A virtual interactive chatbot that helps to track expenditure and helps manage monthly expenditure and savings according to one’s own budget and stay's up to date with one’s savings, current and credit account.
Octopus is an open source MIS platform for microfinance institutions that allows users to manage customer information, loan tracking, accounting, and reporting in a secure online environment. As open source software, Octopus is free to use but users can pay for assistance from the Octopus community or company. The open source model aims to make the software affordable, adaptable to evolving needs, and securely upgradable without relying on expensive proprietary software licenses or consultants.
This document describes a proposed banking bot that would allow users to perform basic banking tasks through a chat interface. The bot would integrate a user's accounts from different banks and enable functions like adding beneficiaries, fund transfers, checking balances and viewing mini statements. It aims to provide an easier and more convenient banking experience compared to traditional methods. The technical components proposed include using machine learning and natural language processing algorithms to understand user queries. The bot would be developed using PHP and MySQL and deployed through a chat interface using Recast.AI. Testing plans include integration, compatibility and other types of testing. Screenshots provide examples of how the bot interface could enable tasks like adding beneficiaries and fund transfers.
Azure as a Chatbot Service: From Purpose To Production With A Cloud Bot Archi...Paul Prae
The document discusses chatbots and artificial intelligence. It provides examples of chatbots used in education to help students with admissions, enrollment, and academic support. It also describes the speaker's background and final school project building a conversational agent named Neona. Technologies discussed include Microsoft Azure Bot Service, LUIS, Azure Search, and Cosmos DB.
Conversational commerce/Conversational Banking means allowing customers worldwide, to text /chat/speak with the bank/retail stores, etc. as easily and conveniently as they text/chat /speak with their friends and family in messaging apps
Conversational Commerce with the help of NLP, Big data and AI will radically expedite digital transformation and offers customers a "zero learning curve" experience – no complex interface to navigate – where they can simply message in natural language with the bank or the retail store, etc. to ask questions and get service on their own terms and timetable.
The Moneyed app allows users to manage their finances in one place. It detects account balances, categorizes expenses as expenses or investments, and provides tips to help users meet savings goals and avoid overspending. The app has a user-friendly interface despite its complex features. It allows monitoring expenses, tracking investments and goals, viewing account balances, and setting bill reminders. Challenges included accessing SMS permissions and categorizing transaction messages. These were addressed through custom coding, natural language processing, and regular expressions. The app was developed using programming languages like Python and React Native for mobile platforms.
This document provides an overview of chat bot applications and related technologies. It discusses what a chat bot is, sample use cases for chat bots like providing commerce and information services, and platforms for developing and deploying chat bots like Azure Bot Service and Cognitive Services. Benefits of chat bots include reducing business costs by automating support, collecting user data to improve products, and providing 24/7 automated assistance to customers.
Einstein Function is an intelligent CRM system that helps build apps, streamline business processes and workflows for every function & industry.
Let's understand what Einstein Bot acts like and how it operates.
Octopus is an open source MIS platform for microfinance institutions that allows users to manage customer information, loan tracking, accounting, and reporting in a secure online environment. As open source software, Octopus is free to use but users can pay for assistance from the Octopus community or company. The open source model aims to make the software affordable, adaptable to evolving needs, and securely upgradable without relying on expensive proprietary software licenses or consultants.
This document describes a proposed banking bot that would allow users to perform basic banking tasks through a chat interface. The bot would integrate a user's accounts from different banks and enable functions like adding beneficiaries, fund transfers, checking balances and viewing mini statements. It aims to provide an easier and more convenient banking experience compared to traditional methods. The technical components proposed include using machine learning and natural language processing algorithms to understand user queries. The bot would be developed using PHP and MySQL and deployed through a chat interface using Recast.AI. Testing plans include integration, compatibility and other types of testing. Screenshots provide examples of how the bot interface could enable tasks like adding beneficiaries and fund transfers.
Azure as a Chatbot Service: From Purpose To Production With A Cloud Bot Archi...Paul Prae
The document discusses chatbots and artificial intelligence. It provides examples of chatbots used in education to help students with admissions, enrollment, and academic support. It also describes the speaker's background and final school project building a conversational agent named Neona. Technologies discussed include Microsoft Azure Bot Service, LUIS, Azure Search, and Cosmos DB.
