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2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014

作者： Becker, T. Kanje, W. Rapoport, D. Thierbach, K. Scherf, N. Roeder, I. Madany Mamlouk, A. Fraunhofer Institution for Marine Biotechnology Lübeck Germany Graduate School for Computing in Medicine and Life Sciences University of Lübeck Germany Institute for Neuro- and Bioinformatics University of Lübeck Germany Institute for Medical Informatics and Biometry Dresden University of Technology Germany

ISBN: (纸本)9781467319591

Mitosis detection poses a major challenge in cell tracking as mitoses are crucial events in the construction of genealogical trees. Making use of typical mitotic patterns that can be seen in phase contrast images of time lapse experiments, we propose a new benchmark data set CeTReS.B-MI consisting of mitotic and non-mitotic cells from the publicly accessible, fully labeled data set CeTReS.B. Using this data, two simple mitosis detectors (based on compactness and intensity) are used exemplarily to train, test and compare their ability to detect mitotic events. As a gold standard, we propose a linear support vector machine (SVM), which is able to separate the classes with a high accuracy (AUC=0.993). To illustrate the potential impact of a robust mitosis detection, the proposed classifiers are combined with two state of the art cell tracking algorithms. For both algorithms, performance does change when adding mitosis detection. Finally, this evaluation also emphasizes how easy implementation and comparison becomes, having suitable benchmark data at hand. © 2014 IEEE.

关键词： Support vector machines

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An alignment-free fingerprint bio-cryptosystem based on modified Voronoi neighbor structures

An alignment-free fingerprint bio-cryptosystem based on modi...

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作者： Yang, Wencheng Hu, Jiankun Wang, Song Stojmenovic, Milos School of Engineering and Information Technology University of New South Wales at the Australia Defence Force Academy Canberra ACT 2600 Australia School of Engineering and Mathematical Sciences La Trobe University VIC 3086 Australia Department of Informatics and Computing Singidunum University Belgrade Serbia

Bio-cryptography is an emerging security technology which combines cryptography with biometrics. A good bio-cryptosystem is required to protect the privacy of the relevant biometric data as well as achieving high recognition accuracy. Fingerprints have been widely used in bio-cryptosystem design. However, fingerprint uncertainty caused by distortion and rotation during the image capturing process makes it difficult to achieve a high recognition rate in most bio-cryptographic systems. Moreover, most existing bio-cryptosystems rely on the accurate detection of singular points for fingerprint image pre-alignment, which is very hard to achieve, and the image rotation transformation during the alignment process can cause significant singular point deviation and minutiae changes. In this paper, by taking full advantage of local Voronoi neighbor structures (VNSs), e.g. local structural stability and distortion insensitivity, we propose an alignment-free bio-cryptosystem based on fixed-length bit-string representations extracted from modified VNSs, which are rotation- and translation-invariant and distortion robust. The proposed alignment-free bio-cryptosystem is able to provide strong security while achieving good recognition performance. Experimental results in comparison with most existing alignment-free bio-cryptosystems using the publicly-available databases show the validity of the proposed scheme. © 2013 Elsevier Ltd. All rights reserved.

关键词： Cryptography

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Estimating packet reception rate in noisy environments

Estimating packet reception rate in noisy environments

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IEEE Conference on ALocal Computer Networks Workshops (LCN Workshops)

作者： James Brown Utz Roedig Carlo Alberto Boano Kay Römer School of Computing and Communications Lancaster University Lancaster United Kingdom Institute for Technical Informatics Graz University of Technology Graz Austria

ISBN: (纸本)9781479937851

For the design of dependable and efficient wireless sensor networks it is essential to estimate the achievable packet reception rate (PRR) in the deployment environment. Making such estimation is not trivial as packet delivery success depends on the level of interference present in the deployment area. In this work we show that it is possible to obtain a meaningful representation of the expected interference levels at the target location by measuring the probability distribution function of idle period lengths, and use this to estimate PRR before network deployment. We show how a probability distribution function of idle period lengths can be measured using off-the-shelf sensor nodes. We illustrate how to exploit this methodology to estimate PRR in dependence of the used packet length, and show that relatively short measurement periods provide enough data to obtain accurate *** carry out an extensive experimental evaluation showing that Wi-Fi interference can be captured using this method which allows PRR predictions in such Wi-Fi interference setting with an average error of only 3.2%.

