QuasiGeostrophic Diagnosis of Mixed-Layer Dynamics Embedded in a Mesoscale Turbulent Field

A quasigeostrophic model is developed to diagnose the three-dimensional circulation, including the vertical velocity, in the upper ocean from high-resolution observations of sea surface height and buoyancy. The formulation for the adiabatic component departs from the classical surface quasigeostrophic framework considered before since it takes into account the stratification within the surface mixed layer that is usually much weaker than that in the ocean interior. To achieve this, the model approximates the ocean with two constant stratification layers: a finite-thickness surface layer (or the mixed layer) and an infinitely deep interior layer. It is shown that the leading-order adiabatic circulation is entirely determined if both the surface streamfunction and buoyancy anomalies are considered. The surface layer further includes a diabatic dynamical contribution. Parameterization of diabatic vertical velocities is based on their restoring impacts of the thermal wind balance that is perturbed by turbulent vertical mixing of momentum and buoyancy. The model skill in reproducing the three-dimensional circulation in the upper ocean from surface data is checked against the output of a high-resolution primitive equation numerical simulation

Investigation and prediction of sea level variations in the northern coasts of Persian Gulf using artificial neural network

Sea- level variations have a significant impact on coastal areas. Prediction of sea level variations expected from the pre most critical information needs associated with the sea environment. For this, various methods exist. In this study, on the northern coast of the Persian Gulf have been studied relation to the effectiveness of parameters such as pressure, temperature and wind speed on sea leve and associated with global parameters such as the North Atlantic Oscillation index and NAO index and present statistic models for prediction of sea level. In the next step by using artificial neural network predict sea level for first in this region. Then compared results of the models. Prediction using statistical models estimated in terms correlation coefficient R = 0.84 and root mean square error (RMS) 21.9 cm for the Bushehr station, and R = 0.85 and root mean square error (RMS) 48.4 cm for Rajai station, While neural network used to have 4 layers and each middle layer six neurons is best for prediction and produces the results reliably in terms of correlation coefficient with R = 0.90126 and the root mean square error (RMS) 13.7 cm for the Bushehr station, and R = 0.93916 and the root mean square error (RMS) 22.6 cm for Rajai station. Therefore, the proposed methodology could be successfully used in the study area.

A test method for analysing disturbed ethernet data streams

Ethernet connections, which are widely used in many computer networks, can suffer from electromagnetic interference. Typically, a degradation of the data transmission rate can be perceived as electromagnetic disturbances lead to corruption of data frames on the network media. In this paper a software-based measuring method is presented, which allows a direct assessment of the effects on the link layer. The results can directly be linked to the physical interaction without the influence of software related effects on higher protocol layers. This gives a simple tool for a quantitative analysis of the disturbance of an Ethernet connection based on time domain data. An example is shown, how the data can be used for further investigation of mechanisms and detection of intentional electromagnetic attacks. © 2015 Author(s).

High Precision Plasma Etch for Pattern Transfer: Towards Fluorocarbon Based Atomic Layer Etching

A basic requirement of a plasma etching process is fidelity of the patterned organic materials. In photolithography, a He plasma pretreatment (PPT) based on high ultraviolet and vacuum ultraviolet (UV/VUV) exposure was shown to be successful for roughness reduction of 193nm photoresist (PR). Typical multilayer masks consist of many other organic masking materials in addition to 193nm PR. These materials vary significantly in UV/VUV sensitivity and show, therefore, a different response to the He PPT. A delamination of the nanometer-thin, ion-induced dense amorphous carbon (DAC) layer was observed. Extensive He PPT exposure produces volatile species through UV/VUV induced scissioning. These species are trapped underneath the DAC layer in a subsequent plasma etch (PE), causing a loss of adhesion. Next to stabilizing organic materials, the major goals of this work included to establish and evaluate a cyclic fluorocarbon (FC) based approach for atomic layer etching (ALE) of SiO2 and Si; to characterize the mechanisms involved; and to evaluate the impact of processing parameters. Periodic, short precursor injections allow precise deposition of thin FC films. These films limit the amount of available chemical etchant during subsequent low energy, plasma-based Ar+ ion bombardment, resulting in strongly time-dependent etch rates. In situ ellipsometry showcased the self-limited etching. X-ray photoelectron spectroscopy (XPS) confirms FC film deposition and mixing with the substrate. The cyclic ALE approach is also able to precisely etch Si substrates. A reduced time-dependent etching is seen for Si, likely based on a lower physical sputtering energy threshold. A fluorinated, oxidized surface layer is present during ALE of Si and greatly influences the etch behavior. A reaction of the precursor with the fluorinated substrate upon precursor injection was observed and characterized. The cyclic ALE approach is transferred to a manufacturing scale reactor at IBM Research. Ensuring the transferability to industrial device patterning is crucial for the application of ALE. In addition to device patterning, the cyclic ALE process is employed for oxide removal from Si and SiGe surfaces with the goal of minimal substrate damage and surface residues. The ALE process developed for SiO2 and Si etching did not remove native oxide at the level required. Optimizing the process enabled strong O removal from the surface. Subsequent 90% H2/Ar plasma allow for removal of C and F residues.