Conversational commerce/Conversational Banking means allowing customers worldwide, to text /chat/speak with the bank/retail stores, etc. as easily and conveniently as they text/chat /speak with their friends and family in messaging apps
Conversational Commerce with the help of NLP, Big data and AI will radically expedite digital transformation and offers customers a "zero learning curve" experience – no complex interface to navigate – where they can simply message in natural language with the bank or the retail store, etc. to ask questions and get service on their own terms and timetable.
The Moneyed app allows users to manage their finances in one place. It detects account balances, categorizes expenses as expenses or investments, and provides tips to help users meet savings goals and avoid overspending. The app has a user-friendly interface despite its complex features. It allows monitoring expenses, tracking investments and goals, viewing account balances, and setting bill reminders. Challenges included accessing SMS permissions and categorizing transaction messages. These were addressed through custom coding, natural language processing, and regular expressions. The app was developed using programming languages like Python and React Native for mobile platforms.
This document provides an overview of chat bot applications and related technologies. It discusses what a chat bot is, sample use cases for chat bots like providing commerce and information services, and platforms for developing and deploying chat bots like Azure Bot Service and Cognitive Services. Benefits of chat bots include reducing business costs by automating support, collecting user data to improve products, and providing 24/7 automated assistance to customers.
Einstein Function is an intelligent CRM system that helps build apps, streamline business processes and workflows for every function & industry.
Let's understand what Einstein Bot acts like and how it operates.
In this presentation we'll cover an Introduction to Einstein Bots:
Introduction of Einstein
Introduction of Einstein Bot
Plan your Einstein Bot
Create an Einstein Bot
Steps to build Einstein Bot
Digital Transformation Services and Solutions - Chatbot DevelopmentPrajaktaKulkarni55
Nella: 85% of businesses will have customer interactions handled by some sort of chatbot by 2020
Nella is capable of taking the burden of time-consuming processes and serve its customers better by Processing information, solving queries, supporting a transaction, Taking orders, Promoting products and services and many more. Nella automatically can answer 65% of your Customer Support Queries and has multiple language support. Thus, customer service handled by Nella is quick and efficient.
The document discusses the opportunities presented by bots, including high demand from companies, the ability to create more natural experiences for users on messaging apps, and simpler deployment and updating than traditional apps. It provides an overview of the typical architecture of a bot, including components like the Bot Builder SDK, LUIS, and the Developer Portal. Several use cases for bots are presented, such as managing cloud resources from Skype, handling customer service, and acting as knowledgeable assistants. Guidelines for creating effective bots focus on solving users' needs with minimal effort and guiding users to discover what the bot can do.
The document summarizes a student project presentation on developing a ChatBot for a higher education system. It includes sections on motivation, objectives, literature review, requirements specification, proposed system design with flowchart, expected results, and conclusion. The motivation is to provide a chat facility for students to easily access course details and information to reduce the workload on instructional staff. The objective is to develop a chatbot using technologies like Python, JavaScript, and HTML/CSS that can answer student questions about coursework, assignments, and deadlines at any time. A literature review is presented covering past research on building chatbots. The proposed system design and flowchart are also included.
This document discusses different types of database interfaces. It introduces interfaces as programs that allow users to query databases without writing code. The main types discussed are form-based interfaces, menu-based interfaces, graphical user interfaces, natural language interfaces, speech-based interfaces, and interfaces for database administrators (DBAs). Examples are provided for each type to illustrate how they work.
Sara Tabor: Testing For Accessibility - ARIA Ready For It?Anna Royzman
The document discusses accessibility testing and compliance. It provides an overview of key accessibility laws and standards like Section 508, ADA, and WCAG 2.0. It also discusses different user personas with disabilities and examples of assistive technologies. The rest of the document outlines strategies for implementing accessibility testing throughout the development process from requirements gathering to post-launch maintenance.
All You Need To Know About Chatbot Development.pdfJPLoft Solutions
Chatbots could reduce your client service costs and waiting time. They're helpful for everyone. They also provide various services ranging from answering simple queries to handling more complex personal requests. Understanding chatbots and their functions will help you determine whether they're the right choice for your needs.
