Dynamic behaviour of a magnetically actuated floating liquid marble

This paper reports the dynamic behaviour of a magnetically actuated floating liquid marble by analysing the oscillation of the marble. A liquid marble is a liquid droplet coated with hydrophobic powder. Magnetite particles inside the marble make it magnetic. The marble floats on a carrier liquid that contains aqueous glycerol of various concentrations. A permanent magnet located under the carrier liquid drives the floating marble with the initial velocity. Stopping the magnet abruptly causes the marble to oscillate around its final position for a few seconds. The oscillation was recorded and analysed using customised image processing and evaluation software. The damped harmonic motion model was then applied to the data and tested. Subsequently, critical parameters of the system such as the initial displacement, friction correction factor, the apparent frequency and the spring constant were determined and discussed. The simple experimental set-up and convenient theoretical approach allow us to characterise the marble motion under the influence of a magnet with good accuracy.     

Development of a web-based insulin decision aid for the elderly: usability barriers and guidelines

Universal Access in the Information Society - In recent years, researchers have attempted to shift patient decision aids (PDAs) from paper-based to web-based to increase its accessibility. Insulin...     

Articulating collaboration in a learning community

A common computer-based collaborative learning approach is to simply introduce contemporary computermediated communication technology into the classroom to support prescribed learning activities. This approach assumes that all students collaborate in similar ways and that presentday technology is sufficient to accommodate all collaboration forms. This view is superficial and limiting. Students collaborate in different ways at different levels on different learning activities. A more detailed articulation of collaboration in learning is crucial to understanding and extending the pedagogical capabilities and usefulness of collaborative technologies. A model is presented for a more finely articulated form of analysis that enumerates types of collaborative learning activities and evaluates how these activities may be supported through different design options. The analysis is based on actual classroom scenarios and the collaboration requirements that emerge from them. The authors have successfully applied this analysis model in the design of a computer-based collaborative learning environment for science education.     

Strategies for Expressing Concise, Helpful Answers

An intelligent help system needs to take into account the user's knowledgewhen formulating answers. This allows the system to provide more conciseanswers, because it can avoid telling users things that they already know.Since these concise answers concentrate exclusively on pertinent newinformation, they are also easier to understand. Information about theuser's knowledge also allows the system to take advantage of the user'sprior knowledge in formulating explanations. The system can provide betteranswers by referring to the user's prior knowledge in the explanation(e.g., through use of similes). This process of refining answers is calledanswer expression.The process of answer expression has been implemented in the UCExpresscomponent of UC (UNIX Consultant), a natural language system that helps theuser solve problems in using the UNIX operating system. UCExpress separatesanswer expression into two phases: pruning and formatting.In the pruning phase, subconcepts of the answer are pruned by being markedas already known by the user (and hence do not need to be generated), ormarked as candidates for generating anaphora or ellipsis (since they arepart of the conversational context). In the formatting phase, UCExpressuses information about the user's prior domain knowledge to select amongspecialized expository formats,such as similes and examples, for expressing information to the user. Theseformats allow UCExpress to present different types of information to theuser in a clear, concise manner. The result of UCExpress' answer expressionprocess is an internal form that a tactical level generator can easily useto produce good English.     

Empirical Evaluation of User Models and User-Adapted Systems

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 insufficient 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.     

Analysis of factors contributing to success in a program of micromanipulation-assisted fertilization

OBJECTIVE: To determine factors important to clinical success in micromanipulation-assisted in vitro fertilization (IVF). DESIGN: Procedures invoked in two separate series of micromanipulation-assisted IVF cycles, one unsuccessful (series I) and the other successful (series II), were compared in an effort to identify changes that led to clinical success. SETTING: University-based IVF clinic. PATIENTS: In both IVF series involving micromanipulation, patients consisted of infertile couples who fit any of five categories of male-factor related infertility. The female patients underwent controlled hyperstimulation for oocyte retrieval and the oocytes were inseminated normally or were subjected either to partial zona dissection or subzonal sperm insertion to assist fertilization. Results in all groups were compared between the two patient series. RESULTS: In the successful series II, a noticeable improvement in fertilization rate and embryo quality was observed compared with series I. A significant increase in the percentage of patients reaching embryo transfer, the pregnancy rate per transfer, and the pregnancy rate per retrieval were noted in series II; a 25% ongoing pregnancy rate per retrieval was observed overall in this successful group, with "ongoing" defined as manifestation of at least a fetal sac on ultrasound with no detectable problems. Patients with a mixed transfer of embryos derived from manipulated and normally inseminated oocytes had a 75% rate of pregnancy per transfer in series II. Differences between the two series could not be attributed to patient selection or biases in selection of oocytes relegated to micromanipulation. However, oocyte handling, micromanipulation, and culture protocols differed significantly between the two series in that temperature and pH of oocytes was better controlled, and micromanipulation time was minimized in series II. CONCLUSION: Success in micromanipulation depends on maintenance of the oocyte in a stable and supportive environment throughout the micromanipulation procedure. It is also important to minimize trauma to the eggs by performing micromanipulation rapidly and with minimal distortion of the egg. Patients with a poor fertilization rate in standard IVF may experience a substantial increase in the likelihood of pregnancy when micromanipulation-assisted fertilization is performed on some eggs.     

