Resource allocation in multi-user telecommunication networks

This dissertation discussed resource allocation mechanisms in several network topologies including infrastructure wireless network, non-infrastructure wireless network and wire-cum-wireless network. Different networks may have different resource constrains. Based on actual technologies and implementation models, utility function, game theory and a modern control algorithm have been introduced to balance power, bandwidth and customers' satisfaction in the system. ^ In infrastructure wireless networks, utility function was used in the Third Generation (3G) cellular network and the network was trying to maximize the total utility. In this dissertation, revenue maximization was set as an objective. Compared with the previous work on utility maximization, it is more practical to implement revenue maximization by the cellular network operators. The pricing strategies were studied and the algorithms were given to find the optimal price combination of power and rate to maximize the profit without degrading the Quality of Service (QoS) performance. ^ In non-infrastructure wireless networks, power capacity is limited by the small size of the nodes. In such a network, nodes need to transmit traffic not only for themselves but also for their neighbors, so power management become the most important issue for the network overall performance. Our innovative routing algorithm based on utility function, sets up a flexible framework for different users with different concerns in the same network. This algorithm allows users to make trade offs between multiple resource parameters. Its flexibility makes it a suitable solution for the large scale non-infrastructure network. This dissertation also covers non-cooperation problems. Through combining game theory and utility function, equilibrium points could be found among rational users which can enhance the cooperation in the network. ^ Finally, a wire-cum-wireless network architecture was introduced. This network architecture can support multiple services over multiple networks with smart resource allocation methods. Although a SONET-to-WiMAX case was used for the analysis, the mathematic procedure and resource allocation scheme could be universal solutions for all infrastructure, non-infrastructure and combined networks. ^

Synthetic studies of azulenyl and pseudoazulenyl nitrones

Free radicals have been implicated in various pathological conditions such as, stroke, aging and ischemic heart disease (IHD), as well as neurodegenerative diseases like Alzheimer’s, Parkinson’s, and Huntington’s disease. The role of antioxidants in protection from the harmful effects of free radicals has long been recognized. Trapping extremely reactive free radicals and eliminating them from circulation has been shown to be effective in animal models. Nitrone-based free radical traps have been extensively explored in biological systems. Examples include nitrones such as PBN, NXY-059, MDL-101,002, DMPO and EMPO. However, these nitrones have extremely high oxidation potentials as compared to natural antioxidants such as Vitamin E (α-tocopherol), and glutathione. Becker et al. (1995) synthesized novel azulenyl nitrones, which were shown to have oxidation potentials much lower than that of any of the previously reported nitrone based spin traps. Another azulenyl nitrone derivative, stilbazulenyl nitrone (STAZN), was shown to have an even lower oxidation potential within the range of natural antioxidants. STAZN, a second generation free radical trap, was found to be markedly superior than the two most studied nitrones, PBN and NXY-059, in animal models of cerebral ischemia and in an in vitro assay of lipid peroxidation. In this study, a third generation azulenyl nitrone was synthesized with an electron donating group on the previously synthesized STAZN derivative with the aim to lower the oxidation potential even more. Pseudoazulenes, because of the presence of an annular heteroatom, have been reported to possess even lower oxidation potential than that of the azulenyl counterpart. Therefore, pseudoazulenyl nitrones were synthesized for the first time by extracting and elaborating valtrate from the roots of Centranthus ruber (Red valerian or Jupiter’s beard). Several pseudoazulenyl nitrones were synthesized by using a facile experimental protocol. The physical and biological properties of these pseudoazulenyl nitrones can be easily modified by simply changing the substituent on the heteroatom. Cyclic voltammetry experiments have shown that these pseudoazulenyl nitrones do indeed have low oxidation potentials. The oxidation potential of these nitrones was lowered even more by preparing derivatives bearing an electron donating group at the 3-position of the five membered ring of the pseudoazulenyl nitrone.

Synthetic Studies of Azulenyl and Pseudoazulenyl Nitrones

Free radicals have been implicated in various pathological conditions such as, stroke, aging and ischemic heart disease (IHD), as well as neurodegenerative diseases like Alzheimer’s, Parkinson’s, and Huntington’s disease. The role of antioxidants in protection from the harmful effects of free radicals has long been recognized. Trapping extremely reactive free radicals and eliminating them from circulation has been shown to be effective in animal models. Nitrone-based free radical traps have been extensively explored in biological systems. Examples include nitrones such as PBN, NXY-059, MDL-101,002, DMPO and EMPO. However, these nitrones have extremely high oxidation potentials as compared to natural antioxidants such as Vitamin E (á-tocopherol), and glutathione. Becker et al. (1995) synthesized novel azulenyl nitrones, which were shown to have oxidation potentials much lower than that of any of the previously reported nitrone based spin traps. Another azulenyl nitrone derivative, stilbazulenyl nitrone (STAZN), was shown to have an even lower oxidation potential within the range of natural antioxidants. STAZN, a second generation free radical trap, was found to be markedly superior than the two most studied nitrones, PBN and NXY-059, in animal models of cerebral ischemia and in an in vitro assay of lipid peroxidation. In this study, a third generation azulenyl nitrone was synthesized with an electron donating group on the previously synthesized STAZN derivative with the aim to lower the oxidation potential even more. Pseudoazulenes, because of the presence of an annular heteroatom, have been reported to possess even lower oxidation potential than that of the azulenyl counterpart. Therefore, pseudoazulenyl nitrones were synthesized for the first time by extracting and elaborating valtrate from the roots of Centranthus ruber (Red valerian or Jupiter’s beard). Several pseudoazulenyl nitrones were synthesized by using a facile experimental protocol. The physical and biological properties of these pseudoazulenyl nitrones can be easily modified by simply changing the substituent on the heteroatom. Cyclic voltammetry experiments have shown that these pseudoazulenyl nitrones do indeed have low oxidation potentials. The oxidation potential of these nitrones was lowered even more by preparing derivatives bearing an electron donating group at the 3-position of the five membered ring of the pseudoazulenyl nitrone.

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.^