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Analysis and Computation of Encryption Technique to Enhance Security of Medical Images

IOP Conference Series: Materials Science and engineering 2020年第1期925卷

作者： Kiran BD Parameshachari HT Panduranga Silvia liberata Ullo VTU Belagaum India. Department of ECE Vidyavardhaka College of Engineering Mysuru India. Department of TCE GSSSIETW Mysuru India. Department of ECE Govt. Polytechnic Turvekere Tumkur India. Engineering Department University of Sannio Italy.

Recently, there are many advanced techniques used in the medical fields, such as smart health, e-health and telemedicine applications. These techniques rely on open source networks to transmit the digital medical images. These images have very sensitive and confidential information about the patients. Regrettably, most of the regularly used algorithms provide very less security and present a high communication overhead, with high computation costs. Due to these issues, a Region of Interest (ROI) method, based on selective image encryption, is proposed in this paper. An active contour image segmentation is first used to divide the ROI and the Region of Background (ROB). Then, a Hilbert curve, with a Skew Tent map are used to implement the Permutation and diffusion techniques. Namely, the ROI part is permuted according to a Hilbert scan pattern, to decrease the similarities between the inside adjacent pixels. Then pixels in the permuted ROI part are XOR pixel-wise with random numbers, generated based on a predefined threshold value from a Skew Tent map. Finally, encrypted ROI and ROB blocks are combined to generate encrypted images. Given the obtained experimental results, the proposed method is very likely to improve image security, through the employment of correlation checking, key sensitivity, entropy, diffusion characteristic and histogram tools.

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Corrigendum for “Review—Latest Trends and Advancement in Porous Carbon for Biowaste Organization and Utilization” ECS J. Solid State Sci. Technol. 11 011003 2022

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ECS Journal of Solid State Science and Technology 2023年第11期12卷 119001-119001页

作者： Kunal Kulkarni Utkarsh Chadha Shreya Yadav D. M. Tarun K. G. Thenmukilan Preetam Bhardwaj Shalu Singh Arghya Chakravorty Chirag Ahuja Srinivasan Latha Arun Kumar Ray Badrish Badoni Nalamala Srinivasa Rao Charanjeet Madan Murali Banavoth Prashant Sonar Department of Analytics School of Computer Science and Engineering (SCOPE) Vellore Institute of Technology Vellore Tamil Nadu-632014 India Department of manufacturing School of Mechanical Engineering (SMEC) Vellore Institute of Technology Vellore Tamil Nadu-632014 India School of Bio Sciences & Technology (SBST) Vellore Institute of Technology Vellore Tamil Nadu-632014 India School of Engineering Presidency University Bengaluru-560064 India Mechanical Department Panimalar Engineering College Chennai-600069 India Center for Nanotechnology Research (CNR) School of Electronics Engineering (SENSE) Vellore Institute of Technology Vellore Tamil Nadu-632014 India Department of Chemistry School of Advanced Sciences Vellore Institute of Technology Tamilnadu—632014 India Department of Biotechnology Guru Jambheshwar University of Science and Technology Hisar Haryana-125001 India Department of Mechanical Engineering Hindu College of Engineering Sonipat Haryana-131001 India Department of Physics Bal Ganga Degree College Sendul Kemar Tehri Garhwal Uttrakhand- 249155 India Department of Chemistry M.R.R. Govt. Degree College Udayagiri SPSR Nellore Andhra Pradesh-524226 India Department of Electrical Engineering Guru Jambheshwar University of Science and Technology Hisar Haryana-125001 India Solar Cells and Photonics Research Laboratory School of Chemistry University of Hyderabad Hyderabad Telangana—500046 India School of Chemistry Physics and Mechanical Engineering Queensland University of Technology (QUT) 4001 Brisbane Australia

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The Internet of Intelligent things: An overview

The Internet of Intelligent things: An overview

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2017 International Conference on Intelligent Communication and Computational Techniques, ICCT 2017

作者： Nathani, Bharti Vijayvergia, Rekha Department of Computer Science Banasthali University Tonk India Department of Computer Engineering Govt. Women Polytechnic College Jaipur India

ISBN: (纸本)9781538630303

In te rnet has affectedthe daily life. Its a dynamic entity which keeps changing. As the broadband and sensor technology is cheaper, the Internet connectivity is ubiquitous i.e. now we can connect everything, anywhere and anytime. This is the reason why Internet is called as future of Internet. Where things can be defined as animals, people, vehicle, building, device and any object equipped with sensors, actuators, software that are connected to the Internet and having the capability to capture, compute and transfer data over the network. When the things in an Internet are powered by Artificial Intelligence, then it is known as Internet of Intelligent things. In this paper we will discuss the basic component of Internet of Intelligent Things and some important application areas where it is used. This paper provides a comprehensive view of Internet of Things to the beginners, business managers and futuristic policy makers. © 2017 IEEE.

