A high efficient biometrics approach for unconstrained iris segmentation and recognition

This dissertation develops an innovative approach towards less-constrained iris biometrics. Two major contributions are made in this research endeavor: (1) Designed an award-winning segmentation algorithm in the less-constrained environment where image acquisition is made of subjects on the move and taken under visible lighting conditions, and (2) Developed a pioneering iris biometrics method coupling segmentation and recognition of the iris based on video of moving persons under different acquisitions scenarios. The first part of the dissertation introduces a robust and fast segmentation approach using still images contained in the UBIRIS (version 2) noisy iris database. The results show accuracy estimated at 98% when using 500 randomly selected images from the UBIRIS.v2 partial database, and estimated at 97% in a Noisy Iris Challenge Evaluation (NICE.I) in an international competition that involved 97 participants worldwide involving 35 countries, ranking this research group in sixth position. This accuracy is achieved with a processing speed nearing real time. The second part of this dissertation presents an innovative segmentation and recognition approach using video-based iris images. Following the segmentation stage which delineates the iris region through a novel segmentation strategy, some pioneering experiments on the recognition stage of the less-constrained video iris biometrics have been accomplished. In the video-based and less-constrained iris recognition, the test or subject iris videos/images and the enrolled iris images are acquired with different acquisition systems. In the matching step, the verification/identification result was accomplished by comparing the similarity distance of encoded signature from test images with each of the signature dataset from the enrolled iris images. With the improvements gained, the results proved to be highly accurate under the unconstrained environment which is more challenging. This has led to a false acceptance rate (FAR) of 0% and a false rejection rate (FRR) of 17.64% for 85 tested users with 305 test images from the video, which shows great promise and high practical implications for iris biometrics research and system design.

A diagnostic framework for demand amplification problems in supply chains

This dissertation delivers a framework to diagnose the Bull-Whip Effect (BWE) in supply chains and then identify methods to minimize it. Such a framework is needed because in spite of the significant amount of literature discussing the bull-whip effect, many companies continue to experience the wide variations in demand that are indicative of the bull-whip effect. While the theory and knowledge of the bull-whip effect is well established, there still is the lack of an engineering framework and method to systematically identify the problem, diagnose its causes, and identify remedies. ^ The present work seeks to fill this gap by providing a holistic, systems perspective to bull-whip identification and diagnosis. The framework employs the SCOR reference model to examine the supply chain processes with a baseline measure of demand amplification. Then, research of the supply chain structural and behavioral features is conducted by means of the system dynamics modeling method. ^ The contribution of the diagnostic framework, is called Demand Amplification Protocol (DAMP), relies not only on the improvement of existent methods but also contributes with original developments introduced to accomplish successful diagnosis. DAMP contributes a comprehensive methodology that captures the dynamic complexities of supply chain processes. The method also contributes a BWE measurement method that is suitable for actual supply chains because of its low data requirements, and introduces a BWE scorecard for relating established causes to a central BWE metric. In addition, the dissertation makes a methodological contribution to the analysis of system dynamic models with a technique for statistical screening called SS-Opt, which determines the inputs with the greatest impact on the bull-whip effect by means of perturbation analysis and subsequent multivariate optimization. The dissertation describes the implementation of the DAMP framework in an actual case study that exposes the approach, analysis, results and conclusions. The case study suggests a balanced solution between costs and demand amplification can better serve both firms and supply chain interests. Insights pinpoint to supplier network redesign, postponement in manufacturing operations and collaborative forecasting agreements with main distributors.^

Improved Annual Average Daily Traffic (AADT) estimation for local roads using parcel-level travel demand modeling

