Kamal Acharya

The Internet of Things refers to connecting things and people through internet, it has imposed itself as the New business practices in different sectors. To make quick and efficient response in real time, IoT enhances the way and provides emergency managers with the necessary information and communication to make use of those assets. In this paper it is proposed that a quick response for fire hazards is evaluated and examined by using IoT based model. Fire is one of the major reasons of accidental deaths in the world. To implement this proposed system a low-cost Wi-Fi module, gas detection sensor, Flame detection sensor, buzzer to alert and temperature sensors are used.

The design and operational principle of the digital calendar and digital clock is the subject of this thesis. The system as realized in this book is made up of six units. The power supply unit supplies the required regulated voltage to the appropriate connections of the overall circuit. The micro controller controls the general operation of the circuit; all the other units are interfaced to it. The input unit is activated by pressing the keypad (buttons) unit to call up the subroutine program that controls the set date, month, year and time with alarm instructions. The decoder with the aid of the micro controller executes the instruction codes, which are transmitted to the light emitting diode that corresponds to the actual day that is to display.

The Internet of Things refers to connecting things and people through internet, it has imposed itself as the New business practices in different sectors. To make quick and efficient response in real time, IoT enhances the way and provides emergency managers with the necessary information and communication to make use of those assets. In this paper it is proposed that a quick response for fire hazards is evaluated and examined by using IoT based model. Fire is one of the major reasons of accidental deaths in the world. To implement this proposed system a low-cost Wi-Fi module, gas detection sensor, Flame detection sensor, buzzer to alert and temperature sensors are used.

The main objective of this paper is to find the best model to predict the value of thestock market. During the process of considering various techniques and variables thatmust be taken into account, we found out that techniques like random forest, supportvector machine were not exploited fully. In, this paper we are going to present andreview a more feasible method to predict the stock movement with higher accuracy.The first thing we have taken into account is the dataset of the stock market pricesfrom previous year. The dataset was pre-processed and tuned up for real analysis.Hence, our paper will also focus on data preprocessing of the raw dataset. Secondly,after pre- processing the data, we will review the use of random forest, support vectormachine on the dataset and the outcomes it generates. In addition, the proposed paperexaminesthe use of the prediction system in real- world settings and issues associatedwith the accuracy of the overall values given. The paper also presents a machinelearning model to predict the longevity of stock in a competitive market. Thesuccessful prediction of the stock will be a great asset for the stock market institutionsand will provide real-life solutions to the problems that stock investors face.

The design and operational principle of the digital calendar and digital clock is the subject of this thesis. The system as realized in this book is made up of six units. The power supply unit supplies the required regulated voltage to the appropriate connections of the overall circuit. The micro controller controls the general operation of the circuit; all the other units are interfaced to it. The input unit is activated by pressing the keypad (buttons) unit to call up the subroutine program that controls the set date, month, year and time with alarm instructions. The decoder with the aid of the micro controller executes the instruction codes, which are transmitted to the light emitting diode that corresponds to the actual day that is to display.

The Internet of Things refers to connecting things and people through internet, it has imposed itself as the New business practices in different sectors. To make quick and efficient response in real time, IoT enhances the way and provides emergency managers with the necessary information and communication to make use of those assets. In this paper it is proposed that a quick response for fire hazards is evaluated and examined by using IoT based model. Fire is one of the major reasons of accidental deaths in the world. To implement this proposed system a low-cost Wi-Fi module, gas detection sensor, Flame detection sensor, buzzer to alert and temperature sensors are used.

Skin diseases are hazardous and often contagious, especially melanoma, eczema, and impetigo. These skin diseases can be cured if detected early. The fundamental problem with it is, only an expert dermatologist is able to detect and classify such disease. Sometimes, the doctors also fail to correctly classify the disease and hence provide inappropriate medications to the patient. Our paper proposes a skin disease detection method based on Image Processing and Deep Learning Techniques. Our system is mobile based so can be used even in remote areas. The patient needs to provide the image of the infected area and it is given as an input to the application. Image Processing and Deep Learning techniques process it and deliver the most accurate output. In this paper, we present a comparison of two different approaches for realtime skin disease detection algorithm based on accuracy. We have compared Navies Bias Classifier. The results of real-time testing are presented.

The main objective of this paper is to find the best model to predict the value of thestock market. During the process of considering various techniques and variables thatmust be taken into account, we found out that techniques like random forest, supportvector machine were not exploited fully. In, this paper we are going to present andreview a more feasible method to predict the stock movement with higher accuracy.The first thing we have taken into account is the dataset of the stock market pricesfrom previous year. The dataset was pre-processed and tuned up for real analysis.Hence, our paper will also focus on data preprocessing of the raw dataset. Secondly,after pre- processing the data, we will review the use of random forest, support vectormachine on the dataset and the outcomes it generates. In addition, the proposed paperexaminesthe use of the prediction system in real- world settings and issues associatedwith the accuracy of the overall values given. The paper also presents a machinelearning model to predict the longevity of stock in a competitive market. Thesuccessful prediction of the stock will be a great asset for the stock market institutionsand will provide real-life solutions to the problems that stock investors face.

The Internet of Things refers to connecting things and people through internet, it has imposed itself as the New business practices in different sectors. To make quick and efficient response in real time, IoT enhances the way and provides emergency managers with the necessary information and communication to make use of those assets. In this paper it is proposed that a quick response for fire hazards is evaluated and examined by using IoT based model. Fire is one of the major reasons of accidental deaths in the world. To implement this proposed system a low-cost Wi-Fi module, gas detection sensor, Flame detection sensor, buzzer to alert and temperature sensors are used.

In the evolving landscape of talent acquisition, organizations face increasing challenges in efficiently identifying the right candidates from large pools of applicants. Traditional recruitment processes often rely on manual resume screening, which is not only time-consuming and resource-intensive but also prone to human bias and inconsistency. The TalentMatch project introduces an AI-powered recruitment platform designed to revolutionize this process by automating and optimizing resume-to-job matching using advanced Natural Language Processing (NLP) and Machine Learning (ML) techniques. The core objective of TalentMatch is to intelligently parse, analyze, and rank candidate resumes against job descriptions by extracting key information such as skills, qualifications, work experience, education, certifications, and contextual relevance to the role. The system utilizes semantic analysis to understand the meaning behind unstructured text data, enabling it to match candidates not just based on keyword overlap, but on true contextual alignment with job requirements. By converting unstructured resumes and job postings into structured data representations, the platform enables a fair, consistent, and data-driven approach to candidate evaluation. The platform architecture comprises a modular backend built with Express and TypeScript, which handles data ingestion, resume parsing, and job description analysis. The intelligent matching engine employs a combination of NLP techniques, such as named entity recognition (NER), word embeddings, vector similarity, and custom scoring algorithms to determine candidate-job fit. On the frontend, a responsive React application provides an intuitive interface for recruiters to view, filter, and interact with ranked candidate lists. The interface also supports customizable scoring metrics, enabling recruiters to prioritize specific attributes like technical skills, years of experience, or educational background based on the unique needs of a role. This report outlines the end-to-end development of TalentMatch, from the initial problem identification and design considerations to implementation, deployment, and performance evaluation. Special focus is given to the use of OpenAI's language models to enhance semantic understanding, as well as the integration of feedback mechanisms that allow for continuous improvement of the ranking system based on recruiter inputs. Extensive testing with real-world job descriptions and anonymized resumes demonstrates the system’s ability to significantly reduce screening time while maintaining or improving the quality of candidate selection. Additionally, the report explores ethical considerations, such as bias mitigation and data privacy, ensuring that the AI system supports fair hiring practices.

The project is a web based application where users can get instant electricity bill and pay them online via credit card. The system automates the conventional process of paying electricity bill by visiting the place. Users have to stand in queue for paying bill and wait for their turn. The process is tiresome and time consuming. They even have to wait for the bill being delivered to their place which sometimes can be delivered late by the delivery boy. Hence the system is developed to automate the electricity bill calculation and payment for user convenience.

