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Secure mining of association rules in horizontally distributed databasesIEEEFINALYEARPROJECTS
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Enforcing secure and privacy preserving information brokering in distributed ...IEEEFINALYEARPROJECTS
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Data mining over diverse data sources is useful
means for discovering valuable patterns, associations, trends, and
dependencies in data. Many variants of this problem are existing,
depending on how the data is distributed, what type of data
mining we wish to do, how to achieve privacy of data and what
restrictions are placed on sharing of information. A transactional
database owner, lacking in the expertise or computational sources
can outsource its mining tasks to a third party service provider
or server. However, both the itemsets along with the association
rules of the outsourced database are considered private property
of the database owner.
In this paper, we consider a scenario where multiple data sources
are willing to share their data with trusted third party called
combiner who runs data mining algorithms over the union
of their data as long as each data source is guaranteed that
its information that does not pertain to another data source
will not be revealed. The proposed algorithm is characterized
with (1) secret sharing based secure key transfer for distributed
transactional databases with its lightweight encryption is used
for preserving the privacy. (2) and rough set based mechanism
for association rules extraction for an efficient and mining task.
Performance analysis and experimental results are provided for
demonstrating the effectiveness of the proposed algorithm.
Secure mining of association rules in horizontally distributed databasesIEEEFINALYEARPROJECTS
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Enforcing secure and privacy preserving information brokering in distributed ...IEEEFINALYEARPROJECTS
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Data mining over diverse data sources is useful
means for discovering valuable patterns, associations, trends, and
dependencies in data. Many variants of this problem are existing,
depending on how the data is distributed, what type of data
mining we wish to do, how to achieve privacy of data and what
restrictions are placed on sharing of information. A transactional
database owner, lacking in the expertise or computational sources
can outsource its mining tasks to a third party service provider
or server. However, both the itemsets along with the association
rules of the outsourced database are considered private property
of the database owner.
In this paper, we consider a scenario where multiple data sources
are willing to share their data with trusted third party called
combiner who runs data mining algorithms over the union
of their data as long as each data source is guaranteed that
its information that does not pertain to another data source
will not be revealed. The proposed algorithm is characterized
with (1) secret sharing based secure key transfer for distributed
transactional databases with its lightweight encryption is used
for preserving the privacy. (2) and rough set based mechanism
for association rules extraction for an efficient and mining task.
Performance analysis and experimental results are provided for
demonstrating the effectiveness of the proposed algorithm.
A Review Study on the Privacy Preserving Data Mining Techniques and Approaches14894
In this paper we review on the
various privacy preserving data mining techniques like data
modification and secure multiparty computation based on the
different aspects.
Index Terms– Privacy and Security, Data Mining, Privacy
Preserving, Secure Multiparty Computation (SMC) and Data
Modification
Every person involved,is concerned about the leakage of private data i.e privacy of the individual's data.Today privacy of data is one of the most serious concerns which people face on an individual as well as organisational level and it has to be dealt with in an effective
manner using privacy preserving data mining.
What I learned at the Infosecurity ISACA North America Conference 2019Ulf Mattsson
The 2019 Infosecurity ISACA North America Expo and Conference was held in New York City’s Javits Convention Center on November 20-21. With more than 50 sessions spanning 5 tracks, this conference offered the best-in-class educational content ISACA members and certification holders depend on, plus unprecedented access to leaders in the security industry.
Join Ulf Mattsson, Head of Innovation at TokenX for a conference recap webinar on the biggest takeaways
Data protection and privacy in the world of database DevOpsRed Gate Software
We dispel the myth that database DevOps and compliance can't go hand in hand. We begin with a brief look at how extending DevOps to the database lays solid foundations for data governance and compliance.
Our guest speaker is James Boother, Sales and Marketing Director at Coeo. Coeo are Europe's most trusted analytics and data management experts, with over 10 years’ experience delivering technology strategy and support for businesses who need to get the most from their data.
In a climate where data breaches are all too frequent, and more and more data lives in the cloud, the challenge of protecting your data can seem daunting.
James addresses the implications of the forthcoming GDPR on database management, highlighting requirements you may need to address. As well as offering guidance for assessing your data estate for GDPR readiness, James shares some great tools and tips for building data protection and privacy into your DevOps processes. With the right preparation, you can be fully compliant, with your data safe, whilst maintaining fast delivery of value to your end users.
