Global ETD Search

311	The relative impact of public and private investment on economic growth: the tale of four Southern African economies Makuyana, Garikai 11 1900 (has links) The study has empirically examined the relative impact of public and private investment on economic growth and has also tested the crowding in or crowding out effect of public investment on private investment in four Southern African economies – Malawi, South Africa, Zambia and Zimbabwe. The analysis used annual time-series data covering the period from 1970 to 2014. The study provides new evidence to contribute firstly to the current debate regarding the relative importance of public and private investment in economic growth processes and secondly, on whether public investment crowds in or crowds out private investment in the selected countries. For this purpose, the study employed two empirical models using the recently developed Autoregressive Distributed Lag (ARDL)-bounds testing approach to cointegration. Model 1 examines the relative impact of public and private investment on economic growth while Model 2 investigates the crowding in or crowding out effect of gross public investment and its subcomponents (infrastructural and non-infrastructural) on private investment. The results of Model 1 largely supported the private investment-led economic growth strategy. In all the study countries, private investment had a positive impact on economic growth. Also, public investment positively contributed to economic growth in Zimbabwe, but in the remaining study countries, public investment had a negative relationship with economic growth. Results from Model 2 reveal that: (i) the crowding out effect of gross public investment on private investment predominates in the study countries; (ii) infrastructural public investment crowds in private investment in South Africa and Zimbabwe in the long run while it crowds out private investment in Malawi and Zambia in the short run; and (iii) non-infrastructural public investment crowds out private investment in South Africa and Zambia. On balance, the results from Model 2 show that public investment tends to crowd out private investment in the selected countries and this further underscore the importance of the private sector-led economic growth processes in the study countries. / Economics / D. Phil. (Economics) Public invesment Private investment Economic growth Crowding out effect Crowding in effect Malawi South Africa Zambia Zimbabwe ADRL-Bounds Testing Approach 332.672520968 Infrastructure (Economics) -- Zambia Infrastructure (Economics) -- Zimbabwe Infrastructure (Economics) -- Malawi
312	Temporal Variations in the Compliance of Gas Hydrate Formations Roach, Lisa Aretha Nyala 20 March 2014 (has links) Seafloor compliance is a non-intrusive geophysical method sensitive to the shear modulus of the sediments below the seafloor. A compliance analysis requires the computation of the frequency dependent transfer function between the vertical stress, produced at the seafloor by the ultra low frequency passive source-infra-gravity waves, and the resulting displacement, related to velocity through the frequency. The displacement of the ocean floor is dependent on the elastic structure of the sediments and the compliance function is tuned to different depths, i.e., a change in the elastic parameters at a given depth is sensed by the compliance function at a particular frequency. In a gas hydrate system, the magnitude of the stiffness is a measure of the quantity of gas hydrates present. Gas hydrates contain immense stores of greenhouse gases making them relevant to climate change science, and represent an important potential alternative source of energy. Bullseye Vent is a gas hydrate system located in an area that has been intensively studied for over 2 decades and research results suggest that this system is evolving over time. A partnership with NEPTUNE Canada allowed for the investigation of this possible evolution. This thesis describes a compliance experiment configured for NEPTUNE Canada’s seafloor observatory and its failure. It also describes the use of 203 days of simultaneously logged pressure and velocity time-series data, measured by a Scripps differential pressure gauge, and a Güralp CMG-1T broadband seismometer on NEPTUNE Canada’s seismic station, respectively, to evaluate variations in sediment stiffness near Bullseye. The evaluation resulted in a (- 4.49 x10-3± 3.52 x 10-3) % change of the transfer function of 3rd October, 2010 and represents a 2.88% decrease in the stiffness of the sediments over the period. This thesis also outlines a new algorithm for calculating the static compliance of isotropic layered sediments. SEAFLOOR COMPLIANCE GAS HYDRATES BULLSEYE VENT TREND ANALYSIS SENSITIVITY ANALYSIS EIGENPARAMETER ANALYSIS HYDRATE MASS VARIATION LONG TERM TRENDS IN HYDRATE MASS MODIFIED YORK METHOD MARINE GEOPHYISCS MARINE SEDIMENT NEPTUNE CANADA SHEAR MODULUS GAS HYDRATE CONCENTRATIONS CASCADIA MARGIN MARINE GAS HYDRATES INFRA-GRAVITY WAVES SEISMOMETERS SCRIPPS DIFFERENTIAL PRESSURE GAUGE SCRIPPS DPG ODP SITE 889 BROADBAND SEISMOMETER gPhone DGP calibration Bottom Pressure Recorder Guralp CGM-1T Coherence transfer function bounds f-test bootstrapping wave propagation matrix static solution ocean bottom seismometer tsunami earthquakes Modified York least squares temporal variations linear trend in gas hydrates Power spectral densities 1D compliance solution 1D compliance algorithm seafloor compliance instrumentation Micro-g gravitimeter triple phase boundary equation ultra-low frequency seismics seafloor pressure spectrum seafloor gravity spectrum pacific ocean off-shore British Columbia seafloor observatory static compliance of layered structures geophysics gas hydrate characterization 0373
