Automated object identification and position estimation for airport lighting quality assessment

The development of an automated system for the quality assessment of aerodrome ground lighting (AGL), in accordance with associated standards and recommendations, is presented. The system is composed of an image sensor, placed inside the cockpit of an aircraft to record images of the AGL during a normal descent to an aerodrome. A model-based methodology is used to ascertain the optimum match between a template of the AGL and the actual image data in order to calculate the position and orientation of the camera at the instant the image was acquired. The camera position and orientation data are used along with the pixel grey level for each imaged luminaire, to estimate a value for the luminous intensity of a given luminaire. This can then be compared with the expected brightness for that luminaire to ensure it is operating to the required standards. As such, a metric for the quality of the AGL pattern is determined. Experiments on real image data is presented to demonstrate the application and effectiveness of the system.

State Estimation for Anaerobic Digesters using the ADM1

The optimization of full-scale biogas plant operation is of great importance to make biomass a competitive source of renewable energy. The implementation of innovative control and optimization algorithms, such as Nonlinear Model Predictive Control, requires an online estimation of operating states of biogas plants. This state estimation allows for optimal control and operating decisions according to the actual state of a plant. In this paper such a state estimator is developed using a calibrated simulation model of a full-scale biogas plant, which is based on the Anaerobic Digestion Model No.1. The use of advanced pattern recognition methods shows that model states can be predicted from basic online measurements such as biogas production, CH4 and CO2 content in the biogas, pH value and substrate feed volume of known substrates. The machine learning methods used are trained and evaluated using synthetic data created with the biogas plant model simulating over a wide range of possible plant operating regions. Results show that the operating state vector of the modelled anaerobic digestion process can be predicted with an overall accuracy of about 90%. This facilitates the application of state-based optimization and control algorithms on full-scale biogas plants and therefore fosters the production of eco-friendly energy from biomass.

Outperformance in exchange-traded fund pricing deviations: Generalized control of data snooping bias

An investigation into exchange-traded fund (ETF) outperforrnance during the period 2008-2012 is undertaken utilizing a data set of 288 U.S. traded securities. ETFs are tested for net asset value (NAV) premium, underlying index and market benchmark outperformance, with Sharpe, Treynor, and Sortino ratios employed as risk-adjusted performance measures. A key contribution is the application of an innovative generalized stepdown procedure in controlling for data snooping bias. We find that a large proportion of optimized replication and debt asset class ETFs display risk-adjusted premiums with energy and precious metals focused funds outperforming the S&P 500 market benchmark. 

The Monetary Value Of Meat Authenticity And Food Safety In Ready To Heat Lasagne: Implications Of The ‘Horse Meat Scandal’ Across Europe

The recent ‘horse meat scandal’ in Europe has sparked huge concerns among consumers, as horse meat was found in beef lasagne ready to be consumed. Within STARTEC, a European funded project, this study investigates consumers’ preferences, attitudes and willingness to pay (WTP) towards characteristics of ready to heat (RTH) fresh lasagne, including origin of the meat, tested for meat authenticity, safety of the lasagne, and nutritional value, using Discrete Choice Experiments in six countries - Republic of Ireland, France, Italy, Spain, Germany and Norway. Our representative sample of 4,598 European consumers makes this the largest cross country study of this kind. The questionnaire was administered online in January 2014. Results from models in WTP-space show that, on average, consumers are willing to pay considerable amount (about €4-9) for food authenticity; on this Irish and Italian are the least concerned while Spanish are the most concerned. As expected from discussing with stakeholders, food safety claims and nutritional value of the RTH lasagne are relatively less important. Consumers also value knowing the origin of ingredients preferring locally sourced meat. Primarily, the results of this study present strong evidence that consumers in Europe are highly concerned about authenticity of the meat in ready meals and strongly prefer to know that the meat is national. This evidence suggests that there is great value in providing information on these attributes, both from a consumer perspective and where this leads to an increased consumer confidence has benefits for the food industry.

A high-value, low-cost bubble continuous positive airway pressure system for low-resource settings:technical assessment and initial case reports

Acute respiratory infections are the leading cause of global child mortality. In the developing world, nasal oxygen therapy is often the only treatment option for babies who are suffering from respiratory distress. Without the added pressure of bubble Continuous Positive Airway Pressure (bCPAP) which helps maintain alveoli open, babies struggle to breathe and can suffer serious complications, and frequently death. A stand-alone bCPAP device can cost $6,000, too expensive for most developing world hospitals. Here, we describe the design and technical evaluation of a new, rugged bCPAP system that can be made in small volume for a cost-of-goods of approximately $350. Moreover, because of its simple design--consumer-grade pumps, medical tubing, and regulators--it requires only the simple replacement of a <$1 diaphragm approximately every 2 years for maintenance. The low-cost bCPAP device delivers pressure and flow equivalent to those of a reference bCPAP system used in the developed world. We describe the initial clinical cases of a child with bronchiolitis and a neonate with respiratory distress who were treated successfully with the new bCPAP device.

