Journal of Science Engineering Technology and Management Science

This study main focus on to analysis the overall performance of the Bajaj auto limited to analysis the overall performance with the help of financial statement with shows all revenues, expenses, assets, and liabilities in the form of a balance sheet and a profit and loss statement This statement is examined; it is referred to as performance; it aids the company in making decisions and provides information about the role of financial components in business. The method used to analysis their performance was ratio analysis (liquidity, profitability and solvency) and fluctuating working capital schedules This technique aids in the analysis of business performance.

Keywords : Financial performance, Financial statement, Ratio Analysis.

Author : M. Ragini, Dr.S. Narender

Title : A STUDY ON FINANCIAL PERFORMANCE ANALYSIS OF BAJAJ AUTO PVT LTD, HYDERABAD

Volume/Issue : 2025;02(07)

Page No : 265-276

Because of improvements in technology, the Human Resources (HR) field has changed totally. Old ways of doing things have been replaced by data-driven, easier processes. This study uses a range of methods to look into how technology is used and how it affects different human resource chores, such as hiring, onboarding, performance management, training, employee involvement, and workforce data. Businesses can now automate boring tasks, make better decisions, and give employees more personalised experiences thanks to the rise of cloud-based human resource information systems, AI, ML, and HRIS.

Keywords : Technology in HR, Human Resources, Data-driven HR, HR Automation, Cloud-based HRIS, Artificial Intelligence, Machine Learning, HRIS, Hiring, Onboarding, Performance Management, Training, Employee Engagement

Author : Mayakannan Sumithra, Ms. Masrath Ayesha

Title : A Study on “Technology in HR-Hetro pharma”

Volume/Issue : 2025;02(07)

Page No : 277-284

In the rapidly evolving digital era, organizations are increasingly turning to Artificial Intelligence (AI) to revolutionize their Learning and Development (L&D) strategies. AI has emerged as a transformative force in corporate training by enabling personalized, efficient, and data-driven learning experiences that align with individual and organizational needs. This study explores the multifaceted role of AI in enhancing L&D programs, focusing on how technologies such as machine learning, natural language processing, and intelligent automation can optimize training delivery, content customization, and learner engagement. Traditional training models often follow a one-size-fits-all approach, which fails to accommodate the diverse learning styles, paces, and preferences of today’s workforce. AI addresses this gap by analyzing learner behavior and performance data to provide adaptive learning paths, real-time feedback, and targeted skill development. Moreover, AI can automate repetitive tasks such as scheduling, assessments, and progress tracking, freeing up time for L&D professionals to focus on strategic initiatives. Through a review of current literature, real-world case studies, and expert perspectives, this research investigates the tangible benefits and challenges of integrating AI into L&D initiatives across various sectors including IT, finance, healthcare, and education. The study also evaluates the effectiveness of AI tools in fostering continuous learning cultures, upskilling employees, and supporting organizational agility in the face of change. While AI offers significant opportunities to make learning more interactive, accessible, and results-driven, the research also highlights the importance of ethical considerations, data privacy, and human oversight in AI-driven L&D. Overall, this study aims to provide a comprehensive understanding of how AI can be strategically leveraged to build smarter, scalable, an

Keywords : artificial intelligences , learning and development , work force training , employee satisfaction ,employee engagement

Author : Nasi kavya, Ms Masrath Ayesha

Title : A study on Exploring the Role of Artificial Intelligence in Enhancing Learning and Development Programs with reference DR. Reddy laboratories pvt ltd

Volume/Issue : 2025;02(07)

Page No : 285-295

Equity analysis is a critical process for investors aiming to make informed decisions in the stock market. This project focuses on understanding and applying the two primary approaches to equity analysis: fundamental analysis and technical analysis. These methods provide distinct yet complementary perspectives on evaluating and predicting stock performance.

