We have concentrated on a range of strategies, methodologies, and distinct fields of research in this article, all of which are useful and relevant in the field of data mining technologies. As we all know, numerous multinational corporations and major corporations operate in various parts of the world. Each location of business may create significant amounts of data. Corporate decision-makers need access to all of these data sources in order to make strategic decisions.
The Survey of Data Mining Applications And Feature Scope IJCSEIT Journal
In this paper we have focused a variety of techniques, approaches and different areas of the research which
are helpful and marked as the important field of data mining Technologies. As we are aware that many MNC’s
and large organizations are operated in different places of the different countries. Each place of operation
may generate large volumes of data. Corporate decision makers require access from all such sources and
take strategic decisions .The data warehouse is used in the significant business value by improving the
effectiveness of managerial decision-making. In an uncertain and highly competitive business
environment, the value of strategic information systems such as these are easily recognized however in
today’s business environment, efficiency or speed is not the only key for competitiveness. This type of huge
amount of data’s are available in the form of tera- to peta-bytes which has drastically changed in the areas
of science and engineering. To analyze, manage and make a decision of such type of huge amount of data
we need techniques called the data mining which will transforming in many fields. This paper imparts more
number of applications of the data mining and also o focuses scope of the data mining which will helpful in
the further research.
DATA SCIENCE METHODOLOGY FOR CYBERSECURITY PROJECTS cscpconf
Cybersecurity solutions are traditionally static and signature-based. The traditional solutions
along with the use of analytic models, machine learning and big data could be improved by
automatically trigger mitigation or provide relevant awareness to control or limit consequences
of threats. This kind of intelligent solutions is covered in the context of Data Science for
Cybersecurity. Data Science provides a significant role in cybersecurity by utilising the power
of data (and big data), high-performance computing and data mining (and machine learning) to
protect users against cybercrimes. For this purpose, a successful data science project requires
an effective methodology to cover all issues and provide adequate resources. In this paper, we
are introducing popular data science methodologies and will compare them in accordance with
cybersecurity challenges. A comparison discussion has also delivered to explain methodologies’
strengths and weaknesses in case of cybersecurity projects.
ISSUES, CHALLENGES, AND SOLUTIONS: BIG DATA MININGcscpconf
Data has become an indispensable part of every economy, industry, organization, business
function and individual. Big Data is a term used to identify the datasets that whose size is
beyond the ability of typical database software tools to store, manage and analyze. The Big
Data introduce unique computational and statistical challenges, including scalability and
storage bottleneck, noise accumulation, spurious correlation and measurement errors. These
challenges are distinguished and require new computational and statistical paradigm. This
paper presents the literature review about the Big data Mining and the issues and challenges
with emphasis on the distinguished features of Big Data. It also discusses some methods to deal
with big data.
Data has become an indispensable part of every economy, industry, organization, business
function and individual. Big Data is a term used to identify the datasets that whose size is
beyond the ability of typical database software tools to store, manage and analyze. The Big
Data introduce unique computational and statistical challenges, including scalability and
storage bottleneck, noise accumulation, spurious correlation and measurement errors. These
challenges are distinguished and require new computational and statistical paradigm. This
paper presents the literature review about the Big data Mining and the issues and challenges
with emphasis on the distinguished features of Big Data. It also discusses some methods to deal
with big data.
The Survey of Data Mining Applications And Feature Scope IJCSEIT Journal
In this paper we have focused a variety of techniques, approaches and different areas of the research which
are helpful and marked as the important field of data mining Technologies. As we are aware that many MNC’s
and large organizations are operated in different places of the different countries. Each place of operation
may generate large volumes of data. Corporate decision makers require access from all such sources and
take strategic decisions .The data warehouse is used in the significant business value by improving the
effectiveness of managerial decision-making. In an uncertain and highly competitive business
environment, the value of strategic information systems such as these are easily recognized however in
today’s business environment, efficiency or speed is not the only key for competitiveness. This type of huge
amount of data’s are available in the form of tera- to peta-bytes which has drastically changed in the areas
of science and engineering. To analyze, manage and make a decision of such type of huge amount of data
we need techniques called the data mining which will transforming in many fields. This paper imparts more
number of applications of the data mining and also o focuses scope of the data mining which will helpful in
the further research.
DATA SCIENCE METHODOLOGY FOR CYBERSECURITY PROJECTS cscpconf
Cybersecurity solutions are traditionally static and signature-based. The traditional solutions
along with the use of analytic models, machine learning and big data could be improved by
automatically trigger mitigation or provide relevant awareness to control or limit consequences
of threats. This kind of intelligent solutions is covered in the context of Data Science for
Cybersecurity. Data Science provides a significant role in cybersecurity by utilising the power
of data (and big data), high-performance computing and data mining (and machine learning) to
protect users against cybercrimes. For this purpose, a successful data science project requires
an effective methodology to cover all issues and provide adequate resources. In this paper, we
are introducing popular data science methodologies and will compare them in accordance with
cybersecurity challenges. A comparison discussion has also delivered to explain methodologies’
strengths and weaknesses in case of cybersecurity projects.