In todays’ world advancement in sophisticated scientific techniques is pushing further the limits of human outreach in various fields of technology. One such field is the field of character recognition commonly known as OCR (Optical Character Recognition). In this fast paced world there is an immense urge for the digitalization of printed documents and documentation of information directly in digital form. And there is still some gap in this area even today. OCR techniques and their continuous improvisation from time to time is trying to fill this gap. This project is about devising an algorithm for recognition of hand written characters also known as HCR (Handwritten Character Recognition) leaving aside types of OCR that deals with recognition of computer or typewriter printed characters. A novel technique is proposed for recognition English language characters using Artificial Neural Network including the schemes of feature extraction of the characters and implemented. The persistency in recognition of characters by the AN network was found to be more than 90% of times.

The project is concerned with identifying a solution that could be used to detect and filter out sites containing fake news for purposes of helping users to avoid being lured by clickbaits. It is imperative that such solutions are identified as they will prove to be useful to both readers and tech companies involved in the issue.

The Internet of Things refers to connecting things andpeople through internet, it has imposed itself as the Newbusiness practices in different sectors. To make quick andefficient response in real time, IoT enhances the way andprovides emergency managers with the necessary informationand communication to make use of those assets.In this paper it is proposed that a quick response for firehazards is evaluated and examined by using IoT based model.Fire is one of the major reasons of accidental deaths in the world.To implement this proposed system a low-cost Wi-Fi module,gas detection sensor, Flame detection sensor, buzzer to alertand temperature sensors are used.

"Worldwide solar radiation is a basic parameter for the plan andoperation frameworks. Long-standing records of worldwide solar radiation data are not accessible in many places because of the cost and maintenance of the measuring instruments. Sun based radiation expecta- tion contains a incredible significance in power generation from sun based energy and makes a difference to measure photovoltaic control frameworks. With this context, we have utilized solar radiation dataset extracted from UCI Machine Learning. The forecasting of solar radiation are attained in four ways. Firstly, the data set is analyzed and preprocessed with Feature Scaling and missing values. Secondly, the correlation of the features is done and the relation of each features are visualized."

The Internet of Things refers to connecting things andpeople through internet, it has imposed itself as the Newbusiness practices in different sectors. To make quick andefficient response in real time, IoT enhances the way andprovides emergency managers with the necessary informationand communication to make use of those assets.In this paper it is proposed that a quick response for firehazards is evaluated and examined by using IoT based model.Fire is one of the major reasons of accidental deaths in the world.To implement this proposed system a low-cost Wi-Fi module,gas detection sensor, Flame detection sensor, buzzer to alertand temperature sensors are used.

"Worldwide solar radiation is a basic parameter for the plan andoperation frameworks. Long-standing records of worldwide solar radiation data are not accessible in many places because of the cost and maintenance of the measuring instruments. Sun based radiation expecta- tion contains a incredible significance in power generation from sun based energy and makes a difference to measure photovoltaic control frameworks. With this context, we have utilized solar radiation dataset extracted from UCI Machine Learning. The forecasting of solar radiation are attained in four ways. Firstly, the data set is analyzed and preprocessed with Feature Scaling and missing values. Secondly, the correlation of the features is done and the relation of each features are visualized."

Skin diseases are hazardous and often contagious, especially melanoma, eczema, and impetigo.These skin diseases can be cured if detected early. The fundamental problem with it is, only an expertdermatologist is able to detect and classify such disease. Sometimes, the doctors also fail to correctlyclassify the disease and hence provide inappropriate medications to the patient. Our paper proposes a skindisease detection method based on Image Processing and Deep Learning Techniques. Our system is mobilebased so can be used even in remote areas. The patient needs to provide the image of the infected area andit is given as an input to the application. Image Processing and Deep Learning techniques process it anddeliver the most accurate output. In this paper, we present a comparison of two different approaches forrealtime skin disease detection algorithm based on accuracy. We have compared Navies Bias Classifier.The results of real-time testing are presented.

The purpose of the project entitled as “Smart Health Prediction” is to develop software which is user friendly simple, fast, and cost – effective. It deals with the collection of patient’s information, diagnosis details, etc. Traditionally, it was done manually The main function of the system is register and store patient details and doctor details and retrieve these details as and when required, and also to manipulate these details meaningfully System input contains patient details, diagnosis details, while system output is to get these details on to the screen. The Smart Health Prediction can be entered using a username and password. It is accessible either by an administrator. Only they can add data into the database. The data can be retrieved easily.The data are well protected for personal use and makes the data processing very fast. This is the document of the Project proposal for developing a health care system. This system is fully updated and we had provide some new things in it. The project aimed to build a fully functional system in order to achieve the efficiency in faster heath treatment and online consultation system. The overall mission of system development is to make the primary treatment quickly and easily complete the Online Consultation System.

Aim of this project is to create doctor patient handling management system that will help doctors in their work and will also help patients to book doctor appointments and view medical progress. The system allows doctors to manage their slots online. Patients are allowed to book empty slots online and those slots are reserved in their name. The system manages the appointment data for multiple doctors in specific areas of specialty at various days and times. Each time a user visits a doctor his/her medical entry is stored in the database by that specific doctor. Next time a user logs in he may view his/her entire medical history as and when needed. At the same time a doctor may view patient’s previous medical history while the patient visits him. The system also consists of Blood donor module. This module allows for Blood donation registration as well as Blood group search. The module is designed to help urgent Blood requirements through easy/instant searches.

The GPS (Global Positioning System) has been used to monitor the transport. The vehicle should be installed with live GPS tracker. The details of the vehicle and count of the passengers is tracked in the app using the fingerprint sensors which is used to make a check-in facility in the Vehicle. Passengers should make a check-in while boarding the vehicle. Then should check-out when they leave the vehicle. The main concept behind this project is that the GPS tracker and fingerprint is attached inside the vehicle the GPS is used to detect the current, then the sensor used to make a check-in and out tasks after verifying the fingerprint the details is shared to the sensors to the app. The app helps the makes the clear view of the passenger check-in and out exact time, date and location. Mainly this app is made for the security purpose for the details of the passengers whether they are in the vehicle or else not. Or whether they were dropped at different destination point. If a passenger from a different vehicle board’s different vehicle of the same management. It allows him to do the check-in but it shows the alert message like this passenger is from this specified vehicle and its number.

Contrasted with the past, improvements in PC and correspondence innovations have given broad and propelled changes. The use of new innovations give incredible advantages to people, organizations, and governments, be that as it may, messes some up against them. For instance, the protection of significant data, security of put away information stages, accessibility of information and so forth. Contingent upon these issues, digital fear based oppression is one of the most significant issues in this day and age. Digital fear, which made a great deal of issues people and establishments, has arrived at a level that could undermine open and nation security by different gatherings, for example, criminal association, proficient people and digital activists. Along these lines, Intrusion Detection Systems (IDS) has been created to maintain a strategic distance from digital assaults. Right now, learning the bolster support vector machine (SVM) calculations were utilized to recognize port sweep endeavors dependent on the new CICIDS2017 dataset with 97.80%, 69.79% precision rates were accomplished individually.

Data security is the essential in the today’s world of internet and networking. In any organization information is critical. In today’s world people are ready to spent thousands and lacks of money in order to ensure high level of information security. In spite of spending such a huge amount, still the objective of securing the information is not achieved as the data some how gets in the hands of hacker. As the technology for securing the data is advancing, hackers are also keeping pace with this technology. Hackers now make use of certain algorithm or other techniques to decode the data encoded by the senders. One of the ways to ensure security is to ensure that data is not visible to the hacker. This can be done by hiding the message itself behind some other objects. Here we are achieving this data security concept through the technique of Steganography.

The main objective of the “Blood Bank management System” all the details in the Blood Bank’sprocess. This project has some tasks to maintain the Blood Bank through computerization. Using this blood bank system people can search blood group available which they are needed. They check it on using our blood bank management website. If in case blood group is not available in blood bank they can also contact numbers of the persons who has the same blood group he is need. And he can request the person to done the blood for saving someone life. The Project describes the smart Blood Bank management system. This report will help you to know in deep the actual work that has been done as a team work. The main objective of this application is to automate the complete operations of the blood bank. They need to maintain hundreds of thousands of records. Also searching should be very faster, so they can find required details instantly. Main objective is to create a system which helps them to complete their work faster in simple way by using computer not the oldest way which is used paper. Also our project contains updated information and many things else.

