JOURNAL OF ADVANCED DATABASE MANAGEMENT & SYSTEMS
ISSN: 2393-8730 Scientific Journal Impact Factor (SJIF): 6.038 Index Copernicus (ICV: 55.92) Journal DOI no.: 10.37591/JoADMS
STM JOURNALS ( Consortium eLearning Network Pvt Ltd)
Overview of Database Management Systems: Components, Abstraction, and Applications
Computer software called a database management system (DBMS) is made to manage databases effectively and conveniently. The primary goal of DBMSs is to efficiently and conveniently store and retrieve data. This paper provides an overview of the DBMS, including an explanation of its components and the data model that specifies how the data should be organized for a given use. Giving users an abstract view of the data is one of a database's main goals. The process of normalization plays a vital role in the development of a database. Developers can remove redundant data and create standards by which all data can be evaluated by employing DBMS. It makes it easy for businesses to create and utilize databases for a range of purposes through database administrators. DBMSs are currently unable to provide this kind of flexibility. The growing amount of data that needs to be indexed and retrieved, coupled with increasingly demanding workloads, has led to issues with scalability, reliability, distribution, and performance in modern search engines. This paper assesses the effectiveness of our system in comparison to existing implementations that rely on storing the complete text index directly within the file system. Additionally, it introduces a novel and uncomplicated integration approach.
Copyright (c) 2023 JOURNAL OF ADVANCED DATABASE MANAGEMENT & SYSTEMS
Blockchain-based Privacy-preserving Data Sharing in Healthcare Systems
Healthcare systems contain expansive yet fragmented sensitive data necessitating secure consolidated access mechanisms respecting patient consent preferences continually. This research develops a decentralized blockchain framework orchestrating granular authorization using cryptography while demonstrating efficacy via clinical implementations optimizing cancer diagnostics through aggregated genome analysis otherwise prohibited under isolated datasets. Comparative benchmarking against traditional database models evaluates correctness, interoperability, and auditability improvements using multiparty endorsement affirming consented transactions. Quantified metrics guide technology adoption trade-offs balancing security, privacy and utility based on contextual needs. Reference implementations confirm 50% enhancement in cohort analytical power reinforced by robust threat protections unalterable absent collusion. Resultant principles inform medical data sharing governance given diversifying data accumulation, computational capabilities and patient participatory expectations entering the digital health era.
Streamlining Data Quality: A Conceptual Model and Excel-based Tool for Email Duplicate Removal
In the realm of data management, ensuring data quality is paramount for meaningful analysis and decision making. This research paper presents a novel conceptual model and practical tool designed to address the challenge of removing duplicate entries from datasets containing email IDs. The proposed mathematical model for duplicate removal is meticulously developed and subsequently implemented in Microsoft Excel, leveraging Visual Basic for Applications. The Excel interface is enhanced with user-friendly macros organized under the newly added 'Manage Emails' tab, which logically groups tasks into three distinct categories: data cleaning, duplicate removal, and report generation. Specifically, the research focuses on the post-acquisition phase, assuming the availability of email datasets, while acknowledging that data acquisition falls beyond the paper's scope and warrants future exploration. The outcome of this study culminates in the creation of a 'Unique Emails' sheet, housing the pre-processed emails after duplicate removal. This research contributes to the domain of data quality enhancement by providing a practical and efficient solution for the removal of duplicate email entries, enabling organizations and analysts to work with cleaner and more reliable data. The proposed model and tool serve as valuable assets for data pre-processing and analysis, ultimately facilitating more accurate and insightful decision-making processes.
microsoft excel visual basic for applications (VBA)
Application of Blockchain Database in Voting Systems
Nowadays, regular voting is conducted by electronic voting machines, or EVMs, which keep track of every voter's vote in a central database. Moreover, most of the scrutinized voting programs employed centralized data storage for their databases. Because these centralized databases are easily hacked and manipulated, all of the data is kept in one place. As a result, the numbers may not add up correctly during the voting process and may not give us the right answer. Because blockchain employs a decentralized method for data storage, where data is kept in a single location, we may use blockchain technology to construct a decentralized application where data tampering becomes nearly impossible. The fundamental goal of the blockchain-based electronic voting system is to develop an electronic voting system through the use of blockchain technology. This method functions exactly like a traditional voting system, with voters using mobile devices and web browsers to complete the identical process of electronic voting that was previously done through traditional paper-based voting. A review of blockchain technology and its application to the electronic voting system is provided in this paper.
