Volume 12 | Issue 10 |

 Abstract

Bharat mein gramin Vikas ke sandrbh mein digital taknik ek Parivartan kari shakti ke roop mein ubhari hai, Jo gramin samudayon ke samne aane wali dirghakalic chunautiyon ke liye Abhinav Samadhan prastut karti hai. Yah sar krishi utpadakta badhane, Shiksha aur swasthya seva Tak pahunch mein sudhar karne aur uddhamita aur Kaushal Vikas ke madhyam se arthik Vikas ko badhava dene mein digital taknik ki bahumukhi bhumika ka pata lagata hai. Mobile taknik aur internet ke ekikaran ne Mausam ke mijaj, bajar ki kimaton aur sarvottam krishi paddhtiyon se sambandhit mahatvpurn suchnaon ke Prasar ki suvidha pradan Ki hai, jisse kisanon ko suchit nirnay Lene mein sashakt banaya hai. E governance pahal ne sarkari sevaon ke vitran mein pardarshita aur dakshata mein sudhar Kiya hai, naukarshahi badhaon ko kam Kiya hai aur labhon Tak samay per pahunch sunishchit Ki hai. Iske alava, digital platform ke samuh ke liye raste khole Hain, arthik Kshetra mein samaveshita aur bhagidari Ko badhava Diya hai. Halanki, ine taknikon ke karyanvayan mein digital nirikshanta, buniyadi dhanche ki Kami aur samajik arthik asamantaon Jaisi chunautiyan Hain. Yah sar satat gramin Vikas ke liye utprerak ke roop mein digital praudyogiki ki kshamta per Prakash dalta hai, Sath Hi maujuda badhaon Ko dur karne ke liye lakshit nitiyon aur nivesh ki avashyakta per Bal deta hai, taki yah sunishchit ho sake ki digital Pragati ka Labh gramin Bharat ke har Kone Tak pahunche.

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 Keywords

Bhartiya gramin Vikas, digital praudyogiki.

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The year 1947 is much known to the Indian subcontinent and the world as the year when India and Pakistan got independence from the British rule. Both the countries had long been under the rule for nearly two centuries. This period was marked by financial, social and religious exploitation. The Britishers had no intentions to leave the subcontinent on its own any time soon. But as they participated in the second world war on behalf of the allied group which went on for six years, they were bankrupted and were very short on resources to run the administration of India. So they decided to grant freedom to India. But while doing so, they divided it into two countries on the basis of religion. One was India of Hindus and the other was Pakistan of Muslims. Religious and communal differences were among the things which beautified the Indian subcontinent and presented it in front of the world as a multicultural land. Such things prevail in the society only when human values are there. But this identity was tarnished because of the partition of India and the bloody and gory events that took place during it. This research paper contains personal views of the people who actually witnessed the partition and brings out their perspective about it and a sense of belonging and alienation they have felt over the years because of partition.

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 Keywords

Partition, Freedom, Human Perspective, Interviews, Eye-witnesses, Experiences, Migration, Religious Riots, Violence, Massacre, Conflict, Homeland, Motherland, Foreign Land, Sense of Belonging, Sense of Alienation

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In the realm of modern recruitment, the surge in applicants for a single job opening presents a formidable challenge for recruiters, necessitating a meticulous review of numerous resumes. This process is both time-consuming and arduous due to the inherent diversity in resume structures, sections, and formats submitted by applicants. To address this challenge and streamline the hiring process, our proposed solution is the Smart Resume Analyzer an innovative system rooted in Natural Language Processing (NLP). The extraction of critical information from resumes, such as contact information, skills, education, and job experience, requires the use of resume parsing. [1] This system comprises two core components: Job Seekers and Recruiters. Job seekers upload their resumes, typically in PDF or DOC formats, initiating a parsing process for field extraction. Subsequently, the system conducts a thorough analysis, assigning a rank to each resume based on factors such as skills, educational background, and other relevant parameters. Furthermore, the system offers valuable feedback to applicants, recommending enhancements like skills, courses, or additional fields to boost their resume's ranking. The analysis results and ranked resumes are stored in a database, furnishing recruiters with a comprehensive overview of the most qualified candidates for a specific role. This approach markedly reduces the time recruiters spend manually reviewing resumes, significantly enhancing the overall efficiency of the hiring process.