Physical Design Methodologies for Low Power and Reliable 3D ICs

As the semiconductor industry struggles to maintain its momentum down the path following the Moore's Law, three dimensional integrated circuit (3D IC) technology has emerged as a promising solution to achieve higher integration density, better performance, and lower power consumption. However, despite its significant improvement in electrical performance, 3D IC presents several serious physical design challenges. In this dissertation, we investigate physical design methodologies for 3D ICs with primary focus on two areas: low power 3D clock tree design, and reliability degradation modeling and management. Clock trees are essential parts for digital system which dissipate a large amount of power due to high capacitive loads. The majority of existing 3D clock tree designs focus on minimizing the total wire length, which produces sub-optimal results for power optimization. In this dissertation, we formulate a 3D clock tree design flow which directly optimizes for clock power. Besides, we also investigate the design methodology for clock gating a 3D clock tree, which uses shutdown gates to selectively turn off unnecessary clock activities. Different from the common assumption in 2D ICs that shutdown gates are cheap thus can be applied at every clock node, shutdown gates in 3D ICs introduce additional control TSVs, which compete with clock TSVs for placement resources. We explore the design methodologies to produce the optimal allocation and placement for clock and control TSVs so that the clock power is minimized. We show that the proposed synthesis flow saves significant clock power while accounting for available TSV placement area. Vertical integration also brings new reliability challenges including TSV's electromigration (EM) and several other reliability loss mechanisms caused by TSV-induced stress. These reliability loss models involve complex inter-dependencies between electrical and thermal conditions, which have not been investigated in the past. In this dissertation we set up an electrical/thermal/reliability co-simulation framework to capture the transient of reliability loss in 3D ICs. We further derive and validate an analytical reliability objective function that can be integrated into the 3D placement design flow. The reliability aware placement scheme enables co-design and co-optimization of both the electrical and reliability property, thus improves both the circuit's performance and its lifetime. Our electrical/reliability co-design scheme avoids unnecessary design cycles or application of ad-hoc fixes that lead to sub-optimal performance. Vertical integration also enables stacking DRAM on top of CPU, providing high bandwidth and short latency. However, non-uniform voltage fluctuation and local thermal hotspot in CPU layers are coupled into DRAM layers, causing a non-uniform bit-cell leakage (thereby bit flip) distribution. We propose a performance-power-resilience simulation framework to capture DRAM soft error in 3D multi-core CPU systems. In addition, a dynamic resilience management (DRM) scheme is investigated, which adaptively tunes CPU's operating points to adjust DRAM's voltage noise and thermal condition during runtime. The DRM uses dynamic frequency scaling to achieve a resilience borrow-in strategy, which effectively enhances DRAM's resilience without sacrificing performance. The proposed physical design methodologies should act as important building blocks for 3D ICs and push 3D ICs toward mainstream acceptance in the near future.

