Volume 10 | Issue 6

 Abstract

The purpose of our proposed system is to predict the stock market from previous years stock data. Increase in uncertainty in stock market gives us the motive for our proposed system to make it easy and available for common people to know and avoid losses using other technologies available today. The approach consists of the following steps - Data pre-processing, clustering, classification and visualization. Classification and correlation of data set makes it easy to understand similarities & dissimilarities amongst the data objects. In our proposed system data collection was done from yfinance. The significance of our proposed system is to give the commoner an insight in stock market pattern and awareness to avoid losses in prior. Stock prices cannot be predicted exactly since it is neither systematic nor random. Even though we cannot predict exact price changes due to uncertainty but can predict the price patterns. The predicted results cannot be 100% accurate but the results show that our application helps in reducing occurrence of losses to a certain extent by providing idea about stock market price pattern. We are collecting stock data from source yfinance. This huge data is used as a record for creating a yfinance stock market analysis. So, the main challenge in front of us is developing a better, efficient stock market pattern detection tool to identify stock patterns effectively and give any suggestion to the viewer on how to proceed further

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STOCK MARKETING PREDICTION USING DEEP LEARNING

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Lane detection plays an important role in intelligent vehicle systems. Therefore, this paper presents a robust road lane marker detection algorithm to detect the left and right lane markers. The algorithm consists of optimization of Canny edge detection and Hough Transform. The system captures images from a front viewing vision sensor placed facing the road behind the windscreen as input. Then a series of image processing is applied to generate the road model. Canny edge detection performs features recognition then followed by Hough Transform lane generation. The algorithm detects visible left and right lane markers on the road based on real-time video processing.

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LANE LINE DETECTION WITH COMPUTER VISION USING ARTIFICIAL INTELLIGENCE

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PREDICTION OF CYBER ATTACKS USING MACHINE LEARNING TECHNIQUE

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To design a recommendation system for the users to recommend the best topics among the users and to develop a system that promotes the interest of the user by recommending them with customized topics. LDA model is used for extracting all the topics of the user. Popular topics are then analysed and extracted. Influence analysis is carried out to find the influenced topics for the users and the topics are classified to positive and negative topics.Those topics are then ranked using SVM algorithm. Finally recommendation of topics are given to the users.

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PERSONALIZED RECOMMENDATION OF TOPIC BY INFLUENCE ANALYSIS USING SUPPORT VECTOR MACHINE ALGORITHM

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Cloud data loss or disruption can occur because of a natural disaster, human error, malicious activity, or other causes. It can damage your reputation, cause client attrition, and lead to unnecessary delays and expenses. Still, most backup systems have been designed and optimized for outdated environments and use cases. That fact, generates frustration over currently backup challenges and leads to a greater willingness to modernize and to consider new technologies. This proposed system set up a flexible data backup operation, using Disaster Backup as a Service (BaaS) solutions, mixing them up with FogDrive local storage system.

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FOG DRIVE DISASTER BACKUP AS A SERVICE FOR CLOUD SERVER USING IOT AND FOG COMPUTING

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In the past decades, there is an increasing interest in predicting markets among economists, policymakers, academics and market makers. The objective of the proposed work is to study and improve the supervised learning algorithms to predict the stock price.Stock Market Analysis of stocks using data mining will be useful for new investors to invest in stock market based on the various factors considered by the software. Stock market includes daily activities like Sensex calculation, exchange of shares. The exchange provides an efficient and transparent market for trading in equity, debt instruments and derivatives. Our aim is to create software that analyses previous stock data of certain companies, with help of certain parameters that affect stock value. We are going to implement these values in data mining algorithms and we will be able to decide which algorithm gives the best result. This will also help us to determine the values that particular stock will have in near future. We will determine the patterns in data with help of machine learning algorithms.

