A preemptive bound for the Resource Constrained Project Scheduling Problem

The Resource Constrained Project Scheduling Problem is one of the most intensively investigated scheduling problems. It requires scheduling a set of interrelated activities, while considering precedence relationships, and limited renewable resources allocation. The objective is to minimize the project duration. We propose a new destructive lower bound for this challenging ${\mathcal {NP}}$ -hard problem. Starting from a previously suggested LP model, we propose several original valid inequalities that aim at tightening the model representation. These new inequalities are based on precedence constraints, incompatible activity subsets, and nonpreemption constraints. We present the results of an extensive computational study that was carried out on 2,040 benchmark instances of PSPLIB, with up to 120 activities, and that provide strong evidence that the new proposed lower bound exhibits an excellent performance. In particular, we report the improvement of the best known lower bounds of 5 instances.     

Moving people tracking with detection by latent semantic analysis for visual surveillance applications

The latent semantic analysis (LSA) has been widely used in the fields of computer vision and pattern recognition. Most of the existing works based on LSA focus on behavior recognition and motion classification. In the applications of visual surveillance, accurate tracking of the moving people in surveillance scenes, is regarded as one of the preliminary requirement for other tasks such as object recognition or segmentation. However, accurate tracking is extremely hard under challenging surveillance scenes where similarity among multiple objects or occlusion among multiple objects occurs. Usual temporal Markov chain based tracking algorithms suffer from the ‘tracking error accumulation problem’. The accumulated errors can finally make the tracking to drift from the target. To handle the problem of tracking drift, some authors have proposed the idea of using detection along with tracking as an effective solution. However, many of the critical issues still remain unsettled in these detection based tracking algorithms. In this paper, we propose a novel moving people tracking with detection based on (probabilistic) LSA. By employing a novel ‘twin-pipeline’ training framework to find the latent semantic topics of ‘moving people’, the proposed detection can effectively detect the interest points on moving people in different indoor and outdoor environments with camera motion. Since the detected interest points on different body parts can be used to locate the position of moving people more accurately, by combining the detection with incremental subspace learning based tracking, the proposed algorithms resolves the problem of tracking drift during each target appearance update process. In addition, due to the time independent processing mechanism of detection, the proposed method is also able to handle the error accumulation problem. The detection can calibrate the tracking errors during updating of each state of the tracking algorithm. Extensive, experiments on various surveillance environments using different benchmark datasets have proved the accuracy and robustness of the proposed tracking algorithm. Further, the experimental comparison results clearly show that the proposed tracking algorithm outperforms the well known tracking algorithms such as ISL, AMS and WSL algorithms. Furthermore, the speed performance of the proposed method is also satisfactory for realistic surveillance applications.     

Characterization and modeling of diffusion process for mass transport through the Tournemire argillites (Aveyron, France)

Argillites are one of the geological formations studied by IRSN for their confining properties for isolation of radioactive wastes. One of the main objectives is the study of water transport through rocks with very low water content and very low hydraulic conductivity by modeling of natural tracer profiles. This paper presents the protocol developed for and applied to the acquisition of data for chloride content in interstitial water of the Toarcian argillites at the Tournemire site (Southern France). This protocol is based on laboratory diffusion experiments and on modeling. Experimental data obtained during the transient and steady-state parts of diffusion experiments enable, respectively, the assessment of the diffusion coefficient and the determination of Cl concentration in pore water. Using this protocol, profiles with depth for both of these data sets have been acquired along the geological sequence. Taking into account the present knowledge of the geological and hydrogeological history of the Tournemire massif, a conceptual model granting the main role for mass transport to diffusion has been proposed. According to this conceptual model, a one-dimensional numerical model was built for simulating the mass transport of chloride through the sedimentary column, over 53 Ma. The good agreement between experimental data and calculated values for both diffusion coefficients and concentrations of chloride confirms that diffusion is likely the main process for mass transport in the massif. This model was also tested with the deuterium content of interstitial water, applying variable concentrations at the aquifer system boundaries for reflecting the thermal dependency of isotopic composition in precipitation. These simulations also reveal the likely important role of heterogeneities, such as fractures, in the variability of tracer concentrations with regards to a simple diffusion profile.     

