Volume 12 | Issue 5

 Abstract

The blood cell classification from smear images of peripheral also known as PBS is a crucial step in diagnosing blood-related illnesses such as anemia, leukemia, infection, polycythemia and malignancy. Hematologists regularly utilize a device which zooms to microscopic level to count, shape, and distribute the cells before making a judgment in blood cell-based analysis. Hematology analyzers and flow cytometry give an accurate and precise CBC that identifies and gives the abnormalities in given smear slides of blood. In multiple hospitals, the techniques that are used are costly, least effective in terms of time and are hectic as they are manual. As a result, a reliable, affordable, and automatic method for identifying different sickness through given PBS image is required. The new proposed model automatically does the examination of the provided data, also does in a faster manner. Therefore, in the studied research we have properly and accurately done the classification of images in such a way that the different cells are classified as the WBCs and RBCs. Feature extraction is done to classify the images. These extracted texture features are subsequently inputted into various classifiers, including artificial neural networks (ANN), machines that are SVM and many other model which are in ML and DL. After comparing the performance metrics, it is determined that the logistic regression method is the most appropriate for the task at hand.

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 Keywords

Images of microscopic blood smears, ML, RBC, Feature identification and export, WBC, CNN, Neural Networks.

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 Abstract

The agricultural sector faces significant challenges in terms of transparency, traceability, and operational efficiency within its supply chains. Conventional methods often struggle to provide timely tracking, authentication, and trust among stakeholders. In recent years, blockchain technology has emerged as a promising solution to tackle these challenges. This study investigates the application of blockchain in agricultural supply chains, known as Agrichain. Agrichain utilizes the decentralized and immutable features of blockchain to enhance transparency and operational efficiency across agricultural supply chains. Through distributed ledger technology, Agrichain facilitates secure and transparent data exchange among farmers, distributors, retailers, and consumers. This study delves into the core elements of Agrichain, including smart contracts for automating transactions, blockchain-enabled traceability for verifying product origin and quality, and decentralized data management for improved supply chain transparency. The research underscores Agrichain's potential to transform the agricultural industry by fostering trust, reducing costs, ensuring food safety, and advancing sustainability efforts.

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 Keywords

Agrichain, blockchain, supply chain, solution, transparent, study, fostering, safety, sustainability

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 Abstract

In contemporary democracies, guaranteeing the security and transparency of voting procedures holds paramount importance. Vote Chain, a blockchain- based voting system, addresses these crucial concerns. This paper conducts a thorough review of existing literature regarding the incorporation of blockchain technology into voting systems. By analyzing different algorithms and performance metrics, it assesses the efficacy of Vote Chain in improving the precision and integrity of electoral processes. Furthermore, the paper deliberates on significant challenges and suggests future research avenues to further enhance the capabilities of blockchain-based voting systems.

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 Keywords

Block chain, Smart Contracts, Vote Chain, Meta Mask, Ganache, Online Voting

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 Abstract

Cryptocurrency represents a digital form of currency characterized by electronic transactions, devoid of physical representation. It contrasts with traditional fiat currency, which is typically centralized and subject to thirdparty oversight. The emergence of digital currencies has introduced a decentralized alternative to traditional financial systems, offering users greater autonomy and control over their financial transactions. Despite the absence of physical form, cryptocurrencies hold significant value and have gained traction as viable mediums of exchange. However, the accessibility of cryptocurrencies has the potential to disrupt international relations and financial markets due to their inherent volatility. The fluctuating prices of cryptocurrencies, including Bitcoin, Ripple, Ethereum, and others, pose challenges for investors, traders, and policymakers alike. Among these virtual currencies, Bitcoin protrude as one of the broadly accepted and recognized cryptocurrencies, enjoying widespread adoption across various sectors. Our analysis goals to develop effective prediction models leveraging deep learning techniques, specifically Long Short Term Memory (LSTM) to forecast changes in Bitcoin prices accurately. By utilizing the potential of deep learning algorithmic programs, we seek to examine historical Bitcoin cost data and analyze designs that can inform future price movements. By leveraging machine learning methodologies, we aim to offering valuable perspectives for investors. for investors, researchers, traders, and policymakers looking to traverse changing landscape of cryptocurrency markets with greater confidence and precision.

