Advanced Programming Language Features for Executable Design Patterns "Better Patterns Through Reflection

The Design Patterns book [GOF95] presents 24 time-tested patterns that consistently appear in well-designed software systems. Each pattern is presented with a description of the design problem the pattern addresses, as well as sample implementation code and design considerations. This paper explores how the patterns from the "Gang of Four'', or "GOF'' book, as it is often called, appear when similar problems are addressed using a dynamic, higher-order, object-oriented programming language. Some of the patterns disappear -- that is, they are supported directly by language features, some patterns are simpler or have a different focus, and some are essentially unchanged.

Robust, High-Speed Network Design for Large-Scale Multiprocessing

As multiprocessor system size scales upward, two important aspects of multiprocessor systems will generally get worse rather than better: (1) interprocessor communication latency will increase and (2) the probability that some component in the system will fail will increase. These problems can prevent us from realizing the potential benefits of large-scale multiprocessing. In this report we consider the problem of designing networks which simultaneously minimize communication latency while maximizing fault tolerance. Using a synergy of techniques including connection topologies, routing protocols, signalling techniques, and packaging technologies we assemble integrated, system-level solutions to this network design problem.

Toward a Theory of Representation Design

This research is concerned with designing representations for analytical reasoning problems (of the sort found on the GRE and LSAT). These problems test the ability to draw logical conclusions. A computer program was developed that takes as input a straightforward predicate calculus translation of a problem, requests additional information if necessary, decides what to represent and how, designs representations capturing the constraints of the problem, and creates and executes a LISP program that uses those representations to produce a solution. Even though these problems are typically difficult for theorem provers to solve, the LISP program that uses the designed representations is very efficient.

Design and Evaluation of the Hamal Parallel Computer

Parallel shared-memory machines with hundreds or thousands of processor-memory nodes have been built; in the future we will see machines with millions or even billions of nodes. Associated with such large systems is a new set of design challenges. Many problems must be addressed by an architecture in order for it to be successful; of these, we focus on three in particular. First, a scalable memory system is required. Second, the network messaging protocol must be fault-tolerant. Third, the overheads of thread creation, thread management and synchronization must be extremely low. This thesis presents the complete system design for Hamal, a shared-memory architecture which addresses these concerns and is directly scalable to one million nodes. Virtual memory and distributed objects are implemented in a manner that requires neither inter-node synchronization nor the storage of globally coherent translations at each node. We develop a lightweight fault-tolerant messaging protocol that guarantees message delivery and idempotence across a discarding network. A number of hardware mechanisms provide efficient support for massive multithreading and fine-grained synchronization. Experiments are conducted in simulation, using a trace-driven network simulator to investigate the messaging protocol and a cycle-accurate simulator to evaluate the Hamal architecture. We determine implementation parameters for the messaging protocol which optimize performance. A discarding network is easier to design and can be clocked at a higher rate, and we find that with this protocol its performance can approach that of a non-discarding network. Our simulations of Hamal demonstrate the effectiveness of its thread management and synchronization primitives. In particular, we find register-based synchronization to be an extremely efficient mechanism which can be used to implement a software barrier with a latency of only 523 cycles on a 512 node machine.

Test Generation Guided Design for Testability

This thesis presents a new approach to building a design for testability (DFT) system. The system takes a digital circuit description, finds out the problems in testing it, and suggests circuit modifications to correct those problems. The key contributions of the thesis research are (1) setting design for testability in the context of test generation (TG), (2) using failures during FG to focus on testability problems, and (3) relating circuit modifications directly to the failures. A natural functionality set is used to represent the maximum functionalities that a component can have. The current implementation has only primitive domain knowledge and needs other work as well. However, armed with the knowledge of TG, it has already demonstrated its ability and produced some interesting results on a simple microprocessor.

