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16th Symposium on Network and Distributed System Security, NDSS 2009

作者： Houmansadr, Amir Kiyavash, Negar Borisov, Nikita Dept. of Electrical and Computer Engineering University of Illinois at Urbana–Champaign United States Dept. of Industrial and Enterprise Systems Engineering University of Illinois at Urbana–Champaign United States

Linking network flows is an important problem in intrusion detection as well as anonymity. Passive traffic analysis can link flows but requires long periods of observation to reduce errors. Watermarking techniques allow for better precision and blind detection, but they do so by introducing significant delays to the traffic flow, enabling attacks that detect and remove the mark, while at the same time slowing down legitimate traffic. We propose a new, non-blind watermarking scheme called RAINBOW that is able to use delays hundreds of times smaller than existing watermarks by eliminating the interference caused by the flow in the blind case. As a result, our watermark is invisible to detection, as confirmed by experiments using information-theoretic detection tools. We analyze the error rates of our scheme based on a mathematical model of network traffic and jitter. We also validate the analysis using an implementation running on PlanetLab. We find that our scheme generates orders of magnitudes lower rates of false errors than passive traffic analysis, while using only a few hundred observed packets. We also extend our scheme so that it is robust to packet drops and repacketization and show that flows can still be reliably linked, though at the cost of somewhat longer observation periods. © 2009 Proceedings of the Symposium on Network and Distributed System Security, NDSS 2009. All Rights Reserved.

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Biomedical Osteosarcoma Image Classification Using Elephant Herd Optimization and Deep Learning

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computers, Materials & Continua 2022年第12期73卷 6443-6459页

作者： Areej A.Malibari Jaber S.Alzahrani Marwa Obayya Noha Negm Mohammed Abdullah Al-Hagery Ahmed S.Salama Anwer Mustafa Hilal Department of Industrial and Systems Engineering College of EngineeringPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversitySaudi Arabia Department of Biomedical Engineering College of EngineeringPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Faculty of Science Mathematics and Computer Science DepartmentMenoufia UniversityEgypt Department of Computer Science College of ComputerQassim UniversitySaudi Arabia Department of Electrical Engineering Faculty of Engineering&TechnologyFuture University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam Bin Abdulaziz UniversityAlKharjSaudi Arabia

Osteosarcoma is a type of malignant bone tumor that is reported across the *** advancements in Machine Learning(ML)and Deep Learning(DL)models enable the detection and classification of malignancies in biomedical *** this regard,the current study introduces a new Biomedical Osteosarcoma Image Classification using Elephant Herd Optimization and Deep Transfer Learning(BOIC-EHODTL)*** presented BOIC-EHODTL model examines the biomedical images to diagnose distinct kinds of *** the initial stage,Gabor Filter(GF)is applied as a pre-processing technique to get rid of the noise from *** addition,Adam optimizer with MixNet model is also employed as a feature extraction technique to generate feature ***,EHOalgorithm is utilized along with Adaptive Neuro-Fuzzy Classifier(ANFC)model for recognition and categorization of *** algorithm is utilized to fine-tune the parameters involved in ANFC model which in turn helps in accomplishing improved classification *** design of EHO with ANFC model for classification of osteosarcoma is the novelty of current *** order to demonstrate the improved performance of BOIC-EHODTL model,a comprehensive comparison was conducted between the proposed and existing models upon benchmark dataset and the results confirmed the better performance of BOIC-EHODTL model over recent methodologies.

关键词： Biomedical imaging osteosarcoma classification deep transfer learning parameter tuning fuzzy logic

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Secure SCADA communication network for detecting and preventing cyber-attacks on power systems

Secure SCADA communication network for detecting and prevent...

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Clemson University Power systems Conference, PSC 2016

作者： Chalamasetty, Goutham K. Mandal, Paras Tseng, Tzu-Liang Bill Department of Electrical and Computer Engineering University of Texas at El Paso 79968 United States Department of Industrial Manufacturing and Systems Engineering University of Texas at El Paso 79968 United States

ISBN: (纸本)9781509006878

This paper presents a scaled model for supervisory control and data acquisition (SCADA) communication network, which monitors and controls power distribution in residential areas. We recommend to integrate advanced communication technologies into current SCADA system to improve its performance in monitoring and controlling the operations of the power systems. This paper further proposes to use ad hoc wireless sensor networks in the residential areas as a part of SCADA communication in power distribution network. Moreover, a trust-based intrusion detection and prevention (IDP) technology built on monitoring, detecting, and rehabilitation (MDR) approach is applied to the proposed network for cyber security analysis. To verify the performance of the proposed SCADA communication network using MDR, simulation is carried out for three different cases and results demonstrate that the proposed MDR approach helps in detecting and preventing the malicious nodes in the network effectively. © 2016 IEEE.

