A Type System For Safe SN Resource Allocation

snBench is a platform on which novice users compose and deploy distributed Sense and Respond programs for simultaneous execution on a shared, distributed infrastructure. It is a natural imperative that we have the ability to (1) verify the safety/correctness of newly submitted tasks and (2) derive the resource requirements for these tasks such that correct allocation may occur. To achieve these goals we have established a multi-dimensional sized type system for our functional-style Domain Specific Language (DSL) called Sensor Task Execution Plan (STEP). In such a type system data types are annotated with a vector of size attributes (e.g., upper and lower size bounds). Tracking multiple size aspects proves essential in a system in which Images are manipulated as a first class data type, as image manipulation functions may have specific minimum and/or maximum resolution restrictions on the input they can correctly process. Through static analysis of STEP instances we not only verify basic type safety and establish upper computational resource bounds (i.e., time and space), but we also derive and solve data and resource sizing constraints (e.g., Image resolution, camera capabilities) from the implicit constraints embedded in program instances. In fact, the static methods presented here have benefit beyond their application to Image data, and may be extended to other data types that require tracking multiple dimensions (e.g., image "quality", video frame-rate or aspect ratio, audio sampling rate). In this paper we present the syntax and semantics of our functional language, our type system that builds costs and resource/data constraints, and (through both formalism and specific details of our implementation) provide concrete examples of how the constraints and sizing information are used in practice.

SOVEREIGN: A Self-Organizing, Vision, Expectation, Recognition, Emotion, Intelligent, Goal-Oriented Navigation System

Both animals and mobile robots, or animats, need adaptive control systems to guide their movements through a novel environment. Such control systems need reactive mechanisms for exploration, and learned plans to efficiently reach goal objects once the environment is familiar. How reactive and planned behaviors interact together in real time, and arc released at the appropriate times, during autonomous navigation remains a major unsolved problern. This work presents an end-to-end model to address this problem, named SOVEREIGN: A Self-Organizing, Vision, Expectation, Recognition, Emotion, Intelligent, Goal-oriented Navigation system. The model comprises several interacting subsystems, governed by systems of nonlinear differential equations. As the animat explores the environment, a vision module processes visual inputs using networks that arc sensitive to visual form and motion. Targets processed within the visual form system arc categorized by real-time incremental learning. Simultaneously, visual target position is computed with respect to the animat's body. Estimates of target position activate a motor system to initiate approach movements toward the target. Motion cues from animat locomotion can elicit orienting head or camera movements to bring a never target into view. Approach and orienting movements arc alternately performed during animat navigation. Cumulative estimates of each movement, based on both visual and proprioceptive cues, arc stored within a motor working memory. Sensory cues are stored in a parallel sensory working memory. These working memories trigger learning of sensory and motor sequence chunks, which together control planned movements. Effective chunk combinations arc selectively enhanced via reinforcement learning when the animat is rewarded. The planning chunks effect a gradual transition from reactive to planned behavior. The model can read-out different motor sequences under different motivational states and learns more efficient paths to rewarded goals as exploration proceeds. Several volitional signals automatically gate the interactions between model subsystems at appropriate times. A 3-D visual simulation environment reproduces the animat's sensory experiences as it moves through a simplified spatial environment. The SOVEREIGN model exhibits robust goal-oriented learning of sequential motor behaviors. Its biomimctic structure explicates a number of brain processes which are involved in spatial navigation.

Energy harvesting embedded wireless sensor system for building environment applications

For many wireless sensor networks applications, indoor light energy is the only ambient energy source commonly available. Many advantages and constraints co-exist in this technology. However, relatively few indoor light powered harvesters have been presented and much research remains to be carried out on a variety of related design considerations and trade-offs. This work presents a solution using the Tyndall mote and an indoor light powered wireless sensor node. It analyses design considerations on several issues such as indoor light characteristics, solar panel component choice, maximum power point tracking, energy storage elements and the trade-offs and choices between them.