Annual Average Daily Traffic (AADT) is a critical input to many transportation analyses. By definition, AADT is the average 24-hour volume at a highway location over a full year. Traditionally, AADT is estimated using a mix of permanent and temporary traffic counts. Because field collection of traffic counts is expensive, it is usually done for only the major roads, thus leaving most of the local roads without any AADT information. However, AADTs are needed for local roads for many applications. For example, AADTs are used by state Departments of Transportation (DOTs) to calculate the crash rates of all local roads in order to identify the top five percent of hazardous locations for annual reporting to the U.S. DOT. ^ This dissertation develops a new method for estimating AADTs for local roads using travel demand modeling. A major component of the new method involves a parcel-level trip generation model that estimates the trips generated by each parcel. The model uses the tax parcel data together with the trip generation rates and equations provided by the ITE Trip Generation Report. The generated trips are then distributed to existing traffic count sites using a parcel-level trip distribution gravity model. The all-or-nothing assignment method is then used to assign the trips onto the roadway network to estimate the final AADTs. The entire process was implemented in the Cube demand modeling system with extensive spatial data processing using ArcGIS. ^ To evaluate the performance of the new method, data from several study areas in Broward County in Florida were used. The estimated AADTs were compared with those from two existing methods using actual traffic counts as the ground truths. The results show that the new method performs better than both existing methods. One limitation with the new method is that it relies on Cube which limits the number of zones to 32,000. Accordingly, a study area exceeding this limit must be partitioned into smaller areas. Because AADT estimates for roads near the boundary areas were found to be less accurate, further research could examine the best way to partition a study area to minimize the impact.^

The Italian Response to the Growing U.S. Wine Demand

Americans are learning more about wines and consuming them in increasingly greater quantities. Italian wines have experienced a tremendous growth in their share of the U. S. market during the last decade. This article analyzes the marketing and success of the wines of Italy with the American consumer.

A Look Back To Look Forward: New Patterns In The Supply/Demand Equation In The Lodging Industry

In his dialogue entitled - A Look Back to Look Forward: New Patterns In The Supply/Demand Equation In The Lodging Industry - by Albert J. Gomes, Senior Principal, Pannell Kerr Forster, Washington, D.C. What the author intends for you to know is the following: “Factors which influence the lodging industry in the United States are changing that industry as far as where hotels are being located, what clientele is being served, and what services are being provided at different facilities. The author charts these changes and makes predictions for the future.” Gomes initially alludes to the evolution of transportation – the human, animal, mechanical progression - and how those changes, in the last 100 years or so, have had a significant impact on the hotel industry. “A look back to look forward treats the past as prologue. American hoteliers are in for some startling changes in their business,” Gomes says. “The man who said that the three most important determinants for the success of a hotel were “location, location, location” did a lot of good only in the short run.” Gomes wants to make you aware of the existence of what he calls, “locational obsolescence.” “Locational obsolescence is a fact of life, and at least in the United States bears a direct correlation to evolutionary changes in transportation technology,” he says. “…the primary business of the hospitality industry is to serve travelers or people who are being transported,” Gomes expands the point. Tied to the transportation element, the author also points out an interesting distinction between hotels and motels. In addressing, “…what clientele is being served, and what services are being provided at different facilities,” Gomes suggests that the transportation factor influences these constituents as well. Also coupled with this discussion are oil prices and shifts in transportation habits, with reference to airline travel being an ever increasing method of travel; capturing much of the inter-city travel market. Gomes refers to airline deregulation as an impetus. The point being, it’s a fluid market rather than a static one, and [successful] hospitality properties need to be cognizant of market dynamics and be able to adjust to the variables in their marketplace. Gomes provides many facts and figures to bolster his assertions. Interestingly and perceptively, at the time of this writing, Gomes alludes to America’s deteriorating road and bridge network. As of right now, in 2009, this is a major issue. Gomes rounds out this study by comparing European hospitality trends to those in the U.S.

Digital Literacy: A Demand for Nonlinear Thinking Styles

This paper makes a case for a direct relationship between digital literacy and nonlinear thinking styles, articulates a demand for nonlinear thinking styles in education and the workplace, and states implications for a connection between nonlinear thinking styles visual literacy, and intuitive artistic practice.

