Eighth Annual Student Research Forum
|
|
- Lorraine Jordan
- 8 years ago
- Views:
Transcription
1 Eighth Annual Student Research Forum February 18, 2011 COMPUTER SCIENCE AND COMPUTATIONAL SCIENCE
2 PRESENTATION SCHEDULE Session Chair: Dr. George Miminis Head, Computer Science: Dr. Edward Brown Director, Computational Science: Dr. Martin Plumer FRIDAY, FEBRUARY 18, 2011, EN Opening Remarks 0930 Proactive Source Routing, Zehua Wang 0950 Evolution of Globular Clusters in the Milky Way Galaxy, Adam Royle 1010 Fall Detection for the Elderly, Biru Cui BREAK 1100 Mathematical Modelling of Thrombin Generation in Children, Steven Dlamini 1120 Approximation Complexity of the Knapsack Problem, Renesa Nizamee 1140 Monte Carlo Simulations to Investigate the Magnetic Properties of Anti-ferromagnetic IrMn3, Vahid Hemmati LUNCH 1400 Positioning Using Motion Information in RF Reference Frames, Wasiq Waqar 1420 Integrating Human Decision-Making within an Ontology Alignment Process, Muhammad Nasir 1440 Data Organization and Visualization Using the Self-Sorting Map, Grant Strong 1500 Closing Remarks
3 FRIDAY, FEBRUARY 18, Zehua Wang, MEng, Faculty of Engineering Proactive Source Routing Routing is a fundamental operation on mobile ad hoc networks. In this work, we propose a Proactive Source Routing protocol (PSR) that is as lightweight as distance vectors and nearly as powerful as link states. PSR maintains full source routing information at all times in order to support opportunistic data forwarding in a dynamically changing multi-hop wireless networks. PSR is shown robust against both high-rate node mobility and fast link quality variation Adam Royle, M.Sc. Computational Science Evolution of Globular Clusters in the Milky Way Galaxy Globular clusters are very old objects that have been orbiting the Galaxy since just after the Galaxy formed, over ten billion years ago. Due to this large time scale, computer simulations provide the best tool to study their evolution. During their orbits, they experience external forces from the Galaxy which may perturb the cluster. A description of the problem, the methods used to simulate these orbits and some preliminary results will be presented Biru Cui, Ph.D. Computer Science Fall Detection for the Elderly Falling is one of the dangerous accidents for elderly people, especially in the case when they become unconscious after the fall. This project proposes a fall detector to alert emergency medical care personnel when this happens Steven C. Dlamini, M.Sc. Computational Science Mathematical Modelling of Thrombin Generation in Children Much research work has been done in modeling thrombin generation for vascular systems. Traditionally thrombin generation problems were not a major concern for children and infants hence most research in this area is largely confined to characterizing the thrombin generation system in adults. However, with the advancement of surgery procedures, there have been increases in incidents of infant
4 mortality due to thrombotic complications during or after surgery. In addition thrombin generation in adults is significantly different from thrombin generation in children hence the current practice of referring to adult values when trying to treat thrombotic complications in children is not accurate. In this light, it is therefore of paramount importance to pursue a study of thrombin generation in children Renesa Nizamee, M.Sc. Computer Science Approximation Complexity of the Knapsack Problem Since NP-complete problems seem to be hard to solve optimally, it is natural to look for approximate solutions. Some NP-complete problems are as hard to approximate as it is to solve optimally. However, there are NP-complete problems that are easy to approximate well; an example of such a problem is the Knapsack problem. We can define the problem as follows: given a set of items, each with a weight and a value, and a weight limit, determine which items to include in the collection so that the total weight is at most the limit and the total value is as large as possible. For example, a humanitarian mission might need to find the best set of donated items to load to a helicopter going to a disaster area. Here we will talk about the algorithms and complexity of approximating Knapsack, both in the traditional and structure-approximation setting Vahid Hemmati, M.Sc. Computational Science Monte Carlo Simulations to Investigate the Magnetic Properties of Anti-ferromagnetic IrMn3. The anti-ferromagnetic IrMn3 is the main material used in stabilizing the magnetization of the soft ferromagnetic layer, employed in rewritable memories. The theories explaining the Exchange Bias phenomena which provides the magnetic field to stabilize a soft ferromagnetic layer, significantly confirms the role of the spin-configuration of magnetic atoms in the ferromagnet. The Metropolis Monte Carlo simulation method is used to determine thermal equilibrium properties and spin configurations on thin films of IrMn3, which are formed from ABC stacked layers of the Kagome lattice. The method, its use in an HPC environment, and some preliminary results will be reviewed.