Machine learning is a subfield of artificial intelligence (AI). The goal of machine learninggenerally is to understand the structure of data and fit that data into models that can beunderstood and utilized by people. Although machine learning is a field within computerscience, it differs from traditional computational approaches. In traditional computing,algorithms are sets of explicitly programmed instructions used by computers to calculate orproblem solve. Machine learning algorithms instead allow for computers to train on data inputsand use statistical analysis in order to output values that fall within a specific range. Because ofthis, machine learning facilitates computers in building models from sample data in order toautomate decision making processes based on data inputs.

This paper presents a Web-based augmented reality (AR) detector thatallows users to identify and locate nearby points of interest using their smartphone.The system uses a combination of GPS data and visual recognition algorithms todetermine the user's location and overlay relevant information on the user's screen.The AR interface provides an intuitive and fun way to interact with the environment,making it ideal for outdoor settings such as parks, tourist attractions, and historic sites.The system is designed to be accessible to a variety of users, regardless of technicalexperience, and can be easily integrated into existing websites or mobile applications.The results of the user study show the effectiveness of the system in improving theuser's ability to navigate and find points of interest nearby. Overall, this web-based ARlocation locator is an important step in the development of mobile AR web-basedapplications that harness the power of the Web to provide innovative and immersiveexperiences to users.

"Cloud storage systems are widely deployed in the world, and many people use them to download and upload their personal stuff like videos, text documents, images, etc. Nowadays many private firms, company\u2019s, governments, and the military move their databases to cloud storage. However, a significant question is, can users trust the media services provided by the media cloud service providers? Many traditional security approaches are proposed to secure the data exchange between users and the media cloud. However, the problem comes to military users if scientist develop a new weapon for military and he want to send a launching code to military admirals \/chiefs through cloud, how he can trust cloud that he\u2019s codes will be safely delivered to admirals. Nowadays cloud storage can easily be cracked by hackers and gain information of military weapons and confidential secrets. It could be dangerous if they sold this information to terrorists or rival countries. In this article, we propose to use steganography, watermarking, image encryption and visual cryptography schemes to protect military weapons data in clouds. steganography allows users to hide the weapons launch code in image captcha. Visual cryptography shares the image captcha in shares which depend on the number of people in a group in the military. image encryption will apply on each share of captcha. After this watermarking is applied on each share for authentications between users and cloud. For receiving the launch code receivers have to form de-watermarking, image decryption then visual cryptography to get captcha and launch code. Our studies show that the proposed approach achieves good security performance and securing the future of country"

In the evolving landscape of talent acquisition, organizations face increasing challenges inefficiently identifying the right candidates from large pools of applicants. Traditionalrecruitment processes often rely on manual resume screening, which is not onlytime-consuming and resource-intensive but also prone to human bias and inconsistency. TheTalentMatch project introduces an AI-powered recruitment platform designed torevolutionize this process by automating and optimizing resume-to-job matching usingadvanced Natural Language Processing (NLP) and Machine Learning (ML) techniques.The core objective of TalentMatch is to intelligently parse, analyze, and rank candidateresumes against job descriptions by extracting key information such as skills, qualifications,work experience, education, certifications, and contextual relevance to the role. The systemutilizes semantic analysis to understand the meaning behind unstructured text data, enablingit to match candidates not just based on keyword overlap, but on true contextual alignmentwith job requirements. By converting unstructured resumes and job postings into structureddata representations, the platform enables a fair, consistent, and data-driven approach tocandidate evaluation.The platform architecture comprises a modular backend built with Express and TypeScript,which handles data ingestion, resume parsing, and job description analysis. The intelligentmatching engine employs a combination of NLP techniques, such as named entityrecognition (NER), word embeddings, vector similarity, and custom scoring algorithms todetermine candidate-job fit. On the frontend, a responsive React application provides anintuitive interface for recruiters to view, filter, and interact with ranked candidate lists. Theinterface also supports customizable scoring metrics, enabling recruiters to prioritize specificattributes like technical skills, years of experience, or educational background based on theunique needs of a role.

The purpose of the project entitled as “Smart Health Prediction” is to develop software which is user friendly simple, fast, and cost – effective. It deals with the collection of patient’s information, diagnosis details, etc. Traditionally, it was done manually The main function of the system is register and store patient details and doctor details and retrieve these details as and when required, and also to manipulate these details meaningfully System input contains patient details, diagnosis details, while system output is to get these details on to the screen. The Smart Health Prediction can be entered using a username and password. It is accessible either by an administrator. Only they can add data into the database. The data can be retrieved easily.The data are well protected for personal use and makes the data processing very fast. This is the document of the Project proposal for developing a health care system. This system is fully updated and we had provide some new things in it. The project aimed to build a fully functional system in order to achieve the efficiency in faster heath treatment and online consultation system. The overall mission of system development is to make the primary treatment quickly and easily complete the Online Consultation System.

Machine learning is a subfield of artificial intelligence (AI). The goal of machine learning generally is to understand the structure of data and fit that data into models that can be understood and utilized by people. Although machine learning is a field within computer science, it differs from traditional computational approaches. In traditional computing, algorithms are sets of explicitly programmed instructions used by computers to calculate or problem solve. Machine learning algorithms instead allow for computers to train on data inputs and use statistical analysis in order to output values that fall within a specific range. Because of this, machine learning facilitates computers in building models from sample data in order to automate decision making processes based on data inputs.

Worldwide solar radiation is a basic parameter for the plan andoperation frameworks. Long-standing records of worldwide solar radiationdata are not accessible in many places because of the cost and maintenance of the measuring instruments. Sun based radiation expecta- tioncontains a incredible significance in power generation from sun basedenergy and makes a difference to measure photovoltaic controlframeworks. With this context, we have utilized solar radiation datasetextracted from UCI Machine Learning. The forecasting of solar radiation are attained in four ways. Firstly, the data set is analyzed andpreprocessed with Feature Scaling and missing values. Secondly, thecorrelation of the features is done and the relation of each features arevisualized.

Data security is the essential in the today’s world of internet and networking. In any organization information is critical. In today’s world people are ready to spent thousands and lacks of money in order to ensure high level of information security. In spite of spending such a huge amount, still the objective of securing the information is not achieved as the data some how gets in the hands of hacker. As the technology for securing the data is advancing, hackers are also keeping pace with this technology. Hackers now make use of certain algorithm or other techniques to decode the data encoded by the senders. One of the ways to ensure security is to ensure that data is not visible to the hacker. This can be done by hiding the message itself behind some other objects. Here we are achieving this data security concept through the technique of Steganography.

This paper presents a Web-based augmented reality (AR) detector that allows users to identify and locate nearby points of interest using their smartphone. The system uses a combination of GPS data and visual recognition algorithms to determine the user's location and overlay relevant information on the user's screen. The AR interface provides an intuitive and fun way to interact with the environment, making it ideal for outdoor settings such as parks, tourist attractions, and historic sites. The system is designed to be accessible to a variety of users, regardless of technical experience, and can be easily integrated into existing websites or mobile applications. The results of the user study show the effectiveness of the system in improving the user's ability to navigate and find points of interest nearby. Overall, this web-based AR location locator is an important step in the development of mobile AR web-based applications that harness the power of the Web to provide innovative and immersive experiences to users.

This paper presents a Web-based augmented reality (AR) detector that allows users to identify and locate nearby points of interest using their smartphone. The system uses a combination of GPS data and visual recognition algorithms to determine the user's location and overlay relevant information on the user's screen. The AR interface provides an intuitive and fun way to interact with the environment, making it ideal for outdoor settings such as parks, tourist attractions, and historic sites. The system is designed to be accessible to a variety of users, regardless of technical experience, and can be easily integrated into existing websites or mobile applications. The results of the user study show the effectiveness of the system in improving the user's ability to navigate and find points of interest nearby. Overall, this web-based AR location locator is an important step in the development of mobile AR web-based applications that harness the power of the Web to provide innovative and immersive experiences to users.

Contrasted with the past, improvements in PC and correspondence innovations have given broad and propelled changes. The use of new innovations give incredible advantages to people, organizations, and governments, be that as it may, messes some up against them. For instance, the protection of significant data, security of put away information stages, accessibility of information and so forth. Contingent upon these issues, digital fear based oppression is one of the most significant issues in this day and age. Digital fear, which made a great deal of issues people and establishments, has arrived at a level that could undermine open and nation security by different gatherings, for example, criminal association, proficient people and digital activists. Along these lines, Intrusion Detection Systems (IDS) has been created to maintain a strategic distance from digital assaults. Right now, learning the bolster support vector machine (SVM) calculations were utilized to recognize port sweep endeavors dependent on the new CICIDS2017 dataset with 97.80%, 69.79% precision rates were accomplished individually.