Mammalian cell cultures as a model system for the determination of cytotoxicity induced by cholesterol oxidation products

Oxysterols are products of cholesterol oxidation, which may be produced endogenously or may be absorbed from the diet where they are commonly found in foods of animal origin. Oxysterols are known to be cyctotoxic to cells in culture and mode of toxicity has been identified as apoptosis in certain cell lines. The cytotoxicity of the oxysterols 25-hydroxycholesterol (25-OH) and 7β-hydroxycholesterol (7β-OH) was examined in two human cell lines, HepG2, a hepatoma cell line, and U937, a monocytic cell line. Both 25-OH and 7β-OH were cytotoxic to the HepG2 cell line but apoptotic cells were not detected and it was concluded that cells underwent necrosis. 25-OH was not cytotoxic to the U937 cell line but it was found to have a cytostatic effect. 7β-OH was shown to induce apoptosis in the U937 line. The mechanism of oxysterol-induced apoptosis has not yet been fully elucidated, however the generation of an oxidative stress and the depletion of glutathione have been associated with the initial stages of the apoptotic process. The concentration of cellular antioxidant enzyme, superoxide dismutase (SOD) was increased in association with 7β-OH induced apoptosis in the U937 cell line. There was no change in the glutathione concentration or the SOD activity of HepG2 cells, which underwent necrosis in the presence of 7β-OH. Many apoptotic pathways center on the activation of caspase-3, which is the key executioner protease of apoptosis. Caspase-3 activity was also shown to increase in association with 7β-OH-induced apoptosis in U937 cells but there was no significant increase in caspase-3 activity in HepG2 cells. DNA fragmentation is regarded as the biochemical hallmark of apoptosis, therefore the comet assay as a measure of DNA fragmentation was assessed as a measure of apoptosis. The level of DNA fragmentation induced by 7β-OH, as measured using the comet assay, was similar for both cell lines. Therefore, it was concluded that the comet assay could not be used to distinguish between 7β-OH-induced apoptosis in U937 cells and 7β-OH-induced necrosis in HepG2 cells. The cytotoxicity and apoptotic potency of oxysterols 25-OH, 7β-OH, cholesterol- 5a,6a-epoxide (a-epoxide), cholesterol-5β,6β-epoxide (β-epoxide), 19-hydroxy-cholesterol (19-OH), and 7-ketocholesterol (7-keto) was compared in the U937 cell line. 7 β-OH, β-epoxide and 7-keto were found to induce apoptosis in U937 cells. 7β-OH-induced apoptosis was associated with a decrease in the cellular glutathione concentration and an increase in SOD activity, 7-keto and β-epoxide did not affect the glutathione concentration or the SOD activity of the cells.a-Epoxide, 19-OH and 25-OH were not cytotoxic to the U937 cell line.

The development of a computer model to optimize the performance of a 50kWp photovoltaic system

A computer model has been developed to optimize the performance of a 50kWp photovoltaic system which supplies electrical energy to a dairy farm at Fota Island in Cork Harbour. Optimization of the system involves maximising the efficiency and increasing the performance and reliability of each hardware unit. The model accepts horizontal insolation, ambient temperature, wind speed, wind direction and load demand as inputs. An optimization program uses the computer model to simulate the optimum operating conditions. From this analysis, criteria are established which are used to improve the photovoltaic system operation. This thesis describes the model concepts, the model implementation and the model verification procedures used during development. It also describes the techniques which are used during system optimization. The software, which is written in FORTRAN, is structured in modular units to provide logical and efficient programming. These modular units may also be used in the modelling and optimization of other photovoltaic systems.

Grid integration of wave energy & generic modelling of ocean devices for power system studies

The work presented in this thesis covers four major topics of research related to the grid integration of wave energy. More specifically, the grid impact of a wave farm on the power quality of its local network is investigated. Two estimation methods were developed regarding the flicker level Pst generated by a wave farm in relation to its rated power as well as in relation to the impedance angle ψk of the node in the grid to which it is connected. The electrical design of a typical wave farm design is also studied in terms of minimum rating for three types of costly pieces of equipment, namely the VAr compensator, the submarine cables and the overhead line. The power losses dissipated within the farm's electrical network are also evaluated. The feasibility of transforming a test site into a commercial site of greater rated power is investigated from the perspective of power quality and of cables and overhead line thermal loading. Finally, the generic modelling of ocean devices, referring here to both wave and tidal current devices, is investigated.