关键词： Actuators

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Identifying Provenance of Information and Anomalous Paths in Attributed Social Networks

Identifying Provenance of Information and Anomalous Paths in...

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International Conference on Computing Methodologies and Communication (ICCMC)

作者： Hetuk Trivedi P V Bindu P Santhi Thilagam Department of Computer Science & Engineering National Institute of Technology Karnataka India Department of Computer Science & Engineering Govt. College of Engineeringy Kannur India

Information provenance problem is an important and challenging problem in social network analysis and it deals with identifying the origin or source of information spread in a social network. In this paper, an approach for detecting the source of an information spread as well as suspicious anomalous paths in a social network is proposed. An anomalous path is a sequence of nodes that propagates an anomalous information to the given destination nodes who cause an anomalous event. The proposed approach is based on attribute-based anomalies and information cascading technique. The anomalous paths are identified in two steps. The first step assigns an anomalous score to each and every vertex in the given graph based on suspicious attributes. The second step detects the source and suspicious anomalous paths in the network using the anomaly scores. The approach is tested on datasets such as Enron and Facebook to demonstrate its effectiveness. Detecting anomalous paths is useful in several applications including identifying terrorist attacks communication path, disease spreading pattern, and match-fixing hidden path between bookie and a cricketer.

关键词： Social network services Terrorism Diseases Conferences computer science Electronic mail Anomaly detection

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Extraction of Relationship Between Characters in Narrative Summaries

Extraction of Relationship Between Characters in Narrative S...

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International Conference on Emerging Trends and Innovations In engineering And Technological Research (ICETIETR)

作者： M Nijila M T Kala M. Tech Computational Linguistics Computer Science & Engineering Department Govt. Engineering College Palakkad India

ISBN: (纸本)9781538657454

Distinguishing relationships between people plays a vital role in understanding of narratives. We can experience different kinds of relationships like family, friendship, hostility, romantic love, etc. We know that Narratives are rich reflections of such relationships. Also extraction of relationship between characters is more helpful in understanding the person's actions, goals and behavior. In actual case relationships between people changes over time. So considering the dynamic nature of relationships will provide a better understanding of narratives. Existing research on analysis of people's relationships in the text has been limited Two simple schemes that use traditional machine learning algorithms. Relevant to this context, this paper proposes a system for extracting interpersonal relationships using deep learning concept convolutional neural network (CNN). The proposed approach produces a better performance over the competitive baseline model.

关键词： Feature extraction Convolutional neural networks Social network services Motion pictures Market research Technological innovation

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A novel method for automatic device control using emotion recognition

A novel method for automatic device control using emotion re...

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2017 International Conference on Intelligent Computing, Instrumentation and Control Technologies, ICICICT 2017

作者： Kamath, Dhanvi Laxmana Jackson, Rhea Jacob, Reena Chacko, Catherine Christy Soumya, C.M. Krishnan, P Remya Computer Science and Engineering Department Govt. Model Engineering College Ernakulam India

ISBN: (纸本)9781509061068

The control of lighting, heating, ventilation, air-conditioning etc. for the home is referred to as home automation. The system proposed here does home automation by recognizing facial emotions. The universal human expressions are sad, neutral, smiling and surprised etc. The intended system recognizes these expressions using the regions of the eye and the mouth and the analyzed information is used to recognize various facial expressions. The output information obtained is fed as an input to a micro-controller that helps in controlling various electronic devices. © 2017 IEEE.

关键词： Emotion Recognition

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Behaviour knowledge space-based fusion for image forgery detection

Behaviour knowledge space-based fusion for image forgery det...

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2017 International Conference on Inventive Communication and Computational Technologies, ICICCT 2017

作者： Monson, Navya Sara Kumar, K. V. Manoj Department of Computer Science and Engineering Govt. Engineering College Thrissur Kerala India

ISBN: (纸本)9781509052974

The detection of manipulated images is of utmost significance nowadays, mainly due to the various technological, moral, and judicial connotations associated with image editing. In this paper, a common form of image manipulation known as image composition or splicing is examined. The forgery detection method proposed here makes use of fine inconsistencies in the colour of the lighting of images. Our approach is machine-learning based which makes use of a behaviour knowledge space. This technique can be used in photographs having two or more people. To achieve forgery detection, complementary illuminant estimators are incorporated on image regions of similar material. Colour-, texture- and edge-based features are extracted from these illuminant estimates which are then provided to a machine-learning approach for automatic decision-making. © 2017 IEEE.