Machine learning is a subfield of artificial intelligence (AI). The goal of machine learning generally is to understand the structure of data and fit that data into models that can be understood and utilized by people. Although machine learning is a field within computer science, it differs from traditional computational approaches. In traditional computing, algorithms are sets of explicitly programmed instructions used by computers to calculate or problem solve. Machine learning algorithms instead allow for computers to train on data inputs and use statistical analysis in order to output values that fall within a specific range. Because of this, machine learning facilitates computers in building models from sample data in order to automate decision making processes based on data inputs.

Worldwide solar radiation is a basic parameter for the plan andoperation frameworks. Long-standing records of worldwide solar radiationdata are not accessible in many places because of the cost and maintenance of the measuring instruments. Sun based radiation expecta- tioncontains a incredible significance in power generation from sun basedenergy and makes a difference to measure photovoltaic controlframeworks. With this context, we have utilized solar radiation datasetextracted from UCI Machine Learning. The forecasting of solar radiation are attained in four ways. Firstly, the data set is analyzed andpreprocessed with Feature Scaling and missing values. Secondly, thecorrelation of the features is done and the relation of each features arevisualized.

Skin diseases are hazardous and often contagious, especially melanoma, eczema, and impetigo. These skin diseases can be cured if detected early. The fundamental problem with it is, only an expert dermatologist is able to detect and classify such disease. Sometimes, the doctors also fail to correctly classify the disease and hence provide inappropriate medications to the patient. Our paper proposes a skin disease detection method based on Image Processing and Deep Learning Techniques. Our system is mobile based so can be used even in remote areas. The patient needs to provide the image of the infected area and it is given as an input to the application. Image Processing and Deep Learning techniques process it and deliver the most accurate output. In this paper, we present a comparison of two different approaches for realtime skin disease detection algorithm based on accuracy. We have compared Navies Bias Classifier. The results of real-time testing are presented.

The main objective of the “Blood Bank management System” all the details in the Blood Bank’sprocess. This project has some tasks to maintain the Blood Bank through computerization. Using this blood bank system people can search blood group available which they are needed. They check it on using our blood bank management website. If in case blood group is not available in blood bank they can also contact numbers of the persons who has the same blood group he is need. And he can request the person to done the blood for saving someone life. The Project describes the smart Blood Bank management system. This report will help you to know in deep the actual work that has been done as a team work. The main objective of this application is to automate the complete operations of the blood bank. They need to maintain hundreds of thousands of records. Also searching should be very faster, so they can find required details instantly. Main objective is to create a system which helps them to complete their work faster in simple way by using computer not the oldest way which is used paper. Also our project contains updated information and many things else.

Worldwide solar radiation is a basic parameter for the plan andoperation frameworks. Long-standing records of worldwide solar radiation data are not accessible in many places because of the cost and maintenance of the measuring instruments. Sun based radiation expecta- tion contains a incredible significance in power generation from sun based energy and makes a difference to measure photovoltaic control frameworks. With this context, we have utilized solar radiation dataset extracted from UCI Machine Learning. The forecasting of solar radiation are attained in four ways. Firstly, the data set is analyzed and preprocessed with Feature Scaling and missing values. Secondly, the correlation of the features is done and the relation of each features are visualized.

Aim of this project is to create doctor patient handling management system that will help doctors in their work and will also help patients to book doctor appointments and view medical progress. The system allows doctors to manage their slots online. Patients are allowed to book empty slots online and those slots are reserved in their name. The system manages the appointment data for multiple doctors in specific areas of specialty at various days and times. Each time a user visits a doctor his/her medical entry is stored in the database by that specific doctor. Next time a user logs in he may view his/her entire medical history as and when needed. At the same time a doctor may view patient’s previous medical history while the patient visits him. The system also consists of Blood donor module. This module allows for Blood donation registration as well as Blood group search. The module is designed to help urgent Blood requirements through easy/instant searches.

This paper presents a Web-based augmented reality (AR) detector thatallows users to identify and locate nearby points of interest using their smartphone.The system uses a combination of GPS data and visual recognition algorithms todetermine the user's location and overlay relevant information on the user's screen.The AR interface provides an intuitive and fun way to interact with the environment,making it ideal for outdoor settings such as parks, tourist attractions, and historic sites.The system is designed to be accessible to a variety of users, regardless of technicalexperience, and can be easily integrated into existing websites or mobile applications.The results of the user study show the effectiveness of the system in improving theuser's ability to navigate and find points of interest nearby. Overall, this web-based ARlocation locator is an important step in the development of mobile AR web-basedapplications that harness the power of the Web to provide innovative and immersiveexperiences to users.

In the evolving landscape of talent acquisition, organizations face increasing challenges inefficiently identifying the right candidates from large pools of applicants. Traditionalrecruitment processes often rely on manual resume screening, which is not onlytime-consuming and resource-intensive but also prone to human bias and inconsistency. TheTalentMatch project introduces an AI-powered recruitment platform designed torevolutionize this process by automating and optimizing resume-to-job matching usingadvanced Natural Language Processing (NLP) and Machine Learning (ML) techniques.The core objective of TalentMatch is to intelligently parse, analyze, and rank candidateresumes against job descriptions by extracting key information such as skills, qualifications,work experience, education, certifications, and contextual relevance to the role. The systemutilizes semantic analysis to understand the meaning behind unstructured text data, enablingit to match candidates not just based on keyword overlap, but on true contextual alignmentwith job requirements. By converting unstructured resumes and job postings into structureddata representations, the platform enables a fair, consistent, and data-driven approach tocandidate evaluation.The platform architecture comprises a modular backend built with Express and TypeScript,which handles data ingestion, resume parsing, and job description analysis. The intelligentmatching engine employs a combination of NLP techniques, such as named entityrecognition (NER), word embeddings, vector similarity, and custom scoring algorithms todetermine candidate-job fit. On the frontend, a responsive React application provides anintuitive interface for recruiters to view, filter, and interact with ranked candidate lists. Theinterface also supports customizable scoring metrics, enabling recruiters to prioritize specificattributes like technical skills, years of experience, or educational background based on theunique needs of a role.

Cloud storage systems are widely deployed in the world, and many people use them todownload and upload their personal stuff like videos, text documents, images, etc. Nowadaysmany private firms, company’s, governments, and the military move their databases to cloudstorage. However, a significant question is, can users trust the media services provided by themedia cloud service providers? Many traditional security approaches are proposed to securethe data exchange between users and the media cloud. However, the problem comes to militaryusers if scientist develop a new weapon for military and he want to send a launching code tomilitary admirals /chiefs through cloud, how he can trust cloud that he’s codes will be safelydelivered to admirals. Nowadays cloud storage can easily be cracked by hackers and gaininformation of military weapons and confidential secrets. It could be dangerous if they sold thisinformation to terrorists or rival countries. In this article, we propose to use steganography,watermarking, image encryption and visual cryptography schemes to protect military weaponsdata in clouds. steganography allows users to hide the weapons launch code in image captcha.Visual cryptography shares the image captcha in shares which depend on the number of peoplein a group in the military. image encryption will apply on each share of captcha. After thiswatermarking is applied on each share for authentications between users and cloud. Forreceiving the launch code receivers have to form de-watermarking, image decryption thenvisual cryptography to get captcha and launch code. Our studies show that the proposedapproach achieves good security performance and securing the future of country

The GPS (Global Positioning System) has been used to monitor the transport. The vehicle should be installed with live GPS tracker. The details of the vehicle and count of the passengers is tracked in the app using the fingerprint sensors which is used to make a check-in facility in the Vehicle. Passengers should make a check-in while boarding the vehicle. Then should check-out when they leave the vehicle. The main concept behind this project is that the GPS tracker and fingerprint is attached inside the vehicle the GPS is used to detect the current, then the sensor used to make a check-in and out tasks after verifying the fingerprint the details is shared to the sensors to the app. The app helps the makes the clear view of the passenger check-in and out exact time, date and location. Mainly this app is made for the security purpose for the details of the passengers whether they are in the vehicle or else not. Or whether they were dropped at different destination point. If a passenger from a different vehicle board’s different vehicle of the same management. It allows him to do the check-in but it shows the alert message like this passenger is from this specified vehicle and its number.