SECURED FREQUENT ITEMSET DISCOVERY IN MULTI PARTY DATA ENVIRONMENT FREQUENT I...Editor IJMTER
Security and privacy methods are used to protect the data values. Private data values are secured with
confidentiality and integrity methods. Privacy model hides the individual identity over the public data values.
Sensitive attributes are protected using anonymity methods. Two or more parties have their own private data under
the distributed environment. The parties can collaborate to calculate any function on the union of their data. Secure
Multiparty Computation (SMC) protocols are used in privacy preserving data mining in distributed environments.
Association rule mining techniques are used to fetch frequent patterns.Apriori algorithm is used to mine association
rules in databases. Homogeneous databases share the same schema but hold information on different entities.
Horizontal partition refers the collection of homogeneous databases that are maintained in different parties. Fast
Distributed Mining (FDM) algorithm is an unsecured distributed version of the Apriori algorithm. Kantarcioglu
and Clifton protocol is used for secure mining of association rules in horizontally distributed databases. Unifying
lists of locally Frequent Itemsets Kantarcioglu and Clifton (UniFI-KC) protocol is used for the rule mining process
in partitioned database environment. UniFI-KC protocol is enhanced in two methods for security enhancement.
Secure computation of threshold function algorithm is used to compute the union of private subsets in each of the
interacting players. Set inclusion computation algorithm is used to test the inclusion of an element held by one
player in a subset held by another.The system is improved to support secure rule mining under vertical partitioned
database environment. The subgroup discovery process is adapted for partitioned database environment. The
system can be improved to support generalized association rule mining process. The system is enhanced to control
security leakages in the rule mining process.
In this work we highlighted some of the concepts of data privacy, techniques used in data privacy, and some techniques used in data privacy in the cloud plus some new research trends.
Privacy Perserving DataBases, how they are managed, built and secured. with an introduction to main methods of Anonymization techniques, PPDB data mining, P3P and Hippocratic DBs.
Enabling data dynamic and indirect mutual trust for cloud computing storage s...IEEEFINALYEARPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
In this era, there are need to secure data in distributed database system. For collaborative data
publishing some anonymization techniques are available such as generalization and bucketization. We consider
the attack can call as “insider attack” by colluding data providers who may use their own records to infer
others records. To protect our database from these types of attacks we used slicing technique for anonymization,
as above techniques are not suitable for high dimensional data. It cause loss of data and also they need clear
separation of quasi identifier and sensitive database. We consider this threat and make several contributions.
First, we introduce a notion of data privacy and used slicing technique which shows that anonymized data
satisfies privacy and security of data which classifies data vertically and horizontally. Second, we present
verification algorithms which prove the security against number of providers of data and insure high utility and
data privacy of anonymized data with efficiency. For experimental result we use the hospital patient datasets
and suggest that our slicing approach achieves better or comparable utility and efficiency than baseline
algorithms while satisfying data security. Our experiment successfully demonstrates the difference between
computation time of encryption algorithm which is used to secure data and our system.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
JAVA 2013 IEEE DATAMINING PROJECT Secure mining of association rules in horiz...IEEEGLOBALSOFTTECHNOLOGIES
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
A Review Study on the Privacy Preserving Data Mining Techniques and Approaches14894
In this paper we review on the
various privacy preserving data mining techniques like data
modification and secure multiparty computation based on the
different aspects.
Index Terms– Privacy and Security, Data Mining, Privacy
Preserving, Secure Multiparty Computation (SMC) and Data
Modification
Every person involved,is concerned about the leakage of private data i.e privacy of the individual's data.Today privacy of data is one of the most serious concerns which people face on an individual as well as organisational level and it has to be dealt with in an effective
manner using privacy preserving data mining.
What I learned at the Infosecurity ISACA North America Conference 2019Ulf Mattsson
The 2019 Infosecurity ISACA North America Expo and Conference was held in New York City’s Javits Convention Center on November 20-21. With more than 50 sessions spanning 5 tracks, this conference offered the best-in-class educational content ISACA members and certification holders depend on, plus unprecedented access to leaders in the security industry.
