Robust real-time 3D head pose estimation from range data

In this paper a real-time 3D pose estimation algorithm using range data is described. The system relies on a novel 3D sensor that generates a dense range image of the scene. By not relying on brightness information, the proposed system guarantees robustness under a variety of illumination conditions, and scene contents. Efficient face detection using global features and exploitation of prior knowledge along with novel feature localization and tracking techniques are described. Experimental results demonstrate accurate estimation of the six degrees of freedom of the head and robustness under occlusions, facial expressions, and head shape variability.     

Attack Propagation in Networks

A new model for intrusion and its propagation through various attack schemes in networks is considered. The model is characterized by the number of network nodes n, and two parameters f and g. Parameter f represents the probability of failure of an attack to a node and is a gross measure of the level of security of the attacked system and perhaps of the intruder’s skills; g represents a limit on the number of attacks that the intrusion software can ever try, due to the danger of being discovered, when it issues them from a particular (broken) network node. The success of the attack scheme is characterized by two factors: the number of nodes captured (the spread factor) and the number of virtual links that a defense mechanism has to trace from any node where the attack is active to the origin of the intrusion (the traceability factor). The goal of an intruder is to maximize both factors. In our model we present four different ways (attack schemes) by which an intruder can organize his attacks. Using analytic and experimental methods, we first show that for any 0 < f < 1, there exists a constant g for which any of our attack schemes can achieve a Θ(n) spread and traceability factor with high probability, given sufficient propagation time. We also show for three of our attack schemes that the spread and the traceability factors are, with high probability, linearly related during the whole duration of the attack propagation. This implies that it will not be easy for a detection mechanism to trace the origin of the intrusion, since it will have to trace a number of links proportional to the nodes captured.     

Energy balanced data propagation in wireless sensor networks

We study the problem of energy-balanced data propagation in wireless sensor networks. The energy balance property guarantees that the average per sensor energy dissipation is the same for all sensors in the network, during the entire execution of the data propagation protocol. This property is important since it prolongs the network’:s lifetime by avoiding early energy depletion of sensors. We propose a new algorithm that in each step decides whether to propagate data one-hop towards the final destination (the sink), or to send data directly to the sink. This randomized choice balances the (cheap) one-hop transimssions with the direct transimissions to the sink, which are more expensive but “bypass” the sensors lying close to the sink. Note that, in most protocols, these close to the sink sensors tend to be overused and die out early. By a detailed analysis we precisely estimate the probabilities for each propagation choice in order to guarantee energy balance. The needed estimation can easily be performed by current sensors using simple to obtain information. Under some assumptions, we also derive a closed form for these probabilities. The fact (shown by our analysis) that direct (expensive) transmissions to the sink are needed only rarely, shows that our protocol, besides energy-balanced, is also energy efficient. This work has been partially supported by the IST/FET/GC Programme of the European Union under contract numbers IST-2001-33135 (CRESCCO) and 6FP 001907 (DELIS). A perliminary version of the work appeared in WMAN 2004 [11]. Charilaos Efthymiou graduated form the Computer Engineering and Informatics Department (CEID) of the University of Patras, Greece. He received his MSc from the same department with advisor in S. Nikoletseas. He currently continuous his Ph.D studies in CEID with advisor L. Kirousis. His research interest include Probabilistic Techniques and Random Graphs, Randomized Algorithms in Computationally Hard Problems, Stochastic Processes and its Applications to Computer Science. Dr. Sotiris Nikoletseas is currently a Senior Researcher and Managing Director of Research Unit 1 (“Foundations of Computer Science, Relevant Technologies and Applications”) at the Computer Technology Institute (CTI), Patras, Greece and also a Lecturer at the Computer Engineering and Informatics Department of Patras University, Greece. His research interests include Probabilistic Techniques and Random Graphs, Average Case Analysis of Graph Algorithms and Randomized Algorithms, Fundamental Issues in Parallel and Distributed Computing, Approximate Solutions to Computationally Hard Problems. He has published scientific articles in major international conferences and journals and has co-authored (with Paul Spirakis) a book on Probabilistic Techniques. He has been invited speaker in important international scientific events and Universities. He has been a referee for the Theoretical Computer Science (TCS) Journal and important international conferences (ESA, ICALP). He has participated in many EU funded R&D projects (ESPRIT/ALCOM-IT, ESPRIT/GEPPCOM). He currently participates in 6 Fifth Framework projects: ALCOM-FT, ASPIS, UNIVERSAL, EICSTES (IST), ARACNE, AMORE (IMPROVING). Jose Rolim is Full Professor at the Department of Computer Science of the University of Geneva where he leads the Theoretical Computer Science and Sensor Lab (TCSensor Lab). He received his Ph.D. degree in Computer Science at the University of California, Los Angeles working together with Prof. S. Greibach. He has published several articles on the areas of distributed systems, randomization and computational complexity and leads two major projects on the area of Power Aware Computing and Games and Complexity, financed by the Swiss National Science Foundation. Prof. Rolim participates in the editorial board of several journals and conferences and he is the Steering Committee Chair and General Chair of the IEEE Distributed Computing Conference in Sensor Systems.     