Accelerating Database Application Development with JsonPowerDB: A Case Study of Student Enrollment Web Form
This paper presents the utilization of JsonPowerDB, a developer-friendly database server with REST API services, in the context of a student enrollment web form. JsonPowerDB offers high performance, lightweight, Ajax-enabled, and serverless features, making it a powerful real-time database for dynamic websites, mobile apps, and data analytics portals. The web form was developed using frontend technologies such as HTML, CSS, JavaScript, and Bootstrap, while JsonPowerDB served as the backend for seamless data storage and retrieval. The study showcases the ease and speed of developing database applications without traditional server-side programming or database installation. With a basic understanding of frontend technologies, developers can effortlessly design and implement efficient web forms. The integration of JsonPowerDB with Java, .NET, Python, or PHP demonstrates its versatility and effectiveness in diverse server-side programming environments. The paper highlights the practical implementation of JsonPowerDB, emphasizing its role in enabling rapid development of the student enrollment web form. The performance, simplicity, and real-time capabilities of JsonPowerDB are evaluated, showcasing its suitability for modern web applications. The presented case study encourages developers to explore JsonPowerDB as a viable solution for building fast and user-friendly database applications.
Storage Facility Management Framework Using NoSQL Database for Healthcare Sector
The tremendous adoption of new technology is responsible for the enormous volume of streaming data currently available. The traditional relational database paradigm faces many issues because of these enormous volumes of data. The primary concerns revolve around the efficiency of data retrieval and the database's ability to flexibly adjust its resources in response to changing requirements. However, because the new application architecture will be built on a NoSQL database, the adoption of NoSQL databases in new businesses is not a significant concern. However, a challenge arises when relational database-dependent systems that are already in place are redesigned to use NoSQL databases. To establish the fresh database structure, they need to review the system prerequisites once again. The goal of this project is to provide a framework for leveraging NoSQL databases to manage storage facilities for the healthcare industry. The notions of a relational structure (Table, Simple Attribute, Primary Key (PK), Foreign Key (FK), and Field List) and NoSQL concept (Document Collection, Document, Field, Embedded Field, ObjectId, DBRef) have been mapped conceptually. By creating object references between items that belong to documents, relationships were made possible. The metadata kept in the MySQL system tables was utilized by the mapping algorithm. PHP was used to implement the system. On the basis of migration speed and query speed, experiments on MySQL and MongoDB were carried out. Five queries were run to retrieve the number of rows from the product table to measure the read speed of each database. For each application, the average of these five requests was taken. MongoDB outperformed MySQL in a time comparison, clocking in at 1.78 sec versus 3.35 sec.
Data Science: Domains, Process, Roles and Responsibilities
The study of information retrieval and analysis, or data science, tries to identify information and correspondence hidden in raw, defined information. To extract useful information from data, data science therefore combines programming expertise with understanding of mathematics and statistics. In the field of data science, machine learning algorithms are employed to handle various types of input, including numerical, textual, visual, and auditory data. Therefore, algorithms perform certain tasks related to data extraction, cleaning, and processing and in turn produce data that becomes a real value for any organization. Fraud detection, targeted marketing, healthcare diagnostics, proactive treatment, and recommendation systems are a few examples of data science applications. Big data's expansion and the accessibility of effective computing resources have made data science more and more relevant in recent years. Because of this, data science has become a field in high demand, and there is a growing need for experts in the sector. Because data now gives businesses a competitive edge, we often talk about data science, but what does that mean? In this study, we have tried to go deeper into this subject.