Join Ulf Mattsson, Head of Innovation at TokenX for a conference recap webinar on the biggest takeaways
Data protection and privacy in the world of database DevOpsRed Gate Software
We dispel the myth that database DevOps and compliance can't go hand in hand. We begin with a brief look at how extending DevOps to the database lays solid foundations for data governance and compliance.
Our guest speaker is James Boother, Sales and Marketing Director at Coeo. Coeo are Europe's most trusted analytics and data management experts, with over 10 years’ experience delivering technology strategy and support for businesses who need to get the most from their data.
In a climate where data breaches are all too frequent, and more and more data lives in the cloud, the challenge of protecting your data can seem daunting.
James addresses the implications of the forthcoming GDPR on database management, highlighting requirements you may need to address. As well as offering guidance for assessing your data estate for GDPR readiness, James shares some great tools and tips for building data protection and privacy into your DevOps processes. With the right preparation, you can be fully compliant, with your data safe, whilst maintaining fast delivery of value to your end users.
SECURED FREQUENT ITEMSET DISCOVERY IN MULTI PARTY DATA ENVIRONMENT FREQUENT I...Editor IJMTER
Security and privacy methods are used to protect the data values. Private data values are secured with
confidentiality and integrity methods. Privacy model hides the individual identity over the public data values.
Sensitive attributes are protected using anonymity methods. Two or more parties have their own private data under
the distributed environment. The parties can collaborate to calculate any function on the union of their data. Secure
Multiparty Computation (SMC) protocols are used in privacy preserving data mining in distributed environments.
Association rule mining techniques are used to fetch frequent patterns.Apriori algorithm is used to mine association
rules in databases. Homogeneous databases share the same schema but hold information on different entities.
Horizontal partition refers the collection of homogeneous databases that are maintained in different parties. Fast
Distributed Mining (FDM) algorithm is an unsecured distributed version of the Apriori algorithm. Kantarcioglu
and Clifton protocol is used for secure mining of association rules in horizontally distributed databases. Unifying
lists of locally Frequent Itemsets Kantarcioglu and Clifton (UniFI-KC) protocol is used for the rule mining process
in partitioned database environment. UniFI-KC protocol is enhanced in two methods for security enhancement.
Secure computation of threshold function algorithm is used to compute the union of private subsets in each of the
interacting players. Set inclusion computation algorithm is used to test the inclusion of an element held by one
player in a subset held by another.The system is improved to support secure rule mining under vertical partitioned
database environment. The subgroup discovery process is adapted for partitioned database environment. The
system can be improved to support generalized association rule mining process. The system is enhanced to control
security leakages in the rule mining process.
In this work we highlighted some of the concepts of data privacy, techniques used in data privacy, and some techniques used in data privacy in the cloud plus some new research trends.
Privacy Perserving DataBases, how they are managed, built and secured. with an introduction to main methods of Anonymization techniques, PPDB data mining, P3P and Hippocratic DBs.
Enabling data dynamic and indirect mutual trust for cloud computing storage s...IEEEFINALYEARPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
In this era, there are need to secure data in distributed database system. For collaborative data
publishing some anonymization techniques are available such as generalization and bucketization. We consider
the attack can call as “insider attack” by colluding data providers who may use their own records to infer
others records. To protect our database from these types of attacks we used slicing technique for anonymization,
as above techniques are not suitable for high dimensional data. It cause loss of data and also they need clear
separation of quasi identifier and sensitive database. We consider this threat and make several contributions.
First, we introduce a notion of data privacy and used slicing technique which shows that anonymized data
satisfies privacy and security of data which classifies data vertically and horizontally. Second, we present
verification algorithms which prove the security against number of providers of data and insure high utility and
data privacy of anonymized data with efficiency. For experimental result we use the hospital patient datasets
and suggest that our slicing approach achieves better or comparable utility and efficiency than baseline
algorithms while satisfying data security. Our experiment successfully demonstrates the difference between
computation time of encryption algorithm which is used to secure data and our system.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
JAVA 2013 IEEE DATAMINING PROJECT Secure mining of association rules in horiz...IEEEGLOBALSOFTTECHNOLOGIES
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
JPD1416 Secure Mining Of Association Rules In Horizantally Distributed Data...chennaijp
We have best 2014 free dot not projects topics are available along with all document, you can easy to find out number of documents for various projects titles.
