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Universal image steganalysis against spatial-domain steganography based on energy distribution of singular values

Universal image steganalysis against spatial-domain steganog...

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7th International Conference on Information Technology and Application, ICITA 2011

作者： Shojaei-Hashemi, Anahita Soltanian-Zadeh, Hamid Ghaemmagham, Shahrokh Kamarei, Mahmoud School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Image Analysis Laboratory Department of Radiology Henry Ford Health System Detroit MI United States Electronics Research Institute Sharif University of Technology Tehran Iran

ISBN: (纸本)9780980326741

A passive image steganalysis method is proposed to universally detect spatial-domain steganography schemes. It is shown to have better performance than universal steganalyzers known to be powerful in spatial domain, including the WFLogSv and the WAM methods. This level of accuracy is the result of improving the WFLogSv steganalyzer by considering a more comprehensive relationship between the singular values of each image block and the linear correlation of the rows and the columns. That is, instead of the closeness of the lower singular values to zero, the energy distribution of the singular values is investigated. An innovative measure is proposed for this investigation, which is inspired from arithmetic mean-geometric mean inequality. Experimental results confirm the supremacy of the proposed steganalysis scheme over its counterparts.

关键词： Singular value decomposition

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Universal steganalysis based on local prediction error in wavelet domain

Universal steganalysis based on local prediction error in wa...

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7th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIHMSP 2011

作者： Shojaei-Hashemi, Anahita Mehdipour-Ghazi, Mostafa Ghaemmaghami, Shahrokh Soltanian-Zadeh, Hamid School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Electronics Research Institute Sharif University of Technology Tehran Iran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Image Analysis Laboratory Department of Radiology Henry Ford Health System Detroit MI United States

ISBN: (纸本)9780769545172

A passive universal image steganalysis method is proposed that is shown to be of higher detection accuracy than existing truly blind steganalysis methods including Farid's and the WAM. This is achieved by improving some weaknesses of Farid's steganalysis scheme in feature extraction, that is, instead of deriving an over-determined equation system for each sub band of the wavelet decomposition, the sub bands are divided into overlapping blocks and an over-determined equation system is constructed for each block. To guarantee the existence of finite answers, the over-determined equation systems are solved in a way different from Farid's by using Moore-Penrose pseudo-inverse concept. Further improvement to the performance is achieved by adding diagonal directions and increasing the number of moments. The comparative evaluations confirm the superiority of the proposed method over prevalent blind steganalysis schemes. © 2011 IEEE.

关键词： Wavelet decomposition

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B-splines and pseudo-inversion as tools for handling saturation constraints in the optimal set-point regulation

B-splines and pseudo-inversion as tools for handling saturat...

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American control Conference

作者： Leopoldo Jetto Valentina Orsini Raffaele Romagnoli Department of Information Engineering University Politecnica delle Marche Ancona Italy Control Engineering and System Analysis (SAAS) Universite Libre de Bruxelles (ULB) Belgium

ISBN: (纸本)9781509045839

This paper deals with the optimal output transition problem under saturation constraints on the control effort. The recently proposed pseudo inversion approach is here adopted to define a feedforward action optimizing the set-point following response of a given stable closed-loop system Σ_(f,c). To take into account saturating actuators, the optimal external input reference r(t) forcing Σ_(f,c) is assumed to be given by a B-spline function. The actual control input u(t) yielded by r(t) and forcing the plant is optimally approximated by a B-spline u(t), whose control points u(t) are chosen in such a way to satisfy the saturation constraints on u(t). If u(t) is a sufficiently accurate approximation of u(t), the exact fulfillment of saturation constraints by u(t) are transferred to u(t). The simulations on a practical case show excellent results.

关键词： Model pseudo-inversion feed-forward control Constrained control B-splines

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Automatic segmentation of brain tumors in magnetic resonance images

Automatic segmentation of brain tumors in magnetic resonance...

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IEEE-EMBS International Conference on Biomedical and Health Informatics, BHI 2012. In Conj. with the 8th Int. Symp.on Medical Devices and Biosensors and the 7th Int. Symp. on Biomedical and Health engineering

作者： Behzadfar, Neda Soltanian-Zadeh, Hamid Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran 14395-515 Iran Pooyandegan Rah Saadat Company Tehran 16756-965 Iran Image Analysis Laboratory Radiology Department HenryFord Healh System Detroit MI 48202 United States

ISBN: (纸本)9781457721779

Segmentation of tumors in magnetic resonance images (MRI) is an important task but is quite time consuming when performed manually by experts. Automating this process is challenging due to the high diversity in appearance of tumor tissue in different patients, and in many cases, similarity between tumor and normal tissues. This paper presents an automatic method for segmentation of brain tumors in MRI. We use images of patients with glioblastoma multiform tumors. After pre-processing and removal of the regions that do not have useful information (e.g., eyes and scalp), we create a projection image for determining the primary location of the tumor. This image provides an overall view of the tumor. Then, we grow the primary region to segment the entire tumor. This method is automatic and independent of the operator. It segments low contrast tumors without requiring their exacta tissue boundaries. The segmentation results obtained by the proposed approach are compared with those of an expert radiologist showing excellent correlations among them (R2=0.97). © 2012 IEEE.

