This thesis presents several techniques that advance search-based algorithms for solving Constraint Optimization Problems (COPs). These techniques exploit structural features common in such problems. In particular, the thesis presents a number of innovative algorithms, and associated data structures, designed to exploit decomposition and symmetry in COPs. First, a new technique called component templating is introduced. Component templates are data structures for efficiently representing the disjoint sub-problems that are encountered during search. Information about each disjoint sub-problem can then be reused during search, increasing efficiency. A new algorithm called OR-decomposition is introduced. This algorithm obtains many of the computational benefits of decomposition without the need to resort to separate recursions. That is, the algorithm explores a standard OR tree rather than an AND-OR tree. In this way, the search algorithm gains greater freedom in its variable ordering compared to previous decomposition algorithms. Although decomposition algorithms such as OR-decomposition are effective techniques for solving COPs with low tree-width, existing decomposition algorithms offer little advantage over branch and bound search on problems with high tree-width. A new method for exploiting decomposition on problems with high tree-width is presented. This technique involves detecting and exploiting decompositions on a selected subset of the problem’s objectives. Such decompositions can then be used to more efficiently compute additional bounds that can be used by branch and bound search. The second half of the thesis explores the use of symmetries in COPs. Using component templates, it is possible to exploit dynamic symmetries that appear during search when some of the variables of a problem have been assigned a value. Symmetries have not previously been combined with decomposition in COPs. An algorithm called Set Branching is presented, which exploits almost-symmetries in the values of a variable by clustering similar values together, then branching on sets of values rather than on each single value. The decomposition and symmetry algorithms presented in this thesis increase the efficiency of constraint optimization solvers. The thesis also presents experimental results that test these algorithms on a variety of real world problems, and demonstrate performance improvements over current state-of-the-art techniques.

This multiple case study describes students who are highly emotionally competent yet have learning disabilities. The study sheds light on how such students perceive their educational experience and begins to answer inter-related questions, such as how emotional strengths assist with learning disabilities. A multiple case study design was used. The participant group ranged from 11 to 16 years of age and came from two separate schools which actively work with students diagnosed with learning disabilities. The study was divided into two phases. In the first phase, the Mayer—Salovey—Caruso Emotional Intelligence Test-Youth Version (MSCEIT-YV) was given to students in the two participating classes. The two students from each class who achieved the highest scores on the MSCEIT-YV were then asked to participate in the second phase of the study. Here, the researcher conducted observations of the participants within the school environment. Additionally, the participants attended a semi-structured interview, with interview questions based on the MSCEIT-YV and school related scenarios. Themes that emerged were then analyzed and compared within and between cases as well as with emotional intelligence research. Case study descriptions emerged from this analysis and a brief follow up interview was conducted with one family member and the participating student as a means of sharing and verifying findings. Participants revealed varying ability with emotional intelligence. However, all students demonstrated strong abilities with the ‘Strategic Emotional Reasoning’ Skills associated with Mayer, Salovey and Caruso’s (2004) theory of emotional intelligence. Moreover, all students showed a strong ability to use their emotional intelligence to improve academic functioning, with one student in particular displaying outstanding abilities and insights into emotional intelligence. The study contributes to our understanding of the complexity of ability and disability that can exist within students diagnosed with learning disabilities; this understanding, in turn, may be reflected in how these students are perceived and understood by researchers and teachers alike.

Due to the fast development of new technologies, the Business Intelligence market is changing rapidly, forcing vendors to adapt their offerings to the customers’ needs. As the amount of data available to companies has been substantially increasing in the past years, the need of suitable software tools that perform the right analyses became essential, even in the small and medium sized business' environment. The previous literature,focused on big firms and traditional implementation of Business Intelligence solutions, highlighted the importance of understanding the key factors in successful projects. In the past few years, a new delivery model for Business Intelligence software is taking place: the cloud computing. To date, key factors for adopting cloud Business Intelligence in small and medium sized enterprises (SMEs) have not been systematically investigated. Existing studies have rarely considered these arguments and we lack of a proven framework. This paper is aimed to fill this gap and the structure of the article is subordinated to this objective. Firstly, the thesis offers an overview of the subject and the terminology used in it with the purpose of facilitating the understanding of a rather complex argument. Therefore, it starts with a short historical overview of the Business Intelligence sector, it defines the term Business Intelligence, and it explains both the characteristics of the Business Intelligence systems (cloud vs on-premise) and the importance of having a business intelligence solution for SME. Subsequently, the theoretical framework of this study is defined, combining the prior theories and empirical data collected through the interviews with four Business Intelligence vendors and customers. Initially, the existing Critical Success Factors (CSFs) of IT and BI projects proposed by different authors in the literature are reviewed. Afterwards, the evaluation criteria for the cloud software are taken into consideration. By integrating insights drawn from these studies, as well as adding new factors coming from the interviews, a framework has been created and utilized as a basis for the further questionnaire development. The choice of pursuing both the quantitative and qualitative approaches is aimed at improving the study’s reliability. Empirical data are mainly primary data, collected during a survey and four interviews, supported by secondary data such as general companies' reports, market and trends analysis from trustworthy sources. Based on the findings, the author of this thesis has ranked the key aspects of a cloud BI adoption in SMEs. It is revealed the most important key adoption factors that SMEs evaluate when purchasing a cloud BI solution are the level of software functionalities, the ubiquitous access to data, the responsive answers to customer support requests, the ability to handle big amount of data and the implementation cost. Regarding the managerial implications, the study’s practical relevance consists in offering to BI suppliers' managers, executives and decision-makers interesting areas of discussion for improving the knowledge of SMEs' needs. Moreover, the results of this investigation can be used by Business Intelligence newcomers as a guidance for evaluating solutions available in the market.