5 1400 Wasiq Waqar, M.Sc., Computer Science Positioning Using Motion Information in RF Reference Frames Due to an increase in the demand of context-aware applications, there is a greater demand for accurate user location information. Today, the location for outdoor environments is mostly provided by the Global Positioning System. However current indoor positioning and tracking technologies for general objects are not as reliable or practical. There is an imminent need for an indoor localization technology which is not only accurate but also responsive. In the past, numerous Inertial Measurement Unit (IMU) based localization techniques have been proposed, but most of them use customized hardware. Now, a new generation of smart phone devices equipped with numerous sensors, supplemented by infrastructure-based radio frequency (RF) capabilities, allow new opportunities for accurate and fast positioning schemes. In this talk, I introduce my research of using smart phone for sensor driven indoor mobile positioning. Today s mobile devices contain embedded sensors like gyroscope, accelerometer, electronic compass, etc. We can use these sensors supplemented by sporadic Wi-Fi signals, to transcribe user location. As IMU-based positioning schemes suffer from integration drift, we can use existing Wi-Fi signals and other techniques to assist in keeping the location estimation error to a minimum. I will conduct research on how we can use the user motion information and Wi-Fi signals in collaboration to develop a near real-time indoor positioning scheme Muhammad Nasir, M.Sc. Computer Science Integrating Human Decision-Making within an Ontology Alignment Process Ontology alignment is of key importance within the information integration domain. Primarily, ontology alignment research focuses on creating state-of-the-art alignment algorithms. Recently, researchers have started to analyse and give importance to various aspects of user involvement within ontology mapping processes. Currently, the so-called user-guided interactive systems experience difficulty in using the feedback in a generalized and effective manner. Several validations of mappings produced by the system are required to be performed by the user. This feedback is then used for different purposes; to remove the rejected mappings from the final mapping set, to discover the order for validations, exploring which mapping approach is best (among the many applied) for the given set of ontologies and others. This results into too many validations at once, specific-to-ontology improvements, and others, which can be improved. Since ontologies are commonly used to represent complex domain knowledge, their size can grow easily. As a consequence, the alignment algorithm produces large number of mappings which ultimately the user has to process and manipulate. The visualization of mappings is supposed to help the users in understanding the
6 underlying features, but representing a large number of mappings usually results in a visual clutter. Therefore we argue that there are three aspects to the solution for an ontology alignment problem that we want to explore in this research. First is the underlying alignment algorithm which uses state-of-the-art techniques using linguistic, semantic, structural similarity and other types of analysis to generate approximate alignment suggestions. The second is the integration of human decision-making within the ontology alignment process. The final is the enhancements to the interface with visual and interaction features to support decision-making process. First instead of working on the entire set of ontologies, we will make use of user s decision-making capabilities in the process. The user will select the relevant subjects based on their judgement regarding the given ontologies upon which the alignment algorithm will attempt to generate mappings. After producing these mappings from each group of selected subsets, the process of integration and conflict resolution will be carried out, using the user s judgement to produce a global mapping set. Secondly, an edge-bundling algorithm with interactive features will be applied for mapping representation and manipulation. The edge-bundling approach is quite successful in representing an organized view of large graphs. Similarly, we have huge ontologies which when aligned results in large number of alignment edges. These edges can be grouped using the bundling algorithm, producing well-structured overview of the mappings. After discovering the interested mapping set (i.e. a bundle), the user can further delve into individual mappings inside the set by using interactive features such as zooming, filtering and focusing. The user will also get immediate feedback regarding the quality of alignment process as a result of attempting to perform a particular mapping manipulation action. The feedback may be used to guide the user in making an informed decision about a mapping by showing that consequent effects of performing that action. We believe that our proposed features would help the user not just performing better in various tasks related to ontology mappings but also to effectively deal with problem of large ontologies and mapping sets Grant Strong, Ph.D. Computer Science Data Organization and Visualization using the Self-Sorting Map Data comes in many forms. High dimensional data in particular is hard for human beings to make sense of in its raw form. Our visual and analytical systems are brilliantly engineered to make sense of and extract patterns from complex pictures yet they are ill-equipped to deal with tables of numbers directly. For this reason people have been trying for years to come up with ways to reduce the dimensionality of their data so it can be displayed in picture form so we can make sense of it easily if there is sense to be made. Of the methods that have been developed, most are limited to dealing with data as vectors and do not put any constraints on the range in which it is output. This lack of constraints means that occlusion can be a real problem and dealing with it is a whole field onto itself. In a lot of cases we are not as concerned with data being perfectly placed in the output space, but rather that the relative relationships between the data are modeled
7 intuitively. We present a general, parallelizable algorithm for organizing data that can work on vector data as well as or better than the predecessors from which it was inspired in terms of speed and final presentation, with the added bonus of it being adaptable to run on non-vector nominal data. The fundamental difference in this algorithm is that it seeks to order data items within the confines of a celled structure so that the correlation between the similarity of the items and the relative positions of them in the structure is maximized.