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STOCK MARKET PRICE PREDICTION USING RANDOM FOREST AND SUPPORT VECTOR MACHINE

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The on-demand service system is built based on service-oriented architecture that is going to be a business model through which Normal people can connect with the domestic workers and provide features. Providing services to the people who are in seek for service. Providing jobs to the domestic workers. Allows the administrator to control the entire system with a web enabled back-end user interface. The System consist of two interfaces for the user the web enabled application and an android application for variable access. The On-demand is a system that connects the service providers and people who seek for service. It is based on SOA architecture and also have an advantage of location-based service. Implementation this application, there is no need of much expensive hardware and software, internet connection and a desktop with basic operating system and a browser will be sufficient. The entire system is built for an organization known as passhouse. This system was built in an intention to showcase the efficient utilization of the services which will be very useful for the developers to save time in doing CRUD operations in common language. This can be easily achieved by modifying the data model as per the requirements.

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ON-DEMAND SERVICE SYSTEM USING SOA

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Data de duplication is one of important data compression techniques for eliminating duplicate copies of repeating data, and has been widely used in cloud storage to reduce the amount of storage space and save bandwidth. To protect the confidentiality of sensitive data while supporting de duplication, the convergent encryption technique has been proposed to encrypt the data before outsourcing. To better protect data security, this proposed system makes the first attempt to formally address the problem of authorized data de duplication. Different from traditional de duplication systems, the differential privileges of users are further considered induplicate check besides the data itself. We also present several new de duplication constructions supporting authorized duplicate check in hybrid cloud architecture. Security analysis demonstrates that our scheme is secure in terms of the definitions specified in the proposed security model. As a proof of concept, the proposed work implements a prototype of our proposed authorized duplicate check scheme and conduct test bed experiments using our prototype. The proposed work shows that our proposed authorized duplicate check scheme incurs minimal overhead compared to normal operations.

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IMPROVING ACCESSING EFFICIENCY OF CLOUD STORAGE USING DEDUPLICATION SCHEMES

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Electronic Advertising is one of the most effective ways for business of all sizes to expand their reach, find new customers & diversifly their revenue stream, with so many option available. E-Advertising is advertising that uses the internet and other forms of digital media to help a business promote and sell goods and services. The Purpose of using E-Advetising is to reach a wide range of potential customers by connecting with them over the web. It is also a lot more cost effective as you can fund your advertising with in the boundaries of your own budget.

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E Advertising, Digital Media, Customer.

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Abstract: The Rapid urbanization and population growth have placed significant pressure on public water distribution systems, leading to challenges such as uneven water supply, leakage, unauthorized usage, and inefficient monitoring. Conventional water distribution management relies heavily on manual inspection and periodic measurement, which often fails to provide real-time insights and timely control. To address these limitations, this paper proposes an Intelligent Public Water Distribution Monitoring System using Raspberry Pi, designed to enhance efficiency, transparency, and reliability in public water management. The proposed system employs an Internet of Things (IoT)-based architecture in which Raspberry Pi acts as the central processing unit, interfaced with water flow sensors, ultrasonic water level sensors, and control units such as solenoid valves. These sensors continuously monitor water flow rate, consumption patterns, and storage tank levels in real time. The collected data is processed locally and transmitted to a cloud-based platform for storage, visualization, and analysis. The system is capable of identifying abnormal flow conditions, detecting possible leakages, and monitoring excessive or unauthorized water usage. Alert notifications are generated automatically, enabling authorities to take prompt corrective action.By providing real-time monitoring and intelligent control, the proposed solution significantly reduces water wastage and operational inefficiencies. The system also supports data-driven decision-making for municipal authorities by offering historical data analysis and usage trends. Due to its low cost, scalability, and ease of deployment, the proposed model is suitable for implementation in urban as well as rural public water distribution networks. The results demonstrate that integrating Raspberry Pi-based IoT solutions into water infrastructure can play a vital role in achieving sustainable water management and supporting smart city initiatives.

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Index Terms - Raspberry Pi, Internet of Things (IoT), Smart Water Management, Public Water Distribution System, Water Flow Monitoring, Ultrasonic Level Sensor, Leakage Detection, Cloud-Based Monitoring, Smart City Infrastructure.

