Lester Hill Revisited

Abstract

Lester Sanders Hill (1890–1961) is best known for the Hill cipher which he published in 1929. However, there seem to be four periods of Hill's career. First, in 1926 and 1927, Hill published a series of papers on mathematical error-detection. Hill's ideas for error-detection are similar to the ideas he used in his cipher. Next, in 1929 and 1931, Hill published two papers that describe the Hill cipher. The third period of Hill's career, from 1927 until 1960, was the time he served on the mathematics faculty of Hunter College. During his time at Hunter College, Hill seems to have had a relationship with the Navy in which he served during World War I. Finally, while teaching at Hunter College, in the 1950s, Hill wrote his “later papers” on cryptography, which were not published but were sent to Naval Communications.     

Review of Alan Turing: His Work and Impact Edited by S. Barry Cooper and Jan van Leeuwen

In this paper, a password authentication scheme based on a unit circle encoding is proposed. In our scheme, a one-way function and a cryptographic operation such as DES (data encryption standard) are adopted. Besides, in our scheme, the system only need to store a master secret key, and each user can select his own password freely. Instead of storing a password verification table inside the computer system, our method only has to store a corresponding table of identities, which is used by the computer system for validating the submitted passwords. Owing to this scheme the system can quickly and efficiently respond to any log-in attempt, and is suitable for real-time applications. Furthermore, in our scheme, the system does not need to reconstruct any term of the existing key table, when a new user is inserted into the system. Thus, our scheme is suitable for practical implementation.     

Joint High-Resolution Fundamental Frequency and Order Estimation

In this paper, we present a novel method for joint estimation of the fundamental frequency and order of a set of harmonically related sinusoids based on the multiple signal classification (MUSIC) estimation criterion. The presented method, termed HMUSIC, is shown to have an efficient implementation using fast Fourier transforms (FFTs). Furthermore, refined estimates can be obtained using a gradient-based method. Illustrative examples of the application of the algorithm to real-life speech and audio signals are given, and the statistical performance of the estimator is evaluated using synthetic signals, demonstrating its good statistical properties.     

Poisson regression models outperform the geometrical model in estimating the peak-to-trough ratio of seasonal variation: a simulation study

IntroductionSeveral statistical methods of assessing seasonal variation are available. Brookhart and Rothman [3] proposed a second-order moment-based estimator based on the geometrical model derived by Edwards [1], and reported that this estimator is superior in estimating the peak-to-trough ratio of seasonal variation compared with Edwards’ estimator with respect to bias and mean squared error. Alternatively, seasonal variation may be modelled using a Poisson regression model, which provides flexibility in modelling the pattern of seasonal variation and adjustments for covariates.MethodBased on a Monte Carlo simulation study three estimators, one based on the geometrical model, and two based on log-linear Poisson regression models, were evaluated in regards to bias and standard deviation (SD). We evaluated the estimators on data simulated according to schemes varying in seasonal variation and presence of a secular trend. All methods and analyses in this paper are available in the R package Peak2Trough [13].ResultsApplying a Poisson regression model resulted in lower absolute bias and SD for data simulated according to the corresponding model assumptions. Poisson regression models had lower bias and SD for data simulated to deviate from the corresponding model assumptions than the geometrical model.ConclusionThis simulation study encourages the use of Poisson regression models in estimating the peak-to-trough ratio of seasonal variation as opposed to the geometrical model.     

‘Salesman? Hell no!’ Identity struggles of nascent design entrepreneurs

The present study offers new input to the discussion of how entrepreneurship education and training programmes can be tailored to suit design professionals. To a large extent, existing entrepreneurship teaching for creative people is based on a traditional administrative management logic that often results in a clash between entrepreneurial demands and creative identities. The paper is based on the following rationale: the better we understand designers' reasoning and their struggles concerning becoming entrepreneurs, the better we are able to design entrepreneurship learning experiences that meet their needs. Since designers' career‐making tends to be highly driven by their strong sense of identity, the paper takes an identity perspective. The empirical foundation of the research is based on observation studies and phenomenological interviews conducted during an eight‐week entrepreneurship training program. Twenty‐five nascent design entrepreneurs with a professional background as designers participated in the voluntary programme. The paper offers novel and critical insights into designers' experiences of the entrepreneurial identity and reasoning as they participate in entrepreneurship training.     