Introduction
In the modern banking landscape, virtual assistants have become increasingly popular tools for banks to enhance customer service, improve operational efficiency, and drive digital transformation. These virtual assistants, powered by artificial intelligence (AI) and natural language processing (NLP), offer a wide range of functionalities, from basic customer support to personalized financial advice. This article explores the role of virtual assistants in banking, their benefits, challenges, and future prospects.
Role of Virtual Assistants in Banking
Virtual assistants in banking serve as digital concierges, offering customers a convenient way to interact with their bank through voice or text interfaces. They can assist customers with a variety of tasks, such as checking account balances, transferring funds, paying bills, and even providing financial insights and advice. Virtual assistants can also help banks streamline their operations by automating routine tasks, such as answering frequently asked questions and processing simple transactions, freeing up human agents to focus on more complex issues.
Benefits of Virtual Assistants in Banking
Improved Customer Experience: Virtual assistants provide customers with instant, round-the-clock support, enhancing their overall banking experience.
Increased Efficiency: By automating routine tasks, virtual assistants help banks reduce operational costs and improve efficiency.
Personalized Service: Virtual assistants can analyze customer data to offer personalized financial advice and product recommendations.
24/7 Availability: Unlike human agents, virtual assistants are available 24/7, providing customers with access to banking services anytime, anywhere.
Scalability: Virtual assistants can handle multiple customer inquiries simultaneously, allowing banks to scale their customer service operations more effectively.
Data Analytics: Virtual assistants can analyze customer interactions to identify trends and patterns, which banks can use to improve their products and services.
Challenges of Virtual Assistants in Banking
Security Concerns: Virtual assistants may raise security concerns, especially when dealing with sensitive financial information. Banks need to ensure that their virtual assistants comply with strict security standards.
Integration Issues: Integrating virtual assistants with existing banking systems and processes can be challenging and may require significant time and resources.
Accuracy and Reliability: Virtual assistants need to be highly accurate and reliable, especially when providing financial advice or processing transactions.
User Adoption: Some customers may be hesitant to interact with virtual assistants, preferring traditional banking channels.
Regulatory Compliance: Virtual assistants need to comply with various regulations, such as data protection and privacy laws, which can vary across different jurisdictions.Future Prospects of Virtual Assistants in Banking
Scaling your product team in a fast growing companyThiga
Thomas Vuchot nous explique l’organisation produit chez Qonto : “Comment passer d’un seul PM à une organisation produit de 4 Product Managers et 3 designers en l’espace de 6 mois ?”
Ne manquez plus aucun RDV du Meetup LPCx
https://www.meetup.com/fr-FR/laproductconf-x/
The Software Challenges of Building Smart Chatbots - ICSE'21Jordi Cabot
Chatbots are popular solutions assisting humans in multiple fields, such as customer support or e-learning. However, building such applications has become a complex task requiring a high-level of expertise in a variety of technical domains. Chatbots need to integrate (AI-based) NLU components, but also connect to internal/external services, deploy on various platforms, etc.
The briefing will first cover the current landscape of chatbot frameworks. Then, we’ll get our hands dirty and create a few bots of increasing difficulty playing with aspects like entity recognition, sentiment analysis, event processing, or testing. By the end of the session, attendees will have all the keys to understand the main steps and obstacles to building a good chatbot.
Artificial Intelligence Virtual Assistants & ChatbotsaNumak & Company
Artificial Intelligence transforms different interfaces into interactive systems that can be interacted with using Natural Language Processing technology. Thus, businesses can offer voice-integrated smart self-service solutions to their customers with Natural Dialogue Solutions, which can be positioned in different areas ranging from IVR systems to virtual assistants, from chatbots to smart systems.
A study states that people are now spending more time in messaging apps than social networking applications. Messaging apps are in trend and chatbots are the future. Learn everything about the chatbots from history to types to working, right here.