The Internet of Things refers to connecting things and people through internet, it has imposed itself as the New business practices in different sectors. To make quick and efficient response in real time, IoT enhances the way and provides emergency managers with the necessary information and communication to make use of those assets. In this paper it is proposed that a quick response for fire hazards is evaluated and examined by using IoT based model. Fire is one of the major reasons of accidental deaths in the world. To implement this proposed system a low-cost Wi-Fi module, gas detection sensor, Flame detection sensor, buzzer to alert and temperature sensors are used.

Cloud storage systems are widely deployed in the world, and many people use them todownload and upload their personal stuff like videos, text documents, images, etc. Nowadaysmany private firms, company’s, governments, and the military move their databases to cloudstorage. However, a significant question is, can users trust the media services provided by themedia cloud service providers? Many traditional security approaches are proposed to securethe data exchange between users and the media cloud. However, the problem comes to militaryusers if scientist develop a new weapon for military and he want to send a launching code tomilitary admirals /chiefs through cloud, how he can trust cloud that he’s codes will be safelydelivered to admirals. Nowadays cloud storage can easily be cracked by hackers and gaininformation of military weapons and confidential secrets. It could be dangerous if they sold thisinformation to terrorists or rival countries. In this article, we propose to use steganography,watermarking, image encryption and visual cryptography schemes to protect military weaponsdata in clouds. steganography allows users to hide the weapons launch code in image captcha.Visual cryptography shares the image captcha in shares which depend on the number of peoplein a group in the military. image encryption will apply on each share of captcha. After thiswatermarking is applied on each share for authentications between users and cloud. Forreceiving the launch code receivers have to form de-watermarking, image decryption thenvisual cryptography to get captcha and launch code. Our studies show that the proposedapproach achieves good security performance and securing the future of country

Machine learning is a subfield of artificial intelligence (AI). The goal of machine learninggenerally is to understand the structure of data and fit that data into models that can beunderstood and utilized by people. Although machine learning is a field within computerscience, it differs from traditional computational approaches. In traditional computing,algorithms are sets of explicitly programmed instructions used by computers to calculate orproblem solve. Machine learning algorithms instead allow for computers to train on data inputsand use statistical analysis in order to output values that fall within a specific range. Because ofthis, machine learning facilitates computers in building models from sample data in order toautomate decision making processes based on data inputs.

"Cloud storage systems are widely deployed in the world, and many people use them to download and upload their personal stuff like videos, text documents, images, etc. Nowadays many private firms, company\u2019s, governments, and the military move their databases to cloud storage. However, a significant question is, can users trust the media services provided by the media cloud service providers? Many traditional security approaches are proposed to secure the data exchange between users and the media cloud. However, the problem comes to military users if scientist develop a new weapon for military and he want to send a launching code to military admirals \/chiefs through cloud, how he can trust cloud that he\u2019s codes will be safely delivered to admirals. Nowadays cloud storage can easily be cracked by hackers and gain information of military weapons and confidential secrets. It could be dangerous if they sold this information to terrorists or rival countries. In this article, we propose to use steganography, watermarking, image encryption and visual cryptography schemes to protect military weapons data in clouds. steganography allows users to hide the weapons launch code in image captcha. Visual cryptography shares the image captcha in shares which depend on the number of people in a group in the military. image encryption will apply on each share of captcha. After this watermarking is applied on each share for authentications between users and cloud. For receiving the launch code receivers have to form de-watermarking, image decryption then visual cryptography to get captcha and launch code. Our studies show that the proposed approach achieves good security performance and securing the future of country"

Skin diseases are hazardous and often contagious, especially melanoma, eczema, and impetigo.These skin diseases can be cured if detected early. The fundamental problem with it is, only an expertdermatologist is able to detect and classify such disease. Sometimes, the doctors also fail to correctlyclassify the disease and hence provide inappropriate medications to the patient. Our paper proposes a skindisease detection method based on Image Processing and Deep Learning Techniques. Our system is mobilebased so can be used even in remote areas. The patient needs to provide the image of the infected area andit is given as an input to the application. Image Processing and Deep Learning techniques process it anddeliver the most accurate output. In this paper, we present a comparison of two different approaches forrealtime skin disease detection algorithm based on accuracy. We have compared Navies Bias Classifier.The results of real-time testing are presented.

Worldwide solar radiation is a basic parameter for the plan andoperation frameworks. Long-standing records of worldwide solar radiation data are not accessible in many places because of the cost and maintenance of the measuring instruments. Sun based radiation expecta- tion contains a incredible significance in power generation from sun based energy and makes a difference to measure photovoltaic control frameworks. With this context, we have utilized solar radiation dataset extracted from UCI Machine Learning. The forecasting of solar radiation are attained in four ways. Firstly, the data set is analyzed and preprocessed with Feature Scaling and missing values. Secondly, the correlation of the features is done and the relation of each features are visualized.

The purpose of the project entitled as “Smart Health Prediction” is to develop software which is user friendly simple, fast, and cost – effective. It deals with the collection of patient’s information, diagnosis details, etc. Traditionally, it was done manually The main function of the system is register and store patient details and doctor details and retrieve these details as and when required, and also to manipulate these details meaningfully System input contains patient details, diagnosis details, while system output is to get these details on to the screen. The Smart Health Prediction can be entered using a username and password. It is accessible either by an administrator. Only they can add data into the database. The data can be retrieved easily.The data are well protected for personal use and makes the data processing very fast. This is the document of the Project proposal for developing a health care system. This system is fully updated and we had provide some new things in it. The project aimed to build a fully functional system in order to achieve the efficiency in faster heath treatment and online consultation system. The overall mission of system development is to make the primary treatment quickly and easily complete the Online Consultation System.

Aim of this project is to create doctor patient handling management system that will help doctors in their work and will also help patients to book doctor appointments and view medical progress. The system allows doctors to manage their slots online. Patients are allowed to book empty slots online and those slots are reserved in their name. The system manages the appointment data for multiple doctors in specific areas of specialty at various days and times. Each time a user visits a doctor his/her medical entry is stored in the database by that specific doctor. Next time a user logs in he may view his/her entire medical history as and when needed. At the same time a doctor may view patient’s previous medical history while the patient visits him. The system also consists of Blood donor module. This module allows for Blood donation registration as well as Blood group search. The module is designed to help urgent Blood requirements through easy/instant searches.

The GPS (Global Positioning System) has been used to monitor the transport. The vehicle should be installed with live GPS tracker. The details of the vehicle and count of the passengers is tracked in the app using the fingerprint sensors which is used to make a check-in facility in the Vehicle. Passengers should make a check-in while boarding the vehicle. Then should check-out when they leave the vehicle. The main concept behind this project is that the GPS tracker and fingerprint is attached inside the vehicle the GPS is used to detect the current, then the sensor used to make a check-in and out tasks after verifying the fingerprint the details is shared to the sensors to the app. The app helps the makes the clear view of the passenger check-in and out exact time, date and location. Mainly this app is made for the security purpose for the details of the passengers whether they are in the vehicle or else not. Or whether they were dropped at different destination point. If a passenger from a different vehicle board’s different vehicle of the same management. It allows him to do the check-in but it shows the alert message like this passenger is from this specified vehicle and its number.

Contrasted with the past, improvements in PC and correspondence innovations have given broad and propelled changes. The use of new innovations give incredible advantages to people, organizations, and governments, be that as it may, messes some up against them. For instance, the protection of significant data, security of put away information stages, accessibility of information and so forth. Contingent upon these issues, digital fear based oppression is one of the most significant issues in this day and age. Digital fear, which made a great deal of issues people and establishments, has arrived at a level that could undermine open and nation security by different gatherings, for example, criminal association, proficient people and digital activists. Along these lines, Intrusion Detection Systems (IDS) has been created to maintain a strategic distance from digital assaults. Right now, learning the bolster support vector machine (SVM) calculations were utilized to recognize port sweep endeavors dependent on the new CICIDS2017 dataset with 97.80%, 69.79% precision rates were accomplished individually.

