Irreconcilable differences? Building a human rights culture and dealing with crime in post apartheid South Africa

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Deep convolutional and LSTM recurrent neural networks for multimodal wearable activity recognition

Human activity recognition (HAR) tasks have traditionally been solved using engineered features obtained by heuristic processes. Current research suggests that deep convolutional neural networks are suited to automate feature extraction from raw sensor inputs. However, human activities are made of complex sequences of motor movements, and capturing this temporal dynamics is fundamental for successful HAR. Based on the recent success of recurrent neural networks for time series domains, we propose a generic deep framework for activity recognition based on convolutional and LSTM recurrent units, which: (i) is suitable for multimodal wearable sensors; (ii) can perform sensor fusion naturally; (iii) does not require expert knowledge in designing features; and (iv) explicitly models the temporal dynamics of feature activations. We evaluate our framework on two datasets, one of which has been used in a public activity recognition challenge. Our results show that our framework outperforms competing deep non-recurrent networks on the challenge dataset by 4% on average; outperforming some of the previous reported results by up to 9%. Our results show that the framework can be applied to homogeneous sensor modalities, but can also fuse multimodal sensors to improve performance. We characterise key architectural hyperparameters’ influence on performance to provide insights about their optimisation

An adverse social welfare consequence of a rich-to-poor income transfer: A relative deprivation approach

A transfer from a richer individual to a poorer one seems to be the most intuitive and straightforward way of reducing income inequality in a society. However, can such a transfer reduce the welfare of the society? We show that a rich-to-poor transfer can induce a response in the individuals’ behaviors which actually exacerbates, rather than reduces, income inequality as measured by the Gini index. We use this result as an input in assessing the social welfare consequence of the transfer. Measuring social welfare by Sen’s social welfare function, we show that the transfer reduces social welfare. These two results are possible even for individuals whose utility functions are relatively simple (namely, at most quadratic in all terms) and incorporate a distaste for low relative income. We first present the two results for a population of two individuals. We subsequently provide several generalizations. We show that our argument holds for a population of any size, and that the choice of utility functions which trigger this response is not singular - the results obtain for an open set of the space of admissible utility functions. In addition, we show that a rich-to-poor transfer can exacerbate inequality when we employ Lorenz-domination, and that it can decrease social welfare when we draw on any increasing, Schur-concave welfare function

An Approximation Algorithm for Stackelberg Network Pricing

We consider the problem of maximizing the revenue raised from tolls set on the arcs of a transportation network, under the constraint that users are assigned to toll-compatible shortest paths. We first prove that this problem is strongly NP-hard. We then provide a polynomial time algorithm with a worst-case precision guarantee of ${1/2}\log_2 m_T+1$, where $m_T$ denotes the number of toll arcs. Finally we show that the approximation is tight with respect to a natural relaxation by constructing a family of instances for which the relaxation gap is reached.Comment: 38 page

The effect of physical activity classes on motor skill in 12-24-month-old children

Background: Children with enhanced fundamental movement skills may benefit from improved physical, social and psychological development, resulting in an increased likelihood of an active lifestyle in later years. Aim: We investigated the effects of a nine-week, child-centred, physical activity programme on cognitive and motor skills in typically developing 12 - 24-month-old toddlers. Methods: In a randomised control trial, 90 toddlers (age 17.0 ± 2.6 months; 52.2% male) were split into two groups stratified by age and sex. The intervention completed was either nine weeks of one-hour per week physical activity classes (n = 45; EXP) or normal physical activity (n = 45; control). Prior to and following the intervention period, safety skills (nine-skill test battery), anthropometric measures (mass and height), motor and cognitive development (Bayley Scales of Infant Development) were assessed. Results: EXP improved overall safety skills score (P = 0.04), toddlers’ abilities to climb over a small-runged A-frame while using a cylinder grip and safe face-the-slope dismount (P = 0.001), and the execution of a safety roll down a foam wedge (P = 0.02). Improvements in development as measured by the Bayley’s Scales were attributed to typical development rather than the intervention. Conclusions: A 9-week, physical activity programme improved toddlers’ safety skills but not overall cognitive or motor development

Sensitivity of wardrop equilibria

We study the sensitivity of equilibria in the well-known game theoretic traffic model due to Wardrop. We mostly consider single-commodity networks. Suppose, given a unit demand flow at Wardrop equilibrium, one increases the demand by ε or removes an edge carrying only an ε-fraction of flow. We study how the equilibrium responds to such an ε-change. Our first surprising finding is that, even for linear latency functions, for every ε> 0, there are networks in which an ε-change causes every agent to change its path in order to recover equilibrium. Nevertheless, we can prove that, for general latency functions, the flow increase or decrease on every edge is at most ε. Examining the latency at equilibrium, we concentrate on polynomial latency functions of degree at most p with nonnegative coefficients. We show that, even though the relative increase in the latency of an edge due to an ε-change in the demand can be unbounded, the path latency at equilibrium increases at most by a factor of (1 + ε) p . The increase of the price of anarchy is shown to be upper bounded by the same factor. Both bounds are shown to be tight. Let us remark that all our bounds are tight. For the multi-commodity case, we present examples showing that neither the change in edge flows nor the change in the path latency can be bounded