Geometric data understanding : deriving case specific features

There exists a tradition using precise geometric modeling, where uncertainties in data can be considered noise. Another tradition relies on statistical nature of vast quantity of data, where geometric regularity is intrinsic to data and statistical models usually grasp this level only indirectly. This work focuses on point cloud data of natural resources and the silhouette recognition from video input as two real world examples of problems having geometric content which is intangible at the raw data presentation. This content could be discovered and modeled to some degree by such machine learning (ML) approaches like deep learning, but either a direct coverage of geometry in samples or addition of special geometry invariant layer is necessary. Geometric content is central when there is a need for direct observations of spatial variables, or one needs to gain a mapping to a geometrically consistent data representation, where e.g. outliers or noise can be easily discerned. In this thesis we consider transformation of original input data to a geometric feature space in two example problems. The first example is curvature of surfaces, which has met renewed interest since the introduction of ubiquitous point cloud data and the maturation of the discrete differential geometry. Curvature spectra can characterize a spatial sample rather well, and provide useful features for ML purposes. The second example involves projective methods used to video stereo-signal analysis in swimming analytics. The aim is to find meaningful local geometric representations for feature generation, which also facilitate additional analysis based on geometric understanding of the model. The features are associated directly to some geometric quantity, and this makes it easier to express the geometric constraints in a natural way, as shown in the thesis. Also, the visualization and further feature generation is much easier. Third, the approach provides sound baseline methods to more traditional ML approaches, e.g. neural network methods. Fourth, most of the ML methods can utilize the geometric features presented in this work as additional features.Geometriassa käytetään perinteisesti tarkkoja malleja, jolloin datassa esiintyvät epätarkkuudet edustavat melua. Toisessa perinteessä nojataan suuren datamäärän tilastolliseen luonteeseen, jolloin geometrinen säännönmukaisuus on datan sisäsyntyinen ominaisuus, joka hahmotetaan tilastollisilla malleilla ainoastaan epäsuorasti. Tämä työ keskittyy kahteen esimerkkiin: luonnonvaroja kuvaaviin pistepilviin ja videohahmontunnistukseen. Nämä ovat todellisia ongelmia, joissa geometrinen sisältö on tavoittamattomissa raakadatan tasolla. Tämä sisältö voitaisiin jossain määrin löytää ja mallintaa koneoppimisen keinoin, esim. syväoppimisen avulla, mutta joko geometria pitää kattaa suoraan näytteistämällä tai tarvitaan neuronien lisäkerros geometrisia invariansseja varten. Geometrinen sisältö on keskeinen, kun tarvitaan suoraa avaruudellisten suureiden havainnointia, tai kun tarvitaan kuvaus geometrisesti yhtenäiseen dataesitykseen, jossa poikkeavat näytteet tai melu voidaan helposti erottaa. Tässä työssä tarkastellaan datan muuntamista geometriseen piirreavaruuteen kahden esimerkkiohjelman suhteen. Ensimmäinen esimerkki on pintakaarevuus, joka on uudelleen virinneen kiinnostuksen kohde kaikkialle saatavissa olevan datan ja diskreetin geometrian kypsymisen takia. Kaarevuusspektrit voivat luonnehtia avaruudellista kohdetta melko hyvin ja tarjota koneoppimisessa hyödyllisiä piirteitä. Toinen esimerkki koskee projektiivisia menetelmiä käytettäessä stereovideosignaalia uinnin analytiikkaan. Tavoite on löytää merkityksellisiä paikallisen geometrian esityksiä, jotka samalla mahdollistavat muun geometrian ymmärrykseen perustuvan analyysin. Piirteet liittyvät suoraan johonkin geometriseen suureeseen, ja tämä helpottaa luonnollisella tavalla geometristen rajoitteiden käsittelyä, kuten väitöstyössä osoitetaan. Myös visualisointi ja lisäpiirteiden luonti muuttuu helpommaksi. Kolmanneksi, lähestymistapa suo selkeän vertailumenetelmän perinteisemmille koneoppimisen lähestymistavoille, esim. hermoverkkomenetelmille. Neljänneksi, useimmat koneoppimismenetelmät voivat hyödyntää tässä työssä esitettyjä geometrisia piirteitä lisäämällä ne muiden piirteiden joukkoon