Pose consensus in networks of heterogeneous robots with variable time delays

This paper proposes a novel pose (position and orientation) consensus controller for networks of heterogeneous robots modeled in the operational space. The proposed controller is a distributed proportional plus damping scheme that, with a slight modification, solves both the leader–follower and leaderless consensus problems. A singularity‐free representation, unit quaternion, is used to describe the robots orientation, and the network is represented by an undirected and connected interconnection graph. Furthermore, it is shown that the controller is robust to interconnection variable time delays. Experiments with a network of two 6‐degrees‐of‐freedom robots are presented to illustrate the performance of the proposed scheme. Copyright © 2014 John Wiley & Sons, Ltd.     

Seasonal dynamics of physico-chemical characteristics and biological responses of Lake Chilwa,Southern Africa

Lake Chilwa is shared by Malawi and Mozambique, it supports an important fishery and its watershed is undergoing rapid population growth and increasing utilization for agricultural production. It is a shallow, closed basin lake with extensive surrounding wetlands; and it has suffered several desiccation events in the last century. To better understand the current condition of the lake, we monitored a suite of physical, chemical and biological parameters at approximately monthly intervals over an annual cycle in 2004–2005. The limnology of the lake was extremely sensitive to seasonal changes in the lake's seasonal hydrological cycle. The physico-chemical parameters, temperature, electrical conductivity, and total suspended solids exhibited clear seasonal patterns driven by the highly seasonal rainfall and resultant lake levels. In response, phytoplankton and zooplankton abundance, as well as biologically dependent oxygen concentrations and pH, exhibited several maxima levels over the year. The peaks of phytoplankton and zooplankton were out of phase suggesting a lag in the zooplankton grazing in response to pulses in primary productivity. Chlorophyll concentrations can exceed 1 mg/L in surface waters indicative of hypereutrophic conditions, but they fell dramatically during zooplankton peaks. This hydrologically driven, shallow and mesohaline lake is a productive and critical resource to the region. Its management poses challenges arising from the dependence of its limnology and fishery on the lakes hydrology, catchment land use and climate variability.     

Generalized linear mixed model with a penalized Gaussian mixture as a random effects distribution

Generalized linear mixed models are popular for regressing a discrete response when there is clustering, e.g. in longitudinal studies or in hierarchical data structures. It is standard to assume that the random effects have a normal distribution. Recently, it has been examined whether wrongly assuming a normal distribution for the random effects is important for the estimation of the fixed effects parameters. While it has been shown that misspecifying the distribution of the random effects has a minor effect in the context of linear mixed models, the conclusion for generalized mixed models is less clear. Some studies report a minor impact, while others report that the assumption of normality really matters especially when the variance of the random effect is relatively high. Since it is unclear whether the normality assumption is truly satisfied in practice, it is important that generalized mixed models are available which relax the normality assumption. A replacement of the normal distribution with a mixture of Gaussian distributions specified on a grid whereby only the weights of the mixture components are estimated using a penalized approach ensuring a smooth distribution for the random effects is proposed. The parameters of the model are estimated in a Bayesian context using MCMC techniques. The usefulness of the approach is illustrated on two longitudinal studies using R-functions.     

Post-buckling dynamic behavior of self-assembled 3D microstructures

The paper presents the snap-through phenomenon in the case of micro fabricated clamped-clamped buckled beam. This dynamic post-buckling behavior is likely to occur in 3D microstructures when they are subjected to large vibration amplitudes. The main difference between this work and previous studies is the MEMS specific beam dimension, especially the large initial deflection of the buckled beam that involves the inversion of the two first resonance frequencies. The mathematical development allows showing how the vibration amplitude of the supporting base affects the post-buckling dynamic behavior of the beam. For each frequency, the limit between the stable behavior and the snap-through behavior is evaluated. Moreover, the effect of environment is taken into account from the damping point of view. Samples are fabricated and the experiment is described. Measurements are compared to the theoretical approach and the results are in good agreement with the proposed model.     

Edge detection and characterization of digitized images

Pattern Analysis and Applications - We present a method for determining which of a large set of pixels are inside or on the boundary of a polygon. The method works much quicker than the standard...     

Introductory programming and young learners with visual disabilities: a review

Universal Access in the Information Society - Computational Thinking (CT) captures the mental processes used to model and solve problems using a computational processes. While often connected to...     

Workload assignment for global real-time scheduling on unrelated clustered platforms

Real-Time Systems - Heterogeneous MPSoCs are being used more and more, from cellphones to critical embedded systems. Most of those systems offer heterogeneous sets of identical cores. In this...