This document summarizes Day 3 of the Fintech Bootcamp hosted by QuantUniversity at Babson College in Boston. It discusses fintech opportunities in emerging markets like India, including social lending apps and crypto-based payment solutions. It also covers building robo-advisors, including key steps like defining investor goals, obtaining data, developing models, and allowing what-if scenarios and analytics. Machine learning techniques that could be used in robo-advisors are also summarized.
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This document discusses using machine learning algorithms to detect credit card fraud. It begins with an introduction to machine learning and its applications. A literature review covers previous research using algorithms like AdaBoost, decision trees, random forests, SVM and logistic regression for fraud detection. The proposed system architecture has five layers of control, including security checks, transaction blocking rules, scoring rules, and human investigators. Dimensionality reduction using PCA and classification with SVM are applied to transaction data. Data visualization with heatmaps is also discussed. The document concludes machine learning proves accurate for fraud detection and future work could explore additional algorithms.
PYTHON AND DATA SCIENCE FOR INVESTMENT PROFESSIONALSQuantUniversity
Join CFA Institute and QuantUniversity for an information session about the upcoming CFA Institute Professional Learning course: Python and Data Science for Investment professionals.
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The document discusses improving security for mobile banking by using steganography to hide transaction details in images, with the goal of addressing challenges with directly sending sensitive information over networks. It was written by students to fulfill requirements for a bachelor's degree in computer science and engineering. The introduction provides background on the growing importance of mobile content delivery and the special requirements of securing data on mobile devices with limited capabilities.
Right now, in most of the countries, inside the people ’s wallet, they probably have a the
couple of credit cards, an identification card, automatic machine teller cards (ATM card), and maybe a few other plastic cards. Without realizing it, these plastic cards havebecome a very important part of their life. Although smart card technology improves security and convenient but it is not used in a wide range in Middle East countries.
User acceptance is vital for further development of any fresh technology and smart card technology as well. One of the factors that can effect on the acceptance of smart card technology is users’ awareness. The goal of this study is to present a general overview of smart card technology and identify the smart card’s benefits, features and characteristics and moreover, the level of users’ knowledge and awareness about smart card technology will be evaluated. In order to achieve this goal, a survey was conducted among the international students of University Technology Malaysia to measure their awareness of smart technology
B. Narayanan is seeking a job as a Software Developer. He has 6 months of experience developing software in .NET and technologies like C#, ASP.NET, SQL Server and JavaScript. His most recent role was at AppXperts Pvt Ltd where he worked on two projects - Handshake, an Android app similar to Facebook, and IMedicly, a medical application that allows patients to request treatment and doctors to provide prescriptions. He has a Bachelor's degree in Computer Science and Engineering.
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This document summarizes Day 3 of the Fintech Bootcamp hosted by QuantUniversity at Babson College in Boston. It discusses fintech opportunities in emerging markets like India, including social lending apps and crypto-based payment solutions. It also covers building robo-advisors, including key steps like defining investor goals, obtaining data, developing models, and allowing what-if scenarios and analytics. Machine learning techniques that could be used in robo-advisors are also summarized.
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This document discusses using machine learning algorithms to detect credit card fraud. It begins with an introduction to machine learning and its applications. A literature review covers previous research using algorithms like AdaBoost, decision trees, random forests, SVM and logistic regression for fraud detection. The proposed system architecture has five layers of control, including security checks, transaction blocking rules, scoring rules, and human investigators. Dimensionality reduction using PCA and classification with SVM are applied to transaction data. Data visualization with heatmaps is also discussed. The document concludes machine learning proves accurate for fraud detection and future work could explore additional algorithms.
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Join CFA Institute and QuantUniversity for an information session about the upcoming CFA Institute Professional Learning course: Python and Data Science for Investment professionals.
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The document discusses improving security for mobile banking by using steganography to hide transaction details in images, with the goal of addressing challenges with directly sending sensitive information over networks. It was written by students to fulfill requirements for a bachelor's degree in computer science and engineering. The introduction provides background on the growing importance of mobile content delivery and the special requirements of securing data on mobile devices with limited capabilities.
Right now, in most of the countries, inside the people ’s wallet, they probably have a the
couple of credit cards, an identification card, automatic machine teller cards (ATM card), and maybe a few other plastic cards. Without realizing it, these plastic cards havebecome a very important part of their life. Although smart card technology improves security and convenient but it is not used in a wide range in Middle East countries.