Keywords : Equity analysis, Investors, Informed decisions

Author : P. Naval, Dr.S. Narender

Title : A PROJECT REPORT ON FUNDAMENTAL AND TECHNICAL ANALYSIS OF EQUITY AT HDFC BANK, HYDERABAD

Volume/Issue : 2025;02(07)

Page No : 296-304

This study explores the impact of Non-Performing Assets (NPAs) on the financial performance and operational efficiency of the State Bank of India (SBI) from 2021 to 2025. NPAs refer to loans where the borrower fails to repay the principal or interest for more than 90 days, causing a direct hit to a bank’s profitability and lending capacity. The research highlights a significant decline in SBI's NPAs during the study period, alongside a steady increase in total advances, indicating improved credit management, recovery mechanisms, and asset quality. The NPA ratio dropped across all loan segments— personal, home, business, agricultural, and priority sector— demonstrating SBI’s robust approach to reducing financial risk and enhancing operational strength. The study relies on both primary and secondary data, including interviews with SBI officials and analysis of bank reports. Key findings suggest that while SBI faced challenges related to rising NPAs in earlier years, the bank has successfully implemented strategies like tighter credit monitoring, improved legal recovery processes, and digital tools to manage and minimize NPAs effectively. In conclusion, the study emphasizes the importance of continuous monitoring and strong policy interventions in managing NPAs. It also reinforces that reducing NPAs is essential for ensuring financial health, public trust, and economic stability in India’s banking sector

Keywords : Asset quality, Credit risk Financial health, Profitability, Recovery Strategies

Author : Sri Ramya Vallamsetty, Dr. S. Narender

Title : Impact of Non-Performing Assets on State Bank of India , Hyd – A STUDY

Volume/Issue : 2025;02(07)

Page No : 305-317

Credit Risk management is a critical component in the banking sector, ensuring financial stability and minimizing potential losses due to borrower defaults. This study investigates the effectiveness of credit risk management practices in Axis Bank, one of India's leading private sector banks. The objective is to analyze the bank’s credit risk identification, assessment, mitigation, and monitoring strategies. Through a review of secondary data, including annual reports, RBI guidelines, and Axis Bank’s risk management framework, as well as primary data gathered via structured questionnaires and interviews with bank officials

Keywords :

Author : Thakur Vikas Singh, Dr. S. Narender

Title : A STUDY ON THE EFFECTIVENESS OF CREDIT RISK MANAGEMENT IN AXIS BANK

Volume/Issue : 2025;02(07)

Page No : 318-327

Portfolio management involves the strategic allocation of financial assets to maximize returns and minimize risks in alignment with the investor`s goals and risk appetite. Axis Bank, one of India`s leading private sectors banks, offers comprehensive portfolio management services (PMS) to highnet-worth individuals (HNIs) and institutional clients through Axis Securities and Axis Asset Management Company. The bank's portfolio management framework focuses on tailored investment solutions, leveraging expert research, dynamic asset allocation strategies, and robust risk management practices. In summary, Axis Bank's portfolio management services aim to deliver superior riskadjusted returns by combining financial expertise, market insights, and customer-centric solutions tailored to individual investment goals.

Keywords : Portfolio Management, Asset Allocation, Risk Management, Investment Goals, Risk Appetite, Axis Bank, High-Net-Worth Individuals (HNIs), Institutional Clients, Axis Securities, Axis Asset Management, Tailored Investment Solutions, Expert Research, Dynamic Strategies, CustomerCentric, Superior Returns, Financial Expertise, Market Insights, Risk-Adjusted Returns

Author : Konda Sandhya, Dr. K. Pusha Latha

Title : A STUDY ON PORTFOLIO MANAGEMENT IN AXIS BANK

Volume/Issue : 2025;02(07)

Page No : 328-339

Effective cash management is critical for the financial health and operational efficiency of any organization. This study focuses on the cash management practices of a selected company, analyzing its ability to maintain liquidity, meet short-term obligations, and optimize cash flow. The research explores key components such as cash inflows and outflows, cash budgeting, and working capital management. It also evaluates the role of cash forecasting and investment of surplus cash in improving financial performance. Using secondary data over a five-year period, the study examines trends and assesses how cash management strategies impact overall financial stability. The findings highlight the importance of strategic planning, timely cash flow analysis, and internal controls in enhancing cash utilization. The study concludes by suggesting measures for better cash optimization to support sustainable business growth.

Keywords : Cash Management, Liquidity, Cash Flow Optimization, Working Capital Management, Cash Budgeting

Author : Aishwika Makthala,Dr K. Pushpa Latha

Title : A STUDY ON CASH MANAGEMENT AT ULTRATECH CEMENT, HYDERABAD

Volume/Issue : 2025;02(07)

Page No : 340-352

The purpose of study is to determine the main elements influencing investor preferences and decision by examining consumer perception of public and private mutual funds. In order to obtain qualitative insights, we employed a mixedmethods approach, surveying a wide rang e of investors and conducting indepth interviews.The results show that while private mutual funds are preferred due to their greater returns and more individualized services, public mutual funds must prior itize trust and openness.The report also emphasizes how financial literacy and market awareness affec t investment decisions.Fund managers and legislators can use these information to improve mutual fu nd offerings and better meet investor expectations.

