IEEE Final Year Projects for M.E/M.TECH-CSE,VLSI,COMMUNICATION SYSTEM,B.E-CSE/IT from any domain & Technologies.For more detail contact:-DreamWeb TechnoSolutions@7200021403/04, 73/5 3rd floor,Kamatchi cmplx,SALAI ROADThillai nagar 1st cross,Trichy
We are offering PROJECTS in EMBEDDED, MATLAB, NS2, VLSI, Power Electronics,Power Systems for BE- ECE & EEE Students.
Own Concepts also accepted.providing real time projects on MATLAB,EMB&VLSI for ECE Dept DreamwebTechnosolutions
73/5,3rd FLOOR,SRI KAMATCHI COMPLEX
OPP.CITY HOSPITAL (NEAR LAKSHMI COMPLEX)
SALAI ROAD,Trichy - 620 018,
Ph: 0431 4050403,7200021403/04.
We are offering PROJECTS in EMBEDDED, MATLAB, NS2, VLSI, Power Electronics,Power Systems for BE- ECE & EEE Students.
Own Concepts also accepted.providing real time projects on MATLAB,EMB&VLSI for ECE Dept DreamwebTechnosolutions
73/5,3rd FLOOR,SRI KAMATCHI COMPLEX
OPP.CITY HOSPITAL (NEAR LAKSHMI COMPLEX)
SALAI ROAD,Trichy - 620 018,
Ph: 0431 4050403,7200021403/04.
We are offering PROJECTS in EMBEDDED, MATLAB, NS2, VLSI, Power Electronics,Power Systems for BE- ECE & EEE Students.
Own Concepts also accepted.providing real time projects on MATLAB,EMB&VLSI for ECE Dept DreamwebTechnosolutions
73/5,3rd FLOOR,SRI KAMATCHI COMPLEX
OPP.CITY HOSPITAL (NEAR LAKSHMI COMPLEX)
SALAI ROAD,Trichy - 620 018,
Ph: 0431 4050403,7200021403/04.
We are offering PROJECTS in EMBEDDED, MATLAB, NS2, VLSI, Power Electronics,Power Systems for BE- ECE & EEE Students.
Own Concepts also accepted.providing real time projects on MATLAB,EMB&VLSI for ECE Dept DreamwebTechnosolutions
73/5,3rd FLOOR,SRI KAMATCHI COMPLEX
OPP.CITY HOSPITAL (NEAR LAKSHMI COMPLEX)
SALAI ROAD,Trichy - 620 018,
Ph: 0431 4050403,7200021403/04.
IEEE Final Year Projects for M.E/M.TECH-CSE,VLSI,COMMUNICATION SYSTEM,B.E-CSE/IT from any domain & Technologies.For more detail contact:-DreamWeb TechnoSolutions@7200021403/04, 73/5 3rd floor,Kamatchi cmplx,SALAI ROADThillai nagar 1st cross,Trichy
We are offering PROJECTS in EMBEDDED, MATLAB, NS2, VLSI, Power Electronics,Power Systems for BE- ECE & EEE Students.
Own Concepts also accepted.providing real time projects on MATLAB,EMB&VLSI for ECE Dept DreamwebTechnosolutions
73/5,3rd FLOOR,SRI KAMATCHI COMPLEX
OPP.CITY HOSPITAL (NEAR LAKSHMI COMPLEX)
SALAI ROAD,Trichy - 620 018,
Ph: 0431 4050403,7200021403/04.
IEEE Final Year Projects for M.E/M.TECH-CSE,VLSI,COMMUNICATION SYSTEM,B.E-CSE/IT from any domain & Technologies.For more detail contact:-DreamWeb TechnoSolutions@7200021403/04, 73/5 3rd floor,Kamatchi cmplx,SALAI ROADThillai nagar 1st cross,Trichy
IEEE Final Year Projects for M.E/M.TECH-CSE,VLSI,COMMUNICATION SYSTEM,B.E-CSE/IT from any domain & Technologies.For more detail contact:-DreamWeb TechnoSolutions@7200021403/04, 73/5 3rd floor,Kamatchi cmplx,SALAI ROADThillai nagar 1st cross,Trichy
We are offering PROJECTS in EMBEDDED, MATLAB, NS2, VLSI, Power Electronics,Power Systems for BE- ECE & EEE Students.
