Performance Comparisons Between Thumb-Based and Finger-Based Input on a Small Touch-Screen Under Realistic Variability

The potential benefits of thumb-based touch interaction have not been fully exploited due to its usability problems and performance deterioration. Despite the well-known problems, mobile phone users often prefer thumb-based input method in their daily context of use. Without understanding input performance under realistic variability, design solutions may not address the problems adequately. This research aims to evaluate performance of one-handed thumb-based input compared to cradled finger-based input for the large number of users and varying task conditions. By investigating performance under a range of user- and task-variability, common patterns can be identified to help infer realistic performance in context of use. For this experiment, 259 participants were recruited balanced on gender and age. They performed user testing of moving an icon on a mobile touch-screen. Overall, the one-handed thumb input showed a 30% reduction in throughput compared to the cradled finger-based input, with significant reduction in speed and accuracy. Reduced throughput is attributed to inaccuracy rather than speed. In addition, the partial effects of touch position, dragging direction, and target size were investigated and quantified. In conclusion, performance could maintain constant throughput only for the finger-based input of limited task conditions, when realistic variability was introduced. Also, high variance of throughput for the thumb-based input led to poor conformity to Fitts’s law. The findings have implications for design of thumb-based touch interface to offset performance reduction and characterizing performance measure for thumb-based input method.     

Measurement feedback control for a class of feedforward nonlinear systems

We propose a measurement feedback controller for a class of feedforward nonlinear systems under sensor noise. The sensor noise has unknown magnitude, frequency, and phase. Our proposed controller is coupled with a low‐pass filter in such a way that the sensor noise is attenuated. We show that the controlled system results in bounded states whose ultimate bounds are inversely proportional to the minimum frequency of the sensor noise. Our result is further generalized to work in a case where the sensor noise is only required to have a Fourier transform with finite energy. Moreover, if the sensor noise enters only at partial states, depending on the location of the sensor noise, the ultimate bounds of the particular states can be made arbitrarily small via the gain factor of the controller. Copyright © 2012 John Wiley & Sons, Ltd.     

An object-based middleware supporting efficient interoperability on a smart home network

This paper proposes a novel object-based home network middleware for supporting the interoperability among home devices and smart grid devices. This middleware provides various types of abstract objects for flexible representation of heterogeneous home devices, which are classified based on their characteristics. It is also flexible enough to allow addition of new protocols and message conversion between different protocols through an abstraction layer, which are not supported by existing home network middlewares so that various protocols can be supported. As a result, it can be utilized to provide the interoperability among a variety of devices from sensors to typical home appliances as well as smart grid devices such as a home electric generator and a battery, which adopt different protocols. In order to demonstrate that home devices and smart grid devices are interoperable through the proposed middleware, we implement applications based on the middleware on a target platform consisting of embedded boards, sensors and laptops for emulation purposes of a home network. According to our emulation, this middleware can provide efficient interoperability among home devices and smart grid devices for future energy efficient home.     

Publishers’ relationships on the web: An examination of how publishers’ websites are causing changes in relations in the book industry

This research, funded by the British National Bibliography Research Fund, examined how publishers’ websites are causing changes in relations in the book industry in order to gain further understanding of the implications of the impact of the Internet on the publishing chain. The paper is set within the context of the development of electronic commerce and how business to consumer commerce is now being overtaken by the activity in business to business trading. Publishers have followed the main business trends in using their websites to develop relationships directly with the consumer, but have been rather slower in developing their business to business activity through the Internet. This study investigated what changes were taking place as a result of current publisher activity on the Web and how these changes were affecting the traditional lines of communication in the book industry. An analysis of a range of consumer publishers’ websites was carried out to see what facilities they were offering both to the general public and to business partners within the industry. Questionnaires and interviews were then conducted to establish how publishers, booksellers and wholesalers were using publishers’ websites and whether these sites were beneficial to the industry as a whole. Facilities found on the websites were examined and analysed in order to determine their usefulness and how they might be developed to aid business to business commerce. Additionally, several issues relating to online sales, changes in sales patterns and changes in working methods were discussed. Although an amount of quantitative data is included in the report, many of the issues raised relied on the perceptions and opinions of practitioners in the book trade.     

Limitations of a Mapping Algorithm with Fragmentation Mimics (MAFM) when modeling statistical data sources based on measured packet network traffic

Knowing the estimation of a statistical process’s parameters for measured network traffic is very important as it can then be further used for the statistical analyses and modeling of network traffic in simulation tools. It is for this reason that different estimation methods are proposed that allow estimations of the statistical processes of network traffic. One of them is our own histograms comparison (EMHC) based method that can be used to estimate statistical data-length process parameters from measured packet traffic. The main part of EMHC method is Mapping Algorithm with Fragmentation Mimics (MAFM).     

Autobiographical Accounts of Students' Experiences Learning Mathematics: A Review

ABSTRACT

In this article, we review published literature that draws on autobiographical accounts of students' experiences learning mathematics. We summarize the main findings of the target literature and present recommendations for further research that will extend this field. Our review indicates that autobiographical and narrative methodological approaches have the potential to occasion important advances in our knowledge of students' experiences learning mathematics. However, relative to accounts of preservice teacher learning, there is a paucity of published research that documents the mathematics learning experiences of kindergarten to Grade 12 students.     

Evaluation of messaging middleware for high-performance cloud computing

Cloud computing is posing several challenges, such as security, fault tolerance, access interface singularity, and network constraints, both in terms of latency and bandwidth. In this scenario, the performance of communications depends both on the network fabric and its efficient support in virtualized environments, which ultimately determines the overall system performance. To solve the current network constraints in cloud services, their providers are deploying high-speed networks, such as 10 Gigabit Ethernet. This paper presents an evaluation of high-performance computing message-passing middleware on a cloud computing infrastructure, Amazon EC2 cluster compute instances, equipped with 10 Gigabit Ethernet. The analysis of the experimental results, confronted with a similar testbed, has shown the significant impact that virtualized environments still have on communication performance, which demands more efficient communication middleware support to get over the current cloud network limitations.     

A review on the combination of binary classifiers in multiclass problems

Several real problems involve the classification of data into categories or classes. Given a data set containing data whose classes are known, Machine Learning algorithms can be employed for the induction of a classifier able to predict the class of new data from the same domain, performing the desired discrimination. Some learning techniques are originally conceived for the solution of problems with only two classes, also named binary classification problems. However, many problems require the discrimination of examples into more than two categories or classes. This paper presents a survey on the main strategies for the generalization of binary classifiers to problems with more than two classes, known as multiclass classification problems. The focus is on strategies that decompose the original multiclass problem into multiple binary subtasks, whose outputs are combined to obtain the final prediction.     

A prototype for cartographic human body analysis

A cartographic-oriented model uses algebraic map operations to perform spatial analysis of medical data relative to the human body. A prototype system uses 3D visualization techniques to deliver analysis results. A prototype implementation suggests the model might provide the basis for a medical application tool that introduces new information insight.