A novel large-scale silicon system platform with 9.6cm² of active silicon interposer area is demonstrated. The platform contains three interposer tiles and two silicon bridges, and a novel self-alignment technology utilizing positive self-alignment structures (PSAS) and a novel mechanically flexible interconnect (MFI) technology are developed and used to align and interconnect tiles and bridges on an FR4 substrate. An accurate alignment < 8μm between silicon bridges and interposer tiles makes it possible to accommodate nanophotonics to enable a high bandwidth and low-energy system in the future. In addition, mechanically flexible interconnects and silicon bridges are used to provide electrical connections between interposer tiles without having to use motherboard-level interconnects. Finally, an elastomeric bump interposer is developed to enable the packaging of PSAS-enabled silicon systems, and PSAS' compatibility with a thermo-compression bonding process is demonstrated to enable a wide range of system configurations involving interposer tiles and bridges, including the multi-chip package configuration used with the elastomeric bump interposers.

This thesis presents a Fuzzy Consensus Building Framework (FCBF), which enables construction project parties to align their teams on their roles and responsibilities early on in their projects. The framework introduces a model that (1) incorporates consensus of construction project teams in aggregating their opinions to decide on the party responsible for every standard task of a construction project; (2) classifies the quality of experts in the decision making process by weighting their responses during aggregation, based on their attributes; and (3) resolves residual conflicts between project teams on their perceived shared tasks, using a consensus reaching process. A template of project and construction management tasks is extracted from relevant standard guidelines and interviews with industry peers. Different extents of the roles and responsibilities of the owner and contractors are described using seven linguistic terms. A modified similarity aggregation method (SAM) aggregates experts opinions in a linguistic framework, using a consensus weight factor for each expert. A fuzzy expert system (FES) determines an importance weight factor for each expert, representing expert quality; opinions are aggregated using this factor and the consensus weight factor. Based on the aggregated opinions of experts, the tasks are classified into three responsibility lists: the owners, the contractors, and the shared responsibility list. The fuzzy preference relations consensus (FPRC) approach is applied to the tasks of shared responsibility, and a linguistic consensus measure is applied to resolve potential conflicts between team members on their perceived shared tasks. Using a case study approach, the FCBF is applied to aid a project owner organization in the field of oil and gas to determine its roles and responsibilities in a customized project delivery system, called owner managing contractor (OMC). The FCBF contributes to the construction industry by solving a fundamental problem for project owners: it helps identify and reduce potential conflicts over the extent of project teams responsibilities prior to the construction stage. It also provides an improvement over previous consensus-based approaches, which rely on a subjective assessment of experts importance weights in aggregating their opinions, and it modifies the SAM to adapt it to a linguistic environment. / Construction Engineering and Management

Thesis (Ph.D)--Industrial and Systems Engineering, Georgia Institute of Technology, 2009. / Committee Chair: Lee, Eva K.; Committee Member: Barnes, Earl; Committee Member: Fan, Yuhong; Committee Member: Johnson, Ellis; Committee Member: Yuan, Ming. Part of the SMARTech Electronic Thesis and Dissertation Collection.

