The applied computer science of economic analyses: Internet prioritization and Internet pricing, and software engineering and software pricing for the mass market

This research examines evolving issues in applied computer science and applies economic and business analyses as well. There are two main areas. The first is internetwork communications as embodied by the Internet. The goal of the research is to devise an efficient pricing, prioritization, and incentivization plan that could be realistically implemented on the existing infrastructure. Criteria include practical and economic efficiency, and proper incentives for both users and providers. Background information on the evolution and functional operation of the Internet is given, and relevant literature is surveyed and analyzed. Economic analysis is performed on the incentive implications of the current pricing structure and organization. The problems are identified, and minimally disruptive solutions are proposed for all levels of implementation to the lowest level protocol. Practical issues are considered and performance analyses are done. The second area of research is mass market software engineering, and how this differs from classical software engineering. Software life-cycle revenues are analyzed and software pricing and timing implications are derived. A profit maximizing methodology is developed to select or defer the development of software features for inclusion in a given release. An iterative model of the stages of the software development process is developed, taking into account new communications capabilities as well as profitability. ^

An exergy based engineering and economic analysis of sustainable building

To achieve the goal of sustainable development, the building energy system was evaluated from both the first and second law of thermodynamics point of view. The relationship between exergy destruction and sustainable development were discussed at first, followed by the description of the resource abundance model, the life cycle analysis model and the economic investment effectiveness model. By combining the forgoing models, a new sustainable index was proposed. Several green building case studies in U.S. and China were presented. The influences of building function, geographic location, climate pattern, the regional energy structure, and the technology improvement potential of renewable energy in the future were discussed. The building’s envelope, HVAC system, on-site renewable energy system life cycle analysis from energy, exergy, environmental and economic perspective were compared. It was found that climate pattern had a dramatic influence on the life cycle investment effectiveness of the building envelope. The building HVAC system energy performance was much better than its exergy performance. To further increase the exergy efficiency, renewable energy rather than fossil fuel should be used as the primary energy. A building life cycle cost and exergy consumption regression model was set up. The optimal building insulation level could be affected by either cost minimization or exergy consumption minimization approach. The exergy approach would cause better insulation than cost approach. The influence of energy price on the system selection strategy was discussed. Two photovoltaics (PV) systems—stand alone and grid tied system were compared by the life cycle assessment method. The superiority of the latter one was quite obvious. The analysis also showed that during its life span PV technology was less attractive economically because the electricity price in U.S. and China did not fully reflect the environmental burden associated with it. However if future energy price surges and PV system cost reductions were considered, the technology could be very promising for sustainable buildings in the future.

Next generation of recommender systems: Algorithms and applications

Personalized recommender systems aim to assist users in retrieving and accessing interesting items by automatically acquiring user preferences from the historical data and matching items with the preferences. In the last decade, recommendation services have gained great attention due to the problem of information overload. However, despite recent advances of personalization techniques, several critical issues in modern recommender systems have not been well studied. These issues include: (1) understanding the accessing patterns of users (i.e., how to effectively model users' accessing behaviors); (2) understanding the relations between users and other objects (i.e., how to comprehensively assess the complex correlations between users and entities in recommender systems); and (3) understanding the interest change of users (i.e., how to adaptively capture users' preference drift over time). To meet the needs of users in modern recommender systems, it is imperative to provide solutions to address the aforementioned issues and apply the solutions to real-world applications. ^ The major goal of this dissertation is to provide integrated recommendation approaches to tackle the challenges of the current generation of recommender systems. In particular, three user-oriented aspects of recommendation techniques were studied, including understanding accessing patterns, understanding complex relations and understanding temporal dynamics. To this end, we made three research contributions. First, we presented various personalized user profiling algorithms to capture click behaviors of users from both coarse- and fine-grained granularities; second, we proposed graph-based recommendation models to describe the complex correlations in a recommender system; third, we studied temporal recommendation approaches in order to capture the preference changes of users, by considering both long-term and short-term user profiles. In addition, a versatile recommendation framework was proposed, in which the proposed recommendation techniques were seamlessly integrated. Different evaluation criteria were implemented in this framework for evaluating recommendation techniques in real-world recommendation applications. ^ In summary, the frequent changes of user interests and item repository lead to a series of user-centric challenges that are not well addressed in the current generation of recommender systems. My work proposed reasonable solutions to these challenges and provided insights on how to address these challenges using a simple yet effective recommendation framework.^

Design for placement of modified optodes to non-invasively map cerebral function

By using near infrared spectroscopy (NIRS) and by modifying the current Somanetics® optodes being used with the INVOS oximeter, the modified optodes are made to be fairly functional not only across the forehead, but across the hairy regions of the scalp as well. A major problem arises in the positioning of these optodes on the patients scalp and holding them in place while recording data. Another problem arises in the inconsistent repeatability of the trends displayed in the recorded data. A method was developed to facilitate the easy placement of these optodes on the patients scalp keeping in mind thepatient's comfort. The sensitivity of the optodes, too, was improved by incorporating better refined techniques for manufacturing the fiber optic brushes and fixing the same to the optode transmitting and receiving windows. The modified and improved optodes, in the single as well as in the multiplexed modes, were subjected to various tests on different areas of the brain to determine their efficiency and functionality.

