A Systems Methodology for Measuring Operational Organization Effectiveness: A Study of the Original Equipment Computer Manufacturing Industry, 1948 to 2001

Optimizing operational organizational effectiveness is the central, although often unstated, goal of engineering management and systems engineering research and applications. Two fundamental problems remain to be addressed in pursuit of this goal. First, despite over fifty years of research in various disciplines, there is still no universally accepted definition of organizational effectiveness. Second, no methodology exists to identify the domains, dimensions, and determinants of operational organizational effectiveness and dynamically model operational organizational effectiveness within a given population. This research synthesizes a systems engineering methodology for identifying the domains, dimensions, and determinants of and dynamically modeling operational organizational effectiveness for an identified population. First, the methodology takes the concept of the niche from ecological theory as its definition of effectiveness. Specifically, an organization that is able to sustain a real nonnegative growth rate in its niche dimension under a set of competitive conditions is defined as being effective. Next, the methodology integrates organizational ecology and open systems theories, principles, and models into a unified systemic model of environmental and organizational domains and dimensions that provide the structure for research into the determinants of organizational effectiveness. Based on this model, the methodology gathers observable data on hypothesized determinants of effectiveness and applies event history survival and effectiveness analyses to identify the statistically significant determinants. The methodology\u27s final two steps are to construct and validate a dynamic simulation model of organizational effectiveness based on the identified determinants and to perform sensitivity analyses

Understanding Quantum Technologies 2022

Understanding Quantum Technologies 2022 is a creative-commons ebook that provides a unique 360 degrees overview of quantum technologies from science and technology to geopolitical and societal issues. It covers quantum physics history, quantum physics 101, gate-based quantum computing, quantum computing engineering (including quantum error corrections and quantum computing energetics), quantum computing hardware (all qubit types, including quantum annealing and quantum simulation paradigms, history, science, research, implementation and vendors), quantum enabling technologies (cryogenics, control electronics, photonics, components fabs, raw materials), quantum computing algorithms, software development tools and use cases, unconventional computing (potential alternatives to quantum and classical computing), quantum telecommunications and cryptography, quantum sensing, quantum technologies around the world, quantum technologies societal impact and even quantum fake sciences. The main audience are computer science engineers, developers and IT specialists as well as quantum scientists and students who want to acquire a global view of how quantum technologies work, and particularly quantum computing. This version is an extensive update to the 2021 edition published in October 2021.Comment: 1132 pages, 920 figures, Letter forma