User acceptance is vital for further development of any fresh technology and smart card technology as well. One of the factors that can effect on the acceptance of smart card technology is users’ awareness. The goal of this study is to present a general overview of smart card technology and identify the smart card’s benefits, features and characteristics and moreover, the level of users’ knowledge and awareness about smart card technology will be evaluated. In order to achieve this goal, a survey was conducted among the international students of University Technology Malaysia to measure their awareness of smart technology
B. Narayanan is seeking a job as a Software Developer. He has 6 months of experience developing software in .NET and technologies like C#, ASP.NET, SQL Server and JavaScript. His most recent role was at AppXperts Pvt Ltd where he worked on two projects - Handshake, an Android app similar to Facebook, and IMedicly, a medical application that allows patients to request treatment and doctors to provide prescriptions. He has a Bachelor's degree in Computer Science and Engineering.
This document outlines a project to create a website for a college. It includes sections on the problem statement, existing system, proposed system, software development lifecycle model, feasibility study, software requirements specification, design including ER diagram and DFDs, results including screenshots, limitations, and future scope. The goal is to provide students and visitors a centralized online platform for information on courses, facilities, events, notices, and a way for students to access academic records and certificates. It was developed using HTML, CSS, JavaScript, PHP and hosted on a local server. Screenshots show functional home, department, faculty, admission and profile pages.
IRJET- Credit Card Fraud Detection using Random ForestIRJET Journal
This document discusses using random forest machine learning algorithms to detect credit card fraud. It begins with an abstract that outlines using random forest classification on transaction data to improve fraud detection accuracy. The introduction then provides background on credit card fraud and how machine learning has been used for detection. It describes random forest as an advanced decision tree algorithm that can improve efficiency and accuracy over other methods. The paper proposes building a fraud detection model using random forest classification to analyze a transaction dataset and optimize result accuracy. Key performance metrics like accuracy, sensitivity and precision are evaluated.
In Banking Loan Approval Prediction Using Machine LearningIRJET Journal
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Fraud detection is a topic which is applicable to many industries including banking and financial sectors, insurances, government agencies, and low enforcement and more.Through the use of sophisticeted use of data mining tools, millions of transactions can be searched to spot patterns and detect fraudulent transactions.
Its a process of identifying fraudulent transaction.
This technique used to recognize fraudulent creddit card transactions so that customers are not charged for items that they did not purchases
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My internship work as Business analyst Intern. This is a Full Circle Business Analysis for mobile app to register a new vehicle insurance (adopted for Ukraine)
The use of Data Science and Machine learning in the investment industry is increasing, and investment professionals, both fundamental and quantitative, are taking notice. Financial firms are taking AI and machine learning seriously to augment traditional investment decision making. Alternative data sets including text analytics, cloud computing, and algorithmic trading are game changers for many firms who are adopting technology at a rapid pace. As more and more technologies penetrate enterprises, financial professionals are enthusiastic about the upcoming revolution and are looking for direction and education on data science and machine learning topics.
In this webinar, we aim to bring clarity to how AI and machine learning is revolutionizing financial services. We will introduce key concepts and through examples and case studies, we will illustrate the role of machine learning, data science techniques, and AI in the investment industry. At the end of this webinar, participants will see a concrete picture of how machine learning and AI techniques are fueling the Fintech wave!
This document proposes using blockchain technology to address issues with fake driving licenses and vehicle smuggling through centralized databases. It outlines developing a decentralized system using smart contracts and distributed ledgers to securely store identity and vehicle registration data in a tamper-proof manner. The document discusses analyzing existing centralized systems, developing a blockchain solution, deploying a smart contract on the Ropsten test network, and potential future applications like integrating the system with transportation companies.
This document proposes a low-cost enhanced authentication service for ATM and POS transactions. It analyzes the limitations of the current system, such as static PINs and easy-to-copy magnetic strips. The proposed solution would outsource authentication to a common hub supporting dynamic OTPs over different channels like SMS. This could help reduce fraud incidents while maintaining PCI security standards at a lower cost than existing options. However, the system would still rely on the instability of TCP/IP networks and require changes to enterprise mindsets and legal frameworks.
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This document proposes an OCR detection and biometric authenticated credit card payment system. It aims to simplify online transactions by using fingerprint authentication and OCR to detect credit/debit card details from images, reducing the multi-step verification process to a single step. The system utilizes convolutional neural networks for OCR and fingerprint authentication via web authentication standards. It analyzes the architecture and implementation steps for OCR detection and fingerprint verification. The document concludes the proposed system could increase security for credit card companies and help reduce online transaction fraud.
The document introduces data science and analytics, covering the following key points:
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- It discusses the history and importance of data science, as well as its applications across different industries such as ecommerce, healthcare, and marketing.