Keywords :

Author : Mekkanti Sunil, Dr K. Pushpa Latha

Title : A STUDY ON CUSTOMER PERCEPTION TOWARDS PUBLIC MUTUAL FUNDS AND PRIVATE MUTUAL FUNDS

Volume/Issue : 2025;02(07)

Page No : 353-361

The goal of capital budgeting is to optimize a company's long-term return on investment. It is the way a business divides up its meager financial resources. Through capital budgeting, a business considers the acquisition of significant fixed assets such as buildings, machinery, and equipment. It distributes the company's limited financial resources across market prospects and only takes longterm, significant investment plans into account. Capital projects will be analyzed using the Internal Rate of Return, Net Present Value, Profitability Index, and Average Rate of Return. For the study, a sample of projects is selected, and their acceptance or rejection is displayed.

Keywords : Capital Budgeting, Investment, NPV, Payback period

Author : Pasula Pavithra, Dr. K. Pushpalatha

Title : A STUDY ON CAPITAL BUDGETING TECHNIQUES IN AXIS BANK

Volume/Issue : 2025;02(07)

Page No : 362-372

The present study aims to evaluate the financial performance of Bajaj FinServ Limited, a leading financial services company in India, through a comprehensive analysis using ratio analysis techniques. Financial analysis is a crucial tool for stakeholders to assess a company's profitability, liquidity, solvency, and overall financial health. This project focuses on understanding the company’s financial position over a specific period by examining key financial ratios such as profitability ratios, liquidity ratios, solvency ratios, and efficiency ratios. Data for the study has been collected primarily from the company’s annual reports and secondary sources such as financial databases and journals. The analysis reveals the strengths and weaknesses in Bajaj FinServ’s financial structure and performance, providing insights into its operational efficiency and financial sustainability. The findings of this study are valuable for investors, financial analysts, and decision-makers in understanding the company’s financial trajectory and making informed decisions. The study concludes with recommendations to enhance financial efficiency and sustain long-term growth

Keywords : Economic, Financial Analysis, Regulatory, Liquidity, profitability, creditors

Author : Chintala Kanth, Dr. K. Pushpalatha

Title : A STUDY ON FINANCIAL ANALYSIS WITH REFERENCE TO BAJAJ FINSERV LIMITED

Volume/Issue : 2025;02(07)

Page No : 373-381

In today’s dynamic market environment, understanding and adapting to changing customer tastes and preferences has become crucial for business sustainability and growth. Customer satisfaction, a subjective and multifaceted concept, plays a pivotal role in shaping consumer behaviour, influencing factors such as repeat purchases and brand loyalty. It is influenced by various psychological and physical elements, making its evaluation essential for strategic decision-making. Particularly in the highly competitive landscape of Multilevel Marketing and retail sectors, identifying the key determinants of customer attitudes is vital for long-term success. Big Bazaar, a major retail chain under the Future Group, exemplifies this evolution. Since its inception in 2001, it has expanded rapidly across India, transforming from a fashion-centric outlet to a comprehensive hypermarket. Offering a diverse range of products—from groceries and apparel to electronics and furniture—Big Bazaar aims to provide a holistic shopping experience that caters to the varied needs of Indian consumers. This study explores the factors influencing customer satisfaction in such dynamic retail environments

Keywords :

Author : A.Vijay kumar, Mr.BH.L.Mohan Raju

Title : A STUDY ON CUSTOMER SATISFACTION ON BIG BAZAR

Volume/Issue : 2025;02(07)

Page No : 382-389

This study uses the CAMELS framework—which stands for Capital Adequacy, Asset Quality, Management, Earnings, Liquidity, and Sensitivity—to assess the State Bank of India's (SBI) financial performance for FY 2024. The analysis, which was based on secondary data from SBI's audited annual report, showed "Excellent" asset quality with a Net NPA of 0.57% and a "Good" capital position with a CAR of 14.28%. However, a high operating expense-to-income ratio of 55.67% resulted in a "Poor" ranking for management quality. With a ROE of 16.19% and a ROA of 0.99%, the earnings were mediocre. Sound financial management was demonstrated by the "Good" ratings for liquidity and sensitivity measures. Overall, SBI showed strength in liquidity, capital, and asset quality, but it struggled with operational efficiency. To improve overall performance, the report suggests portfolio diversification, capital strengthening, and expense reduction.