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Natural Language Processing (NLP), Recruitment, Resume Parsing, Resume Analyzer, Job portal

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In This I have studied the seismic response of various types of slabs in commercial buildings and their seismic behavior is studied. As we know every year uncountable number of earthquakes occur at different places, that means, small movements of tectonic plates occur all the time causing earthquakes. A building designed to withstand seismic activity can protect more people. If we construct seismic resistant slabs and roofs, we will require more columns, however in some situations, such as airports, retail malls, and commercial buildings, extra columns may cause problems. To address this issue, seismic designs for flat slabs and waffle slabs were developed. Flat/Waffle slabs are made up of concrete beams separated at constant intervals in perpendicular directions and are monolithically cast with slab, making them safer in earthquakes than traditional slabs.

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Flat Slab, Earthquake Load, Response Spectrum, Storey Drift, Storey Displacement, E-Tab 2018, Base Shear Time Period, Mode Shapes

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This paper presents a novel machine-learning framework for predicting the health state and remaining useful life (RUL) of industrial machinery and equipment. The proposed approach addresses key challenges in data-driven prognostics, including feature engineering, temporal modelling, and uncertainty quantification. Case studies on wind turbine main bearings and milling machine tool wear further validate the framework's practical applicability and generalizability. Visualization techniques, including t-SNE and reservoir dynamics analysis, provide insights into the learned representations and model behavior. This research advances the field of machine prognostics by providing a flexible, accurate, and interpretable framework for predicting machinery health and RUL. The proposed approach enables more effective predictive maintenance strategies, potentially reducing downtime and maintenance costs in various industrial applications.

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Predictive Maintenance, RUL, Machine Prognostics, Machine Learning

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Creative Commons Attribution 4.0 and The Open Definition

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The implementation of hybrid multi-radio access technologies has great dependency upon the efficiencies of multi-user detection (MUD) available at the receiver unit. In order to get the best performance in hybrid power-domain sparse code multiple accesses (PD-SCMA) system, there is a need for effective and efficient strategies in detecting system due to the MUDs complexity and the processing time. A DL-MUD technique addresses this issue by allowing the system to perform detection of all the symbols without the need to do cumbersome interference cancelation or perform further channel estimation in an overloaded PD-SCMA system. In this work, a MUD-on-DNN-MUD technique is presented for the uplink channel in a PD-SCMA system, with both near users (NUs) and far users (FUs) treated as accommodated NUs through power domain multiplexing and FUs through code domain multiplexing respectively. The proposed system MUD also combines SIC and MPA/EPA in the same MUD architecture wherein SIC enhances MPA and EPA. Such integration solves interference diffusion problems in SIC and the efficiency problems of MPA/EPA. Finally, hollow-batch strategies during the training of the DNN were applied for improving the efficiency of detection by decreasing the shifts to internal cells. Performance evaluations demonstrate that the proposed DNN-MUD significantly surpasses conventional joint SIC-MPA/EPA schemes in terms of average symbol error rate (SER), complexity, and computational time.

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 Keywords

Non-orthogonal Multiple Access(NOMA), Multi-User Detection (MUD), Deep Learning (DL), Power-Domain Sparse Code Multiple Access (PD-SCMA), Successive Interference Cancellation (SIC), Message Passing Algorithm (MPA), Expectation Propagation Algorithm (EPA), Symbol Error Rate (SER), Batch Normalization.