Probabilistic Solution of Inverse Problems

In this thesis we study the general problem of reconstructing a function, defined on a finite lattice from a set of incomplete, noisy and/or ambiguous observations. The goal of this work is to demonstrate the generality and practical value of a probabilistic (in particular, Bayesian) approach to this problem, particularly in the context of Computer Vision. In this approach, the prior knowledge about the solution is expressed in the form of a Gibbsian probability distribution on the space of all possible functions, so that the reconstruction task is formulated as an estimation problem. Our main contributions are the following: (1) We introduce the use of specific error criteria for the design of the optimal Bayesian estimators for several classes of problems, and propose a general (Monte Carlo) procedure for approximating them. This new approach leads to a substantial improvement over the existing schemes, both regarding the quality of the results (particularly for low signal to noise ratios) and the computational efficiency. (2) We apply the Bayesian appraoch to the solution of several problems, some of which are formulated and solved in these terms for the first time. Specifically, these applications are: teh reconstruction of piecewise constant surfaces from sparse and noisy observationsl; the reconstruction of depth from stereoscopic pairs of images and the formation of perceptual clusters. (3) For each one of these applications, we develop fast, deterministic algorithms that approximate the optimal estimators, and illustrate their performance on both synthetic and real data. (4) We propose a new method, based on the analysis of the residual process, for estimating the parameters of the probabilistic models directly from the noisy observations. This scheme leads to an algorithm, which has no free parameters, for the restoration of piecewise uniform images. (5) We analyze the implementation of the algorithms that we develop in non-conventional hardware, such as massively parallel digital machines, and analog and hybrid networks.

Application of Inductive Logic Programming to Structure-Based Drug Design

Enot, D. and King, R. D. (2003) Application of Inductive Logic Programming to Structure-Based Drug Design. 7th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD '03). Springer LNAI 2838 p156-167

Identifying Novice Difficulties in Object Orientated Design

Thomasson, B. Ratcliffe, M. Thomas, L. Identifying Novice Difficulties in Object Orientated Design. ACM SIGCSE Bulletin Volume 38 , Issue 3 (September 2006)

Usability-enhanced coordination design of geovisualisations to communicate coastal flood risk information

For at least two millennia and probably much longer, the traditional vehicle for communicating geographical information to end-users has been the map. With the advent of computers, the means of both producing and consuming maps have radically been transformed, while the inherent nature of the information product has also expanded and diversified rapidly. This has given rise in recent years to the new concept of geovisualisation (GVIS), which draws on the skills of the traditional cartographer, but extends them into three spatial dimensions and may also add temporality, photorealistic representations and/or interactivity. Demand for GVIS technologies and their applications has increased significantly in recent years, driven by the need to study complex geographical events and in particular their associated consequences and to communicate the results of these studies to a diversity of audiences and stakeholder groups. GVIS has data integration, multi-dimensional spatial display advanced modelling techniques, dynamic design and development environments and field-specific application needs. To meet with these needs, GVIS tools should be both powerful and inherently usable, in order to facilitate their role in helping interpret and communicate geographic problems. However no framework currently exists for ensuring this usability. The research presented here seeks to fill this gap, by addressing the challenges of incorporating user requirements in GVIS tool design. It starts from the premise that usability in GVIS should be incorporated and implemented throughout the whole design and development process. To facilitate this, Subject Technology Matching (STM) is proposed as a new approach to assessing and interpreting user requirements. Based on STM, a new design framework called Usability Enhanced Coordination Design (UECD) is ten presented with the purpose of leveraging overall usability of the design outputs. UECD places GVIS experts in a new key role in the design process, to form a more coordinated and integrated workflow and a more focused and interactive usability testing. To prove the concept, these theoretical elements of the framework have been implemented in two test projects: one is the creation of a coastal inundation simulation for Whitegate, Cork, Ireland; the other is a flooding mapping tool for Zhushan Town, Jiangsu, China. The two case studies successfully demonstrated the potential merits of the UECD approach when GVIS techniques are applied to geographic problem solving and decision making. The thesis delivers a comprehensive understanding of the development and challenges of GVIS technology, its usability concerns, usability and associated UCD; it explores the possibility of putting UCD framework in GVIS design; it constructs a new theoretical design framework called UECD which aims to make the whole design process usability driven; it develops the key concept of STM into a template set to improve the performance of a GVIS design. These key conceptual and procedural foundations can be built on future research, aimed at further refining and developing UECD as a useful design methodology for GVIS scholars and practitioners.