Explorations in a meaning making system: Kerry as an entrepreneurial platform and the equine sector as a cluster

This Portfolio is about the changes that can be supported and achieved through transformational education that impacts on personal, professional and organisational levels. Having lived through an era of tremendous change over the second half of the twentieth century and into the twenty-first the author has a great drawing board to contemplate in the context of professional career experience as an engineer. The ability to engage in ‘subject-object’ separation is the means by which Kegan (1994, 2009) explains that transformation takes place and the Essays in this Portfolio aim to support and bring about such change. Exploration of aspects of ‘Kerry’ is the material selected to both challenge support change in the way of knowing from being subject to certain information and knowledge that to being able to consider it more objectively. The task of being able to distance judgement about the economy and economic development of Kerry was facilitated by various readings around of a number of key thinkers including Kegan, Drucker, Porter and Penrose. The central themes of Kerry or the potential for economic development are built into each Essay. Essay One focuses on reflections of Kerry life - on Kerry people within and without Kerry - and events as they affected understandings of how people related to and worked with one another. These reflections formed the basis for transformational goals identified which required a shift from an engineering mindset to encompass an economics-based view. In Essay Two knowledge of economic concepts is developed by exploring the writings of Drucker, Penrose, and Porter with pertinence to considering economic development generally, and for Kerry in particular in the form of an ‘entrepreneurial platform’. The concepts and theories were the basis of explorations presented in Essays Three and Four. Essay Three focuses on Kerry’s potential for economic development give its current economic profile and includes results from interviews with selected businesses. Essay Four is an exercise in the application of Porter’s ‘Cluster’ concept to the equine sector.

The Rpf/DSF system and the regulation of virulence in the plant pathogen Xanthomonas campestris

The full virulence of Xanthomonas campestris pv. campestris (Xcc) to plants depends upon cell-to-cell signalling mediated by the signal molecule DSF (for diffusible signal factor), that has been characterised as cis-11-methyl-2-dodecenoic acid. DSF-mediated signalling regulates motility, biofilm dynamics and the synthesis of particular virulence determinants. The synthesis and perception of the DSF signal molecule involves products of the rpf (regulation of pathogenicity factors) gene cluster. DSF synthesis is fully dependent on RpfF, which encodes a putative enoyl-CoA hydratase. A two-component system, comprising the complex sensor histidine kinase RpfC and the HD-GYP domain regulator RpfG, is implicated in DSF perception. The HD-GYP domain of RpfG is a phosphodiesterase working on cyclic di-GMP; DSF perception is thereby linked to the turnover of this intracellular second messenger. The full range of regulatory influences of the Rpf/DSF system and of cyclic di-GMP in Xcc has yet to be established. In order to further characterise the Rpf/DSF regulatory network in Xcc, a proteomic approach was used to compare protein expression in the wildtype and defined rpf mutants. This work shows that the Rpf/DSF system regulates a range of biological functions that are associated with virulence and biofilm formation but also reveals new functions mediated by DSF regulation. These functions include antibiotic resistance, detoxification and stress tolerance. Mutational analysis showed that several of these regulated protein functions contribute to virulence in Chinese radish. Interestingly, it was demonstrated that different patterns of protein expression are associated with mutations of rpfF, rpfC and rpfG. This suggests that RpfG and RpfC have broader roles in regulation other than perception and transduction of DSF. Taken together, this analysis indicates the broad and complex regulatory role of Rpf/DSF system and identifies a number of new functions under Rpf/DSF control, which were shown to play a role in virulence.

Towards a new model of criminal justice system in the era of globalised criminality: the biggest challenges for criminal process legislation

The main objective of this thesis is the critical analysis of the evolution of the criminal justice systems throughout the past decade, with special attention to the fight against transnational terrorism. It is evident – for any observer - that such threats and the associated risk that terrorism entails, has changed significantly throughout the past decade. This perception has generated answers – many times radical ones – by States, as they have committed themselves to warrant the safety of their populations and to ease a growing sentiment of social panic. This thesis seeks to analyse the characteristics of this new threat and the responses that States have developed in the fight against terrorism since 9/11, which have questioned some of the essential principles and values in place in their own legal systems. In such sense, freedom and security are placed into perspective throughout the analysis of the specific antiterrorist legal reforms of five different States: Israel, Portugal, Spain, the United Kingdom and the United States of America. On the other hand, in light of those antiterrorist reforms, it will be questioned if it is possible to speak of the emergence of a new system of criminal justice (and of a process of a convergence between common law and civil law systems), built upon a control and preventive security framework, significantly different from traditional models. Finally, this research project has the fundamental objective to contribute to a better understanding on the economic, social and civilization costs of those legal reforms regarding human rights, the rule of law and democracy in modern States.

Performance metrics of an optical spectral imaging system for intra-operative assessment of breast tumor margins.

