This document contains details of projects related to digital image processing and medical image processing. It lists 33 digital image processing projects and 30 medical image processing projects, each identified by a unique code. All projects are from 2014-2013 and presented at IEEE conferences. It also provides contact information for S3 Infotech.
VEHICLE CLASSIFICATION USING THE CONVOLUTION NEURAL NETWORK APPROACHJANAK TRIVEDI
We present vehicle detection classification using the Convolution
Neural Network (CNN) of the deep learning approach. The automatic vehicle
classification for traffic surveillance video systems is challenging for the Intelligent
Transportation System (ITS) to build a smart city. In this article, three different
vehicles: bike, car and truck classification are considered for around 3,000 bikes,
6,000 cars, and 2,000 images of trucks. CNN can automatically absorb and extract
different vehicle dataset’s different features without a manual selection of features.
The accuracy of CNN is measured in terms of the confidence values of the detected
object. The highest confidence value is about 0.99 in the case of the bike category
vehicle classification. The automatic vehicle classification supports building an
electronic toll collection system and identifying emergency vehicles in the traffic
Classification and Detection of Vehicles using Deep Learningijtsrd
The vehicle classification and detecting its license plate are important tasks in intelligent security and transportation systems. The traditional methods of vehicle classification and detection are highly complex which provides coarse grained results due to suffering from limited viewpoints. Because of the latest achievements of Deep Learning, it was successfully applied to image classification and detection of objects. This paper presents a method based on a convolutional neural network, which consists of two steps vehicle classification and vehicle license plate recognition. Several typical neural network modules have been applied in training and testing the vehicle Classification and detection of license plate model, such as CNN convolutional neural networks , TensorFlow, Tesseract OCR. The proposed method can identify the vehicle type, number plate and other information accurately. This model provides security and log details regarding vehicles by using AI Surveillance. It guides the surveillance operators and assists human resources. With the help of the original training dataset and enriched testing dataset, the algorithm can obtain results with an average accuracy of about 97.32 in the classification and detection of vehicles. By increasing the amount of the data, the mean error and misclassification rate gradually decreases. So, this algorithm which is based on Deep Learning has good superiority and adaptability. When compared to the leading methods in the challenging Image datasets, our deep learning approach obtains highly competitive results. Finally, this paper proposes modern methods for the improvement of the algorithm and prospects the development direction of deep learning in the field of machine learning and artificial intelligence. Madde Pavan Kumar | Dr. K. Manivel | N. Jayanthi "Classification & Detection of Vehicles using Deep Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-3 , April 2020, URL: https://www.ijtsrd.com/papers/ijtsrd30353.pdf Paper Url :https://www.ijtsrd.com/engineering/software-engineering/30353/classification-and-detection-of-vehicles-using-deep-learning/madde-pavan-kumar
Real Time Object Identification for Intelligent Video Surveillance ApplicationsEditor IJCATR
Intelligent video surveillance system has emerged as a very important research topic in the computer vision field in the
recent years. It is well suited for a broad range of applications such as to monitor activities at traffic intersections for detecting
congestions and predict the traffic flow. Object classification in the field of video surveillance is a key component of smart
surveillance software. Two robust methodology and algorithms adopted for people and object classification for automated surveillance
systems is proposed in this paper. First method uses background subtraction model for detecting the object motion. The background
subtraction and image segmentation based on morphological transformation for tracking and object classification on highways is
proposed. This algorithm uses erosion followed by dilation on various frames. Proposed algorithm in first method, segments the image
by preserving important edges which improves the adaptive background mixture model and makes the system learn faster and more
accurately. The system used in second method adopts the object detection method without background subtraction because of the static
object detection. Segmentation is done by the bounding box registration technique. Then the classification is done with the multiclass
SVM using the edge histogram as features. The edge histograms are calculated for various bin values in different environment. The
result obtained demonstrates the effectiveness of the proposed approach.
Foreground algorithms for detection and extraction of an object in multimedia...IJECEIAES
Background Subtraction of a foreground object in multimedia is one of the major preprocessing steps involved in many vision-based applications. The main logic for detecting moving objects from the video is difference of the current frame and a reference frame which is called “background image” and this method is known as frame differencing method. Background Subtraction is widely used for real-time motion gesture recognition to be used in gesture enabled items like vehicles or automated gadgets. It is also used in content-based video coding, traffic monitoring, object tracking, digital forensics and human-computer interaction. Now-a-days due to advent in technology it is noticed that most of the conferences, meetings and interviews are done on video calls. It’s quite obvious that a conference room like atmosphere is not always readily available at any point of time. To eradicate this issue, an efficient algorithm for foreground extraction in a multimedia on video calls is very much needed. This paper is not to just build Background Subtraction application for Mobile Platform but to optimize the existing OpenCV algorithm to work on limited resources on mobile platform without reducing the performance. In this paper, comparison of various foreground detection, extraction and feature detection algorithms are done on mobile platform using OpenCV. The set of experiments were conducted to appraise the efficiency of each algorithm over the other. The overall performances of these algorithms were compared on the basis of execution time, resolution and resources required.
VEHICLE CLASSIFICATION USING THE CONVOLUTION NEURAL NETWORK APPROACHJANAK TRIVEDI
We present vehicle detection classification using the Convolution
Neural Network (CNN) of the deep learning approach. The automatic vehicle
classification for traffic surveillance video systems is challenging for the Intelligent
Transportation System (ITS) to build a smart city. In this article, three different
vehicles: bike, car and truck classification are considered for around 3,000 bikes,
6,000 cars, and 2,000 images of trucks. CNN can automatically absorb and extract
different vehicle dataset’s different features without a manual selection of features.