Adaptive Integrated Circuit Design for Variation Resilience and Security

The past few decades witness the burgeoning development of integrated circuit in terms of process technology scaling. Along with the tremendous benefits coming from the scaling, challenges are also presented in various stages. During the design time, the complexity of developing a circuit with millions to billions of smaller size transistors is extended after the variations are taken into account. The difficulty of analyzing these nondeterministic properties makes the allocation scheme of redundant resource hardly work in a cost-efficient way. Besides fabrication variations, analog circuits are suffered from severe performance degradations owing to their physical attributes which are vulnerable to aging effects. As such, the post-silicon calibration approach gains increasing attentions to compensate the performance mismatch. For the user-end applications, additional system failures result from the pirated and counterfeited devices provided by the untrusted semiconductor supply chain. Again analog circuits show their weakness to this threat due to the shortage of piracy avoidance techniques. In this dissertation, we propose three adaptive integrated circuit designs to overcome these challenges respectively. The first one investigates the variability-aware gate implementation with the consideration of the overhead control of adaptivity assignment. This design improves the variation resilience typically for digital circuits while optimizing the power consumption and timing yield. The second design is implemented as a self-validation system for the calibration of diverse analog circuits. The system is completely integrated on chip to enhance the convenience without external assistance. In the last design, a classic analog component is further studied to establish the configurable locking mechanism for analog circuits. The use of Satisfiability Modulo Theories addresses the difficulty of searching the unique unlocking pattern of non-Boolean variables

Modelling of a rope-free passenger transportation system for active cabin vibration damping

Conventional vertical passenger transportation is performed by lifts. Conventional traction-drive electrical lifts use ropes to transfer the rotational motion of an electrical motor into a vertical motion of the cabin. The vertical passenger transportation system discussed in this paper does not use any ropes, the motor directly provides a driving force, which moves the cabin. This new propulsion is realized through an electrical linear motor. The use of the linear motor requires a new design of the passenger transportation system (PTS), which includes reducing the weight of the car through lightweight construction. The reduced stiffness of the lightweight design renders the construction more vulnerable to vibrations. In order to improve ride quality of the transportation system it is necessary to develop new concepts to damp the vibrations. One way to increase stiffness characteristics of the system is to introduce active damping components to be used alongside passive damping components. It is essential to derive a dynamic model of the system in order to design and also later control these damping components in the best possible way. This paper describes the fundamental steps undertaken to derive a dynamic model for designing and controlling active damping components for the new type of vertical PTS. The model is derived as a Multi-Body System (MBS), where the connections between the bodies are modelled as spring damper elements. The derivation of the MBS is demonstrated on a transportation system, consisting of three main components: a sledge, holding the rotor of the linear motor; a mounting frame, which is used to provide support for the cabin; and the actual cabin. The modelling of the propulsion system, thus the electrical part of the PTS, will not be the focus of this work

Evaluating a holistic energy benchmarking parameter of lift systems by using computer simulation

At present, there are benchmarking parameters to assess the energy performance of lifts, e.g. one in Germany adopted by VDI (4707-1/2), one internationally published by ISO (BS EN ISO 25745-2:2015), and the other in Hong Kong adopted by The Hong Kong Special Administrative Region (HKSAR) Government. These parameters are mainly checking the energy consumed by a lift drive without considering real time passenger demands and traffic conditions; the one in Hong Kong pinpointing a fully loaded up-journey under rated speed and the two in Europe pinpointing a round trip, bottom floor to top floor and return with an empty car, though including energy consumed by lighting, displays, ventilation etc. A holistic normalization method by Lam et al [1] was developed a number of years ago by one of the co-authors of this article, which can assess both drive efficiency and traffic control, termed J/kg-m, which is now adopted by the HKSAR Government as a good practice, but not specified in the mandatory code. In Europe, the energy unit of Wh has been used but here, Joule (J), i.e. Ws, is adopted to discriminate the difference between the two concepts. In this article, this parameter is evaluated under different lift traffic scenarios using computer simulation techniques, with an aim of arriving at a reasonable figure for benchmarking an energy efficient lift system with both an efficient drive as well as an efficient supervisory traffic control

A study into the influence of the car geometry on the aerodynamic transient effects arising in a high rise lift installation

One of the main goals in designing a high-speed lift system is developing a more aerodynamically efficient car geometry that guarantees a good ride comfort and reduces the energy consumption. In this study, a three-dimensional computational fluid dynamics (CFD) model has been developed to analyse an unsteady turbulent air flow around two cars moving in a lift shaft. The paper is focused on transient aerodynamic effects arising when two cars pass each other in the same shaft at the same speed. The scenarios considered in the paper involve cars having three different geometries. Aerodynamic forces such as the drag force that occur due to the vertical opposite motions of the cars have been investigated. Attention is paid to the airflow velocity and pressure distribution around the car structures. The flow pattern in the boundary layer around each car has been calculated explicitly to examine the flow separation in the wake region. The results presented in the paper would be useful to guide the lift designers to understand and mitigate the aerodynamic effects arising in the lift shaft