A Multi-Criteria GIS-Based Route Selection Tool for Hazardous Material Transport: Consideration of Environmental Consequence, Traffic Congestions and Costs

Hazardous materials are substances that, if not regulated, can pose a threat to human populations and their environmental health, safety or property when transported in commerce. About 1.5 million tons of hazardous material shipments are transported by truck in the US annually, with a steady increase of approximately 5% per year. The objective of this study was to develop a routing tool for hazardous material transport in order to facilitate reduced environmental impacts and less transportation difficulties, yet would also find paths that were still compelling for the shipping carriers as a matter of trucking cost. The study started with identification of inhalation hazard impact zones and explosion protective areas around the location of hypothetical hazardous material releases, considering different parameters (i.e., chemicals characteristics, release quantities, atmospheric condition, etc.). Results showed that depending on the quantity of release, chemical, and atmospheric stability (a function of wind speed, meteorology, sky cover, time and location of accidents, etc.) the consequence of these incidents can differ. The study was extended by selection of other evaluation criteria for further investigation because health risk as an evaluation criterion would not be the only concern in selection of routes. Transportation difficulties (i.e., road blockage and congestion) were incorporated as important factor due to their indirect impact/cost on the users of transportation networks. Trucking costs were also considered as one of the primary criteria in selection of hazardous material paths; otherwise the suggested routes would have not been convincing for the shipping companies. The last but not least criterion was proximity of public places to the routes. The approach evolved from a simple framework to a complicated and efficient GIS-based tool able to investigate transportation networks of any given study area, and capable of generating best routing options for cargos. The suggested tool uses a multi-criteria-decision-making method, which considers the priorities of the decision makers in choosing the cargo routes. Comparison of the routing options based on each criterion and also the overall suitableness of the path in regards to all the criteria (using a multi-criteria-decision-making method) showed that using similar tools as the one proposed by this study can provide decision makers insights in the area of hazardous material transport. This tool shows the probable consequences of considering each path in a very easily understandable way; in the formats of maps and tables, which makes the tradeoffs of costs and risks considerably simpler, as in some cases slightly compromising on trucking cost may drastically decrease the probable health risk and/or traffic difficulties. This will not only be rewarding to the community by making cities safer places to live, but also can be beneficial to shipping companies by allowing them to advertise as environmental friendly conveyors.

An Assessment of the Performances of Several Univariate Tests of Normality

The importance of checking the normality assumption in most statistical procedures especially parametric tests cannot be over emphasized as the validity of the inferences drawn from such procedures usually depend on the validity of this assumption. Numerous methods have been proposed by different authors over the years, some popular and frequently used, others, not so much. This study addresses the performance of eighteen of the available tests for different sample sizes, significance levels, and for a number of symmetric and asymmetric distributions by conducting a Monte-Carlo simulation. The results showed that considerable power is not achieved for symmetric distributions when sample size is less than one hundred and for such distributions, the kurtosis test is most powerful provided the distribution is leptokurtic or platykurtic. The Shapiro-Wilk test remains the most powerful test for asymmetric distributions. We conclude that different tests are suitable under different characteristics of alternative distributions.

A Capability Maturity Model to Assess Supply Chain Performance

In an overcapacity world, where the customers can choose from many similar products to satisfy their needs, enterprises are looking for new approaches and tools that can help them not only to maintain, but also to increase their competitive edge. Innovation, flexibility, quality, and service excellence are required to, at the very least, survive the on-going transition that industry is experiencing from mass production to mass customization. In order to help these enterprises, this research develops a Supply Chain Capability Maturity Model named S(CM)2. The Supply Chain Capability Maturity Model is intended to model, analyze, and improve the supply chain management operations of an enterprise. The Supply Chain Capability Maturity Model provides a clear roadmap for enterprise improvement, covering multiple views and abstraction levels of the supply chain, and provides tools to aid the firm in making improvements. The principal research tool applied is the Delphi method, which systematically gathered the knowledge and experience of eighty eight experts in Mexico. The model is validated using a case study and interviews with experts in supply chain management. The resulting contribution is a holistic model of the supply chain integrating multiple perspectives, and providing a systematic procedure for the improvement of a company’s supply chain operations.