A review of the ICT-enabled development literature: Towards a power parity theory of ICT4D

ICT projects are considered an important means of achieving development goals in developing countries. Although voluminous, the research to date is inconsistent in theorizing how, or why, development outcomes do or do not occur following the introduction of ICT4D. To better understand how and why ICT projects succeed, and even what success means in the ICT4D context, we conducted a literature review of ICT4D studies published during the period 2000–2016. We find that the very meaning of development varies, with four meanings of development emerging from the literature: (1) development as increased freedom, (2) development as expanded inclusion, (3) development as increased economic productivity, and (4) development as improved well-being. An ICT might succeed according to one meaning of development while simultaneously hindering achievement according to another meaning. As revealed by our analysis of the literature, these four perspectives suffer from some limitations, not least among them being the imposition of colonialist views of development on the recipients of the ICT4D. To address the limitations, we employ postcolonial theory to derive a new theory of ICT4D in which development is defined as an increase in power parity between dominant stakeholders and intended beneficiaries.     

An adaptive fuzzy sliding mode controller for remotely operated underwater vehicles

Sliding mode control is a very attractive control scheme because of its robustness against both structured and unstructured uncertainties as well as external disturbances. In this way, it has been widely employed for the dynamic positioning of remotely operated underwater vehicles. Nevertheless, in such situations the discontinuities in the control law must be smoothed out to avoid the undesirable chattering effects. The adoption of properly designed boundary layers has proven effective in completely eliminating chattering, however, leading to an inferior tracking performance. This work describes the development of a dynamic positioning system for remotely operated underwater vehicles. The adopted approach is primarily based on the sliding mode control strategy and enhanced by an adaptive fuzzy algorithm for uncertainty/disturbance compensation. Using the Lyapunov stability theory and Barbalat’s lemma, the boundedness and convergence properties of the closed-loop signals are analytically proven. The performance of the proposed control scheme is also evaluated by means of numerical simulations.     

Gender differences in acute tobacco withdrawal: Effects on subjective, cognitive, and physiological measures.

Gender differences in tobacco withdrawal are of considerable clinical importance, but research findings on this topic have been mixed. Methodological variation in samples sizes, experimental design, and measures across studies may explain the inconsistent results. The current study examined whether male (n = 101) and female (n = 102) smokers (≥15 cigarettes/day) differed in abstinence-induced changes on a battery of self-report measures (withdrawal, affect, craving), cognitive performance tasks (attention, psychomotor performance), and physiological responses (heart rate, blood pressure, brain electroencephalogram). Participants attended 2 counterbalanced laboratory sessions, 1 following 12 hr of abstinence and the other following ad libitum smoking. Results showed that women reported greater abstinence-induced increases in negative affect, withdrawal-related distress, and urge to smoke to relieve withdrawal distress. In contrast, both genders reported similar abstinence-induced changes in positive affect and urge to smoke for pleasure. Men and women exhibited generally similar abstinence-induced changes in physiological and cognitive performance measures. In addition, gender did not moderate the association between withdrawal symptoms and baseline measures of smoking behavior and dependence. Abstinence-induced changes in withdrawal distress mediated the effect of gender on latency until the 1st cigarette of the day at trend levels ( p     

Improving class probability estimates for imbalanced data

Obtaining good probability estimates is imperative for many applications. The increased uncertainty and typically asymmetric costs surrounding rare events increase this need. Experts (and classification systems) often rely on probabilities to inform decisions. However, we demonstrate that class probability estimates obtained via supervised learning in imbalanced scenarios systematically underestimate the probabilities for minority class instances, despite ostensibly good overall calibration. To our knowledge, this problem has not previously been explored. We propose a new metric, the stratified Brier score, to capture class-specific calibration, analogous to the per-class metrics widely used to assess the discriminative performance of classifiers in imbalanced scenarios. We propose a simple, effective method to mitigate the bias of probability estimates for imbalanced data that bags estimators independently calibrated over balanced bootstrap samples. This approach drastically improves performance on the minority instances without greatly affecting overall calibration. We extend our previous work in this direction by providing ample additional empirical evidence for the utility of this strategy, using both support vector machines and boosted decision trees as base learners. Finally, we show that additional uncertainty can be exploited via a Bayesian approach by considering posterior distributions over bagged probability estimates.     