Study of Crypto-Watermarking Method for Secure Transmission of Medical Images
The delivery of online content poses significant challenges due to the lack of a secure framework to protect valuable data. Due to the lack of a solid system for protecting important data, the distribution of secure online information is fraught with difficulties. However, the use of digital watermarking technology, that provides control, identification, and protection of content owners’ rights, offers a viable remedy. This research study proposes a novel method that combines image encryption and watermarking techniques to enable secure transmission and attempts to provide an overview of digital watermarking. The use of this technique and the presentation of the outcomes derived from medical imaging serve as examples of its efficacy. For the safe content transfer, the integration of image encryption and watermarking techniques has been used. Data security and integrity during transmission can be ensured by encrypting the image itself to prevent unauthorized access and alteration. A further layer of security is added by encrypting the secret key using the public-private key encryption technique, as the key is safe even if the encrypted image is intercepted. Only individuals with the appropriate decryption keys are permitted to access and decipher the image, thanks to the included encrypted key that acts as a kind of authentication. Beyond medical imaging, there are several fields where this technique could be used and where the safe transmission of digital content.
The Use Case of Relational and Non-relational Database
The digital revolution has unleashed vast data collection by digital service providers, driving businesses to undergo digital transformation. Intelligent data integration is crucial for this transformation. A reliable database is essential for efficient data reading and writing. Each type of database suits specific use cases, such as relational databases for structured data and NoSQL databases for flexibility. Time-series databases handle time-stamped data, while graph databases manage complex relationships. In-memory databases provide real-time processing, and distributed databases offer scalability. Understanding database suitability is vital for thriving in the data-driven era.
Comparative Analysis of Algorithms for Mining Frequent Patterns
In the computerized world, everything is moving online, and data comes in different shapes and sizes and is collected in different ways. By using data mining, frequent patterns in the databases can be identified, and it can be used in numerous applications. Finding frequent patterns in huge databases is important because it reveals important information that cannot be found through simple data surfing. To find common patterns, a variety of methods are utilized, each of which performs differently. The fundamental methods used in frequent pattern mining are Apriori and FP-growth. The functioning and experimental results of various algorithms are compared in this study, and their benefits and drawbacks are discussed.
Enhancing Language Modelling with RNN and LSTMbased Next Word Prediction
A growing field of study, natural language processing is utilised in many different contexts. We frequently text each other, and we have noticed that whenever we type a message, a recommendation pops up to try to guess what word we will write next. The task of anticipating the next word is known as next word prediction or language modelling. This makes them highly effective for tasks such as language modelling, speech recognition, sentiment analysis, and machine translation. In this study, we will provide a comprehensive overview of RNNs. Additionally, we will explore the limitations and difficulties of RNNs, as well as recent advances such as attention mechanisms that have enhanced their performance. The process for language modelling on a collection of texts now uses artificial neural networks. Recurrent neural networks (RNNs) can use all of the words that have come before to predict the next word, unlike feed-forward networks that can only use a predetermined context length of words.
Real-Time Patient Location Tracking and Monitoring Geofencing System
This study presents a method for tracking patients from COVID centers using geofencing. This article primarily focuses on developing Android applications that can inform people about COVID-19 containment zones and prevent people from entering these zones. Lockdown and quarantine centers have been set up in India and many other countries to reduce the spread. Using a geofencing framework to monitor someone’s Movement during the quarantine period. Geofencing methodologies provide analysis using a layer of geographic boundaries within the original location and Movement. This simulation demonstrates the importance of the distance parameter and gives warnings based on GPS information. This application also notifies when the user enters the security zone and uploads the user’s girlfriend’s IMEI number to an online database. Therefore, this app can be used as a tool to raise public awareness about Maharashtra people’s new need to be vigilant. A geofencing patient tracking system is a location-based service that uses virtual boundaries to track patient movement within a healthcare facility. With this system, geofences are set up around specific areas within a healthcare facility, and when a patient enters or exits one of these areas, their location is automatically recorded by the system. The system can be used to improve patient safety, improve quality of care and prevent unauthorized access to restricted areas.