- It outlines the various jobs and roles in the data science ecosystem, including data analysts, data scientists, data engineers, and analytics consultants, as well as the marketable skills required for each.
- It provides advice on how to start a career in data science, including recommended technologies and skills to learn, as well as resources for building a portfolio.
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This document proposes a new application for Know Your Customer (KYC) authentication using blockchain technology. The current KYC process is lengthy and expensive for both financial institutions and customers. The authors developed a proof-of-concept application using Ethereum, websites as endpoints, and an Android app. Their proposed system would reduce costs for institutions by performing KYC verification only once per customer, regardless of how many institutions they use. It would also improve transparency by securely sharing verification results using blockchain databases. The document outlines the background, methodology, design aspects, and experimental results of their proposed decentralized KYC application based on distributed ledger technology.
Rajeswari G provides her contact information and work experience. She has over 5 years of experience as a Software Engineer at TCS and previously worked as a Lecturer. Her skills include Java/J2EE, SQL, HTML, and she has experience developing applications using tools like Eclipse and RAD. At TCS, she has worked on projects for Citi Bank involving credit card applications and enhancing transactions. Responsibilities included analysis, documentation, development, testing, and post-release tasks.
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This document summarizes a student project on developing an image-based attendance system using face recognition. It was submitted by two students, Swarup Das and Somodeep Seal, to fulfill the requirements for a Bachelor of Technology degree. The project involved building a system that can automatically detect faces in images and identify students to mark attendance. It aimed to streamline the attendance process and reduce administrative work for faculty compared to traditional paper-based methods. The document includes sections on background, methodology, implementation, results and future work. It discusses using computer vision and machine learning algorithms like Haar cascade for face detection and recognition.
Vending machines are outdated as they only accept physical coins and do not allow for consumption monitoring or notify vendors when items need to be refilled. The solution proposed is smart vending machines that accept online and contactless payments, provide consumption analysis, and have a smart interface for users and statistics for vendors. The team proposes to develop a customer interface, web application, local server and other hardware/software to create smart vending machines, targeting their initial release within 12 months for schools and expanding to other markets over time.
10 Key Considerations for AI/ML Model GovernanceQuantUniversity
This document is a summary of a presentation by Sri Krishnamurthy on key considerations for AI/ML model governance. The presentation covered 10 best practices for an effective model risk management program, including adopting a framework-driven approach, customizing the program to the organization, defining roles and responsibilities, integrating model risk management into the model lifecycle, and monitoring model health. It also provided a case study on sentiment analysis of earnings calls using various APIs and building an internal model. The presentation emphasized challenges in moving models from development to production and the need for fairness, explainability and tracking of models.
This document describes an Android application called AMIZONER that was created to allow students to easily check their attendance records from Amity University's student portal. The application logs into the student portal using HTTPS, parses the attendance details, stores them locally in an SQLite database. It then displays the computed attendance information to users in a user-friendly way. The application was created using technologies like HTTPS POST/GET, HTML parsing, SQLite database, and the Android platform. It also includes features for server-client communication using Google App Engine and monitoring application usage with Google Analytics and monetization with advertisements.
1) He discussed several mobile applications for tasks like daily reporting, punchlisting, inspections, photo management, and design collaboration. 2) He explained how these applications can streamline workflows by making information accessible remotely and eliminating paper-based processes. 3) His presentation provided an overview of how construction companies can evaluate technology needs, test applications, and incorporate useful tools to improve project management.
1. The document describes a tour and travel management system developed by students to allow users to book travel packages and hotels online.
2. The system was developed with HTML, CSS, PHP, JavaScript, and Bootstrap for the front end and Java for the back end. It includes modules for admins, employees, packages, hotels, and customers.
3. Customers can register online, view packages and hotels, book orders, and make payments. The system aims to provide a convenient online booking experience for users.
A review on techniques and modelling methodologies used for checking electrom...nooriasukmaningtyas
The proper function of the integrated circuit (IC) in an inhibiting electromagnetic environment has always been a serious concern throughout the decades of revolution in the world of electronics, from disjunct devices to today’s integrated circuit technology, where billions of transistors are combined on a single chip. The automotive industry and smart vehicles in particular, are confronting design issues such as being prone to electromagnetic interference (EMI). Electronic control devices calculate incorrect outputs because of EMI and sensors give misleading values which can prove fatal in case of automotives. In this paper, the authors have non exhaustively tried to review research work concerned with the investigation of EMI in ICs and prediction of this EMI using various modelling methodologies and measurement setups.
