With aggressive technology scaling, within-die random variations are becoming the most dominant source of process variations. Gate-level statistical static timing is becoming a widely accepted approach as an alternative to static timing analysis. However, statistical timing approaches lack good models for handling timing variations due to within-die random variations. Before performing statistical timing analysis on a design or System On Chip (SoC), the cells in the library are pre-characterized for delay as well as constraints due to these random variations. This is referred to as statistical characterization of the cells. The major contribution of this dissertation is the development of novel techniques for statistical characterization and optimization of cells. The methods couple the knowledge of circuits along with the significant factor analysis methods to compute the sensitivities, to perform statistical timing and to perform sensitivity-aware cell optimizations. The first contribution of this dissertation is a statistical delay characterization method developed for computing delay sensitivities of standard cells considering both global and mismatch process variations. In addition to the cells being characterized for delay, the sequential cells are characterized for timing constraints like setup and hold time constraints. The second contribution of this dissertation addresses the problem of constraint sensitivity characterization in sequential cells. Block-based statistical timing approaches lack accurate consideration of the impact of slew variations on both delay and arrival time variations. Specifically, the delay variations due to within-die random variables (mismatch variables) result in a slew-based correlation during timing propagation. Handling within-die random variations more accurately during statistical timing propagation is the topic of the third contribution of this dissertation. Clock networks are more prone to these within-die random variations and can result in significant clock-skew variations. In the fourth contribution, a timing margining methodology is presented that accurately accounts for the clock skew variations in a timing sign-off flow. Typically, the standard cells are designed very early in the design cycle and long before the process reaches production maturity. Any subtle improvements to reduce variability in standard cells can improve parametric yield significantly. Statistical characterization of cells for timing provides a key baseline for understanding the circuit behavior due to different sources of variation. The sensitivity information can also help increase yield by reducing the variability during the circuit design itself. The final contribution in the dissertation addresses this by defining key cell and device criticality metrics. A sensitivity-aware standard cell layout optimization is demonstrated using the proposed criticality metrics. / text

We investigate the statistics of transmission time of wireless systems employing adaptive transmission. Unlike traditional transmission systems where the transmission time of a fixed amount of data is typically regarded as a constant, the transmission time with adaptive transmission systems becomes a random variable, as the transmission rate varies with the fading channel condition. To facilitate the design and optimization of wireless transmission schemes, we present an analytical framework to determine statistical characterizations for the transmission time with adaptive transmission. In particular, we derive the exact statistics of transmission time over block fading channels. The probability mass function (PMF) and cumulative distribution function (CDF) of transmission time are obtained for both slow and fast fading scenarios. We further extend our analysis to Markov channels, where the transmission time becomes a sequence of exponentially distributed random-length time slots. Analytical expression for the probability density function (PDF) of transmission time is derived for both fast and slow fading scenarios. Since the energy consumption can be characterized by the product of power consumption and transmission time, we also evaluate the energy consumption for wireless systems with adaptive transmission. Cognitive radio communication can opportunistically access underutilized spectrum for emerging wireless applications. With interweave cognitive implementation, a secondary user (SU) transmits only if a primary user does not occupy the channel and waits for transmission otherwise. Therefore, secondary packet transmission involves both transmission and waiting periods. The resulting extended delivery time (EDT) is critical to the throughput analysis of secondary system. With the statistical results of transmission time, we derive the PDF of EDT considering random-length SU transmission and waiting periods for continuous spectrum sensing and semi-periodic spectrum sensing. Taking spectrum sensing errors into account, we propose a discrete Markov chain modeling slotted secondary transmission coupled with periodic spectrum sensing. Markov modeling is applied to energy efficiency optimization and queuing performance evaluation. / Graduate

L’environnement opérationnel des pales et des structures porteuses des hydroliennes est de nature incertaine, compte tenu de la variabilité de l’écoulement (turbulence, sillage, houle, courants. . .). Ces éléments structuraux subissent donc des états de contraintes multiaxiaux complexes avec des fortes variations temporelles à caractère aléatoire. Ainsi, le dimensionnement basé sur des critères statiques déterministes apparaît insuffisant pour tenir compte de la complexité de l’histoire du chargement mécanique et de sa variabilité.Ce travail vise à établir des méthodes de dimensionnement adaptées à cette situation, pour la conception de structures hydroliennes aux risques et aux coûts maîtrisés. La démarche adoptée repose sur la description de l’écoulement et de ses grandeurs statistiques, afin de caractériser les efforts exercés sur l’hydrolienne et les contraintes mécaniques extrêmes en pied de pale. / The operating environment of tidal turbines blades and body is uncertain, due to the flow variability (turbulence,wake, tide, streams...). These structural elements then undergo strongly time-varying complex multi-axial random stress states. A design based on static and deterministic criteria thus appears insufficient to take the complexity and the variability of the mechanical loading into account. This work aims at setting sizing methods that are adapted to this situation, in order to design tidal turbines with mastered risks and costs. The proposed method lies on a statistical description of the flow, in order to characterize the load of the turbine and the extreme mechanical stresses at the blade foot.