This document describes a proposed chatbot system for conducting job interviews. The chatbot would automate parts of the interview process to reduce costs and overcome issues like human bias or fatigue. It would verify candidates, ask questions to evaluate them, and generate results and rankings to aid in hiring decisions. The chatbot uses natural language processing, text-to-speech, and sentiment analysis techniques. Its goal is to select suitable candidates for jobs in a more efficient manner than traditional human interviews. The system is still being designed and could be improved in the future by expanding its capabilities.
With lower budgets and staff available, chatbots may be the future of Extension support. Learn how we built our own Extension chatbot called "veggiebot" to help answer questions from the public.
This document provides an introduction to chatbots, including what they are, examples of popular chatbots, why businesses would need chatbots, different types of chatbots, and how chatbot technology works. Specifically, it defines chatbots as computer programs that simulate conversation through artificial intelligence and interact with users via chat interfaces. It lists common chatbots like ELIZA, Alice, and Mitsuku and discusses retrieval-based and generative chatbot models. The document also covers open vs closed domain conversations and short vs long conversations.
IRJET - A Study on Building a Web based Chatbot from ScratchIRJET Journal
This document presents a study on building a web-based chatbot from scratch. It discusses choosing between open and closed domain chatbots as well as retrieval and generative-based models. For technologies, it recommends using PHP, HTML, CSS, JavaScript for the front end and Python and MySQL for the back end. Ajax and JSON can be used for data transfer. The document provides an overview of the steps and considerations for developing a chatbot, including defining the scope, identifying intents and questions, and developing response logic.
INTELLIGENT CHATBOT FOR COLLEGE ENQUIRY SYSTEMIRJET Journal
The document describes a proposed intelligent chatbot system for answering student inquiries about a college. The chatbot would allow students to get information about admissions, fees, scholarships, course timetables, and required documents from anywhere at any time through natural language conversations. It uses techniques like pattern matching, artificial intelligence, machine learning and natural language processing to understand questions and provide relevant responses from its knowledge database. The goal is to streamline the student information process and reduce the workload on college staff.
IRJET- An Intelligent Behaviour Shown by Chatbot System for Banking in Ve...IRJET Journal
This document describes a proposed intelligent chatbot system for providing banking information and services in vernacular languages. The proposed chatbot would be able to identify user context and intent to dynamically generate responses in both English and Hindi. It would allow users to ask banking questions and receive responses without needing to physically visit a bank. The system architecture involves users registering and logging in, with sessions created for each user. The chatbot would use the Porter stemming algorithm and identify user intent through natural language processing to accurately answer questions. Responses could be static predefined answers or dynamically generated by a webhook. The goal is to effectively communicate between users and the banking chatbot system across languages.
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%.
In this presentation we'll cover an Introduction to Einstein Bots:
Introduction of Einstein
Introduction of Einstein Bot
Plan your Einstein Bot
Create an Einstein Bot
Steps to build Einstein Bot
Digital Transformation Services and Solutions - Chatbot DevelopmentPrajaktaKulkarni55
Nella: 85% of businesses will have customer interactions handled by some sort of chatbot by 2020
Nella is capable of taking the burden of time-consuming processes and serve its customers better by Processing information, solving queries, supporting a transaction, Taking orders, Promoting products and services and many more. Nella automatically can answer 65% of your Customer Support Queries and has multiple language support. Thus, customer service handled by Nella is quick and efficient.
The document discusses the opportunities presented by bots, including high demand from companies, the ability to create more natural experiences for users on messaging apps, and simpler deployment and updating than traditional apps. It provides an overview of the typical architecture of a bot, including components like the Bot Builder SDK, LUIS, and the Developer Portal. Several use cases for bots are presented, such as managing cloud resources from Skype, handling customer service, and acting as knowledgeable assistants. Guidelines for creating effective bots focus on solving users' needs with minimal effort and guiding users to discover what the bot can do.
The document summarizes a student project presentation on developing a ChatBot for a higher education system. It includes sections on motivation, objectives, literature review, requirements specification, proposed system design with flowchart, expected results, and conclusion. The motivation is to provide a chat facility for students to easily access course details and information to reduce the workload on instructional staff. The objective is to develop a chatbot using technologies like Python, JavaScript, and HTML/CSS that can answer student questions about coursework, assignments, and deadlines at any time. A literature review is presented covering past research on building chatbots. The proposed system design and flowchart are also included.