关键词： Tumors

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A new scheme for evaluation of air-trapping in CT images

A new scheme for evaluation of air-trapping in CT images

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Iranian Conference on Machine Vision and Image Processing

作者： Hosseini, M. Parsa Soltanian-Zadeh, Hamid Akhlaghpoor, Shahram Behrad, Alireza Department of Electrical Engineering Science and Research Branch Islamic Azad University Tehran Iran Image Analysis Laboratory Radiology Department Henry Ford Health System Detroit MI United States Control and Intelligent Processing Center of Excellence University of Tehran Tehran Iran Department of Radiology Tehran University of Medical Science Sina Hospital Tehran Iran Department of Electrical Engineering Shahed University Tehran Iran

ISBN: (纸本)9781424497065

Air trapping is an abnormal retention of air that occurs after expiration state in the lungs, observed in all types of bronchiolar and obstructive lung diseases such as chronic obstructive pulmonary disease (COPD), asthma, and bronchiolitis obliterans syndrome. Air trapping is often incidentally diagnosed on computed tomography (CT) scanning but this method needs doctors so it is subjective and depends on their experience. In this paper, we present a novel method for evaluation of air trapping in the lungs for detection of COPD in CT images. The proposed method finds volumetric variations of the lungs from inspiration to expiration. To this end, trachea CT images at full inspiration and expiration are compared and the volumetric variations are used to classify the subjects. In the evaluated cases, the proposed method is able to estimate air trapping in the lungs from CT images without human intervention. This method may assist radiologists to measure and evaluate air trapping for detection of COPD as a computer aided diagnosis (CAD) system. © 2010 IEEE.

关键词： Computerized tomography

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Assessing lung volumetric variation to detect and stage COPD

Assessing lung volumetric variation to detect and stage COPD

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2011 1st Middle East Conference on Biomedical engineering, MECBME 2011

作者： Hosseini, M. Parsa Soltanian-Zadeh, Hamid Akhlaghpoor, Shahram Department of Electrical Engineering Islamic Azad University Science and Research Branch of Tehran Tehran Iran Image Analysis Laboratory Department of Radiology Henry Ford Health System Detroit MI United States Department of Radiology Tehran University of Medical Sciences Sina Hospital Tehran Iran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran

ISBN: (纸本)9781424470006

Chronic obstructive pulmonary disease (COPD) is a devastating disease. In this paper, we propose a novel method for scoring of air trapping in the lungs for detection and evaluation of COPD. The proposed method finds volumetric changes of the lungs from inspiration to expiration. To this end, trachea CT images at full inspiration and expiration are compared. For this comparison, the lungs parenchyma in the inspiration and expiration images are found and changes in the surface and volume of the lungs between inspiration and expiration are used to define quantitative measures (features). Using these features, the subjects are classified into two groups of normal class and COPD patients using a Bayesian classifier. In addition, t-tests are applied to evaluate discrimination powers of the features for this classification. The main advantage of the proposed method is its ability to estimate air trapping in the lungs from CT images without human intervention. The proposed method may assists radiologists in the detection of COPD as a computer aided diagnosis (CAD) system. It may also assist them with the scoring of the disease (severity of air trapping in the lungs). © 2011 IEEE.

关键词： Computerized tomography

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STABLE: A new QF-BV SMT solver for hard verification problems combining Boolean reasoning with computer algebra

STABLE: A new QF-BV SMT solver for hard verification problem...

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Design, Automation and Test in Europe Conference and Exhibition

作者： Evgeny Pavlenko Markus Wedler Dominik Stoffel Wolfgang Kunz Alexander Dreyer Frank Seelisch Gert-Martin Greuel Department of Electrical and Computer Engineering University of Kaiserslautern Germany Department of System Analysis Prognosis and Control Fraunhofer ITWM Kaiserslautern Germany Department of Mathematics University of Kaiserslautern Germany

This paper presents a new SMT solver, STABLE, for formulas of the quantifier-free logic over fixed-sized bit vectors (QF-BV). The heart of STABLE is a computer-algebra-based engine which provides algorithms for simplifying arithmetic problems of an SMT instance prior to bit-blasting. As the primary application domain for STABLE we target an SMT-based property checking flow for system-on-Chip (SoC) designs. When verifying industrial data path modules we frequently encounter custom-designed arithmetic components specified at the logic level of the hardware description language being used. This results in SMT problems where arithmetic parts may include non-arithmetic constraints. STABLE includes a new technique for extracting arithmetic bit-level information for these non-arithmetic constraints. Thus, our algebraic engine can solve subproblems related to the entire arithmetic design component. STABLE was successfully evaluated in comparison with other state-of-the-art SMT solvers on a large collection of SMT formulas describing verification problems of industrial data path designs that include multiplication. In contrast to the other solvers STABLE was able to solve instances with bit-widths of up to 64 bits.

关键词： Polynomials Mathematical model system-on-a-chip Adders Engines Algebra

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A novel method for identification of COPD in inspiratory and expiratory states of CT images

A novel method for identification of COPD in inspiratory and...