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 Keywords

Bitcoin , Machine Learning , Electronic , LSTM, Finanace, Trading, Digital currency, Neural Network, Analysis.

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 Abstract

Cryptocurrency stands as a digital representation of value, existing purely in the digital realm, free from any physical form or centralized control. All transactions are made electronically. Cryptocurrency is a valuable asset that transcends traditional notions of physical currency, existing solely in digital formats within decentralized connectivity. Here we highlight the difference between fiat currency, which is decentralized and free of third-party intervention, and the service offered to all virtual currency users. However, access to cryptocurrencies can disrupt international relations and markets due to their volatile prices. There are many virtual currencies such as Bitcoin, Ripple, Ethereum, Ethereum Classic, Litecoin and more. In our research, we focus specifically on Bitcoin, a popular cryptocurrency. Among various virtual currencies, Bitcoin is widely accepted by many organizations, including investors, scholars, traders and legislators. To the best of our capability, our aim is to make effective prediction models based on deep learning, especially Long Short Term Memory (LSTM) and Gated Recurrent Units (GRU), to control Bitcoin price change and achieve its accuracy. Our research involves comparing two real-time deep learning techniques and demonstrating their effectiveness in predicting Bitcoin price.

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 Keywords

Cryptocurrency , Bitcoin , Transactions , Decentralized , LSTM , Finance, Trading, Virtual currency, Forecasting.

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 Abstract

Accurate identification of patients is a pressing issue for many countries in the Asian region. However, accurate patient identification remains the cornerstone of healthcare care and quality. There are several reasons for poor patient identification systems in regional hospitals: Larger hospitals tend to have poor patient management, and clinics exercise a level of financial and personal control that facilitates competition for patient management. system (each department must be responsible for its own bookkeeping). As a result, patients have multiple medical department records and identification numbers. In addition, the lack of a Master Patient Index (MPI) is a standard practice, meaning there is no centralized system for patient identification that cross-references available patient data.

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 Keywords

patients, healthcare, master patient index (MPI), biometric authentication in healthcare, patient records, medical records

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 Abstract

Accurate identification of patients remains not less than a headache in many countries in the sub-Asian region. Nonetheless, accurate patient identification is still essential to providing high-quality, safe healthcare. The following explanations help to explain why patient identification processes in Sub-Asian hospitals are flawed: Larger hospitals tend to have decentralized patient administration because the adoption of a degree of financial and managerial autonomy for clinical departments has encouraged the proliferation of redundant administrative patient management systems (every department wanting to handle its own bookkeeping). Patients so obtain ID numbers and medical records that are department-specific. Furthermore, it should be noted that the lack of a master patient index (MPI) is a general rule, meaning that there are no central patient identification systems that make use of the department's current patient information.

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patients, healthcare, master patient index (MPI), biometric authentication in healthcare, patient records

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

PCOS is a common endocrine condition that affects women who are fertile. It is typified by irregular period, ovarian cysts, and assesses. In order to mitigate the potential long-lasting health issues linked with... PCOS, premature discovery and intervention are essential. In this study, WeCare--a thorough women's wellbeing guide that incorporates front-line technologies for PCOS detection--is introduced. WeCare provides a novel method for the prompt and reliable diagnosis of PCOS by analyzing medical imaging data, including sonography scans and lumbar MRI images, by utilizing Convolutional Neural Network (CNN) algorithms. WeCare improves access to healthcare by utilizing deep learning to enable early intervention, individualized treatment programs, and better symptom management for PCOS By combining advanced technology with healthcare expertise, this interdisciplinary approach enables women to proactively manage their reproductive health and overall well-being.