This document discusses different types of database interfaces. It introduces interfaces as programs that allow users to query databases without writing code. The main types discussed are form-based interfaces, menu-based interfaces, graphical user interfaces, natural language interfaces, speech-based interfaces, and interfaces for database administrators (DBAs). Examples are provided for each type to illustrate how they work.
Sara Tabor: Testing For Accessibility - ARIA Ready For It?Anna Royzman
The document discusses accessibility testing and compliance. It provides an overview of key accessibility laws and standards like Section 508, ADA, and WCAG 2.0. It also discusses different user personas with disabilities and examples of assistive technologies. The rest of the document outlines strategies for implementing accessibility testing throughout the development process from requirements gathering to post-launch maintenance.
All You Need To Know About Chatbot Development.pdfJPLoft Solutions
Chatbots could reduce your client service costs and waiting time. They're helpful for everyone. They also provide various services ranging from answering simple queries to handling more complex personal requests. Understanding chatbots and their functions will help you determine whether they're the right choice for your needs.
Introduction
In the modern banking landscape, virtual assistants have become increasingly popular tools for banks to enhance customer service, improve operational efficiency, and drive digital transformation. These virtual assistants, powered by artificial intelligence (AI) and natural language processing (NLP), offer a wide range of functionalities, from basic customer support to personalized financial advice. This article explores the role of virtual assistants in banking, their benefits, challenges, and future prospects.
Role of Virtual Assistants in Banking
Virtual assistants in banking serve as digital concierges, offering customers a convenient way to interact with their bank through voice or text interfaces. They can assist customers with a variety of tasks, such as checking account balances, transferring funds, paying bills, and even providing financial insights and advice. Virtual assistants can also help banks streamline their operations by automating routine tasks, such as answering frequently asked questions and processing simple transactions, freeing up human agents to focus on more complex issues.
Benefits of Virtual Assistants in Banking
Improved Customer Experience: Virtual assistants provide customers with instant, round-the-clock support, enhancing their overall banking experience.
Increased Efficiency: By automating routine tasks, virtual assistants help banks reduce operational costs and improve efficiency.
Personalized Service: Virtual assistants can analyze customer data to offer personalized financial advice and product recommendations.
24/7 Availability: Unlike human agents, virtual assistants are available 24/7, providing customers with access to banking services anytime, anywhere.
Scalability: Virtual assistants can handle multiple customer inquiries simultaneously, allowing banks to scale their customer service operations more effectively.
Data Analytics: Virtual assistants can analyze customer interactions to identify trends and patterns, which banks can use to improve their products and services.
Challenges of Virtual Assistants in Banking
Security Concerns: Virtual assistants may raise security concerns, especially when dealing with sensitive financial information. Banks need to ensure that their virtual assistants comply with strict security standards.
Integration Issues: Integrating virtual assistants with existing banking systems and processes can be challenging and may require significant time and resources.
Accuracy and Reliability: Virtual assistants need to be highly accurate and reliable, especially when providing financial advice or processing transactions.
User Adoption: Some customers may be hesitant to interact with virtual assistants, preferring traditional banking channels.
Regulatory Compliance: Virtual assistants need to comply with various regulations, such as data protection and privacy laws, which can vary across different jurisdictions.Future Prospects of Virtual Assistants in Banking
Scaling your product team in a fast growing companyThiga
Thomas Vuchot nous explique l’organisation produit chez Qonto : “Comment passer d’un seul PM à une organisation produit de 4 Product Managers et 3 designers en l’espace de 6 mois ?”
Ne manquez plus aucun RDV du Meetup LPCx
https://www.meetup.com/fr-FR/laproductconf-x/
The Software Challenges of Building Smart Chatbots - ICSE'21Jordi Cabot
Chatbots are popular solutions assisting humans in multiple fields, such as customer support or e-learning. However, building such applications has become a complex task requiring a high-level of expertise in a variety of technical domains. Chatbots need to integrate (AI-based) NLU components, but also connect to internal/external services, deploy on various platforms, etc.
