Benefit segmentation of international travelers to Macau, China

The purpose of this study is threefold: (1) to identify the underlying benefits sought by international visitors to Macau, China, which has emerged as a popular gambling destination in Asia; (2) to segment tourists visiting Macau by employing a cluster analysis based on the benefits sought; and (3) to examine any salient differences between the segment groups with regard to their behavioral characteristics, socio-economic characteristics, and demographic profiles. A convenience sample was used to collect data in the Macau International Airport, in the Macau Ferry Terminal, and at the border gate with Mainland China. A total 1,513 useful surveys were retained for data analysis. Cluster analysis discloses four distinct clusters: "convention and business seekers," "family and vacation seekers," "gambling and shopping seekers," and "multi-purpose seekers." Based on the results of our findings, several managerial implications are discussed. © Taylor & Francis Group, LLC.

Application of Wavelet Decomposition to Document Line Segmentation

ACM Computing Classification System (1998): I.7, I.7.5.

The unequal segmentation of public preparedness for mass evacuation:a cross-national perspective

This thesis is concerned with understanding how Emergency Management Agencies (EMAs) influence public preparedness for mass evacuation across seven countries. Due to the lack of cross-national research (Tierney et al., 2001), there is a lack of knowledge on EMAs perspectives and approaches to the governance of public preparedness. This thesis seeks to address this gap through cross-national research that explores and contributes towards understanding the governance of public preparedness. The research draws upon the risk communication (Wood et al., 2011; Tierney et al., 2001) social marketing (Marshall et al., 2007; Kotler and Lee, 2008; Ramaprasad, 2005), risk governance (Walker et al., 2010, 2013; Kuhlicke et al., 2011; IRGC, 2005, 2007; Renn et al., 2011; Klinke and Renn, 2012), risk society (Beck, 1992, 1999, 2002) and governmentality (Foucault, 1978, 2003, 2009) literature to explain this governance and how EMAs responsibilize the public for their preparedness. EMAs from seven countries (Belgium, Denmark, Germany, Iceland, Japan, Sweden, the United Kingdom) explain how they prepare their public for mass evacuation in response to different types of risk. A cross-national (Hantrais, 1999) interpretive research approach, using qualitative methods including semi-structured interviews, documents and observation, was used to collect data. The data analysis process (Miles and Huberman, 1999) identified how the concepts of risk, knowledge and responsibility are critical for theorising how EMAs influence public preparedness for mass evacuation. The key findings grounded in these concepts include: - Theoretically, risk is multi-functional in the governance of public preparedness. It regulates behaviour, enables surveillance and acts as a technique of exclusion. - EMAs knowledge and how this influenced their assessment of risk, together with how they share the responsibility for public preparedness across institutions and the public, are key to the governance of public preparedness for mass evacuation. This resulted in a form of public segmentation common to all countries, whereby the public were prepared unequally.  - EMAs use their prior knowledge and assessments of risk to target public preparedness in response to particular known hazards. However, this strategy places the non-targeted public at greater risk in relation to unknown hazards, such as a man-made disaster. - A cross-national conceptual framework of four distinctive governance practices (exclusionary, informing, involving and influencing) are utilised to influence public preparedness. - The uncertainty associated with particular types of risk limits the application of social marketing as a strategy for influencing the public to take responsibility and can potentially increase the risk to the public.

Fuzzy c-means variants for medical image segmentation

Segmentation is an important step in many medical imaging applications and a variety of image segmentation techniques exist. One group of segmentation algorithms is based on clustering concepts. In this article we investigate several fuzzy c-means based clustering algorithms and their application to medical image segmentation. In particular we evaluate the conventional hard c-means (HCM) and fuzzy c-means (FCM) approaches as well as three computationally more efficient derivatives of fuzzy c-means: fast FCM with random sampling, fast generalised FCM, and a new anisotropic mean shift based FCM. © 2010 by IJTS, ISDER.

Handwritten and machine-printed text discrimination using a template matching approach

We propose a novel template matching approach for the discrimination of handwritten and machine-printed text. We first pre-process the scanned document images by performing denoising, circles/lines exclusion and word-block level segmentation. We then align and match characters in a flexible sized gallery with the segmented regions, using parallelised normalised cross-correlation. The experimental results over the Pattern Recognition & Image Analysis Research Lab-Natural History Museum (PRImA-NHM) dataset show remarkably high robustness of the algorithm in classifying cluttered, occluded and noisy samples, in addition to those with significant high missing data. The algorithm, which gives 84.0% classification rate with false positive rate 0.16 over the dataset, does not require training samples and generates compelling results as opposed to the training-based approaches, which have used the same benchmark.