Design, fabrication and characterisation of components for microfluidic enzymatic biofuel cells

The concept of a biofuel cell takes inspiration from the natural capability of biological systems to catalyse the conversion of organic matter with a subsequent release of electrical energy. Enzymatic biofuel cells are intended to mimic the processes occurring in nature in a more controlled and efficient manner. Traditional fuel cells rely on the use of toxic catalysts and are often not easily miniaturizable making them unsuitable as implantable power sources. Biofuel cells however use highly selective protein catalysts and renewable fuels. As energy consumption becomes a global issue, they emerge as important tools for energy generation. The microfluidic platforms developed are intended to maximize the amount of electrical energy extracted from renewable fuels which are naturally abundant in the environment and in biological fluids. Combining microfabrication processes, chemical modification and biological surface patterning these devices are promising candidates for micro-power sources for future life science and electronic applications. This thesis considered four main aspects of a biofuel cell research. Firstly, concept of a miniature compartmentalized enzymatic biofuel cell utilizing simple fuels and operating in static conditions is verified and proves the feasibility of enzyme catalysis in energy conversion processes. Secondly, electrode and microfluidic channel study was performed through theoretical investigations of the flow and catalytic reactions which also improved understanding of the enzyme kinetics in the cell. Next, microfluidic devices were fabricated from cost-effective and disposable polymer materials, using the state-of-the-art micro-processing technologies. Integration of the individual components is difficult and multiple techniques to overcome these problems have been investigated. Electrochemical characterization of gold electrodes modified with Nanoporous Gold Structures is also performed. Finally, two strategies for enzyme patterning and encapsulation are discussed. Several protein catalysts have been effectively immobilized on the surface of commercial and microfabricated electrodes by electrochemically assisted deposition in sol-gel and poly-(o-phenylenediamine) polymer matrices and characterised with confirmed catalytic activity.

Shipping information pipeline: initial design principles

This paper presents a design science approach to solving persistent problems in the international shipping eco system by creating the missing common information infrastructures. Specifically, this paper reports on an ongoing dialogue between stakeholders in the shipping industry and information systems researchers engaged in the design and development of a prototype for an innovative IT-artifact called Shipping Information Pipeline which is a kind of “an internet” for shipping information. The instrumental aim is to enable information seamlessly to cross the organizational boundaries and national borders within international shipping which is a rather complex domain. The intellectual objective is to generate and evaluate the efficacy and effectiveness of design principles for inter-organizational information infrastructures in the international shipping domain that can have positive impacts on global trade and local economies.

Dealing with emergent design science research projects in IS

Multiple models, methods and frameworks have been proposed to guide Design Science Research (DSR) application to address relevant classes of problems in Information Systems (IS) discipline. While much of the ambiguity around the research paradigm has been removed, only the surface has been scratched on DSR efforts where researcher takes an active role in organizational and industrial engagement to solve a specific problem and generalize the solution to a class of problems. Such DSR projects can have a significant impact on practice, link theories to real contexts and extend the scope of DSR. Considering these multiform settings, the implications to theorizing nor the crucial role of researcher in the interplay of DSR and IS projects have not been properly addressed. The emergent nature of such projects needs to be further investigated to reach such contributions for both theory and practice. This paper raises multiple theoretical, organizational and managerial considerations for a meta-level monitoring model for emergent DSR projects.

Design of Scheduling Algorithms Using Game Theoretic Ideas

Scheduling a set of jobs over a collection of machines to optimize a certain quality-of-service measure is one of the most important research topics in both computer science theory and practice. In this thesis, we design algorithms that optimize {\em flow-time} (or delay) of jobs for scheduling problems that arise in a wide range of applications. We consider the classical model of unrelated machine scheduling and resolve several long standing open problems; we introduce new models that capture the novel algorithmic challenges in scheduling jobs in data centers or large clusters; we study the effect of selfish behavior in distributed and decentralized environments; we design algorithms that strive to balance the energy consumption and performance.

The technically interesting aspect of our work is the surprising connections we establish between approximation and online algorithms, economics, game theory, and queuing theory. It is the interplay of ideas from these different areas that lies at the heart of most of the algorithms presented in this thesis.

The main contributions of the thesis can be placed in one of the following categories.