The briefing will first cover the current landscape of chatbot frameworks. Then, we’ll get our hands dirty and create a few bots of increasing difficulty playing with aspects like entity recognition, sentiment analysis, event processing, or testing. By the end of the session, attendees will have all the keys to understand the main steps and obstacles to building a good chatbot.
Artificial Intelligence Virtual Assistants & ChatbotsaNumak & Company
Artificial Intelligence transforms different interfaces into interactive systems that can be interacted with using Natural Language Processing technology. Thus, businesses can offer voice-integrated smart self-service solutions to their customers with Natural Dialogue Solutions, which can be positioned in different areas ranging from IVR systems to virtual assistants, from chatbots to smart systems.
A study states that people are now spending more time in messaging apps than social networking applications. Messaging apps are in trend and chatbots are the future. Learn everything about the chatbots from history to types to working, right here.
This document describes a proposed chatbot system for conducting job interviews. The chatbot would automate parts of the interview process to reduce costs and overcome issues like human bias or fatigue. It would verify candidates, ask questions to evaluate them, and generate results and rankings to aid in hiring decisions. The chatbot uses natural language processing, text-to-speech, and sentiment analysis techniques. Its goal is to select suitable candidates for jobs in a more efficient manner than traditional human interviews. The system is still being designed and could be improved in the future by expanding its capabilities.
With lower budgets and staff available, chatbots may be the future of Extension support. Learn how we built our own Extension chatbot called "veggiebot" to help answer questions from the public.
This document provides an introduction to chatbots, including what they are, examples of popular chatbots, why businesses would need chatbots, different types of chatbots, and how chatbot technology works. Specifically, it defines chatbots as computer programs that simulate conversation through artificial intelligence and interact with users via chat interfaces. It lists common chatbots like ELIZA, Alice, and Mitsuku and discusses retrieval-based and generative chatbot models. The document also covers open vs closed domain conversations and short vs long conversations.
IRJET - A Study on Building a Web based Chatbot from ScratchIRJET Journal
This document presents a study on building a web-based chatbot from scratch. It discusses choosing between open and closed domain chatbots as well as retrieval and generative-based models. For technologies, it recommends using PHP, HTML, CSS, JavaScript for the front end and Python and MySQL for the back end. Ajax and JSON can be used for data transfer. The document provides an overview of the steps and considerations for developing a chatbot, including defining the scope, identifying intents and questions, and developing response logic.
INTELLIGENT CHATBOT FOR COLLEGE ENQUIRY SYSTEMIRJET Journal
The document describes a proposed intelligent chatbot system for answering student inquiries about a college. The chatbot would allow students to get information about admissions, fees, scholarships, course timetables, and required documents from anywhere at any time through natural language conversations. It uses techniques like pattern matching, artificial intelligence, machine learning and natural language processing to understand questions and provide relevant responses from its knowledge database. The goal is to streamline the student information process and reduce the workload on college staff.
IRJET- An Intelligent Behaviour Shown by Chatbot System for Banking in Ve...IRJET Journal
This document describes a proposed intelligent chatbot system for providing banking information and services in vernacular languages. The proposed chatbot would be able to identify user context and intent to dynamically generate responses in both English and Hindi. It would allow users to ask banking questions and receive responses without needing to physically visit a bank. The system architecture involves users registering and logging in, with sessions created for each user. The chatbot would use the Porter stemming algorithm and identify user intent through natural language processing to accurately answer questions. Responses could be static predefined answers or dynamically generated by a webhook. The goal is to effectively communicate between users and the banking chatbot system across languages.
Similar to Chatbot for personal finance tracking (20)
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%.
TIME DIVISION MULTIPLEXING TECHNIQUE FOR COMMUNICATION SYSTEMHODECEDSIET
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
Literature Review Basics and Understanding Reference Management.pptxDr Ramhari Poudyal
Three-day training on academic research focuses on analytical tools at United Technical College, supported by the University Grant Commission, Nepal. 24-26 May 2024
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Batteries -Introduction – Types of Batteries – discharging and charging of battery - characteristics of battery –battery rating- various tests on battery- – Primary battery: silver button cell- Secondary battery :Ni-Cd battery-modern battery: lithium ion battery-maintenance of batteries-choices of batteries for electric vehicle applications.