ICRP PUBLICATION 118: ICRP Statement on Tissue Reactions and Early and Late Effects of Radiation in Normal Tissues and Organs - Threshold Doses for Tissue Reactions in a Radiation Protection Context

This report provides a review of early and late effects of radiation in normal tissues and organs with respect to radiation protection. It was instigated following a recommendation in Publication 103 (ICRP, 2007), and it provides updated estimates of 'practical' threshold doses for tissue injury defined at the level of 1% incidence. Estimates are given for morbidity and mortality endpoints in all organ systems following acute, fractionated, or chronic exposure. The organ systems comprise the haematopoietic, immune, reproductive, circulatory, respiratory, musculoskeletal, endocrine, and nervous systems; the digestive and urinary tracts; the skin; and the eye. Particular attention is paid to circulatory disease and cataracts because of recent evidence of higher incidences of injury than expected after lower doses; hence, threshold doses appear to be lower than previously considered. This is largely because of the increasing incidences with increasing times after exposure. In the context of protection, it is the threshold doses for very long follow-up times that are the most relevant for workers and the public; for example, the atomic bomb survivors with 40-50years of follow-up. Radiotherapy data generally apply for shorter follow-up times because of competing causes of death in cancer patients, and hence the risks of radiation-induced circulatory disease at those earlier times are lower. A variety of biological response modifiers have been used to help reduce late reactions in many tissues. These include antioxidants, radical scavengers, inhibitors of apoptosis, anti-inflammatory drugs, angiotensin-converting enzyme inhibitors, growth factors, and cytokines. In many cases, these give dose modification factors of 1.1-1.2, and in a few cases 1.5-2, indicating the potential for increasing threshold doses in known exposure cases. In contrast, there are agents that enhance radiation responses, notably other cytotoxic agents such as antimetabolites, alkylating agents, anti-angiogenic drugs, and antibiotics, as well as genetic and comorbidity factors. Most tissues show a sparing effect of dose fractionation, so that total doses for a given endpoint are higher if the dose is fractionated rather than when given as a single dose. However, for reactions manifesting very late after low total doses, particularly for cataracts and circulatory disease, it appears that the rate of dose delivery does not modify the low incidence. This implies that the injury in these cases and at these low dose levels is caused by single-hit irreparable-type events. For these two tissues, a threshold dose of 0.5Gy is proposed herein for practical purposes, irrespective of the rate of dose delivery, and future studies may elucidate this judgement further.     

Robust multiscale stereo matching from fundus images with radiometric differences

A robust multiscale stereo matching algorithm is proposed to find reliable correspondences between low contrast and weakly textured retinal image pairs with radiometric differences. Existing algorithms designed to deal with piecewise planar surfaces with distinct features and Lambertian reflectance do not apply in applications such as 3D reconstruction of medical images including stereo retinal images. In this paper, robust pixel feature vectors are formulated to extract discriminative features in the presence of noise in scale space, through which the response of low-frequency mechanisms alter and interact with the response of high-frequency mechanisms. The deep structures of the scene are represented with the evolution of disparity estimates in scale space, which distributes the matching ambiguity along the scale dimension to obtain globally coherent reconstructions. The performance is verified both qualitatively by face validity and quantitatively on our collection of stereo fundus image sets with ground truth, which have been made publicly available as an extension of standard test images for performance evaluation.     

MeteoBayes: Effective Plan Recognition in a Weather Dialogue System

When you've called a voice portal for any kind of information retrieval, chances are that an automated system guided the entire interaction. It might have correctly identified your goal, but probably only after asking too many questions. MeteoBayes is a meteorological information dialogue system that lets you use natural language to direct the interaction. Based on Bayesian networks, MeteoBayes' inference engine attempts to identify user intentions by consulting its past dialogue repository. For unfamiliar words, MeteoBayes has an unknown-term disambiguation module that learns word similarities from texts to avoid unnecessary system inquiries, thus speeding up the understanding process     

Due date setting with supply constraints in systems using MRP

We propose a new model for quoting due dates in a make-to-order environment where customers request due dates. The model incorporates inventory costs, fill rate issues, and service level issues. In particular, we consider order delay costs that measure the positive difference between the due date requested by the customer and the due date committed by the supplier. The underlying two-stage production model assumes that production is constrained primarily by an uncertain procurement process, as is the case in many assembly systems. This simplification results in a news vendor-like formulation that enables us to obtain a simple approximately optimal due date setting policy that is well suited to MRP environments. The model also yields several interesting policy conclusions. For example, in environments where the importance of service level performance does not reach a certain threshold relative to the importance of order acceptance, the optimal policy is to always quote the requested due date. A special case of our formulation of the problem is to minimize lead-times. However, we show that a lead-time minimization often yields longer quoted due dates than our general formulation.