Digital Currencies: Bitcoin After Next 50 years and Evolution of Blockchain Technology
The term digital is now becoming the prefix for everything done traditionally. Now currency has also become a part of it. And we use the term digital currency or more precisely cryptocurrency for it. Blockchain, the core concept or the power behind the success of Bitcoin is one of the most trending and common topics for digital currency these days. The blockchain serves as the public ledger and transactions stored using this methodology are almost impossible to tamper with. This study portrays blockchain innovation and a couple of convincing explicit applications in both monetary and nonmonetary parts. We at that point look at the difficulties ahead and business openings in this major innovation that is prepared to reform our computerized world. We have also done some surveys on students with IT background to see how much of current generation is aware of blockchain technology and to get insights about future of bitcoin and the blockchain.
Integrating QR Code and Blockchain Technologies for Enhanced Authenticity and Traceability of Products
The counterfeiting of products is a significant challenge faced by the retail market today. Various methods such as RFID tags, machine learning, artificial intelligence, and QR code-based systems have been employed to combat counterfeiting, but they all have some drawbacks. For instance, QR codes can be copied from genuine products to fake ones, and AI and machine learning require high computational power. To address this issue, we propose using blockchain technology to enhance the detection of counterfeit products. Our approach involves storing the supply chain of products at each transaction stage using a QR code, and the blockchain’s decentralized nature ensures that the data is secure and protected from third-party interference. Using QR codes, customers can scan a product and view its complete history, including its origin, manufacturer, and distribution path, which can aid in verifying the product’s authenticity before purchase. This can also help manufacturers and retailers track the product’s movement, preventing it from being diverted to unauthorized channels. Implementing blockchain technology in this manner eliminates the need for middlemen, which can help reduce distribution costs and improve transparency and accountability in the supply chain. Although there are challenges to widespread adoption and integration with existing systems, this approach has significant potential to reduce the prevalence of counterfeit products in the market and enhance overall supply chain efficiency and security.
Review Paper on Platform for Big Data Analytics as a Service with Stock Market Prediction and Analysis
Petabyte-scale data is referred to as big data. The sum of the data in this quantity, which includes audio files, image files, and many more. Due to the unstructured nature of the data, it is challenging to evaluate the information that is gathered from it. As a result of social networking and cloud computing, data has significantly increased. It is therefore difficult to assess, process, and store. Big data processing does not work well with conventional techniques. Utilising relational databases or conducting surveys are examples of traditional tactics. Big data platforms are crucial for improving the accuracy of the analysis phase. There are two main use cases of big data analytics. They are certainly the analysis of big volumes of data and including accurate prediction. The list of some of the most popular big data analytics tools is as follows: Data can be stored and analysed using Hadoop; MongoDB is used for datasets that change quickly; Talend is employed for data integration and management; The Cassandra is a distributed database, which controls data chunks; Spark is a technology for quickly processing and analysing enormous amounts of data; STORM is an open-source real-time computing platform; and Kafka, a system for fault-tolerant storage and distributed streaming.
Privacy Preserving of Vertically Partitioned Data Using Elliptical Curve Cryptography
Data mining's privacy problems have become a big problem as a result of financial considerations. This work investigates the topic regarding the issue of privacy-preserving global association rule analysis over several parties in vertically partitioned data to efficiently prevent hidden trends and perform computations across the parties while respecting the privacy of their data. After that, it suggests using Shamir's method of secret sharing to support distributed mining of association rules. We also provide association rule mining method using elliptic curve cryptography. We believe in this unstable distributed system. The algorithmic approach allows for verification between engaged parties while also protecting entrants and involved parties. Finally, we look at the security and privacy that our proposed division offers.