关键词： Textures

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Cognitive State Classification using Genetic Algorithm based Linear Collaborative Discriminant Regression

Cognitive State Classification using Genetic Algorithm based...

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International Conference on Secure Cyber Computing and Communication (ICSCCC)

作者： K. O. Gupta P. N. Chatur Department of Computer Science and Engineering D. M. Institute of Engineering Technology and Research Wardha India Department of Computer Science and Engineering Govt. College of Engineering Amravati India

ISBN: (纸本)9781538663745;9781538663738

Functional Magnetic Resonance imaging (fMRI) provides sequence of 3D images which contains large number of voxels as information. There are many statistical methods evolved in last few years to analyze this information. Main concern of all these techniques is huge dimensions of the data produced by these images. This paper proposes an efficient hybrid method for feature selection and classification. This method combine entropy based genetic algorithm (EGA) with Linear Collaborative Discriminant Regression Classification (LCDRC) to form feature based classification method. Entropy based genetic algorithm is applied to find maximum significance between the input and output and also it radically reduces the redundancy within the input features. Experiments' using Star-Plus dataset to classify fMRI images shows that EGA-LCDRC reduces up to 60% features and produces 96.73% accuracy.

关键词： Functional magnetic resonance imaging Entropy Feature extraction Genetic algorithms Collaboration Training Classification algorithms

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Experimental investigation of bending characteristics of hybrid composites fabricated by hand layup method

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Journal of Physics: Conference Series 2021年第1期2089卷

作者： M Sadashiva S Praveen Kumar M K Yathish V T Satish MR Srinivasa V Sharanraj Assistant Professor Department of Mechanical Engg P.E.S. College of Engg. Mandya Karnataka India Research Scholar Dept. Mechanical Engineering UVCE Bengaluru Karnataka India Assistant Professor Department of Industrial Production Engg P.E.S. College of Engg. Mandya Karnataka India Assistant Professor Department of Mechanical Engg Malnad College of Engg. Hassan Karnataka India Senior Grade Lecturer Department of Mechanical Engineering (W&SM) S. J.(Govt.) Polytechnic BangaloreIndia

The extensive applications of hybrid composite materials in the field of transportation and structural domine provide prominent advantages in the order of stiffness, strength even cost. However extend the advantages of hybrid campsites in several field such as aviation and marine even more additional properties should be inculcate in them. During production of such profitable composites poses some problems at time at decompose and processing. It's better to develop environment friendly and reusable composites, bio hybrid composite materials such of the one. In this paper, focused on development of Eco-friendly hybrid bio composites with the ingredients of drumstick fibers, glass fiber along with polyester resin. This hybrid bio composites subjected to bending test and evaluate the characteristics of bending properties, this research evident that bending characteristics of hybrid composites with longitudinal fiber orientation better than transverse.

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Big Data and Machine Learning Based Secure Healthcare Framework

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Procedia computer Science 2018年 132卷 1049-1059页

作者： Prableen Kaur Manik Sharma Mamta Mittal Ph.D. Research Scholar Department of Computer Science and Applications DAV University Jalandhar India Department of Computer Science and Applications DAV University Jalandhar India Department of Computer Science and Engineering G.B. Pant Govt. Engineering College New Delhi India

The paper presents a brief introduction to big data and its role in healthcare applications. It is observed that the use of big data architecture and techniques are continuously assisting in managing the expeditious data growth in healthcare industry. Here, initially an empirical study is performed to analyze the role of big data in healthcare industry. It has been observed that significant work has been done using big data in healthcare sector. Nowadays, it is intricate to envision the way the machine learning and big data can influence the healthcare industries. It has been observed that most of the authors who implemented the use of machine learning and big data analytics in disease diagnosis have not given significant weightage to the privacy and security of the data. Here, a novel design of smart and secure healthcare information system using machine learning and advanced security mechanism has been proposed to handle big data of medical industry. The innovation lies in the incorporation of optimal storage and data security layer used to maintain security and privacy. Different techniques like masking encryption, activity monitoring, granular access control, dynamic data encryption and end point validation have been incorporated. The proposed hybrid four layer healthcare model seems to be more effective disease diagnostic big data system.

关键词： Big Data Healthcare Big data analytics disease diagnosis predictive analysis security privacy

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