Az ügyfélszerzési mód hatásának vizsgálata a vevőelégedettségre és a lojalitásra a szervezeti piacon (Analyzing the impact of the customer acquisition mode to the customer satisfaction and loyalty on the corporate market – assessing the effect of recommendation with applying structural equation modelling)

A kutatás célja a marketingeszközök hosszú távú hatásának pontosabb megértése szervezetközi viszonylatban a vevőértékelési modellek egyik nehezen számszerűsíthető tényezője, az ajánlás hatásának vizsgálata által. A hatások elemzésére a strukturális egyenlőségek módszerét (Structural Equation Modelling) alkalmazta a szerző. Rámutatott, hogy az ajánlással szerzett ügyfelek elégedettebbek, lojálisabbak és gyakrabban ajánlják a vállalatot a más módon szerzett ügyfeleknél. Az összefüggések feltárása és bizonyítása különösen az ajánlás kumulatív hatása miatt jelentős. Az eredmények gyakorlati alkalmazásával lehetőség nyílik az ügyfélkör differenciáltabb, értékalapú szegmentációjára, amely pontosabb célcsoport-meghatározást lesz lehetővé, és hosszú távon hozzájárul a vállalat optimális ügyfélportfóliójának kialakításához. ______ The research is aimed at more precise understanding of longterm effects of marketing tools in business to business relations by analysing the impacts of recommendation potential, one of the hardly measurable factors of customer value concept. Structural Equation Modelling is applied for conducting effect analysis. The results show that customers acquired with recommendation are more satisfied, more loyal, and make more recommendation that other customer. These results are more interesting if we take the cumulative effect of recommendation in account. They provide bases for a more differentiated segmentation of customers, which results in a more accurate identification of target groups. In the long-run, the application of the customer-value concept considerably contributes to creating an optimal customer portfolio for companies.

Strategic segmentation: when two monopolies are better than one

In this article we show that the price and the profit of an incumbent firm may increase after a new firm enters its market. Our analysis suggests that a well-established firm after competition emerges on its market might benefit from excluding some consumers from the low- end segment and concentrate only on its loyal consumers. We also find that strategic de-marketing can increase social welfare.

A multimedia indexing and retrieval framework for multimedia database systems

The main challenges of multimedia data retrieval lie in the effective mapping between low-level features and high-level concepts, and in the individual users' subjective perceptions of multimedia content. ^ The objectives of this dissertation are to develop an integrated multimedia indexing and retrieval framework with the aim to bridge the gap between semantic concepts and low-level features. To achieve this goal, a set of core techniques have been developed, including image segmentation, content-based image retrieval, object tracking, video indexing, and video event detection. These core techniques are integrated in a systematic way to enable the semantic search for images/videos, and can be tailored to solve the problems in other multimedia related domains. In image retrieval, two new methods of bridging the semantic gap are proposed: (1) for general content-based image retrieval, a stochastic mechanism is utilized to enable the long-term learning of high-level concepts from a set of training data, such as user access frequencies and access patterns of images. (2) In addition to whole-image retrieval, a novel multiple instance learning framework is proposed for object-based image retrieval, by which a user is allowed to more effectively search for images that contain multiple objects of interest. An enhanced image segmentation algorithm is developed to extract the object information from images. This segmentation algorithm is further used in video indexing and retrieval, by which a robust video shot/scene segmentation method is developed based on low-level visual feature comparison, object tracking, and audio analysis. Based on shot boundaries, a novel data mining framework is further proposed to detect events in soccer videos, while fully utilizing the multi-modality features and object information obtained through video shot/scene detection. ^ Another contribution of this dissertation is the potential of the above techniques to be tailored and applied to other multimedia applications. This is demonstrated by their utilization in traffic video surveillance applications. The enhanced image segmentation algorithm, coupled with an adaptive background learning algorithm, improves the performance of vehicle identification. A sophisticated object tracking algorithm is proposed to track individual vehicles, while the spatial and temporal relationships of vehicle objects are modeled by an abstract semantic model. ^

Color-based surface reflectance separation for scene illumination estimation and rendering

Given the importance of color processing in computer vision and computer graphics, estimating and rendering illumination spectral reflectance of image scenes is important to advance the capability of a large class of applications such as scene reconstruction, rendering, surface segmentation, object recognition, and reflectance estimation. Consequently, this dissertation proposes effective methods for reflection components separation and rendering in single scene images. Based on the dichromatic reflectance model, a novel decomposition technique, named the Mean-Shift Decomposition (MSD) method, is introduced to separate the specular from diffuse reflectance components. This technique provides a direct access to surface shape information through diffuse shading pixel isolation. More importantly, this process does not require any local color segmentation process, which differs from the traditional methods that operate by aggregating color information along each image plane. ^ Exploiting the merits of the MSD method, a scene illumination rendering technique is designed to estimate the relative contributing specular reflectance attributes of a scene image. The image feature subset targeted provides a direct access to the surface illumination information, while a newly introduced efficient rendering method reshapes the dynamic range distribution of the specular reflectance components over each image color channel. This image enhancement technique renders the scene illumination reflection effectively without altering the scene’s surface diffuse attributes contributing to realistic rendering effects. ^ As an ancillary contribution, an effective color constancy algorithm based on the dichromatic reflectance model was also developed. This algorithm selects image highlights in order to extract the prominent surface reflectance that reproduces the exact illumination chromaticity. This evaluation is presented using a novel voting scheme technique based on histogram analysis. ^ In each of the three main contributions, empirical evaluations were performed on synthetic and real-world image scenes taken from three different color image datasets. The experimental results show over 90% accuracy in illumination estimation contributing to near real world illumination rendering effects. ^

