The case for technology in developing regions

Alongside good governance, technology is considered among the greatest enablers for improved quality of life. However, the majority of its benefits have been concentrated in industrialized nations and therefore limited to a fraction of the world's population. We believe that technology has a large role to play in developing regions, that "First World" technology to date has been a poor fit in these areas, and that there is thus a need for technology research for developing regions. Despite the relative infancy of technology studies in developing regions, anecdotal evidence suggests that access to technology has a beneficial economic impact. Cellular telephony is probably the most visible application, but there are many others, some of which we cover in this article. The World Bank's infoDev site catalogs hundreds of information and communications technologies (ICT) projects, albeit not all successful. Most of these projects use existing off-the-shelf technology designed for the industrialized world. Although it is clear that there are large differences in assumptions related to cost, power, and usage, there has been little work on how technology needs in developing regions differ from those of industrialized nations. We argue that Western market forces continue to meet the needs of developing regions accidentally at best.     

Nonlinear dynamic system identification using Chebyshev functionallink artificial neural networks

A computationally efficient artificial neural network (ANN) for the purpose of dynamic nonlinear system identification is proposed. The major drawback of feedforward neural networks, such as multilayer perceptrons (MLPs) trained with the backpropagation (BP) algorithm, is that they require a large amount of computation for learning. We propose a single-layer functional-link ANN (FLANN) in which the need for a hidden layer is eliminated by expanding the input pattern by Chebyshev polynomials. The novelty of this network is that it requires much less computation than that of a MLP. We have shown its effectiveness in the problem of nonlinear dynamic system identification. In the presence of additive Gaussian noise, the performance of the proposed network is found to be similar or superior to that of a MLP. A performance comparison in terms of computational complexity has also been carried out.     

Swing-up and stabilization of a cart–pendulum system under restricted cart track length

This paper describes the swing-up and stabilization of a cart–pendulum system with a restricted cart track length and restricted control force using generalized energy control methods. Starting from a pendant position, the pendulum is swung up to the upright unstable equilibrium configuration using energy control principles. An “energy well” is built within the cart track to prevent the cart from going outside the limited length. When sufficient energy is acquired by the pendulum, it goes into a “cruise” mode when the acquired energy is maintained. Finally, when the pendulum is close to the upright configuration, a stabilizing controller is activated around a linear zone about the upright configuration. The proposed scheme has worked well both in simulation and a practical setup and the conditions for stability have been derived using the multiple Lyapunov functions approach.     

High-Throughput Memory-Based Architecture for DHT Using a New Convolutional Formulation

A new formulation is presented for the computation of an -point discrete Hartley transform (DHT) from two pairs of [(N/2-1)/2]-point cyclic convolutions, and further used to obtain modular structures consisting of simple and regular memory-based systolic arrays for concurrent pipelined realization of the DHT. The proposed structures for direct-memory-based implementation is found to involve nearly the same hardware complexity as those of the existing structures, but offers two to four times more throughput and two to four times less latency compared with others. The distributed-arithmetic (DA)-based implementation is also found to offer very less memory-complexity and considerably low area-delay complexity compared with the existing DA-based structures.     

A technique for generating natural colour images from false colour composite images

Colour is widely used in remote sensing work. In many instances, the use of colour conveys additional information both visually and scientifically. Remote sensing satellites view the earth in different spectral bands, viz. near infrared (NIR), red, green, and blue bands, in a conventional multispectral imaging system. In the absence of a blue channel, colour images can be generated using near infrared, red, and green bands in what is known as a false colour composite (FCC) and does not look natural, like the image we see with the naked eye. For a trained interpreter, this does not pose any problems. However, when the intended use is a fly‐through of a draped terrain, visual interpretation, or a display, meant for the non‐remote sensing professional, this becomes a handicap. To overcome this, there is a requirement to generate natural colour composites (NCC) from the given false colour composite, which demands the simulation of a blue band to be combined with green and red bands. This paper describes a unique method of generating a blue band to form natural colour images from a given false colour image set. We use a spectral transformation method to establish a relationship between the false colour and true colour image pairs provided by a sensor with all the four bands, which has a broader spectral coverage. A transformation function is fitted by selecting radiometric control points along the line of geometric registration to find a set of coefficients to be used for simulating a blue band. This blue band, along with the green and red bands, provides a near true colour or ‘natural colour’ on the display. In this paper, we present a set of adjustable radiometric transformation coefficients to accommodate variation in spatial and dynamic range offered by sensors to generate natural colour. These coefficients seem to work on a large number of images of different seasons, provided similar spectral bands and terrain are used. The proposed ‘natural colour generator’ can be used in changing false colour images to natural colour images with the aim of ‘what you get is what you would have seen’.     