ISSUES, CHALLENGES, AND SOLUTIONS: BIG DATA MININGcscpconf
Data has become an indispensable part of every economy, industry, organization, business
function and individual. Big Data is a term used to identify the datasets that whose size is
beyond the ability of typical database software tools to store, manage and analyze. The Big
Data introduce unique computational and statistical challenges, including scalability and
storage bottleneck, noise accumulation, spurious correlation and measurement errors. These
challenges are distinguished and require new computational and statistical paradigm. This
paper presents the literature review about the Big data Mining and the issues and challenges
with emphasis on the distinguished features of Big Data. It also discusses some methods to deal
with big data.
Data has become an indispensable part of every economy, industry, organization, business
function and individual. Big Data is a term used to identify the datasets that whose size is
beyond the ability of typical database software tools to store, manage and analyze. The Big
Data introduce unique computational and statistical challenges, including scalability and
storage bottleneck, noise accumulation, spurious correlation and measurement errors. These
challenges are distinguished and require new computational and statistical paradigm. This
paper presents the literature review about the Big data Mining and the issues and challenges
with emphasis on the distinguished features of Big Data. It also discusses some methods to deal
with big data.
Real World Application of Big Data In Data Mining Toolsijsrd.com
The main aim of this paper is to make a study on the notion Big data and its application in data mining tools like R, Weka, Rapidminer, Knime,Mahout and etc. We are awash in a flood of data today. In a broad range of application areas, data is being collected at unmatched scale. Decisions that previously were based on surmise, or on painstakingly constructed models of reality, can now be made based on the data itself. Such Big Data analysis now drives nearly every aspect of our modern society, including mobile services, retail, manufacturing, financial services, life sciences, and physical sciences. The paper mainly focuses different types of data mining tools and its usage in big data in knowledge discovery.
Due to the arrival of new technologies, devices, and communication means, the amount of data produced by mankind is growing rapidly every year. This gives rise to the era of big data. The term big data comes with the new challenges to input, process and output the data. The paper focuses on limitation of traditional approach to manage the data and the components that are useful in handling big data. One of the approaches used in processing big data is Hadoop framework, the paper presents the major components of the framework and working process within the framework.
We are living in a world, where a vast amount of digital data which is called big data. Plus as the world becomes more and more connected via the Internet of Things (IoT). The IoT has been a major influence on the Big Data landscape. The analysis of such big data brings ahead business competition to the next level of innovation and productivity.
The software development process is complete for computer project analysis, and it is important to the evaluation of the random project. These practice guidelines are for those who manage big-data and big-data analytics projects or are responsible for the use of data analytics solutions. They are also intended for business leaders and program leaders that are responsible for developing agency capability in the area of big data and big data analytics .
For those agencies currently not using big data or big data analytics, this document may assist strategic planners, business teams and data analysts to consider the value of big data to the current and future programs.
This document is also of relevance to those in industry, research and academia who can work as partners with government on big data analytics projects.
Technical APS personnel who manage big data and/or do big data analytics are invited to join the Data Analytics Centre of Excellence Community of Practice to share information of technical aspects of big data and big data analytics, including achieving best practice with modeling and related requirements. To join the community, send an email to the Data Analytics Centre of Excellence
In the information age, data turns to be the vital. Hence it is important to understand the data in order to face the future information challenges. This paper deals with the importance of data mining while explaining the concepts and life cycle involved. It extracts the basic gist of the topic presented in a user-friendly way. Further, in developing different stages of data mining followed by its extended application usage in practical business platform.
INTRODUCTION TO DATA MINING
This word document contain the notes of data mining. It tells the basics of data mining like what is Data mining, it's types, issues, advantages, disadvantages, applications, social implications, basis tasks and KDD process etc. While making this notes, I had taken help from different websites of google.
Abstract : Fire incident is a disaster that results in the loss of life, damage to the property and endless disaster
to the victim. Fire extinguishing is an exceptionally unsafe undertaking and it might likewise include death risk.
Robotics is the answer to ensure the safeguarding of the surroundings and also the life of firefighters. Fire sensing
and extinguishing robot is a model which can be used in extinguishing the fire with minimum human intervention.
There is a threat to the life of the fire fighters in extinguishing the fire and there are some difficult areas where
they cannot reach like that in the tunnels. At similar kind of places this automatic robot is veritably useful to
perform the task. This robot can be controlled remotely by mobile phone using Bluetooth module. The robot is
equipped with the flame sensors that automatically detects the fire and gives the further signal to the extinguisher
units to start the pump and extinguish the fire by spraying water. Arduino uno is used as the microcontroller to
operate the whole operation. The proposed robot has been used for various trials and proper evaluation has been
done to check the proper functioning and to get the desired result
Abstract: Detection of fake news based on deep learning techniques is a major issue used to mislead people. For
the experiments, several types of datasets, models, and methodologies have been used to detect fake news. Also,
most of the datasets contain text id, tweets id, and user-based id and user-based features. To get the proper results
and accuracy various models like CNN (Convolution neural network), DEEP CNN, and LSTM (Long short-term
memory) are used
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Real World Application of Big Data In Data Mining Toolsijsrd.com
The main aim of this paper is to make a study on the notion Big data and its application in data mining tools like R, Weka, Rapidminer, Knime,Mahout and etc. We are awash in a flood of data today. In a broad range of application areas, data is being collected at unmatched scale. Decisions that previously were based on surmise, or on painstakingly constructed models of reality, can now be made based on the data itself. Such Big Data analysis now drives nearly every aspect of our modern society, including mobile services, retail, manufacturing, financial services, life sciences, and physical sciences. The paper mainly focuses different types of data mining tools and its usage in big data in knowledge discovery.