Toward A Better Understanding of the Evolution of Hotel Development: A Discussion of Product-specific Lodging Demand

In his essay - Toward a Better Understanding of the Evolution of Hotel Development: A Discussion of Product-Specific Lodging Demand - by John A. Carnella, Consultant, Laventhol & Horwath, cpas, New York, Carnella initially describes his piece by stating: “The diversified hotel product in the united states lodging market has Resulted in latent room-night demand, or supply-driven demand resulting from the introduction of a lodging product which caters to a specific set of hotel patrons. The subject has become significant as the lodging market has moved toward segmentation with regard to guest room offerings. The author proposes that latent demand is a tangible, measurable phenomenon best understood in light of the history of the guest room product from its infancy to its present state.” The article opens with an ephemeral depiction of hotel development in the United States, both pre’ and post World War II. To put it succinctly, the author wants you to know that the advent of the inter-state highway system changed the complexion of the hotel industry in the U.S. “Two essential ingredients were necessary for the next phase of hotel development in this country. First was the establishment of the magnificently intricate infrastructure which facilitated motor vehicle transportation in and around the then 48 states of the nation,” says Carnella. “The second event…was the introduction of affordable highway travel. Carnella goes on to say that the next – big thing – in hotel evolution was the introduction of affordable air travel. “With the airways filled with potential lodging guests, developers moved next to erect a new genre of hotel, the airport hotel,” Carnella advances his picture. Growth progressed with the arrival of the suburban hotel concept, which wasn’t fueled by developments in transportation, but by changes in people’s living habits, i.e. suburban affiliations as opposed to urban and city population aggregates. The author explores the distinctions between full-service and limited service lodging operations. “The market of interest with consideration to the extended-stay facility is one dominated by corporate office parks,” Carnella proceeds. These evolutional states speak to latent demand, and even further to segmentation of the market. “Latent demand… is a product-generated phenomenon in which the number of potential hotel guests increases as the direct result of the introduction of a new lodging facility,” Carnella brings his unique insight to the table with regard to the specialization process. The demand is already there; just waiting to be tapped. In closing, “…there must be a consideration of the unique attributes of a lodging facility relative to its ability to attract guests to a subject market, just as there must be an examination of the property's ability to draw guests from within the subject market,” Carnella proposes.

Water Demand and Allocation in the Mara River Basin, Kenya/Tanzania in the Face of Land Use Dynamics and Climate Variability

The Mara River Basin (MRB) is endowed with pristine biodiversity, socio-cultural heritage and natural resources. The purpose of my study is to develop and apply an integrated water resource allocation framework for the MRB based on the hydrological processes, water demand and economic factors. The basin was partitioned into twelve sub-basins and the rainfall runoff processes was modeled using the Soil and Water Assessment Tool (SWAT) after satisfactory Nash-Sutcliff efficiency of 0.68 for calibration and 0.43 for validation at Mara Mines station. The impact and uncertainty of climate change on the hydrology of the MRB was assessed using SWAT and three scenarios of statistically downscaled outputs from twenty Global Circulation Models. Results predicted the wet season getting more wet and the dry season getting drier, with a general increasing trend of annual rainfall through 2050. Three blocks of water demand (environmental, normal and flood) were estimated from consumptive water use by human, wildlife, livestock, tourism, irrigation and industry. Water demand projections suggest human consumption is expected to surpass irrigation as the highest water demand sector by 2030. Monthly volume of water was estimated in three blocks of current minimum reliability, reserve (>95%), normal (80–95%) and flood (40%) for more than 5 months in a year. The assessment of water price and marginal productivity showed that current water use hardly responds to a change in price or productivity of water. Finally, a water allocation model was developed and applied to investigate the optimum monthly allocation among sectors and sub-basins by maximizing the use value and hydrological reliability of water. Model results demonstrated that the status on reserve and normal volumes can be improved to ‘low’ or ‘moderate’ by updating the existing reliability to meet prevailing demand. Flow volumes and rates for four scenarios of reliability were presented. Results showed that the water allocation framework can be used as comprehensive tool in the management of MRB, and possibly be extended similar watersheds.