As many as 20-70% of patients undergoing breast conserving surgery require repeat surgeries due to a close or positive surgical margin diagnosed post-operatively [1]. Currently there are no widely accepted tools for intra-operative margin assessment which is a significant unmet clinical need. Our group has developed a first-generation optical visible spectral imaging platform to image the molecular composition of breast tumor margins and has tested it clinically in 48 patients in a previously published study [2]. The goal of this paper is to report on the performance metrics of the system and compare it to clinical criteria for intra-operative tumor margin assessment. The system was found to have an average signal to noise ratio (SNR) >100 and <15% error in the extraction of optical properties indicating that there is sufficient SNR to leverage the differences in optical properties between negative and close/positive margins. The probe had a sensing depth of 0.5-2.2 mm over the wavelength range of 450-600 nm which is consistent with the pathologic criterion for clear margins of 0-2 mm. There was <1% cross-talk between adjacent channels of the multi-channel probe which shows that multiple sites can be measured simultaneously with negligible cross-talk between adjacent sites. Lastly, the system and measurement procedure were found to be reproducible when evaluated with repeated measures, with a low coefficient of variation (<0.11). The only aspect of the system not optimized for intra-operative use was the imaging time. The manuscript includes a discussion of how the speed of the system can be improved to work within the time constraints of an intra-operative setting.

A low-cost, portable, and quantitative spectral imaging system for application to biological tissues.

The ability of diffuse reflectance spectroscopy to extract quantitative biological composition of tissues has been used to discern tissue types in both pre-clinical and clinical cancer studies. Typically, diffuse reflectance spectroscopy systems are designed for single-point measurements. Clinically, an imaging system would provide valuable spatial information on tissue composition. While it is feasible to build a multiplexed fiber-optic probe based spectral imaging system, these systems suffer from drawbacks with respect to cost and size. To address these we developed a compact and low cost system using a broadband light source with an 8-slot filter wheel for illumination and silicon photodiodes for detection. The spectral imaging system was tested on a set of tissue mimicking liquid phantoms which yielded an optical property extraction accuracy of 6.40 +/- 7.78% for the absorption coefficient (micro(a)) and 11.37 +/- 19.62% for the wavelength-averaged reduced scattering coefficient (micro(s)').

Information-theoretic analysis of a stimulated-Brillouin-scattering-based slow-light system.

We use an information-theoretic method developed by Neifeld and Lee [J. Opt. Soc. Am. A 25, C31 (2008)] to analyze the performance of a slow-light system. Slow-light is realized in this system via stimulated Brillouin scattering in a 2 km-long, room-temperature, highly nonlinear fiber pumped by a laser whose spectrum is tailored and broadened to 5 GHz. We compute the information throughput (IT), which quantifies the fraction of information transferred from the source to the receiver and the information delay (ID), which quantifies the delay of a data stream at which the information transfer is largest, for a range of experimental parameters. We also measure the eye-opening (EO) and signal-to-noise ratio (SNR) of the transmitted data stream and find that they scale in a similar fashion to the information-theoretic method. Our experimental findings are compared to a model of the slow-light system that accounts for all pertinent noise sources in the system as well as data-pulse distortion due to the filtering effect of the SBS process. The agreement between our observations and the predictions of our model is very good. Furthermore, we compare measurements of the IT for an optimal flattop gain profile and for a Gaussian-shaped gain profile. For a given pump-beam power, we find that the optimal profile gives a 36% larger ID and somewhat higher IT compared to the Gaussian profile. Specifically, the optimal (Gaussian) profile produces a fractional slow-light ID of 0.94 (0.69) and an IT of 0.86 (0.86) at a pump-beam power of 450 mW and a data rate of 2.5 Gbps. Thus, the optimal profile better utilizes the available pump-beam power, which is often a valuable resource in a system design.

An immunoglobulin C kappa-reactive single chain antibody fusion protein induces tolerance through receptor editing in a normal polyclonal immune system.

Understanding immune tolerance mechanisms is a major goal of immunology research, but mechanistic studies have generally required the use of mouse models carrying untargeted or targeted antigen receptor transgenes, which distort lymphocyte development and therefore preclude analysis of a truly normal immune system. Here we demonstrate an advance in in vivo analysis of immune tolerance that overcomes these shortcomings. We show that custom superantigens generated by single chain antibody technology permit the study of tolerance in a normal, polyclonal immune system. In the present study we generated a membrane-tethered anti-Igkappa-reactive single chain antibody chimeric gene and expressed it as a transgene in mice. B cell tolerance was directly characterized in the transgenic mice and in radiation bone marrow chimeras in which ligand-bearing mice served as recipients of nontransgenic cells. We find that the ubiquitously expressed, Igkappa-reactive ligand induces efficient B cell tolerance primarily or exclusively by receptor editing. We also demonstrate the unique advantages of our model in the genetic and cellular analysis of immune tolerance.