Biogeochemical Classification of South Florida’s Estuarine and Coastal Waters of Tropical Seagrasses

South Florida’s watersheds have endured a century of urban and agricultural development and disruption of their hydrology. Spatial characterization of South Florida’s estuarine and coastal waters is important to Everglades’ restoration programs. We applied Factor Analysis and Hierarchical Clustering of water quality data in tandem to characterize and spatially subdivide South Florida’s coastal and estuarine waters. Segmentation rendered forty-four biogeochemically distinct water bodies whose spatial distribution is closely linked to geomorphology, circulation, benthic community pattern, and to water management. This segmentation has been adopted with minor changes by federal and state environmental agencies to derive numeric nutrient criteria.

Employment status and health in Spain before and after the Great Recession

This article analyzes the relationship between employment status (ES), on one hand, and self-rated health and psychological distress, on the other, in the context of the Great Recession beginning in 2008. For this purpose, it is necessary to move beyond the employment/unemployment dichotomy characteristics of previous theories and research concerning the relationship between the labor market, recession, and health. The authors use data from the Spanish National Health Surveys in 2006 (n = 15,128), before the crisis, and in 2012 (n = 11,124), when its consequences had taken effect. The results of the regression analysis indicate a structural change in the relationship between ES and health. Health inequality patterns changed during the crisis, with increased deterioration in the health of unemployed, especially the long-term unemployed, and self-employed workers. Health inequalities were reduced for temporary workers. The results support the idea that the structure of the association between ES and health varies according to the economic cycle. The association between recession, ES, and health would be directly related to the specific characteristics of the economic and employment contexts under study. In the Spanish case, labor market segmentation processes based on numerical flexibility—a key feature of the Mediterranean Variety of Capitalism—may explain the results obtained.

A methodology for hierarchical image segmentation evaluation

This paper proposes a method to evaluate hierarchical image segmentation procedures, in order to enable comparisons between different hierarchical algorithms and of these with other (non-hierarchical) segmentation techniques (as well as with edge detectors) to be made. The proposed method builds up on the edge-based segmentation evaluation approach by considering a set of reference human segmentations as a sample drawn from the population of different levels of detail that may be used in segmenting an image. Our main point is that, since a hierarchical sequence of segmentations approximates such population, those segmentations in the sequence that best capture each human segmentation level of detail should provide the basis for the evaluation of the hierarchical sequence as a whole. A small computational experiment is carried out to show the feasibility of our approach.

When Consumption Embraces Faith: How Religious Beliefs and Practices Influence Consumption

Marketers have long looked for observables that could explain differences in consumer behavior. Initial attempts have centered on demographic factors, such as age, gender, and race. Although such variables are able to provide some useful information for segmentation (Bass, Tigert, and Longdale 1968), more recent studies have shown that variables that tap into consumers’ social classes and personal values have more predictive accuracy and also provide deeper insights into consumer behavior. I argue that one demographic construct, religion, merits further consideration as a factor that has a profound impact on consumer behavior. In this dissertation, I focus on two types of religious guidance that may influence consumer behaviors: religious teachings (being content with one’s belongings), and religious problem-solving styles (reliance on God).

Essay 1 focuses on the well-established endowment effect and introduces a new moderator (religious teachings on contentment) that influences both owner and buyers’ pricing behaviors. Through fifteen experiments, I demonstrate that when people are primed with religion or characterized by stronger religious beliefs, they tend to value their belongings more than people who are not primed with religion or who have weaker religious beliefs. These effects are caused by religious teachings on being content with one’s belongings, which lead to the overvaluation of one’s own possessions.

Essay 2 focuses on self-control behaviors, specifically healthy eating, and introduces a new moderator (God’s role in the decision-making process) that determines the relationship between religiosity and the healthiness of food choices. My findings demonstrate that consumers who indicate that they defer to God in their decision-making make unhealthier food choices as their religiosity increases. The opposite is true for consumers who rely entirely on themselves. Importantly, this relationship is mediated by the consumer’s consideration of future consequences. This essay provides an explanation to the existing mixed findings on the relationship between religiosity and obesity.

Temporary contracts and non-protected employment in Argentina, Chile and Perú: incidence and determinants

The diverse kinds of legal temporary contracts and the employment forms that do not comply with legal requirements both facilitate employment adjustment to firms´ requirements and entail labour cost reductions. Their employment incidence depends not only on the economic and labour market evolutions but also on other factors, in particular the historical trajectories followed by labour legislation, state enforcement, and the degree of compliance. To contribute to the understanding of the determinants of the degree of utilization of different employment practices, the study reported in this article explores the use made of the various legal temporary contracts and of precarious employment relationships by private enterprises in three Latin American countries (Argentina, Chile and Peru) during 2003-2012, a period of economic growth, and the explanatory role of diverse factors.