Continuous Tradeoff Research Articles

Between market forces and knowledge based motives: the governance of defence innovation in the UK

The purpose of this contribution is to examine the evolutionary transformations that have characterised the UK defence innovation system since the mid 1980s. It focuses on the central and challenging issue faced by the Ministry of Defence (MoD) in implementing effective governance mechanisms emerging from the continuous trade-off between short-term market driven measures motivated by efficiency arguments, and more long term and relational considerations in terms of knowledge economics. Furthermore, in terms of technology transfer, this evolution has been accompanied by a gradual shift from an initial logic of spin-off to society expected from government driven military projects, to a logic of spin-in where the main concern of the military sector is to broaden its industrial and R&D base.

Pseudorandomness and Average-Case Complexity Via Uniform Reductions

Impagliazzo and Wigderson (1998) gave the first construction of pseudorandom generators from a uniform complexity assumption on EXP (namely EXP ≠ BPP). Unlike results in the nonuniform setting, their result does not provide a continuous trade-off between worst-case hardness and pseudorandomness, nor does it explicitly establish an average-case hardness result. In this paper:

Motion Artifacts of Extended High Frame Rate Imaging

Based on the high frame rate (HFR) imaging method developed in our lab, an extended high frame rate imaging method with various transmission schemes was developed recently. In this method, multiple, limited-diffraction array beams or steered plane wave transmissions are used to increase image resolution and field of view as well as to reduce sidelobes. Furthermore, the multiple, limited-diffraction array beam transmissions can be approximated with square-wave aperture weightings, allowing one or two transmitters to be used with a multielement array transducer to simplify imaging systems. By varying the number of transmissions, the extended HFR imaging method allows a continuous trade-off between image quality and frame rate. Because multiple transmissions are needed to obtain one frame of image for the method, motion could cause phase misalignment and thus produce artifacts, reducing image contrast and resolution and leading to an inaccurate clinical interpretation of images. Therefore, it is important to study how motion affects the method and provide a useful guidance of using the method properly in various applications. In this paper, computer simulations, in vitro and in vivo experiments were performed to study the effects of motion on the method in different conditions. Results show that a number of factors may affect the motion effects. However, it was found that the extended HFR imaging method is not sensitive to the motions commonly encountered in the clinical applications, as is demonstrated by an in vivo heart experiment, unless the number of transmissions is large and objects are moving at a high velocity near the surface of a transducer.

Effects of Phase Aberration and Noise on Extended High Frame Rate Imaging

Based on the high frame rate (HFR) imaging theories, an extended HFR imaging method has been developed recently in our lab where multiple limited-diffraction array beams or steered plane waves are used in transmissions to reconstruct a high quality image of an equivalent dynamic focusing in both transmissions and receptions. The method has the potential to simplify imaging systems because the fast Fourier transform and square-wave aperture weightings can be used. The method is also flexible in using different numbers of transmissions for a continuous trade-off between image quality and frame rate. In this paper, we study the effects of phase aberration and noise on the extended HFR imaging method with in vitro experiments and compare the results with those obtained with a conventional delay-and-sum (D&S) method of a fixed-transmission focus and a dynamically-focused reception. In the experiments, an ATS539 tissue-mimicking phantom and an Acuson V2 phase array transducer (128 elements, 2.5 MHz, and 0.15-mm pitch) were used. The transducer was driven by a homemade general-purpose HFR imaging system that was capable of producing both the limited-diffraction array beams and steeredplane waves and echo data were acquired with the same system and then transferred to a personal computer via a universal serial bus (USB) 2.0 link for image reconstructions. The phase aberration was introduced by adding random phase shifts to both transmission and reception beams. The random noise was added to the received radiofrequency echo data. Results show that the phase aberration and noise degrade both the extended HFR and the conventional delay-and-sum (D&S) imaging method. However, images reconstructed with the extended HFR imaging method have an overall higher quality than those with the D&S method given the phase aberration and noise models studied.