Keywords : Financial performance, Asset quality, Capital Adequacy, Earning etc

Author : Sandhya Pogu Parimala, Dr. K. Pushpalatha

Title : A STUDY ON FINANCIAL PERFORMANCE OF SBI BANK USING CAMELS FRAMEWORK

Volume/Issue : 2025;02(07)

Page No : 390-401

This study investigates the channels of distribution at Kesoram Cements with a focus on identifying the influencing factors, evaluating the impact on retailer satisfaction, and examining the strategic approaches employed by the company. A structured questionnaire was administered to 100 retailers, and the analysis reveals that digital transformation has significantly influenced the preferred modes of ordering, with a large majority opting for mobile apps and online platforms. Retailers exhibited consistent demand trends, with frequent large-quantity orders, and showed a general preference for Rapid Hardening Cement. The study also highlights areas of moderate satisfaction, such as credit terms, product range, and promotional support, while pointing out limitations in communication and transportation cost transparency.

Keywords :

Author : T. Anil, BH.L. Mohan Raju

Title : A STUDY ON CHANNELS OF DISTRIBUTION AT KESORAM

Volume/Issue : 2025;02(07)

Page No : 402-413

The Human Resources Management refers to the systematic approach to the problems in any organization. It is concerned with recruitment, training and Development of personnel. Human resource is the most important asset of an organization. It ensures sufficient supply, proper quantity and as well as effective utilization of human resources. In order to meet human resources needs, and organization will have to plan in advance about the requirement and the sources, etc. The organization may also have to undertake recruiting selecting and training processes. Human Resources Management includes the inventory of present manpower in the organization. In cases sufficient number of persons is not available in the organization then external sources are also identified for employing them.

Keywords : Recruitment, Human resource, etc

Author : Anuganti Pravalika, Mr. Abburi Mahesh

Title : A STUDY ON CHANGING TRENDS IN RECRUITMENT AND SELECTION PROCESS AT INDIAN INFOLINE

Volume/Issue : 2025;02(07)

Page No : 414-424

This study evaluates the financial liquidity position of the State Bank of India (SBI), focusing on key liquidity ratios such as the Current Ratio, Quick Ratio, Cash Ratio, and Loan-toDeposit Ratio. Using both primary data from SBI employee interviews and secondary data from annual reports, the research analyses SBI’s short-term financial health and liquidity management strategies. Findings highlight the bank’s use of asset- liability management and investment policies to maintain liquidity in line with regulatory norms. The study concludes with recommendations to improve liquidity efficiency while supporting sustained growth and profitability.

Keywords : Financial liquidity, liquidity management strategies, investment policies

Author : Ch. Jahnavi, B.Dharani

Title : A STUDY ON FINANCIAL LIQUIDITY POSITION AT SBI BANK, HYDERABAD

Volume/Issue : 2025;02(07)

Page No : 425-432

This study aims to conduct a comprehensive financial analysis of Reliance Industries Ltd. (RIL), one of India’s largest conglomerates, operating across sectors such as petrochemicals, oil and gas, telecommunications, and retail. The analysis utilizes key financial tools such as ratio analysis, trend analysis, and DuPont analysis to evaluate RIL's performance in terms of profitability, liquidity, solvency, and operational efficiency. The research explores the company's growth trajectory, with a particular focus on its diversification strategy and its impact on financial stability and shareholder value. The study also investigates the implications of external factors such as global oil price fluctuations, government policies, and the company’s strategic investments in new sectors like digital services and green energy. The findings provide valuable insights into the company’s financial health and its ability to sustain growth amidst evolving market conditions.

