Internet Studies and Development Discourses: The Cases of China and India

This paper investigates Internet studies in two leading developing countries (i.e. China and India) and finds that the Chinese scholarly community relies on the discourse of liberation from the state as a form of critique, whereas Indian Internet studies question the discourse of modernization to contemplate about the success and failure factors of information and communication technologies in development. The difference generally reflects the academic responses to the development discourses embraced by the two governments. We suggest that Internet studies should not only respond to the realities but also transcend the contextual constraints to direct attention to the often neglected dimensions of development, which are to make actual impacts through allowing the people and the communities to define their own development discourses as well as building research institutions that are oriented to influence policy-making.     

A Novel Approach to Improve the Speech Intelligibility Using Fractional Delta-amplitude Modulation Spectrogram

Abstract

Speech enhancement is an interesting research area that aims at improving the quality and intelligibility of the speech that is affected by the additive noises, such as airport noise, train noise, restaurant noise, and so on. The presence of these background noises degrades the comfort of listening of the end user. This article proposes a speech enhancement method that uses a novel feature extraction which removes the noise spectrum from the noisy speech signal using a novel fractional delta-AMS (amplitude modulation spectrogram) feature extraction and the D-matrix feature extraction method. The fractional delta-AMS feature extraction strategy is the modification of the delta-AMS with the fractional calculus that increases the sharpness of the feature extraction. The extracted features from the frames are used to determine the optimal mask of all the frames of the noisy speech signal and the mask is employed for training the deep belief neural networks (DBN). The two metrics root mean square error (RMSE) and perceptual evaluation of speech quality (PESQ) are used to evaluate the method. The proposed method yields a better value of PESQ at all level of noise and RMSE decreases with increased noise level.     

Dependency treelet translation: the convergence of statistical and example-based machine-translation?

We describe a novel approach to MT that combines the strengths of the two leading corpus-based approaches: Phrasal SMT and EBMT. We use a syntactically informed decoder and reordering model based on the source dependency tree, in combination with conventional SMT models to incorporate the power of phrasal SMT with the linguistic generality available in a parser. We show that this approach significantly outperforms a leading string-based Phrasal SMT decoder and an EBMT system. We present results from two radically different language pairs, and investigate the sensitivity of this approach to parse quality by using two distinct parsers and oracle experiments. We also validate our automated bleu scores with a small human evaluation.     

Efficient reliability estimate of passive thermal hydraulic safety system with automatic differentiation

An approach for efficient estimation of passive safety system functional reliability has been developed and applied to a simplified model of the passive residual heat transport system typical of sodium cooled fast reactors to demonstrate the reduction in computational time. The method is based on generating linear approximations to the best estimate computer code, using the technique of automatic reverse differentiation. This technique enables determination of linear approximation to the code in a few runs independent of the number of input variables for each response variable. The likely error due to linear approximation is reduced by augmented sampling through best estimate code in the neighborhood of the linear failure surface but in a sub domain where linear approximation error is relatively more. The efficiency of this new approach is compared with importance sampling MCS which uses the linear approximation near the failure region and with Direct Monte-Carlo Simulation. In the importance sampling MCS, variants employing random sampling with Box-Muller algorithm and Markov Chain algorithm are inter-compared. The significance of the results with respect to system reliability is also discussed.     

Optical merger of direct vision with virtual images for scaled teleoperation

Scaled teleoperation is increasingly prevalent in medicine, as well as in other applications of robotics. Visual feedback in such systems is essential and should make maximal use of natural hand-eye coordination. This paper describes a new method of visual feedback for scaled teleoperation in which the operator manipulates the handle of a remote tool in the presence of a registered virtual image of the target in real time. The method adapts a concept already used successfully in a new medical device called the sonic flashlight, which permits direct in situ visualization of ultrasound during invasive procedures. The sonic flashlight uses a flat-panel monitor and a half-silvered mirror to merge the visual outer surface of a patient with a simultaneous ultrasound scan of the patient's interior. Adapting the concept to scaled teleoperation involves removing the imaging device and the target to a remote location and adding a master-slave control device. This permits the operator to see his hands, along with what appears to be the tool, and the target, merged in a workspace that preserves natural hand-eye coordination. Three functioning prototypes are described, one based on ultrasound and two on light microscopy. The limitations and potential of the new approach are discussed.     

Environmental impacts of utilizing waste steel slag aggregates as recycled road construction materials

Slag is an industrial waste generated during the steelmaking process. Electric arc furnace slag (EAFS) and ladle furnace slag (LFS) are both produced at different stages of steelmaking process, respectively, in electric arc furnaces and refining ladle furnaces. As part of this research, an extensive suite of engineering and environmental tests were undertaken on steel slag aggregates to evaluate their potential usage as road construction materials. The engineering assessment included particle size distribution, hydrometer, organic content, flakiness index, Atterberg limits, particle density, water absorption, pH, minimum and maximum dry densities with a vibrating table, modified compaction, California bearing ratio (CBR) and Los Angeles abrasion tests. In addition, a suite of environmental tests comprising total and leachable heavy metal tests were undertaken on both types of steel slag aggregates. From an environmental perspective, EAFS and LFS were found to pose no environmental risks for use as aggregates in roadwork applications. The engineering properties of LFS aggregates with its satisfactory geotechnical and environmental results, particularly its high CBR values, indicated that the material was ideal for usage as a construction material in roadwork applications such as pavement base/subbases and engineering fills. EAFS, with its comparatively lower CBR value, was found to be only suitable to use as a construction material for pavement subbases and engineering fills. The usage of steel slag aggregates in roadwork applications would bring about a practical end-of-life alternative for their sustainable reuse and possibly divert large amount of these waste materials from landfills.     

Dynamic optimal experimental design yields marginal improvement over steady‐state results for computational maximisation of regulatory T‐cell induction in ex vivo culture

The isolation of T cells, followed by differentiation into Regulatory T cells (Tregs), and re‐transplantation into the body has been proposed as a therapeutic option for inflammatory bowel disease. A key requirement for making this a viable therapeutic option is the generation of a large population of Tregs. However, cytokines in the local microenvironment can impact the yield of Tregs during differentiation. As such, experimental design is an essential part of evaluating the importance of different cytokine concentrations for Treg differentiation. However, currently only single, constant concentrations of the cytokines have been investigated. This work addresses this point by performing experimental design in silico which seeks to maximize the predicted induction of Tregs relative to Th17 cells, by selecting an optimal input function for the concentrations of TGF‐β, IL‐2, IL‐6, and IL‐23. While this approach sounds promising, the results show that only marginal improvements in the concentration of Tregs can be achieved for dynamic cytokine profiles as compared to optimal constant concentrations. Since constant concentrations are easier to implement in experiments, it is recommended for this particular system to keep the concentrations constant where IL‐6 should be kept low and high concentrations of TGF‐β, IL‐2, and IL‐23 should be used.Inspec keywords: patient treatment, molecular biophysics, proteins, cellular biophysics, diseasesOther keywords: Tregs relative, optimal input function, dynamic cytokine profiles, optimal constant concentrations, IL‐23, computational maximisation, regulatory T‐cell induction, inflammatory bowel disease, viable therapeutic option, local microenvironment, Treg differentiation, single concentrations, predicted induction, dynamic optimal experimental design, interleukin‐2, IL‐6, transforming growth factor‐β