This document proposes using evolutionary algorithms and support vector machine (SVM) classification to detect phishing attacks more effectively than existing techniques. It summarizes previous approaches like blacklisting, neuro-fuzzy systems, and discusses their limitations in terms of feature extraction time and training requirements. The proposed system extracts URL features, trains an SVM model on a dataset of phishing and legitimate sites, then classifies new URLs based on a threshold derived from their feature values. It is claimed this approach reduces time consumption, increases processing speed, and achieves over 99% accuracy in detecting phishing sites.
In spite of the development of aversion strategies, phishing remains an essential risk even after the
primary countermeasures and in view of receptive URL blacklisting. This strategy is insufficient because of the
short lifetime of phishing websites. In order to overcome this problem, developing a real-time phishing website
detection method is an effective solution. This research introduces the PrePhish algorithm which is an automated
machine learning approach to analyze phishing and non-phishing URL to produce reliable result. It represents that
phishing URLs typically have couple of connections between the part of the registered domain level and the path
or query level URL. Using these connections URL is characterized by inter-relatedness and it estimates using
features mined from attributes. These features are then used in machine learning technique to detect phishing
URLs from a real dataset. The classification of phishing and non-phishing website has been implemented by
finding the range value and threshold value for each attribute using decision making classification. This method is
also evaluated in Matlab using three major classifiers SVM, Random Forest and Naive Bayes to find how it works
on the dataset assessed
In spite of the development of aversion strategies, phishing remains an essential risk even after the
primary countermeasures and in view of receptive URL blacklisting. This strategy is insufficient because of the
short lifetime of phishing websites. In order to overcome this problem, developing a real-time phishing website
detection method is an effective solution. This research introduces the PrePhish algorithm which is an automated
machine learning approach to analyze phishing and non-phishing URL to produce reliable result. It represents that
phishing URLs typically have couple of connections between the part of the registered domain level and the path
or query level URL. Using these connections URL is characterized by inter-relatedness and it estimates using
features mined from attributes. These features are then used in machine learning technique to detect phishing
URLs from a real dataset. The classification of phishing and non-phishing website has been implemented by
finding the range value and threshold value for each attribute using decision making classification. This method is
also evaluated in Matlab using three major classifiers SVM, Random Forest and Naive Bayes to find how it works
on the dataset assessed
Review of the machine learning methods in the classification of phishing attackjournalBEEI
The development of computer networks today has increased rapidly. This can be seen based on the trend of computer users around the world, whereby they need to connect their computer to the Internet. This shows that the use of Internet networks is very important, whether for work purposes or access to social media accounts. However, in widely using this computer network, the privacy of computer users is in danger, especially for computer users who do not install security systems in their computer. This problem will allow hackers to hack and commit network attacks. This is very dangerous, especially for Internet users because hackers can steal confidential information such as bank login account or social media login account. The attacks that can be made include phishing attacks. The goal of this study is to review the types of phishing attacks and current methods used in preventing them. Based on the literature, the machine learning method is widely used to prevent phishing attacks. There are several algorithms that can be used in the machine learning method to prevent these attacks. This study focused on an algorithm that was thoroughly made and the methods in implementing this algorithm are discussed in detail.
Detecting malicious URLs using binary classification through ada boost algori...IJECEIAES
Malicious Uniform Resource Locator (URL) is a frequent and severe menace to cybersecurity. Malicious URLs are used to extract unsolicited information and trick inexperienced end users as a sufferer of scams and create losses of billions of money each year. It is crucial to identify and appropriately respond to such URLs. Usually, this discovery is made by the practice and use of blacklists in the cyber world. However, blacklists cannot be exhaustive, and cannot recognize zero-day malicious URLs. So to increase the observation of malicious URL indicators, machine learning procedures should be incorporated. In this study, we have developed a complete prototype of Malicious URL Detection using machine learning methods. In particular, we have attempted an exact formulation of Malicious URL exposure from a machine learning perspective and proposed an approach using the AdaBoost algorithm - the proposed approach has brought forward more accuracy than other existing algorithms.
Author: Dr Sandeep Sood
Password-based authentication is used in online web applications due to its simplicity and convenience. Efficient password-based authentication schemes are required to authenticate the legitimacy of remote users, or data origin over an insecure communication channel. Password-based authentication schemes are highly susceptible to phishing attacks.
CERT STRATEGY TO DEAL WITH PHISHING ATTACKScsandit
Every day, internet thieves employ new ways to obtain personal identity people and get access
to their personal information. Phishing is a somehow complex method that has recently been
considered by internet thieves. First, the present study aims to explain phishing, and why an
organization should deal with it and its challenges of providing. In addition, different kinds of
this attack and classification of security approaches for organizational and lay users are
addressed in this article. Finally, the CERT strategy – which relies on three principles of
informing, supporting and helping- is presented to deal with phishing and studying some antiphishing.
