The strategic alignment in an organization refers to the adequacy and functional integration between external and internal environments to develop skills and maximize organizational performance. In this work, was use the model of Luftman (2000) to analyze the maturity of the strategic alignment, which assesses the relationship of IT with the planning area through a five-level scale, based on six criteria: communication, metrics , governance, partnerships, technology and human resources. According to author, the stronger integration between areas, the highest maturity level of alignment. Was chose to perform this study in two federal universities in the state of RS that have different contexts: one was founded in 1960 and has your processes structured and another was instituted in 2005 and their processes are in developing and consolidation. Departing from this context, the main objective of this dissertation was stipulated that identify the level of alignment between Strategic Planning and Information Technology in both IFES. To achieve this goal, was chose to use the method of multiple case study through a qualitative research of a descriptive nature. The results lead to the identification of different levels of alignment maturity in the institutions, and the institution with longer foundation and more established processes to reach a higher level of maturity regarding the institution with shorter foundation and processes being consolidation. / O alinhamento estratégico em uma organização refere-se à adequação e integração funcional entre ambientes externo e interno para desenvolver as capacidades e maximizar a performance organizacional. Nesse trabalho, foi utilizado o modelo de análise da maturidade do alinhamento estratégico de Luftman (2000), que avalia o relacionamento da área de TI com a área de planejamento através de uma escala de cinco níveis, tendo como base seis critérios: comunicação, métricas, governança, parcerias, tecnologia e recursos humanos. Segundo esse autor, quanto mais forte a integração entre as áreas, mais alto o nível de maturidade do alinhamento. Optou-se realizar esse estudo em duas Instituições Federais de Ensino Superior do interior do estado do RS visto que as mesmas apresentam contextos distintos, sendo que uma foi fundada em 1960 e possui seus processos já estruturados e a outra foi instituída em 2005, passando atualmente pelo processo de elaboração e consolidação de seus processos. Partindo-se desse contexto, foi estipulado como objetivo da dissertação, identificar o nível de maturidade do alinhamento entre PE e TI nas duas IFES. Para atingir esse objetivo, optou-se por utilizar o método de estudo de casos múltiplos, através de uma investigação qualitativa de natureza descritiva. Os resultados obtidos levaram à identificação de níveis diferenciados de maturidade do alinhamento nas instituições, tendo a instituição com maior tempo de fundação e com processos mais estabelecidos atingido um nível maior de maturidade em relação a instituição com menor tempo de fundação e com processos em fase de consolidação.

Business-IT alignment has been a top research topic for three decades now and consistently ranks high on CIO priorities and concerns. In spite of its seeming advantages, sustainable business-IT alignment remains elusive in practice. This can be attributed to the language and knowledge gaps which impede mutual understanding between business and IT stakeholders. It can also be attributed to the limitations imposed by approaching alignment solely from a strategic perspective. This thesis argues for an ontology-based framework that bridges the language and knowledge gaps through closer interaction between business and IT stakeholders throughout the software development and project management lifecycles, especially at the requirements engineering stage. Attempts at achieving sustainable business-IT alignment predominantly focus on strategic alignment and have not been successful for various reasons. Firstly, driving down alignment initiatives to the operational and tactical levels is challenging. Secondly, it is difficult to operationalize the metrics used for evaluating alignment maturity at strategic levels. These limitations are less pronounced at the functional levels of an organization. It is at these levels that business strategies are executed and interaction between business and IT personnel is most frequent. The interaction between business and IT stakeholders in the execution of IT projects presents an opportunity that can be leveraged to drive alignment maturity. The proposed framework is discussed in terms of its underpinning hypotheses, workflows, tool design and implementation, its use with a third party framework and tool. Antecedents to operational and tactical alignment such as quality, reuse, communication, learning, and shared understanding, are proposed as a practical means of achieving sustainable alignment maturity. The framework is applied to real world, business-critical projects in a top global financial services organization and validated using descriptive statistical analysis and structural equation modelling techniques. Contributions made through the study are highlighted. This includes the Alignment Forces Model which unifies the proposed framework and its support tool within software development and project management lifecycles. The Alignment Forces model and how it can be applied in practice is presented. Results of the quantitative data analyses indicate support for the arguments for the framework towards improving business-IT alignment, however with some limitations. Results also indicate support for the hypotheses for the antecedents to sustainable alignment maturity at lower organizational levels put forward. Finally, suggestions on furthering the study, addressing its limitations, and refining the framework and tool are articulated.