Modern computer vision has seen recently significant progress in learning visual concepts from examples. This progress has been fuelled by recent models of visual appearance as well as recently collected large-scale datasets of manually annotated still images. Video is a promising alternative, as it inherently contains much richer information compared to still images. For instance, in video we can observe an object move which allows us to differentiate it from its surroundings, or we can observe a smooth transition between different viewpoints of the same object instance. This richness in information allows us to effectively tackle tasks that would otherwise be very difficult if we only considered still images, or even adress tasks that are video-specific. Our first contribution is a computationally efficient technique for video object segmentation. Our method relies solely on motion in order to rapidly create a rough initial estimate of the foreground object. This rough initial estimate is then refined through an energy formulation to be spatio-temporally smooth. The method is able to handle rapidly moving backgrounds and objects, as well as non-rigid deformations and articulations without having prior knowledge about the objects appearance, size or location. In addition to this class-agnostic method, we present a class-specific method that incorporates additional class-specific appearance cues when the class of the foreground object is known in advance (e.g. a video of a car). For our second contribution, we propose a novel model for temporal video alignment with regard to the viewpoint of the foreground object (i.e., a pair of aligned frames shows the same object viewpoint) Our work relies on our video object segmentation technique to automatically localise the foreground objects and extract appearance measurements solely from them instead of the background. Our model is able to temporally align realistic videos, where events may occur in a different order, or occur only in one of the videos. This is in contrast to previous works that typically assume that the videos show a scripted sequence of events and can simply be aligned by stretching or compressing one of the videos. As a final contribution, we once again use our video object segmentation technique as a basis for automatic visual aspect discovery from videos of an object class. Compared to previous works, we use a broader definition of an aspect that considers four factors of variation: viewpoint, articulated pose, occlusions and cropping by the image border. We pose the aspect discovery task as a clustering problem and provide an extensive experimental exploration on the benefits of object segmentation for this task.

DNA sequence alignment is a fundamental task in gene information processing, which is about searching the location of a string (usually based on newly collected DNA data) in the existing huge DNA sequence databases. Due to the huge amount of newly generated DNA data and the complexity of approximate string match, sequence alignment becomes a time-consuming process. Hence how to reduce the alignment time becomes a significant research problem. Some algorithms of string alignment based on HASH comparison, suffix array and BWT, which have been proposed for DNA sequence alignment. Although these algorithms have reached the speed of O(N), they still cannot meet the increasing demand if they are running on traditional CPUs. Recently, GPUs have been widely accepted as an efficient accelerator for many scientific and commercial applications. A typical GPU has thousands of processing cores which can speed up repetitive computations significantly as compared to multi-core CPUs. However, sequence alignment is one kind of computation procedure with intensive data access, i.e., it is memory-bounded. The access to GPU memory and IO has more significant influence in performance when compared to the computing capabilities of GPU cores. By analyzing GPU memory and IO characteristics, this thesis produces novel parallel algorithms for DNA sequence alignment applications. This thesis consists of six parts. The first two parts explain some basic knowledge of DNA sequence alignment and GPU computing. The third part investigates the performance of data access on different types of GPU memory. The fourth part describes a parallel method to accelerate short-read sequence alignment based on BWT algorithm. The fifth part proposes the parallel algorithm for accelerating BLASTN, one of the most popular sequence alignment software. It shows how multi-threaded control and multiple GPU cards can accelerate the BLASTN algorithm significantly. The sixth part concludes the whole thesis. To summarize, through analyzing the layout of GPU memory and comparing data under the mode of multithread access, this thesis analyzes and concludes a perfect optimization method to achieve sequence alignment on GPU. The outcomes can help practitioners in bioinformatics to improve their working efficiency by significantly reducing the sequence alignment time.

