Optimization of Mobility Parameters using Fuzzy Logic and Reinforcement Learning in Self-Organizing Networks

In this thesis, several optimization techniques for next-generation wireless networks are proposed to solve different problems in the field of Self-Organizing Networks and heterogeneous networks. The common basis of these problems is that network parameters are automatically tuned to deal with the specific problem. As the set of network parameters is extremely large, this work mainly focuses on parameters involved in mobility management. In addition, the proposed self-tuning schemes are based on Fuzzy Logic Controllers (FLC), whose potential lies in the capability to express the knowledge in a similar way to the human perception and reasoning. In addition, in those cases in which a mathematical approach has been required to optimize the behavior of the FLC, the selected solution has been Reinforcement Learning, since this methodology is especially appropriate for learning from interaction, which becomes essential in complex systems such as wireless networks. Taking this into account, firstly, a new Mobility Load Balancing (MLB) scheme is proposed to solve persistent congestion problems in next-generation wireless networks, in particular, due to an uneven spatial traffic distribution, which typically leads to an inefficient usage of resources. A key feature of the proposed algorithm is that not only the parameters are optimized, but also the parameter tuning strategy. Secondly, a novel MLB algorithm for enterprise femtocells scenarios is proposed. Such scenarios are characterized by the lack of a thorough deployment of these low-cost nodes, meaning that a more efficient use of radio resources can be achieved by applying effective MLB schemes. As in the previous problem, the optimization of the self-tuning process is also studied in this case. Thirdly, a new self-tuning algorithm for Mobility Robustness Optimization (MRO) is proposed. This study includes the impact of context factors such as the system load and user speed, as well as a proposal for coordination between the designed MLB and MRO functions. Fourthly, a novel self-tuning algorithm for Traffic Steering (TS) in heterogeneous networks is proposed. The main features of the proposed algorithm are the flexibility to support different operator policies and the adaptation capability to network variations. Finally, with the aim of validating the proposed techniques, a dynamic system-level simulator for Long-Term Evolution (LTE) networks has been designed

How social shopping retains customers? Capturing the essence of website quality and relationship quality

Social shopping as a result of the advancement of social media applications is increasing considerably in e-commerce. As a consequence of the multi-faceted phenomenon of social shopping, website managers encounter a lot of challenges in providing their quality website experience to satisfy their customers’ needs and in developing relationships among participants, and community. In short, providing excellent quality website experience is crucial to support online customers. Therefore, it is necessary to offer further theoretical conceptualizations as well as detailed empirical evidence for such phenomena in which social shopping are supported and enabled. Thus, this paper attempts to investigate the factors affecting purchase intention of social shopping including two constructs: website quality (i.e., system, information, and service quality) and relationship quality (i.e., satisfaction, commitment, and trust). Additionally we aim to identify the mediating roles of commitment and trust. The empirical results show that the perceived system and service quality are important antecedents of customer satisfaction, but not for the effect of perceived information quality on customer satisfaction. Furthermore, it shows that customer satisfaction significantly influences commitment, trust, and purchase intention, and trust in turn significantly affect commitment. Our empirical results confirm that commitment and trust partially mediate the relationship between satisfaction and purchase intention in social shopping context

A regional land use survey based on remote sensing and other data: A report on a LANDSAT and computer mapping project, volume 2

The author has identified the following significant results. The project mapped land use/cover classifications from LANDSAT computer compatible tape data and combined those results with other multisource data via computer mapping/compositing techniques to analyze various land use planning/natural resource management problems. Data were analyzed on 1:24,000 scale maps at 1.1 acre resolution. LANDSAT analysis software and linkages with other computer mapping software were developed. Significant results were also achieved in training, communication, and identification of needs for developing the LANDSAT/computer mapping technologies into operational tools for use by decision makers

Comparative Evaluation and Ranking of the European Countries Based on the Interdependence between Human Development and Internal Security Indicators