This diploma thesis deals with the description of homologous genes and molecular biological databases that are used for their search and allow comparison. Among the most important institutions that deal with data management and analysis, include the EBI, NCBI and CIB. For searching homologous genes is the most fundamental NCBI - National Center for Biotechnology Information. More attention is paid to the search algorithms of homologous genes such as BLASTN and PatternHunter. The practical part of this thesis is the implementation of the algorithm comparing two sequences and locating homologous genes. The comparison is made on the basis of the nucleotide sequence and amino acid sequence. The results generated from the program will be further compared with results from commercially available programs.

A number of attempts have been made to define strategic business and information technology (IT) alignment; several representations of what it is are available in academic and practitioners’ fields. The literature suggests that firms need to achieve strategic business and IT alignment to be competitive. Strategic business and IT alignment impact business performance and IT effectiveness. We propose a unified strategic business and IT alignment model based on four strategic business and IT alignment models: Strategic Alignment Model (SAM), Strategic Alignment Maturity Model (SAMM), information system strategic alignment model and an operational model of strategic alignment. I argue that such a unified model will provide a better understanding of the nature and key aspects of strategic business and IT alignment from different, and sometimes complementary, theories. The unified model represents the concepts and instruments used in these four strategic businesses and IT alignment models. Our principal research goal is to pave the way to develop a common understanding between the different models. The components of the unified strategic business and IT alignment model were ranked with a group of IT experts and business experts from four public universities in Nicaragua. The result can be used as a basis for improving strategic business and IT alignment. / QC 20111212

Due to the explosion of the amount of biomedical data, knowledge and tools that are often publicly available over the Web, a number of difficulties are experienced by biomedical researchers. For instance, it is difficult to find, retrieve and integrate information that is relevant to their research tasks. Ontologies and the vision of a Semantic Web for life sciences alleviate these difficulties. In recent years many biomedical ontologies have been developed and many of these ontologies contain overlapping information. To be able to use multiple ontologies they have to be aligned or merged. A number of systems have been developed for aligning and merging ontologies and various alignment strategies are used in these systems. However, there are no general methods to support building such tools, and there exist very few evaluations of these strategies. In this thesis we give an overview of the existing systems. We propose a general framework for aligning and merging ontologies. Most existing systems can be seen as instantiations of this framework. Further, we develop SAMBO (System for Aligning and Merging Biomedical Ontologies) according to this framework. We implement different alignment strategies and their combinations, and evaluate them in terms of quality and processing time within SAMBO. We also compare SAMBO with two other systems. The work in this thesis is a first step towards a general framework that can be used for comparative evaluations of alignment strategies and their combinations. / <p>Report code: LiU-Tek-Lic-2006:6.</p>

Many applications use multiple cameras to simultaneously capture imagery of a scene from different vantage points on a rigid, moving camera system over time. Multiple cameras often provide unique viewing angles but also additional levels of detail of a scene at different spatio-temporal resolutions. However, in order to benefit from this added information the sources must be temporally aligned. As a result of cost and physical limitations it is often impractical to synchronize these sources via an external clock device. Most methods attempt synchronization through the recovery of a constant scale factor and offset with respect to time. This limits the generality of such alignment solutions. We present an unsupervised method that utilizes a content-based clustering mechanism in order to temporally align multiple non-synchronized image sequences of different and varying spatio-temporal resolutions. We show that the use of temporal constraints and dynamic programming adds robustness to changes in capture rates, field of view, and resolution.