Educational games have become an established paradigm of instructional practice; however, there is still much to be learned about how to design games to be the most beneficial for learners. An important consideration when designing an educational game is whether there is good alignment between its content goals and the instructional behaviors it makes in order to reinforce those goals. Existing methods for measuring alignment are labor intensive and use complex auditing procedures, making it difficult to define and evaluate this alignment in order to guide the educational game design process. This thesis explores a way to operationalize this concept of alignment and demonstrates an analysis technique that can help educational game designers to both measure the alignment of current educational game designs and predict the alignment of prototypes of future iterations. In my work, I explore the use of Replay Analysis, a novel technique that uses in-game replays of player sessions as a data source to support analysis. This method can be used to capture gameplay experience for the evaluation of alignment, as well as other forms of analysis. The majority of this work has been performed in the context of RumbleBlocks, an educational game that teaches basic structural stability and balance concepts to young children. Using Replay Analysis, I leveraged replay data during a formative evaluation of RumbleBlocks to highlight some misalignments the game likely possesses in how it teaches some concepts of stability to players. These results led to suggestions for several design iterations. Through exploring these design iterations, I further demonstrate an extension of Replay Analysis called Projective Replay Analysis, which uses recorded student replay data in prototypes of new versions of a game to predict whether the new version would be an improvement. I implemented two forms of Projective Replay: Literal Projective Replay, which uses a naïve player model that replays past player actions through a new game version exactly as they were originally recorded; and Flexible Projective Replay, which augments the process with an AI player model that uses prior player actions as training data to learn to play through a new game. To assess the validity of this method of game evaluation, I performed a new replication study of the original formative evaluation to validate whether the conclusions reached through virtual methods would agree with those reached in a normal playtesting paradigm. Ultimately, my findings were that Literal Projective Replay was able to predict a new and unanticipated misalignment with the game, but Flexible Projective Replay, as currently implemented, has limitations in its ability to explore new game spaces. This work makes contributions to the fields of human-computer interaction by exploring the benefits and limitations of different replay paradigms for the evaluation of interactive systems; learning sciences by establishing a novel operationalization of alignment for instructional moves; and educational game design by providing a model for using Projective Replay Analysis to guide the iterative development of an educational game.

Information Technology (IT) has emerged as an important issue for the public and private sectors. It has been initially identified as a vehicle in supporting business processes by speeding up the process of decision making and easy access of information as required for the competitive advantage of businesses. Organisations regarded IT as an enabler of their business processes. As IT has grown, its shape and definition have drastically changed from being an enabler of the business processes to become a central and strategic concern within the organisation that drives the business processes. The new IT landscape has made organisations completely dependant on IT for their decision making and effective functioning. The dependence on IT has created a need for unified and effective structures, standards and best practices that ensure the effective execution of business processes using IT. The establishment of IT Governance for institutions of higher learning has created the dual challenges of how IT Governance can work within the culture of inclusiveness and shared decision making while better aligning existing IT structures. These dual challenges vary from one university to another based on the culture of the specific university. This study therefore suggests possible ways that IT Governance can shape an institution of higher learning by strategically aligning the institution’s IT strategy with the overall university strategy through the development of an IT Governance Model. To come up with the said proposed model, qualitative research techniques such as document analysis, observations, interviews, a questionnaire and briefing sessions were used during the research process. The comparative analysis of the case studied was used to identify different IT Governance models adopted by other universities. Literature was reviewed to establish the emerging IT Governance practices established and implemented by different authors. The result from this study is that an IT Governance model specific to WSU has been developed. This model can be used as guiding tool in establishing new IT Governance structures and also modify and improve the existing IT Governance structure of different institutions of higher learning. This model can further be used to guide the development of the institution IT Governance implementation architecture framework.

