Recently many academic researchers have become interested in the retailers as part of the distribution channel. Today retailers have grown so influential, that sometimes they take the functions of the wholesalers. The retailers constitute the road for manufacturers to the end market. Therefore, knowing retailers’ decision variables and assortment considerations is important for manufacturers when designing upon their marketing strategies. The study is conducted with focus on the Bulgarian office products retail industry. The purpose of the present research is to get a deeper understanding of retailers’ assortment criteria and analyze how the latter relates to market coverage strategy. Retailers’ assortment criteria concern decision variables such as profitability and sales, economic conditions, assortment considerations, consumer evaluation, marketing, supplier characteristics, competitive considerations, distributive factors, tactical considerations. The meaning underlying the assortment criteria is applied for arguing what market coverage strategy would best serve the Bulgarian retailers of office products. The research is performed employing qualitative method, in particular, in-depth semi- structured interviews providing the possibility for a broad discussion. The results of the study revealed some common patterns pertaining to four main inductive categories including product, brand positioning, promotion and distributor’s attributes. The patterns corresponding to the categories were further related to the market coverage strategy alternatives, namely, intensive, selective and exclusive coverage strategy. The results of the study showed that the nature of the product requires considerable effort from the distributors’ side to persuade the retailers to become customers who are aware of the products’ attributes. In other words, the nature of the office products calls for certain knowledge and skills that the retailers have to gain in order to be successful as traders to their own customers and that can be best achieved if selective coverage strategy is employed. Further, the results of the study reveal that manufacturers of office products that would like to position their brands on the high quality dimension should pursue highly selective distribution as this creates a superior product image. The results of the study also show that greater selectivity is suitable since it guarantees that the retailers’ requirements related to promotion are met. Last, the authors suggest that higher degrees of selectivity is the most appropriate way for a manufacturer to follow the performance of distributors and thus, to ensure that the desired by the retailers distributor’s attributes are present.

Searching for objects in physical space is one of the most important tasks for humans. Mobile sensor networks can be great tools for the task. Transient targets refer to a class of objects which are not identifiable unless momentary sensing and signaling conditions are satisfied. The transient property is often introduced by target attributes, privacy concerns, environment constraints, and sensing limitations. Transient target localization problems are challenging because the transient property is often coupled with factors such as sensing range limits, various coverage functions, constrained mobility, signal correspondence, limited number of searchers, and a vast searching region. To tackle these challenge tasks, we gradually increase complexity of the transient target localization problem such as Single Robot Single Target (SRST), Multiple Robots Single Target (MRST), Single Robot Multiple Targets (SRMT) and Multiple Robots Multiple Targets (MRMT). We propose the expected searching time (EST) as a primary metric to assess the searching ability of a single robot and the spatiotemporal probability occupancy grid (SPOG) method that captures transient characteristics of multiple targets and tracks the spatiotemporal posterior probability distribution of the target transmissions. Besides, we introduce a team of multiple robots and develop a sensor fusion model using the signal strength ratio from the paired robots in centralized and decentralized manners. We have implemented and validated the algorithms under a hardware-driven simulation and physical experiments.

This thesis consists of two separate parts. The first part consists of one paper and considers problems concerning spatial point processes and the second part includes three papers in the field of bioinformatics. The first part of the thesis is based on a forestry problem of estimating the number of trees in a region by using the information in an aerial photo, showing the area covered by the trees. The positions of the trees are assumed to follow either a binomial point process or a hard-core Strauss process. Furthermore, discs of equal size are used to represent the tree-crowns. We provide formulas for the expectation and the variance of the relative vacancy for both processes. The formulas are approximate for the hard-core Strauss process. Simulations indicate that the approximations are accurate.  The second part of this thesis focuses on pre-processing of microarray data. The microarray technology can be used to measure the expression of thousands of genes simultaneously in a single experiment. The technique is used to identify genes that are differentially expressed between two populations, e.g. diseased versus healthy individuals. This information can be used in several different ways, for example as diagnostic tools and in drug discovery. The microarray technique involves a number of complex experimental steps, where each step introduces variability in the data. Pre-processing aims to reduce this variation and is a crucial part of the data analysis. Paper II gives a review over several pre-processing methods. Spike-in data are used to describe how the different methods affect the sensitivity and bias of the experi­ment. An important step in pre-processing is dye-normalization. This normalization aims to re­move the systematic differences due to the use of different dyes for coloring the samples. In Paper III a novel dye-normalization, the MC-normalization, is proposed. The idea behind this normaliza­tion is to let the channels’ individual intensities determine the cor­rection, rather than the aver­age intensity which is the case for the commonly used MA-normali­zation. Spike-in data showed that  the MC-normalization reduced the bias for the differentially expressed genes compared to the MA-normalization. The standard method for preserving patient samples for diagnostic purposes is fixation in formalin followed by embedding in paraffin (FFPE). In Paper IV we used tongue-cancer micro­RNA-microarray data to study the effect of FFPE-storage. We suggest that the microRNAs are not equally affected by the storage time and propose a novel procedure to remove this bias. The procedure improves the ability of the analysis to detect differentially expressed microRNAs.