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In the textile industry, the accurate and efficient classification of fabric defects is paramount for maintaining high-quality standards. This research explores a novel approach to textile defect classification through feature optimization using Particle Swarm Optimization (PSO) and Random Forest (RF) classification methods, utilizing the real Self Collected Fabrics dataset from 'RADHA LACES'. The process begins with the extraction of pertinent features from textile images, employing techniques to capture texture and color information. PSO is then utilized to optimize the feature set, enhancing the classifier's performance by selecting the most informative features. Subsequently, a Random Forest classification model is constructed, combining the strengths of multiple base classifiers through techniques like Random Forest and Boosting to achieve robust and accurate predictions. The proposed methodology is rigorously evaluated using the SCF dataset, demonstrating significant improvements in classification accuracy and robustness compared to traditional methods. This study highlights the potential of integrating PSO-driven feature optimization with RF learning for advanced defect detection in textiles, offering a viable solution for industrial quality control processes.

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Keywords: Textile Defect Classification, Feature Optimization, Particle Swarm Optimization, Industrial Quality Control, Random Forest Method.

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Creative Commons Attribution 4.0 and The Open Definition

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The health outcomes of tribal populations in India are profoundly influenced by socio-economic factors, creating disparities in healthcare access and outcomes. The Lambadi people, dispersed across various states, confront unique challenges in maintaining their health. Understanding the impact of socio-economic factors on Lambada health outcomes is crucial for tailored interventions. This study investigates this impact, synthesizing 18 articles from Andhra Pradesh, Telangana, Karnataka, Rajasthan, and Maharashtra. Findings reveal prevalent health issues like malnutrition, anemia, diabetes, and hypertension. Socio-economic realities such as poverty, low income, limited access to education and healthcare, and cultural preservation concerns exacerbate these health issues. Key interventions include healthcare provider capacity building, addressing food insecurity, and empowerment programs. Preserving cultural sensitivity in healthcare delivery is essential. This research offers valuable insights for policymakers and stakeholders, emphasizing the need for targeted interventions to improve the health and well-being of Lambada Tribes in India.

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socio-economic factors, health outcomes, Lambada tribes, multi-state analysis

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The energy sector is one of the important key for economic development; they are a strong relationship between the economical growth and more energy consumption. The various countries have different levels of renewable energy sources exist. The development countries are additional resembling to applied for getting job opportunity. T A systematic review of the literature was conducted from 2009 to 2018. During this process, more than 300 articles were classified and 42 papers were filtered for critical review. The literature analysis showed that despite serious efforts at all levels to reduce reliance on fossil fuels by promoting renewable energy as its alternative, fossil fuels continue to contribute 73.5% to the worldwide electricity production in 2017. Conversely, renewable sources contributed only 26.5%. Furthermore, this study highlights that the lack of public awareness is a major barrier to the acceptance of renewable energy technologies. The results of this study show that worldwide energy crises can be managed by integrating renewable energy sources in the power generation. Moreover, in order to facilitate the development of renewable energy technologies, this systematic review has highlighted the importance of public opinion and performed a real-time analysis of public tweets. This example of tweet analysis is a relatively novel initiative in a review study that will seek to direct the attention of future researchers and policymakers toward public opinion and recommend the implications to both academia and industries. KEYWORDS : Sustainable Energy Renewable Energy Sources Solar Power Wind Power Biomass Energy Hydropower Geothermal EnergyEnergy Technologies Public Perception Energy Policy Environmental Sustainability Energy Transition Technology Adoption Community Attitudes Economic Impact Energy Efficiency Climate Change Mitigation.

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Sustainable Energy Renewable Energy Sources Solar Power Wind Power Biomass Energy Hydropower Geothermal EnergyEnergy Technologies Public Perception Energy Policy Environmental Sustainability Energy Transition Technology Adoption Community Attitudes Economic Impact Energy Efficiency Climate Change Mitigation

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Creative Commons Attribution 4.0 and The Open Definition

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This case study explores ITC's journey, its dedication to sustainability, its HR practices and its unique standing in the Indian business landscape.

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Business Initiatives,HR Practices,Diversification strategy,sustainability

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Creative Commons Attribution 4.0 and The Open Definition