The accuracy of CNN is measured in terms of the confidence values of the detected
object. The highest confidence value is about 0.99 in the case of the bike category
vehicle classification. The automatic vehicle classification supports building an
electronic toll collection system and identifying emergency vehicles in the traffic
Classification and Detection of Vehicles using Deep Learningijtsrd
The vehicle classification and detecting its license plate are important tasks in intelligent security and transportation systems. The traditional methods of vehicle classification and detection are highly complex which provides coarse grained results due to suffering from limited viewpoints. Because of the latest achievements of Deep Learning, it was successfully applied to image classification and detection of objects. This paper presents a method based on a convolutional neural network, which consists of two steps vehicle classification and vehicle license plate recognition. Several typical neural network modules have been applied in training and testing the vehicle Classification and detection of license plate model, such as CNN convolutional neural networks , TensorFlow, Tesseract OCR. The proposed method can identify the vehicle type, number plate and other information accurately. This model provides security and log details regarding vehicles by using AI Surveillance. It guides the surveillance operators and assists human resources. With the help of the original training dataset and enriched testing dataset, the algorithm can obtain results with an average accuracy of about 97.32 in the classification and detection of vehicles. By increasing the amount of the data, the mean error and misclassification rate gradually decreases. So, this algorithm which is based on Deep Learning has good superiority and adaptability. When compared to the leading methods in the challenging Image datasets, our deep learning approach obtains highly competitive results. Finally, this paper proposes modern methods for the improvement of the algorithm and prospects the development direction of deep learning in the field of machine learning and artificial intelligence. Madde Pavan Kumar | Dr. K. Manivel | N. Jayanthi "Classification & Detection of Vehicles using Deep Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-3 , April 2020, URL: https://www.ijtsrd.com/papers/ijtsrd30353.pdf Paper Url :https://www.ijtsrd.com/engineering/software-engineering/30353/classification-and-detection-of-vehicles-using-deep-learning/madde-pavan-kumar
Real Time Object Identification for Intelligent Video Surveillance ApplicationsEditor IJCATR
Intelligent video surveillance system has emerged as a very important research topic in the computer vision field in the
recent years. It is well suited for a broad range of applications such as to monitor activities at traffic intersections for detecting
congestions and predict the traffic flow. Object classification in the field of video surveillance is a key component of smart
surveillance software. Two robust methodology and algorithms adopted for people and object classification for automated surveillance
systems is proposed in this paper. First method uses background subtraction model for detecting the object motion. The background
subtraction and image segmentation based on morphological transformation for tracking and object classification on highways is
proposed. This algorithm uses erosion followed by dilation on various frames. Proposed algorithm in first method, segments the image
by preserving important edges which improves the adaptive background mixture model and makes the system learn faster and more
accurately. The system used in second method adopts the object detection method without background subtraction because of the static
object detection. Segmentation is done by the bounding box registration technique. Then the classification is done with the multiclass
SVM using the edge histogram as features. The edge histograms are calculated for various bin values in different environment. The
result obtained demonstrates the effectiveness of the proposed approach.
Foreground algorithms for detection and extraction of an object in multimedia...IJECEIAES
Background Subtraction of a foreground object in multimedia is one of the major preprocessing steps involved in many vision-based applications. The main logic for detecting moving objects from the video is difference of the current frame and a reference frame which is called “background image” and this method is known as frame differencing method. Background Subtraction is widely used for real-time motion gesture recognition to be used in gesture enabled items like vehicles or automated gadgets. It is also used in content-based video coding, traffic monitoring, object tracking, digital forensics and human-computer interaction. Now-a-days due to advent in technology it is noticed that most of the conferences, meetings and interviews are done on video calls. It’s quite obvious that a conference room like atmosphere is not always readily available at any point of time. To eradicate this issue, an efficient algorithm for foreground extraction in a multimedia on video calls is very much needed. This paper is not to just build Background Subtraction application for Mobile Platform but to optimize the existing OpenCV algorithm to work on limited resources on mobile platform without reducing the performance. In this paper, comparison of various foreground detection, extraction and feature detection algorithms are done on mobile platform using OpenCV. The set of experiments were conducted to appraise the efficiency of each algorithm over the other. The overall performances of these algorithms were compared on the basis of execution time, resolution and resources required.
HUMAN BODY DETECTION AND SAFETY CARE SYSTEM FOR A FLYING ROBOTcsandit
Image-processing is one the challenging issue in robotic as well as electrical engineering
research contexts. This study proposes a system for extract and tracking objects by a
quadcopter’s flying robot and how to extract the human body. It is observed in image taken
from real-time camera that is embedded bottom of the quadcopter, there is a variance in human
behaviour being tracked or recorded such as position and, size, of the human. In the regard, the
paper tries to investigate an image-processing method for tracking humans’ body, concurrently.
For this process, an extraction method, which defines features to distinguish a human body, is
proposed. The proposed method creates a virtual shape of bodies for recognizing the body of
humans, also, generate an extractor according to its edge information. This method shows
better performance in term of precision as well as speed experimentally.
Real Time Detection of Moving Object Based on Fpgaiosrjce
IOSR Journal of Electronics and Communication Engineering(IOSR-JECE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of electronics and communication engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in electronics and communication engineering. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
HARDWARE SOFTWARE CO-SIMULATION FOR TRAFFIC LOAD COMPUTATION USING MATLAB SIM...ijcsity
Due to increase in number of vehicles, Traffic is a major problem faced in urban areas throughout the
world. This document presents a newly developed Matlab Simulink model to compute traffic load for real
time traffic signal control. Signal processing, video and image processing and Xilinx Blockset have been
extensively used for traffic load computation. The approach used is Edge detection operation, wherein,
Edges are extracted to identify the number of vehicles. The developed model computes the results with
greater degrees of accuracy and is capable of being used to set the green signal duration so as to release
the traffic dynamically on traffic junctions.
Xilinx System Generator (XSG) provides Simulink Blockset for several hardware operations that could be
implemented on various Xilinx Field programmable gate arrays (FPGAs). The method described in this
paper involves object feature identification and detection. Xilinx System Generator provides some blocks to
transform data provided from the software side of the simulation environment to the hardware side. In our
case it is MATLAB Simulink to System Generator blocks. This is an important concept to understand in the
design process using Xilinx System Generator. The Xilinx System Generator, embedded in MATLAB
Simulink is used to program the model and then test on the FPGA board using the properties of hardware
co-simulation tools.
Basic geometric shape and primary colour detection using image processing on ...eSAT Journals
Abstract This paper gives an approach to identify basic geometric shapes and primary RGB colors in a 2 dimensional image using image processing techniques with the help of MATLAB. The basic shapes included are square, circle, triangle and rectangle. The algorithm involves conversion of RGB image to grey scale image and then to black and white image. This is achieved by thresholding concept, The area of the minimum bounding rectangle is calculated irrespective of the angle of rotation of the object and ratio of this area to area of the object is calculated and compared to the predefined ratio to determine the shape of the given object. The dominant color pixels present helps to determine the color of the object. The practical aspects of this include reducing the manual labour in industries used to segregate the products and providing real time vision to the robots. Keywords: MATLAB, RGB Image, Bounding Rectangle, Shape and Color Detection.
Automated Traffic sign board classification system is one of the key technologies of Intelligent
Transportation Systems (ITS). Traffic Surveillance System is being more and important with improving
urban scale and increasing number of vehicles. This Paper presents an intelligent sign board
classification method based on blob analysis in traffic surveillance. Processing is done by three main
steps: moving object segmentation, blob analysis, and classifying. A Sign board is modelled as a
rectangular patch and classified via blob analysis. By processing the blob of sign boards, the meaningful
features are extracted. Tracking moving targets is achieved by comparing the extracted features with
training data. After classifying the sign boards the system will intimate to user in the form of alarms,
sound waves. The experimental results show that the proposed system can provide real-time and useful
information for traffic surveillance.