Data security is the essential in the today’s world of internet and networking. In any organization information is critical. In today’s world people are ready to spent thousands and lacks of money in order to ensure high level of information security. In spite of spending such a huge amount, still the objective of securing the information is not achieved as the data some how gets in the hands of hacker. As the technology for securing the data is advancing, hackers are also keeping pace with this technology. Hackers now make use of certain algorithm or other techniques to decode the data encoded by the senders. One of the ways to ensure security is to ensure that data is not visible to the hacker. This can be done by hiding the message itself behind some other objects. Here we are achieving this data security concept through the technique of Steganography.

The design and operational principle of the digital calendar and digital clock is the subject of this thesis. The system as realized in this book is made up of six units. The power supply unit supplies the required regulated voltage to the appropriate connections of the overall circuit. The micro controller controls the general operation of the circuit; all the other units are interfaced to it. The input unit is activated by pressing the keypad (buttons) unit to call up the subroutine program that controls the set date, month, year and time with alarm instructions. The decoder with the aid of the micro controller executes the instruction codes, which are transmitted to the light emitting diode that corresponds to the actual day that is to display.

The main objective of the “Blood Bank management System” all the details in the Blood Bank’sprocess. This project has some tasks to maintain the Blood Bank through computerization. Using this blood bank system people can search blood group available which they are needed. They check it on using our blood bank management website. If in case blood group is not available in blood bank they can also contact numbers of the persons who has the same blood group he is need. And he can request the person to done the blood for saving someone life. The Project describes the smart Blood Bank management system. This report will help you to know in deep the actual work that has been done as a team work. The main objective of this application is to automate the complete operations of the blood bank. They need to maintain hundreds of thousands of records. Also searching should be very faster, so they can find required details instantly. Main objective is to create a system which helps them to complete their work faster in simple way by using computer not the oldest way which is used paper. Also our project contains updated information and many things else.

Machine learning is a subfield of artificial intelligence (AI). The goal of machine learninggenerally is to understand the structure of data and fit that data into models that can beunderstood and utilized by people. Although machine learning is a field within computerscience, it differs from traditional computational approaches. In traditional computing,algorithms are sets of explicitly programmed instructions used by computers to calculate orproblem solve. Machine learning algorithms instead allow for computers to train on data inputsand use statistical analysis in order to output values that fall within a specific range. Because ofthis, machine learning facilitates computers in building models from sample data in order toautomate decision making processes based on data inputs.

The Internet of Things refers to connecting things andpeople through internet, it has imposed itself as the Newbusiness practices in different sectors. To make quick andefficient response in real time, IoT enhances the way andprovides emergency managers with the necessary informationand communication to make use of those assets.In this paper it is proposed that a quick response for firehazards is evaluated and examined by using IoT based model.Fire is one of the major reasons of accidental deaths in the world.To implement this proposed system a low-cost Wi-Fi module,gas detection sensor, Flame detection sensor, buzzer to alertand temperature sensors are used.

This paper presents a Web-based augmented reality (AR) detector that allows users to identify and locate nearby points of interest using their smartphone. The system uses a combination of GPS data and visual recognition algorithms to determine the user's location and overlay relevant information on the user's screen. The AR interface provides an intuitive and fun way to interact with the environment, making it ideal for outdoor settings such as parks, tourist attractions, and historic sites. The system is designed to be accessible to a variety of users, regardless of technical experience, and can be easily integrated into existing websites or mobile applications. The results of the user study show the effectiveness of the system in improving the user's ability to navigate and find points of interest nearby. Overall, this web-based AR location locator is an important step in the development of mobile AR web-based applications that harness the power of the Web to provide innovative and immersive experiences to users.

Skin diseases are hazardous and often contagious, especially melanoma, eczema, and impetigo. These skin diseases can be cured if detected early. The fundamental problem with it is, only an expert dermatologist is able to detect and classify such disease. Sometimes, the doctors also fail to correctly classify the disease and hence provide inappropriate medications to the patient. Our paper proposes a skin disease detection method based on Image Processing and Deep Learning Techniques. Our system is mobile based so can be used even in remote areas. The patient needs to provide the image of the infected area and it is given as an input to the application. Image Processing and Deep Learning techniques process it and deliver the most accurate output. In this paper, we present a comparison of two different approaches for realtime skin disease detection algorithm based on accuracy. We have compared Navies Bias Classifier. The results of real-time testing are presented.

Skin diseases are hazardous and often contagious, especially melanoma, eczema, and impetigo.These skin diseases can be cured if detected early. The fundamental problem with it is, only an expertdermatologist is able to detect and classify such disease. Sometimes, the doctors also fail to correctlyclassify the disease and hence provide inappropriate medications to the patient. Our paper proposes a skindisease detection method based on Image Processing and Deep Learning Techniques. Our system is mobilebased so can be used even in remote areas. The patient needs to provide the image of the infected area andit is given as an input to the application. Image Processing and Deep Learning techniques process it anddeliver the most accurate output. In this paper, we present a comparison of two different approaches forrealtime skin disease detection algorithm based on accuracy. We have compared Navies Bias Classifier.The results of real-time testing are presented.

Worldwide solar radiation is a basic parameter for the plan andoperation frameworks. Long-standing records of worldwide solar radiation data are not accessible in many places because of the cost and maintenance of the measuring instruments. Sun based radiation expecta- tion contains a incredible significance in power generation from sun based energy and makes a difference to measure photovoltaic control frameworks. With this context, we have utilized solar radiation dataset extracted from UCI Machine Learning. The forecasting of solar radiation are attained in four ways. Firstly, the data set is analyzed and preprocessed with Feature Scaling and missing values. Secondly, the correlation of the features is done and the relation of each features are visualized.

Worldwide solar radiation is a basic parameter for the plan andoperation frameworks. Long-standing records of worldwide solar radiationdata are not accessible in many places because of the cost and maintenance of the measuring instruments. Sun based radiation expecta- tioncontains a incredible significance in power generation from sun basedenergy and makes a difference to measure photovoltaic controlframeworks. With this context, we have utilized solar radiation datasetextracted from UCI Machine Learning. The forecasting of solar radiation are attained in four ways. Firstly, the data set is analyzed andpreprocessed with Feature Scaling and missing values. Secondly, thecorrelation of the features is done and the relation of each features arevisualized.

This paper presents a Web-based augmented reality (AR) detector thatallows users to identify and locate nearby points of interest using their smartphone.The system uses a combination of GPS data and visual recognition algorithms todetermine the user's location and overlay relevant information on the user's screen.The AR interface provides an intuitive and fun way to interact with the environment,making it ideal for outdoor settings such as parks, tourist attractions, and historic sites.The system is designed to be accessible to a variety of users, regardless of technicalexperience, and can be easily integrated into existing websites or mobile applications.The results of the user study show the effectiveness of the system in improving theuser's ability to navigate and find points of interest nearby. Overall, this web-based ARlocation locator is an important step in the development of mobile AR web-basedapplications that harness the power of the Web to provide innovative and immersiveexperiences to users.

The Internet of Things refers to connecting things and people through internet, it has imposed itself as the New business practices in different sectors. To make quick and efficient response in real time, IoT enhances the way and provides emergency managers with the necessary information and communication to make use of those assets. In this paper it is proposed that a quick response for fire hazards is evaluated and examined by using IoT based model. Fire is one of the major reasons of accidental deaths in the world. To implement this proposed system a low-cost Wi-Fi module, gas detection sensor, Flame detection sensor, buzzer to alert and temperature sensors are used.

Machine learning is a subfield of artificial intelligence (AI). The goal of machine learning generally is to understand the structure of data and fit that data into models that can be understood and utilized by people. Although machine learning is a field within computer science, it differs from traditional computational approaches. In traditional computing, algorithms are sets of explicitly programmed instructions used by computers to calculate or problem solve. Machine learning algorithms instead allow for computers to train on data inputs and use statistical analysis in order to output values that fall within a specific range. Because of this, machine learning facilitates computers in building models from sample data in order to automate decision making processes based on data inputs.