313	Temporal Variations in the Compliance of Gas Hydrate Formations Roach, Lisa Aretha Nyala 20 March 2014 (has links) Seafloor compliance is a non-intrusive geophysical method sensitive to the shear modulus of the sediments below the seafloor. A compliance analysis requires the computation of the frequency dependent transfer function between the vertical stress, produced at the seafloor by the ultra low frequency passive source-infra-gravity waves, and the resulting displacement, related to velocity through the frequency. The displacement of the ocean floor is dependent on the elastic structure of the sediments and the compliance function is tuned to different depths, i.e., a change in the elastic parameters at a given depth is sensed by the compliance function at a particular frequency. In a gas hydrate system, the magnitude of the stiffness is a measure of the quantity of gas hydrates present. Gas hydrates contain immense stores of greenhouse gases making them relevant to climate change science, and represent an important potential alternative source of energy. Bullseye Vent is a gas hydrate system located in an area that has been intensively studied for over 2 decades and research results suggest that this system is evolving over time. A partnership with NEPTUNE Canada allowed for the investigation of this possible evolution. This thesis describes a compliance experiment configured for NEPTUNE Canada’s seafloor observatory and its failure. It also describes the use of 203 days of simultaneously logged pressure and velocity time-series data, measured by a Scripps differential pressure gauge, and a Güralp CMG-1T broadband seismometer on NEPTUNE Canada’s seismic station, respectively, to evaluate variations in sediment stiffness near Bullseye. The evaluation resulted in a (- 4.49 x10-3± 3.52 x 10-3) % change of the transfer function of 3rd October, 2010 and represents a 2.88% decrease in the stiffness of the sediments over the period. This thesis also outlines a new algorithm for calculating the static compliance of isotropic layered sediments. SEAFLOOR COMPLIANCE GAS HYDRATES BULLSEYE VENT TREND ANALYSIS SENSITIVITY ANALYSIS EIGENPARAMETER ANALYSIS HYDRATE MASS VARIATION LONG TERM TRENDS IN HYDRATE MASS MODIFIED YORK METHOD MARINE GEOPHYISCS MARINE SEDIMENT NEPTUNE CANADA SHEAR MODULUS GAS HYDRATE CONCENTRATIONS CASCADIA MARGIN MARINE GAS HYDRATES INFRA-GRAVITY WAVES SEISMOMETERS SCRIPPS DIFFERENTIAL PRESSURE GAUGE SCRIPPS DPG ODP SITE 889 BROADBAND SEISMOMETER gPhone DGP calibration Bottom Pressure Recorder Guralp CGM-1T Coherence transfer function bounds f-test bootstrapping wave propagation matrix static solution ocean bottom seismometer tsunami earthquakes Modified York least squares temporal variations linear trend in gas hydrates Power spectral densities 1D compliance solution 1D compliance algorithm seafloor compliance instrumentation Micro-g gravitimeter triple phase boundary equation ultra-low frequency seismics seafloor pressure spectrum seafloor gravity spectrum pacific ocean off-shore British Columbia seafloor observatory static compliance of layered structures geophysics gas hydrate characterization 0373
314	Intelligent Energy-Savings and Process Improvement Strategies in Energy-Intensive Industries / Intelligent Energy-Savings and Process Improvement Strategies in Energy-Intensive Industries Teng, Sin Yong January 2020 (has links) S tím, jak se neustále vyvíjejí nové technologie pro energeticky náročná průmyslová odvětví, stávající zařízení postupně zaostávají v efektivitě a produktivitě. Tvrdá konkurence na trhu a legislativa v oblasti životního prostředí nutí tato tradiční zařízení k ukončení provozu a k odstavení. Zlepšování procesu a projekty modernizace jsou zásadní v udržování provozních výkonů těchto zařízení. Současné přístupy pro zlepšování procesů jsou hlavně: integrace procesů, optimalizace procesů a intenzifikace procesů. Obecně se v těchto oblastech využívá matematické optimalizace, zkušeností řešitele a provozní heuristiky. Tyto přístupy slouží jako základ pro zlepšování procesů. Avšak, jejich výkon lze dále zlepšit pomocí moderní výpočtové inteligence. Účelem této práce je tudíž aplikace pokročilých technik umělé inteligence a strojového učení za účelem zlepšování procesů v energeticky náročných průmyslových procesech. V této práci je využit přístup, který řeší tento problém simulací průmyslových systémů a přispívá následujícím: (i)Aplikace techniky strojového učení, která zahrnuje jednorázové učení a neuro-evoluci pro modelování a optimalizaci jednotlivých jednotek na základě dat. (ii) Aplikace redukce dimenze (např. Analýza hlavních komponent, autoendkodér) pro vícekriteriální optimalizaci procesu s více jednotkami. (iii) Návrh nového nástroje pro analýzu problematických částí systému za účelem jejich odstranění (bottleneck tree analysis – BOTA). Bylo také navrženo rozšíření nástroje, které umožňuje řešit vícerozměrné problémy pomocí přístupu založeného na datech. (iv) Prokázání účinnosti simulací Monte-Carlo, neuronové sítě a rozhodovacích stromů pro rozhodování při integraci nové technologie procesu do stávajících procesů. (v) Porovnání techniky HTM (Hierarchical Temporal Memory) a duální optimalizace s několika prediktivními nástroji pro podporu managementu provozu v reálném čase. (vi) Implementace umělé neuronové sítě v rámci rozhraní pro konvenční procesní graf (P-graf). (vii) Zdůraznění budoucnosti umělé inteligence a procesního inženýrství v biosystémech prostřednictvím komerčně založeného paradigmatu multi-omics.

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