Traffic Prediction in Wireless Mesh Networks Using Process Mining Algorithms
Traffic Prediction in Wireless Mesh Networks Using Process Mining Algorithms Kirill Krinkin Open Source and Linux lab Saint Petersburg, Russia kirill.krinkin@fruct.org Eugene Kalishenko Saint Petersburg
More informationCHAPTER 1 INTRODUCTION
CHAPTER 1 INTRODUCTION 1.1 Background of the Research Agile and precise maneuverability of helicopters makes them useful for many critical tasks ranging from rescue and law enforcement task to inspection
More informationCONTRIBUTIONS TO THE AUTOMATIC CONTROL OF AERIAL VEHICLES
1 / 23 CONTRIBUTIONS TO THE AUTOMATIC CONTROL OF AERIAL VEHICLES MINH DUC HUA 1 1 INRIA Sophia Antipolis, AROBAS team I3S-CNRS Sophia Antipolis, CONDOR team Project ANR SCUAV Supervisors: Pascal MORIN,
More informationComputer Animation and Visualisation. Lecture 1. Introduction
Computer Animation and Visualisation Lecture 1 Introduction 1 Today s topics Overview of the lecture Introduction to Computer Animation Introduction to Visualisation 2 Introduction (PhD in Tokyo, 2000,
More informationA Demonstration of a Robust Context Classification System (CCS) and its Context ToolChain (CTC)
A Demonstration of a Robust Context Classification System () and its Context ToolChain (CTC) Martin Berchtold, Henning Günther and Michael Beigl Institut für Betriebssysteme und Rechnerverbund Abstract.
More informationHow To Get A Computer Science Degree
MAJOR: DEGREE: COMPUTER SCIENCE MASTER OF SCIENCE (M.S.) CONCENTRATIONS: HIGH-PERFORMANCE COMPUTING & BIOINFORMATICS CYBER-SECURITY & NETWORKING The Department of Computer Science offers a Master of Science
More informationFrom reconfigurable transceivers to reconfigurable networks, part II: Cognitive radio networks. Loreto Pescosolido
From reconfigurable transceivers to reconfigurable networks, part II: Cognitive radio networks Loreto Pescosolido Spectrum occupancy with current technologies Current wireless networks, operating in either
More informationSensor Fusion Mobile Platform Challenges and Future Directions Jim Steele VP of Engineering, Sensor Platforms, Inc.
Sensor Fusion Mobile Platform Challenges and Future Directions Jim Steele VP of Engineering, Sensor Platforms, Inc. Copyright Khronos Group 2012 Page 104 Copyright Khronos Group 2012 Page 105 How Many
More informationLecture 2.1 : The Distributed Bellman-Ford Algorithm. Lecture 2.2 : The Destination Sequenced Distance Vector (DSDV) protocol
Lecture 2 : The DSDV Protocol Lecture 2.1 : The Distributed Bellman-Ford Algorithm Lecture 2.2 : The Destination Sequenced Distance Vector (DSDV) protocol The Routing Problem S S D D The routing problem
More informationCrowdsourcing mobile networks from experiment
Crowdsourcing mobile networks from the experiment Katia Jaffrès-Runser University of Toulouse, INPT-ENSEEIHT, IRIT lab, IRT Team Ecole des sciences avancées de Luchon Networks and Data Mining, Session
More informationBIG DATA IN THE CLOUD : CHALLENGES AND OPPORTUNITIES MARY- JANE SULE & PROF. MAOZHEN LI BRUNEL UNIVERSITY, LONDON
BIG DATA IN THE CLOUD : CHALLENGES AND OPPORTUNITIES MARY- JANE SULE & PROF. MAOZHEN LI BRUNEL UNIVERSITY, LONDON Overview * Introduction * Multiple faces of Big Data * Challenges of Big Data * Cloud Computing
More informationThe Cisco and Pelco Industrial Wireless Video Surveillance Solution: Real-Time Monitoring of Process Environments for Safety and Security
The Cisco and Pelco Industrial Wireless Video Surveillance Solution: Real-Time Monitoring of Process Environments for Safety and Security The Cisco and Pelco Industrial Wireless Video Surveillance Solution
More informationData Isn't Everything
June 17, 2015 Innovate Forward Data Isn't Everything The Challenges of Big Data, Advanced Analytics, and Advance Computation Devices for Transportation Agencies. Using Data to Support Mission, Administration,
More informationMaster of Science (Electrical Engineering) MS(EE)
Master of Science (Electrical Engineering) MS(EE) 1. Mission Statement: The mission of the Electrical Engineering Department is to provide quality education to prepare students who will play a significant
More informationDesign of Remote data acquisition system based on Internet of Things
, pp.32-36 http://dx.doi.org/10.14257/astl.214.79.07 Design of Remote data acquisition system based on Internet of Things NIU Ling Zhou Kou Normal University, Zhoukou 466001,China; Niuling@zknu.edu.cn
More informationClient Overview. Engagement Situation. Key Requirements
Client Overview Our client is one of the leading providers of business intelligence systems for customers especially in BFSI space that needs intensive data analysis of huge amounts of data for their decision
More informationHow To Create A Data Science System
Enhance Collaboration and Data Sharing for Faster Decisions and Improved Mission Outcome Richard Breakiron Senior Director, Cyber Solutions Rbreakiron@vion.com Office: 571-353-6127 / Cell: 803-443-8002
More informationForce/position control of a robotic system for transcranial magnetic stimulation
Force/position control of a robotic system for transcranial magnetic stimulation W.N. Wan Zakaria School of Mechanical and System Engineering Newcastle University Abstract To develop a force control scheme