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
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This document proposes using blockchain technology to address issues with fake driving licenses and vehicle smuggling through centralized databases. It outlines developing a decentralized system using smart contracts and distributed ledgers to securely store identity and vehicle registration data in a tamper-proof manner. The document discusses analyzing existing centralized systems, developing a blockchain solution, deploying a smart contract on the Ropsten test network, and potential future applications like integrating the system with transportation companies.
This document proposes a low-cost enhanced authentication service for ATM and POS transactions. It analyzes the limitations of the current system, such as static PINs and easy-to-copy magnetic strips. The proposed solution would outsource authentication to a common hub supporting dynamic OTPs over different channels like SMS. This could help reduce fraud incidents while maintaining PCI security standards at a lower cost than existing options. However, the system would still rely on the instability of TCP/IP networks and require changes to enterprise mindsets and legal frameworks.
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Time Division Multiplexing (TDM) is a method of transmitting multiple signals over a single communication channel by dividing the signal into many segments, each having a very short duration of time. These time slots are then allocated to different data streams, allowing multiple signals to share the same transmission medium efficiently. TDM is widely used in telecommunications and data communication systems.
### How TDM Works
1. **Time Slots Allocation**: The core principle of TDM is to assign distinct time slots to each signal. During each time slot, the respective signal is transmitted, and then the process repeats cyclically. For example, if there are four signals to be transmitted, the TDM cycle will divide time into four slots, each assigned to one signal.
2. **Synchronization**: Synchronization is crucial in TDM systems to ensure that the signals are correctly aligned with their respective time slots. Both the transmitter and receiver must be synchronized to avoid any overlap or loss of data. This synchronization is typically maintained by a clock signal that ensures time slots are accurately aligned.
3. **Frame Structure**: TDM data is organized into frames, where each frame consists of a set of time slots. Each frame is repeated at regular intervals, ensuring continuous transmission of data streams. The frame structure helps in managing the data streams and maintaining the synchronization between the transmitter and receiver.
4. **Multiplexer and Demultiplexer**: At the transmitting end, a multiplexer combines multiple input signals into a single composite signal by assigning each signal to a specific time slot. At the receiving end, a demultiplexer separates the composite signal back into individual signals based on their respective time slots.
### Types of TDM
1. **Synchronous TDM**: In synchronous TDM, time slots are pre-assigned to each signal, regardless of whether the signal has data to transmit or not. This can lead to inefficiencies if some time slots remain empty due to the absence of data.
2. **Asynchronous TDM (or Statistical TDM)**: Asynchronous TDM addresses the inefficiencies of synchronous TDM by allocating time slots dynamically based on the presence of data. Time slots are assigned only when there is data to transmit, which optimizes the use of the communication channel.
### Applications of TDM
- **Telecommunications**: TDM is extensively used in telecommunication systems, such as in T1 and E1 lines, where multiple telephone calls are transmitted over a single line by assigning each call to a specific time slot.
- **Digital Audio and Video Broadcasting**: TDM is used in broadcasting systems to transmit multiple audio or video streams over a single channel, ensuring efficient use of bandwidth.
- **Computer Networks**: TDM is used in network protocols and systems to manage the transmission of data from multiple sources over a single network medium.
### Advantages of TDM
- **Efficient Use of Bandwidth**: TDM all
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Presentation at IcETRAN 2024 session:
"Inter-Society Networking Panel GRSS/MTT-S/CIS
Panel Session: Promoting Connection and Cooperation"
IEEE Slovenia GRSS
IEEE Serbia and Montenegro MTT-S
IEEE Slovenia CIS
11TH INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONIC AND COMPUTING ENGINEERING
3-6 June 2024, Niš, Serbia
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTjpsjournal1
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELgerogepatton
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesChristina Lin
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
ACEP Magazine edition 4th launched on 05.06.2024Rahul
This document provides information about the third edition of the magazine "Sthapatya" published by the Association of Civil Engineers (Practicing) Aurangabad. It includes messages from current and past presidents of ACEP, memories and photos from past ACEP events, information on life time achievement awards given by ACEP, and a technical article on concrete maintenance, repairs and strengthening. The document highlights activities of ACEP and provides a technical educational article for members.
1. Department : Computer Science and Engineering
Title : Credit Card Fraud Detection
Guide : Mrs. Simran Choudhary (Assistant Professor)
Ravikant Vijayvargiya and Gajendra Saraswat • 18.09.2020
2. Overview
❖ Introduction to Credit Card
Fraud Detection.
❖ Introduction to Data
❖ Model Training
❖ Creating Web App
❖ Sneak Peek into Our Web App
❖ Conclusion
❖ References
2