Own Concepts also accepted.providing real time projects on MATLAB,EMB&VLSI for ECE Dept DreamwebTechnosolutions
73/5,3rd FLOOR,SRI KAMATCHI COMPLEX
OPP.CITY HOSPITAL (NEAR LAKSHMI COMPLEX)
SALAI ROAD,Trichy - 620 018,
Ph: 0431 4050403,7200021403/04.
We are offering PROJECTS in EMBEDDED, MATLAB, NS2, VLSI, Power Electronics,Power Systems for BE- ECE & EEE Students.
Own Concepts also accepted.providing real time projects on MATLAB,EMB&VLSI for ECE Dept DreamwebTechnosolutions
73/5,3rd FLOOR,SRI KAMATCHI COMPLEX
OPP.CITY HOSPITAL (NEAR LAKSHMI COMPLEX)
SALAI ROAD,Trichy - 620 018,
Ph: 0431 4050403,7200021403/04.
We are offering PROJECTS in EMBEDDED, MATLAB, NS2, VLSI, Power Electronics,Power Systems for BE- ECE & EEE Students.
Own Concepts also accepted.providing real time projects on MATLAB,EMB&VLSI for ECE Dept DreamwebTechnosolutions
73/5,3rd FLOOR,SRI KAMATCHI COMPLEX
OPP.CITY HOSPITAL (NEAR LAKSHMI COMPLEX)
SALAI ROAD,Trichy - 620 018,
Ph: 0431 4050403,7200021403/04.
We are offering PROJECTS in EMBEDDED, MATLAB, NS2, VLSI, Power Electronics,Power Systems for BE- ECE & EEE Students.
Own Concepts also accepted.providing real time projects on MATLAB,EMB&VLSI for ECE Dept DreamwebTechnosolutions
73/5,3rd FLOOR,SRI KAMATCHI COMPLEX
OPP.CITY HOSPITAL (NEAR LAKSHMI COMPLEX)
SALAI ROAD,Trichy - 620 018,
Ph: 0431 4050403,7200021403/04.
IEEE Final Year Projects for M.E/M.TECH-CSE,VLSI,COMMUNICATION SYSTEM,B.E-CSE/IT from any domain & Technologies.For more detail contact:-DreamWeb TechnoSolutions@7200021403/04, 73/5 3rd floor,Kamatchi cmplx,SALAI ROADThillai nagar 1st cross,Trichy
We are offering PROJECTS in EMBEDDED, MATLAB, NS2, VLSI, Power Electronics,Power Systems for BE- ECE & EEE Students.
Own Concepts also accepted.providing real time projects on MATLAB,EMB&VLSI for ECE Dept DreamwebTechnosolutions
73/5,3rd FLOOR,SRI KAMATCHI COMPLEX
OPP.CITY HOSPITAL (NEAR LAKSHMI COMPLEX)
SALAI ROAD,Trichy - 620 018,
Ph: 0431 4050403,7200021403/04.
IEEE Final Year Projects for M.E/M.TECH-CSE,VLSI,COMMUNICATION SYSTEM,B.E-CSE/IT from any domain & Technologies.For more detail contact:-DreamWeb TechnoSolutions@7200021403/04, 73/5 3rd floor,Kamatchi cmplx,SALAI ROADThillai nagar 1st cross,Trichy
IEEE Final Year Projects for M.E/M.TECH-CSE,VLSI,COMMUNICATION SYSTEM,B.E-CSE/IT from any domain & Technologies.For more detail contact:-DreamWeb TechnoSolutions@7200021403/04, 73/5 3rd floor,Kamatchi cmplx,SALAI ROADThillai nagar 1st cross,Trichy
This document contains contact information for DreamwebTechnosolutions in Trichy, India and lists several mobile computing, data mining, cloud computing, big data, and network security research project titles and their years. It provides titles and years for 11 mobile computing projects, 11 data mining projects, 13 cloud computing projects, 6 big data projects, and 5 network security projects conducted between 2016-2017. The contact listed is K.RanjithKumar who can be reached by phone.
We are offering PROJECTS in EMBEDDED, MATLAB, NS2, VLSI, Power Electronics,Power Systems for BE- ECE & EEE Students.