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The works introduces a comprehensive image dehazing approach that integrates traditional image processing with advanced deep learning techniques. The proposed algorithm effectively reduces haze effects, significantly enhancing image visibility and clarity. It utilizes the dark channel prior for initial transmission estimation, further refined by a pre-trained neural network, ensuring robust performance under various hazy conditions. The dehazing performance, quantified using the PSNR metric, shows substantial improvements in image quality. The collaboration of refined transmission maps, atmospheric light estimation, and radiance calculation results in high-quality dehazed images, demonstrating the efficacy of this integrated method in overcoming haze-related challenges in imaging.

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dehazing, airlight, transmission map, CNN, Wavelet

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This paper involves designing a smart infant care incubator powered by IoT technology to ensure a safe and nurturing environment for newborns, especially preterm infants. The incubator is equipped with sensors to monitor vital signs like heart rate and oxygen levels, as well as environmental factors such as temperature, humidity, and air quality using IoT connectivity, the system provides real-time data to care giversviaa mobile apporwebplatform, enabling remote monitoring and timely interventions. If conditions deviate from the ide al range, the incubator can automatically adjust settings like heating or ventilation.

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Area-efficient,Lowpower,CSLA,Binarytoexcessoneconverter,Multiplexer.

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Modern society is characterized by the emergence of new cultural features, chief among them the widespread availability of social media. New lifestyle patterns have been brought about by excessive social media use. As a result, ways of communication has changed. These interactions create new power dynamics in which certain people are better and more heard because of their increased visibility, while others who become victims to social media suffer. Thus, it affects our Society in a number of ways, both positively and negatively. The goal of this study was to evaluate both the positive and negative impacts of Social media on Undergraduate college students of Panjab University, Chandigarh.

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Social media, advantages, disadvantages, undergraduate college students.

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The contribution of Agriculture Sector towards State GSDP was near about 20 percent in 2019-20. The livestock and poultry are considered as one of the important agricultural allied activities in the farm households of Assam. The livestock and poultry are the source of milk, meat, egg and manure of rural farming system in Assam. Livestock and poultry sector has immense contribution toward rural household economy, employment, food and nutritional security. The contribution of livestock sector to GSDP is estimated as 7.7%, only second to crop agriculture. Assam has the largest pig population in the country accounting for 17.96% of the country's total pig population. The livestock population in the state is large in numbers but its productivity is very low compared to other parts of the country. In this paper an attempt is made to present the recent status of livestock and poultry sector in the state of Assam.

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Livestock, Poultry, Agriculture, Milk, Egg, Employment etc

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This study examines the multi-layered influence of globalization on the traditional folk performing arts of Assam, including major forms such as Bihu, Ojapali, Bhaona, and Ankiya Naat. These art forms, rooted in agrarian, religious, and communal practices, are integral to Assamese identity. However, with rapid global integration, these traditions are experiencing both revitalization and erosion. The research employs secondary data from academic journals, cultural reports, archival documents, and credible online sources. The results designate that globalization purposes as a ambiguous blade. On one hand, digital platforms like YouTube, Facebook, and Instagram have provided increased visibility, new audiences, and opportunities for cultural exchange and monetization. On the other hand, this exposure often leads to the commodification of folk traditions, diluting their spiritual and social significance. Table-based analysis reveals that while Bihu has successfully adapted through digital dissemination and diaspora engagement, more ritualistic forms like Ojapali and Ankiya Naat remain marginalized and are practiced only by a dwindling number of older performers. Youth engagement trends further highlight the generational gap. While rural youth participate occasionally due to community ties, urban youth are largely disengaged unless the art form is popularized through social media or school-level programs. Motivations have shifted from cultural continuity to digital recognition and entertainment value. Influenced by peer culture, lack of economic incentives, and migration, many youths no longer see folk arts as viable or relevant.

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Globalization, Folk Performing Arts, Assam, Bihu, Ojapali, Bhaona, Ankiya Naat.