The area of Business Intelligence (BI) is both broad and multifaceted and is becoming an increasingly pervasive tool utilized within organizations allowing them to gain greater insight into their business operations as well as well as the way in which their customers interact with them. By enabling businesses to perform powerful, effective analytics and reporting, BI tools allow them to maximize use of their data and facilitate better planning, forecasting and the ability to have a more targeted and efficient value chain. Usage of BI tools allow organizations to not only achieve but leverage their competitive advantage. SMEs are no different in their pursuit for competitive advantage and market share but often is the case that they lack the resources in order to make the substantial investments into the software and infrastructure required to host a solution on-premise. The Software-as-a-Service (SaaS) model of allowing users to have access to powerful tools and services without having to purchase the solutions or the infrastructure needed to host it on-premise allows SMEs an ideal opportunity to perform many or all of the functionalities that on-premise BI provides. SaaS BI is a relatively new concept only a few years old, but improvements in functionality and features, reliability of service levels and lower costs are allowing it to gain traction and it is projected to increase its momentum in the next few years. The aim of this paper is to investigate the factors that lead to adoption/non-adoption, assigned importance and perceived business value of SaaS BI within SMEs. These issues will be addressed through identification of the key decision criteria that influence SMEs to adopt SaaS BI solutions over an on-premise solution and vice versa. Greater insight into the decision making process, usage and value will be investigated with the cooperation of two vendors within the BI field. A two pronged approach targeting both SaaS and on-premise BI vendors and the users is adopted in order to find out the perspective on either end and whether or not they are incongruent. Semi-structured interviews were targeted at both an on-premise vendor and a SaaS vendor and their customers. A questionnaire was deployed to clients of both these vendors. Analysis was then conducted on the findings using an integrated selection model encompassing BI and SaaS theories and concepts outlined in the paper. 

Omvärlden ändras snabbt, vilket sätter press på moderna organisationer. Organisationer kan därför använda sig av Business Intelligence (BI) till att fatta bra och effektiva beslut. Enligt författare till litteratur, skribenter på Internettidningar, och debattörer på Internet, kan det dock vara skillnad på hur BI används i små och stora organisationer, då dessa inte har samma förutsättningar till BI användande (Chang, 2009). Vid påbörjandet av denna studie var det oklart hur SME och stora organisationer använder BI, samt på vilket sätt BI användande i SME och stora organisationer skiljde sig, och vad denna skillnad bestod av. Det fanns alltså kunskapsbrist inom detta område inom BI. För att berika ämnet BI med ny kunskap gjordes därför en studie där BI användandet i SME och stora organisationer beskrevs, samt redogjordes det för de skillnader som upptäcktes mellan BI användandet i SME och stora organisationer. Andra författare hade visserligen skrivit om BI användande i SME, fast de hade inte gjort någon typ av jämförelse mellan BI användande i små och stora organisationer. Även detta sågs som kunskapsbrist. En induktiv ansats med kvalitativ metod användes när empiri insamlades. Fokus var att samla mycket information av bra kvalitet om få enheter, vilket dessa metoder lämpade sig bra till. Totalt intervjuades sex enheter. Fem enheter intervjuades personligt, och en enhet fick svara på enkätfrågor samt intervjuades via telefon. För att kunna beskriva de fenomen som uppstod i empirin utifrån en "BI synvinkel" användes en teoretisk bakgrund när studien gjordes. Den teoretiska bakgrunden beskrev bland annat vad BI är för något, hur det används, varför det används, samt de komponenter och aktiviteter som hör till BI. I diskussionskapitlet redovisades och diskuterades SME och stora organisationers BI användande, samt den skillnad som upptäcktes gällande BI användandet. Dessa resultat kopplades också till den teoretiska bakgrunden för att beskrivas utifrån en "BI synvinkel". Resultaten kopplades även till den tidigare forskning som var gjord om detta ämne för att se vilka likheter och skillnader som fanns. Slutsatserna i uppsatsen tydde på att det inte fanns särskilt många skillnader mellan SME och stora organisationers BI användande. Slutsatserna tydde även på att resultaten inte var generella, då få enheter undersöktes. Resultaten ansågs dock som konkreta då skillnaderna(och likheterna) som faktiskt fanns, framkom tydligt. Slutligen gavs förslag på fortsatt forskning till läsarna och förslag på hur en studie likt denna kan bli mer "generaliserbar".