Own Concepts also accepted.providing real time projects on MATLAB,EMB&VLSI for ECE Dept DreamwebTechnosolutions
73/5,3rd FLOOR,SRI KAMATCHI COMPLEX
OPP.CITY HOSPITAL (NEAR LAKSHMI COMPLEX)
SALAI ROAD,Trichy - 620 018,
Ph: 0431 4050403,7200021403/04.
IEEE Final Year Projects for M.E/M.TECH-CSE,VLSI,COMMUNICATION SYSTEM,B.E-CSE/IT from any domain & Technologies.For more detail contact:-DreamWeb TechnoSolutions@7200021403/04, 73/5 3rd floor,Kamatchi cmplx,SALAI ROADThillai nagar 1st cross,Trichy
We are offering PROJECTS in EMBEDDED, MATLAB, NS2, VLSI, Power Electronics,Power Systems for BE- ECE & EEE Students.
Own Concepts also accepted.providing real time projects on MATLAB,EMB&VLSI for ECE Dept DreamwebTechnosolutions
73/5,3rd FLOOR,SRI KAMATCHI COMPLEX
OPP.CITY HOSPITAL (NEAR LAKSHMI COMPLEX)
SALAI ROAD,Trichy - 620 018,
Ph: 0431 4050403,7200021403/04.
IEEE Final Year Projects for M.E/M.TECH-CSE,VLSI,COMMUNICATION SYSTEM,B.E-CSE/IT from any domain & Technologies.For more detail contact:-DreamWeb TechnoSolutions@7200021403/04, 73/5 3rd floor,Kamatchi cmplx,SALAI ROADThillai nagar 1st cross,Trichy
IEEE Final Year Projects for M.E/M.TECH-CSE,VLSI,COMMUNICATION SYSTEM,B.E-CSE/IT from any domain & Technologies.For more detail contact:-DreamWeb TechnoSolutions@7200021403/04, 73/5 3rd floor,Kamatchi cmplx,SALAI ROADThillai nagar 1st cross,Trichy
IEEE Final Year Projects for M.E/M.TECH-CSE,VLSI,COMMUNICATION SYSTEM,B.E-CSE/IT from any domain & Technologies.For more detail contact:-DreamWeb TechnoSolutions@7200021403/04, 73/5 3rd floor,Kamatchi cmplx,SALAI ROADThillai nagar 1st cross,Trichy
A review on techniques and modelling methodologies used for checking electrom...nooriasukmaningtyas
The proper function of the integrated circuit (IC) in an inhibiting electromagnetic environment has always been a serious concern throughout the decades of revolution in the world of electronics, from disjunct devices to today’s integrated circuit technology, where billions of transistors are combined on a single chip. The automotive industry and smart vehicles in particular, are confronting design issues such as being prone to electromagnetic interference (EMI). Electronic control devices calculate incorrect outputs because of EMI and sensors give misleading values which can prove fatal in case of automotives. In this paper, the authors have non exhaustively tried to review research work concerned with the investigation of EMI in ICs and prediction of this EMI using various modelling methodologies and measurement setups.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELgerogepatton
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Sinan KOZAK
Sinan from the Delivery Hero mobile infrastructure engineering team shares a deep dive into performance acceleration with Gradle build cache optimizations. Sinan shares their journey into solving complex build-cache problems that affect Gradle builds. By understanding the challenges and solutions found in our journey, we aim to demonstrate the possibilities for faster builds. The case study reveals how overlapping outputs and cache misconfigurations led to significant increases in build times, especially as the project scaled up with numerous modules using Paparazzi tests. The journey from diagnosing to defeating cache issues offers invaluable lessons on maintaining cache integrity without sacrificing functionality.