For More Details:
http://jpinfotech.org/final-year-ieee-projects/2014-ieee-projects/dot-net-projects/
Secure Mining of Association Rules in Horizontally Distributed DatabasesIJSRD
We suggest a protocol for secure mining of association rules in horizontally distributed databases. The existing primary protocol is that of Kantarcioglu and Clifton [1]. Our protocol, like theirs, is rely on the Fast Distributed Mining (FDM) algorithm of Cheungetal, which is not a secured distributed version of the Apriori algorithm. The major ingredients in our protocol are two novel safe multi-party algorithmsâ€â€one that calculates the combination of private subsets that each of the interacting players have, and another that tests the insertion of an element contained by one player in a subset contained by another. Our protocol offers enhanced privacy with respect to the protocol in [1]. In count, it is simpler and is signiï¬Âcantly more effective in terms of interaction rounds, communication charge and computational cost. Data mining techniques are used to discover patterns in huge databases of information. But sometimes these patterns can disclose susceptible information about the data holder or persons whose information are the subject of the patterns. The idea of privacy-preserving data mining is to recognize and prohibit such revelations as evident in the kinds of patterns learned using traditional data mining techniques.[5].
Secure mining of association rules in horizontally distributed databasesShakas Technologies
We propose a protocol for secure mining of association rules in horizontally distributed databases. The current leading protocol is that of Kantarcioglu and Clifton. Our protocol, like theirs, is based on the Fast Distributed Mining (FDM) algorithm of Cheung et al. which is an unsecured distributed version of the Apriori algorithm.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
The advent of Big Data has presented nee challenges in terms of Data Security. There is an increasing need of research
in technologies that can handle the vast volume of Data and make it secure efficiently. Current Technologies for securing data are
slow when applied to huge amounts of data. This paper discusses security aspect of Big Data.
Fusion of data from multiple sources is generating new information from existing data. Now users can access any information from inside or outside of the organization very easily. It helps to increase the user productivity and knowledge shared within the organization. But this leads to a new area of network security threat, “Inside Threat”. Now users can share critical information of organization to outside the organization if he/she has access to the information. The current network security tool cannot prevent the new threat. In this paper, we address this issue by “Building real time anomaly detection system based on users’ current behavior and previous behavior”.
Adaptive and Fast Predictions by Minimal Itemsets CreationIJERA Editor
Association rules in data mining are useful for the analysis and prediction of an individual user’s behavior which facilitates the data analysis on a regular basis for market basket data, clustering of products, designing catalogs and playing an immense role for store layout setting. This paper presents a successor of the Apriori and variation of the CHARM algorithm, which is the MG-CHARM algorithm that is used for finding relationships between certain attributes instead of the whole dataset. The MG-CHARM algorithm is an Association Rule Mining (ARM) algorithm that is used to select the target database which in turn takes less time to find the desired association rules. In the proposed implementation, the actions performed by a user will be effectively recorded in the target database. The datasets that are generated will have to be fed to the semi - automated, adaptive software which will fetch the output based on ARM algorithm. The algorithm will determine the relations for different datasets by mining Minimal Generators (mGs) from Frequently Closed Itemsets (FCI’s) to carry out decision making and pattern analysis of the Itemsets.
Multiple Minimum Support Implementations with Dynamic Matrix Apriori Algorith...ijsrd.com
Data mining can be defined as the process of uncovering hidden patterns in random data that are potentially useful. The discovery of interesting association relationships among large amounts of business transactions is currently vital for making appropriate business decisions. Association rule analysis is the task of discovering association rules that occur frequently in a given transaction data set. Its task is to find certain relationships among a set of data (itemset) in the database. It has two measurements: Support and confidence values. Confidence value is a measure of rule’s strength, while support value corresponds to statistical significance. There are currently a variety of algorithms to discover association rules. Some of these algorithms depend on the use of minimum support to weed out the uninteresting rules. Other algorithms look for highly correlated items, that is, rules with high confidence. Traditional association rule mining techniques employ predefined support and confidence values. However, specifying minimum support value of the mined rules in advance often leads to either too many or too few rules, which negatively impacts the performance of the overall system. This work proposes a way to efficiently mine association rules over dynamic databases using Dynamic Matrix Apriori technique and Multiple Support Apriori (MSApriori). A modification for Matrix Apriori algorithm to accommodate this modification is proposed. Experiments on large set of data bases have been conducted to validate the proposed framework. The achieved results show that there is a remarkable improvement in the overall performance of the system in terms of run time, the number of generated rules, and number of frequent items used.