EVALUATION OF TERM UTILITY FUNCTIONS FOR VERY SHORT MULTIDOCUMENT SUMMARIES

We describe results from an application for relevance assessment in a setting related to multidocument summarization. For the task of characterizing given document collections by a short list of relevant terms, we have proposed the term utility function PxR. The measure is competitive to a variety of utility functions commonly used in text mining. Our function incorporates a user-definable parameter that allows for explicit, continuous trade-off between precision and recall, which was preferred by our users over the more opaque term utility functions from text mining. The F β measure is similar but not identical to our measure and will also be discussed. Despite our users' preference for a user-definable parameter, the improvement by setting different user-defined parameter values for each document collection are limited, and a static value for the parameter works almost as well. This seems to be true for the F β measure as well. A simple measure, SR, also performs competitively. In light of this evidence, a user-definable parameter seems to be unnecessary to achieve competitive performance.

Real-time range acquisition by adaptive structured light

The goal of this paper is to provide a "self-adaptive" system for real-time range acquisition. Reconstructions are based on a single frame structured light illumination. Instead of using generic, static coding that is supposed to work under all circumstances, system adaptation is proposed. This occurs on-the-fly and renders the system more robust against instant scene variability and creates suitable patterns at startup. A continuous trade-off between speed and quality is made. A weighted combination of different coding cues--based upon pattern color, geometry, and tracking--yields a robust way to solve the correspondence problem. The individual coding cues are automatically adapted within a considered family of patterns. The weights to combine them are based on the average consistency with the result within a small time-window. The integration itself is done by reformulating the problem as a graph cut. Also, the camera-projector configuration is taken into account for generating the projection patterns. The correctness of the range maps is not guaranteed, but an estimation of the uncertainty is provided for each part of the reconstruction. Our prototype is implemented using unmodified consumer hardware only and, therefore, is cheap. Frame rates vary between 10 and 25 fps, dependent on scene complexity.

The political economy of urban transport-system choice

This paper analyzes the political economy of transport-system choice, with the goal of gaining an understanding of the forces involved in this important urban public policy decision. Transport systems pose a continuous trade-off between time and money cost, so that a city can choose a fast system with a high money cost per mile or a slower, cheaper system. The paper compares the socially optimal transport system to the one chosen under the voting process, focusing on both homogeneous and heterogeneous cities, while considering different landownership arrangements. The analysis identifies a bias toward underinvestment in transport quality in heterogeneous cities.

Receiver Operating Characteristic Analysis: A Primer 1

This issue of Academic Radiology is the second of two issues honoring the memory of Dr. Charles E.Metz, who pioneered the application of receiver operating characteristic (ROC) analysis for evaluating the diagnostic performance of radiology exams (1). Along with 10 articles that appeared in the December 2012 issue of Academic Radiology (2–11), the 15 articles featured in this issue represent some of the latest research in ROC analysis. Together, the 25 articles are a fitting tribute to the groundwork laid by Dr. Metz. If you examine the references cited in these articles, you will discover that a number of Dr. Metz’s seminal articles in ROC analysis have appeared in the pages ofAcademic Radiology. ROC analysis can be complex, and it is filled with methodological nuances. To aid the reader, I have been asked by the Editor to place each of the articles in a context that is accessible to the practicing academic radiologist, as I did for the first Metz memorial issue (12). The classic ROC curve represents an intrinsic property of a diagnostic test and plots the continuous tradeoff between sensitivity and specificity of the test. In practice, a radiologist chooses, consciously or subconsciously, one sensitivity/specificity point on the ROC curve at which to operate. But which operating point is optimum? The ROC curve by itself cannot answer this question. Defining the optimum operating point requires additional information, mainly the prevalence of the disease being diagnosed and the relative clinical value of the possible test outcomes (true positive, false positive, true negative, and false negative). This additional information also defines the overall clinical value of the diagnostic test when the optimum operating point on the ROC curve is used. Clinically speaking, the ROC curve by itself says little about the value of the diagnostic test. Determining the relative clinical value of the possible diagnostic test outcomes involves utility theory (13,14) and is beyond the scope of this editorial. Such work can be

