The conventional computing techniques are based on the assumption of a near constant source of input power. While this assumption is reasonable for high-end devices such as servers and mobile phones, it does not always hold in embedded devices. An increasing number of Internet of Things (IoTs) is powered by intermittent power supplies which harvest energy from ambient resources, such as vibrations. While the energy harvesters provide energy autonomy, they introduce uncertainty in input power. Intermittent computing techniques were proposed as a coping mechanism to ensure forward progress even with frequent power loss. They utilize non-volatile memory to store a snapshot of the system state as a checkpoint. The conventional security mechanisms do not always hold in intermittent computing. This research takes a top-down approach to design secure intermittent systems. To that end, we identify security threats, design a secure intermittent system, optimize its performance, and evaluate our design using embedded benchmarks. First, we identify vulnerabilities that arise from checkpoints and demonstrates potential attacks that exploit the same. Then, we identify the minimum security requirements for protecting intermittent computing and propose a generic protocol to satisfy the same. We then propose different security levels to configure checkpoint security based on application needs. We realize configurable intermittent security to optimize our generic secure intermittent computing protocol to reduce the overhead of introducing security to intermittent computing. Finally, we study the role of application in intermittent computing and study the various factors that affect the forward progress of applications in secure intermittent systems. This research highlights that power loss is a threat vector even in embedded devices, establishes the foundation for security in intermittent computing. / Doctor of Philosophy / The embedded systems are present in every aspect of life. They are available in watches, mobile phones, tablets, servers, health aids, home security, and other everyday useful technology. To meet the demand for powering up a rising number of embedded devices, energy harvesters emerged as a solution to provide an autonomous solution to power on low-power devices. With energy autonomy, came energy scarcity that introduced intermittent computing, where embedded systems operate intermittently because of lack of constant input power. The intermittent systems store snapshots of their progress as checkpoints in non-volatile memory and restore the checkpoints to resume progress. On the whole, the intermittent system is an emerging area of research that is being deployed in critical locations such as bridge health monitoring. This research is focused on securing intermittent systems comprehensively. We perform a top-down analysis to identify threats, mitigate them, optimize the mitigation techniques, and evaluate the implementation to arrive at secure intermittent systems. We identify security vulnerabilities that arise from checkpoints to demonstrate the weakness in intermittent systems. To mitigate the identified vulnerabilities, we propose secure intermittent solutions to protect intermittent systems using a generic protocol. Based on the implementation of the generic protocol and its performance, we propose several optimizations based on the needs of the application to securing intermittent systems. And finally, we benchmark the security properties using two-way relation between security and application in intermittent systems. With this research, we create a foundation for designing secure intermittent systems.

Hyperspectral imaging (HSI) produces spatial images with pixels that, instead of consisting of three colors, consist of hundreds of spectral measurements. Because there are so many measurements for each pixel, analysis of HSI is difficult. Frequently, standard techniques are used to help make analysis more tractable by representing the HSI data in a different manner. This research explores the utility of representing the HSI data in a learned dictionary basis for the express purpose of material identification and classification. Multiclass classification is performed on the transformed data using the RandomForests algorithm. Performance results are reported. In addition to classification, single material detection is considered also. Commonly used detection algorithm performance is demonstrated on both raw radiance pixels and HSI represented in dictionary-learned bases. Comparison results are shown which indicate that detection on dictionary-learned sparse representations perform as well as detection on radiance. In addition, a different method of performing detection, capitalizing on dictionary learning is established and performance comparisons are reported, showing gains over traditional detection methods.

