An empirical investigation into the difficulties experienced by visually impaired Internet users

In this paper, an empirical based study is described which has been conducted to gain a deeper understanding of the challenges faced by the visually impaired community when accessing the Web. The study, involving 30 blind and partially sighted computer users, has identified navigation strategies, perceptions of page layout and graphics using assistive devices such as screen readers. Analysis of the data has revealed that current assistive technologies impose navigational constraints and provide limited information on web page layout. Conveying additional spatial information could enhance the exploration process for visually impaired Internet users. It could also assist the process of collaboration between blind and sighted users when performing web-based tasks. The findings from the survey have informed the development of a non-visual interface, which uses the benefits of multimodal technologies to present spatial and navigational cues to the user.     

Dynamic graph cuts for efficient inference in Markov Random Fields

Abstract-In this paper we present a fast new fully dynamic algorithm for the st-mincut/max-flow problem. We show how this algorithm can be used to efficiently compute MAP solutions for certain dynamically changing MRF models in computer vision such as image segmentation. Specifically, given the solution of the max-flow problem on a graph, the dynamic algorithm efficiently computes the maximum flow in a modified version of the graph. The time taken by it is roughly proportional to the total amount of change in the edge weights of the graph. Our experiments show that, when the number of changes in the graph is small, the dynamic algorithm is significantly faster than the best known static graph cut algorithm. We test the performance of our algorithm on one particular problem: the object-background segmentation problem for video. It should be noted that the application of our algorithm is not limited to the above problem, the algorithm is generic and can be used to yield similar improvements in many other cases that involve dynamic change.     

Modeling sensorimotor learning with linear dynamical systems

Recent studies have employed simple linear dynamical systems to model trial-by-trial dynamics in various sensorimotor learning tasks. Here we explore the theoretical and practical considerations that arise when employing the general class of linear dynamical systems (LDS) as a model for sensorimotor learning. In this framework, the state of the system is a set of parameters that define the current sensorimotor transformation-the function that maps sensory inputs to motor outputs. The class of LDS models provides a first-order approximation for any Markovian (state-dependent) learning rule that specifies the changes in the sensorimotor transformation that result from sensory feedback on each movement. We show that modeling the trial-by-trial dynamics of learning provides a substantially enhanced picture of the process of adaptation compared to measurements of the steady state of adaptation derived from more traditional blocked-exposure experiments. Specifically, these models can be used to quantify sensory and performance biases, the extent to which learned changes in the sensorimotor transformation decay over time, and the portion of motor variability due to either learning or performance variability. We show that previous attempts to fit such models with linear regression have not generally yielded consistent parameter estimates. Instead, we present an expectation-maximization algorithm for fitting LDS models to experimental data and describe the difficulties inherent in estimating the parameters associated with feedback-driven learning. Finally, we demonstrate the application of these methods in a simple sensorimotor learning experiment: adaptation to shifted visual feedback during reaching.     

Graduate school origins of Journal of Counseling Psychology authors: Volumes 15-28.

Examined the graduate school origins of authors of Journal of Counseling Psychology (JCP) articles in Volumes 15–28 to extend a previous analysis of Volumes 1–24 by the 3rd author et al (1969). Comparisons of the 2 14-yr periods reveal that some universities retained the same or similar ranks across both periods, some declined in importance as sources of authors, and others emerged as major sources of JCP authors. (6 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

An Investigation into Lubrication and Oxide Breakdown During Load-Carrying Capacity Testing

Changes occurring in the friction and wear mechanisms during a load-carrying capacity test, lubricated with cetane containing a carboxylic acid, were investigated. The changes in wear scar/track appearance and oxide coverage/composition were analyzed during every load stage.

The main conclusions were as follows:

• The breakdown in the protective oxide layer formed on the opposing steel surfaces was found to be the prerequisite for initiation of seizure.

• The seizure load achieved during load-carrying capacity testing quantifies the ability of the test fluid to prevent transition to the adhesive wear regime.

• The most severe surface damage was found to occur during the first few seconds after test initiation. Desorption of the adsorbed lubricant film and the subsequent removal of the naturally occurring thin oxide layer results in the initial period of adhesive wear.

• Partial recovery to a state of acceptable friction occurs after the period of initial seizure. During this period, the surface coverage by the adsorption lubricant molecules and the oxide coverage are sufficient to prevent severe adhesive wear from occurring. Wear is primarily a combination of oxidative, abrasive, and fatigue wear (all possible in the regions of mixed friction and boundary lubrication).