Keywords : Financial Analysis, Reliance Industries Ltd, Ratio Analysis, Profitability and Liquidity, Diversification Strategy

Author : Mohammad Azaad, Dr. N. Ramanjaneyulu

Title : A STUDY ON FINANCIAL ANALYSIS OF RELIANCE INDUSTRIES LTD

Volume/Issue : 2025;02(07)

Page No : 433-444

This study investigated the effectiveness of employee grievance handling mechanisms at UltraTech Cements by surveying 100 employees across various hierarchical levels. The research employed a structured questionnaire to capture demographic information, grievance experiences, reporting methods, perceived procedural clarity, and satisfaction with outcomes. Findings revealed that 60.0% of employees had encountered at least one grievance, with interpersonal conflicts (30.0%) and compensation issues (25.0%) as the predominant complaint types. Verbal reporting to immediate supervisors emerged as the most common channel (40.0%), while formal grievance committees were underutilized (15.0%). Although 75.0% of grievances were resolved within four weeks, one-quarter of respondents remained neutral or dissatisfied with procedural transparency and confidentiality. These results highlighted the strengths of timely resolution and managerial accessibility, but also exposed gaps in consistent policy communication and professional handling

Keywords :

Author : Nethetla Anuhya, Ms T. Manju Usha sree

Title : A STUDY ON EMPLOYEE GRIEVANCE AT ULTRATECH CEMENTS

Volume/Issue : 2025;02(07)

Page No : 445-454

Transformer failures represent a significant threat to the stability and reliability of electrical power systems, often resulting in unexpected outages, costly maintenance, and prolonged downtimes. Proactive and accurate classification of potential transformer faults is critical for minimizing operational disruptions and enabling efficient maintenance scheduling. This study introduces an ensemble machine learning framework aimed at improving the prediction accuracy and reliability of transformer failure classification. The existing system utilizes a Decision Tree Classifier due to its interpretability and ease of implementation. However, it suffers from overfitting and limited generalization, especially when exposed to complex or noisy datasets. To address these challenges, a Random Forest Classifier is proposed, leveraging ensemble learning by combining the outputs of multiple decision trees. This approach enhances model robustness, effectively reduces variance, and improves the handling of non-linear feature interactions. Comparative analysis using standard performance metrics—including accuracy, precision, recall, and F1-score—reveals that the Random Forest model consistently outperforms the Decision Tree across all metrics. The proposed model demonstrates a more reliable and scalable solution for intelligent fault diagnosis in the power grid. Overall, this project emphasizes the importance of ensemble-based machine learning in critical infrastructure applications, offering a practical pathway toward smarter and more resilient transformer monitoring systems

Keywords : Transformer failure prediction, ensemble learning, decision tree, random forest classifier, power system reliability, fault classification, machine learning, model evaluation

Author : P. Sujatha, A. Amala, Uday Kumar Burugu, Gopavarapu Indrasena Reddy,Vamshi Krishna Balla

Title : ENSEMBLE-BASED APPROACH FOR PREDICTIVE CLASSIFICATION OF TRANSFORMER FAILURES

Volume/Issue : 2025;02(07)

Page No : 455-464

This research introduces an intelligent, IoT-enabled poultry farming system powered by the ESP32 microcontroller, aimed at automating and optimizing crucial environmental and operational parameters for efficient and healthy poultry production. The system integrates several input modules: an RTC (Real-Time Clock) for scheduling tasks, Bluetooth for wireless connectivity, a DHT11 sensor for monitoring temperature and humidity, a pH sensor for assessing water quality, and an ultrasonic sensor for measuring feed or water levels. These components continuously collect data, which is processed by the ESP32 in real-time.In response to the sensor inputs, the system activates output devices, including an LCD to display live environmental readings, a buzzer for alert notifications, and a servo-operated pump to automatically dispense water or nutrients as needed. Additionally, the system enables remote monitoring and control through IoT platforms, empowering farmers to manage their poultry environment from any location. This enhances farm efficiency, improves animal health and welfare, minimizes manual intervention, and reduces operational costs. The proposed system is scalable, energy-efficient, and adaptable for both smallholder and commercial poultry operations, offering a robust solution for modern poultry farm management

Keywords : IoT, ESP32, Smart Poultry Farming, Real-Time Monitoring, DHT11, pH Sensor, Ultrasonic Sensor, Automation, Remote Control, Environmental Optimization

Author : Shaik Imam Vali, Y. Vishwa Sri, Karthik Reddy Koppula, Saisharath Allivadha, Mekala Abhilash Reddy, Ramavath Parashuram

Title : SMART AQUACULTURE A CLOUD-ENABLED IOT FRAMEWORK FOR REAL-TIME WATER QUALITY MONITORING AND MANAGEMENT

Volume/Issue : 2025;02(07)