New lower bounds for statistical query learning

We prove two lower bounds in the statistical query (SQ) learning model. The first lower bound is on weak-learning. We prove that for a concept class of SQ-dimension d, a running time of Ω ( d / log d ) is needed. The SQ-dimension of a concept class is defined to be the maximum number of concepts that are “uniformly correlated”, in that each of their pair has nearly the same correlation. This lower bound matches the upper bound in Blum et al. (Weakly Learning DNF and Characterizing Statistical Query Learning using Fourier Analysis, STOC 1994, pp. 253–262), up to a logarithmic factor. We prove this lower bound against an “honest SQ-oracle”, which gives a stronger result than the ones against the more frequently used “adversarial SQ-oracles”. The second lower bound is more general. It gives a continuous trade-off between the “advantage” of an algorithm in learning the target function and the number of queries it needs to make, where the advantage of an algorithm is the probability it succeeds in predicting a label minus the probability it does not. Both lower bounds extend and/or strengthen previous results, and solve an open problem left in previous papers. An earlier version of this paper [K. Yang, New lower bounds for statistical query learning, in: The Proceedings of the 15th Annual Conference on Computational Learning Theory, COLT 2002, Sydney, Australia, July 8–10, Lecture Notes in Computer Science, vol. 2375, 2002, pp. 229–243.] appeared in the proceedings of the 15th Annual Conference on Computational Learning Theory (COLT 2002).

Communication lower bounds for distributed-memory matrix multiplication

We present lower bounds on the amount of communication that matrix multiplication algorithms must perform on a distributed-memory parallel computer. We denote the number of processors by P and the dimension of square matrices by n. We show that the most widely used class of algorithms, the so-called two-dimensional (2D) algorithms, are optimal, in the sense that in any algorithm that only uses O(n2/P) words of memory per processor, at least one processor must send or receive Ω(n2/P1/2) words. We also show that algorithms from another class, the so-called three-dimensional (3D) algorithms, are also optimal. These algorithms use replication to reduce communication. We show that in any algorithm that uses O(n2/P2/3) words of memory per processor, at least one processor must send or receive Ω(n2/P2/3) words. Furthermore, we show a continuous tradeoff between the size of local memories and the amount of communication that must be performed. The 2D and 3D bounds are essentially instantiations of this tradeoff. We also show that if the input is distributed across the local memories of multiple nodes without replication, then Ω(n2) words must cross any bisection cut of the machine. All our bounds apply only to conventional Θ(n3) algorithms. They do not apply to Strassen's algorithm or other o(n3) algorithms.

Generalized Alamouti Codes for Trading Quality of Service against Data Rate in MIMO UMTS

New space-time block coding schemes for multiple transmit and receive antennas are proposed. First, the well-known Alamouti scheme is extended to transmit antennas achieving high transmit diversity. Many receiver details are worked out for four and eight transmit antennas. Further, solutions for arbitrary, even numbers of transmit antennas are presented achieving decoding advantages due to orthogonalization properties while preserving high diversity. In a final step, such extended Alamouti and BLAST schemes are combined, offering a continuous trade-off between quality of service (QoS) and data rate. Due to the simplicity of the coding schemes, they are very well suited to operate under UMTS with only very moderate modifications in the existing standard. The number of supported antennas at transmitter alone is a sufficient knowledge to select the most appropriate scheme. While the proposed schemes are motivated by utilization in UMTS, they are not restricted to this standard.

Benchmarking combined biological phosphorus and nitrogen removal wastewater treatment processes

