Facility location with double-peaked preferences

We study the problem of locating a single facility on a real line based on the reports of self-interested agents, when agents have double-peaked preferences, with the peaks being on opposite sides of their locations. We observe that double-peaked preferences capture real-life scenarios and thus complement the well-studied notion of single-peaked preferences. As a motivating example, assume that the government plans to build a primary school along a street; an agent with single-peaked preferences would prefer having the school built exactly next to her house. However, while that would make it very easy for her children to go to school, it would also introduce several problems, such as noise or parking congestion in the morning. A 5-min walking distance would be sufficiently far for such problems to no longer be much of a factor and at the same time sufficiently close for the school to be easily accessible by the children on foot. There are two positions (symmetrically) in each direction and those would be the agent’s two peaks of her double-peaked preference. Motivated by natural scenarios like the one described above, we mainly focus on the case where peaks are equidistant from the agents’ locations and discuss how our results extend to more general settings. We show that most of the results for single-peaked preferences do not directly apply to this setting, which makes the problem more challenging. As our main contribution, we present a simple truthful-in-expectation mechanism that achieves an approximation ratio of \(1+b/c\) for both the social and the maximum cost, where b is the distance of the agent from the peak and c is the minimum cost of an agent. For the latter case, we provide a 3 / 2 lower bound on the approximation ratio of any truthful-in-expectation mechanism. We also study deterministic mechanisms under some natural conditions, proving lower bounds and approximation guarantees. We prove that among a large class of reasonable strategyproof mechanisms, there is no deterministic mechanism that outperforms our truthful-in-expectation mechanism. In order to obtain this result, we first characterize mechanisms for two agents that satisfy two simple properties; we use the same characterization to prove that no mechanism in this class can be group-strategyproof.     

Band depth analysis of CHRIS/PROBA data for the study of a Mediterranean natural ecosystem. Correlations with leaf optical properties and ecophysiological parameters

The absorption feature approach was used in CHRIS multiangular hyperspectral data in order to investigate its potential for ecosystem remote sensing. For that purpose, CHRIS images in mode 1 were acquired throughout a two-year period for a Mediterranean ecosystem dominated by the semi-deciduous shrub Phlomis fruticosa. During each acquisition, coincident in situ Leaf spectra and ecophysiological measurements (Leaf Area Index, leaf pigment content and leaf water potential) were conducted. After data preprocessing, absorption feature information was calculated for both CHRIS and Leaf spectra for the whole spectrum. Three common characteristic absorption features within the spectral areas 450-550 nm, 550-750 nm and 900-1000 nm were detected. Each spectral area was then examined separately and four characteristic parameters were calculated that described the pattern, magnitude and position of the maximum absorption. Correlations between CHRIS and Leaf spectra for each date and viewing angle (VA) were then conducted. All correlations, either on full continuum removed spectra or on spectral areas, showed high coefficients of determination, especially (i) in higher observation angles (VA + 55), (ii) during the wet season and (iii) in strong absorptions such as the “red absorption”. Subsequently, correlations between CHRIS and Leaf absorption parameters of selected spectral areas with field-measured ecophysiological parameters were examined. Ecophysiological parameters proved to be highly correlated to CHRIS and Leaf absorption parameters in magnitude and/or pattern of the absorption feature and less in wavelength of the maximum absorption. CHRIS VAs +/− 36 showed the highest correlations although the type of relation, linear or nonlinear, was not conclusive. Finally, a first comparison between narrowband spectral indices and absorption features in correlations with ecophysiological parameters showed that both methods provide significant and comparable results, with oblique angles showing best performance. However, ecophysiological parameters are generally better predicted linearly by narrowband spectral indices issued from CHRIS, with most significant differences appearing on pigments absorbing mainly within 450-550 nm.     

Environmental assessment of brick production in Greece

Brick constitutes one of the major materials used for the construction of buildings. The present study analyses the different stages followed during brick production and the materials and energy used in each stage. The purpose is to identify ‘hot-spots’, i.e. parts of the life cycle that are important to the total environmental impact. The analysis is performed using life cycle assessment (LCA) methodology, which is a method used to identify and quantify the environmental performance of a process or a product from “cradle to grave”. LCA methodology provides a quantitative basis for assessing potential improvements in environmental performance of a system throughout the life cycle. The system investigated includes raw material acquisition, industrial production, packaging and transportation. Energy use and emissions are quantified and the potential environmental effects are assessed. The main energy inputs to the production system are electricity, diesel and solid fuel (Pet-Coke). The environmental burdens that arise from the operation of a brick industry are mainly due to air emissions derived from fossil fuel utilization.     

