Continuous Approximation of Multi Cycle Time for Multi Aisles Automated Storage and Retrieval Systems.

Knowing that, in an automated storage and retrieval system, the travel time of the storage/retrieval machine is an important parameter which affects the whole system performances, several works were dedicated to its evaluation and its modeling, in single, dual and multi command. These models were proposed for different configurations of AS/RS; such as unit load, multi-aisles and Mobile Racks. These models are based mainly on a discrete approach and the analytical expressions represent the system functioning exactly. In this paper we present a general approach for analytical modeling of multi command cycle time by giving particularly the modeling of the Time Between that we will use to model the Dual Cycle time and the Multi Cycle time. This continuous approach with its simplified mathematical expressions aims to make the calculations more easy than the discrete approach and can be generalized for any one deep physical configuration of AS/RSs and later used to make an optimization of the dimensions of such systems. Key words: Multi-aisles automated storage and retrieval systems, analytical modeling, multi-cycle

PDE Based Enhancement of Color Images in RGB Space

International audienceA novel method for color image enhancement is proposed as an extension of scalar diffusion-shock filter coupling model, where noisy and blurred images are denoised and sharpened. The proposed model is based on using single vectors of the gradient magnitude and the second derivatives as a technique to relate different color components of the image. This model can be viewed as a generalization of Bettahar-Stambouli filter to multi-valued images. The proposed algorithm is more efficient than the mentioned filter and some previous works on color image denoising and deblurring without creating false colors

Towards a Robust Thermal-Visible Heterogeneous Face Recognition Approach Based on a Cycle Generative Adversarial Network

Security is a sensitive area that concerns all authorities around the world due to the emerging terrorism phenomenon. Contactless biometric technologies such as face recognition have grown in interest for their capacity to identify probe subjects without any human interaction. Since traditional face recognition systems use visible spectrum sensors, their performances decrease rapidly when some visible imaging phenomena occur, mainly illumination changes. Unlike the visible spectrum, Infrared spectra are invariant to light changes, which makes them an alternative solution for face recognition. However, in infrared, the textural information is lost. We aim, in this paper, to benefit from visible and thermal spectra by proposing a new heterogeneous face recognition approach. This approach includes four scientific contributions. The first one is the annotation of a thermal face database, which has been shared via Github with all the scientific community. The second is the proposition of a multi-sensors face detector model based on the last YOLO v3 architecture, able to detect simultaneously faces captured in visible and thermal images. The third contribution takes up the challenge of modality gap reduction between visible and thermal spectra, by applying a new structure of CycleGAN, called TV-CycleGAN, which aims to synthesize visible-like face images from thermal face images. This new thermal-visible synthesis method includes all extreme poses and facial expressions in color space. To show the efficacy and the robustness of the proposed TV-CycleGAN, experiments have been applied on three challenging benchmark databases, including different real-world scenarios: TUFTS and its aligned version, NVIE and PUJ. The qualitative evaluation shows that our method generates more realistic faces. The quantitative one demonstrates that the proposed TV -CycleGAN gives the best improvement on face recognition rates. Therefore, instead of applying a direct matching from thermal to visible images which allows a recognition rate of 47,06% for TUFTS Database, a proposed TV-CycleGAN ensures accuracy of 57,56% for the same database. It contributes to a rate enhancement of 29,16%, and 15,71% for NVIE and PUJ databases, respectively. It reaches an accuracy enhancement of 18,5% for the aligned TUFTS database. It also outperforms some recent state of the art methods in terms of F1-Score, AUC/EER and other evaluation metrics. Furthermore, it should be mentioned that the obtained visible synthesized face images using TV-CycleGAN method are very promising for thermal facial landmark detection as a fourth contribution of this paper

Influence of Site Parameters on Fourier Amplification Application for 1D Linear Viscoelastic Method