IQ Imbalance in Multiuser Systems: Channel Estimation and Compensation

In this paper, we consider the uplink of a single-cell multi-user single-input multiple-output (MU-SIMO) system with in-phase and quadrature-phase imbalance (IQI). Particularly, we investigate the effect of receive (RX) IQI on the performance of MU-SIMO systems with large antenna arrays employing maximum-ratio combining (MRC) receivers. In order to study how IQI affects channel estimation, we derive a new channel estimator for the IQI-impaired model and show that the higher the value of signal-to-noise ratio (SNR) the higher the impact of IQI on the spectral efficiency (SE). Moreover, a novel pilot-based joint estimator of the augmented MIMO channel matrix and IQI coefficients is described and then, a low-complexity IQI compensation scheme is proposed which is based on the
IQI coefficients’ estimation and it is independent of the channel gain. The performance of the proposed compensation scheme is analytically evaluated by deriving a tractable approximation of the ergodic SE assuming transmission over Rayleigh fading channels with large-scale fading. Furthermore, we investigate how many MSs should be scheduled in massive multiple-input multiple-output (MIMO) systems with IQI and show that the highest SE loss occurs at the optimal operating point. Finally,
by deriving asymptotic power scaling laws, and proving that the SE loss due to IQI is asymptotically independent of the number of BS antennas, we show that massive MIMO is resilient to the effect of RX IQI.

Development of the Consumer Refrigerator Safety Questionnaire (CRSQ): A Measure of Consumer Perceptions and Practices

Food preparation and storage behaviors in the home deviating from the ‘best practice’ food safety recommendations may result in food borne illnesses. Currently, there are limited tools available to fully evaluate the consumer knowledge, perceptions and behavior in the area of refrigerator safety. The current study aimed to develop a valid and reliable tool in the form of a questionnaire (CFSQCRSQ) for assessing systematically all these aspects. Items relating to refrigerator safety knowledge (n=17), perceptions (n=46), reported behavior (n=30) were developed and pilot tested by an expert reference group and various consumer groups to assess face and content validity (n=20), item difficulty and item consistency (n=55) and construct validity (n=23). The findings showed that the CFSQCRSQ has acceptable face and content validity with acceptable levels of item difficulty. Item consistency was observed for 12 out of 15 refrigerator safety knowledge. Further, all five of the subscales of consumer perceptions of refrigerator safety practices relating to risk of developing foodborne disease food poisoning showed acceptable internal consistency (Cronbach’s α value > 0.8). Construct validity of the CFSQCRSQ was shown to be very good (p=0.022). The CFSQCRSQ exhibited acceptable test-retest reliability at 14 days with majority of knowledge items (93.3%) and reported behavior items (96.4%) having correlation coefficients of greater than 0.70. Overall, the CFSQCRSQ was deemed valid and reliable in assessing refrigerator safety knowledge and behavior and therefore has the potential for future use in identifying groups of individuals at increased risk of deviating from recommended refrigerator safety practices as well as the assessment of refrigerator safety knowledge, behavior for use before and after an intervention.

Exploring Consumer Opportunism Conundrum in the Insurance Industry: The Role of Marketing

Drawing from the extant literature, this paper explores the prevalent consumer opportunism in the insurance transactions, its links to consumers’ perception, and the relevance of marketing strategies in curbing the menace. It shows that insurance opportunism could be perpetrated by any party in the insurance transaction system and at any stage of the process involved. Among factors identified as prompting this conundrum are economic motive, resentment towards the insurance companies, laxity in the application processing/asymmetric information, and insiders’ collaborations. Nonetheless, the paper suggests that strong commitment of insurance marketers to creating and delivering value to the customers more robustly through a proactive and all-embracing implementation of marketing strategies vis-àvis relationship marketing could significantly enhance consumers’ positive perception of insurance business and consequently result in a healthier insurance industry.

Soft-computing techniques applied to artificial tissue temperature estimation

Tese dout., Engenharia electrónica e computação - Processamento de sinal, Universidade do Algarve, 2008

Open source data sensing software for ultrasonic non-invasive temperature estimation

In this paper, an open source solution for measurement of temperature and ultrasonic signals (RF-lines) is proposed. This software is an alternative to the expensive commercial data acquisition software, enabling the user to tune applications to particular acquisition architectures. The collected ultrasonic and temperature signals were used for non-invasive temperature estimation using neural networks. The existence of precise temperature estimators is an essential point aiming at the secure and effective applica tion of thermal therapies in humans. If such estimators exist then effective controllers could be developed for the therapeutic instrumentation. In previous works the time-shift between RF-lines echoes were extracted, and used for creation of neural networks estimators. The obtained estimators successfully represent the temperature in the time-space domain, achieving a maximum absolute error inferior to the threshold value defined for hyperthermia/diathermia applications.