Deep Learning for Biomedical Unstructured Time SeriesPetteriTeikariPhD
1D Convolutional neural networks (CNNs) for time series analysis, and inspiration from beyond biomedical field. Short intro for various different steps involved in Time Series Analysis including outlier detection, imputation, denoising, segmentation, classification and forecasting.
Available also from:
https://www.dropbox.com/s/cql2jhrt5mdyxne/timeSeries_deepLearning.pdf?dl=0
HUMAN BODY DETECTION AND SAFETY CARE SYSTEM FOR A FLYING ROBOTcsandit
Image-processing is one the challenging issue in robotic as well as electrical engineering
research contexts. This study proposes a system for extract and tracking objects by a
quadcopter’s flying robot and how to extract the human body. It is observed in image taken
from real-time camera that is embedded bottom of the quadcopter, there is a variance in human
behaviour being tracked or recorded such as position and, size, of the human. In the regard, the
paper tries to investigate an image-processing method for tracking humans’ body, concurrently.
For this process, an extraction method, which defines features to distinguish a human body, is
proposed. The proposed method creates a virtual shape of bodies for recognizing the body of
humans, also, generate an extractor according to its edge information. This method shows
better performance in term of precision as well as speed experimentally.
Real Time Detection of Moving Object Based on Fpgaiosrjce
IOSR Journal of Electronics and Communication Engineering(IOSR-JECE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of electronics and communication engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in electronics and communication engineering. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
HARDWARE SOFTWARE CO-SIMULATION FOR TRAFFIC LOAD COMPUTATION USING MATLAB SIM...ijcsity
Due to increase in number of vehicles, Traffic is a major problem faced in urban areas throughout the
world. This document presents a newly developed Matlab Simulink model to compute traffic load for real
time traffic signal control. Signal processing, video and image processing and Xilinx Blockset have been
extensively used for traffic load computation. The approach used is Edge detection operation, wherein,
Edges are extracted to identify the number of vehicles. The developed model computes the results with
greater degrees of accuracy and is capable of being used to set the green signal duration so as to release
the traffic dynamically on traffic junctions.
Xilinx System Generator (XSG) provides Simulink Blockset for several hardware operations that could be
implemented on various Xilinx Field programmable gate arrays (FPGAs). The method described in this
paper involves object feature identification and detection. Xilinx System Generator provides some blocks to
transform data provided from the software side of the simulation environment to the hardware side. In our
case it is MATLAB Simulink to System Generator blocks. This is an important concept to understand in the
design process using Xilinx System Generator. The Xilinx System Generator, embedded in MATLAB
Simulink is used to program the model and then test on the FPGA board using the properties of hardware
co-simulation tools.
Basic geometric shape and primary colour detection using image processing on ...eSAT Journals
Abstract This paper gives an approach to identify basic geometric shapes and primary RGB colors in a 2 dimensional image using image processing techniques with the help of MATLAB. The basic shapes included are square, circle, triangle and rectangle. The algorithm involves conversion of RGB image to grey scale image and then to black and white image. This is achieved by thresholding concept, The area of the minimum bounding rectangle is calculated irrespective of the angle of rotation of the object and ratio of this area to area of the object is calculated and compared to the predefined ratio to determine the shape of the given object. The dominant color pixels present helps to determine the color of the object. The practical aspects of this include reducing the manual labour in industries used to segregate the products and providing real time vision to the robots. Keywords: MATLAB, RGB Image, Bounding Rectangle, Shape and Color Detection.
Automated Traffic sign board classification system is one of the key technologies of Intelligent
Transportation Systems (ITS). Traffic Surveillance System is being more and important with improving
urban scale and increasing number of vehicles. This Paper presents an intelligent sign board
classification method based on blob analysis in traffic surveillance. Processing is done by three main
steps: moving object segmentation, blob analysis, and classifying. A Sign board is modelled as a
rectangular patch and classified via blob analysis. By processing the blob of sign boards, the meaningful
features are extracted. Tracking moving targets is achieved by comparing the extracted features with
training data. After classifying the sign boards the system will intimate to user in the form of alarms,
sound waves. The experimental results show that the proposed system can provide real-time and useful
information for traffic surveillance.
Deep Learning for Biomedical Unstructured Time SeriesPetteriTeikariPhD
1D Convolutional neural networks (CNNs) for time series analysis, and inspiration from beyond biomedical field. Short intro for various different steps involved in Time Series Analysis including outlier detection, imputation, denoising, segmentation, classification and forecasting.
Available also from:
https://www.dropbox.com/s/cql2jhrt5mdyxne/timeSeries_deepLearning.pdf?dl=0
Smqt Based Fingerprint Enhancement And Encryption For Border Crossing Securit...theijes
Biometric passport (e-passport) is to prevent the illegitimate entry of traveler into a particular country and border the use of counterfeit documents by more accurate identification of an individual. The electronic passport, as it is sometimes called, represents a bold proposal in the procedure of two new technologies: cryptography authentication protocols and biometrics (face, fingerprints, palm prints and iris).The goal of the adoption of the electronic passport is not only to accelerate processing at border crossings, but also to increase safety measures. Adaptive fingerprint enhancement method is used to enhance the fingerprint image. The term adaptive implies that parameters of the method are automatically adjusted based on the input fingerprint image. The adaptive fingerprint enhancement method comprises five processing blocks. 1) Pre-processing; 2) global analysis; 3) local analysis; and 4) matched filtering; 4) Image segmentation. In the pre-processing and local analysis blocks, a nonlinear dynamic range adjustment method, SMQT is used. These processing blocks yield an improved and new adaptive fingerprint image processing method. . For assuring security cryptography can be used with enhancement technique for encrypting the enhanced image so as to provide additional protection against fake. For this an image encryption approach using stream ciphers based on non linear filter generator along with AES encryption is used here. In this work a novel image encryption scheme using stream cipher algorithm based on nonlinear filter generator is considered. In this work a novel image encryption scheme is proposed based on stream cipher algorithm using pseudorandom generator with filtering function. This algorithm makes it possible to cipher and decipher images by guaranteeing a maximum security. The proposed cryptosystem is based on the use the linear feedback shift register (LFSR) with large secret key filtered by resilient function whose resiliency order, algebraic degree and nonlinearity attain Siegenthaler’s and Sarkar, al.’s bounds. This scheme is simple and highly efficient.
Ieee 2014 2015 matlab projects titles list globalsoft technologiesIEEEDOTNETPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.globalsofttechnologies.org
Ieee 2014 2015 matlab projects titles list globalsoft technologiesIEEEJAVAPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.globalsofttechnologies.org
2014 2015 ieee matlab projects titles list globalsoft technologiesIEEEDOTNETPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.globalsofttechnologies.org
2014 2015 ieee matlab projects titles list globalsoft technologiesIEEEJAVAPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.globalsofttechnologies.org
Ieee 2014 2015 matlab projects titles list globalsoft technologiesIEEEMATLABPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.globalsofttechnologies.org
Ieee 2014 2015 matlab projects titles list globalsoft technologiesIEEEMATLABPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.globalsofttechnologies.org
Similar to Matlab titles 2014_2015_For ME_M.Tech (20)
NS2 Completed IEEE projects list are here. All this listed NS2 IEEE Projects are 100% completed projects. More Details call: 9884848198 (S3 Infotech IEEE Projects).