Real-Time and Data-Driven Operation Optimization and Knowledge Discovery for an Enterprise Information System

An enterprise information system (EIS) is an integrated data-applications platform characterized by diverse, heterogeneous, and distributed data sources. For many enterprises, a number of business processes still depend heavily on static rule-based methods and extensive human expertise. Enterprises are faced with the need for optimizing operation scheduling, improving resource utilization, discovering useful knowledge, and making data-driven decisions.

This thesis research is focused on real-time optimization and knowledge discovery that addresses workflow optimization, resource allocation, as well as data-driven predictions of process-execution times, order fulfillment, and enterprise service-level performance. In contrast to prior work on data analytics techniques for enterprise performance optimization, the emphasis here is on realizing scalable and real-time enterprise intelligence based on a combination of heterogeneous system simulation, combinatorial optimization, machine-learning algorithms, and statistical methods.

On-demand digital-print service is a representative enterprise requiring a powerful EIS.We use real-life data from Reischling Press, Inc. (RPI), a digit-print-service provider (PSP), to evaluate our optimization algorithms.

In order to handle the increase in volume and diversity of demands, we first present a high-performance, scalable, and real-time production scheduling algorithm for production automation based on an incremental genetic algorithm (IGA). The objective of this algorithm is to optimize the order dispatching sequence and balance resource utilization. Compared to prior work, this solution is scalable for a high volume of orders and it provides fast scheduling solutions for orders that require complex fulfillment procedures. Experimental results highlight its potential benefit in reducing production inefficiencies and enhancing the productivity of an enterprise.

We next discuss analysis and prediction of different attributes involved in hierarchical components of an enterprise. We start from a study of the fundamental processes related to real-time prediction. Our process-execution time and process status prediction models integrate statistical methods with machine-learning algorithms. In addition to improved prediction accuracy compared to stand-alone machine-learning algorithms, it also performs a probabilistic estimation of the predicted status. An order generally consists of multiple series and parallel processes. We next introduce an order-fulfillment prediction model that combines advantages of multiple classification models by incorporating flexible decision-integration mechanisms. Experimental results show that adopting due dates recommended by the model can significantly reduce enterprise late-delivery ratio. Finally, we investigate service-level attributes that reflect the overall performance of an enterprise. We analyze and decompose time-series data into different components according to their hierarchical periodic nature, perform correlation analysis,

and develop univariate prediction models for each component as well as multivariate models for correlated components. Predictions for the original time series are aggregated from the predictions of its components. In addition to a significant increase in mid-term prediction accuracy, this distributed modeling strategy also improves short-term time-series prediction accuracy.

In summary, this thesis research has led to a set of characterization, optimization, and prediction tools for an EIS to derive insightful knowledge from data and use them as guidance for production management. It is expected to provide solutions for enterprises to increase reconfigurability, accomplish more automated procedures, and obtain data-driven recommendations or effective decisions.

Of mice, birds, and men: the mouse ultrasonic song system has some features similar to humans and song-learning birds.

Humans and song-learning birds communicate acoustically using learned vocalizations. The characteristic features of this social communication behavior include vocal control by forebrain motor areas, a direct cortical projection to brainstem vocal motor neurons, and dependence on auditory feedback to develop and maintain learned vocalizations. These features have so far not been found in closely related primate and avian species that do not learn vocalizations. Male mice produce courtship ultrasonic vocalizations with acoustic features similar to songs of song-learning birds. However, it is assumed that mice lack a forebrain system for vocal modification and that their ultrasonic vocalizations are innate. Here we investigated the mouse song system and discovered that it includes a motor cortex region active during singing, that projects directly to brainstem vocal motor neurons and is necessary for keeping song more stereotyped and on pitch. We also discovered that male mice depend on auditory feedback to maintain some ultrasonic song features, and that sub-strains with differences in their songs can match each other's pitch when cross-housed under competitive social conditions. We conclude that male mice have some limited vocal modification abilities with at least some neuroanatomical features thought to be unique to humans and song-learning birds. To explain our findings, we propose a continuum hypothesis of vocal learning.