Fuel Cells: Introduction- importance and classification of fuel cells - description, principle, components, applications of fuel cells: H2-O2 fuel cell, alkaline fuel cell, molten carbonate fuel cell and direct methanol fuel cells.
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ML Based Model for NIDS MSc Updated Presentation.v2.pptx
Chatbot for personal finance tracking
1. CHATBOT FOR PERSONAL
FINANCE TRACKING
Submitted by,
Aathira N
Anagha M
Gautham S K
Christy Aby Varghese
Guided by,
Prof. Hazeena Yoosaf
Dept. of CSE
2. CONTENTS
• Objective
• Existing scenario
• Proposed system
• System requirements
• Modules
• Software components
• Working
• Functionalities
• Working model screenshots
• References
3. A chatbot is a computer program which
conducts a conversation via auditory or
textual methods.
4. OBJECTIVE
❖ To develop a virtual interactive chatbot that helps to track
expenditure
❖ Helps manage monthly expenditure and savings according to one’s
own budget
❖ To stay up to date with one’s savings, current and credit account
5. EXISTING SCENARIO
Managing money, sticking to a budget and even
handling investment decisions are done with personal finance
apps
• Mint
• Wally
• You need a budget(YNAB)
6. PROPOSED SYSTEM
The idea is to integrate finance tracking into a virtual chat interface
The chatbot gives personalised opinions for each customer/user.
Works as a budget assistant
Enter the monthly budget and expenses often
Users can ask questions about their balance, savings, etc.
7. SYSTEM REQUIREMENTS
Software Requirements
Frontend : Python
Backend : MySQL
Platform : Messenger
GUI : Tkinter
Dataset : Corpus
Libraries : Pretty table
Playsound
Chatterbot
NLTK
Hardware Requirements
System : PC
9. SOFTWARE COMPONENTS
• Python
Python is an easy to learn, powerful programming language. It has efficient high-
level data structures and a simple but effective approach to object-oriented programming.
Python’s elegant syntax and dynamic typing, together with its interpreted nature, make it an
ideal language for scripting and rapid application development in many areas on most
platforms.
10. CONT.…
• Tkinter
Tkinter is the standard GUI library for Python. Python when combined with Tkinter provides a fast
and easy way to create GUI applications. Tkinter provides a powerful object-oriented interface to the Tk
GUI toolkit.
• MySQL
MySQL is a freely available open source Relational Database Management System (RDBMS) that
uses Structured Query Language (SQL).SQL is the most popular language for adding, accessing and
managing content in a database. It is most noted for its quick processing, proven reliability, ease and
flexibility of use.
13. CONT.…
Chatbot
o To calculate money spent on various factors like rent, food, etc. on a daily and
monthly basis.
o To calculate the total income per month and plan a monthly budget.
o Analyse spending behavior and identifies opportunity to save money by using a
threshold
o Can view expenses and income in table mode.
14. CONT..
Chatbot
o Responses to general queries to make the conversation humane.
o Individual user login after checking the user id and password.
o Plays notification sound for all incoming and outgoing messages.
o Gives alert in case of invalid username or password
o To give alert/notification if a certain category exceeds the threshold or if savings is
too low
19. REFERENCES
[1] Minghui Qiu,Feng-Lin Li,Siyu Wang,Xing Gao,Yan Chen, Weipeng Zhao,Haiqing Chen,Jun
Huang,Wei Chu.2017. AliMe Chat: A Sequence to Sequence and Rerank based Chatbot Engine.
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics ,Vancouver,
Canada, July 30 - August 4, 2017. Association for Computational Linguistics
[2] Piotr Bojanowski, Edouard Grave, Armand Joulin, and Tomas Mikolov. 2016. Enriching word
vectors with subword information. arXiv preprint arXiv:1607.04606 .
[3] Kyunghyun Cho, Bart van Merrienboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares,
Holger Schwenk, and Yoshua Bengio. 2014. Learning phrase representations using rnn encoder–
decoder for statistical machine translation. In Proceedings of EMNLP. pages 1724–1734.