Humidity sensitivity of optical structures prepared by r.f.-biased r.f. sputtering

In an attempt to produce optical structures with a lower humidity sensitivity than that of structures deposited by conventional evaporation, we used r.f.-biased r.f. sputtering for the preparation of coatings. The sensitivity was effectively reduced owing to the high density of bias-sputtered films which are subjected to controlled ion bombardment during their growth. Our experiments suggest that neither rate monitoring nor optical monitoring is necessary, at least not in the preparation of simple structures with few layers, if glow discharge sputtering processes comprising r.f. substrate biasing in diode, triode or magnetron set-ups are used to deposit the coatings.     

A new analysis of the false positive rate of a Bloom filter

A Bloom filter is a space-efficient data structure used for probabilistic set membership testing. When testing an object for set membership, a Bloom filter may give a false positive. The analysis of the false positive rate is a key to understanding the Bloom filter and applications that use it. We show experimentally that the classic analysis for false positive rate is wrong. We formally derive a correct formula using a balls-and-bins model and show how to numerically compute the new, correct formula in a stable manner. We also prove that the new formula always results in a predicted greater false positive rate than the classic formula. This correct formula is numerically compared to the classic formula for relative error - for a small Bloom filter the prediction of false positive rate will be in error when the classic formula is used.     

An empirical investigation of architectural prototyping

Architectural prototyping is the process of using executable code to investigate stakeholders’ software architecture concerns with respect to a system under development. Previous work has established this as a useful and cost-effective way of exploration and learning of the design space of a system and in addressing issues regarding quality attributes, architectural risks, and the problem of knowledge transfer and conformance. However, the actual industrial use of architectural prototyping has not been thoroughly researched so far. In this article, we report from three studies of architectural prototyping in practice. First, we report findings from an ethnographic study of practicing software architects. Secondly, we report from a focus group on architectural prototyping involving architects from four companies. And, thirdly, we report from a survey study of 20 practicing software architects and software developers. Our findings indicate that architectural prototyping plays an important and frequent role in resolving problems experimentally, but less so in exploring alternative solutions. Furthermore, architectural prototypes include end-user or business related functionality rather than purely architectural functionality. Based on these observations we provide recommendations for effective industrial architectural prototyping.     

Selecting informative data for developing peptide-MHC binding predictors using a query by committee approach

Strategies for selecting informative data points for training prediction algorithms are important, particularly when data points are difficult and costly to obtain. A Query by Committee (QBC) training strategy for selecting new data points uses the disagreement between a committee of different algorithms to suggest new data points, which most rationally complement existing data, that is, they are the most informative data points. In order to evaluate this QBC approach on a real-world problem, we compared strategies for selecting new data points. We trained neural network algorithms to obtain methods to predict the binding affinity of peptides binding to the MHC class I molecule, HLA-A2. We show that the QBC strategy leads to a higher performance than a baseline strategy where new data points are selected at random from a pool of available data. Most peptides bind HLA-A2 with a low affinity, and as expected using a strategy of selecting peptides that are predicted to have high binding affinities also lead to more accurate predictors than the base line strategy. The QBC value is shown to correlate with the measured binding affinity. This demonstrates that the different predictors can easily learn if a peptide will fail to bind, but often conflict in predicting if a peptide binds. Using a carefully constructed computational setup, we demonstrate that selecting peptides with a high QBC performs better than low QBC peptides independently from binding affinity. When predictors are trained on a very limited set of data they cannot be expected to disagree in a meaningful way and we find a data limit below which the QBC strategy fails. Finally, it should be noted that data selection strategies similar to those used here might be of use in other settings in which generation of more data is a costly process.