Cette thèse présente des outils de vidéo inpainting permettant de reconstruire de manière efficace les zones perdues d'une séquence vidéo. Deux catégories d'approches sont particulièrement étudiées. Dans une première étape les approches basées sur l'exemple sont considérées. Différentes contributions ont été proposées. Une application des méthodes de neighbor embedding pour l'approximation des pixels perdus dans un exemple est d'abord considérée en utilisant deux méthodes de réduction de dimensionnalité: la factorisation de matrice non négative (FMN) et le locally linear embedding (LLE). La méthode d'inpainting proposée a été ensuite adaptée à l'application de dissimulation d'erreurs en utilisant une étape de pré-traitement d'estimation des vecteurs de mouvement perdus. Une approche multisolution a également été considérée pour réduire la complexité. Les évaluations expérimentales de cette approche démontrent son efficacité dans les applications de suppression d'objets et de dissimulation des erreurs. Une deuxième catégorie de méthodes de vidéo inpaintinting a été par la suite étudiée en utilisant une approche basée sur l'optimisation globale d'une fonction d'énergie exprimant la cohérence spatio-temporelle de la région reconstruite. Enfin, le problème d'inpainting des vidéos capturées par des caméras en mouvement a été étudié. L'alignement des images en utilisant une homographie par région montre de meilleure performances que les méthodes classiques d'alignement par optimisation d'une homography par pixel. / This thesis presents video inpainting tools to efficiently recover space-time holes in different kinds of video sequences. Two categories of video inpainting approaches are particularly studied. The first category concerns exemplar-based approach. Several contributions have been proposed for this approach. Neighbor embedding techniques have been proposed for patch sampling using two data dimensionality reductions methods: non-negative matrix factorization (NMF) and locally linear embedding (LLE). An analysis of similarity metrics for patches matching have then been proposed based on both subjective and objective tests. The proposed framework have been also adapted to the error concealment application by using a preprocessing step of motion estimation. A multiresolution approach has been considered to reduce the computational time of the method. The experimental evaluations demonstrate the effectiveness of the proposed video inpainting approach in both object removal and error concealment applications. The video inpainting problem has been also solved using a second approach based on the optimization of a well-defined cost function expressing the global consistency of the recovered regions. The camera moving videos has later been takled by using a region-based homography. The neighboring frames in the sequence are aligned based on segmented planar regions. This method has been shown to give better performance compared to classical optimization-based homography.

The purpose of this research was to determine the value derived from leadership development programmes by line managers. This research was useful in that its findings would add value to organizations and learning institutions that offered leadership development programmes. A qualitative research methodology was used. Convenience sampling technique was used as data gathering was based on the researchers personal contacts and their referrals. This technique is known to be the least reliable. But this was taken into account in interpreting the results. Content analysis was used to analyze data. Themes were identified in the literature review upfront and analyzed in the findings as per the priori content analysis technique. Four main themes were identified from the data. The first theme looked at the maturity level of organizations. Feedback on organizations behaviour during a recession was on of the factors used to determine their maturity level. The second theme focused on factors identified as contributing to the failure of leadership development efforts. The third theme discussed factors that result in the success of leadership development programmes. The last theme looked at the value derived by managers from leadership development programmes. Also considering how managers measured this value. The outcomes of the research were largely aligned to the literature review, with few instances where findings did not reveal any evidence to support or dispute some points. / Dissertation (MBA)--University of Pretoria, 2012. / Gordon Institute of Business Science (GIBS) / unrestricted

The dissertation "Alignment of supply and demand within a supply chain: a qualitative study” determines the causes of the misalignment between the supply and demand within a supply chain, with specific focus on Kraft Foods South Africa. The costs of a mismatch between supply and demand are growing in many industries. Companies have tried various approaches, however these approaches, while useful, have failed to address a number of the drivers of supply-demand mismatch. The literature study starts with an overview of supply chain management. The study covers the various concepts of supply chain management, the importance of supply chain performance, the challenges of managing supply chains, demand management, supply management, as well as the relationship between supply and demand. The literature study continues to cover the various concepts related to the alignment of supply and demand within a supply chain. The study covers the effects of the misalignment between supply and demand within a supply chain, traditional approaches to align supply and demand and the transformation to a more responsive organisation. The various approaches to decrease the supply and demand lead time gap are also discussed. The literature study concludes with an overview of the supply chain of Kraft Foods South Africa, as well as the global Kraft Foods organisation. The review covers the challenges, the sustainable growth plan, the organisational set-up, sources and product range, geographical layout, people, functions and technology involved in Kraft’s supply chain. The review concludes with an overview of the current alignment between supply and demand within Kraft Foods South Africa’s supply chain. Chapter five discusses the details of the research design and methodology that was followed in conducting the research. Chapter six indicates the findings of the structured interviews with the key players in Kraft Foods South Africa’s supply chain. Chapter seven makes certain recommendations for the supply chain of Kraft Foods South Africa that will assist in improving the alignment between supply and demand. / Dissertation (MCom)--University of Pretoria, 2006. / Business Management / unrestricted