Copyright (c) 2022 JOURNAL OF ADVANCED DATABASE MANAGEMENT & SYSTEMS
Study Analysis of Geolocational Data with Statistics: A Review
The biggest challenge while traveling is looking for a place to stay, and considering doing a complete, thorough analysis of real-world data. The objective of the present study is to refer, clean, fetch, analyze and run K Means clustering on geolocational data to suggest lodgings to the travelers and immigrants of a city; maximizing the likelihood of the distances between the target and the landmarks, given the observed delays, yields an estimate of the target location. An algorithm that combines gradient ascent and force-directed approaches accomplishes this. The pendularity of migration flows, or the degree to which migrants move back and forth between their countries of origin and destination, can also be described using geolocation data. Then, geographic contour levels corresponding to a certain probability level of co-occurrence of the numerous taxa can be calculated using probability density functions. The accuracy and precision of geolocation can then be calculated as functions of latitude, longitude, elevation, and other environmental factors. To categorize oncampus housing options for new students, we will consider their preferences for facilities, available funds, and distance from the school.
Data Breaches and Malware Detection in Healthcare System
The healthcare sector is undergoing a chaotic digital transformation, but the incorporation of new technologies is not typically the cause of health information-related data breaches. According to published industry studies, there are still many recorded data breaches as a result of equipment theft, hacking, ransomware attacks, and misuse, as well as a lack of basic security precautions. When compared to any other field, protecting health information is given the highest priority. Several internal and external cyberattacks have been launched against the healthcare/medical industry as a result of the digitalization of patient records in the medical area. Healthcare has seen a sharp increase in the number of data breaches. Data breaches continue to occur on a regular basis although there are security standards like HIPAA (Health Insurance Portability and Accountability Act). By using malicious software or malware, cybercriminals attempt to attack and gain passage to computer networks or systems of numerous businesses, particularly in the healthcare sector, in order to compromise or corrupt sensitive data or carry out illicit financial activities. Healthcare companies are storing their large amount of data in virtual and cloud settings. Hence such malicious attacks have been increasing during the past few years. As a result, the healthcare sector is very concerned about medical data retention. This essay seeks to understand the factors behind the ransomware, the incident that led to a medical data breach and its impact on patients and healthcare professionals. The report also examines current and potential improvements in health care safety systems by assessing their effectiveness. Additionally, this study offers a powerful strategy for malware identification and classification utilizing machine learning methods.
Blockchain Technology using Cyber Security
Blockchain has become one of the most inspected subjects starting from the development of Santoshi Nakamoto's paper related to Bitcoin. It has enchanted basic thought due to its tremendous decision of likely applications and its principal appearance since Bitcoin. Blockchain is known for getting data assembling and traveling through decentralized, trustless, and dissipated structures. This evaluation deliberately recognizes the potential benefits that encourage its use. The encryption technique used in Blockchain makes it peculiar for anybody to add on existing data records, so when we use blockchain to store IoT Data, strengthens the ability to keep venomous aggressors from impeding progress or development. Each new block in a cryptocurrency chain is linked to all the blocks before it in such a way that tampering is nearly impossible. Each payment enshrined in the blocks is verified and accepted by a consensus mechanism, ensuring that each agreement is true and accurate.
Blockchain and its impacts on the improvement of Bookkeeping
At its generally essential level, blockchain innovation can possibly assist us with disposing of focal outsider specialists like the Stock Trade, Public Instalment Framework, and Property Registers. They keep up with track of two-party exchanges and give checked receipts or duplicates of the data. Bookkeeping utilizes these checked receipts or duplicates of papers to keep exchanges in the books of records. Since blockchain is a shared organization, it does not need the support of a focal power. Exchanges will be safely put away in blocks, and organizations will at this point not be expected to keep physical or computerized duplicates of them. Because of the trouble of controlling the blockchain, circumstances of manufacturing papers to execute extortion will be basically nonexistent. At long last, blockchain may make ongoing blockchain bookkeeping conceivable at its most advanced level. A product arrangement thusly may empower cash, monetary subsidiaries, and other computerized instruments exchanges between at least two closely involved individuals and record the exchanges in cryptographically gotten blocks that can be approved. It could likewise be computerized to make instalments and settlements in light of the instruments’ development and record the exchanges. At this level, bookkeepers’ liabilities are probably going to be bound to areas of judgment, for example, stock worth, deterioration or arrangement strategy choice, etc. They will not be the clerks any longer. Be that as it may, as recently noticed, this will require mechanical headway past the ongoing stage.