Due to the arrival of new technologies, devices, and communication means, the amount of data produced by mankind is growing rapidly every year. This gives rise to the era of big data. The term big data comes with the new challenges to input, process and output the data. The paper focuses on limitation of traditional approach to manage the data and the components that are useful in handling big data. One of the approaches used in processing big data is Hadoop framework, the paper presents the major components of the framework and working process within the framework.
We are living in a world, where a vast amount of digital data which is called big data. Plus as the world becomes more and more connected via the Internet of Things (IoT). The IoT has been a major influence on the Big Data landscape. The analysis of such big data brings ahead business competition to the next level of innovation and productivity.
The software development process is complete for computer project analysis, and it is important to the evaluation of the random project. These practice guidelines are for those who manage big-data and big-data analytics projects or are responsible for the use of data analytics solutions. They are also intended for business leaders and program leaders that are responsible for developing agency capability in the area of big data and big data analytics .
For those agencies currently not using big data or big data analytics, this document may assist strategic planners, business teams and data analysts to consider the value of big data to the current and future programs.
This document is also of relevance to those in industry, research and academia who can work as partners with government on big data analytics projects.
Technical APS personnel who manage big data and/or do big data analytics are invited to join the Data Analytics Centre of Excellence Community of Practice to share information of technical aspects of big data and big data analytics, including achieving best practice with modeling and related requirements. To join the community, send an email to the Data Analytics Centre of Excellence
In the information age, data turns to be the vital. Hence it is important to understand the data in order to face the future information challenges. This paper deals with the importance of data mining while explaining the concepts and life cycle involved. It extracts the basic gist of the topic presented in a user-friendly way. Further, in developing different stages of data mining followed by its extended application usage in practical business platform.
INTRODUCTION TO DATA MINING
This word document contain the notes of data mining. It tells the basics of data mining like what is Data mining, it's types, issues, advantages, disadvantages, applications, social implications, basis tasks and KDD process etc. While making this notes, I had taken help from different websites of google.
Abstract : Fire incident is a disaster that results in the loss of life, damage to the property and endless disaster
to the victim. Fire extinguishing is an exceptionally unsafe undertaking and it might likewise include death risk.
Robotics is the answer to ensure the safeguarding of the surroundings and also the life of firefighters. Fire sensing
and extinguishing robot is a model which can be used in extinguishing the fire with minimum human intervention.
There is a threat to the life of the fire fighters in extinguishing the fire and there are some difficult areas where
they cannot reach like that in the tunnels. At similar kind of places this automatic robot is veritably useful to
perform the task. This robot can be controlled remotely by mobile phone using Bluetooth module. The robot is
equipped with the flame sensors that automatically detects the fire and gives the further signal to the extinguisher
units to start the pump and extinguish the fire by spraying water. Arduino uno is used as the microcontroller to
operate the whole operation. The proposed robot has been used for various trials and proper evaluation has been
done to check the proper functioning and to get the desired result
Abstract: Detection of fake news based on deep learning techniques is a major issue used to mislead people. For
the experiments, several types of datasets, models, and methodologies have been used to detect fake news. Also,
most of the datasets contain text id, tweets id, and user-based id and user-based features. To get the proper results
and accuracy various models like CNN (Convolution neural network), DEEP CNN, and LSTM (Long short-term
memory) are used
Abstract : The project’s major goal is to create an intelligent trash can that would aid in maintaining a clean
and environmentally friendly environment. The Swachh Bharat Mission motivates us. Since technology is
becoming increasingly intelligent, we are utilising Arduino nano to develop an intelligent dustbin to help clean
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intelligent trash can. The Smart Dustbin application will launch when all hardware and software connections
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Abstract: A technology called Quantum Dot Cellular Automata (QCA) offers a far more effective computational
platform than CMOS. Through the polarization of electrons, digital information is represented. In comparison to
CMOS technology, it is more attractive because to its size, faster speed, feature, high degree of scalability, greater
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ABSTRACT: In the field of computer science known as "machine learning," a computer makes predictions about
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interacting with the environment or by using digitalized training sets. In contrast to static programming
algorithms, which require explicit human guidance, machine learning algorithms may learn from data and
generate predictions on their own. Various supervised and unsupervised strategies, including rule-based
techniques, logic-based techniques, instance-based techniques, and stochastic techniques, have been presented in
order to solve problems. Our paper's main goal is to present a comprehensive comparison of various cutting-edge
supervised machine learning techniques.
Abstract: In many fields, such as industry, commerce, government, and education, knowledge discovery and data
mining can be immensely valuable to the subject of Artificial Intelligence. Because of the recent increase in
demand for KDD techniques, such as those used in machine learning, databases, statistics, knowledge acquisition,
data visualisation, and high performance computing, knowledge discovery and data mining have grown in
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Abstract—This paper provides a brief overview of the Intelligent Traffic Management System based on Artificial
Neural Networks (ANN). It is being utilized to enhance the present traffic management system and human resource
reliance. The most basic problem with the current traffic lights is their dependency on humans for their working.