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Assam is the gateway of North Eastern Region (NER) of India occupying an area of 78,438 sq. km. The great river Brahmaputra covers 800 km across the length of Assam and virtually dividing the state into two halves. It touches through 19 districts of Assam and gives birth of Chars and Chapories in 14 districts as Barpeta, Bongaigaon, Darrang, Dhemaji, Dhubri, Goalpara, Jorhat Kamrup, Lakhimpur, Morigaon Nagaon, Nalbari, and Sonitpur, Tinsukia. According to the Socio-Economic Survey Report 2002-2003, the total Char-Chaporiareas of Assam consist about 3,60,927 hectares in which 2,42,277 hectares are cultivable and 1,18,650 hectares are uncultivable.The governments of Assam have introduced various measures for socio-economic development of char-chapories. But all these measures have no yield proper result due to various short comings related to their miss-implementation. The proposed study focusses only on status and changing trend of rice cultivation among major food grains production in Assam which completely depends on secondary sources of data. The required data would collect from government publications, economic survey of state government, various journals and books.

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, Alleviation, Char-Chapory, Cultivation, Erosion, Agriculture, Minorities.

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In reality, the wealth of the modern economy no longer depends on physical assets; rather, it depends on intangible intellectual assets. The most crucial component of success in the modern economic era is intellectual capital, which is also essential for maintaining competitive advantage and adding value to the company. Intellectual Capital embodies the intangible assets and resources of a company, such as knowledge, know-how, professional skills and expertise, employees, databases, intellectual properties, technologies, customers, etc., that can benefit a company. It determines its potential to grow in the future when managed and used wisely. Companies believe that intellectual capital disclosure is a good way to improve their relationships with different stakeholders and lessen information asymmetry. The intellectual capital disclosure includes the disclosure of three components of intellectual capital i.e human capital disclosure, structural capital disclosure, and relational capital disclosure. The knowledge incorporated into information technology (IT) systems, the results and products of knowledge conversion, including papers, databases, processes, plans, and the company's intellectual property, as well as all non-human knowledge repositories within a company, are all considered structural capital. This paper is an attempt to understand the different themes of human capital disclosure.

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Intellectual capital, Intellectual capital disclosure, Structural capital disclosure

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The healthcare landscape is evolving rapidly with the integration of advanced technologies like artificial intelligence (AI) and machine learning (ML). Software as a Medical Device (SaMD) stands at the forefront of this transformation, promising groundbreaking innovations in medical diagnosis, treatment, and management. However, along with its potential benefits, SaMD brings forth significant ethical and legal considerations that necessitate comprehensive regulatory oversight. Ensuring patient safety is paramount as SaMD becomes increasingly involved in clinical decision-making. Additionally, safeguarding data privacy and addressing algorithmic transparency and accountability are critical. Effective regulatory frameworks are essential to strike a balance between fostering innovation and protecting patient welfare. By providing clear guidance and standards for SaMD development, validation, and post-market surveillance, policymakers can instill confidence in these technologies' safety and efficacy. This paper aims to explore the ethical and legal implications of SaMD regulation, focusing on key issues such as patient safety, data privacy, and algorithmic accountability. Through an examination of existing regulatory frameworks and emerging best practices, it seeks to offer insights and recommendations for stakeholders across the healthcare ecosystem. By addressing these challenges collaboratively, we can harness the transformative potential of SaMD while upholding ethical standards and patient-centered care.

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Software as a Medical Device (SaMD), Regulatory Frameworks, Ethical Considerations, Legal Implications, Patient Safety, Data Privacy, Algorithmic Accountability

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Vashishtha Narayan Singh a name that one resonated will brilliances and promise in the world of mathematics, is a poignant reminder that of the delicate balance between genius and mental health. His life marked by extraordinary intellectual achievement and a tragic descent into mental illness serves as a cautionary tale of the pressure faced by exception minds and the importance of metal well-being.

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Brilliance, Poignant, Delicate, Genius, Extraordinary, Intellectual, achiement, Cautionary.

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