The main objective of this paper is to find the best model to predict the value of thestock market. During the process of considering various techniques and variables thatmust be taken into account, we found out that techniques like random forest, supportvector machine were not exploited fully. In, this paper we are going to present andreview a more feasible method to predict the stock movement with higher accuracy.The first thing we have taken into account is the dataset of the stock market pricesfrom previous year. The dataset was pre-processed and tuned up for real analysis.Hence, our paper will also focus on data preprocessing of the raw dataset. Secondly,after pre- processing the data, we will review the use of random forest, support vectormachine on the dataset and the outcomes it generates. In addition, the proposed paperexaminesthe use of the prediction system in real- world settings and issues associatedwith the accuracy of the overall values given. The paper also presents a machinelearning model to predict the longevity of stock in a competitive market. Thesuccessful prediction of the stock will be a great asset for the stock market institutionsand will provide real-life solutions to the problems that stock investors face.

"Cloud storage systems are widely deployed in the world, and many people use them to download and upload their personal stuff like videos, text documents, images, etc. Nowadays many private firms, company\u2019s, governments, and the military move their databases to cloud storage. However, a significant question is, can users trust the media services provided by the media cloud service providers? Many traditional security approaches are proposed to secure the data exchange between users and the media cloud. However, the problem comes to military users if scientist develop a new weapon for military and he want to send a launching code to military admirals \/chiefs through cloud, how he can trust cloud that he\u2019s codes will be safely delivered to admirals. Nowadays cloud storage can easily be cracked by hackers and gain information of military weapons and confidential secrets. It could be dangerous if they sold this information to terrorists or rival countries. In this article, we propose to use steganography, watermarking, image encryption and visual cryptography schemes to protect military weapons data in clouds. steganography allows users to hide the weapons launch code in image captcha. Visual cryptography shares the image captcha in shares which depend on the number of people in a group in the military. image encryption will apply on each share of captcha. After this watermarking is applied on each share for authentications between users and cloud. For receiving the launch code receivers have to form de-watermarking, image decryption then visual cryptography to get captcha and launch code. Our studies show that the proposed approach achieves good security performance and securing the future of country"

In the evolving landscape of talent acquisition, organizations face increasing challenges inefficiently identifying the right candidates from large pools of applicants. Traditionalrecruitment processes often rely on manual resume screening, which is not onlytime-consuming and resource-intensive but also prone to human bias and inconsistency. TheTalentMatch project introduces an AI-powered recruitment platform designed torevolutionize this process by automating and optimizing resume-to-job matching usingadvanced Natural Language Processing (NLP) and Machine Learning (ML) techniques.The core objective of TalentMatch is to intelligently parse, analyze, and rank candidateresumes against job descriptions by extracting key information such as skills, qualifications,work experience, education, certifications, and contextual relevance to the role. The systemutilizes semantic analysis to understand the meaning behind unstructured text data, enablingit to match candidates not just based on keyword overlap, but on true contextual alignmentwith job requirements. By converting unstructured resumes and job postings into structureddata representations, the platform enables a fair, consistent, and data-driven approach tocandidate evaluation.The platform architecture comprises a modular backend built with Express and TypeScript,which handles data ingestion, resume parsing, and job description analysis. The intelligentmatching engine employs a combination of NLP techniques, such as named entityrecognition (NER), word embeddings, vector similarity, and custom scoring algorithms todetermine candidate-job fit. On the frontend, a responsive React application provides anintuitive interface for recruiters to view, filter, and interact with ranked candidate lists. Theinterface also supports customizable scoring metrics, enabling recruiters to prioritize specificattributes like technical skills, years of experience, or educational background based on theunique needs of a role.

"Worldwide solar radiation is a basic parameter for the plan andoperation frameworks. Long-standing records of worldwide solar radiation data are not accessible in many places because of the cost and maintenance of the measuring instruments. Sun based radiation expecta- tion contains a incredible significance in power generation from sun based energy and makes a difference to measure photovoltaic control frameworks. With this context, we have utilized solar radiation dataset extracted from UCI Machine Learning. The forecasting of solar radiation are attained in four ways. Firstly, the data set is analyzed and preprocessed with Feature Scaling and missing values. Secondly, the correlation of the features is done and the relation of each features are visualized."

Cloud storage systems are widely deployed in the world, and many people use them todownload and upload their personal stuff like videos, text documents, images, etc. Nowadaysmany private firms, company’s, governments, and the military move their databases to cloudstorage. However, a significant question is, can users trust the media services provided by themedia cloud service providers? Many traditional security approaches are proposed to securethe data exchange between users and the media cloud. However, the problem comes to militaryusers if scientist develop a new weapon for military and he want to send a launching code tomilitary admirals /chiefs through cloud, how he can trust cloud that he’s codes will be safelydelivered to admirals. Nowadays cloud storage can easily be cracked by hackers and gaininformation of military weapons and confidential secrets. It could be dangerous if they sold thisinformation to terrorists or rival countries. In this article, we propose to use steganography,watermarking, image encryption and visual cryptography schemes to protect military weaponsdata in clouds. steganography allows users to hide the weapons launch code in image captcha.Visual cryptography shares the image captcha in shares which depend on the number of peoplein a group in the military. image encryption will apply on each share of captcha. After thiswatermarking is applied on each share for authentications between users and cloud. Forreceiving the launch code receivers have to form de-watermarking, image decryption thenvisual cryptography to get captcha and launch code. Our studies show that the proposedapproach achieves good security performance and securing the future of country

This paper presents a Web-based augmented reality (AR) detector that allows users to identify and locate nearby points of interest using their smartphone. The system uses a combination of GPS data and visual recognition algorithms to determine the user's location and overlay relevant information on the user's screen. The AR interface provides an intuitive and fun way to interact with the environment, making it ideal for outdoor settings such as parks, tourist attractions, and historic sites. The system is designed to be accessible to a variety of users, regardless of technical experience, and can be easily integrated into existing websites or mobile applications. The results of the user study show the effectiveness of the system in improving the user's ability to navigate and find points of interest nearby. Overall, this web-based AR location locator is an important step in the development of mobile AR web-based applications that harness the power of the Web to provide innovative and immersive experiences to users.

Machine learning is a subfield of artificial intelligence (AI). The goal of machine learning generally is to understand the structure of data and fit that data into models that can be understood and utilized by people. Although machine learning is a field within computer science, it differs from traditional computational approaches. In traditional computing, algorithms are sets of explicitly programmed instructions used by computers to calculate or problem solve. Machine learning algorithms instead allow for computers to train on data inputs and use statistical analysis in order to output values that fall within a specific range. Because of this, machine learning facilitates computers in building models from sample data in order to automate decision making processes based on data inputs.

The Internet of Things refers to connecting things and people through internet, it has imposed itself as the New business practices in different sectors. To make quick and efficient response in real time, IoT enhances the way and provides emergency managers with the necessary information and communication to make use of those assets. In this paper it is proposed that a quick response for fire hazards is evaluated and examined by using IoT based model. Fire is one of the major reasons of accidental deaths in the world. To implement this proposed system a low-cost Wi-Fi module, gas detection sensor, Flame detection sensor, buzzer to alert and temperature sensors are used.

Skin diseases are hazardous and often contagious, especially melanoma, eczema, and impetigo. These skin diseases can be cured if detected early. The fundamental problem with it is, only an expert dermatologist is able to detect and classify such disease. Sometimes, the doctors also fail to correctly classify the disease and hence provide inappropriate medications to the patient. Our paper proposes a skin disease detection method based on Image Processing and Deep Learning Techniques. Our system is mobile based so can be used even in remote areas. The patient needs to provide the image of the infected area and it is given as an input to the application. Image Processing and Deep Learning techniques process it and deliver the most accurate output. In this paper, we present a comparison of two different approaches for realtime skin disease detection algorithm based on accuracy. We have compared Navies Bias Classifier. The results of real-time testing are presented.

"Machine learning is a subfield of artificial intelligence (AI). The goal of machine learning generally is to understand the structure of data and fit that data into models that can be understood and utilized by people. Although machine learning is a field within computer science, it differs from traditional computational approaches. In traditional computing, algorithms are sets of explicitly programmed instructions used by computers to calculate or problem solve. Machine learning algorithms instead allow for computers to train on data inputs and use statistical analysis in order to output values that fall within a specific range. Because of this, machine learning facilitates computers in building models from sample data in order to automate decision making processes based on data inputs."