The technologies used in the making of this automated traffic lights are Internet of Things, Machine Learning and
Artificial Intelligence. The basic steps used in Internet of Things are reported along with different ANN trainings.
This ANN model can be used for the minimization of traffic on roads and less waiting time at traffic lights. As a
result, we can make traffic lights more automated which in turn eventually deceases our dependency on human
resources
MANET Mutual Authentication System (IMMAS) provides an implied mutual authentication or all routing and data traffic with in a Mobile Ad-hoc Network (MANET) by combining Elliptic Curve Crypt-ography a public- key crypto-system, with the MANETs Routing Protocol. IMMAS provides security by effectively hiding network topology from adver-saries while reducing the potential for, among other things, traffic analysis and data tampering, all while providing a graceful degradation for each of the authentication components. Current research in MANET's tends to focus primarily on routing issue leaving topics such as security and authentication for future research. IMMAS focuses on achieving a higher level of security with the potential for substantial increases in efficiency of processing power and bandwidth compared to alternative exterior mechanism tacked on after protocol development and Standardization.
Cloud computing makes the dream ofcomputing real as a tool and in the form of service. This internet based ongoing technology which has brought flexibility, capacity and power of processing has realized service- oriented idea and has created a new ecosystem in the computing world with its great power and benefits. Cloud capabilities have been able to move IT industry one step forward. Nowadays, large and famous enterprise has resorted to cloud computing and have transferred their processing and storage to it. Due to popularity and progress of cloud in different organizations, cloud performance evaluation is of special importance and this evaluation can help users make right decisions. In this paper we define the cloud perfor-mance issues which are cause for quality of any cloud or database. In the cloud we can improve the performance by the reducing these issues. We also provide a large view of latency which is a hot topic in the research field for improving the performance of cloud.
This paper considers the waiting of students in colleges at the time of admissions at fee counter as a single-channel queuing system with Poisson arrivals and exponential service rate where service discipline is first come first serve. Queue is a common phenom-enon which has seen usually in colleges at the time of fee submission. Hence queuing theory which is the mathematical study of waiting lines or queue is suitable to be applied in the fee counter because it is associated with queue and waiting line where students who cannot be served immediately have to queue for service
In the present work, a dynamic model is developed for the Multi-effect evaporator (MEE) to study the transient behavior of the system. Each effect in the process is represented by some variables which are related to the energy and material balance equ-ations for the feed, product and liquor flow. Backward feed is used for the development of the model for six effect evaporator system. For the steady state and dynamic simulation, the 'fsolve' and 'ODE45' solvers in MATLAB source code is used respectively.
This paper analyzes a bi-directional DC-DC converter having four active switches for higher transformation ratio. The converter steps up the DC voltage in forward direction and steps down in reverse direction and various modes of operation are possible. To investigate the performance of converter, simulations are performed on MATLAB/ Simpower system platform. To study reverse power flow capability, PMBLDC motor is connected as load andregeneration is carried out.
This paper presents decentralized control scheme for Load Frequency Control in a Power System by appreciating the performance of the methods in a two area hybrid interconnected powersystem. This project analysis is done with the use of Autonmatic Generation Control of Interconnected using Load Frequency control. The Power system whole system is tuned with the help of integral controller to reduce area control error and error in tieline which may cause impr-ovement in the steady state output of inter-connected hybrid system. Load freq-uency control (LFC)including PI controller is proposed in order to suppress frequency deviations for a power system involving gas, hydro and thermal plants owing to load and generating power fluctuations caused by penetration of renewable resources. Restructuring of whole power system is done by dividing it into GENCO, TRANSCO, DISCO and ISO which has been explained in detail in the report. The power generated by the GENCO has to be sold to DISCO at optimum rates. DISCO and GENCO will have contracts within its own area or with intercon-nected area and thus the power is exchanged between their interconnected area according to the contracts scheduled between them.ln this system there are four GENCOs namely, steam, hydro and gas and four DISCO interconnected using bilateral contract and the modeling of the system is done using MAT LAB simulation. It employs Synchronous static series compensator.. The robustness and reliability of the various control schemes is examined through simulations. The significant improvement of optimal transient performance is observed with the addition of a these controllers.
A reduced size slotted rectangular micro strip patch antenna is introduced which exploits RT DUROID 5880 substrate from Rogers-Corp with dielectric constant of 2.2 and thickness of 0.76mm. The proposed antenna uses a finite ground plane with slotted rectangular patch to achieve an excellent impedance matching, high gain, along with operating frequency range of 3.06-3.145GHz and a radiation efficiency of 95.524%. The various simulations are provided to evaluate its performance parameters. This antenna is highly efficient for S-band (3.1-10 GHz) applications.
Due to demand of voice, data and multimedia, the services in telecommunications are increasing day by day. The wireless network providers are facing so many problems and it is difficult to provide cost effective and reliable service to each consumer. To deal with these problems, optical fiber communication system was introduced. But when a signal of combined order is transmitted through optical fiber a large amount of distortion is received. The motivation of this work was non-linearity present in the fiber communication that can be compensated by dispersion. So the higher order study needed typical values of parameters of fiber core radius, length of fiber and power attenuation constant. Moreover the study of higher order dispersion for the fiber optic communication system becomes important.