Comparative analysis between traditional aquaponics and reconstructed aquapon...bijceesjournal
The aquaponic system of planting is a method that does not require soil usage. It is a method that only needs water, fish, lava rocks (a substitute for soil), and plants. Aquaponic systems are sustainable and environmentally friendly. Its use not only helps to plant in small spaces but also helps reduce artificial chemical use and minimizes excess water use, as aquaponics consumes 90% less water than soil-based gardening. The study applied a descriptive and experimental design to assess and compare conventional and reconstructed aquaponic methods for reproducing tomatoes. The researchers created an observation checklist to determine the significant factors of the study. The study aims to determine the significant difference between traditional aquaponics and reconstructed aquaponics systems propagating tomatoes in terms of height, weight, girth, and number of fruits. The reconstructed aquaponics system’s higher growth yield results in a much more nourished crop than the traditional aquaponics system. It is superior in its number of fruits, height, weight, and girth measurement. Moreover, the reconstructed aquaponics system is proven to eliminate all the hindrances present in the traditional aquaponics system, which are overcrowding of fish, algae growth, pest problems, contaminated water, and dead fish.
This document contains contact information for DreamwebTechnosolutions in Trichy, India and lists several mobile computing, data mining, cloud computing, big data, and network security research project titles and their years. It provides titles and years for 11 mobile computing projects, 11 data mining projects, 13 cloud computing projects, 6 big data projects, and 5 network security projects conducted between 2016-2017. The contact listed is K.RanjithKumar who can be reached by phone.
We are offering PROJECTS in EMBEDDED, MATLAB, NS2, VLSI, Power Electronics,Power Systems for BE- ECE & EEE Students.
Own Concepts also accepted.providing real time projects on MATLAB,EMB&VLSI for ECE Dept DreamwebTechnosolutions
73/5,3rd FLOOR,SRI KAMATCHI COMPLEX
OPP.CITY HOSPITAL (NEAR LAKSHMI COMPLEX)
SALAI ROAD,Trichy - 620 018,
Ph: 0431 4050403,7200021403/04.
IEEE Final Year Projects for M.E/M.TECH-CSE,VLSI,COMMUNICATION SYSTEM,B.E-CSE/IT from any domain & Technologies.For more detail contact:-DreamWeb TechnoSolutions@7200021403/04, 73/5 3rd floor,Kamatchi cmplx,SALAI ROADThillai nagar 1st cross,Trichy
We are offering PROJECTS in EMBEDDED, MATLAB, NS2, VLSI, Power Electronics,Power Systems for BE- ECE & EEE Students.
Own Concepts also accepted.providing real time projects on MATLAB,EMB&VLSI for ECE Dept DreamwebTechnosolutions
73/5,3rd FLOOR,SRI KAMATCHI COMPLEX
OPP.CITY HOSPITAL (NEAR LAKSHMI COMPLEX)
SALAI ROAD,Trichy - 620 018,
Ph: 0431 4050403,7200021403/04.
IEEE Final Year Projects for M.E/M.TECH-CSE,VLSI,COMMUNICATION SYSTEM,B.E-CSE/IT from any domain & Technologies.For more detail contact:-DreamWeb TechnoSolutions@7200021403/04, 73/5 3rd floor,Kamatchi cmplx,SALAI ROADThillai nagar 1st cross,Trichy
IEEE Final Year Projects for M.E/M.TECH-CSE,VLSI,COMMUNICATION SYSTEM,B.E-CSE/IT from any domain & Technologies.For more detail contact:-DreamWeb TechnoSolutions@7200021403/04, 73/5 3rd floor,Kamatchi cmplx,SALAI ROADThillai nagar 1st cross,Trichy
IEEE Final Year Projects for M.E/M.TECH-CSE,VLSI,COMMUNICATION SYSTEM,B.E-CSE/IT from any domain & Technologies.For more detail contact:-DreamWeb TechnoSolutions@7200021403/04, 73/5 3rd floor,Kamatchi cmplx,SALAI ROADThillai nagar 1st cross,Trichy
A review on techniques and modelling methodologies used for checking electrom...nooriasukmaningtyas
The proper function of the integrated circuit (IC) in an inhibiting electromagnetic environment has always been a serious concern throughout the decades of revolution in the world of electronics, from disjunct devices to today’s integrated circuit technology, where billions of transistors are combined on a single chip. The automotive industry and smart vehicles in particular, are confronting design issues such as being prone to electromagnetic interference (EMI). Electronic control devices calculate incorrect outputs because of EMI and sensors give misleading values which can prove fatal in case of automotives. In this paper, the authors have non exhaustively tried to review research work concerned with the investigation of EMI in ICs and prediction of this EMI using various modelling methodologies and measurement setups.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELgerogepatton
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Sinan KOZAK
Sinan from the Delivery Hero mobile infrastructure engineering team shares a deep dive into performance acceleration with Gradle build cache optimizations. Sinan shares their journey into solving complex build-cache problems that affect Gradle builds. By understanding the challenges and solutions found in our journey, we aim to demonstrate the possibilities for faster builds. The case study reveals how overlapping outputs and cache misconfigurations led to significant increases in build times, especially as the project scaled up with numerous modules using Paparazzi tests. The journey from diagnosing to defeating cache issues offers invaluable lessons on maintaining cache integrity without sacrificing functionality.