Global Expansion of Cryptocurrencies and Their Effects on the Environment
With the introduction of blockchain, trustless transactions between parties in different countries are now simple. The ability to enable robust and safe exchange between many sorts of tokens is a fundamental demand given the abundance of diverse tokens entering the cryptocurrency ecosystem. The bitcoin market's ICO boom has caused a stratospheric spike in the funding of research-based enterprises. The limited understanding of these various token types is preventing inexperienced developers from realizing the full potential of blockchain technology. Tokens, whether fungible or non-fungible, can represent a wide range of assets and science groups. This study's main goal is to provide a summary of tokens and a comparative analysis of token standards that are currently available in the cryptocurrency market.
Blockchain Based Architecture of Pharmaceutical Supply Chain Solution
The years 2020 and 2021 have witnessed unparalleled increment in demand for medical devices and resources due to the ongoing COVID-19 pandemic. An increase in demand also increased the presence of duplicate drugs within the market, and this poses a significant threat because it is difficult for human beings to apprehend the correct cost and best of purchased drugs because of a full-size loss of transparency within the modern gadgets. Also, tampering in the delivery chain is hard to locate whilst suspected of illegal or unethical practices. The majority of today's systems, procedures, and technology are inefficient in managing the medical equipment supply chain. Functionalities like reliability, traceability, security, operational transparency, decentralization, and trustworthiness are inadequate. This research gives an analysis of a decentralized Ethereum blockchain-based approach to enhance medical supply chain operations which enable data exchange amongst all the stakeholders involved to supply them in a completely secure, transparent, traceable, and trustworthy manner. Each product in the chain is typically transferred among authenticated chain entities using an event request-reaction mechanism. All transactions among entities are stored into the blockchain through the usage of clever contracts which can be immutable, and this provides us with product traceability to its supply.
Usability of Blockchain in Internet of Things
Internet of things commonly known as IoT is a technology that is helping in making life easier. It basically means connecting various devices that perform a specific task together on a network so that the devices can be accessed much more easily, and their accessibility can increase, though with the increase in technology, problems in IoT arise. Concerns like data security, access management and scalability arise. In this study, we identify those problems and see how using blockchain, the technology behind all cryptocurrency and being a distributed ledger with features like immutability on a distributed network these problems can be tackled. A single point of failure is created by the server/client model, which mandates that all devices connect to and are authenticated by the server. Therefore, it might be best to decentralize the Internet of Things system. One of the most common decentralized technologies is blockchain. The Blockchain is a potent technology that decentralizes administration and computation processes, which can address many IoT problems, particularly security. We come to the conclusion that combining blockchain and IoT can result in a potent strategy that can greatly open the door for new business models and distributed applications.
Securing Toll Booth Data Using Blockchain
Presently, blockchain has come up to be one of the most famous and assuring technologies in the smart transportation system. Smart vehicles communicate with each other through internet. Data sharing is important as it encourages more collaboration among the involved participants. So, in order to do secure data sharing in vehicular networks, we require a decentralized mechanism which is scalable and secured. Previously, the collection of road toll was done either manually or by using tools like Radio Frequency Identification (RFID). In this study, we are using blockchain technology for automated toll collection in the smart transportation system. It is a secure and more reliable technology. We have tried to make a decentralized system using blockchain. We have developed a model which uses smart contracts in blockchain for the payment of toll fee. Our work focuses on the better distribution of traffic on highways by diverting the traffic on toll booths with lower traffic. Also, the blockchain keeps the transactions track for every vehicle that passes from the toll.
Building Blockchain for Blood Bank Center
With population growth in India, numbers of disease increase, and related to disease, blood-bank plays an important role. Due to the huge increase in population, many of us suffer from various diseases; to fight against diseases, we require large supply of blood and we lack it most of the time. Even many of us have donated blood to various blood bank centers but no one has a record, whether it has reached the right person. To overcome this, let us createa database in blockchain and share records and details so that the system should be transparent. We can trace the record from the day it is donated to when it is received to required patient with all the blood types and samples.
