http://WWW.FINALYEARPROJECTS.NET
http://WWW.FINALYEARPROJECTS.NET

Checking delivery availability...

background-sm
Search

Updates found with 'regards'

Page  1 1

Updates found with 'regards'

IEEE 2016 JAVA PROJECTS ABSTRACT ENHANCED CONTROL FOR ADAPTIVE RESOURCE RESERVATION OF GUARANTEED SERVICES IN LTE NETWORKSABSTRACT: Mobile innovative services are being introduced continuously to enhance people’s life through facilitating the interaction between human and the rest of the world. The world of ”Internet of Things” (IoT) is expanding everyday to include more things to be connected. Considering more and more innovative mobile services are being introduced, the LTE telecom systems/networks will be more complicated, require more resources, and demand more challenging requirements. The LTEEvolved Packet Core network (EPC) internal design is inadequate with regards to the resources reservation techniques used to carry out the guaranteed dedicated services. In fact, EPC does not have the capabilities to utilize properly the unused bandwidth of the guaranteed bearer when the reserved bandwidth is not fully used by the mobile service, the unused guaranteed bandwidths considered as wasted resources and consequently the whole LTE/EPC network efficiency gets affected. In this paper, we propose an adaptive technique which enhances the resource reservation for the LTE Mobile guaranteed services, our solution provides techniques to: analyze the ongoing mobile guaranteed traffic usage, provide time-series models that mathematically represent the conducted data, forecast the mobile service guaranteed resource consumption, identify the wasted/unused resources, and utilize these resources by other services. Our experiment were conducted on a dataset captured on an LTE network, the experimental results show that our approach is feasible and beneficial as it enhances the resource allocation for the T-Mobile services and increases the overall throughput of the LTE/EPC networks.
Send Enquiry
Read More
IEEE 2016 JAVA PROJECTS ABSTRACTENHANCED CONTROL FOR ADAPTIVE RESOURCE RESERVATION OF GUARANTEED SERVICES IN LTE NETWORKS ABSTRACT: Mobile innovative services are being introduced continuously to enhance people’s life through facilitating the interaction between human and the rest of the world. The world of ”Internet of Things” (IoT) is expanding everyday to include more things to be connected. Considering more and more innovative mobile services are being introduced, the LTEtelecom systems/networks will be more complicated, require more resources, and demand more challenging requirements. The LTE Evolved Packet Core network (EPC) internal design is inadequate with regards to the resources reservation techniques used to carryout the guaranteed dedicated services. In fact, EPC does not have the capabilities to utilize properly the unused bandwidth of the guaranteed bearer when the reserved bandwidth is not fully used by the mobile service, the unused guaranteed bandwidths considered as wasted resources and consequently the wholeLTE/EPC network efficiency gets affected. In this paper, we propose an adaptive technique which enhances the resource reservation for the LTE Mobile guaranteed services, our solution provides techniques to: analyze the ongoing mobile guaranteed traffic usage, provide time-series models that mathematically represent the conducted data, forecast the mobile service guaranteed resource consumption, identify the wasted/unused resources, and utilize these resources by other services. Our experiments were conducted on a dataset captured on an LTE network, the experimental results show that our approach is feasible an beneficial as it enhances the resource allocation for the LTE mobile services and increases the overall throughput of theLTE/EPC networks
Send Enquiry
Read More