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2011 1st Middle East Conference on Biomedical engineering, MECBME 2011

ISBN: (纸本)9781424470006

Chronic obstructive pulmonary disease (COPD) refers to a group of lung diseases that block airflow and cause a huge degree of human suffering. While there is no cure for COPD and the lung damage that results in this disease cannot be reversed, it is very important to diagnose it as early as possible. Additional to diagnosis, using a mathematical model to estimate severity of disease would be helpful for evaluation of treatment effects. This paper presents a new method for identifying COPD from three-dimensional (3-D) pulmonary X-ray CT images. The method has five main steps. First, corresponding positions of lungs in inspiration and expiration are found based on anatomical structures. Then, lung regions are segmented from the CT images by active contours. Next, the left and right lungs are separated using a sequence of morphological operations. Then, parenchyma variations in each lung are found as a relationship between inspiratory and expiratory states. Finally, a classifier is used to decide about the disease and its severity. A t-test is done to evaluate the results. Twelve patients with variable severity of COPD and twelve normal adults were included in this study. The proposed method may assist radiologists in the detection of COPD as a computer aided diagnosis (CAD) system. © 2011 IEEE.

关键词： Pulmonary diseases

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Data-driven Model Based Online Fault Detection Using OMP-ERR 4

Data-driven Model Based Online Fault Detection Using OMP-ERR

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4th International Conference on Industrial Artificial Intelligence, IAI 2022

作者： Zhou, Guangze Luo, Zhong Zhu, Yunpeng Gao, Yi Wang, Zhiao Northeastern University School of Mechanical Engineering and Automation Shenyang110819 China Northeastern University Key Laboratory of Vibration and Control of Aero-Propulsion Systems Ministry of Education of China Shenyang110819 China Dalian University of Technology State Key Laboratory of Structural Analysis for Industrial Equipment Dalian116024 China University of Sheffield Department of Automatic Control and System Engineering SheffieldS13JD United Kingdom

ISBN: (数字)9781665451208

ISBN: (纸本)9781665451208

Model based online fault detection often conducted by extracting features from models driven by system input and output data under various working conditions. The efficiency of online system modelling is therefore significant to improve the performance of online fault detections. In this study, a novel fast data-driven modelling approach, known as the OMP (Orthogonal Matching Pursuit)- ERR (Error Reduction Ratio) method is proposed to improve the efficiency of online fault detections. The new system identification method is motivated by noticing that the traditional OMP algorithm is much faster but usually less accurate than the OLS (Orthogonal least squares) algorithm in the identification of system NARX (Nonlinear Auto-Regressive with Exogenous inputs) models. The problem is first illustrated by the identification of a Single Degree of Freedom (SDoF) system. After that, the OMP-ERR algorithm is developed to improve the NARX modelling efficiency for the purpose of system model-based online fault detections. A case study on the crack detection of a cantilever beam shows that the new approach is over 10 times faster than the traditional OLS modelling process, demonstrating the promising applications of the new approach in online fault detections in engineering practice. © 2022 IEEE.

关键词： Least squares approximations

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Fog-Cloud-IoT Enabled WSN Architecture 3

Fog-Cloud-IoT Enabled WSN Architecture

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3rd International Conference on Intelligent engineering and Management, ICIEM 2022

作者： Anitha Christy Angelin, P. Samuel Devakumar, P.V. Al-Farhani, Liwa H. Kumar, Gandam Vijay Deep, Shaurya Mohammad, Shoaib PSNA College of Engineering and Technology Tamilnadu Dindigul India Karunya Institute of Technology and Sciences Tamilnadu Coimbatore India RUDN University System Analysis Control and Information Processing Academy of Engineering Moscow Russia Career Point University Computer Science and Engineering Rajasthan India IIMT College of Management Greater Noida India IMS Unison University Department of Law Uttarakhand Dehradun India

ISBN: (数字)9781665467568

ISBN: (纸本)9781665467568

Remote Because of the exciting innovation it introduces, the WSN likely to be a subject of research in recent time. Because of the impromptu distant connections, adaptability, and simplicity of execution, this has all the makings of becoming the most maintainable innovation for ecological detecting, whether it's about limited or huge scope watching. In any case, the main drawbacks stem from the limited capacity, processing, and accessibility of organization centers for information. Virtual machines resources have been adopted to overcome such constraints, devices to expanded capacity, computation, and easy-to-understand availability. This was a natural progression from traditional WSN designs among pattern in recent theories evolved along advent of Internet-of-Things advancements. Against the growing popularity of WSN associated cloud checking frameworks, still the issues are detected because of the distributed comp ting's disadvantages, like dormancy with the capacity charges. In this paper, the advancements achieved to a fog-cloud-IoT associated with WSN architecture of putting a bit of computing at the network part are elaborated, a process, which follows the smart Fog associated with Cloud-computing concept of dissecting also following up on IoT data. A similar investigation was carried out to illustrate the improvements made possible by processing at the organization's edge. © 2022 IEEE.

关键词： Fog computing

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