"Many current and future medical devices are wearable, using the human body as a conduit for wireless communication, which implies that human body serves as a crucial part of the transmission medium in body area networks (BANs). Implantable medical devices such as Pacemaker and Cardiac Defibrillators are designed to provide patients with timely monitoring and treatment. Endoscopy capsules, pH Monitors and blood pressure sensors are used as clinical diagnostic tools to detect physiological abnormalities and replace traditional wired medical devices. Body-mounted sensors need to be investigated for use in providing a ubiquitous monitoring environment. In order to better design these medical devices, it is important to understand the propagation characteristics of channels for in-body and on- body wireless communication in BANs. The IEEE 802.15.6 Task Group 6 is officially working on the standardization of Body Area Network, including the channel modeling and communication protocol design. This thesis is focused on the propagation characteristics of human body movements. Specifically, standing, walking and jogging motions are measured, evaluated and analyzed using an empirical approach. Using a network analyzer, probabilistic models are derived for the communication links in the medical implant communication service band (MICS), the industrial scientific medical band (ISM) and the ultra- wideband (UWB) band. Statistical distributions of the received signal strength and second order statistics are presented to evaluate the link quality and outage performance for on-body to on- body communications at different antenna separations. The Normal distribution, Gamma distribution, Rayleigh distribution, Weibull distribution, Nakagami-m distribution, and Lognormal distribution are considered as potential models to describe the observed variation of received signal strength. Doppler spread in the frequency domain and coherence time in the time domain from temporal variations is analyzed to characterize the stability of the channels induced by human body movements. The shape of the Doppler spread spectrum is also investigated to describe the relationship of the power and frequency in the frequency domain. All these channel characteristics could be used in the design of communication protocols in BANs, as well as providing features to classify different human body activities. Realistic data extracted from built-in sensors in smart devices were used to assist in modeling and classification of human body movements along with the RF sensors. Variance, energy and frequency domain entropy of the data collected from accelerometer and orientation sensors are pre- processed as features to be used in machine learning algorithms. Activity classifiers with Backpropagation Network, Probabilistic Neural Network, k-Nearest Neighbor algorithm and Support Vector Machine are discussed and evaluated as means to discriminate human body motions. The detection accuracy can be improved with both RF and inertial sensors."