In the microwave field, Gunn diode oscillators have important role in the development of commutnication systems because of its low noise behavior and medium power. The primary application of Gunn diode is as a local oscillator in microwave receivers. At higher microwave frequencies, transistors cannot generate required low noise power, suitable for receivers. The Gunn diode is two-terminal solid-state negative impedance device, where the real part of the impedance is negative over a range of frequencies. This paper introduces Design Philosophy of high-frequency Gunn Oscillators and discusses the design and implementation steps to produce the oscillator. For example the Waveguide Cavity Gunn Oscillator at 94 GHz frequency, which consists of a packaged Gunn device mounted in WR-IO waveguide, and tuning plunger is used to tune the desired frequency. The matching circuit is a post mounting network and a waveguide — height transformer.
Radio-frequency identification technology, based on the reader/tag paradigm, is quickly permeating several aspects of everyday life. To allow optimum impedance matching with enhanced CP bandwidth, the microstrip feed technique is employed in this design. The design of a simple UHF (ultrahigh frequency) RFID (radio frequency identification) reader antenna that operates within the 900 MHz band (902—928 MHz) is studied. To allow optimum impedance matching with enhanced CP bandwidth, the proposed antenna can also yield an impedance bandwidth (10-dB return loss) from 880 to 1100 MHz, while good CP performances between 901 to 930 MHz are exhibited.
Sign language recognition will be a boost to the hard hearing and deaf people. It is a topic of current research in Computer Science and Engineering field. Deaf people are not able to use the computers and other hand held devices as it is very difficult for them to interact with such devices. So, a lot of research is going on to help them in this area. Either no standard database or no system is available to carry research in this area in India for them. In this research paper we developed a system for hard hearing and physically impaired persons. Here we presented a framework about Indian Sign Language (ISL) with international standards.Planned Outline For Indian Sign Language Recognition
Sign language recognition will be a boost to the hard hearing and deaf people. It is a topic of current research in Computer Science and Engineering field. Deaf people are not able to use the computers and other hand held devices as it is very difficult for them to interact with such devices. So, a lot of research is going on to help them in this area. Either no standard database or no system is available to carry research in this area in India for them. In this research paper we developed a system for hard hearing and physically impaired persons. Here we presented a framework about Indian Sign Language (ISL) with international standards.
MANETs can manage dynamic infrastructure and can stay active rapid changes in the network topology. The one of the key challenges in deploying Mobile Ad-Hoc Networks is routing with scalable and robustness. The objective of this paper is to create of the different mobile ad-hoc routing protocols, and to survey and compare representative examples for every classification of protocols. In this paper we compared three types of routing protocols i.e. pro-active, reactive and hybrid. In order to operate the Ad-hoc Networks as efficiently as possible, appropriate on-demand routing protocols have to be incorporated, to find best effective routes between source to destination. In this paper we provide an overview of a wide range of the existing routing protocols with focused on their characteristics and functionality. This paper focus on the survey of re-active (on-demand), proactive (table-driven) and hybrid routing protocols like AODV, DSDV and ZRP. Further this paper will help the researchers to get an overview of the existing protocols and suggest which protocols may perform better with respect to varying network scenarios.
Bug report is a report which contains the information about the defects in the system or in the software. Generally, bug report contains the issues written by the wide variety of reporters, with different levels of training and knowledge about the system being discussed. Bug tracking systems are made to manage bug reports, which are collected from various sources. These bug reports are needed to be labeled as security bug reports or non security bug reports, since security bug reports (SBRs) contain more risk than non-security bug reports (NSBRs). In this paper we are using Naive Bayes classifier to classify the bug reports. With naive bayes classifier, feature subset selection method such as Gain Ratio is applied to rank the attributes of the dataset. Gain Ratio is utilized as an iterative process where we select smaller sets of features in incremental manner. Result prove that the classification accuracy is high for attributes having high gain ratio and low for attributes having low gain ratio.
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When a customer search for a automobile, if the automobile is available, they will be taken to a page that shows the details of the automobile including automobile name, automobile ID, quantity, price etc. “Automobile Management System” is useful for maintaining automobiles, customers effectively and hence helps for establishing good relation between customer and automobile organization. It contains various customized modules for effectively maintaining automobiles and stock information accurately and safely.
When the automobile is sold to the customer, stock will be reduced automatically. When a new purchase is made, stock will be increased automatically. While selecting automobiles for sale, the proposed software will automatically check for total number of available stock of that particular item, if the total stock of that particular item is less than 5, software will notify the user to purchase the particular item.
Also when the user tries to sale items which are not in stock, the system will prompt the user that the stock is not enough. Customers of this system can search for a automobile; can purchase a automobile easily by selecting fast. On the other hand the stock of automobiles can be maintained perfectly by the automobile shop manager overcoming the drawbacks of existing system.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Courier management system project report.pdfKamal Acharya
It is now-a-days very important for the people to send or receive articles like imported furniture, electronic items, gifts, business goods and the like. People depend vastly on different transport systems which mostly use the manual way of receiving and delivering the articles. There is no way to track the articles till they are received and there is no way to let the customer know what happened in transit, once he booked some articles. In such a situation, we need a system which completely computerizes the cargo activities including time to time tracking of the articles sent. This need is fulfilled by Courier Management System software which is online software for the cargo management people that enables them to receive the goods from a source and send them to a required destination and track their status from time to time.