More informationSTRUCTURAL HEALTH MONITORING AT ROME UNDERGROUND, ROMA, ITALY
Ref: WhP_Rome_vA STRUCTURAL HEALTH MONITORING AT ROME UNDERGROUND, ROMA, ITALY WHITE PAPER Summary: This white paper shows how Structural Health Monitoring (SHM), helps to improve the quality in the construction
More informationLocation tracking: technology, methodology and applications
Location tracking: technology, methodology and applications Marina L. Gavrilova SPARCS Laboratory Co-Director Associate Professor University of Calgary Interests and affiliations SPARCS Lab Co-Founder
More informationSan Jose State University
San Jose State University San Jose State University San José State University (SJSU), a metropolitan university, has a long and proud history as a supplier of excellent higher education, a contributor
More informationSynergistic Sensor Location for Cost-Effective Traffic Monitoring
Synergistic Sensor Location for Cost-Effective Traffic Monitoring ManWo Ng, Ph.D. Assistant Professor Department of Modeling, Simulation and Visualization Engineering & Department of Civil and Environmental
More informationArtificial Intelligence and Robotics @ Politecnico di Milano. Presented by Matteo Matteucci
1 Artificial Intelligence and Robotics @ Politecnico di Milano Presented by Matteo Matteucci What is Artificial Intelligence «The field of theory & development of computer systems able to perform tasks
More informationANDROID APPLICATION DEVELOPMENT FOR ENVIRONMENT MONITORING USING SMART PHONES
ANDROID APPLICATION DEVELOPMENT FOR ENVIRONMENT MONITORING USING SMART PHONES ABSTRACT K. Krishnakanth 1 and P. Kavipriya 2 1 M.E Embedded Systems, Sathyabama University, Chennai, India. krishnakoneru99@gmail.com
More informationCourse 803401 DSS. Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization
Oman College of Management and Technology Course 803401 DSS Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization CS/MIS Department Information Sharing
More informationPolitecnico di Milano Advanced Network Technologies Laboratory
Politecnico di Milano Advanced Network Technologies Laboratory Energy and Mobility: Scalable Solutions for the Mobile Data Explosion Antonio Capone TIA 2012 GreenTouch Open Forum June 6, 2012 Energy consumption
More informationA bachelor of science degree in electrical engineering with a cumulative undergraduate GPA of at least 3.0 on a 4.0 scale
What is the University of Florida EDGE Program? EDGE enables engineering professional, military members, and students worldwide to participate in courses, certificates, and degree programs from the UF
More informationCloud Enabled Emergency Navigation Using Faster-than-real-time Simulation
Cloud Enabled Emergency Navigation Using Faster-than-real-time Simulation Huibo Bi and Erol Gelenbe Intelligent Systems and Networks Group Department of Electrical and Electronic Engineering Imperial College
More informationA Knowledge Management Framework Using Business Intelligence Solutions
www.ijcsi.org 102 A Knowledge Management Framework Using Business Intelligence Solutions Marwa Gadu 1 and Prof. Dr. Nashaat El-Khameesy 2 1 Computer and Information Systems Department, Sadat Academy For
More informationHow To Choose A Business Intelligence Toolkit
Background Current Reporting Challenges: Difficulty extracting various levels of data from AgLearn Limited ability to translate data into presentable formats Complex reporting requires the technical staff
More informationANALYTICS BUILT FOR INTERNET OF THINGS
ANALYTICS BUILT FOR INTERNET OF THINGS Big Data Reporting is Out, Actionable Insights are In In recent years, it has become clear that data in itself has little relevance, it is the analysis of it that
More informationHigh Resolution RF Analysis: The Benefits of Lidar Terrain & Clutter Datasets
0 High Resolution RF Analysis: The Benefits of Lidar Terrain & Clutter Datasets January 15, 2014 Martin Rais 1 High Resolution Terrain & Clutter Datasets: Why Lidar? There are myriad methods, techniques
More informationCenterMind G+ Smart and Proactive Environment Monitoring
CenterMind G+ Smart and Proactive Environment Monitoring Smart and Proactive Environment Monitoring real-time visibility into the state of your computer room or data center environment, 24/7 RiT CenterMind
More informationThe Challenge of Handling Large Data Sets within your Measurement System
The Challenge of Handling Large Data Sets within your Measurement System The Often Overlooked Big Data Aaron Edgcumbe Marketing Engineer Northern Europe, Automated Test National Instruments Introduction
More informationbigdata Managing Scale in Ontological Systems
Managing Scale in Ontological Systems 1 This presentation offers a brief look scale in ontological (semantic) systems, tradeoffs in expressivity and data scale, and both information and systems architectural
More informationA survey on Spectrum Management in Cognitive Radio Networks
A survey on Spectrum Management in Cognitive Radio Networks Ian F. Akyildiz, Won-Yeol Lee, Mehmet C. Vuran, Shantidev Mohanty Georgia Institute of Technology Communications Magazine, vol 46, April 2008,