The exceptional properties of nanocrystals (NCs) are strongly influenced by many different characteristics, such as their size and shape, but also by characteristics on the atomic scale, such as their crystal structure, their surface structure, as well as by potential microstructure defects. While the size and shape of NCs are frequently determined in a statistical manner, atomic-scale characteristics are usually quantified only for a small number of individual NCs and thus with limited statistical relevance. Within this work, a characterization workflow was established that is capable of determining relevant NC characteristics simultaneously in a sufficiently detailed and statistically relevant manner. The workflow is based on transmission electron microscopy, networked by a correlative multiscale approach that combines atomic-scale information on NCs obtained from high-resolution imaging with statistical information on NCs obtained from low-resolution imaging, assisted by a semi-automatic segmentation routine. The approach is complemented by other characterization techniques, such as X-ray diffraction, UV-vis spectroscopy, dynamic light scattering, or alternating gradient magnetometry. The general applicability of the developed workflow is illustrated on several examples, i.e., on the classification of Au NCs with different structures, on the statistical determination of the facet configurations of Au nanorods, on the study of the hierarchical structure of multi-core iron oxide nanoflowers and its influence on their magnetic properties, and on the evaluation of the interplay between size, morphology, microstructure defects, and optoelectronic properties of CdSe NCs.:List of abbreviations and symbols 1 Introduction 1.1 Types of nanocrystals 1.2 Characterization of nanocrystals 1.3 Motivation and outline of this thesis 2 Materials and methods 2.1 Nanocrystal synthesis 2.1.1 Au nanocrystals 2.1.2 Au nanorods 2.1.3 Multi-core iron oxide nanoparticles 2.1.4 CdSe nanocrystals 2.2 Nanocrystal characterization 2.2.1 Transmission electron microscopy 2.2.2 X-ray diffraction 2.2.3 UV-vis spectroscopy 2.2.3.1 Au nanocrystals 2.2.3.2 Au nanorods 2.2.3.3 CdSe nanocrystals 2.2.4 Dynamic light scattering 2.2.5 Alternating gradient magnetometry 2.3 Methodical development 2.3.1 Correlative multiscale approach – Statistical information beyond size and shape 2.3.2 Semi-automatic segmentation routine 3 Classification of Au nanocrystals with comparable size but different morphology and defect structure 3.1 Introduction 3.1.1 Morphologies and structures of Au nanocrystals 3.1.2 Localized surface plasmon resonance of Au nanocrystals 3.1.3 Motivation and outline 3.2 Results 3.2.1 Microstructural characteristics of the Au nanocrystals 3.2.2 Insufficiency of two-dimensional size and shape for an unambiguous classification of the Au nanocrystals 3.2.3 Statistical classification of the Au nanocrystals 3.2.4 Advantage of a multidimensional characterization of the Au nanocrystals 3.2.5 Estimation of the density of planar defects in the Au nanoplates 3.3 Discussion 3.4 Conclusions 4 Statistical determination of the facet configurations of Au nanorods 4.1 Introduction 4.1.1 Growth mechanism and facet formation of Au nanorods 4.1.2 Localized surface plasmon resonance of Au nanorods 4.1.3 Catalytic activity of Au nanorods 4.1.4 Motivation and outline 4.2 Results 4.2.1 Statistical determination of the size and shape of the Au nanorods 4.2.2 Microstructural characteristics and facet configurations of the Au nanorods 4.2.3 Statistical determination of the facet configurations of the Au nanorods 4.3 Discussion 4.4 Conclusions 5 Influence of the hierarchical architecture of multi-core iron oxide nanoflowers on their magnetic properties 5.1 Introduction 5.1.1 Phase composition and phase distribution in iron oxide nanoparticles 5.1.2 Magnetic properties of iron oxide nanoparticles 5.1.3 Mono-core vs. multi-core iron oxide nanoparticles 5.1.4 Motivation and outline 5.2 Results 5.2.1 Phase composition, vacancy ordering, and antiphase boundaries 5.2.2 Arrangement and coherence of individual cores within the iron oxide nanoflowers 5.2.3 Statistical determination of particle, core, and shell size 5.2.4 Influence of the coherence of the cores on the magnetic properties 5.3 Discussion 5.4 Conclusions 6 Interplay between size, morphology, microstructure defects, and optoelectronic properties of CdSe nanocrystals 6.1 Introduction 6.1.1 Polymorphism in CdSe nanocrystals 6.1.2 Optoelectronic properties of CdSe nanocrystals 6.1.3 Nucleation, growth, and coarsening of CdSe nanocrystals 6.1.4 Motivation and outline 6.2 Results 6.2.1 Influence of the synthesis temperature on the optoelectronic properties of the CdSe nanocrystals 6.2.2 Microstructural characteristics of the CdSe nanocrystals 6.2.3 Statistical determination of size, shape, and amount of oriented attachment of the CdSe nanocrystals 6.3 Discussion 6.4 Conclusions 7 Summary and outlook References Publications