Simultaneous nonlinear absorption and index effects in the propagation of intense TEA CO2 laser pulses through CDF3

Changes in the beam profile of the CO2 laser 10R(26) line, caused by transmission through, and absorption by, CDF3 were studied using an array of pyroelectric detectors. During the propagation of the laser beam through CDF3, nonlinear absorption and self-defocusing of the beam have both been determined from measurements of the effect on the exit beam of fluence, radiant energy, CDF3 pressure, transmission cell length, and distance from the exit of the cell to the detector array.     

Effects of the heterogeneity of game complexity and user population in learning performance of business simulation games

Previous studies on business simulation games (BSGs) have concluded that improved performance may not be the primary benefit of using BSGs, due to mixed results between student performance and perceptions. Two relevant and insightful issues attract our attention, namely, the impacts of the heterogeneous student population and the different complexity levels of BSG software. To address these issues, the present study aims to understand the relationship between student profile/characteristics and performance in the classroom with BSG-facilitated learning. An in-depth case study is conducted on a general college course designed to teach three different complexities of BSGs to students enrolled in different majors. Four student profile factors are individually tested for differences in performance scores as evaluated by the teacher. Additionally, the influences of 11 student characteristics are assessed with regard their self-reported perceived learning performances. Regression analysis and ANOVA are used to investigate the impacts of heterogeneous users and game complexity on student performance. Based on the regression analyses of the data collected from 43 respondents who participated in the general course, the study concludes that knowledge and skill may influence the heterogeneous student population; moreover, student participation and tacit learning preference improve performance, and students with an auditory learning preference or high learning motivation may not perform well in classroom BSG learning. However, the low value of adjusted R square implies that more dimensions or variables are needed to increase the explaining power of the performance scores in the regression analyses. In contrast, heterogeneous BSG software with different complexity levels present different results. The current research contributes practical and incremental knowledge on the complexity of heterogeneous BSG software on performance scores and the perceived learning performance of heterogeneous student populations. With the research limitations acknowledged, a series of suggestions for teachers pertaining to appropriate applications of BSGs in classes is offered as well as recommendations to BSG providers. Nevertheless, in-depth analyses are required, preferably with larger student population samples, to further explore the insignificant relationship between student perceptions and attitude under nonlinear extended complexity.     

An enhanced Support Vector Machine classification framework by using Euclidean distance function for text document categorization

This paper presents the implementation of a new text document classification framework that uses the Support Vector Machine (SVM) approach in the training phase and the Euclidean distance function in the classification phase, coined as Euclidean-SVM. The SVM constructs a classifier by generating a decision surface, namely the optimal separating hyper-plane, to partition different categories of data points in the vector space. The concept of the optimal separating hyper-plane can be generalized for the non-linearly separable cases by introducing kernel functions to map the data points from the input space into a high dimensional feature space so that they could be separated by a linear hyper-plane. This characteristic causes the implementation of different kernel functions to have a high impact on the classification accuracy of the SVM. Other than the kernel functions, the value of soft margin parameter, C is another critical component in determining the performance of the SVM classifier. Hence, one of the critical problems of the conventional SVM classification framework is the necessity of determining the appropriate kernel function and the appropriate value of parameter C for different datasets of varying characteristics, in order to guarantee high accuracy of the classifier. In this paper, we introduce a distance measurement technique, using the Euclidean distance function to replace the optimal separating hyper-plane as the classification decision making function in the SVM. In our approach, the support vectors for each category are identified from the training data points during training phase using the SVM. In the classification phase, when a new data point is mapped into the original vector space, the average distances between the new data point and the support vectors from different categories are measured using the Euclidean distance function. The classification decision is made based on the category of support vectors which has the lowest average distance with the new data point, and this makes the classification decision irrespective of the efficacy of hyper-plane formed by applying the particular kernel function and soft margin parameter. We tested our proposed framework using several text datasets. The experimental results show that this approach makes the accuracy of the Euclidean-SVM text classifier to have a low impact on the implementation of kernel functions and soft margin parameter C.