More informationChristian Bettstetter. Mobility Modeling, Connectivity, and Adaptive Clustering in Ad Hoc Networks
Christian Bettstetter Mobility Modeling, Connectivity, and Adaptive Clustering in Ad Hoc Networks Contents 1 Introduction 1 2 Ad Hoc Networking: Principles, Applications, and Research Issues 5 2.1 Fundamental
More informationUniGR Workshop: Big Data «The challenge of visualizing big data»
Dept. ISC Informatics, Systems & Collaboration UniGR Workshop: Big Data «The challenge of visualizing big data» Dr Ir Benoît Otjacques Deputy Scientific Director ISC The Future is Data-based Can we help?
More informationNetView 360 Product Description
NetView 360 Product Description Heterogeneous network (HetNet) planning is a specialized process that should not be thought of as adaptation of the traditional macro cell planning process. The new approach
More informationInternet of Things (IoT): A vision, architectural elements, and future directions
SeoulTech UCS Lab 2014-2 st Internet of Things (IoT): A vision, architectural elements, and future directions 2014. 11. 18 Won Min Kang Email: wkaqhsk0@seoultech.ac.kr Table of contents Open challenges
More informationChapter 5 Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization
Turban, Aronson, and Liang Decision Support Systems and Intelligent Systems, Seventh Edition Chapter 5 Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization
More informationIn the pursuit of becoming smart
WHITE PAPER In the pursuit of becoming smart The business insight into Comarch IoT Platform Introduction Businesses around the world are seeking the direction for the future, trying to find the right solution
More informationMEng, BSc Computer Science with Artificial Intelligence
School of Computing FACULTY OF ENGINEERING MEng, BSc Computer Science with Artificial Intelligence Year 1 COMP1212 Computer Processor Effective programming depends on understanding not only how to give
More informationOptimization applications in finance, securities, banking and insurance
IBM Software IBM ILOG Optimization and Analytical Decision Support Solutions White Paper Optimization applications in finance, securities, banking and insurance 2 Optimization applications in finance,
More informationApp coverage. ericsson White paper Uen 284 23-3212 Rev B August 2015
ericsson White paper Uen 284 23-3212 Rev B August 2015 App coverage effectively relating network performance to user experience Mobile broadband networks, smart devices and apps bring significant benefits
More informationA! Aalto University Comnet
NETS2020 Project Task #2.3: Self-organization in Dynamic Networks Olav Tirkkonen, Jyri Hämäläinen 1 Content Subtask #2.3.1: Convergence of Distributed Network Algorithms: The project outcome Subtask #2.3.2:
More informationExploration and Visualization of Post-Market Data
Exploration and Visualization of Post-Market Data Jianying Hu, PhD Joint work with David Gotz, Shahram Ebadollahi, Jimeng Sun, Fei Wang, Marianthi Markatou Healthcare Analytics Research IBM T.J. Watson
More informationCognitive and Organizational Challenges of Big Data in Cyber Defense
Cognitive and Organizational Challenges of Big Data in Cyber Defense Nathan Bos & John Gersh Johns Hopkins University Applied Laboratory nathan.bos@jhuapl.edu, john.gersh@jhuapl.edu The cognitive and organizational
More informationSmart Infrastructure Emerging Trends and Future Opportunities. Tim Wark 7 May 2013
Smart Infrastructure Emerging Trends and Future Opportunities Tim Wark 7 May 2013 INTELLIGENT CITIES SUMMIT 2013 What is the future of our cities? Presentation title Presenter name Page 2 Image: Ilja Musik
More informationDATA CENTER INFRASTRUCTURE MANAGEMENT
THE nlyte SOLUTION nlyte Software was founded by data center professionals for data center professionals and is the independent provider of data center infrastructure Management (DCIM) solutions. The nlyte
More informationAdvanced Methods for Pedestrian and Bicyclist Sensing
Advanced Methods for Pedestrian and Bicyclist Sensing Yinhai Wang PacTrans STAR Lab University of Washington Email: yinhai@uw.edu Tel: 1-206-616-2696 For Exchange with University of Nevada Reno Sept. 25,
More informationHow to use Big Data in Industry 4.0 implementations. LAURI ILISON, PhD Head of Big Data and Machine Learning
How to use Big Data in Industry 4.0 implementations LAURI ILISON, PhD Head of Big Data and Machine Learning Big Data definition? Big Data is about structured vs unstructured data Big Data is about Volume
More informationBasic Principles of Inertial Navigation. Seminar on inertial navigation systems Tampere University of Technology
Basic Principles of Inertial Navigation Seminar on inertial navigation systems Tampere University of Technology 1 The five basic forms of navigation Pilotage, which essentially relies on recognizing landmarks
More informationMEng, BSc Applied Computer Science
School of Computing FACULTY OF ENGINEERING MEng, BSc Applied Computer Science Year 1 COMP1212 Computer Processor Effective programming depends on understanding not only how to give a machine instructions
More informationWhere is... How do I get to...