Due to the rapid variation of the world economic conditions, the situation of property competition has turned from regional into global. The traditional property is facing the unprecedented challenge. Especially after joined the WTO, Taiwan¡¦s traditional property is confronting the turning point to either the better or the worse. In such a rapid-changing economic circumstance, the enterprisers should not only keep in the lead status, but pursue competitive superiority on business strategy. Therefore only making good use of innovation management can make the firms move on with the age. For the past ten years, the growth of business profits are mostly come from reducing the prime cost; however, presently the prime cost has no way to condense down, so finding the new directions and energy for the next phase are the common anxiety to the all enterprisers. At the present time, all the experts believe that the key to making business profits in the next phase is only by creativity and innovation. In recent years, the traditional property has paid much attention on ¡§property innovation¡¨ than before. This could be practiced by several firms absorbing the concept of innovation, and making higher ROI than before, also promoting the constitution of the firms. In this way, ¡§property innovation¡¨ can prove several aspects such as the more proactive development of the firms, and eliminate the stereotype that the traditional property is the declining property. This research is focusing on cognition of OPTION on product innovation during designing and the exploitation process. The innovation of products not just makes the firms operate sustainedly, but also be the only way to earn rich profits. The creativity of a successful innovative product needs to possess the explicit features and orientation. Also, product innovation should gain the consumers¡¦ identification to make the substantial economic benefits. Formerly, the product innovation is discussed from the viewpoints of the products¡¦ exterior designing or the management of the firms, and the both have the great influences on product innovation. This research analyses that the foregoing two points contribute to the consultation and estimation during exploiting the new products, and help to reduce the gap between the consumers and the firms¡¦ R&D department, and in this way, the firms can be closer to the consumers¡¦ needs for the new products. Key word: Innovation¡BInnovation management¡BExploiting the new products¡BOPTION on product innovation

The aim of this research is to investigate parallel problem generation for structured optimization problems. The result of this research has produced a novel parallel model generator tool, namely the Parallel Structured Model Generator (PSMG). PSMG adopts the model syntax from SML to attain backward compatibility for the models already written in SML [1]. Unlike the proof-of-concept implementation for SML in [2], PSMG does not depend on AMPL [3]. In this thesis, we firstly explain what a structured problem is using concrete real-world problems modelled in SML. Presenting those example models allows us to exhibit PSMG’s modelling syntax and techniques in detail. PSMG provides an easy to use framework for modelling large scale nested structured problems including multi-stage stochastic problems. PSMG can be used for modelling linear programming (LP), quadratic programming (QP), and nonlinear programming (NLP) problems. The second part of this thesis describes considerable thoughts on logical calling sequence and dependencies in parallel operation and algorithms in PSMG. We explain the design concept for PSMG’s solver interface. The interface follows a solver driven work assignment approach that allows the solver to decide how to distribute problem parts to processors in order to obtain better data locality and load balancing for solving problems in parallel. PSMG adopts a delayed constraint expansion design. This allows the memory allocation for computed entities to only happen on a process when it is necessary. The computed entities can be the set expansions of the indexing expressions associated with the variable, parameter and constraint declarations, or temporary values used for set and parameter constructions. We also illustrate algorithms that are important for delivering efficient implementation of PSMG, such as routines for partitioning constraints according to blocks and automatic differentiation algorithms for evaluating Jacobian and Hessian matrices and their corresponding sparsity partterns. Furthermore, PSMG implements a generic solver interface which can be linked with different structure exploiting optimization solvers such as decomposition or interior point based solvers. The work required for linking with PSMG’s solver interface is also discussed. Finally, we evaluate PSMG’s run-time performance and memory usage by generating structured problems with various sizes. The results from both serial and parallel executions are discussed. The benchmark results show that PSMG achieve good parallel efficiency on up to 96 processes. PSMG distributes memory usage among parallel processors which enables the generation of problems that are too large to be processed on a single node due to memory restriction.

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In this thesis, we present a hybrid semantic web service discovery framework that exploits both the signatures and specifications of a web service, whilst adopting logical and non-logical service matching methods. For signature level service matching, we have developed two techniques: (i) logical similarity measures applied to the services’ input/output concepts; and (b) non-logical matching based on a Structure Preserving Semantic Matching algorithm. For specification level service matching, we have applied a unique short sentence matching approach on the textual-description of a web service. We evaluated the performance of our S5 Web Service Matchmaker using the OWLS-TC dataset, and furthermore compared its performance with the OWLS-MX discovery model. Our results indicate that S5 Web Service Matchmaker offers an improved web service matching performance with a significant increase in recall and subtle improvements in precision. / Web services are independent software systems designed to offer machine-to-machine interactions over the WWW to achieve well-described operations. The description of a web service entails (a) a syntactic component detailing the service’s operations and data structures in terms of the Web Services Description Language (WSDL), and (b) a semantic component that offers a semantic description, in terms of an ontology, of the services’ data and operations. Typically, service providers expose their services to the public by providing brief descriptions of the service’s operations; the challenge is to discover the right service based on rather sparse service descriptions in response to a specific service request. In this thesis, we present a hybrid semantic web service discovery framework that offer semantic web service discovery at both the signature and specification levels of a web service, whilst exploiting logical and non-logical service matching methods. For signature level service matching, we have developed two techniques: (i) logical similarity measures applied to the services’ input/output concepts; and (b) non-logical matching based on a Structure Preserving Semantic Matching algorithm. For specification level service matching, we have applied a unique short sentence matching approach on the textual-description of a web service. The cumulative similarly measures determine the overall similarity of a services’ description with the service request. We evaluated the performance of our S5 Web Service Matchmaker using the OWLS-TC dataset, and furthermore compared its performance with the OWLS-MX discovery model. Our results indicate that S5 Web Service Matchmaker offers an improved web service matching performance with a significant increase in recall and subtle improvements in precision.