IEEE 2016 MAT LAB PROJECTS ABSTRACTOPTIMIZED LTE CELL PLANNING WITH VARYING SPATIAL AND TEMPORAL USER DENSITIES ABSTRACT: Base station deployment in cellular networks is one of the fundamental problems in network design. This paper proposes a novel method for the cell planning problem for the fourth generation (4G) cellular networks using meta-heuristic algorithms. In this approach, we aim to satisfy both cell coverage and capacity constraints simultaneously by formulating an optimization problem that captures practical planning aspects. The starting point of the planning process is defined through a dimensioning exercise that captures both coverage and capacity constraints. Afterwards, we implement a meta-heuristic algorithm based on swarm intelligence (e.g., particle swarm optimization or the recently-proposed grey wolf optimizer) to find suboptimal base station locations that satisfy both problem constraints in the area of interest which can be divided into several subareas with different spatial user densities. Subsequently, an iterative approach is executed to eliminate eventual redundant base stations. We also perform Monte Carlo simulations to study the performance of the proposed scheme and compute the average number of users in outage. Next, the problems of green planning with regards to temporal traffic variation and planning with location constraints due to tight limits on electromagnetic radiations are addressed, using the proposed method. Finally, in our simulation results, we apply our proposed approach for different scenarios with different subareas and user distributions and show that the desired network quality of service targets are always reached even for large-scale problems.
Send Enquiry
Read More
IEEE 2016-2017 EMBEDDED PROJECTS ABSTRACTFLEXIBLE TECHNOLOGIES FOR SMART CAMPUS ABSTRACT: The project deals with different wireless technologies are compared in regards to their main feature and field of application. In general the characteristics of a Blue Tooth Low Energy, BLE, are highlighted. This is elaborated upon in the Smart Campus example. The Smart Campus is an indoor wireless network to deliver location and user based dynamic information to the different visitors, teacher or students of a university campus, both for day-to-day use as for specific events. The system interesting and to augment ease-of-use for all kind of users and content providers, a dedicated content management system is developed within the Smart Campus case. An experimental prototype consists of a set of beacons for day to day monitoring. The data from the beacon gets transmitted and it can be monitored in smart phone or personal computer.EXISTING SYSTEM:-• In existing system only for GPS identification of particular location.• Using wireless data transmission Bluetooth & wi-fi• Transmission data time more.PROPOSED SYSTEM:-• The proposed model is a pure wireless data communication system for smart phone.• I beacon used in long range distance and particular location identification automatically through phone • Transmission data time less .HARDWARE REQUIREMENT:-• I BEACON MODULE• AT89S52• BATTERY• MOBILE PHONE • PCSOFTWARE REQUIREMENT:-• KEIL IDE• EMBEDDED C• I BEACON APP
Send Enquiry
Read More
IEEE 2017_2018 BIO_MEDICAL PROJECT TITLES Segmentation, Splitting, and Classification of Overlapping Bacteria in Microscope Images for Automatic Bacterial Vaginosis DiagnosisAbstract—Quantitative analysis of bacterial morpho types in the microscope images plays a vital role in diagnosis of bacterial vaginosis (BV) based on the Nugent score criterion. However, there are two main challenges for this task: (1) It is quite difficult to identify the bacterial regions due to various appearance, faint boundaries, heterogeneous shapes, low contrast with the background, and small bacteria sizes with regards to the image; (2) There are numerous bacteria overlapping with each other, which hinder us to conduct accurate analysis on individual bacterium. To overcome these challenges, we propose an automatic method in this paper to diagnose BV by quantitative analysis of bacterial morphotypes, which consists of a three-step approach, i.e., bacteria regions segmentation, overlapping bacteria splitting, and bacterial morphotypes classification. Specifically, we first segment the bacteria regions via saliency cut, which simultaneously evaluates the global contrast and spatial weighted coherence. And then Markov random field model is applied for high quality unsupervised segmentation of small object. We then decompose overlapping bacteria clumps into markers, and associate a pixel with markers to identify evidence for eventual individual bacterium splitting. Next, we extract morphotype features from each bacterium to learn the descriptors and to characterize the types of bacteria using an Adaptive Boosting (AdaBoost) machine learning framework. Finally, BV diagnosis is implemented based on the Nugent score criterion. Experiments demonstrate that our proposed method achieves high accuracy and efficiency in computation for BV diagnosis.CONTACT:GANESAN.P89034103199865862045
Send Enquiry
Read More
Page 1 0.5