice due to its recurrent nature and varying response to conventional therapies. This review discusses the holistic perspective of Ayurveda in understanding Dadru, emphasizing the importance of dosha imbalance, immune modulation, and lifestyle modifications in its management and provides an in-depth analysis of two traditional Ayurveda treatment modalities, Raktamokshan and Vidangadi Lepa in the management of Dadru. Vidangadi Lepa, a topical formulation comprising herbs like Vidanga (Embelia ribes) and Haridra (Curcuma longa), has been traditionally employed for its antifungal and antiinflammatory properties. The review examines the pharmacological actions of the individual components and their synergistic effects in combating fungal infections. Additionally, the review delves into the therapeutic approach of Raktamokshana by Jalauka-avcharana, a bloodletting procedure in Ayurveda, for the management of Dadru. Raktamokshana aims to eliminate vitiated blood and toxins from the body, thereby alleviating the underlying imbalance responsible for fungal skin infections. This review aims to fill this gap by providing a thorough description of Raktamokshana and Vidangadi Lepa in the context of Dadru.

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Dadru, Dermatophytosis, Fungal infection.

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[The COVID-19 pandemic had a profound and lasting impact on the tourism industry worldwide. The restrictions on movement, lockdowns, and border closures severely disrupted travel plans, leading to a significant decline in tourism activities. Travel was halted, borders were closed, planes were cancelled, and tourism was slowed down by COVID-19 restrictions. The impact on countries that depend significantly on tourism showed the interdependence of the world and the vulnerability of sectors that depend on human mobility. The aim of this paper is to understand the effect of Covid-19 on tourism industry of Dakshina Kannada by analysing the difference between tourist visited the district pre- Covid-19 and post- Covid-19. Moreover, the study considers selected tourist attraction places for the year 2018 and 2021. This research utilizes secondary data gathered from 14 well-known religious and natural tourism destinations in Dakshina Kannada district collected from Tourist Office, Department of Tourism, Mangalore, Dakshina Kannada District and Government of Karnataka. As we had to compare two years' data, the analysis employs the Paired T- test to assess the data.And as a result it is known that there is a lot of difference in tourist arrivals after pandemic and it is mainly due to Covid-19. Through this paper, we would like to suggest that Government and local bodies must concentrate more on improving the tourism places in Dakshina Kannada by providing clean and safer environment. This will give assurance for tourists regarding their visit and hence, Dakshina Kannada can attract more visitors].

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Covid-19, Pandemic, Tourism, Dakshina Kannada, T-test.

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It presents a machine learning based approach for predicting solar power generation. The approach includes data collection, preprocessing, feature selection, training, selection, evaluation, model and deployment. High-quality data from multiple sources, including weather data, and historical solar power generation data, are collected and pre-processed to remove outliers, handle missing values, and normalize the data. Relevant features such as temperature, humidity, wind speed, and solar irradiance are selected for model training. Additionally, the model may consider time-related features such as time of day, day of the week, and seasonal variations. This project leverages advanced machine learning techniques, specifically Random Forest Regression and Gradient Boosting models, to predict solar power output. These models are chosen for their robustness in handling non-linear relationships and their ability to manage large datasets with numerous features. By integrating weather data, historical solar power generation records, and other relevant environmental parameters, the models aim to provide accurate short-term and long-term forecasts of solar energy production. The methodology involves data preprocessing, feature selection, model training, and validation. The performance of the Random Forest Regression and Gradient Boosting models is evaluated using metrics such as Mean Absolute Error (MAE) and R squared. The results demonstrate that machine learning models can significantly enhance the accuracy of solar power generation forecasts.

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Machine learning, Random Forest Regression, Gradient Boosting model, Mean Absolute Error (MAE), R squared, Voting Regressor approach

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