We offering Projects for EEE Projects, ECE Projects, CSE Projects, IT Projects for Students. We developing projects in all technologies like Dotnet, Java, MATLAB, VLSI, Embedded systems, NS2 & Hadoop bigdata technologies.
More Details call : +91 9884848198
S3 Infotech IEEE Projects
10/1, Jones Road,
Saidapet,
Chennai-600015
www.s3computes.com
MATLAB Completed IEEE projects list are here. All this listed MATLAB IEEE Projects are 100% completed projects. More Details call: 9884848198 (S3 Infotech IEEE Projects).
We offering Projects for EEE Projects, ECE Projects, CSE Projects, IT Projects for Students. We developing projects in all technologies like Dotnet, Java, MATLAB, VLSI, Embedded systems, NS2 & Hadoop bigdata technologies.
More Details call : +91 9884848198
S3 Infotech IEEE Projects
10/1, Jones Road,
Saidapet,
Chennai-600015
www.s3computes.com
We are Developing ME, M.Tech, BE, B.Tech, MCA & Phd IEEE 2015 projects in JAVA, Dotnet, MATLAB, VLSI, EMBEDDED, Hadoop & NS2 Technologies.
We Develop Your Own IEEE Concepts Also. We are giving support for National & International Level Assignment Preparation, Journal Preparation & Journal Publication also and we deliver projects through online itself. Send your base paper to yes3info@gmail.com or info@s3computers.com
S3 Infotech,
#10/1, Jones Road, Saidapet,
Chennai-600015, India.
Mob: +91 9884848198
www.s3computers.com
info@s3computers.com
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdfTechSoup
In this webinar you will learn how your organization can access TechSoup's wide variety of product discount and donation programs. From hardware to software, we'll give you a tour of the tools available to help your nonprofit with productivity, collaboration, financial management, donor tracking, security, and more.
Ethnobotany and Ethnopharmacology:
Ethnobotany in herbal drug evaluation,
Impact of Ethnobotany in traditional medicine,
New development in herbals,
Bio-prospecting tools for drug discovery,
Role of Ethnopharmacology in drug evaluation,
Reverse Pharmacology.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
This is a presentation by Dada Robert in a Your Skill Boost masterclass organised by the Excellence Foundation for South Sudan (EFSS) on Saturday, the 25th and Sunday, the 26th of May 2024.
He discussed the concept of quality improvement, emphasizing its applicability to various aspects of life, including personal, project, and program improvements. He defined quality as doing the right thing at the right time in the right way to achieve the best possible results and discussed the concept of the "gap" between what we know and what we do, and how this gap represents the areas we need to improve. He explained the scientific approach to quality improvement, which involves systematic performance analysis, testing and learning, and implementing change ideas. He also highlighted the importance of client focus and a team approach to quality improvement.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
1. S3 INFOTECH +919884848198
# 10/1, Jones Road, Saidapet, Chennai – 15. Ph: 044-3201 7467, 9884848198.
www.s3computers.com E-Mail: info@s3computers.com
MATLAB
2. S3 INFOTECH +919884848198
# 10/1, Jones Road, Saidapet, Chennai – 15. Ph: 044-3201 7467, 9884848198.
www.s3computers.com E-Mail: info@s3computers.com
DIGITAL IMAGE PROCESSING:
PROJECT
CODES
NAME OF THE PROJECTS YEAR
EPMTI-001
EPMTI-002
EPMTI-003
EPMTI-004
EPMTI-005
EPMTI-006
EPMTI-007
EPMTI-008
EPMTI-009
EPMTI-010
EPMTI-011
EPMTI-012
EPMTI-013
EPMTI-014
EPMTI-015
EPMTI-016
Action Recognition Using Nonnegative Action Component Representation and
Sparse Basis Selection
Building Change Detection Based on Satellite Stereo Imagery and Digital
Surface Models
Compressing Encrypted Images with Auxiliary Information
Design and Implementation of an MSI number based Image Watermarking
Architecture in Transform Domain
Discrete Anamorphic Transform for Image Compression
Digital Watermarking in Video for Copy Right Protection
Effect of Image Down sampling on Steganographic Security
Efficient adaptive fuzzy-based switching weighted average filter for the
restoration of impulse corrupted digital images.
Effective Estimation of Image Rotation Angle Using Spectral Method
Frame Rate Up-Conversion Method Based on Texture Adaptive Bilateral
Motion Estimation
Fingerprint Compression Based on Sparse Representation
Face recognition and facial expression identification using PCA.
Impact of Wavelet Transform and Median Filtering on Removal of Salt and
Pepper Noise in Digital Images
Mitigation of Azimuth Ambiguities in Spaceborne Stripmap SAR Images Using
Selective Restoration
Novel Restoration process for Degraded Image (Development of GUI for
Restoration of Degraded image by different Filters)
Performances of the estimation and motion compensation for the reconstruction
of motion areas in a sequence video Motion JPEG 2000
IEEE 2014
IEEE 2014
IEEE 2014
IEEE 2014
IEEE 2014
IEEE 2014
IEEE 2014
IEEE 2014
IEEE 2014
IEEE 2014
IEEE 2014
IEEE 2014
IEEE 2014
IEEE 2014
IEEE 2014
IEEE 2014
3. S3 INFOTECH +919884848198
# 10/1, Jones Road, Saidapet, Chennai – 15. Ph: 044-3201 7467, 9884848198.
www.s3computers.com E-Mail: info@s3computers.com
EPMTI-017
EPMTI-018
EPMTI-019
EPMTI-020
EPMTI-021
EPMTI-022
EPMTI-023
EPMTI-024
EPMTI-025
EPMTI-026
EPMTI-027
EPMTI-028
EPMTI-029
EPMTI-030
EPMTI-031
EPMTI-032
EPMTI-033
Post Processing Algorithm for reduction of Blocking Artifact in HDTV
Real-Time Spatially Adaptive Image Restoration Using Truncated Constrained
Least Squares Filter
Reduction of Signal-Dependent Noise From Hyperspectral Images for Target
Detection
Region-based Moving Object Detection Using Spatially Conditioned
Nonparametric Models in a GPU.
