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. ^

Maltreatment, psychiatric symptoms and human immunodeficiency virus/sexual transmitted infection risk behavior among youth with alcohol and other drug use problems: A person-centered analysis

Multi-problem youth undergoing treatment for substance use problems are at high behavioral risk for exposure to sexually transmitted infections (STIs), including human immunodeficiency virus (HIV). Specific risk factors include childhood adversities such as maltreatment experiences and subsequent forms of psychopathology. The current study used a person-centered analytical approach to examine how childhood maltreatment experiences were related to patterns of psychiatric symptoms and HIV/STI risk behaviors in a sample of adolescents (N = 408) receiving treatment services. Data were collected in face-to-face interviews at two community-based facilities. Descriptive statistics and Latent Profile Analysis (LPA) were used to (a) classify adolescents into groups based on past year psychiatric symptoms, and (b) examine relations between class membership and forms of childhood maltreatment experiences, as well as past year sexual risk behavior (SRB). ^ LPA results indicated significant heterogeneity in psychiatric symptoms among the participants. The three classes generated via the optimal LPA solution included: (a) a low psychiatric symptoms class, (b) a high alcohol symptoms class and (c) a high internalizing symptoms class. Class membership was associated significantly with adolescents’ self-reported scores for childhood sexual abuse and emotional neglect. ANOVAs documented significant differences in mean scores for multiple indices of SRB indices by class membership, demonstrating differential risk for HIV/STI exposure across classes. The two classes characterized by elevated psychiatric symptom profiles and more severe maltreatment histories were at increased behavioral risk for HIV/STI exposure, compared to the low psychiatric symptoms class. The high internalizing symptoms class reported the highest scores for most of the indices of SRB assessed. The heterogeneity of psychiatric symptom patterns documented in the current study has important implications for HIV/STI prevention programs implemented with multi-problem youth. The results highlight complex relations between childhood maltreatment experiences, psychopathology and multiple forms of health risk behavior among adolescents. The results underscore the importance of further integration between substance abuse treatment and HIV/STI risk reduction efforts to improve morbidity and mortality among vulnerable youth. ^

Tip Allocation: A Compliance Study tor Restaurants

Survey research of the commercial food service industry with regard to tips and tip allocation revealed that 50 percent of restaurateurs require that employees report a minimum amount or percentage of sales and over 50 percent which allocate tips report them as employee income. The authors discuss these results and point out other problems.

Hotel Managers Identify Ethical Problems: A Survey of their Concerns

This study identified and examined the concerns of hotel general managers regarding ethics in the hospitality industry. Thirty-five managers were interviewed during and immediately following the economic recession to determine which ethical issues in the hotel industry and at their own properties concerned them the most. Results showed that more people and organizations attempted to renegotiate hotel rates, which actions, in turn, led to some lapses in ethical behavior. Managers said that because of the economic downturn, they felt pressure from both private owners and corporate headquarters. They also said a lack of work ethic, low motivation, and low pay caused many workers to underperform in ways that raised ethical issues. Managers also mentioned diversity issues and theft by both guests and employees as ethical issues of concern, and shared stories about their experiences.

The effect of domestic credit in the economic *development process

A commonly held view is that creation of excessive domestic credit may lead to inflation problems, however, many economists uphold the possibility that, generous domestic credit under appropriate conditions will result in increases of output. This hypothesis is examined for Japan and Colombia for the period 1950-1993.^ Domestic credit theories are reviewed since the times of Thornton and Smith, until the recent times of Lewis, McKinnon, Stiglitz and of Japanese economists like K. Emi, Tachi R. and others. It is found that in Japan of the Post-War period, efficient financial markets and the decisive role of the government in orienting investment decisions seem to have influenced positively the effectiveness of domestic credit as an output-stimulating variable. On the contrary, in Colombia the absence of the above features seems to explain why domestic credit is not very effective as an output-stimulating variable.^ Multiple regression analyses show that domestic credit is a strong explanatory variable for output increases in Japan and a weak one for Colombia's case in the studied period. For Japan the correlation depicts a positive relationship between the two variables with a decreasing rate very similar to a typical production function. Moreover, the positive decreasing rate is confirmed if net domestic credit is used in the correlations. For Colombia a positive relationship is also found when accumulated domestic credit is used, but, if net domestic credit is the source of correlations, the positive decreasing rate is not obtained.^ Granger causality tests determined causality from domestic credit to output for Japan and no-causality for Colombia at the 1% significance level; the differences are explained by: (1) The low development level of the financial system in Colombia. (2) The nonexistence of consistent domestic credit policy to foster economic development. (3) The lack of an authoritative orientation in the allocation of financial resources and the nonexistence of long range industrialization programs in Colombia that could channel productively credit resources. For the system of equations relating domestic credit and exports, the Granger causality tests determined no-causality between domestic credit and exports for both Japan and Colombia also at the 1% significance level. ^

