Abstract. Empirical evaluations are needed to determine which users are helped or hindered by user-adapted interaction in user modeling systems. A review of past UMUAI articles reveals insuf¢cient empirical evaluations, but an encouraging upward trend. Rules of thumb for experimental design, useful tests for covariates, and common threats to experimental validity are presented. Reporting standards including effect size and power are proposed. Key words: empirical evaluation, experimental design, covariant variables, e¡ect size, treatment magnitude, power, sensitivity. 1. What Is Empirical Evaluation? Empirical evaluation refers to the appraisal of a theory by observation in experiments. The key to good empirical evaluation is the proper design and execution of the experiments so that the particular factors to be tested can be easily separated from other confounding factors. For example, one may want to test whether a software system with a user model works better than the same system without a user model, test the effect of different levels of user modeling or different user model parameter settings, or test different user interfaces. These factors, which

In view of the difficulties in evaluating computer pointing devices across different tasks within dynamic and complex systems, new performance measures are needed. This paper proposes seven new accuracy measures to elicit (sometimes subtle) differences among devices in precision pointing tasks. The measures are target re-entry, task axis crossing, movement direction change, orthogonal direction change, movement variability, movement error, and movement offset. Unlike movement time, error rate, and throughput, which are based on a single measurement per trial, the new measures capture aspects of movement behaviour during a trial. The theoretical basis and computational techniques for the measures are described, with examples given. An evaluation with four pointing devices was conducted to validate the measures. A causal relationship to pointing device efficiency (viz. throughput) was found, as was an ability to discriminate among devices in situations where differences did not otherwise appear. Implications for pointing device research are discussed.

analysis technique that has found applications in various areas. In this paper, we study some multivariate statistical analysis methods in Secure 2-party Computation (S2C) framework illustrated by the following scenario: two parties, each having a secret data set, want to conduct the statistical analysis on their joint data, but neither party is willing to disclose its private data to the other party or any third party. The current statistical analysis techniques cannot be used directly to support this kind of computation because they require all parties to send the necessary data to a central place. In this paper, We define two Secure 2-party multivariate statistical analysis problems: Secure 2-party Multivariate Linear Regression problem and Secure 2-party Multivariate Classification problem. We have developed a practical security model, based on which we have developed a number of building blocks for solving these two problems.

The field of view (FOV) in most head-mounted displays (HMDs) is no more than 60 degrees wide -- far narrower than our normal FOV of about 200 wide. This mismatch arises mostly from the difficulty and expense of building wide-FOV HMDs. Restricting a person's FOV, however, has been shown in real environments to affect people's behavior and degrade task performance. Previous work in virtual reality too has shown that restricting FOV to 50 or less in an HMD can degrade performance. I conducted experiments with a custom, wide-FOV HMD and found that performance is degraded even at the relatively high FOV of 112, and further at 48. The experiments used a prototype tiled wide-FOV HMD to measure performance in VR at up to 176 total horizontal FOV, and a custom large-area tracking system to establish new findings on performance while walking about a large virtua...

Brain metabolic mapping techniques, such as positron emis-sion tomography (PET), can provide information about the functional interactions within entire neural systems. With the large quantity of data that can accumulate from a mapping study, a network analysis, which makes sense of the com-plex interactions among neural elements, is necessary. A network analysis was performed on data obtained from a PET study that examined both the changes in regional ce-rebral blood flow (rCBF) and interregional correlations among human cortical areas during performance of an object vision (face matching) and spatial vision (dot-location matching) task. Brain areas for the network were selected based on regions showing significant rCBF or interregional correla-tions between tasks. Anterior temporal and frontal lobe regions were added to the network using a principal com-

Abstract. Understanding how to implement SPI successfully is arguably the most challenging issue facing the SPI field today. The SPI literature contains many case studies of successful companies and descriptions of their SPI programs. However, there has been no systematic attempt to synthesize and organize the prescriptions offered. The research efforts to date are limited and inconclusive and without adequate theoretical and psychometric justification. This paper provides a synthesis of prescriptions for successful quality management and process improvement found from an extensive review of the quality management, organizational learning, and software process improvement literature. The literature review was confirmed by empirical studies among both researchers and practitioners. The main result is an instrument for measuring the key factors of success in SPI based on data collected from 120 software organizations. The measures were found to have satisfactory psychometric properties. Hence, managers can use the instrument to guide SPI activities in their respective organizations and researchers can use it to build models to relate the facilitating factors to both learning processes and SPI outcomes.

In this study, we examined empirical results on the h index and its most important variants in order to determine whether the variants developed are associated with an incremental contribution for evaluation purposes. The results of a factor analysis using bibliographic data on postdoctoral researchers in biomedicine indicate that regarding the h index and its variants, we are dealing with two types of indices that load on one factor each. One type describes the most productive core of a scientist’s output and gives the number of papers in that core. The other type of indices describes the impact of the papers in the core. Because an index for evaluative purposes is a useful yardstick for comparison among scientists if the index corresponds strongly with peer assessments, we calculated a logistic regression analysis with the two factors resulting from the factor analysis as independent variables and peer assessment of the postdoctoral researchers as the dependent variable. The results of the regression analysis show that peer assessments can be predicted better using the factor ‘impact of the productive core ’ than using the factor ‘quantity of the productive core.’

ACKNOWLEDGEMENTS: We thank the senior editor on the manuscript, V. Sambamurthy, and the anonymous associate editor and reviewers for their many insightful suggestions on earlier

This paper examines the ability of the risk-shifting hypothesis and the backdoor equity hypothesis to explain firms ’ decisions to issue convertible debt. Using a security choice model that incorporates pre-offer issue, issuer, and macroeconomic information, we document significant variation in the market reaction to new convertible debt issues depending on whether investors expect the motivation for issuance to be asset substitution or asymmetric information. Our results suggest that both motives explain the use and design of convertible debt. Some firms issue convertible debt instead of straight debt to mitigate the costs of bondholder/stockholder agency conflicts. Other issuers use convertible debt instead of common equity to reduce the costs of adverse selection. Thus, in contrast to standard securities like straight debt or common equity, which solve some financing problems but exacerbate others, hybrid securities such as convertible debt are seen as providing a more flexible funding choice that can solve conflicting financing problems. Financial economists study the security issue decision to understand more fully why firms choose to issue a particular security and how investors in financial markets react to that choice. The research documents several results about investor reaction to the announcement of

Abstract—Understanding how to implement software process improvement (SPI) successfully is arguably the most challenging issue facing the SPI field today. The SPI literature contains many case studies of successful companies and descriptions of their SPI programs. However, the research efforts to date are limited and inconclusive and without adequate theoretical and psychometric justification. This paper extends and integrates models from prior research by performing an empirical investigation of the key factors for success in SPI. A quantitative survey of 120 software organizations was designed to test the conceptual model and hypotheses of the study. The results indicate that success depends critically on six organizational factors, which explained more than 50 percent of the variance in the outcome variable. The main contribution of the paper is to increase the understanding of the influence of organizational issues by empirically showing that they are at least as important as technology for succeeding with SPI and, thus, to provide researchers and practitioners with important new insights regarding the critical factors of success in SPI.