Similar to IEEE 2014 JAVA DATA MINING PROJECTS Secure mining of association rules in horizontally distributed databases (20)
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
6th International Conference on Machine Learning & Applications (CMLA 2024)ClaraZara1
6th International Conference on Machine Learning & Applications (CMLA 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of on Machine Learning & Applications.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
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.
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
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
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
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.
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.
An Approach to Detecting Writing Styles Based on Clustering Techniquesambekarshweta25
An Approach to Detecting Writing Styles Based on Clustering Techniques
Authors:
-Devkinandan Jagtap
-Shweta Ambekar
-Harshit Singh
-Nakul Sharma (Assistant Professor)
Institution:
VIIT Pune, India
Abstract:
This paper proposes a system to differentiate between human-generated and AI-generated texts using stylometric analysis. The system analyzes text files and classifies writing styles by employing various clustering algorithms, such as k-means, k-means++, hierarchical, and DBSCAN. The effectiveness of these algorithms is measured using silhouette scores. The system successfully identifies distinct writing styles within documents, demonstrating its potential for plagiarism detection.
Introduction:
Stylometry, the study of linguistic and structural features in texts, is used for tasks like plagiarism detection, genre separation, and author verification. This paper leverages stylometric analysis to identify different writing styles and improve plagiarism detection methods.
Methodology:
The system includes data collection, preprocessing, feature extraction, dimensional reduction, machine learning models for clustering, and performance comparison using silhouette scores. Feature extraction focuses on lexical features, vocabulary richness, and readability scores. The study uses a small dataset of texts from various authors and employs algorithms like k-means, k-means++, hierarchical clustering, and DBSCAN for clustering.
Results:
Experiments show that the system effectively identifies writing styles, with silhouette scores indicating reasonable to strong clustering when k=2. As the number of clusters increases, the silhouette scores decrease, indicating a drop in accuracy. K-means and k-means++ perform similarly, while hierarchical clustering is less optimized.
Conclusion and Future Work:
The system works well for distinguishing writing styles with two clusters but becomes less accurate as the number of clusters increases. Future research could focus on adding more parameters and optimizing the methodology to improve accuracy with higher cluster values. This system can enhance existing plagiarism detection tools, especially in academic settings.
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.
Online aptitude test management system project report.pdfKamal Acharya
The purpose of on-line aptitude test system is to take online test in an efficient manner and no time wasting for checking the paper. The main objective of on-line aptitude test system is to efficiently evaluate the candidate thoroughly through a fully automated system that not only saves lot of time but also gives fast results. For students they give papers according to their convenience and time and there is no need of using extra thing like paper, pen etc. This can be used in educational institutions as well as in corporate world. Can be used anywhere any time as it is a web based application (user Location doesn’t matter). No restriction that examiner has to be present when the candidate takes the test.
Every time when lecturers/professors need to conduct examinations they have to sit down think about the questions and then create a whole new set of questions for each and every exam. In some cases the professor may want to give an open book online exam that is the student can take the exam any time anywhere, but the student might have to answer the questions in a limited time period. The professor may want to change the sequence of questions for every student. The problem that a student has is whenever a date for the exam is declared the student has to take it and there is no way he can take it at some other time. This project will create an interface for the examiner to create and store questions in a repository. It will also create an interface for the student to take examinations at his convenience and the questions and/or exams may be timed. Thereby creating an application which can be used by examiners and examinee’s simultaneously.
Examination System is very useful for Teachers/Professors. As in the teaching profession, you are responsible for writing question papers. In the conventional method, you write the question paper on paper, keep question papers separate from answers and all this information you have to keep in a locker to avoid unauthorized access. Using the Examination System you can create a question paper and everything will be written to a single exam file in encrypted format. You can set the General and Administrator password to avoid unauthorized access to your question paper. Every time you start the examination, the program shuffles all the questions and selects them randomly from the database, which reduces the chances of memorizing the questions.