• Final lubricant breakdown and eventual seizure are initiated when the oxide removal rate exceeds the oxide formation rate resulting in severe adhesive wear followed by seizure.

     

Water and Sustainable Development in Ghana

Abstract

Water is vital for the survival and development of every community or society. The health of a given community is reflected to a large extent in the water quality of the community's available water resources. In Ghana, efforts have been made since colonial days to supply both the urban and the rural communities with potable water to enhance the rapid socio-economic development of the country. It is economically viable due to the remoteness of most of the rural communities to supply them with potable water from local sources such as groundwater. The urban water supply systems are mainly based on surface water sources. With the ever-expanding population, there is a need to improve freshwater resources conservation and management in order to avoid impending shortages. To ensure the total coverage of all rural and urban communities by the year 2020, a huge capital outlay of $1 billion and 51.5 billion, respectively, is needed. Most of these funds are expected to come from the private sector, both local and foreign, with the Government making some substantial contribution.     

A longitudinal study of emoticon use in text messaging from smartphones

Our goal in the present study was to understand how emoticons are used in text messaging and, in particular, how genders differed in the frequency and variety of emoticons used via this medium. Previous research has found small and sundry differences in emotive expression online suggesting that technology has closed the gender gap. However, the data collected in these studies were public. In this study, we collected real portions of private communications data from individuals’ smartphones over a 6-month period. SMS messages, in general, were not used very much overall, with only 4% of all messages containing at least one emoticon. Still, differences between genders manifested in the amount and variety of emoticons used. Females sent more messages with emoticons; however, surprisingly, males used a more diverse range of emoticons.     

Soft syntactic constraints for Arabic–English hierarchical phrase-based translation

In adding syntax to statistical machine translation, there is a tradeoff between taking advantage of linguistic analysis and allowing the model to exploit parallel training data with no linguistic analysis: translation quality versus coverage. A number of previous efforts have tackled this tradeoff by starting with a commitment to linguistically motivated analyses and then finding appropriate ways to soften that commitment. We present an approach that explores the tradeoff from the other direction, starting with a translation model learned directly from aligned parallel text, and then adding soft constituent-level constraints based on parses of the source language. We argue that in order for these constraints to improve translation, they must be fine-grained: the constraints should vary by constituent type, and by the type of match or mismatch with the parse. We also use a different feature weight optimization technique, capable of handling large amount of features, thus eliminating the bottleneck of feature selection. We obtain substantial improvements in performance for translation from Arabic to English.     

Smooth Transition Quantile Capital Asset Pricing Models with Heteroscedasticity

Capital asset pricing model (CAPM) has become a fundamental tool in finance for assessing the cost of capital, risk management, portfolio diversification and other financial assets. It is generally believed that the market risks of the assets, often denoted by a beta coefficient, should change over time. In this paper, we model timevarying market betas in CAPM by a smooth transition regime switching CAPM with heteroscedasticity, which provides flexible nonlinear representation of market betas as well as flexible asymmetry and clustering in volatility. We also employ the quantile regression to investigate the nonlinear behavior in the market betas and volatility under various market conditions represented by different quantile levels. Parameter estimation is done by a Bayesian approach. Finally, we analyze some Dow Jones Industrial stocks to demonstrate our proposed models. The model selection method shows that the proposed smooth transition quantile CAPM?CGARCH model is strongly preferred over a sharp threshold transition and a symmetric CAPM?CGARCH model.     

Polyaniline / carbon nanotube composites: starting with phenylamino functionalized carbon nanotubes

Summary Composites of carbon a nanotube with polymers are a developing and interesting area of research. The dispersion of the nanotube in polymer matrices is an important factor while making its nanocomposites. Even though in-situ polymerization approach offers a better approach for synthesizing homogeneous polymer nanotube composites, the dispersion of the nanotubes in the monomer solution is a problem. In this article we report a new chemical method for dispersing nanotubes in monomer and the preparation of uniform tubular composite of polyaniline (PANI) and multiwalled carbon nanotube (MWNT). For this the oxidized multiwalled nanotube (o-MWNT) was functionalized with p-phenylenediamine, which gave phenylamine functional groups on the surface. This functionalization helped to disperse the nanotubes in acidic solution. The in-situ polymerization of aniline in the presence of these well dispersed nanotubes gave a new tubular composite of carbon nanotube having an ordered uniform encapsulation of doped polyaniline. The phenylamine functional groups on the surface were grown into polyaniline chain so that the composite contains polyaniline functionalized CNT and they were no more an impurity in the final nanocomposite. The microscopic and structural properties of this composite were compared with that of a composite prepared under identical condition using o-MWNT.