Revealing the Traces of Median Filtering Using High-Order Local Ternary
Patterns
Robust Digital Image Reconstruction via the Discrete Fourier Slice Theorem
Robust Text Detection in Natural Scene Images
Saliency-Aware Video Compression
Separation of Weak Reflection from a Single Superimposed Image
Shape Based Copy Move Forgery Detection Using Level Set Approach
Structured Time Series Analysis for Human Action Segmentation and
Recognition
Tolerance Evaluation for Defocused Images to Optical Watermarking Technique
Two-layer motion estimation algorithm for video coding
Video Watermarking by Adjusting the Pixel Values and Using Scene Change
Detection
Facial expression recognition using thermal image processing and neural
network.
Novel True-Motion Estimation Algorithm and Its Application to Motion
Compensated Temporal Frame Interpolation.
Motion Analysis Using 3D High-Resolution Frequency Analysis.
IEEE 2014
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4. S3 INFOTECH +919884848198
# 10/1, Jones Road, Saidapet, Chennai – 15. Ph: 044-3201 7467, 9884848198.
www.s3computers.com E-Mail: info@s3computers.com
EPMTI-034
EPMTI-035
EPMTI-036
EPMTI-037
EPMTI-038
EPMTI-039
EPMTI-040
EPMTI-041
EPMTI-042
EPMTI-043
EPMTI-044
EPMTI-045
EPMTI-046
EPMTI-047
EPMTI-048
EPMTI-049
EPMTI-050
EPMTI-051
EPMTI-052
Visual Tracking with Spatio-Temporal Dempster–Shafer Information Fusion.
Multiple-Kernel, Multiple-Instance Similarity Features for Efficient Visual
Object Detection.
Texture Enhanced Histogram Equalization Using TV- Image Decomposition.
Corner Detection and Classification Using Anisotropic Directional Derivative
Representations.
Robust Face Representation Using Hybrid Spatial Feature Interdependence
Matrix.
Depth Estimation of Face Images Using the Nonlinear Least-Squares Model
Local Linear SURE-Based Edge-Preserving Image Filtering
Visually Lossless Encoding for JPEG2000
Wavelet Domain Multifractal Analysis for Static and Dynamic Texture
Classification
Video Object Tracking in the Compressed Domain Using Spatio-Temporal
Markov Random Fields
Action Search by Example Using Randomized Visual Vocabularies
Image Noise Level Estimation by Principal Component Analysis
Nonlocal Image Restoration With Bilateral Variance Estimation
Adaptive Inpainting Algorithm Based on DCT Induced Wavelet Regularization.
Automatic License Plate Recognition
Fast Positive Deconvolution of Hyperspectral Images
Robust Image Analysis With Sparse Representation
Image Enhancement Using the Hypothesis Selection Filter
Simultaneous Facial Feature Tracking and Facial Expression Recognition
IEEE 2013
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IEEE 2013
5. S3 INFOTECH +919884848198
# 10/1, Jones Road, Saidapet, Chennai – 15. Ph: 044-3201 7467, 9884848198.
www.s3computers.com E-Mail: info@s3computers.com
EPMTI-053
EPMTI-054
EPMTI-055
EPMTI-056
EPMTI-057
EPMTI-058
EPMTI-059
EPMTI-060
EPMTI-061
EPMTI-062
EPMTI-063
EPMTI-064
EPMTI-065
EPMTI-066
EPMTI-067
EPMTI-068
EPMTI-069
EPMTI-070
Exploring Visual and Motion Saliency for Automatic Video Object Extraction
Enhanced Compressed Sensing Recovery With Level Set Normals
Image Sharpness Assessment Based on Local Phase Coherence
Scene Text Detection via Connected Component Clustering and Nontext
Filtering
Object ranging and tracking for aircraft landing system
Image Fusion With Guided Filtering
An Efficient Character Recognition Scheme Based on K-Means Clustering
Hybrid GMDH Model for and written Character Recognition
A Vision-Based Obstacle Detection System for Parking Assistance.
Efficient Image Compression Based on Seam Carving for Arbitrary Resolution
Display Devices
Image Compression Using Lifting Based Wavelet Transform Coupled With
SPIHT Algorithm.
A Segmentation and Graph-Based Video Sequence Matching Method for Video
Copy Detection.
Automatic Tuning of Spatially Varying Transfer Functions for Blood Vessel
Visualization
A Novel Reversible Data Hiding Scheme Based on Two-Dimensional
Difference-Histogram Modification.
Fast Restoration of Natural Images Corrupted by High-Density Impulse Noise
Histology Image Retrieval in Optimized Multifeature Spaces.
Techniques for Compensating Memory Errors in JPEG2000.
Optical flow estimation used for flame detection in videos
IEEE 2013
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6. S3 INFOTECH +919884848198
# 10/1, Jones Road, Saidapet, Chennai – 15. Ph: 044-3201 7467, 9884848198.
www.s3computers.com E-Mail: info@s3computers.com
MEDICAL IMAGE PROCESSING SYSTEMS:
PROJECT
CODES
NAME OF THE PROJECTS YEAR
EPMTM-001
EPMTM-002
EPMTM-003
EPMTM-004
EPMTM-005
EPMTM-006
EPMTM-007
EPMTM-008
EPMTM-009
EPMTM-010
EPMTM-011
EPMTM-012
EPMTM-013
Integration of Network Topological and Connectivity Properties for
Neuroimaging Classification
Detection of Life-Threatening Arrhythmias Using Feature Selection and
Support Vector Machines
Gradient-Based Reliability Maps for ACM-Based Segmentation of
Hippocampus
Organic Biophotonic Nanoparticles: Porphysomes and Beyond
An Ultrasound System for Tumor Detection in Soft Tissues Using Low
Transient Pulse
A Statistical Modeling Approach to Computer-Aided Quantification of Dental
Biofilm.