关键词： Network security

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Quadratic MPC with 0-input constraint 19

Quadratic MPC with 0-input constraint

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19th IFAC World Congress on International Federation of Automatic Control, IFAC 2014

作者： Aguilera, Ricardo P. Delgado, Ramón Dolz, Daniel Agüero, Juan C. University of New South Wales Australia School of Electrical Engineering and Computer Science University of Newcastle Australia Department of Industrial Systems Engineering and Design Universitat Jaume I Castelló Spain

ISBN: (纸本)9783902823625

In this paper we propose a novel quadratic model predictive control technique that constrains the number of active inputs at each control horizon instant. This problem is known as sparse control. We use an iterative convex optimization procedure to solve the corresponding optimization problem subject to sparsity constraints defined by means of the 0-norm. We also derive a sufficient condition on the minimum number of active of inputs that guarantees the exponential stability of the closed-loop system. A simulation example illustrates the benefits of the control design method proposed in the paper. © IFAC.

关键词： Iterative methods

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Enhancing engineering outreach with interactive game assessment

Enhancing engineering outreach with interactive game assessm...

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113th Annual ASEE Conference and Exposition, 2006

作者： Lyons, Leilah Pasek, Zbigniew University of Michigan United States Dept. of Electrical Engineering and Computer Science University of Michigan United States Dept. of Industrial and Manufacturing Systems Engineering University of Windsor Canada

The need to educate general public about technology grows with broadening gap between technology use and its understanding in a consumer society. One of the effective venues for such education is that of hands-on museums, which engage a wide spectrum of visitors. This paper reports on the use of a data collection mechanism embedded in an interactive museum exhibit that highlights principles of modern consumer product engineering. The exhibit is comprised of a set of computer games and complementary physical displays. The games have a built-in data collection system tracking users' actions while playing the game. Collected data allows for demographic analysis of visitor population, user performance assessment, and provides game-play perspective useful for effective game design. Presented results are based on a year-long study involving about 17,000 museum visitors. © American Society for engineering Education, 2006.

关键词： Animation

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Optimizing natural gas supply and energy portfolios of a generation company

Optimizing natural gas supply and energy portfolios of a gen...

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2010 IEEE 11th International Conference on Probabilistic Methods Applied to Power systems, PMAPS 2010

作者： Kittithreerapronchai, Oran Jirutitijaroen, Panida Kim, Sujin Prina, José Department of Electrical and Computer Engineering National University of Singapore Singapore 117576 Singapore Department of Industrial and Systems Engineering Pontificia Universidad Católica de Chile Santiago 7820436 Chile

ISBN: (纸本)9781424457236

In a deregulated electricity market environment, a natural gas-fired generation company must manage its natural gas supply and construct energy portfolios by engaging in contracts to buy natural gas and generate electricity. The contracts protect the company from fluctuations in prices and demands, but provide minimal profits. The company may gain larger profits - and possible loses- by accessing natural gas spot and electricity pool markets. To capture such hedging decisions and the interactions between the natural gas and electricity markets, we formulate a Stochastic Programming model and study its benefits over an expected value problem. The stochastic model enables the company to optimize the electricity generation schedule and the natural gas consumption as well as to develop managerial insights. © 2010 IEEE.

关键词： Stochastic programming

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A generalized prediction framework for granger causality

A generalized prediction framework for granger causality

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2011 IEEE Conference on computer Communications Workshops, INFOCOM WKSHPS 2011

作者： Quinn, Christopher J. Coleman, Todd P. Kiyavash, Negar Department of Electrical and Computer Engineering University of Illinois Urbana IL 61801 United States Department of Industrial and Enterprise Systems Engineering University of Illinois Urbana IL 61801 United States

ISBN: (纸本)9781457702488

In his 1969 paper, Granger proposed a statistical definition of causality between stochastic processes. It is based on whether causal side information helps in a sequential prediction task. However, his formulation was limited to linear predictors. We describe a generalized framework, where predictions are beliefs and compare the best predictor with side information to the best predictor without side information. The difference in the prediction performance, i.e., regret of such predictors, is used as a measure of causal influence of the side information. Specifically when log loss is used to quantify each predictor's loss and an expectation over the outcomes is used to quantify the regret, we show that the directed information, an information theoretic quantity, quantifies Granger causality. We also explore a more pessimistic setup perhaps better suited for adversarial settings where minimax criterion is used to quantify the regret. © 2011 IEEE.