The boomerang returns? Accounting for the impact of uncertainties on the dynamics of remanufacturing systems

Recent years have witnessed companies abandon traditional open-loop supply chain structures in favour of closed-loop variants, in a bid to mitigate environmental impacts and exploit economic opportunities. Central to the closed-loop paradigm is remanufacturing: the restoration of used products to useful life. While this operational model has huge potential to extend product life-cycles, the collection and recovery processes diminish the effectiveness of existing control mechanisms for open-loop systems. We systematically review the literature in the field of closed-loop supply chain dynamics, which explores the time-varying interactions of material and information flows in the different elements of remanufacturing supply chains. We supplement this with further reviews of what we call the three ‘pillars’ of such systems, i.e. forecasting, collection, and inventory and production control. This provides us with an interdisciplinary lens to investigate how a ‘boomerang’ effect (i.e. sale, consumption, and return processes) impacts on the behaviour of the closed-loop system and to understand how it can be controlled. To facilitate this, we contrast closed-loop supply chain dynamics research to the well-developed research in each pillar; explore how different disciplines have accommodated the supply, process, demand, and control uncertainties; and provide insights for future research on the dynamics of remanufacturing systems.     

Group III–V ternary compound semiconductor materials for unipolar conduction in tunnel field-effect transistors

A distinct materials combination is presented for tunnel field-effect transistors (TFETs): gallium arsenide phosphide (GaAsP) as a wider-bandgap material in the drain and channel regions with indium gallium arsenide (InGaAs) as a narrow-bandgap material for the source region. The introduction of this novel materials combination greatly improves the ON-state current, OFF-state current, ambipolar behavior, threshold voltage, and subthreshold slope compared with other group III–V ternary heterojunction TFETs. In GaAsP–InGaAs TFETs, the ambipolar current remains equal to the OFF-state current. This paper explores the potential of the proposed device for ultralow-power high-performance applications.     

A review of occupant control on natural ventilation

According to IPCC (Intergovernmental Panel on Climate Change), the largest use of energy in commercial buildings is space heating in colder climates and air conditioning in hot climates. In Europe, the Directive on the energy performance of buildings EPBD (European Energy Performance of Buildings Directive) [1] provides a framework for national building performance regulations and calculation procedures. However, there are often large discrepancies between calculated and measured energy performance of buildings. One main reason is the behaviour of occupants, which is often not reflected in calculation models.This paper presents a literature review of various parameters influencing the effectiveness of occupant controlled natural ventilation. Additionally possibilities to implement these influences into calculation procedures/building simulation and adaptive thermal comfort evaluation are discussed.     

Bayesian method for multirate data synthesis and model calibration

Data‐driven models are widely used in process industries for monitoring and control purposes. No matter what kind of models one chooses, model‐plant mismatch always exists; it is, therefore, important to implement model update strategies using the latest observation information of the investigated process. In practice, multiple observation sources such as frequent but inaccurate or accurate but infrequent measurements coexist for a same quality variable. In this article, we show how the flexibility of the Bayesian approach can be exploited to account for multiple‐source observations with different degrees of belief. A practical Bayesian fusion formulation with time‐varying variances is proposed to deal with possible abnormal observations. A sequential Monte Carlo sampling based particle filter is used for simultaneously handling systematic and nonsystematic errors (i.e., bias and noise) in the presence of process constraints. The proposed method is illustrated through a simulation example and a data‐driven soft sensor application in an oil sands froth treatment process. © 2010 American Institute of Chemical Engineers AIChE J, 57: 1514–1525, 2011     

Stress relaxation behavior and low cycle fatigue behavior of bulk SAC 305

Bulk Sn_96.5Ag₃Cu_0.5 samples were mechanically tested to investigate the effect of temperature, frequency and applied stress on the low cycle fatigue and stress relaxation behavior and the corresponding microstructure. Samples were tested under a variety of parameters including applied stresses between 8 and 80 MPa, temperatures of 25, 50, 100 and 150 °C and frequencies of 1, 0.1 and 0.01 Hz, respectively. Samples used for the stress relaxation behavior exhibited plastic behavior with increased softening behavior with increased stress levels, increased temperature and lower frequencies. Bayesian analysis revealed that stress relaxation behavior could be expressed in general by the following expression: ?σ = AN ^B In the previous expression, Bayesian analysis showed that the testing frequency has an exponential dependency while the temperature has a power law dependency on the parameters A and b. The results of the low cycle fatigue study showed that life decreased with increased applied stress, decreased frequency and increased temperature. Bayesian analysis revealed that the low cycle fatigue behavior could be described by the following expression: ?σ = G(logN) ^m . Additionally, Bayesian analysis showed that the testing frequency and temperature both have a power law dependency on the parameters G and m.