"The Internet of Things refers to connecting things and people through internet, it has imposed itself as the New business practices in different sectors. To make quick and efficient response in real time, IoT enhances the way and provides emergency managers with the necessary information and communication to make use of those assets. In this paper it is proposed that a quick response for fire hazards is evaluated and examined by using IoT based model. Fire is one of the major reasons of accidental deaths in the world. To implement this proposed system a low-cost Wi-Fi module, gas detection sensor, Flame detection sensor, buzzer to alert and temperature sensors are used."

"Skin diseases are hazardous and often contagious, especially melanoma, eczema, and impetigo. These skin diseases can be cured if detected early. The fundamental problem with it is, only an expert dermatologist is able to detect and classify such disease. Sometimes, the doctors also fail to correctly classify the disease and hence provide inappropriate medications to the patient. Our paper proposes a skin disease detection method based on Image Processing and Deep Learning Techniques. Our system is mobile based so can be used even in remote areas. The patient needs to provide the image of the infected area and it is given as an input to the application. Image Processing and Deep Learning techniques process it and deliver the most accurate output. In this paper, we present a comparison of two different approaches for realtime skin disease detection algorithm based on accuracy. We have compared Navies Bias Classifier. The results of real-time testing are presented."

"This paper presents a Web-based augmented reality (AR) detector that allows users to identify and locate nearby points of interest using their smartphone. The system uses a combination of GPS data and visual recognition algorithms to determine the user's location and overlay relevant information on the user's screen. The AR interface provides an intuitive and fun way to interact with the environment, making it ideal for outdoor settings such as parks, tourist attractions, and historic sites. The system is designed to be accessible to a variety of users, regardless of technical experience, and can be easily integrated into existing websites or mobile applications. The results of the user study show the effectiveness of the system in improving the user's ability to navigate and find points of interest nearby. Overall, this web-based AR location locator is an important step in the development of mobile AR web-based applications that harness the power of the Web to provide innovative and immersive experiences to users."

"In recent years, motion detection has attracted a great interest from computer vision researchers due to its promising applications in many areas, such as video surveillance. In motion detection the task is to detect a region of interest embodied in a region of awareness, where the region of awareness, or in terms of the camera geometry, the field of view, is defined as the portion of environment being monitored. The region of interest is in the present case the portion of the environment with activity. For the sake of simplicity and generality, recognition-based detection is not assumed. A region of interest can be therefore a person, an animal, or an artifact; circumscribed with the term moving objects. The motion detection algorithm is based on background change detection, i.e. the difference method by background subtraction. This assumes that the background model for the expected image sequence is known in advance and that it does not change over time. Such conditions are rarely given for an indoor scene, e.g. when illumination changes occur and objects are moved around. Hence a confident adaption method is required. An adaption region must be specified that discerns between foreground and background objects. By definition the background change detection itself yields that distinction but is inappropriate because undetected foreground objects will be falsely adapted to the modelled background image."

Embedded systems are the developing system at this time.The combination of hardware and software components that are embedded into a system to make it interact intelligently with its (physical) environment to meet a specific need with performance in given time.

A cake shop management system is a computerized management system. This system provides the Records of hardware assets beside software of the organization. the proposed system keep a track of different types of cakes available in the system. The main objective of cake shop management system is to provide solution for the customers to manage their work using computerized process. this software application will help to handle the customer information details about the products, payment detailed information etc. detailed explanation about modules and design are provided in the documentation.

Online Book Store’s main facilities available in this project are:- - Maintaining book details. - Purchase feature. - Add and update book details

Skin diseases are hazardous and often contagious, especially melanoma, eczema, and impetigo. These skin diseases can be cured if detected early. The fundamental problem with it is, only an expert dermatologist is able to detect and classify such disease. Sometimes, the doctors also fail to correctly classify the disease and hence provide inappropriate medications to the patient. Our paper proposes a skin disease detection method based on Image Processing and Deep Learning Techniques. Our system is mobile based so can be used even in remote areas. The patient needs to provide the image of the infected area and it is given as an input to the application. Image Processing and Deep Learning techniques process it and deliver the most accurate output. In this paper, we present a comparison of two different approaches for realtime skin disease detection algorithm based on accuracy. We have compared Navies Bias Classifier. The results of real-time testing are presented.

"The main objective of this paper is to find the best model to predict the value of the stock market. During the process of considering various techniques and variables that must be taken into account, we found out that techniques like random forest, support vector machine were not exploited fully. In, this paper we are going to present and review a more feasible method to predict the stock movement with higher accuracy. The first thing we have taken into account is the dataset of the stock market prices from previous year. The dataset was pre-processed and tuned up for real analysis. Hence, our paper will also focus on data preprocessing of the raw dataset. Secondly, after pre- processing the data, we will review the use of random forest, support vector machine on the dataset and the outcomes it generates. In addition, the proposed paper examinesthe use of the prediction system in real- world settings and issues associated with the accuracy of the overall values given. The paper also presents a machinelearning model to predict the longevity of stock in a competitive market. The successful prediction of the stock will be a great asset for the stock market institutions and will provide real-life solutions to the problems that stock investors face."

This project Entrance Seat Allotment System is windows application in which students can register with their rank number for the entrance examination and the administrator can allot the seats for the students. Administrator can add the college details and he batch details. Using this software the entrance seat allotment became easier and can be implemented using system. The main advantage of the project is the computerization of the entrance seat allotment process. Administrator has the power for the allotment. He can add the allotted seats into a file and the details are saved into the system. The total time for the entrance allotment became lesser and the allotment process became faster.

Orphanage Connecting System is being developed for the welfare of the orphanage and can be used by NGOs for co-operative social work. System is mainly for the systematic usage of the website by the user, adopters, charity or NGO’s and the admin. The objective of this application is to develop a centralized website for orphanages. To provide facilities of various social activities in a single website. People can adopt the children and they can donate through online.

"Flying bird animation is a type of computer animation that simulates the movement of a bird in flight. The animation involves creating a sequence of images that simulate the flapping of wings, the rotation of the body, and the movement of the bird in space.The process of creating a flying bird animation typically involves several steps. First, the animator creates a 3D model of the bird in a computer graphics software program. The model is then rigged with a skeletal structure, which allows the animator to animate the bird's movements.The animator then creates a series of keyframes that define the bird's movements at specific points in time. These keyframes are used to create a sequence of frames that show the bird in motion. The animator can adjust the timing and spacing of the keyframes to create a more natural-looking motion.Once the animation is complete, the frames are rendered into a final animation sequence that can be played back as a video. Advanced techniques such as particle systems and physics simulations can also be used to add additional detail and realism to the animation.Flying bird animation is often used in movies, TV shows, and video games to add realistic and dynamic movement to birds in various scenes. It can also be used for educational and scientific purposes, such as simulating the flight of birds for research or educational videos."

The basic concept of this society system, we create global web based application in asp.net with C# language to manage Society with House and Owner of house detail. We provide platform to register society to our system, and there are many houses according to each society. Each house allocated to owner of house, all the owner are members of our project. After becoming a member they can login to give his house on rent or sell for all users. The people can easily find search the rent house or sell house in which society and get contact detail of owner of house by visiting our website. All members can make online complain related home to society management.

Phishing is a new word produced from 'fishing', it refers to the act that the attacker allure users to visit a faked Web site by sending them faked e-mails (or instant messages), and stealthily get victim's personal information such as user name, password, and national security ID, etc. This information then can be used for future target advertisements or even identity theft attacks (e.g., transfer money from victims' bank account). The frequently used attack method is to send e-mails to potential victims, which seemed to be sent by banks, online organizations, or ISPs. In these e-mails, they will make up some causes, e.g. the password of your credit card had been mis-entered for many times, or they are providing upgrading services, to allure you visit their Web site to conform or modify your account number and password through the hyperlink provided in the e-mail (Leon, 2008).

Dental Clinics, Dental department or other specialty department in a general hospital can use this software. Though this software was designed primarily with the inputs from dental Clinics, it could be adoptable in other specialty hospitals also, with some little changes in the medical terms, database etc. DCMS software has been developed to provide comprehensive software solution for the clinics. But there are clinics that cannot afford to run such comprehensive system or may not be required due to the volume of work handled. Still to encourage such clinics to use computers for generating useful information to run the organization efficiently, we provide the following Software from which one can choose according to their requirement.