This study sought to evaluate the effectiveness of the third grade Summer Reading Camp (SRC) in a large urban school district. The SRC curriculum was assessed to determine if it aligned with effective remediation and filled the third grade students’ knowledge voids in reading. The study further analyzed how the school district officials selected the curriculum content utilized in the SRC. This study was conducted using qualitative and quantitative methods. Data were collected through questionnaires and interviews of school district personnel on the SRC committee regarding the implementation of the 2012 lesson plan, and from students’ Winter Benchmark Assessment scores. The school district implemented the SRC to fulfill a state requirement that all students who received a Level 1 on the reading Florida Comprehensive Assessment Test (FCAT) Reading must receive remediation. The SRC committee designed the curriculum using the state reading benchmarks and decided the activities required during SRC would be whole group, small group, writing, and independent reading. The program was to be evaluated each year using teacher and administrator survey data and the analysis of test scores to determine changes to be implemented. Of the 10 benchmarks assessed on the school district reading benchmark test, only three were aligned with the students’ knowledge voids. There were a total of eight FCAT tested reading benchmarks that were not taught during SRC. The researcher suggests the school district re-align the curriculum with the needs of the students as identified by the Winter Reading Benchmark. It is further recommended that each iii student’s specific remediation needs be evaluated to ensure the curriculum is meeting the needs of all the students in attendance at SCR.

Machine face recognition has traditionally been studied under the assumption of a carefully controlled image acquisition process. By controlling image acquisition, variation due to factors such as pose, lighting, and background can be either largely eliminated or specifically limited to a study over a discrete number of possibilities. Applications of face recognition have had mixed success when deployed in conditions where the assumption of controlled image acquisition no longer holds. This dissertation focuses on this unconstrained face recognition problem, where face images exhibit the same amount of variability that one would encounter in everyday life. We formalize unconstrained face recognition as a binary pair matching problem (verification), and present a data set for benchmarking performance on the unconstrained face verification task. We observe that it is comparatively much easier to obtain many examples of unlabeled face images than face images that have been labeled with identity or other higher level information, such as the position of the eyes and other facial features. We thus focus on improving unconstrained face verification by leveraging the information present in this source of weakly supervised data. We first show how unlabeled face images can be used to perform unsupervised face alignment, thereby reducing variability in pose and improving verification accuracy. Next, we demonstrate how deep learning can be used to perform unsupervised feature discovery, providing additional image representations that can be combined with representations from standard hand-crafted image descriptors, to further improve recognition performance. Finally, we combine unsupervised feature learning with joint face alignment, leading to an unsupervised alignment system that achieves gains in recognition performance matching that achieved by supervised alignment.

Retention of engineering students to graduation and career is important business for both United States (U.S.) industries and engineering education institutions alike. Industries need competent engineers dedicated to working in the field of engineering beyond graduation in order to achieve business success and national economic growth, while engineering education institutions need retention to graduation to achieve their own business goals. This dissertation took a three-pronged approach to identifying relationships between depth and specificity of engineering and response factors related to graduation and career retention of engineers. Occupational alignment, graduate school decisions, and engineering identity were evaluated for relationships with specificity or depth of discipline within engineering degrees to evaluate if increasing the depth or specificity increased the response factors. Using historical data analysis, occupational alignment and graduate school decisions were both found to be influenced by specificity of discipline. Traditional engineering disciplines were found to report the most occupational alignment after graduation, while specific engineering disciplines were more likely to attend graduate school after graduation. Additionally, for all students reporting graduate school attendance, all specificities were most likely to align their graduate degree discipline to their undergraduate degree discipline. A national survey of undergraduate engineering students revealed that engineering identity is related to depth of discipline. Students enrolled in more specific engineering curriculum, in the form of a discipline-specific major with a concentration, reported higher engineering identity. However, the discipline-specific depth of discipline followed closely behind, indicating the impact of depth of discipline is small. The largest difference in scores between the two depths of discipline was found in students' reports of a construct termed "interest". Ultimately, this dissertation found statistically significant relationships between depth and specificity of discipline and occupational alignment, graduate school decisions, and engineering identity. Though these findings are statistically significant, they were incremental, meaning depth and specificity of discipline should not be considered the main factor of influence.

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