A value chain analysis of tuna industry in Ghana

Every can of tuna purchased by the consumer has taken a long journey before reaching the supermarket shelves. For each can bought there is a lengthy process from sea to shelf. A large proportion of the tuna cans purchased in the European Union come all the way from West Africa; a developing region with a high dependency on fisheries. Amidst an ever-increasing demand for tuna products the global tuna fisheries are set to continue expanding, apparently one of the last natural resource based industries fit to do so in West Africa. Tuna is the biggest fisheries export and dominates the fisheries sector in Ghana, a country situated in West Africa. This thesis aims to understand how this globally important industrial fisheries functions in terms of procedures, practices, Governance and finance. Socioeconomic influences, in the setting of a developing country, were also examined. For these purposes a Value Chain Analysis was employed. A Value Chain Analysis is a tool commonly used to understand how different companies and organizations participate in a domestic policy environment, which directs conclusion in the global economy. This analysis has the potential to allow researchers to fully understand a commodity chain and hence identify realistic opportunities for consequential improvements. Interviews and questionnaires were employed in-field Ghana along with secondary data collection techniques. It was found that the fisheries functions at the production level under influences from large multinational companies and tends to operate with a certain degree of lawlessness. Governance over the value chain is well defined, however implementation is poor or non-existent. The processors, whom are also dominated by multinationals, exert some control over the producers and their sales, however the high value links which are highlighted occur at the retail stage. Socioeconomic dynamics acting in the chain included the lack of communication between the public and private sector, power imbalances amongst players at production, the role of local businesswomen as actors in the chain and the general characteristics of the workers in the industry. Value addition and upgrading are needed the most in Governance over the chain, especially within Monitoring, Control and Surveillance. The results of the study provide a wealth of material about the components of a cost-heavy fishing industry in a developing country; an industry on which many eyes have recently turned due to illegal fishing activities. It highlights clearly where funding and future focus are needed. This value chain can be used as a guide for those that need to comprehend the financial complexities and real life dynamics of the Ghanaian tuna fishing industry today.

Essays on Applications of the Factor Model

Thesis (Ph.D.)--University of Washington, 2013

Choosing the Right Promotional Tool in the Hotel Industry: The Case of the Chinese Consumer.

The rapid growth of the Chinese tourism has stimulated competition within tourism-related industries, such as the hospitality industry. The purpose of this study is to examine the Chinese consumer reaction to different promotional tools used by hotels in China and, thus, to provide a deeper understanding for marketers of how to use sales promotion effectively to generate appropriate consumer responses. An experimental survey was administered yielding a total sample of 319 Chinese customers, who were probed using different types of sales promotion tools. Data analysis indicates that bonus packs (e.g. a 3-night stay at a hotel for the price of 2) induced the highest consumer perceived value, brand switching, and purchase acceleration intention, whereas price discounts resulted in the highest intention to spend more. Although this study has its limitations given its reliance on a convenience sample, it offers insightful practical implications for hotel business owners in Asia regarding targeting the right customers with the right promotional tools, where it is proposed that bonus packs successfully attract new Chinese customers and price discounts support in generating more sales.

Does Cost-Effectiveness Analysis Have a Role in US Managed Care Drug Formularies? An Empirical Study of Utilization, Costs, Outcomes, and Elasticity of Demand of a Value-Based Formulary

Thesis (Ph.D.)--University of Washington, 2015

A data-mining-based methodology for transmission expansion planning

In recent decades, all over the world, competition in the electric power sector has deeply changed the way this sector’s agents play their roles. In most countries, electric process deregulation was conducted in stages, beginning with the clients of higher voltage levels and with larger electricity consumption, and later extended to all electrical consumers. The sector liberalization and the operation of competitive electricity markets were expected to lower prices and improve quality of service, leading to greater consumer satisfaction. Transmission and distribution remain noncompetitive business areas, due to the large infrastructure investments required. However, the industry has yet to clearly establish the best business model for transmission in a competitive environment. After generation, the electricity needs to be delivered to the electrical system nodes where demand requires it, taking into consideration transmission constraints and electrical losses. If the amount of power flowing through a certain line is close to or surpasses the safety limits, then cheap but distant generation might have to be replaced by more expensive closer generation to reduce the exceeded power flows. In a congested area, the optimal price of electricity rises to the marginal cost of the local generation or to the level needed to ration demand to the amount of available electricity. Even without congestion, some power will be lost in the transmission system through heat dissipation, so prices reflect that it is more expensive to supply electricity at the far end of a heavily loaded line than close to an electric power generation. Locational marginal pricing (LMP), resulting from bidding competition, represents electrical and economical values at nodes or in areas that may provide economical indicator signals to the market agents. This article proposes a data-mining-based methodology that helps characterize zonal prices in real power transmission networks. To test our methodology, we used an LMP database from the California Independent System Operator for 2009 to identify economical zones. (CAISO is a nonprofit public benefit corporation charged with operating the majority of California’s high-voltage wholesale power grid.) To group the buses into typical classes that represent a set of buses with the approximate LMP value, we used two-step and k-means clustering algorithms. By analyzing the various LMP components, our goal was to extract knowledge to support the ISO in investment and network-expansion planning.