Big Data, Fast Data, Spatial Data Making Sense of Location Data in a Smart City Hans Viehmann Product Manager EMEA ORACLE Corporation August 19, 2015 Copyright 2014, Oracle and/or its affiliates. All rights
More informationEvent Processing Middleware for Wireless Sensor Networks
Event Processing Middleware for Wireless Sensor Networks Selvakennedy Selvadurai University of Sydney Outline Introduction System Assumptions EPM Architecture Group Management and Centre Localisation Components
More informationWorld Trade Analysis
World Trade Analysis Brendan Fruin brendan@cs.umd.edu Introduction With the vast amount of data being collected and made publicly available, individuals from all walks of life have been able to provide
More informationIRMA: Integrated Routing and MAC Scheduling in Multihop Wireless Mesh Networks
IRMA: Integrated Routing and MAC Scheduling in Multihop Wireless Mesh Networks Zhibin Wu, Sachin Ganu and Dipankar Raychaudhuri WINLAB, Rutgers University 2006-11-16 IAB Research Review, Fall 2006 1 Contents
More informationSECOND YEAR. Major Subject 3 Thesis (EE 300) 3 Thesis (EE 300) 3 TOTAL 3 TOTAL 6. MASTER OF ENGINEERING IN ELECTRICAL ENGINEERING (MEng EE) FIRST YEAR
MASTER OF SCIENCE IN ELECTRICAL ENGINEERING (MS EE) FIRST YEAR Elective 3 Elective 3 Elective 3 Seminar Course (EE 296) 1 TOTAL 12 TOTAL 10 SECOND YEAR Major Subject 3 Thesis (EE 300) 3 Thesis (EE 300)
More informationEvolution in Mobile Radio Networks
Evolution in Mobile Radio Networks Multiple Antenna Systems & Flexible Networks InfoWare 2013, July 24, 2013 1 Nokia Siemens Networks 2013 The thirst for mobile data will continue to grow exponentially
More informationCisco Context-Aware Mobility Solution: Put Your Assets in Motion
Cisco Context-Aware Mobility Solution: Put Your Assets in Motion How Contextual Information Can Drastically Change Your Business Mobility and Allow You to Achieve Unprecedented Efficiency What You Will
More informationDevelopment of Automatic shooting and telemetry system for UAV photogrammetry INTRODUCTION
Development of Automatic shooting and telemetry system for UAV photogrammetry Jinwoo PARK 1, Minseok KIM 1, Khin Mar Yee 1, Chuluong CHOI 1 1 Department of Spatial Information Engineering, Pukyong National
More informationA Noble Integrated Management System based on Mobile and Cloud service for preventing various hazards
, pp.166-171 http://dx.doi.org/10.14257/astl.205.98.42 A Noble Integrated Management System based on Mobile and Cloud service for preventing various hazards Yeo ChangSub 1, Ryu HyunKi 1 and Lee HaengSuk
More informationAdvanced Big Data Analytics with R and Hadoop
REVOLUTION ANALYTICS WHITE PAPER Advanced Big Data Analytics with R and Hadoop 'Big Data' Analytics as a Competitive Advantage Big Analytics delivers competitive advantage in two ways compared to the traditional
More informationCourse Curriculum for Master Degree in Electrical Engineering/Wireless Communications
Course Curriculum for Master Degree in Electrical Engineering/Wireless Communications The Master Degree in Electrical Engineering/Wireless Communications, is awarded by the Faculty of Graduate Studies
More informationIntroduction. Chapter 1. 1.1 Scope of Electrical Engineering
Chapter 1 Introduction 1.1 Scope of Electrical Engineering In today s world, it s hard to go through a day without encountering some aspect of technology developed by electrical engineers. The impact has
More informationINTRUSION PREVENTION AND EXPERT SYSTEMS
INTRUSION PREVENTION AND EXPERT SYSTEMS By Avi Chesla avic@v-secure.com Introduction Over the past few years, the market has developed new expectations from the security industry, especially from the intrusion
More informationCHAPTER 1 INTRODUCTION
CHAPTER 1 INTRODUCTION 1.1 Background The command over cloud computing infrastructure is increasing with the growing demands of IT infrastructure during the changed business scenario of the 21 st Century.