Computer simulations have emerged as a cost efficient complement to laboratory experiments, as computers have become increasingly powerful. The aim of the present work is to explore the ideas of some state of the art software development practices, and ways in which these can be useful for developing high performance research codes. The introduction of these practices, and the modular designs that they give rise to, raises issues regarding a potential conflict between runtime efficiency on one hand and development efficiency on the other. Flexible software modules, based on mathematical abstractions, will provide support for convenient implementation and modification of numerical operators. Questions still remain about whether such modules will provide the efficiency which is required for high performance applications. To answer these questions, investigations were performed within two different problem domains. The first domain consisted of modular frameworks for the numerical solution of Partial Differential Equations. Such frameworks proved a suitable setting, since several of my research questions revolved around the issue of modularity. The second problem domain was that of symmetry exploiting algorithms. These algorithms are based on group theory, and make ample use of mathematical abstractions from that field. The domain of symmetry exploiting algorithms gave us opportunities to investigate difficulties in combining modularity based on high level abstractions with low level optimizations using data layout and parallelization. In conclusion, my investigation of software development practices for the area of high performance computing has proved very fruitful indeed. I have found that none of the concerns that were raised should lead us to refrain from the use of the practices that I have considered. On the contrary, in the two case studies presented here, these practices lead to designs that perform well in terms of usability as well as runtime efficiency.

Hardware evolves faster than software. While a hardware system might need replacement every one to five years, the average lifespan of a software system is a decade, with some instances living up to several decades. Inevitably, code outlives the platform it was developed for and may become legacy: development of the software stops, but maintenance has to continue to keep up with the evolving ecosystem. No new features are added, but the software is still used to fulfil its original purpose. Even in the cases where it is still functional (which discourages its replacement), legacy code is inefficient, costly to maintain, and a risk to security. This thesis proposes methods to leverage the expertise put in the development of legacy code and to extend its useful lifespan, rather than to throw it away. A novel methodology is proposed, for automatically exploiting platform specific optimisations when retargeting a program to another platform. The key idea is to leverage the optimisation information embedded in vector processing intrinsic functions. The performance of the resulting code is shown to be close to the performance of manually retargeted programs, however with the human labour removed. Building on top of that, the question of discovering optimisation information when there are no hints in the form of intrinsics or annotations is investigated. This thesis postulates that such information can potentially be extracted from profiling the data flow during executions of the program. A context-aware data dependence profiling system is described, detailing previously overlooked aspects in related research. The system is shown to be essential in surpassing the information that can be inferred statically, in particular about loop iterators. Loop iterators are the controlling part of a loop. This thesis describes and evaluates a system for extracting the loop iterators in a program. It is found to significantly outperform previously known techniques and further increases the amount of information about the structure of a program that is available to a compiler. Combining this system with data dependence profiling improves its results even more. Loop iterator recognition enables other code modernising techniques, like source code rejuvenation and commutativity analysis. The former increases the use of idiomatic code and as a result increases the maintainability of the program. The latter can potentially drive parallelisation and thus dramatically improve runtime performance.

This thesis explores the connection between animal rights (abolitionism) and corporate social responsibility (CSR) in an animal-exploiting company. Looking at how companies should treat animals has long been neglected in academic research. For this reason, the thesis investigates how animal rights, in particular, relate to Carroll's pyramid of CSR. The research adopts qualitative research methods with semi-structured interviews. Carroll's pyramid of CSR and its four dimensions are used as the theoretical framework to both direct the data gathering and analyse the information that was acquired. The thesis concludes with several major findings. Firstly, it is found that animal-exploiting businesses do not address animal rights but animal welfare in their CSR strategy. Secondly, the findings identify relations between animal rights and the four levels of Carroll’s CSR framework, namely economic, legal, ethical, and philanthropic levels. Finally, an adjusted version of the framework is developed correlating with abolitionism.