Security Evaluation of Substation Network Architectures

In recent years, security of industrial control systems has been the main research focus due to the potential cyber-attacks that can impact the physical operations. As a result of these risks, there has been an urgent need to establish a stronger security protection against these threats. Conventional firewalls with stateful rules can be implemented in the critical cyberinfrastructure environment which might require constant updates. Despite the ongoing effort to maintain the rules, the protection mechanism does not restrict malicious data flows and it poses the greater risk of potential intrusion occurrence. The contributions of this thesis are motivated by the aforementioned issues which include a systematic investigation of attack-related scenarios within a substation network in a reliable sense. The proposed work is two-fold: (i) system architecture evaluation and (ii) construction of attack tree for a substation network. Cyber-system reliability remains one of the important factors in determining the system bottleneck for investment planning and maintenance. It determines the longevity of the system operational period with or without any disruption. First, a complete enumeration of existing implementation is exhaustively identified with existing communication architectures (bidirectional) and new ones with strictly unidirectional. A detailed modeling of the extended 10 system architectures has been evaluated. Next, attack tree modeling for potential substation threats is formulated. This quantifies the potential risks for possible attack scenarios within a network or from the external networks. The analytical models proposed in this thesis can serve as a fundamental development that can be further researched.

Strategic Optimization Techniques For FRTU Deployment and Chip Physical Design

Combinatorial optimization is a complex engineering subject. Although formulation often depends on the nature of problems that differs from their setup, design, constraints, and implications, establishing a unifying framework is essential. This dissertation investigates the unique features of three important optimization problems that can span from small-scale design automation to large-scale power system planning: (1) Feeder remote terminal unit (FRTU) planning strategy by considering the cybersecurity of secondary distribution network in electrical distribution grid, (2) physical-level synthesis for microfluidic lab-on-a-chip, and (3) discrete gate sizing in very-large-scale integration (VLSI) circuit. First, an optimization technique by cross entropy is proposed to handle FRTU deployment in primary network considering cybersecurity of secondary distribution network. While it is constrained by monetary budget on the number of deployed FRTUs, the proposed algorithm identi?es pivotal locations of a distribution feeder to install the FRTUs in different time horizons. Then, multi-scale optimization techniques are proposed for digital micro?uidic lab-on-a-chip physical level synthesis. The proposed techniques handle the variation-aware lab-on-a-chip placement and routing co-design while satisfying all constraints, and considering contamination and defect. Last, the first fully polynomial time approximation scheme (FPTAS) is proposed for the delay driven discrete gate sizing problem, which explores the theoretical view since the existing works are heuristics with no performance guarantee. The intellectual contribution of the proposed methods establishes a novel paradigm bridging the gaps between professional communities.

Host and Network Optimizations for Performance Enhancement and Energy Efficiency in Data Center Networks

Modern data centers host hundreds of thousands of servers to achieve economies of scale. Such a huge number of servers create challenges for the data center network (DCN) to provide proportionally large bandwidth. In addition, the deployment of virtual machines (VMs) in data centers raises the requirements for efficient resource allocation and find-grained resource sharing. Further, the large number of servers and switches in the data center consume significant amounts of energy. Even though servers become more energy efficient with various energy saving techniques, DCN still accounts for 20% to 50% of the energy consumed by the entire data center. The objective of this dissertation is to enhance DCN performance as well as its energy efficiency by conducting optimizations on both host and network sides. First, as the DCN demands huge bisection bandwidth to interconnect all the servers, we propose a parallel packet switch (PPS) architecture that directly processes variable length packets without segmentation-and-reassembly (SAR). The proposed PPS achieves large bandwidth by combining switching capacities of multiple fabrics, and it further improves the switch throughput by avoiding padding bits in SAR. Second, since certain resource demands of the VM are bursty and demonstrate stochastic nature, to satisfy both deterministic and stochastic demands in VM placement, we propose the Max-Min Multidimensional Stochastic Bin Packing (M3SBP) algorithm. M3SBP calculates an equivalent deterministic value for the stochastic demands, and maximizes the minimum resource utilization ratio of each server. Third, to provide necessary traffic isolation for VMs that share the same physical network adapter, we propose the Flow-level Bandwidth Provisioning (FBP) algorithm. By reducing the flow scheduling problem to multiple stages of packet queuing problems, FBP guarantees the provisioned bandwidth and delay performance for each flow. Finally, while DCNs are typically provisioned with full bisection bandwidth, DCN traffic demonstrates fluctuating patterns, we propose a joint host-network optimization scheme to enhance the energy efficiency of DCNs during off-peak traffic hours. The proposed scheme utilizes a unified representation method that converts the VM placement problem to a routing problem and employs depth-first and best-fit search to find efficient paths for flows.