Online aptitude test management system project report.pdf
IEEE 2014 JAVA DATA MINING PROJECTS Secure mining of association rules in horizontally distributed databases
1. GLOBALSOFT TECHNOLOGIES
IEEE PROJECTS & SOFTWARE DEVELOPMENTS
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Secure Mining of Association Rules in Horizontally
Distributed Databases
Abstract
We propose a protocol for secure mining of association rules in horizontally distributed
databases. Our protocol, like theirs, is based on the Fast Distributed Mining (FDM)
algorithm which is an unsecured distributed version of the Apriori algorithm.
The main ingredients in our protocol are two novel secure multi-party algorithms
— one that computes the union of private subsets that each of the interacting players hold,
and another that tests the inclusion of an element held by one player in a subset held by
another. Our protocol offers enhanced privacy with respect to the protocol. In addition, it
is simpler and is significantly more efficient in terms of communication rounds,
communication cost and computational cost.
Existing System
In Existing System, the problem of secure mining of association rules in
horizontally partitioned databases. In that setting, there are several sites (or players) that
hold homogeneous databases, i.e., databases that share the same schema but hold
information on different entities. The inputs are the partial databases, and the required
output is the list of association rules that hold in the unified database with support and
confidence no smaller.
2. Disadvantage:
o Less number of features in previous system.
o Difficulty to get accurate item set.
Proposed System
In Proposed System, propose an alternative protocol for the secure computation of the
union of private subsets. The proposed protocol improves upon that in terms of simplicity
and efficiency as well as privacy. In particular, our protocol does not depend on
commutative encryption and oblivious transfer (what simplifies it significantly and
contributes towards much reduced communication and computational costs). While our
solution is still not perfectly secure, it leaks excess information only to a small number
(three) of possible coalitions, unlike the protocol of that discloses information also to
some single players. In addition, we claim that the excess information that our protocol
may leak is less sensitive than the excess information leaked by the protocol.
Advantage:
1) As a rising subject, data mining is playing an increasingly important role in the
decision support activity of every walk of life.
2) Get Efficient Item set result based on the customer request.
Modules
1. User Module.
2. Admin Module.
3. Association Rule.
4. Apriori Algorithm.
3. Modules Description
User Module
In this module, privacy preserving data mining has considered two related
settings. One, in which the data owner and the data miner are two different entities, and
another, in which the data is distributed among several parties who aim to jointly perfor m
data mining on the unified corpus of data that they hold.
In the first setting, the goal is to protect the data records from the data miner.
Hence, the data owner aims at anonymizing the data prior to its release. The main
approach in this context is to apply data perturbation. He perturbed data can be used to
infer general trends in the data, without revealing original record information.
In the second setting, the goal is to perform data mining while protecting the data
records of each of the data owners from the other data owners.
Admin Module
In this module, is used to view user details. Admin to view the item set based on
the user processing details using association role with Apriori algorithm.
Association Rule:
Association rules are if/then statements that help uncover relationships between
seemingly unrelated data in a relational database or other information repository. An
example of an association rule would be "If a customer buys a dozen eggs, he is 80%
likely to also purchase milk."
Association rules are created by analyzing data for frequent if/then patterns and
using the criteria support and confidence to identify the most important relationships.
4. Support is an indication of how frequently the items appear in the database. Confidence
indicates the number of times the if/then statements have been found to be true.
Apriori Algorithm:
Apriori is designed to operate on databases containing transactions. The purpose of
the Apriori Algorithm is to find associations between different sets of data. It is sometimes
referred to as "Market Basket Analysis". Each set of data has a number of items and is
called a transaction. The output of Apriori is sets of rules that tell us how often items are
contained in sets of data.
Algorithm - Fast Distributed Mining (FDM)
The FDM algorithm proceeds as follows:
(1) Initialization
(2) Candidate Sets Generation
(3) Local Pruning
(4) Unifying the candidate item sets
(5) Computing local supports
(6) Broadcast Mining Results
SYSTEM SPECIFICATION
Hardware Requirements:
• System : Pentium IV 2.4 GHz.
• Hard Disk : 40 GB.
• Floppy Drive : 1.44 Mb.
• Monitor : 14’ Colour Monitor.
• Mouse : Optical Mouse.
• Ram : 512 Mb.
• Keyboard : 101 Keyboards.
Software Requirements:
• Operating system : Windows 7 Ultimate (32-bit)
• Front End : VS2010
• Coding Language : ASP.Net with C#
• Data Base : SQL Server 2008