Analysis of E-health Monitoring Systems and Its Uses
Health care has been one of the most crucial topics in the post COVID-19 era. Research have shown that people are more aware about their health now and are starting to take it seriously. Hence, even the healthcare system is now extended to online and electronic medium to provide assistance to people. E-health can provide assistance to people without any time and geographical bounds. This study will be used to understand the current usage of E-healthcare systems. The main objective of this web app project is to ease the health monitoring on daily basis, even doctors can fetch up patient through this app which can help in their business and admin on the other hand can have administrative functionalities like add, del, or alter doctor details for smooth functioning of the application. Proposed system is all in one which provides facilities of self-assessment and establishes communication between doctors and patients which the current system lacks. The input parameters for existing system are too technical for patients’ use which is countered in our system as we ask only simple inputs which is user-friendly.
Loan Prediction Using Random Forest Algorithm
With the growth of the banking sector, more and more people are applying for bank loans. All of these loans are not allowed. The principal income of bank assets arises from the interest earned on the loan. Bank profit or loss depends largely on the amount of the loan, i.e., whether customers pay off the loan or fail. The main purpose of banks is to invest their assets in secure customers. Today, many banks approve loans after a number of verifications and verification processes but yet there is no guarantee that the selected customer is safe or not. By predicting defaulters, the bank can reduce its non-performing Assets. This makes a study of this situation very important. Previous research in this period has shown that there are many ways to learn the problem of controlling loan default. But as appropriate predictions are very important for increase in profit, it is important to study the type of different methods and their comparisons. A very important method in predictive analysis is used to study the problem of predicting those who fail to borrow money. It is therefore important to use a variety of strategies in the banking sector to select a customer who pays the loan on time. In this report, we use a random forest algorithm to separate the data. The random forest algorithm creates a model from a trained database and this model is used in test data and we obtain the required output.
Blockchain Smart Contracts: Applications, Challenges, and Solutions
Blockchain technology has shown its importance in the fields of crypto-currency, medical record preservation, logistics supply chain industry, IoT (Internet of Things) and many more. In recent years, the growing development of blockchain technology and crypto-currencies has revolutionized the financial industry by creating a new crypto economy. The art of maintaining information in a decentralized, transparent and immutable manner makes blockchain one of the foremost means of handling information in various application areas. Even though there are various benefits to smart contracts, several issues continue to undermine their adoption, such as security threats, vulnerabilities, and legal issues. Various types have been discussed in this study. We have tried to showcase blockchain- enabled smart contracts from both technical and usage points of view within this research work. Therefore, we present a detailed bifurcation of existing blockchain-enabled smart contract solutions, categorize the included research papers, and discuss the existing smart contractbased use cases. And finally, we identify future trends.
As the database executive's field has expanded to include settings where questions are increasingly unpredictable, insights are less accessible, or information is put away remotely; there has been an affirmation that the accessible enhancement systems are inadequate. This has prompted plenty of new strategies, by and large set under the regular flag of enhancing complex inquiries that attention on revamping the unpredictable questions in a straightforward way. Question streamlining is the bottleneck of database application execution, particularly those which store history, for example, information distribution center. Inquiry optimization is the most required field these days, Late centre arrangements with communication and looking for information. To improve the presentation of the question results, it requires the advancement of information preparation time. This examination gives an exhaustive overview of various models and approaches utilized for question advancement to limit execution time and to improve asset use. We have been aiming for different research works done on query streamlining for traditional SQL and MapReduce stages.
RFID-based Tracking system in Warehouse using IOT
The global positioning framework in light of long reach radio frequency identification (RFID) has been sent in distribution center. There are numerous merchandise go through the door of the plant stockroom. To build the quantity of RFID labels recognition, the counter crash procedure is applied in RFID per user and tag. In this paper, the relative examination aftereffects of the particular three opened Aloha hostile to impact conventions, Q, QT and FQT-calculations are introduced. The adjusted RFID tag in view of FQT calculation has been joined in the stockroom. The products global positioning framework has been carried out and showed the constant stock by means of the portable application.
RFID, Anti-collision protocol, warehouse, tracking system