Comparative analysis between traditional aquaponics and reconstructed aquapon...bijceesjournal
The aquaponic system of planting is a method that does not require soil usage. It is a method that only needs water, fish, lava rocks (a substitute for soil), and plants. Aquaponic systems are sustainable and environmentally friendly. Its use not only helps to plant in small spaces but also helps reduce artificial chemical use and minimizes excess water use, as aquaponics consumes 90% less water than soil-based gardening. The study applied a descriptive and experimental design to assess and compare conventional and reconstructed aquaponic methods for reproducing tomatoes. The researchers created an observation checklist to determine the significant factors of the study. The study aims to determine the significant difference between traditional aquaponics and reconstructed aquaponics systems propagating tomatoes in terms of height, weight, girth, and number of fruits. The reconstructed aquaponics system’s higher growth yield results in a much more nourished crop than the traditional aquaponics system. It is superior in its number of fruits, height, weight, and girth measurement. Moreover, the reconstructed aquaponics system is proven to eliminate all the hindrances present in the traditional aquaponics system, which are overcrowding of fish, algae growth, pest problems, contaminated water, and dead fish.
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...University of Maribor
Slides from talk presenting:
Aleš Zamuda: Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapter and Networking.
Presentation at IcETRAN 2024 session:
"Inter-Society Networking Panel GRSS/MTT-S/CIS
Panel Session: Promoting Connection and Cooperation"
IEEE Slovenia GRSS
IEEE Serbia and Montenegro MTT-S
IEEE Slovenia CIS
11TH INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONIC AND COMPUTING ENGINEERING
3-6 June 2024, Niš, Serbia
A SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMSIJNSA Journal
The smart irrigation system represents an innovative approach to optimize water usage in agricultural and landscaping practices. The integration of cutting-edge technologies, including sensors, actuators, and data analysis, empowers this system to provide accurate monitoring and control of irrigation processes by leveraging real-time environmental conditions. The main objective of a smart irrigation system is to optimize water efficiency, minimize expenses, and foster the adoption of sustainable water management methods. This paper conducts a systematic risk assessment by exploring the key components/assets and their functionalities in the smart irrigation system. The crucial role of sensors in gathering data on soil moisture, weather patterns, and plant well-being is emphasized in this system. These sensors enable intelligent decision-making in irrigation scheduling and water distribution, leading to enhanced water efficiency and sustainable water management practices. Actuators enable automated control of irrigation devices, ensuring precise and targeted water delivery to plants. Additionally, the paper addresses the potential threat and vulnerabilities associated with smart irrigation systems. It discusses limitations of the system, such as power constraints and computational capabilities, and calculates the potential security risks. The paper suggests possible risk treatment methods for effective secure system operation. In conclusion, the paper emphasizes the significant benefits of implementing smart irrigation systems, including improved water conservation, increased crop yield, and reduced environmental impact. Additionally, based on the security analysis conducted, the paper recommends the implementation of countermeasures and security approaches to address vulnerabilities and ensure the integrity and reliability of the system. By incorporating these measures, smart irrigation technology can revolutionize water management practices in agriculture, promoting sustainability, resource efficiency, and safeguarding against potential security threats.
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...
Ieee 2016 project titles in mobilecomputing for me m.tech
1. DreamwebTechnosolutions
73/5,3rdFLOOR, SRI KAMATCHI COMPLEX
OPP.CITY HOSPITAL (NEAR LAKSHMI COMPLEX)
SALAI ROAD,Trichy - 620 018,
Contact:-K.RanjithKumar:7200021403/04 PH: 0431 4050403.