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.
Vaccine management system project report documentation..pdfKamal Acharya
The Division of Vaccine and Immunization is facing increasing difficulty monitoring vaccines and other commodities distribution once they have been distributed from the national stores. With the introduction of new vaccines, more challenges have been anticipated with this additions posing serious threat to the already over strained vaccine supply chain system in Kenya.
TECHNICAL TRAINING MANUAL GENERAL FAMILIARIZATION COURSEDuvanRamosGarzon1
AIRCRAFT GENERAL
The Single Aisle is the most advanced family aircraft in service today, with fly-by-wire flight controls.
The A318, A319, A320 and A321 are twin-engine subsonic medium range aircraft.
The family offers a choice of engines
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.
Top 10 Oil and Gas Projects in Saudi Arabia 2024.pdf
Data Mining Applications And Feature Scope Survey
1. NIET Journal of Engineering & Technology (NIETJET)
Volume 6, Issue Winter 2017 ISSN: 2229-5828 (Print)
11 | Page
Publisher: Noida Institute of Engineering & Technology,
19, Knowledge Park-II, Institutional Area, Greater Noida (UP), India.
Abstract: We have concentrated on a range of strategies, methodologies, and distinct fields of research in this article, all
of which are useful and relevant in the field of data mining technologies. As we all know, numerous multinational
corporations and major corporations operate in various parts of the world. Each location of business may create significant
amounts of data. Corporate decision-makers need access to all of these data sources in order to make strategic decisions. The
data warehouse adds substantial value to the firm by increasing the efficiency of management decision-making. The
significance of strategic information systems like these is immediately recognised in an uncertain and highly competitive
corporate climate, but in today's business world, efficiency or speed is not the sole route to competitiveness. This massive
amount of data is available in the form of terabytes to petabytes, which has profoundly impacted research and engineering.
To evaluate, manage, and make decisions with such a large volume of data, we need data mining tools, which will alter
numerous fields. This work provides a greater number of data mining applications as well as a more focused scope of data
mining, which will be useful in future research.
Keywords: Task data mining and web mining, Life cycle in data mining, data mining visualization, Application on
data mining.
1. Introduction
Because the data is available in a variety of formats, the appropriate action may be made. Not only should these
facts be analysed, but they should also be used to make excellent decisions and keep track of them. The data should
be obtained from the database as and when the client requires it in order to make the best decision possible. This
method is referred to as data mining, knowledge hub, or simply KDD (Knowledge Discovery Process). The finding
of helpful the perception of "we are data abundant but information poor" drew a lot of attention in the field of
information technology.
Due to knowledge from massive collections of data in the subject of "Data mining,"
There is a massive amount of data, but we are hardly able to transform it into meaningful information and knowledge
for corporate decision-making. It is necessary to collect a large amount of data in order to develop information.
Different media, such as audio/video, numbers, text, figures, and hypertext formats, may be used. To fully use data,
a tool for automatic data summarization, extraction of the core of stored information, and pattern detection in raw
data is required.
With the massive amounts of data saved in files, databases, and other repositories, it is becoming increasingly vital
to build effective tools for data analysis and interpretation, as well as the extraction of useful information that may
aid decision-making.
The one and only Data Mining' is the answer to all of the above. The extraction of hidden predictive data is known
as data mining. Information from enormous datasets; it's a strong tool with a lot of promise for helping people. In
Data Mining Applications and Feature
Scope Survey
Dr Shahid1
, Mr Bijay Singh2
, Shuchi Sethi3
1
AP ,Deptt of ICT, ISBAT University, Kampala Uganda
2
Astt Prof, Netaji Subhash Institute of Technology, Patna
3
Research Scholar, Dept of Computer Science, Jamia Millia Islamia, New Delhi
2. NIET Journal of Engineering & Technology (NIETJET)
Volume 6, Issue Winter 2017 ISSN: 2229-5828 (Print)
12 | Page
Publisher: Noida Institute of Engineering & Technology,
19, Knowledge Park-II, Institutional Area, Greater Noida (UP), India.
their data warehouses, firms concentrate on the most important information [1,2,3,4]. Data mining software
forecasts future patterns and behaviours, allowing businesses to take preventative measures. Decisions based on
knowledge [2]. Data mining's automated, prospective assessments are a game changer.
Beyond the analysis of previous occurrences offered by prospective decision-making tools,
systems. Data mining techniques can provide answers to queries that were previouslytoo time consuming to address.
it takes a long time to fix They create databases in order to uncover hidden patterns and make predictions.
Information that specialists may overlook because it falls outside of their usual scope.
We presented a new approach of defining the KDD Process. Section 6 provides a brief overview of some of the
most often used data mining techniques. The heart of the article is Chapter 7, in which we examine applications and
recommend feature directions for various data mining applications.
1.1 Data Analysis for Exploratory Purposes:
A tremendous quantity of information is available in the repositories. This data mining activity will accomplish two
goals (i). Without knowing what the consumer is looking for, it (ii) analyses the data.
For the client, these tactics are engaging and visible.