Page No : 465-470

Road safety has emerged as a major public concern with the increasing incidence of traffic accidents, many of which are attributed to overspeeding and violations of traffic regulations. To address this issue, the present project introduces an IoT-driven smart traffic enforcement system aimed at the automatic detection and penalization of speed violations. The system employs a combination of technologies including RFID for vehicle identification, IR sensors for speed monitoring, an ESP32- CAM for visual evidence capture, and a GSM module for e-challan dispatch.The process initiates when a vehicle passes through a monitored segment outfitted with two IR sensors positioned at a fixed interval. By calculating the time taken to travel between the sensors, the system determines the vehicle's speed. If the calculated speed exceeds the designated threshold, the ESP32-CAM captures an image of the violating vehicle. Simultaneously, the RFID module retrieves the vehicle's unique ID, linking the violation to a registered owner. The GSM module then transmits a digital fine notification (e-challan) to the owner's mobile number.This solution offers a contactless and automated alternative to traditional traffic policing, minimizing the potential for human error and corruption. It enhances enforcement efficiency while encouraging compliance with speed regulations. The system also generates real-time violation data, contributing to improved traffic analytics and supporting smart city development initiatives. Designed for scalability and affordability, the proposed system is well-suited for deployment in both urban and semi-urban environments

Keywords : IoT, Speed Detection, ESP32-CAM, RFID, GSM, E-Challan, Smart Traffic System, RealTime Monitoring, Intelligent Policing, Road Safety

Author : P. Hussain, Shaik Imam Vali, Vijay Kumar A, Pavan Teja Mallaiah, Gopaiah N, Anuga Naresh

Title : AN INTELLIGENT SURVEILLANCE SYSTEM FOR AUTOMATED DETECTION OF SPEED VIOLATIONS IN URBAN TRAFFIC

Volume/Issue : 2025;02(07)

Page No : 471-477

As the demand for eco-friendly agricultural solutions grows, hydroponics offers a modern approach to farming that eliminates the need for soil while significantly conserving water and nutrients. This research presents a compact, solar-powered smart hydroponic system integrated with IoT capabilities, specifically designed for indoor environments. The setup incorporates an ESP32 microcontroller at its core, managing real-time data acquisition and automated decision-making processes.Essential components include a suite of sensors that track environmental and system parameters such as temperature, humidity, water reservoir levels, and nutrient concentrations. A 16x2 LCD provides onsite feedback, while a buzzer alerts users to critical system changes. The irrigation system is operated by an AC water pump, which functions in two modes: Manual mode allows remote activation via an IoT dashboard, whereas Automatic mode relies on sensor thresholds to maintain optimal growth conditions autonomously.All system data is uploaded to a cloud-based IoT platform, enabling remote observation, logging, and analysis. Powered entirely by solar panels, the system reduces energy consumption and supports sustainable indoor agriculture. The automation of irrigation and environmental control reduces labor, ensures optimal plant health, and supports continuous food production in space-limited areas. This innovation highlights a practical and scalable solution for urban farming and smart agriculture

Keywords : IoT, Hydroponics, Solar Power, Indoor Farming, Plant Growth Chamber, Cloud Computing, sustainable farming, precision irrigation

Author : A. Amala, Dr. P. Anil Kumar, Khusboo Solanki, Srinesh Goud E, Rahul S V, Ganji Nikhil

Title : IOT INTEGRATED SOLAR POWERED SMART HYDROPONICS SYSTEM FOR SUSTAINABLE INDOOR AGRICULTURE

Volume/Issue : 2025;02(07)

Page No : 478-485

Optical Character Recognition (OCR) is a fundamental technology used to digitize and extract text from printed and handwritten documents, playing a crucial role in legal and financial domains. Traditional OCR techniques, such as bounding box analysis, typically rely on rectangular text segmentation but face significant limitations when processing complex layouts, varying text orientations, and handwritten elements. These challenges highlight the need for a more adaptive and robust approach to enable efficient and accurate text extraction in document-intensive industries.The proposed method integrates advanced natural language processing (NLP)-based post-processing to enhance contextual accuracy and significantly reduce recognition errors. Unlike conventional bounding box analysis, the system dynamically adjusts to diverse text structures, making it particularly effective for processing multi-column legal documents, financial statements, and tabular data. This adaptability ensures precise extraction from a wide range of document formats, thus streamlining workflow automation in the legal and financial sectors.Performance evaluations demonstrate that the proposed OCR system outperforms traditional techniques in terms of recognition accuracy, processing speed, and scalability. By addressing the shortcomings of existing methods, this innovation offers a transformative solution for legal and financial institutions seeking improved efficiency, accuracy, and automation in their document handling processes