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Convolutional Neural Network (CNN), Diagnosis, Medical Imaging, Early Intervention, Personalized Treatment, Reproductive Health, Polycystic Ovary Syndrome Detection, Deep Learning- based Hormone Analysis, PCOS Diagnosis Algorithm

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 Abstract

In institutions with a high student population, manually creating schedules takes a lot of effort and frequently leads to scheduling issues, where teachers teach multiple classes at once or where classes compete with one another over timing or space. Numerous limitations and problems with the technology arise from this manual procedure. The organization's inability to meet demands in a timely manner and the possibility of inaccurate results are mostly attributable to frequent human errors that are challenging to avoid in such procedures. Our suggestion is to create an automated mechanism in order to address these problems. The Automatic Timetable Generator system would receive a variety of inputs, including information on the faculty, students, and subjects, and use this information to create a workable schedule that makes the most use of all available resources and best fits the given constraints or college policies. An automated system called the Adaptive Timetable Generator creates timetables based on user-provided data. Gathering information on the branch, semester, subjects, laboratories, and total number of periods is one of the application's primary needs. Students must select their electives from a list of subjects that may contain both core and elective courses. After that, the application creates the schedule based on the parameters.

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Automated, time-table, constraints, college, clashes.

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 Abstract

To streamline and expedite the process of contributing to charities, a software project known as the Donation System was developed. This method acts as a link between donors and recipients in an increasingly digital environment, guaranteeing an open and effective approach for helping the underprivileged. Donors can examine a variety of charity organizations, track the impact of their efforts, and make online contributions thanks to the system. Beneficiaries benefit from the system's assistance in efficiently managing and allocating donations. By working together on this initiative, we hope to improve the philanthropic ecosystem as a whole and encourage a culture of giving while improving the lives of people in need. The Helping Hand Donation System (HHDS) is an all-inclusive platform created to make charity donations and aid to underprivileged people and communities easier. This method attempts to close the gap between help providers and recipients by offering an easy-to-use interface for sending money and allocating aid efficiently. To optimize its effects and guarantee sustainability, accountability, and openness, the HHDS integrates a number of characteristics and capabilities. The goal of the HHDS design and development phase is to create a platform that is easy to use and suitable for a wide variety of users. This provides functions for tracking donations, processing secure payments, and reporting. To guarantee that everyone who could donate or benefit from the system may do so, special consideration is given to accessibility and inclusivity.

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 Keywords

Donation, Charitable Organization, Donors, Beneficiary, Android

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In recent years, blockchain technology has gained considerable recognition due to its capacity to revolutionize numerous sectors, agriculture included. This research paper delves into the integration of blockchain in agricultural supply chains, referred to as Agrichain, to address challenges related to transparency, traceability, and operational efficiency. Agrichain leverages blockchain's decentralized and immutable nature to enhance transparency and trust among stakeholders in agricultural supply chains. Through smart contracts, Agrichain automates transactions, reduces costs, and ensures the execution of predefined rules, enhancing efficiency and reliability. Blockchain-based traceability in Agrichain enables real- time tracking of product provenance, quality, and sustainability, empowering consumers with accurate and verifiable information. Decentralized data management promotes secure data exchange, enhances visibility across the supply chain, and empowers informed decision- making based on data analysis. The inherent security features of blockchain technology, such as cryptographic hashing and consensus mechanisms, ensure data integrity, minimize fraud risks, and strengthen cybersecurity across the supply chain.

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AgriChain Innovations: Empowering Agricultural Management with Blockchain Technology

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 Abstract

In contemporary educational settings, examinations can be broadly classified into two categories: objective and subjective. While competitive exams commonly adopt the multiple-choice question format, which can be conveniently administered and evaluated online, subjective exams like board exams present a different challenge. Due to their nature, they cannot be effectively conducted through computerized means. Consequently, there is a growing need to integrate Artificial Intelligence (AI) into online examination systems to address this issue [1]. By leveraging AI, the evaluation of subjective answers could be significantly streamlined, leading to faster and more accurate results. Our proposed system aims to replicate the assessment process carried out by human evaluators, ensuring reliability and consistency. This innovative approach holds immense promise for educational institutions seeking to enhance the efficiency of their assessment procedures.

