This document discusses using machine learning approaches to detect cyberbullying on social networks. It begins with an abstract that introduces the problem of cyberbullying and its negative impacts. It then discusses related work on using natural language processing and machine learning like SVM, neural networks, and co-training models to identify cyberbullying. The document aims to compare different machine learning algorithms (Naive Bayes, Decision Tree, Random Forest, SVM, DNN) to determine the most effective technique for detecting cyberbullying. It discusses preprocessing data and extracting features before applying the algorithms. The results will show which algorithm has the highest accuracy on a Twitter comment dataset.
Importance of cyber security in education sectorSeqrite
Data security in the education sector is incredibly important as the information collected by these institutes can be misused by hackers. This slideshare takes you through the security threats in education sector.
Importance of cyber security in education sectorSeqrite
Data security in the education sector is incredibly important as the information collected by these institutes can be misused by hackers. This slideshare takes you through the security threats in education sector.
Internet and computers have changed working, communication, meeting and business requirements and conditions all over globe. Due to this high profile technology, everyone can share any activity that was unexpected and unimaginable few decades back. It was the imagination of people that they will live their lives in this manner and do their business quickly and imagination and dream has come true with the introduction of internet only. Modern society is now associated with internet and related technologies, over a quarter of the world's population is wired into the net and this number is growing every day
This presentation is to analyze how Pantene was successful with its emotional TV commercial called "you can shine". The ad did not mention about the brand or the product during its 4 minutes of lenghth. However, it is a touching and unforgettable ad that went viral.
Internet and computers have changed working, communication, meeting and business requirements and conditions all over globe. Due to this high profile technology, everyone can share any activity that was unexpected and unimaginable few decades back. It was the imagination of people that they will live their lives in this manner and do their business quickly and imagination and dream has come true with the introduction of internet only. Modern society is now associated with internet and related technologies, over a quarter of the world's population is wired into the net and this number is growing every day
This presentation is to analyze how Pantene was successful with its emotional TV commercial called "you can shine". The ad did not mention about the brand or the product during its 4 minutes of lenghth. However, it is a touching and unforgettable ad that went viral.
Exploratory Data Analysis and Feature Selection for Social Media Hackers Pred...CSEIJJournal
In machine learning, the intelligence of a developed model is greatly influenced by the dataset used for the
target domain on which the developed model will be deployed. Social media platform has experienced
more of hackers’ attacks on the platform in recent time. To identify a hacker on the platform, there are two
possible ways. The first is to use the activities of the user while the second is to use the supplied details the
user registered the account with. To adequately identify a social media user as hacker proactively, there
are relevant user details called features that can be used to determine whether a social media user is a
hacker or not. In this paper, an exploratory data analysis was carried out to determine the best features
that can be used by a predictive model to proactively identify hackers on the social media platform. A web
crawler was developed to mine the user dataset on which exploratory data analysis was carried out to
select the best features for the dataset which could be used to correctly identify a hacker on a social media
platform.
EXPLORATORY DATA ANALYSIS AND FEATURE SELECTION FOR SOCIAL MEDIA HACKERS PRED...CSEIJJournal
In machine learning, the intelligence of a developed model is greatly influenced by the dataset used for the
target domain on which the developed model will be deployed. Social media platform has experienced
more of hackers’ attacks on the platform in recent time. To identify a hacker on the platform, there are two
possible ways. The first is to use the activities of the user while the second is to use the supplied details the
user registered the account with. To adequately identify a social media user as hacker proactively, there
are relevant user details called features that can be used to determine whether a social media user is a
hacker or not. In this paper, an exploratory data analysis was carried out to determine the best features
that can be used by a predictive model to proactively identify hackers on the social media platform. A web
crawler was developed to mine the user dataset on which exploratory data analysis was carried out to
select the best features for the dataset which could be used to correctly identify a hacker on a social media
platform.
Deterring Sybil Attack in Online Communication System via Peer-to-peer Audio ...Eswar Publications
In recent time the use of communication gadgets (mobile phones, laptop, desktop etc.) and service for online communication between two parties over a long distance has become sine-qua-non. Some criminal minded people are using this online communication method to deceive their prey via proxy communication where individual claiming to be discussing is not really the one. In this paper, we focus on prevention of identity impersonation attacks in an Online Communication System. Peer-peer Audio Visual Communication System is design to enhance security through online communication system by revealing the identity of the communicators and records the communication if necessary. Embedded application system was design for mobile and desktop devices for audio
visual charting using modern IT devices.