Approaches to Provisioning Network Topology of Virtual Machines in Cloud Systems

The current infrastructure as a service (IaaS) cloud systems, allow users to load their own virtual machines. However, most of these systems do not provide users with an automatic mechanism to load a network topology of virtual machines. In order to specify and implement the network topology, we use software switches and routers as network elements. Before running a group of virtual machines, the user needs to set up the system once to specify a network topology of virtual machines. Then, given the user’s request for running a specific topology, our system loads the appropriate virtual machines (VMs) and also runs separated VMs as software switches and routers. Furthermore, we have developed a manager that handles physical hardware failure situations. This system has been designed in order to allow users to use the system without knowing all the internal technical details.

Structural Data Acquisition Using Sensor Network

The development cost of any civil infrastructure is very high; during its life span, the civil structure undergoes a lot of physical loads and environmental effects which damage the structure. Failing to identify this damage at an early stage may result in severe property loss and may become a potential threat to people and the environment. Thus, there is a need to develop effective damage detection techniques to ensure the safety and integrity of the structure. One of the Structural Health Monitoring methods to evaluate a structure is by using statistical analysis. In this study, a civil structure measuring 8 feet in length, 3 feet in diameter, embedded with thermocouple sensors at 4 different levels is analyzed under controlled and variable conditions. With the help of statistical analysis, possible damage to the structure was analyzed. The analysis could detect the structural defects at various levels of the structure.

Engineered zeolitic materials: synthesis and application

Les zéolithes étant des matériaux cristallins microporeux ont démontré leurs potentiels et leur polyvalence dans un nombre très important d’applications. Les propriétés uniques des zéolithes ont poussé les chercheurs à leur trouver constamment de nouvelles utilités pour tirer le meilleur parti de ces matériaux extraordinaires. Modifier les caractéristiques des zéolithes classiques ou les combiner en synergie avec d’autres matériaux se trouvent être deux approches viables pour trouver encore de nouvelles applications. Dans ce travail de doctorat, ces deux approches ont été utilisées séparément, premièrement avec la modification morphologique de la ZSM-12 et deuxièmement lors de la formation des matériaux de type coeur/coquille (silice mésoporeuses@silicalite-1). La ZSM-12 est une zéolithe à haute teneur en silice qui a récemment attiré beaucoup l’attention par ses performances supérieures dans les domaines de l’adsorption et de la catalyse. Afin de synthétiser la ZSM-12 avec une pureté élevée et une morphologie contrôlée, la cristallisation de la zéolithe ZSM-12 a été étudiée en détail en fonction des différents réactifs chimiques disponibles (agent directeur de structure, types de silicium et source d’aluminium) et des paramètres réactionnels (l’alcalinité, ratio entre Na, Al et eau). Les résultats présentés dans cette étude ont montré que, contrairement à l’utilisation du structurant organique TEAOH, en utilisant un autre structurant, le MTEAOH, ainsi que le Al(o-i-Pr)3, cela a permis la formation de monocristaux ZSM-12 monodisperses dans un temps plus court. L’alcalinité et la teneur en Na jouent également des rôles déterminants lors de ces synthèses. Les structures de types coeur/coquille avec une zéolithe polycristalline silicalite-1 en tant que coquille, entourant un coeur formé par une microsphère de silice mésoporeuse (tailles de particules de 1,5, 3 et 20-45 μm) ont été synthétisés soit sous forme pure ou chargée avec des espèces hôtes métalliques. Des techniques de nucléations de la zéolithe sur le noyau ont été utilisées pour faire croitre la coquille de façon fiable et arriver à former ces matériaux. C’est la qualité des produits finaux en termes de connectivité des réseaux poreux et d’intégrité de la coquille, qui permet d’obtenir une stéréosélectivité. Ceci a été étudié en faisant varier les paramètres de synthèse, par exemple, lors de prétraitements qui comprennent ; la modification de surface, la nucléation, la calcination et le nombre d’étapes secondaires de cristallisation hydrothermale. En fonction de la taille du noyau mésoporeux et des espèces hôtes incorporées, l’efficacité de la nucléation se révèle être influencée par la technique de modification de surface choisie. En effet, les microsphères de silice mésoporeuses contenant des espèces métalliques nécessitent un traitement supplémentaire de fonctionnalisation chimique sur leur surface externe avec des précurseurs tels que le (3-aminopropyl) triéthoxysilane (APTES), plutôt que d’utiliser une modification de surface avec des polymères ioniques. Nous avons également montré que, selon la taille du noyau, de deux à quatre traitements hydrothermaux rapides sont nécessaires pour envelopper totalement le noyau sans aucune agrégation et sans dissoudre le noyau. De tels matériaux avec une enveloppe de tamis moléculaire cristallin peuvent être utilisés dans une grande variété d’applications, en particulier pour de l’adsorption et de la catalyse stéréo-sélective. Ce type de matériaux a été étudié lors d’une série d’expériences sur l’adsorption sélective du glycérol provenant de biodiesel brut avec des compositions différentes et à des températures différentes. Les résultats obtenus ont été comparés à ceux utilisant des adsorbants classiques comme par exemple du gel de sphères de silice mésoporeux, des zéolithes classiques, silicalite-1, Si-BEA et ZSM-5(H+), sous forment de cristaux, ainsi que le mélange physique de ces matériaux références, à savoir un mélange silicalite-1 et le gel de silice sphères. Bien que le gel de sphères de silice mésoporeux ait montré une capacité d’adsorption de glycérol un peu plus élevée, l’étude a révélé que les adsorbants mésoporeux ont tendance à piéger une quantité importante de molécules plus volumineuses, telles que les « fatty acid methyl ester » (FAME), dans leur vaste réseau de pores. Cependant, dans l’adsorbant à porosité hiérarchisée, la fine couche de zéolite silicalite-1 microporeuse joue un rôle de membrane empêchant la diffusion des molécules de FAME dans les mésopores composant le noyau/coeur de l’adsorbant composite, tandis que le volume des mésopores du noyau permet l’adsorption du glycérol sous forme de multicouches. Finalement, cette caractéristique du matériau coeur/coquille a sensiblement amélioré les performances en termes de rendement de purification et de capacité d’adsorption, par rapport à d’autres adsorbants classiques, y compris le gel de silice mésoporeuse et les zéolithes.

