Hefestos: an intelligent system applied to ubiquitous accessibility

This article proposes Hefestos, an intelligent system applied to ubiquitous accessibility. This model uses ubiquitous computing concepts to manage accessibility resources for people with disabilities. Among the concepts employed, context awareness, user profiles and trails management can be highlighted. The paper proposes an ontology for accessibility and delineates scenarios of its application in everyday life of people with disabilities. Moreover, the implementation of a smart wheelchair prototype and its application in a practical experiment is described. Ten users with a range of disability degrees tried the system and filled out a survey based on the technology acceptance model. This experiment demonstrated the main functionalities and the acceptance of the system. The results showed 96 % of acceptance regarding perceived easy of use and 98 % in perceived usefulness. These results were encouraging and show the potential for implementing Hefestos in real life situations.     

A study on effects of security risks on acceptance of enterprise cloud service: moderating of employment and non-employment using PLS multiple group analysis

This paper analyzed the effects of security risk factors fit for cloud computing paradigm on the acceptance of enterprise cloud service with intent to illuminate the factors for vitalizing the adoption of corporate cloud services in the future. The acceptance intention was set as a dependent variable. Independent variables were set in reference to the technology acceptance theory. Security risks were categorized into compliance risk, information leakage risk, troubleshooting risk and service discontinuation risk to design a model for analysis.     

Analytic center cutting plane method for multiple kernel learning

Multiple Kernel Learning (MKL) is a popular generalization of kernel methods which allows the practitioner to optimize over convex combinations of kernels. We observe that many recent MKL solutions can be cast in the framework of oracle based optimization, and show that they vary in terms of query point generation. The popularity of such methods is because the oracle can fortuitously be implemented as a support vector machine. Motivated by the success of centering approaches in interior point methods, we propose a new approach to optimize the MKL objective based on the analytic center cutting plane method (accpm). Our experimental results show that accpm outperforms state of the art in terms of rate of convergence and robustness. Further analysis sheds some light as to why MKL may not always improve classification accuracy over naive solutions.     

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.     

Extraction of enhanced evoked potentials using wavelet filtering

In order to remove physiological artefacts and gain the improved evoked potentials, we propose a filtering method using the multi-resolution wavelet transform. The wavelet transform is repeatedly performed until all resolution levels are obtained. It decomposes the measured evoked potentials into scale coefficients corresponding to low frequency components and wavelet coefficients corresponding to high frequency components. In the wavelet domain, artefacts are dispersed mainly at the wavelet coefficients rather than the scaling coefficients. Thus, when the inverse wavelet transform is performed, this method shrinks the wavelet coefficients to reduce artefacts with shrinkage functions. By repeatedly performing the inverse wavelet transform, an evoked potential having the reduced artefacts and background noise is obtained. In this study, quantitative evaluation with simulation data and actual clinical data were conducted. As a result, characteristic peaks of evoked potential could be gained removing background EEG and artefacts using suggested shrinkage function. It was improved more than 0.2–1.6Db compared to the conventional averaging method. Also, the system for measuring and analyzing evoked potentials using DSP is implemented.     

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).