More informationRequirements Analysis Concepts & Principles. Instructor: Dr. Jerry Gao
Requirements Analysis Concepts & Principles Instructor: Dr. Jerry Gao Requirements Analysis Concepts and Principles - Requirements Analysis - Communication Techniques - Initiating the Process - Facilitated
More informationLIST OF FIGURES. Figure No. Caption Page No.
LIST OF FIGURES Figure No. Caption Page No. Figure 1.1 A Cellular Network.. 2 Figure 1.2 A Mobile Ad hoc Network... 2 Figure 1.3 Classifications of Threats. 10 Figure 1.4 Classification of Different QoS
More informationChapter 5. Warehousing, Data Acquisition, Data. Visualization
Decision Support Systems and Intelligent Systems, Seventh Edition Chapter 5 Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization 5-1 Learning Objectives
More informationTORNADO Solution for Telecom Vertical
BIG DATA ANALYTICS & REPORTING TORNADO Solution for Telecom Vertical Overview Last decade has see a rapid growth in wireless and mobile devices such as smart- phones, tablets and netbook is becoming very
More informationAutomated Data Acquisition & Analysis. Revolutionize Validation Testing & Launch With Confidence
Automated Data Acquisition & Analysis Revolutionize Validation Testing & Launch With Confidence Stop waiting for this... Pass Fail CONTROLTEC is leveraging 21st century technologies to enable customers
More informationSense Making in an IOT World: Sensor Data Analysis with Deep Learning
Sense Making in an IOT World: Sensor Data Analysis with Deep Learning Natalia Vassilieva, PhD Senior Research Manager GTC 2016 Deep learning proof points as of today Vision Speech Text Other Search & information
More informationA REMOTE HOME SECURITY SYSTEM BASED ON WIRELESS SENSOR NETWORK AND GSM TECHNOLOGY
A REMOTE HOME SECURITY SYSTEM BASED ON WIRELESS SENSOR NETWORK AND GSM TECHNOLOGY AIM: The main aim of this project is to implement Remote Home Security System Based on Wireless Sensor Network and GSM
More informationA Platform for Supporting Data Analytics on Twitter: Challenges and Objectives 1
A Platform for Supporting Data Analytics on Twitter: Challenges and Objectives 1 Yannis Stavrakas Vassilis Plachouras IMIS / RC ATHENA Athens, Greece {yannis, vplachouras}@imis.athena-innovation.gr Abstract.
More informationNew trend in Russian informatics curricula: integration of math and informatics
New trend in Russian informatics curricula: integration of math and informatics Svetlana Gaisina Academy of post-degree pedagogical education, Saint Petersburg, g.selania@gmail.com Sergei Pozdniakov Saint
More informationANALYTICS STRATEGY: creating a roadmap for success
ANALYTICS STRATEGY: creating a roadmap for success Companies in the capital and commodity markets are looking at analytics for opportunities to improve revenue and cost savings. Yet, many firms are struggling
More informationAn Implementation of Active Data Technology
White Paper by: Mario Morfin, PhD Terri Chu, MEng Stephen Chen, PhD Robby Burko, PhD Riad Hartani, PhD An Implementation of Active Data Technology October 2015 In this paper, we build the rationale for
More informationD A T A M I N I N G C L A S S I F I C A T I O N
D A T A M I N I N G C L A S S I F I C A T I O N FABRICIO VOZNIKA LEO NARDO VIA NA INTRODUCTION Nowadays there is huge amount of data being collected and stored in databases everywhere across the globe.
More informationVEHICLE TRACKING USING ACOUSTIC AND VIDEO SENSORS
VEHICLE TRACKING USING ACOUSTIC AND VIDEO SENSORS Aswin C Sankaranayanan, Qinfen Zheng, Rama Chellappa University of Maryland College Park, MD - 277 {aswch, qinfen, rama}@cfar.umd.edu Volkan Cevher, James
More informationSTMicroelectronics is pleased to present the. SENSational. Attend a FREE One-Day Technical Seminar Near YOU!