Phishing detection in ims using domain ontology and cba an innovative rule ...ijistjournal
User ignorance towards the use of communication services like Instant Messengers, emails, websites, social networks etc. is becoming the biggest advantage for phishers. It is required to create technical awareness in users by educating them to create a phishing detection application which would generate phishing alerts for the user so that phishing messages are not ignored. The lack of basic security features to detect and prevent phishing has had a profound effect on the IM clients, as they lose their faith in e-banking and e-commerce transactions, which will have a disastrous impact on the corporate and banking sectors and businesses which rely heavily on the internet.Very little research contributions were available in for phishing detection in Instant messengers. A context
based, dynamic and intelligent phishing detection
methodology in IMs is proposed, to analyze and detect phishing in Instant Messages with relevance to domain ontology (OBIE) and utilizes the Classification based on Association (CBA) for generating phishing rules and alerting the victims. A PDS Monitoring system algorithm is used to identify the phishing activity during exchange of messages in IMs, with high ratio of precision and recall. The results have shown improvement by the increased percentage of precision and recall when compared to the existing methods.
DDSGA: A Data-Driven Semi-Global Alignment Approach for Detecting Masquerade ...1crore projects
IEEE PROJECTS 2015
1 crore projects is a leading Guide for ieee Projects and real time projects Works Provider.
It has been provided Lot of Guidance for Thousands of Students & made them more beneficial in all Technology Training.
Dot Net
DOTNET Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
Java Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
ECE IEEE Projects 2015
1. Matlab project
2. Ns2 project
3. Embedded project
4. Robotics project
Eligibility
Final Year students of
1. BSc (C.S)
2. BCA/B.E(C.S)
3. B.Tech IT
4. BE (C.S)
5. MSc (C.S)
6. MSc (IT)
7. MCA
8. MS (IT)
9. ME(ALL)
10. BE(ECE)(EEE)(E&I)
TECHNOLOGY USED AND FOR TRAINING IN
1. DOT NET
2. C sharp
3. ASP
4. VB
5. SQL SERVER
6. JAVA
7. J2EE
8. STRINGS
9. ORACLE
10. VB dotNET
11. EMBEDDED
12. MAT LAB
13. LAB VIEW
14. Multi Sim
CONTACT US
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
Keystroke with Data Leakage Detection for Secure Email AuthenticationYogeshIJTSRD
The user authentication is the important factor which allows the user to use a particular software. The user authentication is also performed in various kinds of social media such as Gmail, Facebook, etc. The traditional password system is used for user authentication. But this technique has a lot of demerits in it. Some hackers also cracks the password and perform some unwanted actions in the user authentication. In order to remove the difficulties in this traditional password technique and to provide additional security in user authentication, the keystroke with data leakage detection for secure email authentication is designed. This system uses Keystroke Dynamics. This system consists of five different types of modules such as Email Framework Construction, User Enrolment, Keystroke Authentication, Data Sharing and Data Leakage Detection. This system gets the details of the user such as name and email. Then it allows to enter the password. This password is stored along with the keystroke dynamics data such as the typing speed of the password and the threshold value. Both the Keystroke dynamics data and the original password are stored in the database. When the user wants to log into the system, the user has to give the password according to the keystroke dynamics data. Then only, the user can log into the system. Hence this system can also be used in Cyber security and provide security and privacy for the user data. Mrs. V. Hemalatha | V. Boominathan | K. Harithas | P. Raj Kumar | S. Vijaya Bharathi "Keystroke with Data Leakage Detection for Secure Email Authentication" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-3 , April 2021, URL: https://www.ijtsrd.com/papers/ijtsrd39969.pdf Paper URL: https://www.ijtsrd.com/computer-science/computer-security/39969/keystroke-with-data-leakage-detection-for-secure-email-authentication/mrs-v-hemalatha
Phishing is a social engineering Technique which they main aim is to target the user Information like user id, password, credit card information and so on. Which result a financial loss to the user. Detecting Phishing is the one of the challenge problem that relay to human vulnerabilities. This paper proposed the Detecting Phishing Web Sites using different Machine Learning Approaches. In this to evaluate different classification models to predict malicious and benign websites by using Machine Learning Algorithms. Experiments are performed on data set consisting malicious and benign, In This paper the results shows the proposed Algorithms has high detection accuracy. Nakkala Srinivas Mudiraj ""Detecting Phishing using Machine Learning"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23755.pdf
Paper URL: https://www.ijtsrd.com/computer-science/computer-security/23755/detecting-phishing-using-machine-learning/nakkala-srinivas-mudiraj
A novel way of integrating voice recognition and one time passwords to preven...ijdpsjournal
Phishing is a threat to all users of the internet who intend to use the web for secure transactions. In the
recent years the number of phishing attacks have increased drastically especially since the advent of ecommerce,
net banking and other services that have an emphasis on security. Phishing is characterized as
any malicious attack aided by a spoofed webpage to encourage users to input their security details.