This paper describes the implementation of a simulation benchmark for studying the influence of control strategy implementations on combined nitrogen and phosphorus removal processes in a biological wastewater treatment plant. The presented simulation benchmark plant and its performance criteria are to a large extent based on the already existing nitrogen removal simulation benchmark. The paper illustrates and motivates the selection of the treatment plant lay-out, the selection of the biological process model, the development of realistic influent disturbance scenarios for dry, rain and storm weather conditions respectively, the definition of performance indexes that include the phosphorus removal processes, and the selection of a suitable operating point for the plant. Two control loops were implemented: one for dissolved oxygen control using the oxygen transfer coefficient K La as manipulated variable, the second one for nitrate control in the anoxic zone using the internal recirculation flow rate as manipulated variable. Dynamic simulations for different dissolved oxygen set points illustrate the complex interactions in this plant, and the necessity for a continuous trade off between supplying sufficient oxygen to promote nitrification on the one hand, and the need for low dissolved oxygen concentrations on the other hand to allow sufficient development of phosphorus accumulating organisms. The potential for aeration energy savings in the plant is highlighted based on the dissolved oxygen profiles resulting from open loop simulations with a dynamic dry weather influent scenario. The influence of the dissolved oxygen set point selection on the nitrate control loop performance observed in the simulations further illustrates the need for a plant-wide optimization approach to reach optimal plant performance.

Streaming BDD manipulation

Binary decision diagrams (BDDs) are commonly used for handling Boolean functions because of their excellent efficiency in terms of time and space. However, the conventional BDD manipulation algorithm is strongly based on the hash table technique, so it always encounters the memory overflow problem when handling large-scale BDD data. This paper proposes a new streaming BDD manipulation method that never causes memory overflow or swap out. This method allows us to handle very large-scale BDD stream data beyond the memory limitation. Our method can be characterized as follows: (1) it gives a continuous tradeoff curve between memory usage and stream data length, (2) valid solutions for a partial Boolean space can be obtained if we break the process before finishing, and (3) easily accelerated by pipelined multiprocessing. An experimental result demonstrates that we can succeed in finding a number of solutions to a SAT problem using a commodity PC with a 64 MB memory, where as the conventional BDD manipulator would have required a 100 GB memory. BDD manipulation has been considered as an intensively memory-consuming procedure, but now we can also utilize the hard disk and network resources as well. The method leads to a new approach to BDD manipulation.

Space-Time Tradeoffs for Emptiness Queries

We develop the first nontrivial lower bounds on the complexity of online hyperplane and halfspace emptiness queries. Our lower bounds apply to a general class of geometric range query data structures called partition graphs. Informally, a partition graph is a directed acyclic graph that describes a recursive decomposition of space. We show that any partition graph that supports hyperplane emptiness queries implicitly defines a halfspace range query data structure in the Fredman/Yao semigroup arithmetic model, with the same asymptotic space and time bounds. Thus, results of Brönnimann, Chazelle, and Pach imply that any partition graph of size s that supports hyperplane emptiness queries in time t satisfies the inequality $st^d = \Omega((n/\log n)^{d - (d-1)/(d+1)})$. Using different techniques, we improve previous lower bounds for Hopcroft's problem---Given a set of points and hyperplanes, does any hyperplane contain a point?---in dimensions four and higher. Using this offline result, we show that for online hyperplane emptiness queries, $\Omega(n^d/{\mbox{ polylog }} n)$ space is required to achieve polylogarithmic query time, and $\Omega(n^{(d-1)/d}/{\mbox{ polylog }} n)$ query time is required if only O(n polylog n) space is available. These two lower bounds are optimal up to polylogarithmic factors. For two-dimensional queries, we obtain an optimal continuous tradeoff $st^2=\Omega(n^2)$ between these two extremes. Finally, using a lifting argument, we show that the same lower bounds hold for both offline and online halfspace emptiness queries in ${\mathbb{R}}^{d(d+3)/2}$.

Memory-Efficient Matrix Multiplication in the BSP Model

The model of bulk-synchronous parallel (BSP) computation is an emerging paradigm of general-purpose parallel computing. Its modification, the BSPRAM model, allows one to combine the advantages of distributed and shared-memory style programming. In this paper we study the BSP memory complexity of matrix multiplication. We propose new memory-efficient BSP algorithms both for standard and for fast matrix multiplication. The BSPRAM model is used to simplify the description of the algorithms. The communication and synchronization complexity of our algorithms is slightly higher than that of known time-efficient BSP algorithms. The current time-efficient and new memory-efficient algorithms are connected by a continuous tradeoff.