Photoactive (supra)molecular devices in double layer membranes

Biological systems are complex and highly organized architectures governed by non-covalent interactions responsible for the regulation of essential tasks in all living organisms. These systems are a constant source of inspiration for supramolecular chemists aiming to design multicomponent molecular assemblies able to perform elaborated tasks, thanks to the role and action of the components that constitute them. Artificial supramolecular systems exploit non-covalent interactions to mimic naturally occurring events. In this context, stimuli-responsive supramolecular systems have attracted attention due to the possibility to control macroscopic effects through modifications at the nanoscale. This thesis is divided in three experimental chapters, characterized by a progressive increase in molecular complexity. Initially, the preparation and studies of liposomes functionalized with a photoactive guest such as azobenzene in the bilayer were tackled, in order to evaluate the effect of such photochrome on the vesicle properties. Subsequently, the synthesis and studies of thread-like molecules comprising an azobenzene functionality was reported. Such molecules were conceived to be intercalated in the bilayer membrane of liposomes with the aim to be used as components for photoresponsive transmembrane molecular pumps. Finally, a [3]rotaxane was developed and studied in solution. This system is composed of two crown ether rings interlocked with an axle containing three recognition sites for the macrocycles, i.e. two pH-switchable ammonium stations and a permanent triazolium station. Such molecule was designed to achieve a change in the ratio between the recognition sites and the crown ethers as a consequence of acid-base inputs. This leads to the formation of rotaxanes containing a number of recognition sites respectively larger, equal or lower than the number of interlocked rings and connected by a network of acid-base reactions.