Keywords : OCR, Text Extraction, Legal Documents, Financial Documents, NLP Post-Processing, Complex Layouts, Recognition Accuracy, Document Automation, Tabular Data Processing, Scalable OCR Systems

Author : B. Nagalaxmi, P. Sujatha, Gandlakanna.Sandeep, G. Lakshmi Varun, B. Harshavardhan Teja

Title : OPTIMIZED OCR APPROACHES FOR ACCURATE TEXT EXTRACTION IN LEGAL AND FINANCIAL DOCUMENT AUTOMATION

Volume/Issue : 2025;02(07)

Page No : 486-495

The primary audience for sell-side analysts' recommendations is institutional investors that are required to invest in a broad range of companies within client-mandated equity benchmarks, like the FTSE/JSE All-Share index. It might be difficult for portfolio managers to make unbiased investment judgements given the various sell-side recommendations for a single stock. Using random forest, extreme gradient boosting, deep neural networks, and logistic regression, this study investigates the utilisation of past sell-side recommendations to produce an impartial fusion of analyst forecasts that optimises bidirectional accuracy. While eliminating forward-looking biases, we incorporated 12-month rolling features derived from common sell-side recommendations, such as analyst coverage, point and directional accuracy. By combining forecast features from many analysts using machine learning techniques, we introduce a novel "AI analyst". By methodically producing objective and incrementally better prediction accuracy from publicly available sell-side recommendations, we were able to observe the additional benefits of using these features from multiple analysts. The Decision Tree algorithm, XGB Random forest, and KNeighbors algorithms demonstrated the highest relative performance. Machine learning algorithms perform better in resource-related industries with high volatility than in industries with low volatility, indicating the value of rolling features in bi-directional prediction under such conditions. We observe the incremental contribution of rolling features using feature significance, illuminating the connections between analyst coverage, volatility, and the accuracy of bidirectional forecasts. Furthermore, when modelling analysts' directional forecasts, factors using logistic regression highlight volatility features, initial and target price as some of the crucial aspects

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Author : K.Krishna,M.Sravanthi,M.Mrudula,M.Vamsi Priya,Emani Sri Lakshmi,Dr.G.Sravanthi

Title : OPTIMIZING FINANCIAL FORECASTS WITH BIDIRECTIONAL ANALYST MODEL FUSION

Volume/Issue : 2025;02(07)

Page No : 496-503

Sign language is the main form of communication for the community of people who are speech- and hearing-impaired. The general public finds it very difficult to fully understand or interpret sign language. The creation of a sign language recognition system is necessary to overcome this communication obstacle. Since wearable sensors are the foundation of the majority of sign language identification systems now in use, most people cannot afford the recognition system. Furthermore, not all of the spatial and temporal information needed for precise recognition is taken into account by the vision-based sign recognition frameworks that are now in use. This paper proposes a novel vision-based hybrid deep neural net methodology for custom sign gestures and American Sign Language (ASL) recognition. The objective of the suggested framework is to provide a unified system for monitoring and obtaining multi-semantic attributes, like non-manual components. include co-articulations by hand. Besides, a Hybrid Deep Neural Network (HDNN) with atrous convolutions is used for spatial feature extraction from the sign gestures. HDNN based on attention is utilized for the extraction of sequential and temporal features. Moreover, altered auto encoders are used for the extraction of the unique abstract features. The hybrid attention module is utilized in the discriminative feature extraction process to distinguish desired transition gestures from sign gestures. Experiments with the innovative multi-signer ASL and custom sign language dataset have been conducted to test the proposed model. The hybrid neural net architecture that is being presented, which uses HDNN in particular, performs better than existing state-of-the-art frameworks for sign language recognition. Moreover, Flask web is used to integrate a detection module that enables manual picture and sign input for real-time acknowledgement

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Author : K.Krishna, Yegetela Ram Kumar, Shivarao Yannam, Bandari Rajesh,Bujpa Shivakarthik,Ajmeera Ramakrishna

Title : A CNN-BASED APPROACH TO MULTI-CULTURAL SIGN LANGUAGE DETECTION AND INTERPRETATION

Volume/Issue : 2025;02(07)

Page No : 504-510