Balancing minimum spanning trees and shortest-path trees

This paper give a simple linear-time algorithm that, given a weighted digraph, finds a spanning tree that simultaneously approximates a shortest-path tree and a minimum spanning tree. The algorithm provides a continuous trade-off: given the two trees and epsilon > 0, the algorithm returns a spanning tree in which the distance between any vertex and the root of the shortest-path tree is at most 1+epsilon times the shortest-path distance, and yet the total weight of the tree is at most 1+2/epsilon times the weight of a minimum spanning tree. This is the best tradeoff possible. The paper also describes a fast parallel implementation.

Bounded knapsack sharing

A bounded knapsack sharing problem is a maximin or minimax mathematical programming problem with one or more linear inequality constraints, an objective function composed of single variable continuous functions called tradeoff functions, and lower and upper bounds on the variables. A single constraint problem which can have negative or positive constraint coefficients and any type of continuous tradeoff functions (including multi-modal, multiple-valued and staircase functions) is considered first. Limiting conditions where the optimal value of a variable may be plus or minus infinity are explicitly considered. A preprocessor procedure to transform any single constraint problem to a finite form problem (an optimal feasible solution exists with finite variable values) is developed. Optimality conditions and three algorithms are then developed for the finite form problem. For piecewise linear tradeoff functions, the preprocessor and algorithms are polynomially bounded. The preprocessor is then modified to handle bounded knapsack sharing problems with multiple constraints. An optimality condition and algorithm is developed for the multiple constraint finite form problem. For multiple constraints, the time needed for the multiple constraint finite form algorithm is the time needed to solve a single constraint finite form problem multiplied by the number of constraints. Some multiple constraint problems cannot be transformed to multiple constraint finite form problems.

A space-efficient short-finding algorithm [VLSI layouts

A common method of locating electrical shorts in VLSI layouts is to build a connectivity graph of the shorted net and then find the shortest path between the two offending signals. The memory requirement of this method is proportional to the size of the net, which can be quite large. This paper presents a dynamic graph construction algorithm that significantly reduces the peak memory requirement. The algorithmic framework allows continuous trade-offs between run times and memory requirements. >

Solving knapsack sharing problems with general tradeoff functions

A knapsack sharing problem is a maximin or minimax mathematical programming problem with one or more "knapsack" constraints (an inequality constraint with all non-negative coefficients). All knapsack sharing algorithms to date have assumed that the objective function is composed of single variable functions called tradeoff functions which are strictly increasing continuous functions. This paper develops optimality conditions and algorithms for knapsack sharing problems with any type of continuous tradeoff function including multiple-valued and staircase functions which can be increasing, decreasing, unimodal, bimodal, or even multi-modal. To do this, optimality conditions are developed for a special type of multiple-valued, nondecreasing tradeoff function called an ascending function. The optimal solution to any knapsack sharing problem can then be found by solving an equivalent problem where all the tradeoff functions have been transformed to ascending functions. Polynomial algorithms are developed for piecewise linear tradeoff functions with a fixed number of breakpoints. The techniques needed to construct efficient algorithms for any type of tradeoff function are discussed.

An alternative approach to reduced-complexity CPM-receivers

By separating the two complexity problems connected with optimum coherent CPM (continuous phase modulation) receivers, namely, the number of linear filters and the number of memory states required, a straightforward procedure for reducing the complexity is proposed and its usefulness is evaluated. A concise analysis of the inherent trellis encoder associated with CPM is given. It is then demonstrated that for almost all schemes of interest in practice, it is quite sufficient for the receiver to implement only four or six linear filters which represent proper reference signals. For a reduction in the number of memory states, decision-feedback sequence estimation together with minimization of the unprocessed intersymbol interference is proposed. Modifications of this procedure allow a state reduction without losses or with only negligible losses because only error events with large distances are affected. Combinations of these methods make possible an almost continuous tradeoff between receiver complexity and SNR (signal/noise ratio) losses. Several examples are considered for which evaluations of minimum Euclidean distances and simulation results are given. >