THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

In the real world, a realistic setting for computer vision or multimedia recognition problems is that we have some classes containing lots of training data and many classes contain a small amount of training data. Therefore, how to use frequent classes to help learning rare classes for which it is harder to collect the training data is an open question. Learning with Shared Information is an emerging topic in machine learning, computer vision and multimedia analysis. There are different level of components that can be shared during concept modeling and machine learning stages, such as sharing generic object parts, sharing attributes, sharing transformations, sharing regularization parameters and sharing training examples, etc. Regarding the specific methods, multi-task learning, transfer learning and deep learning can be seen as using different strategies to share information. These learning with shared information methods are very effective in solving real-world large-scale problems. This special issue aims at gathering the recent advances in learning with shared information methods and their applications in computer vision and multimedia analysis. Both state-of-the-art works, as well as literature reviews, are welcome for submission. Papers addressing interesting real-world computer vision and multimedia applications are especially encouraged. Topics of interest include, but are not limited to:  • Multi-task learning or transfer learning for large-scale computer vision and multimedia analysis • Deep learning for large-scale computer vision and multimedia analysis • Multi-modal approach for large-scale computer vision and multimedia analysis • Different sharing strategies, e.g., sharing generic object parts, sharing attributes, sharing transformations, sharing regularization parameters and sharing training examples, • Real-world computer vision and multimedia applications based on learning with shared information, e.g., event detection, object recognition, object detection, action recognition, human head pose estimation, object tracking, location-based services, semantic indexing. • New datasets and metrics to evaluate the benefit of the proposed sharing ability for the specific computer vision or multimedia problem. • Survey papers regarding the topic of learning with shared information.  Authors who are unsure whether their planned submission is in scope may contact the guest editors prior to the submission deadline with an abstract, in order to receive feedback.

IEEE transactions on pattern analysis and machine intelligence

The Silent Language

Visual notations form an integral part of the language of software engineering (SE). Yet historically, SE researchers and notation designers have ignored or undervalued issues of visual representation. In evaluating and comparing notations, details of visual syntax are rarely discussed. In designing notations, the majority of effort is spent on semantics, with graphical conventions largely an afterthought. Typically, no design rationale, scientific or otherwise, is provided for visual representation choices. While SE has developed mature methods for evaluating and designing semantics, it lacks equivalent methods for visual syntax. This paper defines a set of principles for designing cognitively effective visual notations: ones that are optimized for human communication and problem solving. Together these form a design theory, called the Physics of Notations as it focuses on the physical (perceptual) properties of notations rather than their logical (semantic) properties. The principles were synthesized from theory and empirical evidence from a wide range of fields and rest on an explicit theory of how visual notations communicate. They can be used to evaluate, compare, and improve existing visual notations as well as to construct new ones. The paper identifies serious design flaws in some of the leading SE notations, together with practical suggestions for improving them. It also showcases some examples of visual notation design excellence from SE and other fields.

The “Physics” of Notations: Toward a Scientific Basis for Constructing Visual Notations in Software Engineering

The mass customization decade: An updated review of the literature

https://repository.ust.hk/ir/bitstream/1783.1-2663/1/paper_14June2006.pdf

Foot measurements from three-dimensional scans: A comparison and evaluation of different methods

Although the subjective workload assessment technique (SWAT) has been widely used, it has two main problems: it is not very sensitive for low mental workloads and it requires a time-consuming card sorting pretask procedure. In this study are presented five variations of SWAT in an effort to overcome the limitations. Four of the variants used the continuous SWAT subscales while one used the discrete SWAT subscale. Fifteen subjects participated in the experiment. The scales were compared with the original SWAT scale in terms of sensitivity and pretask procedure completion time when performing arithmetic tasks. The results show that all four variants are more sensitive than the conventional SWAT scale and that the pairwise comparison procedure takes significantly less pretask completion time compared with the original SWAT scale. Thus, the conventional pretask procedure can be replaced by a simple unweighted averaging to yield a scale of high sensitivity.

Simplified subjective workload assessment technique.

Very few standards exist for fitting products to people. Footwear is a noteworthy example. This study is an attempt to evaluate the quality of footwear fit using two-dimensional foot outlines. Twenty Hong Kong Chinese students participated in an experiment that involved three pairs of dress shoes and one pair of athletic shoes. The participants’ feet were scanned using a commercial laser scanner, and each participant wore and rated the fit of each region of each shoe. The shoe lasts were also scanned and were used to match the foot scans with the last scans. The ANOVA showed significant (p 5 0.05) differences among the four pairs of shoes for the overall, fore-foot and rear-foot fit ratings. There were no significant differences among shoes for mid-foot fit rating. These perceived differences were further analysed after matching the 2D outlines of both last and feet. The pointwise dimensional difference between foot and shoe outlines were computed and analysed after normalizing with foot perimeter. The dimensional difference (DD) plots along the foot perimeter showed that fore-foot fit was strongly correlated (R 2 4 0.8) with two of the minimums in the DD-plot while mid-foot fit was strongly correlated (R 2 4 0.9) with the dimensional difference around the arch region and a point on the lateral side of the foot. The DD-plots allow the designer to determine the critical locations that may affect footwear fit in addition to quantifying the nature of misfit so that design changes to shape and material may be possible.

Dimensional differences for evaluating the quality of footwear fit

A qualitative study on the comfort and fit of ladies' dress shoes.

Icons are a very important component of graphical user interfaces. However, icon design is still predominantly artistic in nature and as a result icon selection is generally based on usability evaluations after a set of alternative icons are developed. This process tends to be time-consuming and costly. In this research, we address the issues ofwhat should be depicted in an icon, given the function it should represent, and how training affects the performance of novice users when using an iconic interface. A set of 36 concrete icons (12 functions) were selected and tested with a total of 30 participants. The experimental results indicate that complete representations are generally superior for both untrained and trained participants. Results also show that trained participants had shorter response times when compared to untrained participants. Further analysis suggests that ambiguity, uniqueness and dominance are three important aspects to consider when designing and developing icons. Applications of this research include the design of appropriate icons for graphical user interfaces prior to usability testing and the importance of a short training period to illustrate the composition of an icon in an effort to improve the mental model associated with each design.

Ravindra S. Goonetilleke

Papers

Foot measurements from three-dimensional scans: A comparison and evaluation of different methods

Simplified subjective workload assessment technique.

Dimensional differences for evaluating the quality of footwear fit

A qualitative study on the comfort and fit of ladies' dress shoes.

Effects of training and representational characteristics in icon design