关键词： Interference IEEE 802.11 Standards Wireless sensor networks Estimation Length measurement Probability density function Accuracy

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Scene radiance estimation from human corneal reflections

Scene radiance estimation from human corneal reflections

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Imaging Systems and Applications, ISA 2014

作者： Tominaga, Shoji Ohtera, Ryo Nishi, Shogo Graduate School of Advanced Integration Science Chiba University Inage-ku Chiba-shi Chiba 263-8522 Japan Graduate School of Information Technology Kobe Institute of Computing Chuo-ku Kobe 650-0001 Japan Department of Engineering Informatics Osaka Electro-Communication University Neyagawa Osaka 572-8530 Japan

ISBN: (纸本)9781557523082

A method is proposed for estimating spectral radiances of the surrounding scene from a reflected image on the corneal surface. A digital color camera and the human eyeball are used to develop a simple imaging system without any specific device. The corneal image consists of a mixture of specular and diffuse reflections from the cornea and the iris. The desired scene radiances are only recovered from the specular reflection component after removing the diffuse reflection component. Experiments are executed in several different conditions. © 2014 OSA.

关键词： Imaging systems

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A data collection approach for Mobile Botnet analysis and detection

A data collection approach for Mobile Botnet analysis and de...

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IEEE Symposium on Wireless technology and Applications (ISWTA)

作者： Meisam Eslahi Mohammad Reza Rostami H. Hashim N. M. Tahir Maryam Var Naseri Faculty of Computing Engineering & Technology Asia Pacific University of Technology & Innovation Malaysia Faculty of Electrical Engineering Universiti Teknologi MARA Advanced Informatics School University Technology Malaysia

Recently, MoBots or Mobile Botnets have become one of the most critical challenges in mobile communication and cyber security. The integration of Mobile devices with the Internet along with enhanced features and capabilities has made them an environment of interest for cyber criminals. Therefore, the spread of sophisticated malware such as Botnets has significantly increased in mobile devices and networks. On the other hand, the Bots and Botnets are newly migrated to mobile devices and have not been fully explored yet. Thus, the efficiency of current security solutions is highly limited due to the lack of available Mobile Botnet datasets and samples. As a result providing a valid dataset to analyse and understand the Mobile botnets has become a crucial issue in mobile security and privacy. In this paper we present an overview of the current available data set and samples and we discuss their advantages and disadvantages. We also propose a model to implement a mobile Botnet test bed to collect data for further analysis.

关键词： Mobile communication Malware Mobile handsets Mobile computing Command and control systems Servers

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Message from SNAA 2014 program chairs

ASONAM 2014 - Proceedings of the 2014 IEEE/ACM International...

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ASONAM 2014 - Proceedings of the 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2014年 xxxiv页

作者： Bródka, Piotr Magnani, Matteo Musial, Katarzyna Institute of Informatics Wroclaw University of Technology Poland Department of Information Technology Division of Computing Science Uppsala University Sweden School of Natural and Mathematical Sciences Department of Informatics King's College London United Kingdom

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Q-Learning: From Computer Network Security to Software Security

Q-Learning: From Computer Network Security to Software Secur...

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International Conference on Machine Learning and Applications (ICMLA)

作者： Arisoa S. Randrianasolo Larry D. Pyeatt School of Computing and Informatics Lipscomb University Nashville TN USA Department of Mathematics and Computer Science South Dakota School of Mines and Technology Rapid City SD USA

Reinforcement learning techniques become more popular in computer network security. The same reinforcement learning techniques developed for network security can be applied to software security as well. This research summarizes a work in progress attempt to incorporate Q-learning algorithm in software security. The Q-learning method is embedded as part of the software itself to provide a security mechanism that has ability to learn by itself to develop a temporary repair mechanism. The results of the experiment express that given the right parameters and the right setting the Q-learning approach rapidly learns to block all malicious actions. Data analysis on the Q-values produced by the software can provide security diagnostic as well. A larger scale experiment is expected to be seen in the future work.