We focus on the effect of site parameters, also called site proxies, on the variation of the amplification factor. This latter, named Fourier Amplification Factor (FAF) is defined as the ratio of the Fourier transform of the seismic motion at surface and at bedrock. For this study, the wave propagation theory is used limited to 1D linear viscoelastic domain. At this effect, a set of FAF, is established for a set of 858 real profiles. From there, the site parameters are also derived, it is necessary to mention that the FAF can be computed in independent manner of seismic signals which it is applicable only on linear domain.In Nuclear Power Industry application, the FAF is mostly used and can be approximated by limited number of site proxies. As the usual code practice implies a lower number of site proxies (generally 1, sometimes 2) as UBC97 or EC8, a sensitivity analysis is conducted to identify the "best performing" site parameters. The results show that by far, using the six site proxies lead to a better prediction of FAF. However if we have to use one single site parameter, results show that the best one is the overall resonance frequency (f0). In the case when we intend to use two site parameters built from the average shear wave velocity over the upper 30 m (Vs30) and the resonance frequency (f0) which are preferred and give an important variance reduction superior than 61%. In the result, a new formula has been established

Future Sustainable Water and Energy Policy for Algeria

This paper summarises the findings of many studies and surveys in the water and energy sectors in order to make recommendations for water and energy policies in Algeria. We provide an overview of current policy concerning water, energy, and climate change. We investigate the impact of the water-energy nexus on current policy developments. We made specific proposals to aid in the integration of water and energy policies in Algeria. This study demonstrates how, in the absence of integrated policies, the inextricable historical linkages between water and electricity have given rise to spurious trade-offs between water and energy. Drought and climate change are projected to increase demand for electricity, and water sector adaptation strategies have the potential to contribute to climate change by encouraging investment in energy-intensive technologies such as desalination and enhanced wastewater treatment. The findings indicate that demand management programmes and water pricing regulations that lower water and energy intensity in important industries are likely to benefit Algeria's whole economy and environment. The findings are equally applicable to other countries confronted with the burden of developing appropriate strategies to manage their water and energy issues

Characterization of greater middle eastern genetic variation for enhanced disease gene discovery

The Greater Middle East (GME) has been a central hub of human migration and population admixture. The tradition of consanguinity, variably practiced in the Persian Gulf region, North Africa, and Central Asia1-3, has resulted in an elevated burden of recessive disease4. Here we generated a whole-exome GME variome from 1,111 unrelated subjects. We detected substantial diversity and admixture in continental and subregional populations, corresponding to several ancient founder populations with little evidence of bottlenecks. Measured consanguinity rates were an order of magnitude above those in other sampled populations, and the GME population exhibited an increased burden of runs of homozygosity (ROHs) but showed no evidence for reduced burden of deleterious variation due to classically theorized ‘genetic purging’. Applying this database to unsolved recessive conditions in the GME population reduced the number of potential disease-causing variants by four- to sevenfold. These results show variegated genetic architecture in GME populations and support future human genetic discoveries in Mendelian and population genetics

Integration of the environmental management aspect in the optimization of the design and planning of energy systems

The increasing concerns regarding the environmental pollution derived from anthropogenic activities, such as the use of fossil fuels for power generation, has driven many interested parties to seek different alternatives, e.g. use of renewable energy sources, use of “cleaner” fuels and use of more effective technologies, in order to minimize and control the quantity of emissions that are produced during the life cycle of conventional energy sources. In addition to these alternatives, the use of an integrated procedure in which the environmental aspect will be taken into account during the design and planning of energy systems could provide a basis on which emissions reduction will be dealt with a life cycle approach. The work presented in this paper focuses on the examination of the possibilities of integrating the environmental aspects in the preliminary phase of the conventional design and planning of energy systems in conjunction with other parameters, such as financial cost, availability, capacity, location, etc. The integration of the environmental parameter to the design is carried out within a context where Eco-design concepts are applied. Due to the multi-parameter nature of the design procedure, the tools that are used are Life Cycle Analysis and Multi-criteria Analysis. The proposed optimization model examines and identifies optimum available options of the use of different energy sources and technologies for the production of electricity and/or heat by minimizing both the financial cost and the environmental impacts, with regard to a multiple objective optimization subject to a set of specific constraints. Implementation of the proposed model in the form of a case study for the island of Rhodes in Greece revealed that an optimized solution both cost and environmental-wise, would be an almost balanced participation of renewables and non-renewable energy sources in the energy mix