S/No PROJECT CAPTION YEAR
MOBILE COMPUTING TITLES LIST
1 A Street-Centric Opportunistic Routing Protocol Based on Link
Correlation for Urban VANETs
2016-17
2 Detecting Node Failures in Mobile Wireless Networks: A Probabilistic
Approach
2016-17
3 Optimizing Video Request Routing in Mobile Networks with Built-in
Content Caching
2016-17
4 Toward Optimal Distributed Monitoring of Multi-Channel Wireless
Networks
2016-17
5 Delay Minimization for Data Dissemination in Large-Scale VANETs
with Buses and Taxis
2016-17
6 Profit Maximization through Online Advertising Scheduling for a
Wireless Video Broadcast Network
2016-17
7 Secure Run: Cheat-Proof and Private Summaries for Location-Based
Activities
2016-17
8 Distance-based Location Management Utilizing Initial Position for
Mobile CommunicationNetworks
2016-17
9 ALTERDROID: Differential Fault Analysis of Obfuscated Smartphone
Malware
2016-17
10 Propagation- and Mobility-Aware D2D Social Content Replication 2016-17
DATA MINING TITLES LIST
1 A Novel Recommendation Model Regularized with User Trust and Item
Ratings
2016-17
2 Resolving Multi-Party Privacy Conflicts in Social Media 2016-17
3 A Framework for Categorizing and Applying Privacy-Preservation
Techniques in Big Data Mining
2016-17
4 Truth Discovery in Crowdsourced Detection of Spatial Events 2016-17
2. DreamwebTechnosolutions
73/5,3rdFLOOR, SRI KAMATCHI COMPLEX
OPP.CITY HOSPITAL (NEAR LAKSHMI COMPLEX)
SALAI ROAD,Trichy - 620 018,
Contact:-K.RanjithKumar:7200021403/04 PH: 0431 4050403.
5 Inductive Visual Miner Plugin Customization for the Detection of
Eventualities in the Processes of a Hospital Information System
2016-17
6 Hierarchical Spatio-Temporal Pattern Discovery and Predictive
Modeling
2016-17
7 Resolving Multi-party Privacy Conflicts in Social Media 2016-17
S/No PROJECT CAPTION YEAR
CLOUD COMPUTINGTITLES LIST
1 Encrypted Data Management with Deduplication in Cloud Computing 2016-17
2 Secure Data Analytics for Cloud-Integrated Internet of Things
Applications
2016-17
3 Security in Cloud-Computing-Based Mobile Health 2016-17
4 Migrating Smart City Applications to the Cloud 2016-17
5 Optimizing Cost for Online Social Networks on Geo-Distributed Clouds 2016-17
6 Supporting Multi Data Stores Applications in Cloud Environments 2016-17
7 Dispersing Instant Social Video Service Across Multiple Clouds 2016-17
8 Propagation- and Mobility-Aware D2D Social Content Replication
9 ALTERDROID: Differential Fault Analysis of Obfuscated Smartphone
Malware
BIG DATA TITLES LIST
1 Conjunctive Keyword Search With Designated Tester and Timing
Enabled Proxy Re-Encryption Function for E-Health Clouds
2016-17
2 Leveraging Data Deduplication to Improve the Performance of Primary
Storage Systems in the Cloudk
2016-17
3. DreamwebTechnosolutions
73/5,3rdFLOOR, SRI KAMATCHI COMPLEX
OPP.CITY HOSPITAL (NEAR LAKSHMI COMPLEX)
SALAI ROAD,Trichy - 620 018,
Contact:-K.RanjithKumar:7200021403/04 PH: 0431 4050403.
3 A Parallel Patient Treatment Time Prediction Algorithm and Its
Applications in Hospital Queuing-Recommendation in
a Big Data Environment
2016-17
4 OverFlow: Multi-Site Aware Big Data Management for Scientific
Workflows on Clouds
2016-17
5 Conjunctive Keyword Search With Designated Tester and Timing
Enabled Proxy Re-Encryption Function for E-Health Clouds
2016-17
6 Leveraging Data Deduplication to Improve the Performance of Primary
Storage Systems in the Cloudk
2016-17
NETWORK SECURITY TITLES LIST
1 FakeMask: A Novel Privacy Preserving Approach for Smartphones 2016-17
2 The Server Provisioning Problem for Continuous Distributed Interactive
Application
2016-17