Limitations may exist in the current practices to assess and identify giftedness, particularly among children of poverty (Davis & Rimm, 2004; Slocumb & Payne, 2000). The purpose of this study was to examine educators perceptions about the concept of giftedness, specifically if children of poverty are being adequately identified in the recruitment process for enrichment programs. An adapted version of the survey entitled, Assumptions Underlying the Identification of Gifted and Talented Students (Renzulli, Brown, & Gubbins, 2005) was distributed to approximately 500 administrators, classroom teachers, and resource room/learning assistance teachers of elementary schools in a large urban school division. There were 101 respondents. The survey consisted of twenty-five statements, utilizing a five point Likert scale, exploring teachers perceptions of assessment practices used to identify gifted and/or talented students. Respondents were also invited to convey their personal professional opinions regarding giftedness by answering a series of open-ended questions. <p>Descriptive analyses (e.g., mean, standard deviation) of continuous variables (e.g., years of experience), and frequency distributions of categorical variables (e.g., school setting, current position) were conducted. Analyses of variance (ANOVAs) were conducted for comparisons among the average responses (i.e., teacher responses, administrator responses) for each factor. In addition, Pearson correlations were also conducted to investigate relationships between dependent variables (e.g., the factors) and independent variables (e.g., age, years of experience). Open-ended questions were categorized with consideration to common themes based upon the responses of the participants and analyzed using descriptive analyses. The culminating examinations and interpretations indicated that educators believe the processes of defining and identifying giftedness among students in poverty are flawed and restrictive. Furthermore, the responses were indicative of educators desires to embrace giftedness in a variety of contexts and domains.

The purpose of the study was to examine the relationship between emotional intelligence and leadership styles among Texas AgriLife Extension Service mid‐managers. A web based three part instrument was administered to participants. A general questionnaire about demographics, work history and views of leadership was part one. The Multifactor Leadership Questionnaire (MLQ form 5x) developed by Avolio and Bass examined the leader’s self reported leadership style. The MLQ identifies scores for transformational, transactional and laissez‐faire leadership styles and those were compared with scores on the BarOn Emotional Quotient Inventory Test (EQ‐i). An independent samples t test was performed to assess whether the mean EI subscales scores for the high transformational leadership group differed significantly from the low transformational leadership group. Six EI constructs were statistically significant in relation to transformational leadership behavior. The six were: optimism, happiness, empathy, interpersonal relationships, self‐regard, and stress tolerance. An independent samples t test was performed to assess whether the mean EI subscales scores for the high transactional leadership group differed significantly from the low transactional leadership group. Social responsibility was the one EI construct that was statistically significant in relation to transactional leadership behavior. The findings from this study indicate the leaders can develop and strengthen emotional intelligence and in doing so can more likely exhibit the use of transformational leadership behaviors. Further study would be needed to demonstrate the extent of possible application, but it is commendable that if leaders are trained in EI and those skills are fostered, they will be more likely to utilize transformational leadership further resulting in organizational effectiveness and follower satisfaction.

<p>The area of Business Intelligence (BI) is both broad and multifaceted and is becoming an increasingly pervasive tool utilized within organizations allowing them to gain greater insight into their business operations as well as well as the way in which their customers interact with them. By enabling businesses to perform powerful, effective analytics and reporting, BI tools allow them to maximize use of their data and facilitate better planning, forecasting and the ability to have a more targeted and efficient value chain. Usage of BI tools allow organizations to not only achieve but leverage their competitive advantage. SMEs are no different in their pursuit for competitive advantage and market share but often is the case that they lack the resources in order to make the substantial investments into the software and infrastructure required to host a solution on-premise. The Software-as-a-Service (SaaS) model of allowing users to have access to powerful tools and services without having to purchase the solutions or the infrastructure needed to host it on-premise allows SMEs an ideal opportunity to perform many or all of the functionalities that on-premise BI provides. SaaS BI is a relatively new concept only a few years old, but improvements in functionality and features, reliability of service levels and lower costs are allowing it to gain traction and it is projected to increase its momentum in the next few years. The aim of this paper is to investigate the factors that lead to adoption/non-adoption, assigned importance and perceived business value of SaaS BI within SMEs. These issues will be addressed through identification of the key decision criteria that influence SMEs to adopt SaaS BI solutions over an on-premise solution and vice versa. Greater insight into the decision making process, usage and value will be investigated with the cooperation of two vendors within the BI field. A two pronged approach targeting both SaaS and on-premise BI vendors and the users is adopted in order to find out the perspective on either end and whether or not they are incongruent. Semi-structured interviews were targeted at both an on-premise vendor and a SaaS vendor and their customers. A questionnaire was deployed to clients of both these vendors. Analysis was then conducted on the findings using an integrated selection model encompassing BI and SaaS theories and concepts outlined in the paper.</p><p></p>

Thèse de doctorat : Sciences informatiques : Paris 12 : 2007. / Thèse uniquement consultable au sein de l'Université Paris 12 (Intranet). Titre provenant de l'écran-titre. Bibliogr. : 77 réf.

Thèse de doctorat : Sciences de l'information et de la communication : Nancy 2 : 2007. / Titre provenant de l'écran-titre.