Mixed spatial and nonspatial problems in location based services

With hundreds of millions of users reporting locations and embracing mobile technologies, Location Based Services (LBSs) are raising new challenges. In this dissertation, we address three emerging problems in location services, where geolocation data plays a central role. First, to handle the unprecedented growth of generated geolocation data, existing location services rely on geospatial database systems. However, their inability to leverage combined geographical and textual information in analytical queries (e.g. spatial similarity joins) remains an open problem. To address this, we introduce SpsJoin, a framework for computing spatial set-similarity joins. SpsJoin handles combined similarity queries that involve textual and spatial constraints simultaneously. LBSs use this system to tackle different types of problems, such as deduplication, geolocation enhancement and record linkage. We define the spatial set-similarity join problem in a general case and propose an algorithm for its efficient computation. Our solution utilizes parallel computing with MapReduce to handle scalability issues in large geospatial databases. Second, applications that use geolocation data are seldom concerned with ensuring the privacy of participating users. To motivate participation and address privacy concerns, we propose iSafe, a privacy preserving algorithm for computing safety snapshots of co-located mobile devices as well as geosocial network users. iSafe combines geolocation data extracted from crime datasets and geosocial networks such as Yelp. In order to enhance iSafe's ability to compute safety recommendations, even when crime information is incomplete or sparse, we need to identify relationships between Yelp venues and crime indices at their locations. To achieve this, we use SpsJoin on two datasets (Yelp venues and geolocated businesses) to find venues that have not been reviewed and to further compute the crime indices of their locations. Our results show a statistically significant dependence between location crime indices and Yelp features. Third, review centered LBSs (e.g., Yelp) are increasingly becoming targets of malicious campaigns that aim to bias the public image of represented businesses. Although Yelp actively attempts to detect and filter fraudulent reviews, our experiments showed that Yelp is still vulnerable. Fraudulent LBS information also impacts the ability of iSafe to provide correct safety values. We take steps toward addressing this problem by proposing SpiDeR, an algorithm that takes advantage of the richness of information available in Yelp to detect abnormal review patterns. We propose a fake venue detection solution that applies SpsJoin on Yelp and U.S. housing datasets. We validate the proposed solutions using ground truth data extracted by our experiments and reviews filtered by Yelp.

Essays on intergenerational and regional aspects of water management

This dissertation consists of three essays on different aspects of water management. The first essay focuses on the sustainability of freshwater use by introducing the notion that altruistic parents do bequeath economic assets for their offspring. Constructing a two-period, over-lapping generational model, an optimal ratio of consumption and pollution for old and young generations in each period is determined. Optimal levels of water consumption and pollution change according to different parameters, such as, altruistic degree, natural recharge rate, and population growth. The second essay concerns water sharing between countries in the case of trans-boundary river basins. The paper recognizes that side payments fail to forge water-sharing agreement among the international community and that downstream countries have weak bargaining power. An interconnected game approach is developed by linking the water allocation issue with other non-water issues such as trade or border security problems, creating symmetry between countries in bargaining power. An interconnected game forces two countries to at least partially cooperate under some circumstances. The third essay introduces the concept of virtual water (VW) into a traditional international trade model in order to estimate water savings for a water scarce country. A two country, two products and two factors trade model is developed, which includes not only consumers and producer's surplus, but also environmental externality of water use. The model shows that VW trade saves water and increases global and local welfare. This study should help policy makers to design appropriate subsidy or tax policy to promote water savings especially in water scarce countries.^

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.

Mixed Spatial and Nonspatial Problems in Location Based Services

With hundreds of millions of users reporting locations and embracing mobile technologies, Location Based Services (LBSs) are raising new challenges. In this dissertation, we address three emerging problems in location services, where geolocation data plays a central role. First, to handle the unprecedented growth of generated geolocation data, existing location services rely on geospatial database systems. However, their inability to leverage combined geographical and textual information in analytical queries (e.g. spatial similarity joins) remains an open problem. To address this, we introduce SpsJoin, a framework for computing spatial set-similarity joins. SpsJoin handles combined similarity queries that involve textual and spatial constraints simultaneously. LBSs use this system to tackle different types of problems, such as deduplication, geolocation enhancement and record linkage. We define the spatial set-similarity join problem in a general case and propose an algorithm for its efficient computation. Our solution utilizes parallel computing with MapReduce to handle scalability issues in large geospatial databases. Second, applications that use geolocation data are seldom concerned with ensuring the privacy of participating users. To motivate participation and address privacy concerns, we propose iSafe, a privacy preserving algorithm for computing safety snapshots of co-located mobile devices as well as geosocial network users. iSafe combines geolocation data extracted from crime datasets and geosocial networks such as Yelp. In order to enhance iSafe's ability to compute safety recommendations, even when crime information is incomplete or sparse, we need to identify relationships between Yelp venues and crime indices at their locations. To achieve this, we use SpsJoin on two datasets (Yelp venues and geolocated businesses) to find venues that have not been reviewed and to further compute the crime indices of their locations. Our results show a statistically significant dependence between location crime indices and Yelp features. Third, review centered LBSs (e.g., Yelp) are increasingly becoming targets of malicious campaigns that aim to bias the public image of represented businesses. Although Yelp actively attempts to detect and filter fraudulent reviews, our experiments showed that Yelp is still vulnerable. Fraudulent LBS information also impacts the ability of iSafe to provide correct safety values. We take steps toward addressing this problem by proposing SpiDeR, an algorithm that takes advantage of the richness of information available in Yelp to detect abnormal review patterns. We propose a fake venue detection solution that applies SpsJoin on Yelp and U.S. housing datasets. We validate the proposed solutions using ground truth data extracted by our experiments and reviews filtered by Yelp.