Wireless interference networks with limited feedback

Wir betrachten das Problem der Akquirierung von Kanalzustandsinformationen an den Sendern von drahtlosen Netzwerken und entwickeln Feedbackverfahren und Sendestrategien für verschiedene Netzwerk Architekturen. Die entwickelten Verfahren werden analysiert und die Skalierung der Performance des Gesamtsystems anhand bestimmter Systemparameter bestimmt. Zuerst betrachten wir eine einzelne Zelle eines zellularen Systems und nehmen an, dass die Beamformingvektoren durch ein festes Codebuch vorgegeben sind. Wir entwickeln und analysieren ein neues Feedbackverfahren, dass Flexibilität und Robustheit vereint und dadurch effiziente und zuverlässige Kommunikation mit den Empfängern ermöglicht. Eine Analyse des Verfahrens zeigt, dass die Skalierung des Ratenverlustes durch quantisierte Kanalzustandsinformation besser ist als bei vergleichbaren Verfahren. Für das Feedbackverfahren wird ein spezieller Algorithmus entwickelt der es ermöglicht Codebücher für verschiedene Kanalmodelle zu generieren und zu optimieren. Die analytischen Ergebnisse werden durch Simulationen validiert und bestätigen einen Gewinn gegenüber vergleichbaren Verfahren. Anschließend betrachten wir zellulare Systeme mit mehreren Zellen. Wir charakterisieren die Freiheitsgrade (degrees of freedom) unter verschiedenen Annahmen über das Kanalmodell. Des weiteren entwickeln wir verschiedene Algorithmen, die die optimalen Freiheitsgrade erreichen können. Anschließend wird ein Feedbackverfahren entwickelt, dass den Feedbackaufwand für die entwickelten Algorithmen signifikant reduziert. Wir analysieren eine breite Klasse von zellularen Systemen die beliebige koordinierte Sendestrategien verwenden. Für diese Klasse von Systemen leiten wir die Skalierung des Ratenverlustes relativ zum Feedbackaufwand her. Abschließend zeigen wir, wie die analytischen Ergebnisse auf das entwickelte Feedbackverfahren angewendet werden können. Im letzten Kapitel entwickeln wir ein Framework, dass das Potenzial von Compressed Sensing nutzt um den Messaufwand und Feedbackaufwand in zellularen Systemen mit vielen Teilnehmern signifikant zu reduzieren. Das Framework ermöglicht es die Datenraten der Nutzer innerhalb gegebener Fehlerschranken zu schätzen. Grundlage ist neben Compressed Sensing ein neues Messverfahren, dass die Überlagerung von Signalen im Kanal nutzt, um zufällige nicht adaptive Messungen der Kanalkoeffizienten am Empfänger zu ermöglichen. Diese Messungen werden zu einer zentralen Steuereinheit übertragen und dort dekodiert. Wir analysieren die Genauigkeit der Rekonstruktion für einen linearen und einen nicht-linearen Dekodierer und leiten die Skalierung mit der Anzahl der Messungen her. Abschließend zeigen wir, wie der entwickelte Ansatz in zellularen Systemen angewendet werden kann.We consider the problem of acquiring accurate channel state information at the transmitters of a wireless network. We develop different feedback and transmit strategies for different network architectures and analyze their performance. First, we consider a single cell of cellular system and assume that the beamforming vectors are given by a fixed transmit codebook. We develop and analyze a new feedback and transmit strategy which combines flexibility and robustness needed for efficient and reliable communication. We prove that it has better scaling properties compared to classical results on the limited feedback problem in the broadcast channel and that this benefit improves with an increasing number of transmit antennas. We show how feedback codebooks can be designed for different propagation environments. Link level and system level simulations sustain the analytic results showing performance gains of up to 50 % or 70 % compared to zeroforcing when using multiple antennas at the base station and multiple antennas or a single antenna at the terminals, respectively. We characterize the degrees of freedom (i.e. the multiplexing gain) of multi-cellular systems under different assumptions on the channel model and for different system setups. We propose different algorithms that possibly achieve the optimal degrees of freedom. The first algorithm aims on aligning the interference at each receiver in a subspace of the available receive space. Our second algorithm aims on directly maximizing the signal-to-interference-plus-noise ratio (SINR) of all receivers. By allowing symbol extensions over time or frequency and including a user selection we are able to achieve the alignment of interference for many system setups and exploit multi-user diversity. For coordinated transmit strategies we find the scaling of the performance loss with the feedback load. A distributed interference alignment algorithm is introduced. The algorithm makes efficient use of quantized channel state information and significantly reduces the feedback overhead. We develop a framework that we call compressive rate estimation. To this end, we assume that the composite channel gain matrix (i.e. the matrix of all channel gains between all network nodes) is compressible which means it can be approximated by a sparse or low rank representation. We develop a sensing protocol that exploits the superposition principle of the wireless channel and enables the receiving nodes to obtain non-adaptive random measurements of columns of the composite channel matrix. The random measurements are fed back to a central controller who decodes the composite channel gain matrix (or parts of it) and estimates individual user rates. We analyze the rate loss for a linear and a non-linear decoder and find the scaling laws according to the number of non-adaptive measurements

Leadership for resilient urban systems : two cases in Asheville, NC

The role of leadership in the resilience of urban systems is poorly understood. Leadership can be thought of as a complex practice, where the functions of leadership emerge from the relationships amongst actors, systems and institutions. There are five theorized functions of Complexity Leadership: Community Building, Information Gathering, Information Using, Generative and Administrative. The purpose of this dissertation was to explore the connection, if any, between Complexity Leadership and the resilience of urban systems.  This was explored in the context of two cases in Asheville, NC: the Residents' Council of Public Housing of Asheville and Rainbow Community School. The Residents' Council is a non profit that represents residents’ interests; Public Housing in Asheville is a typical for a 100k small city. The case documents some of the Residents' Council's attempt to adopt Dynamic Governance, a set of self-organizing governance practices. Rainbow Community School is a private k-8 school, recognized internationally as an Ashoka Change-Maker School for its innovative model of education. Data was collected through a hybrid of traditional ethnographic techniques and distributed ethnography. Data was analyzed inductively, using a combination of qualitative analysis and set theoretic analysis. The research generated findings of three kinds.  First, complexity leadership was necessary but not sufficient to account for the observed resilience qualities. To explain the observed coordination across other functions and capacity to engage with mystery , this research theorizes an additional function of Complexity Leadership—a Spiritual function. Second, individual strategic leadership played a role in fostering resilience through strengthening weak functions of complexity leadership. Third, resilience qualities emerged over time through the process of Panarchy. Spiritual leadership plays a role in fostering Panarchy through creating conditions for cross-scale resonance. The dissertation closes with the contributions of this research to theory, practice, and methods for research in complex urban systems.Community and Regional Plannin