Phishing is largely done to retrieve passwords and security details of unsuspecting users. This paper
details a new and more secure way to counteract the method of phishing
Review of the machine learning methods in the classification of phishing attackjournalBEEI
The development of computer networks today has increased rapidly. This can be seen based on the trend of computer users around the world, whereby they need to connect their computer to the Internet. This shows that the use of Internet networks is very important, whether for work purposes or access to social media accounts. However, in widely using this computer network, the privacy of computer users is in danger, especially for computer users who do not install security systems in their computer. This problem will allow hackers to hack and commit network attacks. This is very dangerous, especially for Internet users because hackers can steal confidential information such as bank login account or social media login account. The attacks that can be made include phishing attacks. The goal of this study is to review the types of phishing attacks and current methods used in preventing them. Based on the literature, the machine learning method is widely used to prevent phishing attacks. There are several algorithms that can be used in the machine learning method to prevent these attacks. This study focused on an algorithm that was thoroughly made and the methods in implementing this algorithm are discussed in detail.
Detecting malicious URLs using binary classification through ada boost algori...IJECEIAES
Malicious Uniform Resource Locator (URL) is a frequent and severe menace to cybersecurity. Malicious URLs are used to extract unsolicited information and trick inexperienced end users as a sufferer of scams and create losses of billions of money each year. It is crucial to identify and appropriately respond to such URLs. Usually, this discovery is made by the practice and use of blacklists in the cyber world. However, blacklists cannot be exhaustive, and cannot recognize zero-day malicious URLs. So to increase the observation of malicious URL indicators, machine learning procedures should be incorporated. In this study, we have developed a complete prototype of Malicious URL Detection using machine learning methods. In particular, we have attempted an exact formulation of Malicious URL exposure from a machine learning perspective and proposed an approach using the AdaBoost algorithm - the proposed approach has brought forward more accuracy than other existing algorithms.
Author: Dr Sandeep Sood
Password-based authentication is used in online web applications due to its simplicity and convenience. Efficient password-based authentication schemes are required to authenticate the legitimacy of remote users, or data origin over an insecure communication channel. Password-based authentication schemes are highly susceptible to phishing attacks.
CERT STRATEGY TO DEAL WITH PHISHING ATTACKScsandit
Every day, internet thieves employ new ways to obtain personal identity people and get access
to their personal information. Phishing is a somehow complex method that has recently been
considered by internet thieves. First, the present study aims to explain phishing, and why an
organization should deal with it and its challenges of providing. In addition, different kinds of
this attack and classification of security approaches for organizational and lay users are
addressed in this article. Finally, the CERT strategy – which relies on three principles of
informing, supporting and helping- is presented to deal with phishing and studying some antiphishing.
Phishing detection in ims using domain ontology and cba an innovative rule ...ijistjournal
User ignorance towards the use of communication services like Instant Messengers, emails, websites, social networks etc. is becoming the biggest advantage for phishers. It is required to create technical awareness in users by educating them to create a phishing detection application which would generate phishing alerts for the user so that phishing messages are not ignored. The lack of basic security features to detect and prevent phishing has had a profound effect on the IM clients, as they lose their faith in e-banking and e-commerce transactions, which will have a disastrous impact on the corporate and banking sectors and businesses which rely heavily on the internet.Very little research contributions were available in for phishing detection in Instant messengers. A context
based, dynamic and intelligent phishing detection
methodology in IMs is proposed, to analyze and detect phishing in Instant Messages with relevance to domain ontology (OBIE) and utilizes the Classification based on Association (CBA) for generating phishing rules and alerting the victims. A PDS Monitoring system algorithm is used to identify the phishing activity during exchange of messages in IMs, with high ratio of precision and recall. The results have shown improvement by the increased percentage of precision and recall when compared to the existing methods.
DDSGA: A Data-Driven Semi-Global Alignment Approach for Detecting Masquerade ...1crore projects
IEEE PROJECTS 2015
1 crore projects is a leading Guide for ieee Projects and real time projects Works Provider.
It has been provided Lot of Guidance for Thousands of Students & made them more beneficial in all Technology Training.