关键词： Connectors Security Maintenance engineering Software systems Learning (artificial intelligence) Detectors

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Automatic Identification of Solid-Phase Medication Intake Using Wireless Wearable Accelerometers

Automatic Identification of Solid-Phase Medication Intake Us...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Rui Wang Zdenka Sitova Xiaoqing Jia Xiang He Tobi Abramson Paolo Gasti Kiran S. Balagani Aydin Farajidavar Integrated Medical Systems (IMS) Laboratory at the School of Engineering and Computing Sciences New York Institute of Technology (NYIT) Faculty of Informatics Masaryk University School of health profession NYIT Cyber Security and Privacy Laboratory at the School of Engineering and Computing Sciences NYIT

ISBN: (纸本)9781424479276

We have proposed a novel solution to a fundamental problem encountered in implementing non-ingestion based medical adherence monitoring systems, namely, how to reliably identify pill medication intake. We show how wireless wearable devices with tri-axial accelerometer can be used to detect and classify hand gestures of users during solid-phase medication intake. Two devices were worn on the wrists of each user. Users were asked to perform two activities in the way that is natural and most comfortable to them: (1) taking empty gelatin capsules with water, and (2) drinking water and wiping mouth. 25 users participated in this study. The signals obtained from the devices were filtered and the patterns were identified using dynamic time warping algorithm. Using hand gesture signals, we achieved 84.17 percent true positive rate and 13.33 percent false alarm rate, thus demonstrating that the hand gestures could be used to effectively identify pill taking activity.

关键词： Time series analysis Monitoring Mouth Medical diagnostic imaging Acceleration Accelerometers

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Robust ladder-climbing with a humanoid robot with application to the DARPA Robotics Challenge

Robust ladder-climbing with a humanoid robot with applicatio...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Jingru Luo Yajia Zhang Kris Hauser H. Andy Park Manas Paldhe C. S. George Lee Michael Grey Mike Stilman Jun Ho Oh Jungho Lee Inhyeok Kim Paul Oh School of Informatics and Computing Indiana University Bloomington School of Electrical and Computer Engineering Purdue University USA School of Interactive Computing Georgia Institute of Technology USA Korea Advanced Institute of Science and Technology South Korea Rainbow Co. South Korea Mechanical Engineering and Mechanics Drexel University USA

This paper presents an autonomous planning and control framework for humanoid robots to climb general ladder- and stair-like structures. The approach consists of two major components: 1) a multi-limbed locomotion planner that takes as input a ladder model and automatically generates a whole-body climbing trajectory that satisfies contact, collision, and torque limit constraints; 2) a compliance controller which allows the robot to tolerate errors from sensing, calibration, and execution. Simulations demonstrate that the robot is capable of climbing a wide range of ladders and tolerating disturbances and errors. Physical experiments demonstrate the DRC-Hubo humanoid robot successfully mounting, climbing, and dismounting an industrial ladder similar to the one intended to be used in the DARPA Robotics Challenge Trials.

关键词： Joints Planning Foot Collision avoidance Robot sensing systems Robot kinematics

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A nature-inspired hybrid Fuzzy C-means algorithm for better clustering of biological data sets

A nature-inspired hybrid Fuzzy C-means algorithm for better ...

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International Conference on Data Science & Engineering (ICDSE)

作者： T A Arunanand K A Abdul Nazeer Mathew J Palakal Meeta Pradhan Department of Computer Science and Engineering National Institute of Technology Calicut INDIA National Institute of Technology Calicut Calicut Kerala IN School of Informatics and Computing Indiana University Purdue University Indianapolis USA

Clustering is one of the widely used unsupervised methods to interpret and analyze huge amount of data in the field of Bioinformatics. One of the major issues involved in clustering is to address the growing data so that the cluster quality does not decrease with increase in the size of the data. In this work, we compare the promising clustering algorithms on various cancer domains and suggest improvements to them, with the help of a optimization techniques viz. Harmony Search (HS) algorithm. This paper discusses comparison of these techniques, various steps taken to achieve the target, and finally suggests an improved method that combines the merits of Fuzzy C-means algorithm and HS optimization technique.

关键词： Clustering algorithms Algorithm design and analysis Cancer Iris Linear programming Optimization Data mining

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