A NEW OUTCOME MEASURE FOR COST-UTILITY ANALYSES OF SCREENING PROGRAMS

In this paper we provide a new outcome measure for the cost-utility analyses of alternative screening programs of a particular disease. We show that for non-invasive screening programs satisfying plausible assumptions, QALYs can be replaced by a simpler outcome: the sensitivity of the program. In other words, the cost-utility analysis can be made without computing the utility each program offers. Consequently, results would be immune to two of the most controversial issues in the cost-utility analysis approach: the elicitation method to obtain quality weights of health profiles, and the discount rate for future health benefits. The assumptions are particularly suitable in the case of selecting between the universal and the selective implementation of a non-invasive screening program. Therefore, we apply our result to provide an additional viewpoint in the current debate about the implementation of a universal or selective newborn screening program to detect congenital hearing impairment.Cost-utility analysis, cost-sensitivity ratios, screening programs,

Fast Deterministic Consensus in a Noisy Environment

It is well known that the consensus problem cannot be solved deterministically in an asynchronous environment, but that randomized solutions are possible. We propose a new model, called noisy scheduling, in which an adversarial schedule is perturbed randomly, and show that in this model randomness in the environment can substitute for randomness in the algorithm. In particular, we show that a simplified, deterministic version of Chandra's wait-free shared-memory consensus algorithm (PODC, 1996, pp. 166-175) solves consensus in time at most logarithmic in the number of active processes. The proof of termination is based on showing that a race between independent delayed renewal processes produces a winner quickly. In addition, we show that the protocol finishes in constant time using quantum and priority-based scheduling on a uniprocessor, suggesting that it is robust against the choice of model over a wide range.Comment: Typographical errors fixe

Creating a Religious Properties Database for the City of New Bedford: an Analysis of Best Practices and Available Systems

This policy analysis was written to provide the city of New Bedford, the Waterfront Historic Area League, Inter-church Council of Greater New Bedford, and the congregations with possible database systems to consider in creating their historic religious properties database. It also provides the best methodology to use when choosing a database. Deciding on who will be involved in the choosing process, determining a budget, and listing the mandatory requirements the database should provide are all important to consider in the decision making process

Randomized protocols for asynchronous consensus

The famous Fischer, Lynch, and Paterson impossibility proof shows that it is impossible to solve the consensus problem in a natural model of an asynchronous distributed system if even a single process can fail. Since its publication, two decades of work on fault-tolerant asynchronous consensus algorithms have evaded this impossibility result by using extended models that provide (a) randomization, (b) additional timing assumptions, (c) failure detectors, or (d) stronger synchronization mechanisms than are available in the basic model. Concentrating on the first of these approaches, we illustrate the history and structure of randomized asynchronous consensus protocols by giving detailed descriptions of several such protocols.Comment: 29 pages; survey paper written for PODC 20th anniversary issue of Distributed Computin

Optimizing for confidence - Costs and opportunities at the frontier between abstraction and reality

Is there a relationship between computing costs and the confidence people place in the behavior of computing systems? What are the tuning knobs one can use to optimize systems for human confidence instead of correctness in purely abstract models? This report explores these questions by reviewing the mechanisms by which people build confidence in the match between the physical world behavior of machines and their abstract intuition of this behavior according to models or programming language semantics. We highlight in particular that a bottom-up approach relies on arbitrary trust in the accuracy of I/O devices, and that there exists clear cost trade-offs in the use of I/O devices in computing systems. We also show various methods which alleviate the need to trust I/O devices arbitrarily and instead build confidence incrementally "from the outside" by considering systems as black box entities. We highlight cases where these approaches can reach a given confidence level at a lower cost than bottom-up approaches.Comment: 11 pages, 1 figur

Nanopore Sequencing Technology and Tools for Genome Assembly: Computational Analysis of the Current State, Bottlenecks and Future Directions