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 Keywords

Automated answer verifier, answer verifier, theory answer checker, matching answers

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 Abstract

Web- grounded training and placement cell operation is a major step towards automating largely homemade and tedious tasks in the training and placement department. This provides a platform with all the necessary pupil information to match the requirements of an accurate pupil profile and enterprise. The TnP is developed to maintain the details of pupil information, trace the details of pupil also maintain the information about the company vacuity. The goal of creating the Placement Management System was to capture companies and scholars by limiting similar large databases to specific classes of scholars or companies. The system provides the capability to view particular and academic information for both scholars and companies, search for eligible scholars and companies, and also allows directors to fit and cancel records. The main purpose of this design is to give friendly access to its druggies, similar as scholars, apprentice and externship officers, or university staff. scholars simply enter the needed data into the system and TPO can fluently recoup the matching pupil data they need. As this is a completely automated system, it saves a lot of mortal trouble and saves both the pupil and TPO a lot of time in submitting and searching for the needed data. This system can also be used as a central depository to manage enjoy all data of pupil's academic details.

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 Keywords

TPO (Training Placement Officer), TnP (Training and Placement Cell).

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Web- grounded preparing and situation cell operation could be a major step towards automating to a great extent hand crafted and monotonous assignments within the preparing and arrangement division. This gives a stage with all the vital understudy data to coordinate the prerequisites of an precise understudy profile and undertaking. The TnP is created to preserve the subtle elements of understudy data, follow the subtle elements of understudy too keep up the data almost the company vacuity. The objective of making the Situation Administration Framework was to capture companies and researchers by restricting comparative huge databases to particular classes of researchers or companies. The system provides the capability to see particular and scholarly data for both researchers and companies, seek for qualified researchers and companies, conjointly permits executives to fit and cancel records. The most reason of this plan is to allow inviting get to to its druggies, similar as researchers, disciple and externship officers, or college staff. researchers essentially enter the required information into the framework and TPO can easily recover the coordinating student information they require. As typically a totally mechanized framework, it spares a part of mortal inconvenience and saves both the understudy and TPO a part of time in submitting and searching for the required information. This framework can moreover be utilized as a central store to oversee appreciate all information of pupil's scholastic points of interest.

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TPO (Training Placement Officer), TnP (Training and Placement Cell).

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 Abstract

Presently, the focus on security intensifies owing to the widespread utilization of the internet. Correspondingly, the surge in internet usage has led to an increase in the daily exchange of data. This upsurge in data exchange poses a potential risk of deceit by hackers. An effective strategy to tackle this issue is Steganography. Steganography involves the covert embedding of confidential information within harmless cover files, rendering the detection of the hidden data challenging. This study delves into video Steganography, a technique wherein data is concealed within video frames. It proposes a dual-layered security strategy, employing both Steganography and cryptography. Initially, the data undergoes encryption using cryptographic algorithms, fol- lowing which the encrypted data is integrated into video frames. The embedding method employed is LSB coding, known for its simplicity and efficacy in concealing large amounts of data.

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 Keywords

Steganography, Multimedia Security, Video Steganography, LSB Coding, Adaptive Embedding, Content Au- thentication, Copyright Protection, Covert Communication

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In today's digital age, where the internet is widely used, ensuring security has become a top priority. As internet usage continues to soar, the amount of data exchanged daily has also surged, presenting a growing risk of exploitation by malicious actors. One effective strategy to address this growing concern is the adoption of Steganography, a technique used to hide secret information within seemingly innocent files. Specifically, this paper delves into the realm of video Steganography, a method wherein data is concealed within the frames of videos, offering an additional layer of security. By combining Steganography with cryptography, this approach provides a dual-layered de- fense mechanism against potential threats. Through encryption using cryptographic algorithms followed by the embedding of encrypted data into video frames using LSB coding, this method ensures both simplicity and efficiency in safeguarding large volumes of sensitive information.

