Usability Principles for Augmented Reality Applications in a Smartphone Environment

Through the rapid spread of smartphones, users have access to many types of applications similar to those on desktop computer systems. Smartphone applications using augmented reality (AR) technology make use of users' location information. As AR applications will require new evaluation methods, improved usability and user convenience should be developed. The purpose of the current study is to develop usability principles for the development and evaluation of smartphone applications using AR technology. We develop usability principles for smartphone AR applications by analyzing existing research about heuristic evaluation methods, design principles for AR systems, guidelines for handheld mobile device interfaces, and usability principles for the tangible user interface. We conducted a heuristic evaluation for three popularly used smartphone AR applications to identify usability problems. We suggested new design guidelines to solve the identified problems. Then, we developed an improved AR application prototype of an Android-based smartphone, which later was conducted a usability testing to validate the effects of usability principles.     

The impact of watching television on evening melatonin levels

Self‐luminous electronic devices emit optical radiation at short wavelengths, close to the peak sensitivity of melatonin suppression. The present paper investigated if light from a 178‐cm (70 in.) television suppressed melatonin. Results showed that light from televisions does not impact melatonin levels in the evening.     

Studies on a New Concept of 3D Data Integration about Reaches and Forces of a Disabled Person on a Wheelchair (CAD Methods in Car and Market Ergonomics)

The article presents a new concept of combining the three dimensions (3D) of a person's manipulation space. The data concern information about the reach of the arms and biomechanical data about limiting the load of a disabled person sitting in a wheelchair. Measurement data were acquired empirically, on original measuring station. The data included, respectively, arms' reach (static and dynamic) or, alternatively, measurements of limiting forces. The obtained data were processed into virtual 3D surfaces of arms' reach and forces. These surfaces provide the required graphic model of anthropotechnical and biomechanical data. Developed model was utilized to perform a virtual analysis of the accessibility of a disabled person to technical means: in a market sale space and in the ergonomic analysis into the space of a personal car. The presented method of 3D graphic modeling of anthropometrical and biomechanical data can be universally applied in ergonomic designing of work stations not only for disabled persons. © 2011 Wiley Periodicals, Inc.     

The Research Experience for Education Graduate Students: A Phenomenographic Study

This article presents the findings of an exploratory study of education graduate students’ information-seeking behavior and attitudes. Qualitative data included interviews with education students, focusing on their research habits, and analyzed from phenomenographic approach that focused on variations in individuals’ experiences. The quantitative analysis stemmed from participants’ responses to the survey of their information-seeking behavior. A comparison of interview participants and survey respondents’ search skills, research strategies, and attitudes toward previous library instruction illustrate the wide variation in students’ abilities and experiences between the groups. This suggests the need for further analysis of these students’ information seeking behaviors.     

Code reordering using local random extraction and insertion (LREI) operator for GPGPU-based track-before-detect systems

Track-before-detect (TBD) algorithms are used for tracking systems, where the object’s signal is below the noise floor (low-SNR objects). A lot of computations and memory transfers for real-time signal processing are necessary. GPGPU in parallel processing devices for TBD algorithms is well suited. Finding optimal or suboptimal code, due to lack of documentation for low-level programming of GPGPUs is not possible. High-level code optimization is necessary and the evolutionary approach, based on the single parent and single child is considered, that is local search approach. Brute force search technique is not feasible, because there are N! code variants, where N is the number of motion vectors components. The proposed evolutionary operator—LREI (local random extraction and insertion) allows source code reordering for the reduction of computation time due to better organization of memory transfer and the texture cache content. The starting point, based on the sorting and the minimal execution time metric is proposed. The unbiased random and biased sorting techniques are compared using experimental approach. Tests shows significant improvements of the computation speed, about 8 % over the conventional code for CUDA code. The time period of optimization for the sample code is about 1 h (1,000 iterations) for the considered recursive spatio-temporal TBD algorithm.     

Calculus Students' Use and Interpretation of Variables: Algebraic vs. Arithmetic Thinking

Abstract

The ability to use and interpret algebraic variables as generalized numbers and changing quantities is fundamental to the learning of calculus. This study considers the use of variables in these advanced ways as a component of algebraic thinking. College introductory calculus students' (n = 174) written responses to algebra problems requiring the use and interpretation of variables as changing quantities were examined for evidence of algebraic and arithmetic thinking. A framework was developed to describe and categorize examples of algebraic, transitional, and arithmetic thinking reflected in these students' uses of variables. The extent to which students' responses showed evidence of algebraic or arithmetic thinking was quantified and related to their course grades. Only one third of the responses of these entering calculus students were identified as representative of algebraic thinking. This study extends previous research by showing that evidence of algebraic thinking in students' work was positively related to successful performance in calculus.     

The determinants of continuous use of social networking sites: An empirical study on Taiwanese journal-type bloggers’ continuous self-disclosure behavior

The popularity and growth of social networking sites (SNSs) have resulted in fierce competition among SNS providers. A critical concern of SNSs is to identify how to have users continuously use a specific SNS. This study examines the determinants of journal-type bloggers’ continuous self-disclosure. An analysis of 283 samples with continuous self-disclosure experiences in journal-type blogs shows that personal factors, specifically the habit of self-disclosure, are the major factors affecting bloggers’ continuous self-disclosure, followed by self-benefits. In contrast, social factors, such as positive audience feedback and social benefits, are not related to continuous self-disclosure. These results suggest that SNS providers must encourage users to develop the habit of using their web sites regularly. By providing differential benefits to users, SNS providers may attract users to continuously use their services.     

Harmony search-based hidden Markov model optimization for online classification of single trial eegs during motor imagery tasks

This paper presents an improved method based on single trial EEG data for the online classification of motor imagery tasks for brain-computer interface (BCI) applications. The ultimate goal of this research is the development of a novel classification method that can be used to control an interactive robot agent platform via a BCI system. The proposed classification process is an adaptive learning method based on an optimization process of the hidden Markov model (HMM), which is, in turn, based on meta-heuristic algorithms. We utilize an optimized strategy for the HMM in the training phase of time-series EEG data during motor imagery-related mental tasks. However, this process raises important issues of model interpretation and complexity control. With these issues in mind, we explore the possibility of using a harmony search algorithm that is flexible and thus allows the elimination of tedious parameter assignment efforts to optimize the HMM parameter configuration. In this paper, we illustrate a sequential data analysis simulation, and we evaluate the optimized HMM. The performance results of the proposed BCI experiment show that the optimized HMM classifier is more capable of classifying EEG datasets than ordinary HMM during motor imagery tasks.     

Hydrophilic polycarbonate chips for generation of oil-in-water (O/W) and water-in-oil-in-water (W/O/W) emulsions

Modification of the surfaces of polycarbonate (PC) with the use of a solution of tin (II) chloride renders them hydrophilic. The surface draping is stable against exposure to water and to alcohols. Exposure to alkanes reduces but does not diminish the effect. The method is compatible—in using the same solvent and temperature—with the hydrophobic modification of PC Jankowski et al. ( Lab Chip 11:748–752, 2011). The combination of these methods makes it possible to generate single and multiple monodisperse emulsions with the use of flow-focusing junctions in systems made in PC—material that is suitable for fabrication of multilayer, high throughput microfluidic devices.