There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

This chapter introduces the subject of statistical pattern recognition (SPR). It starts by considering how features are defined and emphasizes that the nearest neighbor algorithm achieves error rates comparable with those of an ideal Bayes’ classifier. The concepts of an optimal number of features, representativeness of the training data, and the need to avoid overfitting to the training data are stressed. The chapter shows that methods such as the support vector machine and artificial neural networks are subject to these same training limitations, although each has its advantages. For neural networks, the multilayer perceptron architecture and back-propagation algorithm are described. The chapter distinguishes between supervised and unsupervised learning, demonstrating the advantages of the latter and showing how methods such as clustering and principal components analysis fit into the SPR framework. The chapter also defines the receiver operating characteristic, which allows an optimum balance between false positives and false negatives to be achieved.

Statistical Pattern Recognition

Internet-of-Things (IoT) are everywhere in our daily life. They are used in our homes, in hospitals, deployed outside to control and report the changes in environment, prevent fires, and many more beneficial functionality. However, all those benefits can come of huge risks of privacy loss and security issues. To secure the IoT devices, many research works have been conducted to countermeasure those problems and find a better way to eliminate those risks, or at least minimize their effects on the user’s privacy and security requirements. The survey consists of four segments. The first segment will explore the most relevant limitations of IoT devices and their solutions. The second one will present the classification of IoT attacks. The next segment will focus on the mechanisms and architectures for authentication and access control. The last segment will analyze the security issues in different layers.

A Survey on Security and Privacy Issues in Internet-of-Things

Antenna Theory And Design

Free-space optical (FSO) communication is known for its various impairments such as atmospheric turbulence and misalignment fading. In this paper, we study the performance of an FSO link operating under combined path loss and atmospheric and misalignment fadings. We derive a closed-form expression for the bit error rate (BER) of the FSO link in such conditions when the on-off keying (OOK) modulation is employed and when the fluctuations of the received signal are modeled by Gamma- Gamma distribution. In addition, we evaluate the effects of the combined fadings on the outage probability of the FSO link for different strengths of turbulence and pointing errors. Furthermore, we investigate the advantages of combining radio frequency (RF) with FSO to form hybrid FSO/ RF systems. The RF link is based on 16 quadrature amplitude modulation (16-QAM) and on Rician channel fading. We study the performance of the hybrid FSO/RF system in terms of outage probability and BER and find that the hybrid FSO/RF system can overcome the weaknesses of FSO links, which are sensitive to atmospheric variations and misalignment fading.

On the effects of combined atmospheric fading and misalignment on the hybrid FSO/RF transmission

In order to reach higher coding efficiency compared to its predecessor, a state-of-the-art video compression standard, the High Efficiency Video Coding (HEVC), has been designed to rely on many improved coding tools and sophisticated techniques. The new features are achieving significant coding efficiency but at the cost of huge implementation complexity. This complexity has increased the HEVC encoders’ need for fast algorithms and hardware friendly implementations. In fact, encoders have to perform the different encoding decisions, overcoming the real-time encoding constraint while taking care of coding efficiency. In this sense, in order to reduce the encoding complexity, HEVC encoders rely on look-ahead mechanisms and pre-processing solutions. In this context, we propose a gradient-based pre-processing stage. We investigate particularly the Prewitt operator used to generate the gradient and we propose necessary approaches that enhance the gradient performance of detecting the HEVC intra modes. We also set different probability scenarios, based on the gradient information, in order to speed up the mode search process. Moreover, we propose a gradient-based estimation of the texture complexity that we use for coding unit decision. Results show that the proposed algorithm achieves a reduction of 42.8% in encoding time with an increase in BD rate of only 1.1%.

/pdf/gradient-based-pre-processing-for-intra-prediction-in-high-4w78pev26o.pdf

Gradient-based pre-processing for intra prediction in High Efficiency Video Coding

A new biometrics-based key establishment protocol in WBAN: energy efficiency and security robustness analysis

Security and privacy are challenging task in resource constrained in Internet of things (IoT) and Wireless Sensor Networks (WSN). Hence, anonymity and trust are prominent for many common IoT and WSN applications, in which we conceal nodes identity and give confidential data to a trusted node. The majority of exiting IoT security solutions cannot achieve complete security needs and/or have large computation overheads. In this paper we design a secure generic model for IoT and WSN to ensure anonymity, data secrecy and trust between nodes. Our work is based on lightweight key agreement protocol, the Identity Based Encryption (IBE) and Pseudonym Based Encryption (PBC).

An efficient scheme for anonymous communication in IoT

We present an acoustic location system that adopts the time of arrival of the path of maximum amplitude as a signature and estimates the target position through nonparametric kernel regression. The system was evaluated in experiments for two main configurations: a privacy-oriented configuration with code division multiple access operation and a centralized configuration with time division multiple access operation. The effects of the number and positions of sources on the performance of the privacy-oriented system was studied. Moreover, the effect of the number of fingerprint positions on the performance of both systems was investigated. Results showed that our privacy-oriented scheme provides an accuracy of 8.5 cm with 87% precision, whereas our centralized system provides an accuracy of 2.7 cm for 93% of measurements. A comparison between our privacy-oriented system and another acoustic location system based on code division multiple access operation and lateration was conducted on our test bench and revealed that the cumulative error distribution function of the fingerprint-based system is better than that of the lateration-based system. This result is similar to that found for Wi-Fi radio-based localization. However, our experiments are the first to demonstrate the detrimental effect that reverberation has on naive acoustic localization approaches.

/pdf/performance-evaluation-of-an-acoustic-indoor-localization-2gsc782wrd.pdf

Ammar Bouallegue

Papers

On the effects of combined atmospheric fading and misalignment on the hybrid FSO/RF transmission

Gradient-based pre-processing for intra prediction in High Efficiency Video Coding

A new biometrics-based key establishment protocol in WBAN: energy efficiency and security robustness analysis

An efficient scheme for anonymous communication in IoT

Performance evaluation of an acoustic indoor localization system based on a fingerprinting technique