A Quality-Scalable and Energy-Efficient Approach for Spectral Analysis of
Heart Rate Variability
Random Forests Based Sub-Vocal Electromyogram Signal Acquisition and
Classification for Rehabilitative Applications
High-Fidelity Data Transmission of Multi Vital Signs for Distributed e-Health
Applications
An Automatic Graph-Based Approach for Artery/Vein Classification in Retinal
Images
Segmentation of Skin Lesions From Digital Images Using Joint Statistical
Texture Distinctiveness
Constrained TpV Minimization for Enhanced Exploitation of Gradient
Sparsity: Application to CT Image Reconstruction
Segmentation of Blood Vessels and Optic Disc in Retinal Images
IEEE 2014
IEEE 2014
IEEE 2014
IEEE 2014
IEEE 2014
IEEE 2014
IEEE 2014
IEEE 2014
IEEE 2014
IEEE 2014
IEEE 2014
IEEE 2014
IEEE 2014
7. S3 INFOTECH +919884848198
# 10/1, Jones Road, Saidapet, Chennai – 15. Ph: 044-3201 7467, 9884848198.
www.s3computers.com E-Mail: info@s3computers.com
EPMTM-014
EPMTM-015
EPMTM-016
EPMTM-017
EPMTM-018
EPMTM-019
EPMTM-020
EPMTM-021
EPMTM-022
EPMTM-023
EPMTM-024
EPMTM-025
EPMTM-026
EPMTM-027
EPMTM-028
EPMTM-029
EPMTM-030
EPMTM-031
EPMTM-032
A Multi-staged Automatic Restoration of Noisy Microscopy Cell Images
Automatic Diagnosis of Breast Abnormality using Digital IR Camera
Blood Vessel Extraction For Retinal Images Using Morphological Operator and
KCN Clustering
Performance Analysis Of Region Of Interest Based Compression Method For
Medical Images
Exploiting Prior Knowledge in Compressed Sensing Wireless ECG Systems
Performance Evaluation of the Spread Spectrum Human Body Communication
Devices
Modern Methods for the Description of Complex Couplings in the
Neurophysiology of Respiration
Breast Cancer Detection Using Mammograms
Automatic Cough Detection
ECG Data Analysis To Diagnosis Cardio Vascular Disease
Human Daily Activity Recognition With Sparse Representation
De noising MRI Using Spectral Subtraction
Facial Tissue Tracking in Thermal Imaging
Tumor Targeting Enhancement
Automatic Segmentation of Antenatal Ultrasound Images.
Latent fingerprint matching using descriptor-based Hough transform
An automated drusen detection system for classifying age-related macular
degeneration with color fundus photographs
Blood cell counting system
Automatic Tuning of Spatially Varying Transfer Functions for Blood Vessel
Visualization
IEEE 2014
IEEE 2014
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IEEE 2013
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IEEE 2013
8. S3 INFOTECH +919884848198
# 10/1, Jones Road, Saidapet, Chennai – 15. Ph: 044-3201 7467, 9884848198.
www.s3computers.com E-Mail: info@s3computers.com
SPEECH AND AUDIO PROCESSING:
PROJECT
CODES
NAME OF THE PROJECTS YEAR
EPMTS-001
EPMTS-002
EPMTS-003
EPMTS-004
EPMTS-005
EPMTS-006
EPMTS-007
EPMTS-008
EPMTS-009
EPMTS-010
EPMTS-011
EPMTS-012
Analysis By Synthesis Spatial Audio Coding
A Family Of Discriminative Manifold Learning Algorithms And Their
Application To Speech Recognition
A Simple Ladder Realization Of Maximally Flat Allpass Fractional Delay
Filters
A Fuzzy Mask Based On Wavelet Packet For Improving Speech Quality And
Intelligibility
A Novel Technique For Data Hiding In Audio Carrier By Using Sample
Comparison In DWT Domain
A Synthesis Model With Intuitive Control Capabilities For Rolling Sounds
A Framework For The Calculation Of Dynamic Crosstalk Cancellation Filters
An Approach To Building Language-Independent Text-To-Speech Synthesis
For English Language
Robust Audio-Visual Speech Recognition Under Noisy Audio-Video
Conditions
Turbo Processing For Speech Recognition
Joint Audiovisual Hidden Semi-Markov Model-Based Speech Synthesis
Cross-Lingual Subspace Gaussian Mixture Models For Low-Resource Speech
Recognition.
IEEE 2014
IEEE 2014
IEEE 2014
IEEE 2014
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IEEE 2014
IEEE 2014
IEEE 2014
IEEE 2014
IEEE 2014
IEEE 2014
IEEE 2014
9. S3 INFOTECH +919884848198
# 10/1, Jones Road, Saidapet, Chennai – 15. Ph: 044-3201 7467, 9884848198.
www.s3computers.com E-Mail: info@s3computers.com
EPMTS-013
EPMTS-014
EPMTS-015
EPMTS-016
EPMTS-017
EPMTS-018
EPMTS-019
EPMTS-020
EPMTS-021
EPMTS-022
EPMTS-023
EPMTS-024
EPMTS-025
EPMTS-026
EPMTS-027
Statistical Analysis Of A Jointly Optimized Beamformer-Assisted Acoustic
Echo Canceller
Maximum Likelihood Acoustic Factor Analysis Models For Robust Speaker
Verification In Noise
Sparse Array-Based Room Transfer Function Estimation For Echo Cancellation
Maximum Phase Modeling For Sparse Linear Prediction Of Speech
Cascaded Long Term Prediction For Enhanced Compression Of Polyphonic
Audio Signals
Time-Frequency Transform-Based Differential Scheme For Microgrid
Protection
Wearable Audio Monitoring: Content-Based Processing Methodology And
Implementation
Hierarchical Covering Algorithm
Investigation Of Speech Separation As A Front-End For Noise Robust Speech
Recognition
Cepstrum-Based Bandwidth Extension For Super-Wideband Coders
Noise-Robust Classification Of Ground Moving Targets Based On Time-
Frequency Feature From Micro-Doppler Signature
Complexity Reduction In Karhunen-Loève Transform Based Speech Coder For
Voice Transmission
Discrete Fractional Fourier Transform And Vector Quantization Based Speaker
Identification System
Memory Proportionate APA With Individual Activation Factors For Acoustic
Echo Cancellation
Pitch Estimation For Musical Note Recognition Using Artificial Neural
Networks
IEEE 2014
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IEEE 2014
10. S3 INFOTECH +919884848198
# 10/1, Jones Road, Saidapet, Chennai – 15. Ph: 044-3201 7467, 9884848198.
www.s3computers.com E-Mail: info@s3computers.com
EPMTS-028
EPMTS-029
EPMTS-030
EPMTS-031
EPMTS-032
EPMTS-033
EPMTS-034
EPMTS-035
EPMTS-036
EPMTS-037
EPMTS-038
EPMTS-039
EPMTS-040
EPMTS-041
EPMTS-042
EPMTS-043
EPMTS-044
Estimation Of Allpass Transfer Functions By Introducing Sparsity Constraints
To Particle Swarm Optimization
Better Phone Alignment For Confidence Measures In Voice Based Querying
Epochs Based Compression Of LP Residual For Source Modeling In Text-To-
Speech Synthesis
Combination Of Cepstral And Phonetically Discriminative Features For
Speaker Verification
Predicting Continuous Conflict Perception With Bayesian Gaussian Processes
Coherence Analysis Of EEG Signal Using Power Spectral Density
Cloud-Based Framework For Mobile Learning Content Adaptation
A Variable Step-Size-Based ICA Method For A Fast And Robust Acoustic
Echo Cancellation System Without Requiring Double-Talk Detector
Audio Lossless Coding/Decoding Method Using Basis Pursuit Algorithm
Real-Time Covert VOIP Communications Over Smart Grids By Using AES-
Based Audio Steganography
Time-Frequency Multiplier Estimation system
Kalman Filter for Echo Cancellation
Joint Discriminative Decoding of Words and Semantic Tags for Spoken
Language Understanding
Speaker Verification
Bayesian Feature Enhancement for Reverberation and Noise Robust Speech
Recognition
Spoken Term Detection
Acoustic Emotion Recognition
IEEE 2014
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11. S3 INFOTECH +919884848198