Role of non-coding RNA alterations in melanoma

Cutaneous melanoma (CM) is a potentially lethal form of skin cancer and its most important histopathologic factor for staging is Breslow thickness (BT). Its correct determination is fundamental for pathologists. A deeper understanding of the molecular processes guiding CM pathogenesis could improve diagnosis, treatment and prognosis. MicroRNAs (miRNAs) play a key role in CM biology. The firs aim was to investigate miRNA expression in reference to BT assessment. We found that the combined miRNA expression of miR-21-5p and miR-146a-5p above or below 1.5 was significantly associated with overall survival and successfully identified all superficially spreading melanoma (SSM) patients with relapsing suggesting that the combined assessment of these miRNAs expression could aid in SSM staging. Secondly, we focus on multiple primary melanoma (MPM) patients, which develop multiple primary melanomas in their lifetime, and represent a model of high-risk CM occurrence. We explored the miRNome of single CM and MPM: CM and MPM present several dysregulated miRNAs, including key miRNAs involved in epithelial-mesenchymal transition. A different miRNA profile was observed between 1st and 2nd melanoma from the same patient. MiRNA target analysis revealed a more differentiated and less invasive status of MPMs compared to CMs. This characterization of the miRNA regulatory network of MPMs highlights molecular features differentiating this subtype from CM. Recently, NGS experiments revealed the existence of miRNA variants (isomiRs) with different length and sequence. We identified a shorter 3’isoform as tenfold over-represented compared to the canonical form of miR-125a-5p. Target analysis revealed that miRNA shortening could change the pattern of target gene regulation. Finally, we study miRNA and isomiR dysregulation in benign nevi (BN) and CM and in CM and melanoma metastasis. The reported non-random dysregulation of specific isomiRs contributes to the understanding of the complex melanoma pathogenesis and serves as the basis for further functional studies.

Automated service provisioning in programmable network infrastructures

Modern networks are undergoing a fast and drastic evolution, with software taking a more predominant role. Virtualization and cloud-like approaches are replacing physical network appliances, reducing the management burden of the operators. Furthermore, networks now expose programmable interfaces for fast and dynamic control over traffic forwarding. This evolution is backed by standard organizations such as ETSI, 3GPP, and IETF. This thesis will describe which are the main trends in this evolution. Then, it will present solutions developed during the three years of Ph.D. to exploit the capabilities these new technologies offer and to study their possible limitations to push further the state-of-the-art. Namely, it will deal with programmable network infrastructure, introducing the concept of Service Function Chaining (SFC) and presenting two possible solutions, one with Openstack and OpenFlow and the other using Segment Routing and IPv6. Then, it will continue with network service provisioning, presenting concepts from Network Function Virtualization (NFV) and Multi-access Edge Computing (MEC). These concepts will be applied to network slicing for mission-critical communications and Industrial IoT (IIoT). Finally, it will deal with network abstraction, with a focus on Intent Based Networking (IBN). To summarize, the thesis will include solutions for data plane programming with evaluation on well-known platforms, performance metrics on virtual resource allocations, novel practical application of network slicing on mission-critical communications, an architectural proposal and its implementation for edge technologies in Industrial IoT scenarios, and a formal definition of intent using a category theory approach.

Optimizing AI at the Edge: from network topology design to MCU deployment

The first topic analyzed in the thesis will be Neural Architecture Search (NAS). I will focus on two different tools that I developed, one to optimize the architecture of Temporal Convolutional Networks (TCNs), a convolutional model for time-series processing that has recently emerged, and one to optimize the data precision of tensors inside CNNs. The first NAS proposed explicitly targets the optimization of the most peculiar architectural parameters of TCNs, namely dilation, receptive field, and the number of features in each layer. Note that this is the first NAS that explicitly targets these networks. The second NAS proposed instead focuses on finding the most efficient data format for a target CNN, with the granularity of the layer filter. Note that applying these two NASes in sequence allows an "application designer" to minimize the structure of the neural network employed, minimizing the number of operations or the memory usage of the network. After that, the second topic described is the optimization of neural network deployment on edge devices. Importantly, exploiting edge platforms' scarce resources is critical for NN efficient execution on MCUs. To do so, I will introduce DORY (Deployment Oriented to memoRY) -- an automatic tool to deploy CNNs on low-cost MCUs. DORY, in different steps, can manage different levels of memory inside the MCU automatically, offload the computation workload (i.e., the different layers of a neural network) to dedicated hardware accelerators, and automatically generates ANSI C code that orchestrates off- and on-chip transfers with the computation phases. On top of this, I will introduce two optimized computation libraries that DORY can exploit to deploy TCNs and Transformers on edge efficiently. I conclude the thesis with two different applications on bio-signal analysis, i.e., heart rate tracking and sEMG-based gesture recognition.