Nanopore sequencing technology has the potential to render other sequencing technologies obsolete with its ability to generate long reads and provide portability. However, high error rates of the technology pose a challenge while generating accurate genome assemblies. The tools used for nanopore sequence analysis are of critical importance as they should overcome the high error rates of the technology. Our goal in this work is to comprehensively analyze current publicly available tools for nanopore sequence analysis to understand their advantages, disadvantages, and performance bottlenecks. It is important to understand where the current tools do not perform well to develop better tools. To this end, we 1) analyze the multiple steps and the associated tools in the genome assembly pipeline using nanopore sequence data, and 2) provide guidelines for determining the appropriate tools for each step. We analyze various combinations of different tools and expose the tradeoffs between accuracy, performance, memory usage and scalability. We conclude that our observations can guide researchers and practitioners in making conscious and effective choices for each step of the genome assembly pipeline using nanopore sequence data. Also, with the help of bottlenecks we have found, developers can improve the current tools or build new ones that are both accurate and fast, in order to overcome the high error rates of the nanopore sequencing technology.Comment: To appear in Briefings in Bioinformatics (BIB), 201

Strategies in Underwriting the Costs of Catastrophic Disease

In this thesis we address the problem of integrated software pipelining for clustered VLIW architectures. The phases that are integrated and solved as one combined problem are: cluster assignment, instruction selection, scheduling, register allocation and spilling. As a first step we describe two methods for integrated code generation of basic blocks. The first method is optimal and based on integer linear programming. The second method is a heuristic based on genetic algorithms. We then extend the integer linear programming model to modulo scheduling. To the best of our knowledge this is the first time anybody has optimally solved the modulo scheduling problem for clustered architectures with instruction selection and cluster assignment integrated. We also show that optimal spilling is closely related to optimal register allocation when the register files are clustered. In fact, optimal spilling is as simple as adding an additional virtual register file representing the memory and have transfer instructions to and from this register file corresponding to stores and loads. Our algorithm for modulo scheduling iteratively considers schedules with increasing number of schedule slots. A problem with such an iterative method is that if the initiation interval is not equal to the lower bound there is no way to determine whether the found solution is optimal or not. We have proven that for a class of architectures that we call transfer free, we can set an upper bound on the schedule length. I.e., we can prove when a found modulo schedule with initiation interval larger than the lower bound is optimal. Experiments have been conducted to show the usefulness and limitations of our optimal methods. For the basic block case we compare the optimal method to the heuristic based on genetic algorithms. This work has been supported by The Swedish national graduate school in computer science (CUGS) and Vetenskapsrådet (VR)

A Moment in Human Development: Legal Protection, Ethical Standards and Social Policy on the Selective Non-Treatment of Handicapped Neonates

Selective non-treatment decisions involving severely handicapped neonates have recently come under renewed judicial and legislative scrutiny. In this article, the author examines the legal, ethical and social considerations attendant to the non-treatment decision. In Part II he discusses the predominant ethical viewpoints relating to this issue and proposes a new moral standard based on personal interests. Part III presents a survey of the jurisprudence relating to selective non-treatment decisions. Parts IV and V of this article provide a critical examination of the recently enacted Child Abuse Amendments of 1984, a federal legislative initiative designed to regulate treatment decisions relating to handicapped infants. The author suggests that the ethical standards and treatment criteria proposed in this article may prove useful to courts seeking to balance the handicapped neonate\u27s constitutional right to privacy with the requirements of the new federal law

Process-oriented Iterative Multiple Alignment for Medical Process Mining

Adapted from biological sequence alignment, trace alignment is a process mining technique used to visualize and analyze workflow data. Any analysis done with this method, however, is affected by the alignment quality. The best existing trace alignment techniques use progressive guide-trees to heuristically approximate the optimal alignment in O(N2L2) time. These algorithms are heavily dependent on the selected guide-tree metric, often return sum-of-pairs-score-reducing errors that interfere with interpretation, and are computationally intensive for large datasets. To alleviate these issues, we propose process-oriented iterative multiple alignment (PIMA), which contains specialized optimizations to better handle workflow data. We demonstrate that PIMA is a flexible framework capable of achieving better sum-of-pairs score than existing trace alignment algorithms in only O(NL2) time. We applied PIMA to analyzing medical workflow data, showing how iterative alignment can better represent the data and facilitate the extraction of insights from data visualization.Comment: accepted at ICDMW 201