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Steganography, Multimedia Security, Video Steganography, LSB Coding, Adaptive Embedding, Content Au- thentication, Copyright Protection, Covert Communication

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Many more people are seeking for bank loans as a result of the growth in the banking industry. These loans cannot all be approved. Gains from loans are what bank assets primarily make revenue from. The goal of banks is to allocate their resources towards secure clientele. Even though loans are approved by many banks these days following extensive verification and validation procedures, there is never a guarantee that the chosen consumer will be secure. As a result, it's critical that the banking industry use a variety of strategies to identify clients who make their loan payments on schedule. The random forest technique is used in this report to classify the data. Using a training dataset, the Random Forests method creates a model. This model is then applied to test data, yielding the desired result. Many more people are seeking for bank loans as a result of the growth in the banking industry. These loans cannot all be approved. Gains from loans are what bank assets primarily make revenue from. The goal of banks is to allocate their resources towards secure clientele.

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outlier, Prediction, loan, component, Overfitting, Safe, Bank loans, Transform, machine learning

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In our monetary system, banks have various things to sell yet head sort of income of any banks is on its credit line. A bank's advantage or a setback relies by and large upon credits for instance whether the clients are dealing with the development or defaulting. By anticipating the development defaulters, the bank can lessen its Non Performing Assets. This makes the examination of this characteristic essential. Past examination in this time has shown that there are such endless strategies to focus on the issue of controlling Development default. Be that as it may, as the right expectations are vital for the boost of benefits, it is crucial for concentrate on the idea of the various strategies and their correlation.[1] A vital approach in prescient examination is utilized to concentrate on the issue of anticipating credit defaulters: The Calculated relapse model. Strategic Relapse models have been performed and the various proportions of exhibitions are registered.

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outlier, Prediction, loan, component, Overfitting, Safe, Bank loans, Transform

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Creative Commons Attribution 4.0 and The Open Definition

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This document suggests a manual method of moving the cursor position without requiring for an electronic device. On the other hand, various hand motions will be used to do tasks like clicking and dragging objects. A webcam is all that will be needed as an input device for the proposed system. The PC's camera will perceive different hand motions and utilize that data to move the mouse, or cursor, in light of the developments. It will even utilize distinct gestures to click the left and right buttons. The These models hold the key to significantly increasing the usability of such computer vision solutions by simulating the swaying motion of human hand motions. Numerous technologies are continually changing in the technological landscape of today. The idea is to imitate mouse functionalities on a screen without the requirement for any equipment by utilizing hand and finger signals, an interaction known as motion acknowledgment. This essay aims to reduce human-computer connection and dependence on technology in light of the COVID-19 pandemic. These results will eventually motivate further research and boost the use of virtual environments. These limitations are absent from the proposed period, which might instead rely on gesture recognition.

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 Keywords

Gesture Control Virtual Mouse, Virtual Mouse, Hand Gestures, OpenCV

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 Abstract

Effective waste management is essential for sustainable urban development, necessitating innovative solutions to tackle waste accumulation and environmental pollution. Our project focuses on developing and implementing a "Smart Dustbin" system to optimize waste collection processes. The primary goal is to design and deploy a network of intelligent dustbins capable of autonomously monitoring waste levels and transmitting real-time data signals with location information. By utilizing ultrasonic sensors and microcontroller units, these smart dustbins continuously monitor fill levels, enhancing the efficiency of waste collection operations. Key features of the system include wireless communication modules for real-time updates to a central monitoring station and the integration of GPS technology for precise location tracking. This facilitates route optimization and resource allocation for waste collection fleets. A significant innovation in our project is the development of a user-friendly dashboard interface, allowing municipal authorities to visualize and analyze waste collection data in real time. Data analytics algorithms enable the identification of high-traffic areas, prediction of waste generation patterns, and optimization of collection routes. The smart dustbin system offers tangible benefits for municipalities and residents by reducing overflowing bins, littering, and environmental pollution. It also optimizes waste collection routes, reducing fuel consumption and mitigating carbon emissions

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SMART DUSTBIN MONITORING SYSTEM

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