A MACHINE LEARNING ENSEMBLE MODEL FOR THE DETECTION OF CYBERBULLYINGijaia
The pervasive use of social media platforms, such as Facebook, Instagram, and X, has significantly amplified
our electronic interconnectedness. Moreover, these platforms are now easily accessible from any location at
any given time. However, the increased popularity of social media has also led to cyberbullying.It is imperative
to address the need for finding, monitoring, and mitigating cyberbullying posts on social media platforms.
Motivated by this necessity, we present this paper to contribute to developing an automated system for
detecting binary labels of aggressive tweets.Our study has demonstrated remarkable performance compared to
previous experiments on the same dataset. We employed the stacking ensemble machine learning method,
utilizing four various feature extraction techniques to optimize performance within the stacking ensemble
learning framework. Combining five machine learning algorithms,Decision Trees, Random Forest, Linear
Support Vector Classification, Logistic Regression, and K-Nearest Neighbors into an ensemble method, we
achieved superior results compared to traditional machine learning classifier models. The stacking classifier
achieved a high accuracy rate of 94.00%, outperforming traditional machine learning models and surpassing
the results of prior experiments that utilized the same dataset. The outcomes of our experiments showcased an
accuracy rate of 0.94% in detection tweets as aggressive or non-aggressive.
A Machine Learning Ensemble Model for the Detection of Cyberbullyinggerogepatton
The pervasive use of social media platforms, such as Facebook, Instagram, and X, has significantly amplified
our electronic interconnectedness. Moreover, these platforms are now easily accessible from any location at
any given time. However, the increased popularity of social media has also led to cyberbullying.It is imperative
to address the need for finding, monitoring, and mitigating cyberbullying posts on social media platforms.
Motivated by this necessity, we present this paper to contribute to developing an automated system for
detecting binary labels of aggressive tweets.Our study has demonstrated remarkable performance compared to
previous experiments on the same dataset. We employed the stacking ensemble machine learning method,
utilizing four various feature extraction techniques to optimize performance within the stacking ensemble
learning framework. Combining five machine learning algorithms,Decision Trees, Random Forest, Linear
Support Vector Classification, Logistic Regression, and K-Nearest Neighbors into an ensemble method, we
achieved superior results compared to traditional machine learning classifier models. The stacking classifier
achieved a high accuracy rate of 94.00%, outperforming traditional machine learning models and surpassing
the results of prior experiments that utilized the same dataset. The outcomes of our experiments showcased an
accuracy rate of 0.94% in detection tweets as aggressive or non-aggressive.
A Machine Learning Ensemble Model for the Detection of Cyberbullyinggerogepatton
The pervasive use of social media platforms, such as Facebook, Instagram, and X, has significantly amplified
our electronic interconnectedness. Moreover, these platforms are now easily accessible from any location at
any given time. However, the increased popularity of social media has also led to cyberbullying.It is imperative
to address the need for finding, monitoring, and mitigating cyberbullying posts on social media platforms.
Motivated by this necessity, we present this paper to contribute to developing an automated system for
detecting binary labels of aggressive tweets.Our study has demonstrated remarkable performance compared to
previous experiments on the same dataset. We employed the stacking ensemble machine learning method,
utilizing four various feature extraction techniques to optimize performance within the stacking ensemble
learning framework. Combining five machine learning algorithms,Decision Trees, Random Forest, Linear
Support Vector Classification, Logistic Regression, and K-Nearest Neighbors into an ensemble method, we
achieved superior results compared to traditional machine learning classifier models. The stacking classifier
achieved a high accuracy rate of 94.00%, outperforming traditional machine learning models and surpassing
the results of prior experiments that utilized the same dataset. The outcomes of our experiments showcased an
accuracy rate of 0.94% in detection tweets as aggressive or non-aggressive.
Hyperparameter optimization using custom genetic algorithm for classificatio...IJECEIAES
Hyperparameter optimization is one of the main challenges in deep learning despite its successful exploration in many areas such as image classification, speech recognition, natural language processing, and fraud detections. Hyperparameters are critical as they control the learning rate of a model and should be tuned to improve performance. Tuning the hyperparameters manually with default values is a challenging and time-intensive task. Though the time and efforts spent on tuning the hyperparameters are decreasing, it is always a burden when it comes to a new dataset or solving a new task or improving the existing model. In our paper, we propose a custom genetic algorithm to auto-tune the hyperparameters of the deep learning sequential model to classify benign and malicious traffic from internet of things-23 dataset captured by Czech Technical University, Czech Republic. The dataset is a collection of 30.85 million records of malicious and benign traffic. The experimental results show a promising outcome of 98.9% accuracy.
Similar to Cyberbullying Detection on Social Networks Using Machine Learning Approaches (20)
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.