# 10/1, Jones Road, Saidapet, Chennai – 15. Ph: 044-3201 7467, 9884848198.
www.s3computers.com E-Mail: info@s3computers.com
EPMTS-045
EPMTS-046
EPMTS-047
EPMTS-048
EPMTS-049
EPMTS-050
EPMTS-051
EPMTS-052
EPMTS-053
Microphone Noise Reduction Based on Orthogonal Noise Signal
Decompositions
Voice Activity Detection in Presence of Transient Noise Using Spectral
Clustering
Nonlinear Least Squares Methods for Pitch Estimation
A Two-Stage Beamforming Approach for Noise Reduction and
Dereverberation
Automatic Adaptation of the Time-Frequency Resolution for Sound Analysis
Speaker Identification System Using HMM And Mel Frequency Cepstral
coefficient
Informed Audio Source Separation Using Linearly Constrained Spatial Filters
Robust Speaker Diarization Using Privacy-Preserving Audio Representations
A reversible data embedding scheme for MPEG-4video using HVS
characteristics
IEEE 2013
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IEEE 2013
IEEE 2013
12. S3 INFOTECH +919884848198
# 10/1, Jones Road, Saidapet, Chennai – 15. Ph: 044-3201 7467, 9884848198.
www.s3computers.com E-Mail: info@s3computers.com
WIRELESS AND COMMUNICATION SYSTEMS:
PROJECT
CODES
NAME OF THE PROJECTS YEAR
EPMTC-001
EPMTC-002
EPMTC-003
EPMTC-004
EPMTC-005
EPMTC-006
EPMTC-007
EPMTC-008
EPMTC-009
EPMTC-010
EPMTC-011
EPMTC-012
Adaptive Gradient-Based Methods for Adaptive Power Allocation in OFDM-
Based Cognitive Radio Networks
An Adaptively Weighted Least Square Estimation Method of Channel
Mismatches in Phase for Multichannel SAR Systems in Azimuth
Accuracy of Harmonic Mean Approximation in Performance Analysis of
Multihop Amplify-and-Forward Relaying
A Frequency-Selective I/Q Imbalance Analysis Technique
Assessment of Energy Detection Spectrum Sensing Under Different Wireless
Channels
Adaptive Threshold Blanker in an Impulsive Noise Environment
A Low-Complexity Robust OFDM Receiver for Fast Fading Channels
A Factor Graph Approach to Joint OFDM Channel Estimation and Decoding in
Impulsive Noise Environments
A Hybrid PAPR Reduction Scheme for OFDM Using SLM with Clipping at
the Transmitter, and Sparse Reconstruction at the Receiver
Compressive Sensing Based Channel Estimation for OFDM Systems Under
Long Delay Channels
Closed-Loop Beam Alignment for Massive MIMO Channel Estimation
Digital Phase Noise Cancellation for a Coherent-Detection Microwave
Photonic Link
IEEE 2014
IEEE 2014
IEEE 2014
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IEEE 2014
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IEEE 2014
IEEE 2014
IEEE 2014
IEEE 2014
13. S3 INFOTECH +919884848198
# 10/1, Jones Road, Saidapet, Chennai – 15. Ph: 044-3201 7467, 9884848198.
www.s3computers.com E-Mail: info@s3computers.com
EPMTC-013
EPMTC-014
EPMTC-015
EPMTC-016
EPMTC-017
EPMTC-018
EPMTC-019
EPMTC-020
EPMTC-021
EPMTC-022
EPMTC-023
EPMTC-024
EPMTC-025
EPMTC-026
EPMTC-027
EPMTC-028
Efficient Parallel Turbo-Decoding for High-Throughput Wireless Systems
Fourier-Based Transmit Beampattern Design Using MIMO Radar
Green optical orthogonal frequency-division multiplexing networks
High-Rate Hidden Communications Channel: A Multidimensional Signaling
Approach
Improved FFT-Based Frequency Offset Estimation Algorithm for Coherent
Optical Systems
Linear Phase VDF Design with Unabridged Bandwidth Control over the
Nyquist Band
Link Adaptation in Closed-Loop Coded MIMO Systems with LMMSE-IC
based Turbo Receivers
Low-complexity data decoding using binary phase detection in SLM-OFDM
systems
Mapping Optimization for a MAP Turbo Detector Over a Frequency-Selective
Channel
Matrix Approximation Based Design of a Combined Analog and Digital
Beamformer in Frequency-Selective Fading Channels
MIMO-Radar Waveform Covariance Matrix for High SINR and Low Side-
Lobe Levels
Noise Interpolation for Unique Word OFDM
PAPR Analysis and Mitigation Algorithms for Beamforming MIMO OFDM
Systems
Performance Evaluation of the Spread Spectrum Human Body Communication
Devices
Pilot-Assisted PAPR Reduction Technique for Optical OFDM Communication
Systems
PAPR-Constrained Pareto-Optimal Waveform Design for OFDM-STAP Radar
IEEE 2014
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IEEE 2014
14. S3 INFOTECH +919884848198
# 10/1, Jones Road, Saidapet, Chennai – 15. Ph: 044-3201 7467, 9884848198.
www.s3computers.com E-Mail: info@s3computers.com
EPMTC-029
EPMTC-030
EPMTC-031
EPMTC-032
EPMTC-033
EPMTC-034
EPMTC-035
EPMTC-036
EPMTC-037
EPMTC-038
EPMTC-039
EPMTC-040
EPMTC-041
EPMTC-042
EPMTC-043
EPMTC-044
EPMTC-045
EPMTC-046
Quasi-Pilot Aided Phase Noise Estimation for Coherent Optical OFDM
Systems
Retransmission Delays With Bounded Packets: Power-Law Body and
Exponential Tail
SLNC for Multi-Source Multi-Relay BICM-OFDM Systems
Scalable Synchronization and Reciprocity Calibration for Distributed Multiuser
MIMO
The Jamming Capacity of the Fading Multiple Access Channel
Unequal Error Correcting Capability Aware Iterative Receiver for (Parallel)
Turbo Coded Communications
W-Band Large-Scale High-Gain Planar Integrated Antenna Array
Robust Performance of Spectrum Sensing in Cognitive Radio Networks
Energy-Efficient Uplink Multi-User MIMO
Performance Analysis of OFDM Systems with Selected Mapping in the
Presence of Nonlinearity
Compressive Sensing for Spread Spectrum Receivers
Multi-Channel Allocation in Distributed OFDMA-Based Networks
Turbo Receiver with ICI-Aware Dual-List Detection for Mobile MIMO-OFDM
Systems
Energy Efficiency Optimization for MIMO Broadcast Channels
Efficient Margin Adaptive Scheduling for MIMO-OFDMA Systems
On Frequency Offset Estimation for OFDM system.