关键词： Forecasting

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Supervisory control of software execution for failure avoidance: Experience from the Gadara project

Supervisory control of software execution for failure avoida...

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作者： Wang, Yin Cho, Hyoun Kyu Liao, Hongwei Nazeem, Ahmed Kelly, Terence P. Lafortune, Stéphane Mahlke, Scott Reveliotis, Spyros A. Hewlett-Packard Laboratories United States Department of Electrical Engineering and Computer Science University of Michigan United States School of Industrial and Systems Engineering Georgia Institute of Technology United States

ISBN: (纸本)9783902661791

We discuss our experience in the Gadara project, whose objective is to control the execution of software to avoid potential failures using discrete-event control techniques. We summarize our accomplishments so far and discuss future challenges. After initial work on safety of workflow scripts via supervisory control techniques, we have focused our efforts on deadlock avoidance in multithreaded C programs that use locking primitives to control access to shared data. We describe how we automatically construct automata models of workflows and Petri net models of concurrent programs. In the case of multithreaded C programs, the resulting models characterize a new class of resource-allocation Petri nets called Gadara nets. These nets enjoy structural properties that facilitate the synthesis of liveness-enforcing control policies that are maximally-permissive. We describe our strategy for run-time implementation of these control policies, especially by a technique known as code instrumentation. It is hoped that the lessons learned so far in the Gadara project will be useful in other application areas and will suggest avenues for future theoretical investigations.

关键词： Petri nets

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Approximating discrete probability distributions with causal dependence trees

Approximating discrete probability distributions with causal...

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2010 20th International Symposium on Information Theory and Its Applications, ISITA 2010 and the 2010 20th International Symposium on Spread Spectrum Techniques and Applications, ISSSTA 2010

ISBN: (纸本)9781424460175

Chow and Liu considered the problem of approximating discrete joint distributions with dependence tree distributions where the goodness of the approximations were measured in terms of KL distance. They (i) demonstrated that the minimum divergence approximation was the tree with maximum sum of mutual informations, and (ii) specified a low-complexity minimum-weight spanning tree algorithm to find the optimal tree. In this paper, we consider an analogous problem of approximating the joint distribution on discrete random processes with causal, directed, dependence trees, where the approximation is again measured in terms of KL distance. We (i) demonstrate that the minimum divergence approximation is the directed tree with maximum sum of directed informations, and (ii) specify a low-complexity minimum weight directed spanning tree, or arborescence, algorithm to find the optimal tree. We also present an example to demonstrate the algorithm. © 2010 IEEE.

关键词： Random processes

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Fuzzy Logic Enabled Stress Detection Using Physiological Signals 4th

Fuzzy Logic Enabled Stress Detection Using Physiological Sig...

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4th International Conference on Emerging Technologies in Computing, iCEtiC 2021

作者： Naqvi, Shabbar Shaikh, Aamir Zeb Altaf, Talat Singh, Saurabh Department of Computer Systems Engineering Balochistan University of Engineering and Technology Khuzdar Pakistan Department of Electronic Engineering NED University of Engineering and Technology Karachi Karachi Pakistan Department of Electrical Engineering Sir Syed University of Engineering and Technology Karachi Pakistan Department of Industrial and Systems Engineering Dongguk University Seoul Seoul Korea Republic of

ISBN: (纸本)9783030900151

Stress is attributed as the natural response of body towards unwanted and challenging conditions of society and environment. The consequences of stress are in general very harmful. However, in some specific situations, stress can be highly serious to the human health as it impacts the cardiovascular system in addition to other body sub systems. Timely Detection of stress through physiological sensors may help in arresting the disease. As the stress results in change of heart rate, skin conduction, temperature, blood pressure and oxygen levels, hence, measurement and assessment of these parameters is useful in deciding the stress levels into a candidate. In this paper, a fuzzy logic based automatic stress detection system is designed to timely detect the patients passing through this silent killer disease. The physiological signals of human body are used to assess the current state of person. The parameters used for the purpose are heart rate, Galvanic Skin Response (GSR), and temperature. The fuzzy logic is an exciting branch of artificial intelligence that is used to make useful decisions under uncertain and incomplete input knowledge. A synthetic data set of 500 patients is also developed to train and test the proposed architecture. The algorithms used for this purpose are Hill Climbing (HC) and Simulated Annealing (SA) for fuzzy membership functions training. The results show that Simulated Annealing gives a testing accuracy of 89% in comparison to Hill climbing with 81% accuracy. Future work is directed towards using new methods like type-2 fuzzy logic and deep learning etc. © 2021, ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Fuzzy logic

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