This paper aims to find out how media in different countries in the same part of a continent portray the latest development in the Korean conflict. To achieve this, the articles published by two newspapers, The Japan Times and The Korea Times, in the last five months have been analysed. The theory used to analyse the published articles is the agenda setting theory. This paper has found that geography, in the sense of proximity to the conflict, do affect what stories the newspapers publish and how they portray the story.

This study explores healthcare coverage disparity using a quantitative analysis on a large dataset from the United States. One of the objectives is to build supervised models including decision tree and neural network to study the efficient factors in healthcare coverage. We also discover groups of people with health coverage problems and inconsistencies by employing unsupervised modeling including K-Means clustering algorithm. Our modeling is based on the dataset retrieved from Medical Expenditure Panel Survey with 98,175 records in the original dataset. After pre-processing the data, including binning, cleaning, dealing with missing values, and balancing, it contains 26,932 records and 23 variables. We build 50 classification models in IBM SPSS Modeler employing decision tree and neural networks. The accuracy of the models varies between 76% and 81%. The models can predict the healthcare coverage for a new sample based on its significant attributes. We demonstrate that the decision tree models provide higher accuracy that the models based on neural networks. Also, having extensively analyzed the results, we discover the most efficient factors in healthcare coverage to be: access to care, age, poverty level of family, and race/ethnicity.

Current geocasting algorithms for VANETs are being designed to enable either private or reliable communications, but not both. Existing algorithms preserve privacy by minimizing the information used for routing, and sacrifice message delivery success. On the other hand, reliable protocols often store node information that can be used to compromise a vehicle's privacy. We have designed two private and reliable geocasting protocols for VANETs that ensure confidentiality. One is a probabilistic algorithm that uses direction-based dissemination, while the other is a deterministic algorithm that uses transmission-coverage dissemination. To preserve privacy, we create unlinkable and pseudonymous channels of communication with geocasting. For encryption and authentication, we use a public key technique. Our probabilistic forwarding model depends on message rate and cumulative payload, as well as the value of the angle of spreading of the direction-based scheme. To reduce message duplication, we apply dynamic traffic restriction and probabilistic forwarding techniques. The deterministic forwarding algorithm delays forwarding messages based on its uncovered transmission area after neighbouring nodes have broadcast the message. We prove that both algorithms ensure node privacy with appropriate message encryption security, and we ran simulations to demonstrate that both meet the message delivery requirements. From the gathered data, we observe that both algorithms behave differently depending on the scenario, with node density affecting the deterministic algorithm, while the angle of spreading does have a significant impact on the probabilistic protocol.

<p>This study is aimed at empirically examining health seeking behaviours in terms of illness response on household level at South Africa using 2007 General Household Survey and other<br /> relevant secondary sources. It provides an assessment of health seeking behaviours at the household level using individuals as unit of analysis by exploring the type of health care provider sought, the reason for delay in health seeking and the cause for not consulting. This study also assesses the extent of dissatisfaction among households using medical centres and this factor in health care utilisation is considered as the main reason for not consulting health care services. All the demographic and health seeking variables utilised in this study are controlled for medical aid cover because it is a critical variable in health care seeking. Therefore this study makes distinction on illness reporting and they type of health care consulted by medical aid holders and non medical aid holders. Statistical analyses are conducted to explore and predict the way in which demographic variables and socio economic variables affect health care seeking behaviours.</p>

This study explores the extent to which national newspaper coverage of a successful female coach reflects the broader gender ideology of society. This study looks specifically at the New York Times, The Washington Post and USA Today's coverage of six Women's Division I national basketball tournaments in which Pat Summitt coached the University of Tennessee in the championship game. The years included for this analysis are 1996, 1997, 1998, 2000, 2003 and 2004. This rhetorical analysis examines this print coverage to determine if, consistent with previous research on media coverage of the female athlete, Summitt's traditional gender role is privileged over her coaching role. The results suggest that Summitt is characterized in ways that marginalize and trivialize her coaching acomplishments. The findings also suggest that even as women succeed in the male-dominated world of sport, societal pressures require that they be presented as properly gendered heterosexual females.

The Rideout trial in 1978 was the first case in the United States in which a wife charged her husband with rape while the couple was still living together. This thesis furthers research in the area of marital rape by examining the press coverage through textual analysis. The scope of the research is limited to newspaper coverage (local and national) and the subsequent made-for-television movie based on the trial. As a case study, the Rideout trial illustrates how the press has covered sexual assault in the United States—especially during the height of the 1970s women’s movement. The findings indicate that through the execution of various rape-centered scripts, traditional rape stereotypes were perpetuated and only a few were challenged. This perpetuation led to an initial invalidation of marital rape, including Greta Rideout’s claim of rape.

Wireless sensor networks (WSNs) are now widely used in many applications. Connected Dominating Set (CDS) based routing which is one kind of hierarchical methods has received more attention to reduce routing overhead. The concept of k-connected m-dominating sets (kmCDS) is used to provide fault tolerance and routing flexibility. In this thesis, we first consider how to construct a CDS in WSNs. After that, centralized and distributed algorithms are proposed to construct a kmCDS. Moreover, we introduce some basic ideas of how to use CDS in other potential applications such as partial coverage and data dissemination in WSNs.