Performance Analysis of Packet Aggregation for IEEE 802.11
Spectrum Sensing for Digital Primary Signals in Cognitive Radio
IEEE 2014
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IEEE 2013
IEEE 2013
15. S3 INFOTECH +919884848198
# 10/1, Jones Road, Saidapet, Chennai – 15. Ph: 044-3201 7467, 9884848198.
www.s3computers.com E-Mail: info@s3computers.com
EPMTC-047
EPMTC-048
EPMTC-049
EPMTC-050
EPMTC-051
EPMTC-052
EPMTC-053
EPMTC-054
EPMTC-055
EPMTC-056
EPMTC-057
EPMTC-058
EPMTC-059
EPMTC-060
EPMTC-061
EPMTC-062
Space Time Coded Systems For Wireless Communications
Performance Analysis Of Multi Carrier DS-CDMA Communication System
A combination of CS-CDMA and OFDM for enhanced LTE on downlink
Spectrum management models for cognitive radios
Subcarrier Allocation for Uplink-OFDMA under Time-Varying Channels
Min-Sum Decoding Algorithm for Non-Binary LDPC Codes
An Adaptive Receiver Design for OFDM Systems Using Conjugate
Transmission
Carrier Sense Multiple Access Communications on Multipacket Reception
Channels
Signal Uncertainty in Spectrum Sensing for Cognitive Radio
Intensity modualtion full field detection optical fast OFDM.
Digital baseband transmitter modelling and analysis with high performance
reconfigurable spectrally efficient FDM.
Adaptive wireless channel probing for shared key generation based in PID
controller.
Channel switching cost aware and energy efficient cooperative sensing
scheduling for cognitive radio networks.
A Method to Defense against Cooperative SSDF Attacks in Cognitive Radio
Networks.
Interference management in cognitive radio systems with feasibility detection.
Phased-MIMO Radar With Frequency Diversity for Range-Dependent
Beamforming.
IEEE 2013
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IEEE 2013
16. S3 INFOTECH +919884848198
# 10/1, Jones Road, Saidapet, Chennai – 15. Ph: 044-3201 7467, 9884848198.
www.s3computers.com E-Mail: info@s3computers.com
NETWORKING:
PROJECT
CODES
NAME OF THE PROJECTS YEAR
EPMTN-001
EPMTN-002
EPMTN-003
EPMTN-004
EPMTN-005
EPMTN-006
EPMTN-007
EPMTN-008
EPMTN-009
EPMTN-010
EPMTN-011
EPMTN-012
EPMTN-013
EPMTN-014
Unveiling the Hidden Assumptions of Energy Detector Based Spectrum
Sensing for Cognitive Radios
Degenerate Mode-Group Division Multiplexing using MIMO Digital Signal
Processing
Reliable Spectrum Sensing and Opportunistic Access in Network-Coded
Communications
A Cooperative Matching Approach for Resource Management in Dynamic
Spectrum Access Networks
Non-linear space–time Kalman filter for cooperative spectrum sensing in
cognitive radios
Optimal Transmit Precoding for Distributed Estimation in Correlated WSN
On Optimal Downlink Coverage in Poisson Cellular Networks with Power
Density Constraints
Wavelet Based Signal Processing Technique for Classification of Power
Quality Disturbances
Energy-Aware Cooperation Strategy with Uncoordinated Group Relays for
Delay-Sensitive Services
An improved leach protocol for indoor wireless sensor networks
Energy Efficient Routing Protocol for Wireless Sensor Network
Cooperative handover algorithm based on auxiliary carrier in LTE-Advanced
relay system
Cross-Layer Resource Allocation for Video Streaming over OFDMA Cognitive
Radio Networks with Imperfect Cross-Link CSI
A New Approach to Coding In Content-Based MANETs
IEEE 2014
IEEE 2014
IEEE 2014
IEEE 2014
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IEEE 2014
IEEE 2014
IEEE 2014
IEEE 2014
IEEE 2014
17. S3 INFOTECH +919884848198
# 10/1, Jones Road, Saidapet, Chennai – 15. Ph: 044-3201 7467, 9884848198.
www.s3computers.com E-Mail: info@s3computers.com
EPMTN-015
EPMTN-016
EPMTN-017
EPMTN-018
EPMTN-019
EPMTN-020
EPMTN-021
EPMTN-022
EPMTN-023
EPMTN-024
EPMTN-025
EPMTN-026
EPMTN-027
EPMTN-028
EPMTN-029
Joint Network Channel Fountain Scheme for Reliable Communication in
Wireless Networks
A Globally Optimal Neyman-Pearson Test for Hard Decisions Fusion in
Cooperative Spectrum Sensing
Energy-aware Dynamic Cooperative Strategy Selection for Relay-assisted
Cellular Networks: An Evolutionary Game Approach
Inter-Relay Cooperation: A New Paradigm for Enhanced Relay-Assisted FSO
Communications
Transmission Strategy Design in Cognitive Radio Systems with Primary ARQ
Control and QoS Provisioning
Retroactive Antijamming for MISO Broadcast Channels
Channel Time Allocations and Handoff Management for Fair Throughput in
Wireless Mesh Networks
Load-aware Routing for Non-Persistent Small-World Wireless Mesh Networks
A Secure and Energy-Efficient Stochastic Routing Protocol for Wireless
Mobile Ad-hoc Networks
Adaptive Transmission-Reception-Sensing Strategy for Cognitive Radios with
Full-duplex Capabilities
Predicting Software Reliability Using Ant Colony Optimization Technique
Recent Advances in Radio Resource Management for Heterogeneous LTE/
LTE-A Networks.
A local-world evolving hypernetwork model
Cross-Layer Design of Congestion Control and Power Control in Fast-Fading
Wireless Networks
Hierarchical Competition for Downlink Power Allocation in OFDMA
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ELSEVIER
2014
IEEE 2013
IEEE 2013
18. S3 INFOTECH +919884848198
# 10/1, Jones Road, Saidapet, Chennai – 15. Ph: 044-3201 7467, 9884848198.
www.s3computers.com E-Mail: info@s3computers.com
EPMTN-030
EPMTN-031
EPMTN-032
EPMTN-033
EPMTN-034
EPMTN-035
Femtocell Networks
Distributed Beamforming with Imperfect Phase Synchronization for Cognitive
Radio Networks
Efficient PMU Networking with Software Defined Networks
Detecting False Data Injection in Smart Grid In-Network Aggregation
MAC Contention Distributions for Efficient Geo-routing in Vehicular
Networks.
Load Balancing Based on Clustering Methods for LTE Networks.
Energy efficient Routing protocol implementation in wireless sensor networks
using CAMP & HEED
IEEE 2013
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