Dot Net
DOTNET Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
Java Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
ECE IEEE Projects 2015
1. Matlab project
2. Ns2 project
3. Embedded project
4. Robotics project
Eligibility
Final Year students of
1. BSc (C.S)
2. BCA/B.E(C.S)
3. B.Tech IT
4. BE (C.S)
5. MSc (C.S)
6. MSc (IT)
7. MCA
8. MS (IT)
9. ME(ALL)
10. BE(ECE)(EEE)(E&I)
TECHNOLOGY USED AND FOR TRAINING IN
1. DOT NET
2. C sharp
3. ASP
4. VB
5. SQL SERVER
6. JAVA
7. J2EE
8. STRINGS
9. ORACLE
10. VB dotNET
11. EMBEDDED
12. MAT LAB
13. LAB VIEW
14. Multi Sim
CONTACT US
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
Keystroke with Data Leakage Detection for Secure Email AuthenticationYogeshIJTSRD
The user authentication is the important factor which allows the user to use a particular software. The user authentication is also performed in various kinds of social media such as Gmail, Facebook, etc. The traditional password system is used for user authentication. But this technique has a lot of demerits in it. Some hackers also cracks the password and perform some unwanted actions in the user authentication. In order to remove the difficulties in this traditional password technique and to provide additional security in user authentication, the keystroke with data leakage detection for secure email authentication is designed. This system uses Keystroke Dynamics. This system consists of five different types of modules such as Email Framework Construction, User Enrolment, Keystroke Authentication, Data Sharing and Data Leakage Detection. This system gets the details of the user such as name and email. Then it allows to enter the password. This password is stored along with the keystroke dynamics data such as the typing speed of the password and the threshold value. Both the Keystroke dynamics data and the original password are stored in the database. When the user wants to log into the system, the user has to give the password according to the keystroke dynamics data. Then only, the user can log into the system. Hence this system can also be used in Cyber security and provide security and privacy for the user data. Mrs. V. Hemalatha | V. Boominathan | K. Harithas | P. Raj Kumar | S. Vijaya Bharathi "Keystroke with Data Leakage Detection for Secure Email Authentication" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-3 , April 2021, URL: https://www.ijtsrd.com/papers/ijtsrd39969.pdf Paper URL: https://www.ijtsrd.com/computer-science/computer-security/39969/keystroke-with-data-leakage-detection-for-secure-email-authentication/mrs-v-hemalatha
Phishing is a social engineering Technique which they main aim is to target the user Information like user id, password, credit card information and so on. Which result a financial loss to the user. Detecting Phishing is the one of the challenge problem that relay to human vulnerabilities. This paper proposed the Detecting Phishing Web Sites using different Machine Learning Approaches. In this to evaluate different classification models to predict malicious and benign websites by using Machine Learning Algorithms. Experiments are performed on data set consisting malicious and benign, In This paper the results shows the proposed Algorithms has high detection accuracy. Nakkala Srinivas Mudiraj ""Detecting Phishing using Machine Learning"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23755.pdf
Paper URL: https://www.ijtsrd.com/computer-science/computer-security/23755/detecting-phishing-using-machine-learning/nakkala-srinivas-mudiraj
A novel way of integrating voice recognition and one time passwords to preven...ijdpsjournal
Phishing is a threat to all users of the internet who intend to use the web for secure transactions. In the
recent years the number of phishing attacks have increased drastically especially since the advent of ecommerce,
net banking and other services that have an emphasis on security. Phishing is characterized as
any malicious attack aided by a spoofed webpage to encourage users to input their security details.
Phishing is largely done to retrieve passwords and security details of unsuspecting users. This paper
details a new and more secure way to counteract the method of phishing
A Hybrid Approach For Phishing Website Detection Using Machine Learning.vivatechijri
In this technical age there are many ways where an attacker can get access to people’s sensitive information illegitimately. One of the ways is Phishing, Phishing is an activity of misleading people into giving their sensitive information on fraud websites that lookalike to the real website. The phishers aim is to steal personal information, bank details etc. Day by day it’s getting more and more risky to enter your personal information on websites fearing that it might be a phishing attack and can steal your sensitive information. That’s why phishing website detection is necessary to alert the user and block the website. An automated detection of phishing attack is necessary one of which is machine learning. Machine Learning is one of the efficient techniques to detect phishing attack as it removes drawback of existing approaches. Efficient machine learning model with content based approach proves very effective to detect phishing websites.
Our proposed system uses Hybrid approach which combines machine learning based method and content based method. The URL based features will be extracted and passed to machine learning model and in content based approach, TF-IDF algorithm will detect a phishing website by using the top keywords of a web page. This hybrid approach is used to achieve highly efficient result. Finally, our system will notify and alert user if the website is Phishing or Legitimate.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
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.
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.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers