PG Embedded Systems
www.pgembeddedsystems.com
#197 B, Surandai Road
Pavoorchatram,Tenkasi
Tirunelveli
Tamil Nadu
India 627 808
Tel:04633-251200
Mob:+91-98658-62045, +91-7598462045.
General Information and Enquiries:
g12ganesh@gmail.com
Data mining is an important part of business intelligence and refers to discovering interesting patterns from large amounts of data. It involves applying techniques from multiple disciplines like statistics, machine learning, and information science to large datasets. While organizations collect vast amounts of data, data mining is needed to extract useful knowledge and insights from it. Some common techniques of data mining include classification, clustering, association analysis, and outlier detection. Data mining tools can help organizations apply these techniques to gain intelligence from their data warehouses.
Iris Solutions is a Leading ISO Certified Training and placement Company.
We Providing Final year projects With Innovative training Methods.
Project Training & Course Classes Handling by Extraordinary Qualified Staffs and also Having Very good Infrastructure.
Job support for qualified candidates. Projects in Java, J2ee, Vb, C#, .Net, Embedded, VLSI & Matlab. domain Using Networking, Network security, Mobile computing, Image Processing,etc......
Eligibility:
M.E /M.TECH, MCA, M.Sc(CSE, IT)
B.E/ B.TECH (ECE, EEE, E&I, ICE, CSE, IT)
DIPLOMA (ECE, E&I, EEE, CSE, IT, ROBOTICS)
BCA, B.Sc (CSE, IT)
FINAL YEAR STUDENT PROJECTS
REALTIME PROJECT Assistance
HIGH QUALITY TRAINING AT AFFORDABLE COST
EMBEDDED SYSTEM PROJECTS:
. WIRELESS BASED EMBEDDED SYSTEM PROJECT
. ZIGBEE BASED WIRELESS SENSOR networks
. IEEE SOLVED PAPERS PROJECT
. RFID, SMART CARD AND FINGER PRINT PROJECT
. GSM/GPRS/GPS
. ROBOTICS PROJECT
. ELECTRICAL BASED EMBEDDED SYSTEM PROJECT
. POWER ELECTRONICS PROJECT
. MATLAB PROJECT
. IMAGE PROCESSING PROJECT
*POWER ELECTRONIC ALL IEEE PAPARS…
VLSI& MATLAB.
SAFTWARE PROJECTS:
ANDROID PROJECTS
. JAVA/J2EE/J2ME PROJECTS
. .NET PROJECTS,VB,C#
. CLOUD COMPUTING PROJECTS
IMAGE PROCESSING PROJECTS
REAL TIME PROJECTS
IRIS SOLUTIONS.
Trichy - 9943 314 314
Tanjore- 9943 317 317
Kumbakonam- 9943 357 357
www.irisprojects.com
The document is a chapter from a textbook on data mining written by Akannsha A. Totewar, a professor at YCCE in Nagpur, India. It provides an introduction to data mining, including definitions of data mining, the motivation and evolution of the field, common data mining tasks, and major issues in data mining such as methodology, performance, and privacy.
Dsp Project Titles, 2009 2010 Ncct Final Year Projectsncct
Final Year Projects, IEEE Projects, Final Year Projects in Chennai, Final Year IEEE Projects, final year projects, college projects, student projects, java projects, asp.net projects, software projects, software ieee projects, ieee 2009 projects, 2009 ieee projects, embedded projects, final year software projects, final year embedded projects, ieee embedded projects, matlab projects, microcontroller projects, vlsi projects, dsp projects, free projects, project review, project report, project presentation, free source code, free project report, Final Year Projects, IEEE Projects, Final Year Projects in Chennai, Final Year IEEE Projects, final year projects, college projects, student projects, java projects, asp.net projects, software projects, software ieee projects, ieee 2009 projects, 2009 ieee projects, embedded projects, final year software projects, final year embedded projects, ieee embedded projects, matlab projects
Detecting phishing websites using associative classification (2)Alexander Decker
This document summarizes research on using data mining techniques like associative classification algorithms to detect phishing websites. It discusses how phishing aims to steal personal information through fake websites mimicking real ones. The paper reviews previous work applying classification and association rule mining to phishing detection and compares algorithms like CBA and MCAR. The goal is to investigate using automated data mining to help classify websites as phishing or not based on characteristics like URL errors.
Data-Mining Twitter for Political Science -Hickman, Alfredo - Honors ThesisAlfredo Hickman
This thesis examines the creation of a data mining system to extract, process, and analyze tweets from Twitter for use in political science research. The author builds an information system that collects Twitter data in real-time from a random list of 279 Members of Congress. The tweets and accompanying metadata are analyzed to provide insights into political behavior and discourse. By studying uncensored political discussions online, researchers can better understand important issues, how information spreads, and identify political networks. Analyzing social media can advance understanding of government communication and enhance research on political deliberation.
ieee projects 2014-15 for cse with abstract and base paper vsanthosh05
Siddhi Soft Solutions is a software development company that offers customized business and software solutions. It has expertise in developing complex software solutions. The company aims to exceed client expectations with innovative IT services, applications, and support solutions delivered on time. Siddhi Soft is experienced in software and web application development, and builds long-term relationships with clients by ensuring high quality and customer service.
Data mining is an important part of business intelligence and refers to discovering interesting patterns from large amounts of data. It involves applying techniques from multiple disciplines like statistics, machine learning, and information science to large datasets. While organizations collect vast amounts of data, data mining is needed to extract useful knowledge and insights from it. Some common techniques of data mining include classification, clustering, association analysis, and outlier detection. Data mining tools can help organizations apply these techniques to gain intelligence from their data warehouses.
Iris Solutions is a Leading ISO Certified Training and placement Company.
We Providing Final year projects With Innovative training Methods.
Project Training & Course Classes Handling by Extraordinary Qualified Staffs and also Having Very good Infrastructure.
Job support for qualified candidates. Projects in Java, J2ee, Vb, C#, .Net, Embedded, VLSI & Matlab. domain Using Networking, Network security, Mobile computing, Image Processing,etc......
Eligibility:
M.E /M.TECH, MCA, M.Sc(CSE, IT)
B.E/ B.TECH (ECE, EEE, E&I, ICE, CSE, IT)
DIPLOMA (ECE, E&I, EEE, CSE, IT, ROBOTICS)
BCA, B.Sc (CSE, IT)
FINAL YEAR STUDENT PROJECTS
REALTIME PROJECT Assistance
HIGH QUALITY TRAINING AT AFFORDABLE COST
EMBEDDED SYSTEM PROJECTS:
. WIRELESS BASED EMBEDDED SYSTEM PROJECT
. ZIGBEE BASED WIRELESS SENSOR networks
. IEEE SOLVED PAPERS PROJECT
. RFID, SMART CARD AND FINGER PRINT PROJECT
. GSM/GPRS/GPS
. ROBOTICS PROJECT
. ELECTRICAL BASED EMBEDDED SYSTEM PROJECT
. POWER ELECTRONICS PROJECT
. MATLAB PROJECT
. IMAGE PROCESSING PROJECT
*POWER ELECTRONIC ALL IEEE PAPARS…
VLSI& MATLAB.
SAFTWARE PROJECTS:
ANDROID PROJECTS
. JAVA/J2EE/J2ME PROJECTS
. .NET PROJECTS,VB,C#
. CLOUD COMPUTING PROJECTS
IMAGE PROCESSING PROJECTS
REAL TIME PROJECTS
IRIS SOLUTIONS.
Trichy - 9943 314 314
Tanjore- 9943 317 317
Kumbakonam- 9943 357 357
www.irisprojects.com
The document is a chapter from a textbook on data mining written by Akannsha A. Totewar, a professor at YCCE in Nagpur, India. It provides an introduction to data mining, including definitions of data mining, the motivation and evolution of the field, common data mining tasks, and major issues in data mining such as methodology, performance, and privacy.
Dsp Project Titles, 2009 2010 Ncct Final Year Projectsncct
Final Year Projects, IEEE Projects, Final Year Projects in Chennai, Final Year IEEE Projects, final year projects, college projects, student projects, java projects, asp.net projects, software projects, software ieee projects, ieee 2009 projects, 2009 ieee projects, embedded projects, final year software projects, final year embedded projects, ieee embedded projects, matlab projects, microcontroller projects, vlsi projects, dsp projects, free projects, project review, project report, project presentation, free source code, free project report, Final Year Projects, IEEE Projects, Final Year Projects in Chennai, Final Year IEEE Projects, final year projects, college projects, student projects, java projects, asp.net projects, software projects, software ieee projects, ieee 2009 projects, 2009 ieee projects, embedded projects, final year software projects, final year embedded projects, ieee embedded projects, matlab projects
Detecting phishing websites using associative classification (2)Alexander Decker
This document summarizes research on using data mining techniques like associative classification algorithms to detect phishing websites. It discusses how phishing aims to steal personal information through fake websites mimicking real ones. The paper reviews previous work applying classification and association rule mining to phishing detection and compares algorithms like CBA and MCAR. The goal is to investigate using automated data mining to help classify websites as phishing or not based on characteristics like URL errors.
Data-Mining Twitter for Political Science -Hickman, Alfredo - Honors ThesisAlfredo Hickman
This thesis examines the creation of a data mining system to extract, process, and analyze tweets from Twitter for use in political science research. The author builds an information system that collects Twitter data in real-time from a random list of 279 Members of Congress. The tweets and accompanying metadata are analyzed to provide insights into political behavior and discourse. By studying uncensored political discussions online, researchers can better understand important issues, how information spreads, and identify political networks. Analyzing social media can advance understanding of government communication and enhance research on political deliberation.
ieee projects 2014-15 for cse with abstract and base paper vsanthosh05
Siddhi Soft Solutions is a software development company that offers customized business and software solutions. It has expertise in developing complex software solutions. The company aims to exceed client expectations with innovative IT services, applications, and support solutions delivered on time. Siddhi Soft is experienced in software and web application development, and builds long-term relationships with clients by ensuring high quality and customer service.
This chapter discusses selection statements in C++. It covers relational expressions, if-else statements, nested if statements, the switch statement, and common programming errors. Relational expressions are used to compare operands and evaluate to true or false. If-else statements select between two statements based on a condition. Nested if statements allow if statements within other if statements. The switch statement compares a value to multiple cases and executes the matching case's statements. Programming errors can occur from incorrect operators, unpaired braces, and untested conditions.
This document describes a data mining project to detect fraud using two different datasets. It outlines using the CRISP-DM methodology to define the business problem, understand the data, prepare the data, choose modeling techniques, evaluate results, and deploy models. Specifically, it will analyze German credit card and Give Me Some Credit datasets using classification algorithms to predict fraudulent transactions and financial distress. The goal is to help financial institutions and individuals prevent identity theft and make smarter credit decisions.
The document discusses conditional statements in C# including if, if-else, nested if statements, and switch-case statements. It covers:
- Comparison and logical operators that are used to compose logical conditions for conditional statements
- How the if and if-else statements provide conditional execution of code blocks based on evaluating conditions
- Nested if statements allow creating more complex logic by placing if statements inside other if or else blocks
- The switch-case statement selects code for execution depending on the value of an expression, making it useful for multiple comparisons
The document discusses various concepts in data mining and decision trees including:
1) Pruning trees to address overfitting and improve generalization,
2) Separating data into training, development and test sets to evaluate model performance,
3) Information gain favoring attributes with many values by having less entropy,
4) Strategies for dealing with missing attribute values such as predicting values or focusing on other attributes/classes,
5) Changing stopping conditions for regression trees to use standard deviation thresholds rather than discrete classes.
The document discusses perceptrons and gradient descent algorithms for training perceptrons on classification tasks. It contains 4 exercises:
1) Explains the role of the learning rate in perceptron training and which Boolean functions can/cannot be modeled with perceptrons.
2) Applies a perceptron to a sample dataset, calculates outputs, and determines the accuracy.
3) Performs one iteration of gradient descent on the same dataset, computing weight updates with a learning rate of 0.2.
4) Performs one iteration of stochastic gradient descent on the dataset, recomputing outputs and updating weights after each instance.
Tree pruning removes parts of a decision tree that overfit the training data due to noise or outliers, making the tree smaller and less complex. There are two pruning strategies: postpruning removes subtrees after full tree growth, while prepruning stops growing branches when information becomes unreliable. Decision tree algorithms are efficient for small datasets but have performance issues for very large real-world datasets that may not fit in memory.
The document describes speech channel assignment and channel mode modification procedures in 3 G mobile networks. It discusses (1) how the BSC assigns TCH channels to an MS based on a service request, (2) the internal BSC signaling for channel assignment, and (3) how the BSC modifies the channel mode based on an assignment request from the MSC.
Applied Machine Learning For Search Engine Relevance charlesmartin14
The document discusses machine learning techniques for search engine relevance and personalized recommendations. It describes using linear regression models to predict relevance scores and regularization methods like Tikhonov regularization to avoid overfitting. It also discusses using empirical Bayesian models like the Poisson gamma model to estimate relevance probabilities. Finally, it mentions using techniques like singular value decomposition and non-negative matrix factorization to find patterns in user behavior data and remove noise.
Product Description:
Repair And Service:-
We bring forth our vast industrial experience and expertise in this business and are instrumental in offering wide assortment of Agricultural Motor Pump.
CONTACT:-
P.GANESAN
MOBILE : 9865862045, 7598462045
Mail Id : g14ganesh@gmail.com
Our accomplished and dedicated professionals are occupied in presenting a world class series of Pump Set, Diesel Engine Pump Set. It is available with us in diverse specifications that meet on customer’s demand. The entire array is checked on defined quality norms prior to its dispatch. These products are extremely praised by our customers for their durability, easy to use and top quality.
PRODUCT DESCRIPTION:-
We also provide our customers with various PTC Diesel Engine Pump Sets. These are designed to offer excellent operational efficiency along with ensuring high discharge rate and fuel efficiency.
This 3 sentence summary provides the high level information from the document:
The document describes a diesel pump set that is priced at approximately Rs 17,000 per piece. The diesel pump set has a discharge pressure of 12 HP and is described as providing optimum quality.
We are involved in offering a wide range of Diesel Pump Set to our most valued clients. Our range of Diesel Pump Set is widely appreciated by our clients which are situated all round the nation. These are manufactured as per the set industry standards using supreme class components under our experts’ supervision. We offer our range of Diesel Pump Set at most affordable prices.
We are remarkable entity, engaged in offering superior assortment of Domestic Water Booster Pump that is suitable for using in bungalow as pressure boosting unit for bathrooms, shower and shower panel. Designed and developed at our vendors’ end in compliance with defined quality standards using high grade raw materials, this pump booster is broadly demanded in the market. To ensure excellent quality, it is quality tested on well defined parameters by our team of quality analysts.
We are the leading organization in the industry to provide our clients the best quality range of Booster Pump. The provided Booster Pump is exclusively manufactured by our highly experienced professionals using the best grade components and modern technology. Offered Booster Pump is available in various technical specifications as per the requirements of our precious clients. Further, our valuable clients can avail this Booster Pump from us at most affordable price.
PG Embedded Systems
www.pgembeddedsystems.com
#197 B, Surandai Road
Pavoorchatram,Tenkasi
Tirunelveli
Tamil Nadu
India 627 808
Tel:04633-251200
Mob:+91-98658-62045, +91-7598462045.
General Information and Enquiries:
g12ganesh@gmail.com
The document lists 20 communication projects from 2014-2015. The projects cover various topics in communication domains including wireless sensor networks, cognitive radio networks, cooperative positioning, MIMO, relay networks, and more. The projects aim to improve techniques for spectrum sensing, energy efficiency, positioning, resource allocation, and other challenges in wireless communication networks.
PG Embedded Systems
www.pgembeddedsystems.com
#197 B, Surandai Road
Pavoorchatram,Tenkasi
Tirunelveli
Tamil Nadu
India 627 808
Tel:04633-251200
Mob:+91-98658-62045, +91-7598462045.
General Information and Enquiries:
g12ganesh@gmail.com
International Conference on NLP, Artificial Intelligence, Machine Learning an...gerogepatton
International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2024) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.
This chapter discusses selection statements in C++. It covers relational expressions, if-else statements, nested if statements, the switch statement, and common programming errors. Relational expressions are used to compare operands and evaluate to true or false. If-else statements select between two statements based on a condition. Nested if statements allow if statements within other if statements. The switch statement compares a value to multiple cases and executes the matching case's statements. Programming errors can occur from incorrect operators, unpaired braces, and untested conditions.
This document describes a data mining project to detect fraud using two different datasets. It outlines using the CRISP-DM methodology to define the business problem, understand the data, prepare the data, choose modeling techniques, evaluate results, and deploy models. Specifically, it will analyze German credit card and Give Me Some Credit datasets using classification algorithms to predict fraudulent transactions and financial distress. The goal is to help financial institutions and individuals prevent identity theft and make smarter credit decisions.
The document discusses conditional statements in C# including if, if-else, nested if statements, and switch-case statements. It covers:
- Comparison and logical operators that are used to compose logical conditions for conditional statements
- How the if and if-else statements provide conditional execution of code blocks based on evaluating conditions
- Nested if statements allow creating more complex logic by placing if statements inside other if or else blocks
- The switch-case statement selects code for execution depending on the value of an expression, making it useful for multiple comparisons
The document discusses various concepts in data mining and decision trees including:
1) Pruning trees to address overfitting and improve generalization,
2) Separating data into training, development and test sets to evaluate model performance,
3) Information gain favoring attributes with many values by having less entropy,
4) Strategies for dealing with missing attribute values such as predicting values or focusing on other attributes/classes,
5) Changing stopping conditions for regression trees to use standard deviation thresholds rather than discrete classes.
The document discusses perceptrons and gradient descent algorithms for training perceptrons on classification tasks. It contains 4 exercises:
1) Explains the role of the learning rate in perceptron training and which Boolean functions can/cannot be modeled with perceptrons.
2) Applies a perceptron to a sample dataset, calculates outputs, and determines the accuracy.
3) Performs one iteration of gradient descent on the same dataset, computing weight updates with a learning rate of 0.2.
4) Performs one iteration of stochastic gradient descent on the dataset, recomputing outputs and updating weights after each instance.
Tree pruning removes parts of a decision tree that overfit the training data due to noise or outliers, making the tree smaller and less complex. There are two pruning strategies: postpruning removes subtrees after full tree growth, while prepruning stops growing branches when information becomes unreliable. Decision tree algorithms are efficient for small datasets but have performance issues for very large real-world datasets that may not fit in memory.
The document describes speech channel assignment and channel mode modification procedures in 3 G mobile networks. It discusses (1) how the BSC assigns TCH channels to an MS based on a service request, (2) the internal BSC signaling for channel assignment, and (3) how the BSC modifies the channel mode based on an assignment request from the MSC.
Applied Machine Learning For Search Engine Relevance charlesmartin14
The document discusses machine learning techniques for search engine relevance and personalized recommendations. It describes using linear regression models to predict relevance scores and regularization methods like Tikhonov regularization to avoid overfitting. It also discusses using empirical Bayesian models like the Poisson gamma model to estimate relevance probabilities. Finally, it mentions using techniques like singular value decomposition and non-negative matrix factorization to find patterns in user behavior data and remove noise.
Product Description:
Repair And Service:-
We bring forth our vast industrial experience and expertise in this business and are instrumental in offering wide assortment of Agricultural Motor Pump.
CONTACT:-
P.GANESAN
MOBILE : 9865862045, 7598462045
Mail Id : g14ganesh@gmail.com
Our accomplished and dedicated professionals are occupied in presenting a world class series of Pump Set, Diesel Engine Pump Set. It is available with us in diverse specifications that meet on customer’s demand. The entire array is checked on defined quality norms prior to its dispatch. These products are extremely praised by our customers for their durability, easy to use and top quality.
PRODUCT DESCRIPTION:-
We also provide our customers with various PTC Diesel Engine Pump Sets. These are designed to offer excellent operational efficiency along with ensuring high discharge rate and fuel efficiency.
This 3 sentence summary provides the high level information from the document:
The document describes a diesel pump set that is priced at approximately Rs 17,000 per piece. The diesel pump set has a discharge pressure of 12 HP and is described as providing optimum quality.
We are involved in offering a wide range of Diesel Pump Set to our most valued clients. Our range of Diesel Pump Set is widely appreciated by our clients which are situated all round the nation. These are manufactured as per the set industry standards using supreme class components under our experts’ supervision. We offer our range of Diesel Pump Set at most affordable prices.
We are remarkable entity, engaged in offering superior assortment of Domestic Water Booster Pump that is suitable for using in bungalow as pressure boosting unit for bathrooms, shower and shower panel. Designed and developed at our vendors’ end in compliance with defined quality standards using high grade raw materials, this pump booster is broadly demanded in the market. To ensure excellent quality, it is quality tested on well defined parameters by our team of quality analysts.
We are the leading organization in the industry to provide our clients the best quality range of Booster Pump. The provided Booster Pump is exclusively manufactured by our highly experienced professionals using the best grade components and modern technology. Offered Booster Pump is available in various technical specifications as per the requirements of our precious clients. Further, our valuable clients can avail this Booster Pump from us at most affordable price.
PG Embedded Systems
www.pgembeddedsystems.com
#197 B, Surandai Road
Pavoorchatram,Tenkasi
Tirunelveli
Tamil Nadu
India 627 808
Tel:04633-251200
Mob:+91-98658-62045, +91-7598462045.
General Information and Enquiries:
g12ganesh@gmail.com
The document lists 20 communication projects from 2014-2015. The projects cover various topics in communication domains including wireless sensor networks, cognitive radio networks, cooperative positioning, MIMO, relay networks, and more. The projects aim to improve techniques for spectrum sensing, energy efficiency, positioning, resource allocation, and other challenges in wireless communication networks.
PG Embedded Systems
www.pgembeddedsystems.com
#197 B, Surandai Road
Pavoorchatram,Tenkasi
Tirunelveli
Tamil Nadu
India 627 808
Tel:04633-251200
Mob:+91-98658-62045, +91-7598462045.
General Information and Enquiries:
g12ganesh@gmail.com
International Conference on NLP, Artificial Intelligence, Machine Learning an...gerogepatton
International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2024) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.
Use PyCharm for remote debugging of WSL on a Windo cf5c162d672e4e58b4dde5d797...shadow0702a
This document serves as a comprehensive step-by-step guide on how to effectively use PyCharm for remote debugging of the Windows Subsystem for Linux (WSL) on a local Windows machine. It meticulously outlines several critical steps in the process, starting with the crucial task of enabling permissions, followed by the installation and configuration of WSL.
The guide then proceeds to explain how to set up the SSH service within the WSL environment, an integral part of the process. Alongside this, it also provides detailed instructions on how to modify the inbound rules of the Windows firewall to facilitate the process, ensuring that there are no connectivity issues that could potentially hinder the debugging process.
The document further emphasizes on the importance of checking the connection between the Windows and WSL environments, providing instructions on how to ensure that the connection is optimal and ready for remote debugging.
It also offers an in-depth guide on how to configure the WSL interpreter and files within the PyCharm environment. This is essential for ensuring that the debugging process is set up correctly and that the program can be run effectively within the WSL terminal.
Additionally, the document provides guidance on how to set up breakpoints for debugging, a fundamental aspect of the debugging process which allows the developer to stop the execution of their code at certain points and inspect their program at those stages.
Finally, the document concludes by providing a link to a reference blog. This blog offers additional information and guidance on configuring the remote Python interpreter in PyCharm, providing the reader with a well-rounded understanding of the process.
Software Engineering and Project Management - Introduction, Modeling Concepts...Prakhyath Rai
Introduction, Modeling Concepts and Class Modeling: What is Object orientation? What is OO development? OO Themes; Evidence for usefulness of OO development; OO modeling history. Modeling
as Design technique: Modeling, abstraction, The Three models. Class Modeling: Object and Class Concept, Link and associations concepts, Generalization and Inheritance, A sample class model, Navigation of class models, and UML diagrams
Building the Analysis Models: Requirement Analysis, Analysis Model Approaches, Data modeling Concepts, Object Oriented Analysis, Scenario-Based Modeling, Flow-Oriented Modeling, class Based Modeling, Creating a Behavioral Model.
The CBC machine is a common diagnostic tool used by doctors to measure a patient's red blood cell count, white blood cell count and platelet count. The machine uses a small sample of the patient's blood, which is then placed into special tubes and analyzed. The results of the analysis are then displayed on a screen for the doctor to review. The CBC machine is an important tool for diagnosing various conditions, such as anemia, infection and leukemia. It can also help to monitor a patient's response to treatment.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
artificial intelligence and data science contents.pptxGauravCar
What is artificial intelligence? Artificial intelligence is the ability of a computer or computer-controlled robot to perform tasks that are commonly associated with the intellectual processes characteristic of humans, such as the ability to reason.
› ...
Artificial intelligence (AI) | Definitio
The Python for beginners. This is an advance computer language.
IEEE 2014 - 2015 DATA MINING PROJECT TITLES
1. www.pgembeddedsystems.com
DATA MINING PROJECT TITLES 2014 – 2015
S.NO PROJECT TITLES DOMAIN YEAR
1 A Unified Data Embedding and
Scrambling Method
Data mining 2014
2 A Uniform Time-Domain Finite Integration
Technique (TDFIT) Using an Eff cient Extraction of
Conformal Information
Data mining 2014
3 An Active Sensing Principle for Haptic Interaction With
Dynamical Systems
Data mining 2014
4 An Asymmetric Matching Method for a Robust Binary
Audio Fingerprinting
Data mining 2014
5 An EEMD-IVA Framework for Concurrent
Multidimensional EEG and Unidimensional Kinematic
Data Analysis
Data mining 2014
6 Analyzing Implicit Social Networks in Multiplayer
Online Games
Data mining 2014
7 Big Mobile Data Mining:
Good or Evil?
Data mining 2014
8 Bitcoin: Benefit or Curse? Data mining 2014
9 Data Hiding in Encrypted H.264/AVC Video Streams
by Codeword Substitution
Data mining 2014
10 Data Mining for Optimizing IC Feature Designs to
Enhance Overall Wafer Effectiveness
Data mining 2014
11 Data Mining with Big Data Data mining 2014
12 Dependency Parse Reranking
with Rich Subtree Features
Data mining 2014
13 Depth-Assisted Temporal Error Concealment fo Intra
Frame Slices in 3-D Video
Data mining 2014
2. www.pgembeddedsystems.com
14 Developing Vehicular Data Cloud
Services in the IoT Environment
Data mining 2014
15 Discriminative Multimetric Learning
for Kinship Verification
Data mining 2014
16 Generating Summary Risk Scores
for Mobile Applications
Data mining 2014
17 Guest Editorial: Data Mining in
Bioinformatics,Biomedicine, and Healthcare
Informatics
Data mining 2014
18 Investigation of Dominant Failure Mode(s) for Field-
Aged Crystalline Silicon PV Modules Under Desert
Climatic Conditions
Data mining 2014
19 Local State Space Analysis Leads to
Better Partial Order Reduction
Data mining 2014
20 Mining Gene Expression Data Focusing Cancer
Therapeutics: A Digest
Data mining 2014
21 Mining Private information from Public data: the
transantiago case
Data mining 2014
22 Mining Sensor Data in Cyber-Physical Systems Data mining 2014
23 Multilabel Image Classification via High-Order Label
Correlation Driven Active Learning
Data mining 2014
24 Persistent Homology of Delay Embeddings and its
Application to Wheeze Detection
Data mining 2014
25 SAR Image Categorization Using Parametric and
Nonparametric Approaches Within a Dual Tree CWT
Data mining 2014
26 Signal-Integrity Optimization for Complicated Multiple-
Input Multiple-Output Networks Based on Data Mining
of S-Parameters
Data mining 2014
27 Sport Type Classification of Mobile Videos Data mining 2014
28 Topic-Sensitive Influencer Mining in Interest-Based
Social Media Networks via Hypergraph Learning
Data mining 2014
3. www.pgembeddedsystems.com
29 Online Feature Selection and Its Applications Data mining 2014
30 Imaging of Compact Objects Buried in Underwater
Sediments Using Electrical Impedance Tomography
Data mining 2014
31 A Differential Sequence Component Protection Scheme
for Microgrids With Inverter-Based Distributed
Generators
Data mining 2014
32 Decision Trees for Mining Data Streams Based on the
Gaussian Approximation
Data mining 2014
33 Discovering Conservation Rules Data mining 2014
34 A Cocktail Approach for Travel
Package Recommendation
Data mining 2014
35 A Compressive Sensing based Secure Watermark
Detection and Privacy Preserving Storage Framework
Data mining 2014
36 A Flexible Approach to Finding Representative Pattern
Sets
Data mining 2014
37 A Framework for Goal-Oriented Discovery of
Resources in the RESTful Architecture
Data mining 2014
38 A Framework for Periodic Outlier Pattern Detection in
Time-Series Sequences
Data mining 2014
39 A Group Incremental Approach to Feature Selection
Applying Rough Set Technique
Data mining 2014
40 A K-Main Routes Approach to Spatial Network Activity
Summarization
Data mining 2014
41 A Multiple Migration and Stacking Algorithm Designed
for Land Mine Detection
Data mining 2014
42 A New Multiobjective Evolutionary Algorithm for
Mining a Reduced Set of Interesting Positive and
Negative Quantitative Association Rules
Data mining 2014
43 A Nonlinear Semantic-Preserving Projection Approach
to Visualize Multivariate Periodical Time Series
Data mining 2014
4. www.pgembeddedsystems.com
44 A Novel Graph-Based Estimation of the Distribution
Algorithm and Its Extension Using Reinforcement
Learning
Data mining 2014
45 A Novel Methodology for Assessing the Fall Risk
Using Low-Cost and Off-the-Shelf Devices
Data mining 2014
46 A Novel Protein Complex Identification Algorithm
Based on Connected Affinity Clique Extension (CACE)
Data mining 2014
47 A Probabilistic Approach to String
Transformation
Data mining 2014
48 A Retrieval Strategy for Case-Based Reasoning Using
Similarity and Association Knowledge
Data mining 2014
49 A Review on Multi-Label Learning Algorithms Data mining 2014
50 A Rough Hypercuboid Approach for Feature Selection
in Approximation Spaces
Data mining 2014
51 A Scalable Two-Phase Top-Down
Specialization Approach for Data
Anonymization Using MapReduce on Cloud
Data mining 2014
52 A Segmentation-Based Method to Extract Structural and
Evolutionary Features for Protein Fold Recognition
Data mining 2014
53 A Segmentation-Based Method to Extract Structural and
Evolutionary Features for Protein Fold Recognition
Data mining 2014
54 A System for Automatic Notification and Severity
Estimation of Automotive Accidents
Data mining 2014
55 A Two-Level Topic Model Towards Knowledge
Discovery from Citation Networks
Data mining 2014
56 A Unified Data Embedding and
Scrambling Method
Data mining 2014
57 A Unified Framework for Outlier Detection in Trace
Data Analysis
Data mining 2014
58 Activity Detection in Scientific Visualization Data mining 2014
5. www.pgembeddedsystems.com
59 Adaptation Regularization: A General
Framework for Transfer Learning
Data mining 2014
60 Adaptive Operator Selection With Bandits for a
Multiobjective Evolutionary Algorithm Based on
Decomposition
Data mining 2014
61 An EEMD-IVA Framework for Concurrent
Multidimensional EEG and Unidimensional Kinematic
Data Analysis
Data mining 2014
62 An Efficient Approach for Outlier Detection with
Imperfect Data Labels
Data mining 2014
63 An Efficient Recommendation Method for Improving
Business Process Modeling
Data mining 2014
64 An Evolutionary Multiobjective Approach for
Community Discovery in Dynamic Networks
Data mining 2014
65 An Integrated System for Regional Environmental
Monitoring and Management Based on Internet of
Things
Data mining 2014
66 An Intelligent Decision Support System for the
Operating Theater: A Case Study
Data mining 2014
67 An Ontology-Based Text Mining Method to Develop D-
Matrix from Unstructured Text
Data mining 2014
68 Automatic GCP Extraction of Fully
Polarimetric SAR Images
Data mining 2014
69 Automatic Generation of the Domain Module from
Electronic Textbooks: Method and Validation
Data mining 2014
70 Automatic Identification of Large Fragments in a Pile of
Broken Rock Using a Time-of-Flight Camera
Data mining 2014
71 Automatic Spectral–Spatial Classification Framework
Based on Attribute Profiles and Supervised Feature
Extraction
Data mining 2014
6. www.pgembeddedsystems.com
72 Chaos Theory-Based Data-Mining Technique for Image
Endmember Extraction: Laypunov Index
and Correlation Dimension (L and D)
Data mining 2014
73 CoDe Modeling of Graph Composition for Data
Warehouse Report Visualization
Data mining 2014
74 Collaborative Online Multitask Learning Data mining 2014
75 Collaborative Policy Administration Data mining 2014
76 CommTrust: Computing Multi-Dimensional Trust by
Mining E-Commerce Feedback Comments
Data mining 2014
77 Commuter Route Optimized Energy Management of
Hybrid Electric Vehicles
Data mining 2014
78 Complex Network Clustering by Multiobjective
Discrete Particle Swarm Optimization Based on
Decomposition
Data mining 2014
79 COMPOSE: A Semisupervised Learning Framework for
Initially Labeled Nonstationary Streaming Data
Data mining 2014
80 Consistency of Measurements of Wavelength Position
From Hyperspectral Imagery: Use of the Ferric Iron
Crystal Field Absorption at ∼900 nm as an Indicator of
Mineralogy
Data mining 2014
81 CoRE: A Context-Aware Relation
Extraction Method for Relation Completion
Data mining 2014
82 Data Hiding in Encrypted H.264/AVC Video Streams
by Codeword Substitution
Data mining 2014
83 Data Mining with Big Data Data mining 2014
84 Dealing With Concept Drifts in Process Mining Data mining 2014
85 Dependency Parse Reranking with Rich Subtree
Features
Data mining 2014
86 Depth-Assisted Temporal Error Concealment for Intra
Frame Slices in 3-D Video
Data mining 2014
7. www.pgembeddedsystems.com
87 Determining Process Model Precision and
Generalization with Weighted Artificial Negative
Events
Data mining 2014
88 Developing Vehicular Data Cloud
Services in the IoT Environment
Data mining 2014
89 Discovering the Top-k k Unexplained Sequences in
Time-Stamped Observation Data
Data mining 2014
90 Discriminative Multimetric Learning
for Kinship Verification
Data mining 2014
91 Efficient Enumeration of Minimal Unsafe States in
Complex Resource Allocation Systems
Data mining 2014
92 Enhancing Memory Recall via an Intelligent Social
Contact Management System
Data mining 2014
93 Ensembles of -Trees for Imbalanced Classification
Problems
Data mining 2014
94 Exploiting Environmental Information for Improved
Underwater Target Classification in Sonar Imagery
Data mining 2014
95 Extensions of Kmeans-Type Algorithms: A New
Clustering Framework by Integrating Intracluster
Compactness and Intercluster Separation
Data mining 2014
96 Fault Isolation of Nonlinear Processes Based on Fault
Directions and Features
Data mining 2014
97 Feature Learning for Image Classification via
Multiobjective Genetic Programming
Data mining 2014
98 Feature-Based Analysis of Plasma-Based Particle
Acceleration Data
Data mining 2014
99 Frame-Based Recovery of Corrupted Video Files Using
Video Codec Specifications
Data mining 2014
100 From Principal Curves to Granular Principal Curves Data mining 2014
101 Generating Summary Risk Scores
for Mobile Applications
Data mining 2014
8. www.pgembeddedsystems.com
102 HEigen: Spectral Analysis
for Billion-Scale Graphs
Data mining 2014
103 Hybrid Method Inference for the Construction of
Cooperative Regulatory Network in Human
Data mining 2014
104 Hypercube-Based Multipath Social Feature Routing in
Human Contact Networks
Data mining 2014
105 Identifying Features in Opinion Mining via Intrinsic and
Extrinsic Domain Relevance
Data mining 2014
106 Improved and Promising Identification
of Human MicroRNAs by Incorporating a High-Quality
Negative Set
Data mining 2014
107 Infrequent Weighted Itemset Mining
Using Frequent Pattern Growth
Data mining 2014
108 Instance-Level Constraint-Based Semisupervised
Learning With Imposed Space-Partitioning
Data mining 2014
109 Interpreting the Public Sentiment Variations on Twitter Data mining 2014
110 Knowledge Fusion for Probabilistic Generative
Classifiers with Data Mining Applications
Data mining 2014
111 Large-Scale Experimental Evaluation of Cluster
Representations for Multi objective Evolutionary
Clustering
Data mining 2014
112 Large-Scale Overlays and Trends: Visually Mining,
Panning and Zooming the Observable Universe
Data mining 2014
113 Learning Phenotype Structure Using
Sequence Model
Data mining 2014
114 Local State Space Analysis Leads to
Better Partial Order Reduction
Data mining 2014
115 Local Thresholding in General
Network Graphs
Data mining 2014
9. www.pgembeddedsystems.com
116 Maiter: An Asynchronous Graph Processing Framework
for Delta-Based Accumulative Iterative Computation
Data mining 2014
117 Measuring the Effects of Lighting Distribution on
Walking Speed and Head Pitch With Wearable Inertial
Measurement Units
Data mining 2014
118 Mining Gene Expression Data Focusing Cancer
Therapeutics: A Digest
Data mining 2014
119 Mining Probabilistically Frequent Sequential Patterns in
Large Uncertain Databases
Data mining 2014
120 Mining Recurring Concepts in a Dynamic Feature Space Data mining 2014
121 Mining Statistically Significant Co-location and
Segregation Patterns
Data mining 2014
122 Mining Weakly Labeled Web Facial Images for Search-
Based Face Annotation
Data mining 2014
123 Mobile App Classification with Enriched Contextual
Information
Data mining 2014
124 Multi-Aspect + Transitivity + Bias: An Integral Trust
Inference Model
Data mining 2014
125 MultiComm: Finding Community Structure in Multi-
Dimensional Networks
Data mining 2014
126 Multifrequency Excitation and Support Vector Machine
Regressor for
ECT Defect Characterization
Data mining 2014
127 Multilabel Image Classification via High-Order Label
Correlation Driven Active Learning
Data mining 2014
128 Nationwide Prediction of Drought Conditions in Iran
Based on Remote Sensing Data
Data mining 2014
129 Novel Just-In-Time Learning-Based Soft Sensor
Utilizing Non-Gaussian Information
Data mining 2014
10. www.pgembeddedsystems.com
130 OCCT: A One-Class Clustering Tree for Implementing
One-to-Many Data Linkage
Data mining 2014
131 Occurrence-Oriented Design Strategy for Developing
Business Process Monitoring Systems
Data mining 2014
132 On the Influence Propagation of Web Videos Data mining 2014
133 On the Use of Side Information for Mining Text Data Data mining 2014
134 Online Discovery of Gathering Patterns over
Trajectories
Data mining 2014
135 Optimization of Wind Power and Its Variability With a
Computational Intelligence Approach
Data mining 2014
136 Parameters Affecting Interferometric
Coherence—The Case of a Dynamic
Agricultural Region
Data mining 2014
137 Personalized Recommendation Combining User Interest
and Social Circle
Data mining 2014
138 Population Classification in Fire Evacuation: A
Multiobjective Particle Swarm Optimization Approach
Data mining 2014
139 Prediction of Human Activity by Discovering Temporal
Sequence Patterns
Data mining 2014
140 Probabilistic Aspect Mining Model for Drug Reviews Data mining 2014
141 Probabilistic Framework for Assessing the Accuracy of
Data Mining Tool for Online Prediction of Transient
Stability
Data mining 2014
142 Quantum to Classical Randomness Extractors Data mining 2014
143 QueRIE: Collaborative Database Exploration Data mining 2014
144 Random Projection Random Discretization
Ensembles—Ensembles of Linear Multivariate Decision
Trees
Data mining 2014
145 Reacting to Different Types of Concept Drift: The
Accuracy Updated Ensemble Algorithm
Data mining 2014
11. www.pgembeddedsystems.com
146 Reliability-Based Design Optimization for Cloud
Migration
Data mining 2014
147 REPENT: Analyzing the Nature
of Identifier Renamings
Data mining 2014
148 Retrieval-Based Face Annotation by Weak Label
Regularized Local Coordinate Coding
Data mining 2014
149 Right-Protected Data Publishing with Provable
Distance-Based Mining
Data mining 2014
150 Road Centerline Extraction in Complex Urban Scenes
From LiDAR Data Based on Multiple Features
Data mining 2014
151 Rough Sets, Kernel Set, and Spatiotemporal Outlier
Detection
Data mining 2014
152 SAR Automatic Target Recognition Using
Discriminative Graphical Models
Data mining 2014
153 Scalable Similarity Search With Topology Preserving
Hashing
Data mining 2014
154 Searching Dimension Incomplete Databases Data mining 2014
155 Secure Mining of Association Rules in
Horizontally Distributed Databases
Data mining 2014
156 Secure Two-Party Differentially Private Data Release
for Vertically Partitioned Data
Data mining 2014
157 Self-Adaptive Semantic Focused Crawler for Mining
Services Information Discovery
Data mining 2014
158 Semantic-Based Resource Discovery and Orchestration
in Home and Building Automation: A Multi-Agent
Approach
Data mining 2014
159 Semi-supervised Linear Discriminant Clustering Data mining 2014
160 Semisupervised Classification Through the Bag-of-
Paths Group Betweenness
Data mining 2014
161 Semisupervised Kernel Feature Extraction for Remote
Sensing Image Analysis
Data mining 2014
12. www.pgembeddedsystems.com
162 Semisupervised Wrapper Choice and
Generation for Print-Oriented Documents
Data mining 2014
163 Set Predicates in SQL: Enabling Set-Level Comparisons
for Dynamically Formed Groups
Data mining 2014
164 Signal-Integrity Optimization for Complicated Multiple-
Input Multiple-Output Networks Based on Data Mining
of S-Parameters
Data mining 2014
165 Similarity Searching for Defective Wafer Bin Maps in
Semiconductor Manufacturing
Data mining 2014
166 Social Network Modeling and Agent-Based Simulation
in Support of Crisis De-Escalation
Data mining 2014
167 Social Voting Advice Applications -
Definitions, Challenges, Datasets
and Evaluation
Data mining 2014
168 Sparse MIMO Array Forward-Looking GPR Imaging
Based on Compressed Sensing in Clutter Environment
Data mining 2014
169 Spatially Aware Term Selection for Geotagging Data mining 2014
170 Spatiotemporal Patterns in Large-Scale Traffic Speed
Prediction
Data mining 2014
171 Sport Type Classification of Mobile Videos Data mining 2014
172 Subgroup Discovery in Smart Electricity Meter Data Data mining 2014
173 Survey of Multiobjective Evolutionary Algorithms for
Data Mining: Part II
Data mining 2014
174 Temporal Analysis of Motif Mixtures
Using Dirichlet Processes
Data mining 2014
175 The Places of Our Lives: Visiting
Patterns and Automatic Labeling
from Longitudinal Smartphone Data
Data mining 2014
176 The Role of Hubness in Clustering
High-Dimensional Data
Data mining 2014
13. www.pgembeddedsystems.com
177 The Sum-over-Forests Density Index:
Identifying Dense Regions in a Graph
Data mining 2014
178 Thermography-Based Virtual MPPT Scheme for
Improving PV Energy Efficiency Under Partial Shading
Conditions
Data mining 2014
179 Topic-Sensitive Influencer Mining in Interest-Based
Social Media Networks via Hypergraph Learning
Data mining 2014
180 TotalPLS: Local Dimension Reduction for
Multicategory Microarray Data
Data mining 2014
181 Trajectory Improves Data Delivery in Urban Vehicular
Networks
Data mining 2014
182 Transfer Learning with Graph Co-Regularization Data mining 2014
183 Uncertain One-Class Learning and Concept
Summarization Learning on Uncertain Data Streams
Data mining 2014
184 Unified Design of a Feature-Based ADAC System for
Mine Hunting Using Synthetic Aperture Sonar
Data mining 2014
185 Using Delayed Observations for Long-Term Vehicle
Tracking in Large Environments
Data mining 2014
186 Using Incomplete Information for Complete Weight
Annotation of Road Networks
Data mining 2014
187 Variability Mining: Consistent Semi-automatic
Detection of Product-Line Features
Data mining 2014
188 Wireless Spectrum Occupancy Prediction Based on
Partial Periodic Pattern Mining
Data mining 2014
189 Performance Metric Ensemble for Multiobjective
Evolutionary Algorithms
Data mining 2014
190 Effective and Efficient Clustering Methods for
Correlated Probabilistic Graphs
Data mining 2014
191 Data Mining for Optimizing IC Feature Designs
to Enhance Overall Wafer Effectiveness
Data mining 2014