1.2 Modeling that is descriptive:
It contains models for the data's overall probability distribution, partitioning of the p-dimensional space into groups,
and models characterising the connections between the variables.
1.3 Modeling for Prediction:
This approach allows the value of one variable to be predicted based on the values of other variables that are known.
1.4 Patterns and Rules to Look for:
This assignment is mostly utilised to uncover the cluster's hidden pattern as well as to locate the hidden pattern. A
cluster has a variety of designs and clusters of various sizes. The goal of this work is to figure out "how best we can
recognise patterns." This may be performed by employing rule induction and other data mining approaches such as
(K-Means/K-Medoids). This is referred to as the clustering algorithm.
1.5 Content-based retrieval:
The main goal of this work is to locate data sets that are regularly utilised in the audio/video and picture fields. It is
the discovery of a pattern in the data set that is comparable to the pattern of interest.
2. Data Mining System Types:
A variety of characteristics may be used to classify data mining systems. The categorisation is as follows:
2.1 Life Cycle of Data Mining:
A data mining project's life cycle is divided into six stages[2,4]. The stages are not in any particular order. It's
constantly necessary to switch back and forth
between stages. It is determined by the results of each step. The following are the key stages:
2.1.1 Understanding of Business:
This phase focuses on collecting a business knowledge of the project objectives and requirements, then translating
that information into a data mining issue definition and a preliminary plan to achieve the goals.
2.1.2 Data comprehension:
It begins with a data gathering phase to familiarise yourself with the data, find data quality issues, get early insights
into the data, or identify intriguing subsets to generate hypotheses about hidden information.
2.1.3 Preparation of Data:
This step takes all of the different data sets and creates the different types of activities based on the raw data.
3. NIET Journal of Engineering & Technology (NIETJET)
Volume 6, Issue Winter 2017 ISSN: 2229-5828 (Print)
13 | Page
Publisher: Noida Institute of Engineering & Technology,
19, Knowledge Park-II, Institutional Area, Greater Noida (UP), India.
2.2 Data Mining Model Visualization
The basic goal of data visualisation is to convey the general concept of the data mining methodology. The majority
of the time in data mining, we are getting data from repositories that are concealed. For a user, this is the most
challenging task. As a result, this depiction of the data mining approach aids us in providing the highest levels of
comprehension and trust.
Clustering is a phrase that refers to analysing various data items without consulting a recognised class level.
Unsupervised learning or segmentation are other terms for it. It is the process of dividing or segmenting data into
groups or clusters. Domain specialists evaluate the behaviour of the data to determine the clusters. The phrase
segmentation has a very precise meaning; it refers to the division of a database into separate groups of comparable
tuples. The process of displaying the summarised information from the data is known as summarization. The
association rule determines the relationship between the various properties. The mining of association rules is a
two-step procedure:
Identifying all frequent item sets and generating strong association rules from them.
3. Methods of Data Mining:
Rules and Decision Trees
Methods of Nonlinear Regression and Classification
Methods based on Examples
Graphical Dependency Models with Probabilistic Constraints
Models of Relational Learning
4. Applications of Data Mining in Healthcare:
Health data mining applications have a lot of promise and can be very beneficial .However, the availability of good
healthcare data is critical to the success of healthcare data mining. In this regard, the healthcare business must
investigate how data may be acquired, saved, processed, and mined more effectively. Standardization of clinical
language and data sharing across companies are two possible routes for enhancing the advantages of healthcare data
mining technologies.
4.1 Data mining is used for market basket analysis:
MBA students employ data mining techniques (Market Basket Analysis). When a consumer wants to buy anything,
this approach aids us in determining the relationships between the many goods that the customer has placed
4. NIET Journal of Engineering & Technology (NIETJET)
Volume 6, Issue Winter 2017 ISSN: 2229-5828 (Print)
14 | Page
Publisher: Noida Institute of Engineering & Technology,
19, Knowledge Park-II, Institutional Area, Greater Noida (UP), India.
in their shopping carts. The finding of such relationships, which enhances the business technique, may be found
here. In this approach, merchants employ data mining techniques to determine which consumers' intentions are
(buying the different pattern). In this way, the strategy is employed to increase business revenues while also assisting
in the purchase of connected things.
5. Data Mining's Purpose
Searching for important business information in a vast database, for example, locating connected goods in terabytes
of store scanner data, and mining a mountain for a vein of lucrative metal are all examples of data mining. Both
techniques need either sorting through a massive amount of data or probing it intelligently to determine where the
value is hidden. Data mining technology, when used with datasets of appropriate size and quality, can open up new
business prospects by enabling the following capabilities:
6. Conclusion:
The numerous data mining applications were briefly explored in this study. This review will aid academics in
concentrating on the many aspects of data mining. In a future course, we'll look at several classification techniques
and the importance of using evolutionary computing (genetic programming) to create effective data mining
classification systems. The majority of earlier research on data mining applications in various industries used a wide
range of data kinds, from text to pictures, and stored them in a variety of databases and data structures. Different
data mining approaches are employed to extract patterns and hence knowledge from these various datasets. Data
and technique selection for data mining is a crucial responsibility in this process, and it necessitates understanding.