Lattice Boltzmann Methods for Wind Energy Analysis

An estimate of the United States wind potential conducted in 2011 found that the energy available at an altitude of 80 meters is approximately triple the wind energy available 50 meters above ground. In 2012, 43% of all new electricity generation installed in the U.S. (13.1 GW) came from wind power. The majority of this power, 79%, comes from large utility scale turbines that are being manufactured at unprecedented sizes. Existing wind plants operate with a capacity factor of only approximately 30%. Measurements have shown that the turbulent wake of a turbine persists for many rotor diameters, inducing increased vibration and wear on downwind turbines. Power losses can be as high as 20-30% in operating wind plants, due solely to complex wake interactions occurring in wind plant arrays. It is my objective to accurately predict the generation and interaction of turbine wakes and their interaction with downwind turbines and topology by means of numerical simulation with high-performance parallel computer systems. Numerical simulation is already utilized to plan wind plant layouts. However, available computational tools employ severe geometric simplifications to model wake interactions and are geared to providing rough estimates on desktop PCs. A three dimensional simulation tool designed for modern parallel computers based upon lattice Boltzmann methods for fluid-dynamics, a general six-degree-of-freedom motion solver, and foundational beam solvers has been proposed to meet this simulation need. In this text, the software development, verification, and validation are detailed. Fundamental computational fluid dynamics issues of boundary conditions and turbulence modeling are examined through classic cases (Cavity, Jeffery-Hammel, Kelvin-Helmholtz, Pressure wave, Vorticity wave, Backward facing step, Cylinder in cross-flow, Airfoils, Tandem cylinders, and Turbulent flow over a hill) to asses the accuracy and computational cost of developed alternatives. Simulations of canonical motion (falling beam), fluid-structure-interaction cases (Hinged wing and Flexible pendulum), and realistic horizontal axis wind turbine geometries (Vestas v27, NREL 5MW, and MEXICO) are validated against benchmarks and experiments. Results from simulations of the three turbine array at the Scaled Wind Farm Test facility are presented for two steady wind conditions

The Fifth NASA Symposium on VLSI Design

The fifth annual NASA Symposium on VLSI Design had 13 sessions including Radiation Effects, Architectures, Mixed Signal, Design Techniques, Fault Testing, Synthesis, Signal Processing, and other Featured Presentations. The symposium provides insights into developments in VLSI and digital systems which can be used to increase data systems performance. The presentations share insights into next generation advances that will serve as a basis for future VLSI design

Representing information flow in building design process using the parameter-based design structure matrix

Cataloged from PDF version of article.The Architecture/Engineering/Construction (AEC) industry is one of the multidisciplinary domains in which collaboration among related parties is of utmost importance. Despite the intense flow of information between design professionals, there is a lack of research to better understand and manipulate these flows. Most of the current process modeling tools in the AEC industry do not enable analyses of iterative information cycles. Moreover, these tools represent the process at high levels, thus, they are inappropriate for multi-parameter problems like building design. With a view to alleviate these problems, this thesis introduces the use of parameter-based design structure matrix as a process modeling and system analysis tool for building design. The method reveals insights into the process structure, optimum sequence of parameter decisions, iterative cycles and concurrency in the process. A framework for parameter-based DSM applications in building design is proposed and the application of the framework is demonstrated through two case studies on real life building design problems. Keywords: Collaborative Building Design, Design Integration, Design Management, Design Process Modeling, Information Flow, and Parameter-based Design Structure Matrix.Pektaş, Şule TaşlıPh.D

The Sixth Copper Mountain Conference on Multigrid Methods, part 1

The Sixth Copper Mountain Conference on Multigrid Methods was held on 4-9 Apr. 1993, at Copper Mountain, CO. This book is a collection of many of the papers presented at the conference and as such represents the conference proceedings. NASA LaRC graciously provided printing of this document so that all of the papers could be presented in a single forum. Each paper was reviewed by a member of the conference organizing committee under the coordination of the editors. The multigrid discipline continues to expand and mature, as is evident from these proceedings. The vibrancy in this field is amply expressed in these important papers, and the collection clearly shows its rapid trend to further diversity and depth