SENSational STMicroelectronics is pleased to present the SENSational Seminar Attend a FREE One-Day Technical Seminar Near YOU! Seminar Sensors and the Internet of Things are changing the way we interact
More informationDevelopment of Integrated Management System based on Mobile and Cloud Service for Preventing Various Hazards
, pp. 143-150 http://dx.doi.org/10.14257/ijseia.2015.9.7.15 Development of Integrated Management System based on Mobile and Cloud Service for Preventing Various Hazards Ryu HyunKi 1, Yeo ChangSub 1, Jeonghyun
More informationWAITER: A Wearable Personal Healthcare and Emergency Aid System
Sixth Annual IEEE International Conference on Pervasive Computing and Communications WAITER: A Wearable Personal Healthcare and Emergency Aid System Wanhong Wu 1, Jiannong Cao 1, Yuan Zheng 1, Yong-Ping
More informationTOPOLOGIES NETWORK SECURITY SERVICES
TOPOLOGIES NETWORK SECURITY SERVICES 1 R.DEEPA 1 Assitant Professor, Dept.of.Computer science, Raja s college of Tamil Studies & Sanskrit,Thiruvaiyaru ABSTRACT--In the paper propose about topology security
More informationThermal Management of Datacenter
Thermal Management of Datacenter Qinghui Tang 1 Preliminaries What is data center What is thermal management Why does Intel Care Why Computer Science 2 Typical layout of a datacenter Rack outlet temperature
More informationBig Data Text Mining and Visualization. Anton Heijs
Copyright 2007 by Treparel Information Solutions BV. This report nor any part of it may be copied, circulated, quoted without prior written approval from Treparel7 Treparel Information Solutions BV Delftechpark
More informationLNG Monitoring. Fiber-Optic Leakage Detection System. Pipeline leakage detection. Regasification and liquefaction monitoring
LNG Monitoring Fiber-Optic Leakage Detection System Pipeline leakage detection Regasification and liquefaction monitoring Tank annulus and base slab monitoring Spill containment control Intelligent Solutions
More informationNext Generation Business Performance Management Solution
Next Generation Business Performance Management Solution Why Existing Business Intelligence (BI) Products are Inadequate Changing Business Environment In the face of increased competition, complex customer
More informationTowards Elastic Application Model for Augmenting Computing Capabilities of Mobile Platforms. Mobilware 2010
Towards lication Model for Augmenting Computing Capabilities of Mobile Platforms Mobilware 2010 Xinwen Zhang, Simon Gibbs, Anugeetha Kunjithapatham, and Sangoh Jeong Computer Science Lab. Samsung Information
More informationIncident Reporting & Management
Rivo Software Solution Layer allows you to report and manage incidents such as injuries, accidents and theft. With powerful capabilities including analytical trending you can make better decisions to reduce
More informationDevelopment of Integrated Management System based on Mobile and Cloud service for preventing various dangerous situations
Development of Integrated Management System based on Mobile and Cloud service for preventing various dangerous situations Ryu HyunKi, Moon ChangSoo, Yeo ChangSub, and Lee HaengSuk Abstract In this paper,
More informationMedial Axis Construction and Applications in 3D Wireless Sensor Networks
Medial Axis Construction and Applications in 3D Wireless Sensor Networks Su Xia, Ning Ding, Miao Jin, Hongyi Wu, and Yang Yang Presenter: Hongyi Wu University of Louisiana at Lafayette Outline Introduction
More informationUnique Visualization and Management Capabilities Deliver Superior Wireless Network Reliability
SOLUTION PAPER Unique Visualization and Management Capabilities Deliver Superior Wireless Network Reliability The Motorola One Point Wireless Suite s management tools leverage innovative real-time visualization
More informationUsing Business Intelligence to Mitigate Graduation Delay Issues
Using Business Intelligence to Mitigate Graduation Delay Issues Khaled Almgren PhD Candidate Department of Computer science and Engineering University of Bridgeport Abstract Graduate master students usually
More informationEnterprise IT Solutions (Hardware, Software, Services) Shared Services and Outsourcing Technology Products Distribution and Trading
Enterprise IT Solutions (Hardware, Software, Services) Shared Services and Outsourcing Technology Products Distribution and Trading Enterprise Solution Professionals on Information and Network E-SPIN carry
More informationInternet of Things: IoT Day Special Edition
Table of Contents Executive Summary..1 Introduction...2 Stack Layers in Internet of Things...4 Trends..5 Assignee-wise technology distribution. 8 Appendix...9 Executive Summary Internet of Things (IoT)
More informationAbstract. Cycle Domain Simulator for Phase-Locked Loops
Abstract Cycle Domain Simulator for Phase-Locked Loops Norman James December 1999 As computers become faster and more complex, clock synthesis becomes critical. Due to the relatively slower bus clocks
More informationRESEARCH ON THE FRAMEWORK OF SPATIO-TEMPORAL DATA WAREHOUSE
RESEARCH ON THE FRAMEWORK OF SPATIO-TEMPORAL DATA WAREHOUSE WANG Jizhou, LI Chengming Institute of GIS, Chinese Academy of Surveying and Mapping No.16, Road Beitaiping, District Haidian, Beijing, P.R.China,
More information