New solutions and techniques for developing country policies are used under real conditions. The present study aims to propose a new approach for evaluating and ranking the European countries by using the interrelation between two groups of criteria, associated with the Human Development Index (HDI) and the World Internal Security and Police Index (WISPI). HDI and its components rank countries by value and detail the values of the components of longevity, education and income per capita. WISPI focuses on the effective rendering of security services and the outcome of rendered services. The priority of criteria is determined in the descending order of their correlation values with other group criteria. The criteria weights are set simultaneously for both groups by applying the weight balancing method WEBIRA. The methodology based on minimising sum of squared differences of the weighted sums within groups is used. Finally, the generalised criteria measuring the level of the country are calculated using the SAW method. Cluster analysis of the countries was carried out and compared with MCDM results. The study revealed that WEBIRA ranking of countries is basically consistent with the results of cluster analysis. The proposed methodology can be applied to develop the management policy of the countries, as well as to their evaluation and ranking by using various indices, criteria and procedures. The results of this research can also be used to reveal national policy choices, to point out government policy priorities.This article belongs to the Special Issue Optimization for Decision Makin

Genetic Characterization of the Pee Dee Cotton Breeding Program

The history of cotton breeding in the southeastern United States is multifaceted and complex. Public and private breeding programs have driven cotton’s genetic development over the past two centuries. The Pee Dee breeding program in Florence, South Carolina, has had a substantial role in the development of well-adapted cotton cultivars with improved fiber strength, fiber length, and performance in farmers’ fields. Despite the historic importance of the cotton germplasm lines and varieties from the Pee Dee program, little has been done to characterize the population structure and genetic architecture of key traits in this closed breeding program. Here, I first provide an in-depth exploration of the rich history of cotton breeding and genetics over the past century to provide some context for the remainder of this thesis. Then, I discuss the interface of breeding goals, population genetics, and historical implications of a representative sample across 85+ years of cotton breeding in the Pee Dee program. Once the family structure had been evaluated, I applied modern statistical methodology to find gene haplotypes that are associated with improved fiber quality or field performance and attempted to trace the origin of some beneficial alleles. Lastly, I talk about the implications of our work and how it may influence future breeding efforts to utilize the germplasm from this diverse cotton collection

SIGLEC-8 LIGANDS IN HUMAN AIRWAY AND AIRWAY SECRETIONS

Siglecs – sialic acid binding Ig-like lectins – are regulatory molecules expressed on subsets of immune cells where most inhibit inflammation when engaged by complementary sialoglycan ligands on target tissues. Both eosinophils and mast cells express Siglec-8 on the cell surface, and when Siglec-8 binds to sialoglycan ligands on tissues apoptosis of eosinophils and inhibition of mediator release by mast cells is induced, limiting inflammation. Although Siglec-8 has been shown to bind a synthetic glycan 6’-sulfated sialyl N-acetyllactosamine, the endogenous Siglec-8 ligand in human airways was still unknown. This study provides evidence of endogenous high molecular weight Siglec-8 ligands in human airway and airway secretions that are sensitive to sialidase and keratanase treatment. Siglec-8 ligands were isolated and identified from normal postmortem human airways or from nasal lavage. Glycoproteins were separated by size exclusion chromatography and resolved by composite agarose-acrylamide gel electrophoresis, blotted, and probed with human Fc-tagged Siglec-8, revealing three binding species (270 kDa, 600 kDa and 1000 kDa) in tracheal extracts and one major binding specie (~900 kDa) in nasal lavage. Ligand-containing fractions were pooled, and ligands were captured by immunoprecipitation using His-tagged pentameric Siglec-8 bound to nickel-Sepharose beads. Siglec-8-precipitated ligands were subjected to mass spectrometric proteomic analysis, revealing the proteoglycan aggrecan as the predominant protein in all three-size species of Siglec-8 ligands extracted from trachea and glycoprotein-340 as the predominant protein in sample purified from nasal lavage. Anti-aggrecan antibody immunoblots of electrophoresed tracheal purified Siglec-8 ligand revealed co-migrating aggrecan immunoreactivity that was sensitive to aggrecanase treatment. Anti-GP340 antibody immunoblots of electrophoresed nasal lavage purified Siglec-8 ligand revealed co-migrating GP340 immunoreactivity. All Siglec-8 ligands were sensitive to sialidase and keratanase treatment. In conclusion, human airway Siglec-8 ligands are sialylated keratan sulfate chains presented on different proteins dependent on where they are expressed