1. Classical Unrelated Machine Scheduling: We give the first polygorithmic approximation algorithms for minimizing the average flow-time and minimizing the maximum flow-time in the offline setting. In the online and non-clairvoyant setting, we design the first non-clairvoyant algorithm for minimizing the weighted flow-time in the resource augmentation model. Our work introduces iterated rounding technique for the offline flow-time optimization, and gives the first framework to analyze non-clairvoyant algorithms for unrelated machines.

2. Polytope Scheduling Problem: To capture the multidimensional nature of the scheduling problems that arise in practice, we introduce Polytope Scheduling Problem (\psp). The \psp problem generalizes almost all classical scheduling models, and also captures hitherto unstudied scheduling problems such as routing multi-commodity flows, routing multicast (video-on-demand) trees, and multi-dimensional resource allocation. We design several competitive algorithms for the \psp problem and its variants for the objectives of minimizing the flow-time and completion time. Our work establishes many interesting connections between scheduling and market equilibrium concepts, fairness and non-clairvoyant scheduling, and queuing theoretic notion of stability and resource augmentation analysis.

3. Energy Efficient Scheduling: We give the first non-clairvoyant algorithm for minimizing the total flow-time + energy in the online and resource augmentation model for the most general setting of unrelated machines.

4. Selfish Scheduling: We study the effect of selfish behavior in scheduling and routing problems. We define a fairness index for scheduling policies called {\em bounded stretch}, and show that for the objective of minimizing the average (weighted) completion time, policies with small stretch lead to equilibrium outcomes with small price of anarchy. Our work gives the first linear/ convex programming duality based framework to bound the price of anarchy for general equilibrium concepts such as coarse correlated equilibrium.

Using electronic health record data for substance use Screening, Brief Intervention, and Referral to Treatment among adults with type 2 diabetes: Design of a National Drug Abuse Treatment Clinical Trials Network study.

BACKGROUND: The Affordable Care Act encourages healthcare systems to integrate behavioral and medical healthcare, as well as to employ electronic health records (EHRs) for health information exchange and quality improvement. Pragmatic research paradigms that employ EHRs in research are needed to produce clinical evidence in real-world medical settings for informing learning healthcare systems. Adults with comorbid diabetes and substance use disorders (SUDs) tend to use costly inpatient treatments; however, there is a lack of empirical data on implementing behavioral healthcare to reduce health risk in adults with high-risk diabetes. Given the complexity of high-risk patients' medical problems and the cost of conducting randomized trials, a feasibility project is warranted to guide practical study designs. METHODS: We describe the study design, which explores the feasibility of implementing substance use Screening, Brief Intervention, and Referral to Treatment (SBIRT) among adults with high-risk type 2 diabetes mellitus (T2DM) within a home-based primary care setting. Our study includes the development of an integrated EHR datamart to identify eligible patients and collect diabetes healthcare data, and the use of a geographic health information system to understand the social context in patients' communities. Analysis will examine recruitment, proportion of patients receiving brief intervention and/or referrals, substance use, SUD treatment use, diabetes outcomes, and retention. DISCUSSION: By capitalizing on an existing T2DM project that uses home-based primary care, our study results will provide timely clinical information to inform the designs and implementation of future SBIRT studies among adults with multiple medical conditions.

FUELGEN: effective evolutionary design of refuellings for pressurized water reactors

The paper describes the design of an efficient and robust genetic algorithm for the nuclear fuel loading problem (i.e., refuellings: the in-core fuel management problem) - a complex combinatorial, multimodal optimisation., Evolutionary computation as performed by FUELGEN replaces heuristic search of the kind performed by the FUELCON expert system (CAI 12/4), to solve the same problem. In contrast to the traditional genetic algorithm which makes strong requirements on the representation used and its parameter setting in order to be efficient, the results of recent research results on new, robust genetic algorithms show that representations unsuitable for the traditional genetic algorithm can still be used to good effect with little parameter adjustment. The representation presented here is a simple symbolic one with no linkage attributes, making the genetic algorithm particularly easy to apply to fuel loading problems with differing core structures and assembly inventories. A nonlinear fitness function has been constructed to direct the search efficiently in the presence of the many local optima that result from the constraint on solutions.