Parallel Godunov smoothed particle hydrodynamics (SPH) with improved treatment of Boundary Conditions and an application to granular flows

Smoothed Particle Hydrodynamics has been successfully used for various fluid-dynamics problems, such as breaking-waves, flooding etc., since it was originally proposed. While the Lagrangian approach is naturally suitable for free-surface flows, enforcing boundary conditions and poor approximations in the presence of discontinuities in the solution are major difficulties with the method. In this paper we present an enhanced conservative Godunov SPH based on the work of Inutsuka [S. Inutsuka, Reformulation of smoothed particle hydrodynamics with Riemann solver, Journal of Computational Physics 179 (2002) 238–267] that accurately resolves discontinuities without the need to use artificial viscosity, preserves partition of unity everywhere in the domain, correctly and flexibly enforces necessary essential and frictional slip boundary conditions to approximately solve free-surface granular flows. The development is motivated by the need to improve upon depth averaged grid based models of large scale debris flows and avalanches often characterized as granular flows. Simple validation of the results is obtained by comparison to table-top experiments.     

Review of tools and algorithms for network motif discovery in biological networks

Network motifs are recurrent and over‐represented patterns having biological relevance. This is one of the important local properties of biological networks. Network motif discovery finds important applications in many areas such as functional analysis of biological components, the validity of network composition, classification of networks, disease discovery, identification of unique subunits etc. The discovery of network motifs is a computationally challenging task due to the large size of real networks, and the exponential increase of search space with respect to network size and motif size. This problem also includes the subgraph isomorphism check, which is Nondeterministic Polynomial (NP)‐complete. Several tools and algorithms have been designed in the last few years to address this problem with encouraging results. These tools and algorithms can be classified into various categories based on exact census, mapping, pattern growth, and so on. In this study, critical aspects of network motif discovery, design principles of background algorithms, and their functionality have been reviewed with their strengths and limitations. The performances of state‐of‐art algorithms are discussed in terms of runtime efficiency, scalability, and space requirement. The future scope, research direction, and challenges of the existing algorithms are presented at the end of the study.Inspec keywords: computational complexity, graph theory, biology, search problemsOther keywords: network size, motif size, network motif discovery, biological networks, network composition, recurrent patterns, over‐represented patterns, local properties, search space, subgraph isomorphism check, NP‐complete problem, NP‐complete problem, exact census, design principles, background algorithms, runtime efficiency, space requirement     

Electron paramagnetic resonance and Mössbauer spectroscopy of transition metal ion doped mullite

Appreciable difference in the properties of undoped and oxide-doped mullite are observed. The oxidation state of cation, its concentration and the position of the mullite lattice occupied by it appear to be the responsible factors. Mullite has, therefore, been doped with four transition metal ions, Mn, Fe, Cr and Ti. With the help of EPR and Mössbauer spectroscopy (supplimented by X-ray diffractometry) the oxidation states of these ions and the mullite lattice sites where they enter has been investigated. It was observed that Mn ion was present in Mn²⁺ and Mn³⁺ states, the former remained as clusters and the latter occupied the octahedral sites in the mullite lattice. Only Fe³⁺ ion was detected and conclusive evidence was obtained for the entry of Fe³⁺ in the octahedral lattice position of mullite from the analysis of Mössbauer spectra with the help of a specially written computer programme. The Cr ion entered the mullite structure only in the Cr³⁺ state. The change in lattice parameters of Cr doped mullite were measured by the XRD technique. The results showed that the expansion of b-axis was more than that of the a-axis which supported the presence of Cr³⁺ ion in the octahedral site of mullite lattice. The absence of signal in the EPR spectra of Ti doped mullite suggested the presence of only Ti⁴⁺ (3d⁰) ion. Very low electrical resistivity of Ti doped mullite and close similarity between mullite and Al₂TiO₅ structures stood as evidence for incorporation of Ti⁴⁺ ion in the octahedral site of mullite lattice by replacing Al³⁺ ion.     

Phase assignment for synthesis of low-power domino circuits

High performance circuit techniques such as domino logic have migrated from the microprocessor world into more mainstream ASIC designs but domino logic comes at a heavy cost in terms of total power dissipation. A set of results related to automated phase assignment for the synthesis of low-power domino circuits is presented: (1) it is demonstrated that the choice of phase assignment at the primary outputs of a circuit can significantly impact lower dissipation in the domino block, and (2) a method to determine a phase assignment that minimises power consumption in the final circuit implementation is proposed. Preliminary experimental results on a mixture of public domain benchmarks and real industry circuits show potential power savings as high as 34% over the minimum area realisation of the logic. Furthermore, the low-power synthesised circuits still meet timing constraints     

Deploying a Rural Wireless Telemedicine System: Experiences in Sustainability

A novel ICT project in rural India uses long-distance Wi-Fi networking to enable high-quality videoconferencing between eye hospitals and remote village clinics. The project highlights the importance of sustainability as a first-class goal for systems research.