Several attempts have been made to design and build a generic data mining system, but no system has been found
to be completely universal. As a result, for each domain, a domain expert's assistant is necessary. Domain experts
will lead the domain experts to successfully use their experience toward the production of data mining system
knowledge Domain specialists must determine the type of data that should be collected in a specific issue area, as
well as the selection of specific data for data mining, as well as the cleansing of data and data processing, pattern
extraction for knowledge development, and pattern interpretation and knowledge development.
Reference
[1] Introduction to Data Mining and Knowledge Discovery, Third Edition ISBN: 1-892095-02-5, Two Crows
Corporation, 10500 Falls Road, Potomac, MD 20854 (U.S.A.), 1999.
[2] Larose, D. T., “Discovering Knowledge in Data: An Introduction to Data Mining”, ISBN 0-471-66657-2, ohn
Wiley & Sons, Inc, 2005.
[3] Dunham, M. H., Sridhar S., “Data Mining: Introductory and Advanced Topics”, Pearson Education,New Delhi,
ISBN: 81-7758-785-4, 1st Edition, 2006
[4] Chapman, P., Clinton, J., Kerber, R., Khabaza, T., Reinartz, T., Shearer, C. and Wirth, R... “CRISP-DM 1.0 :
Step-by-step data mining guide, NCR Systems Engineering Copenhagen (USA and Denmark),
DaimlerChrysler AG (Germany), SPSS Inc. (USA) and OHRA Verzekeringenen Bank Group B.V (The
Netherlands), 2000”.
[5] Fayyad, U., Piatetsky-Shapiro, G., and Smyth P., “From Data Mining to Knowledge
[6] Discovery in Databases,” AI Magazine, American Association for Artificial Intelligence, 1996.
[7] Tan Pang-Ning, Steinbach, M., Vipin Kumar. “Introduction to Data Mining”, Pearson Education, New Delhi,
ISBN: 978-81-317-1472-0, 3rd Edition, 2009. Bernstein, A. and Provost, F., “An Intelligent Assistant for the
Knowledge Discovery Process”, Working Paper of the Center for Digital Economy Research, New York
University and also presented at the IJCAI 2001 Workshop on Wrappers for Performance Enhancement in
Knowledge Discovery in Databases.
[8] Baazaoui, Z., H., Faiz, S., and Ben Ghezala, H., “A Framework for Data Mining Based Multi-Agent: An
Application to Spatial Data, volume 5, ISSN 1307-6884,” Proceedings of World Academy of Science,
Engineering and Technology, April 2005.
[9] Rantzau, R. and Schwarz, H., “A Multi-Tier Architecture for High-Performance Data Mining, A Technical
Project Report of ESPRIT project, The consortium of CRITIKAL project, Attar Software Ltd. (UK), Gehe AG
(Denmark); Lloyds TSB Group (UK), Parallel Applications Centre, University of Southampton (UK), BWI,
University of Stuttgart (Denmark), IPVR, University of Stuttgart (Denmark)”.
[10]Botia, J. A., Garijo, M. y Velasco, J. R., Skarmeta, A. F., “A Generic Data mining System basic design and
implementation guidelines”, A Technical Project Report of
5. NIET Journal of Engineering & Technology (NIETJET)
Volume 6, Issue Winter 2017 ISSN: 2229-5828 (Print)
15 | Page
Publisher: Noida Institute of Engineering & Technology,
19, Knowledge Park-II, Institutional Area, Greater Noida (UP), India.
[11]CYCYTprojectofSpanishGovernment.1998.WebSite:
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.53.1935
[12]Campos, M. M., Stengard, P. J., Boriana, L. M., “Data-Centric Automated Data
Mining”,WebSite.:www.oracle.com/technology/products/bi/odm/pdf/automated_data_mining_paper_1205.pd
f.
[13]Amit ,Choudhary S P Singh, V K Pandey; 'A Low Power and High Gain CMOS Tunable OTA with Cascade
Current Mirrors',Volume No.2,Issue No.1,2013,PP.075-078,ISSN :2229-5828
[14]Anju Gauniya Pandey , Sanjita Das , S. P.Basu, Palak Srivastava; 'Design and Evaluation Of Nanoemulsion
For Delivery of Diclofenac Sodium',Volume No.2,Issue No.1,2013,PP.079-082,ISSN :2229-5828
[15]Raj Kumar Goel , Rinku Sharma Dixit, Dr. Manu Pratap Singh; 'Implementaion of Pattern Storage Neural
network As Associative Memory For Storage and Recalling of Finger Prints',Volume No.2,Issue
No.1,2013,PP.083-090,ISSN :2229-5828
[16]Amit Kumar Yadav, Satyendra Sharma; 'Design and Simulation of Multiplier for High -speed
Application',Volume No.2,Issue No.2,2014,PP.001-007,ISSN :2229-5828
[17]Deepak Kumar ,Anjana Rani Gupta, Somesh Kumar; 'Dynamic Simulation of Multiple Effect Evaporators in
Paper Industry Using MATLAB',Volume No.2,Issue No.2,2014,PP.008-014,ISSN :2229-5828
[18]Devendra Pratap, Satyendra Sharma; 'Planning and Modelling of Indoor WLAN Through Field Measurement
at 2.437 GHz Frequency',Volume No.2,Issue No.2,2014,PP.015-019,ISSN :2229-5828