Fault-tolerant and efficient data propagation in wireless sensor networks using local,additional network information

We propose a new data dissemination protocol for wireless sensor networks, that basically pulls some additional knowledge about the network in order to subsequently improve data forwarding towards the sink. This extra information is still local, limited and obtained in a distributed manner. This extra knowledge is acquired by only a small fraction of sensors thus the extra energy cost only marginally affects the overall protocol efficiency. The new protocol has low latency and manages to propagate data successfully even in the case of low densities. Furthermore, we study in detail the effect of failures and show that our protocol is very robust. In particular, we implement and evaluate the protocol using large scale simulation, showing that it significantly outperforms well known relevant solutions in the state of the art.     

A 5‐Gbps USB3.0 transmitter and receiver linear equalizer

A USB3.0 compatible transmitter and the linear equalizer of the corresponding receiver are presented in this paper. The architecture and circuit design techniques used to meet the strict requirements of the overall link design are explored. Output voltage amplitude and de‐emphasis levels are programmable, whereas the output impedance is calibrated to 50Ω. A programmable receiver equalizer is also presented with its main purpose being to compensate for the channel losses; this is employed together with a DC offset compensation scheme. The 6.25‐GHz equalizer provides a 10 dB overall gain equalization and 5.5‐dB peaking at the maximum gain setting. Designed using a mature and well established 65 nm complementary metal oxide semiconductor process, the layout area is 400 µm × 210 µm for the transmitter core, and 140 µm × 70 µm for the equalizer core. The power consumption is 55 and 4 mW, respectively, from a 1.2 V supply at a data rate of 5 Gbps. The target application for such high‐speed blocks is to implement the critical part of the physical layer that defines the signaling technology of SuperSpeed USB3 PHY. However, identical iterations of the circuitry discussed can be used for similar high‐speed applications like the PCI express (PCIe). Copyright © 2014 John Wiley & Sons, Ltd.     

Hydrolysis rate of submicron Zn particles for solar H2 synthesis

The hydrolysis rate of Zn particles by up to 50 mol% water vapor in Ar gas was measured by thermogravimetric analysis at atmospheric pressure and 330–360 °C and quantified by a core-shell model. An initial ZnO layer led to an initially linear conversion profile attributed to a fast surface reaction (half-order with respect to water vapor mole fraction, y) followed by a parabolic conversion profile independent of y but dependent on Zn ion diffusion through a ZnO layer. The latter is most important for solar H₂ formation by the Zn/ZnO water-splitting cycle as it determines the required process residence time for Zn hydrolysis. A ready-to-use equation for calculation of ZnO and H₂ formation during Zn hydrolysis is proposed and compared to literature data revealing enhanced hydrolysis rates for submicron Zn particles.     

Silicon Fuel: A hydrogen storage material

Considerable effort is focused on developing alternative approaches to generating and storing energy to reduce the world's reliance on fossil fuels. Hydrogen offers one such alternative, which is zero-emission at the point of use when used to supply a fuel cell to generate electricity. However, the availability of hydrogen by methods that are both cost-effective and environmentally friendly remains a significant challenge.The formulation presented in this work, which we call Silicon Fuel, contains 90% silicon and can generate high hydrogen yields of 70% or more in just a few minutes. This means that the dry material effectively has a hydrogen content of at least 9 wt% and a realistic specific energy of at least 1.5 kWh/kg if the hydrogen supplies a fuel cell with 50% efficiency. As the hydrogen can be generated in a commercially useful time frame, it is suitable for applications such as automotive refuelling, where consumers expect to be able to refuel their vehicle within a few minutes.     

Adaptive lighting controllers using smart sensors

The aim of this paper is to present an advanced controller for artificial lights evaluated in several rooms in two European Hospitals located in Chania, Greece and Ancona, Italy. Fuzzy techniques have been used for the architecture of the controller. The energy efficiency of the controllers has been calculated by running the controller coupled with validated models of the RADIANCE back-wards ray tracing software. The input of the controller is the difference between the current illuminance value and the desired one, while the output is the change of the light level that should be applied in the artificial lights. Simulation results indicate significant energy saving potentials. Energy saving potential is calculated from the comparison of the current use of the artificial lights by the users and the proposed one. All simulation work has been conducted using Matlab and RADIANCE environment.     

Aggregated mobility-based topology inference for fast sensor data collection

We investigate the problem of efficient data collection in wireless sensor networks where both the sensors and the sink move. We especially study the important, realistic case where the spatial distribution of sensors is non-uniform and their mobility is diverse and dynamic. The basic idea of our protocol is for the sink to benefit of the local information that sensors spread in the network as they move, in order to extract current local conditions and accordingly adjust its trajectory. Thus, sensory motion anyway present in the network serves as a low cost replacement of network information propagation. In particular, we investigate two variations of our method: a) the greedy motion of the sink towards the region of highest density each time and b) taking into account the aggregate density in wider network regions. An extensive comparative evaluation to relevant data collection methods (both randomized and optimized deterministic), demonstrates that our approach achieves significant performance gains, especially in non-uniform placements (but also in uniform ones). In fact, the greedy version of our approach is more suitable in networks where the concentration regions appear in a spatially balanced manner, while the aggregate scheme is more appropriate in networks where the concentration areas are geographically correlated. We also investigate the case of multiple sinks by suggesting appropriate distributed coordination methods.