Two-stage stochastic minimum cost consensus models with asymmetric adjustment costs

When dealing with consensus cost problems with asymmetric adjustment costs, the uncertain scenarios with certain probabilities which are becoming a serious problem decision-makers have to face. However, existing optimization-based consensus models have failed to consider uncertain factors that could influence the final consensus and total consensus cost. In order to better deal with these issues, it is necessary to develop practical consensus optimal models. Thus, we establish three two-stage stochastic minimum cost consensus models with asymmetric adjustment costs that may eventually lead the way to better consensus outcomes. The impact of uncertain parameters (such as individual opinions, unit asymmetric adjustment costs, compromise limits, cost-free thresholds) are investigated by modeling three kinds of uncertain consensus models. We solve the proposed two-stage stochastic consensus problem iteratively using the L-shaped algorithm and show the convergence of the algorithm. Furthermore, a case of pollution control negotiations verifies the practicability of the proposed models. Moreover, the comparison of results with the L-shaped algorithm and CPLEX shows that the L-shaped algorithm is more effective in solving time. Some discussions and comparisons on local and global sensitivity analysis of the uncertain parameters are presented to reveal the features of the proposed models. Finally, the relationships between the minimum cost consensus model and minimum cost consensus models with asymmetric adjustment costs and the proposed models are also provided.     

Banding formation and eutectic lamellar growth in directional solidified Ni50Al20Fe30 alloy

Banding formation and eutectic lamellar growth in a directionally solidified Ni₅₀Al₂₀Fe₃₀ alloy were investigated. It was found that the banding area consists of two layers. The first layer is a γ layer, while the subsequent one is a γ layer. The composition of various phases around the banding area changes with the solidification process. The banding is formed by two steps process and caused by factors such as the fractions during the sample growth process. It was found that the band was found at relatively low growth rate. Therefore. this study indicates that increasing the growth rate is an effective method to eliminate the band formation. Eutectic lamellae nucleate and grow again after the banding formation. During the initial transition lamellar growth, the relationship between the square lamellar spacing, γ₂, and the distance from, the banding, d, can be described by the following equation: γ₂ = K [1-exp(A.d)] where K and A are constant.     

一种基于目标圆的有向强栅栏构建算法

K-栅栏覆盖是有向传感器网络覆盖控制的研究热点之一。提出一种基于目标圆的分布式有向强栅栏构建方法（DBCTC）。首次构建了节点目标圆和能耗比2个模型。以节点感知区域内横坐标最大的点为圆心,以感知半径为半径的圆就是目标圆。节点的运动能耗和栅栏增益的比值就是能耗比。前一个节点根据目标圆模型选择后一个节点的最佳目标位置。从附近移动节点中选择能耗比最少的移动节点构建有向强栅栏。仿真结果证明,该栅栏构建方法比其他算法降低60%左右的能耗。     

Signage Versus Environmental Affordances: Is the Explicit Information Strong Enough to Guide Human Behavior During a Wayfinding Task?

This study aims to explore how people behave when they have to find a location within a complex building and are confronted with situations where directional signage (i.e., explicit information) is in opposition to environmental affordances that naturally direct users towards a specific path, creating a situation with conflicting information (e.g., a brighter corridor vs. a darker corridor but with a directional sign indicating to follow the darker one). A virtual reality–based methodology was used and a between‐subject design was considered. Thus, participants were given the tasks of finding three publicly accessible central points in a virtual hotel and confronted with a two forced‐choice task of local scenes in which environmental variables (i.e., corridor width and brightness) and signage varied systematically, in two experimental conditions (i.e., neutral and signage). For the signage condition, signs were inserted to explicitly point in the opposite direction than that implicitly suggested by the environmental affordances, creating situations with conflicting information. Results indicate that environmental variables were able to direct people indoors acting as environmental affordances. Users preferred to follow the wider and brighter paths. However, when directional signage pointed in the opposite direction of the paths preferred by the participants, most of them complied with signage.     

Interannual vegetation phenology estimates from global AVHRR measurements: Comparison with in situ data and applications

In a previous paper, we described a procedure to correct the directional effects in AVHRR reflectance time series. The corrected measurements show much less high frequency variability than their original counterparts, which makes them suitable to study vegetation dynamics. The time series are used here to estimate the start and ending dates of the growing season for 18 years from 1982 to 1999. We focus on the interannual variations of these phenological parameters.A database of in situ phenology observations is used to quantify the accuracy of the satellite-based estimates. Although based on a limited sampling of the Northern mid and high latitudes, the comparison indicates that i) the satellite phenological product contains meaningful information on interannual onset anomalies; ii) there is a higher degree of consistency over regions covered by Broadleaf Forests, Grasses and cereal Crops than over those covered by Needleleaf Forests or Savannas; and iii) the satellite phenological product is of lower quality in regions with mountainous terrain. In favorable conditions, interannual variations of the onset are captured with an accuracy of a few days.As this satellite-derived product captures the interannual onset variability at ground-truth sites, we confidently use it to larger scales studies. Mapped at a continental scale, the onset anomalies show coherent patterns at the regional (≈ 1000 km) scale for the mid and high latitudes of the Northern hemisphere, which is consistent with a meteorological forcing. In the tropics, there is larger spatial heterogeneity, which suggests more complex controls of the phenology. The relation between vegetation phenology and climate is further investigated over Europe by comparing the variability of the satellite-derived vegetation onset and that of the winter North Atlantic Oscillation index, at a fine spatial scale. The strong correlations observed confirm that this climate forcing parameter explains most of the onset variability over a large fraction of Northern Europe (earlier onsets for positive winter NAO), with lower impact towards the south and opposite effects around the Mediterranean basin. The NAO has a predictive character as the January-February NAO index is strongly correlated with the vegetation onset that occurs around April in Northern Europe.     

基于方向导数的多光谱图像快速融合新算法

针对提升小波变换的特点,研究图像融合规则,提出了一种新的基于方向导数的多分辨多光谱图像快速融合算法。首先,利用提升小波变换得到待融合源图像的多分辨分析;然后以小波域方向导数为判据,在图像的多分辨分析的相应各级上进行融合,得到融合图像的多分辨分析;最后,利用提升小波反变换重构融合图像。使用多光谱图像对算法进行验证并与方向对比度算法进行对比,结果表明,融合图像完好的融合了源图像的信息,且算法运算时间短。     

Priority-based target coverage in directional sensor networks using a genetic algorithm

Sensor networks have been applied in a wide variety of situations. Recently directional sensor networks consisting of directional sensors have gained attention. As for the traditional target coverage problem, the limited sensing angle of directional sensors makes it even more challenging. Moreover, individual targets may also be associated with differentiated priorities. Considering the distance between the directional sensors and targets influences sensing quality, this paper proposes the priority-based target coverage problem and strives to choose a minimum subset of directional sensors that can monitor all targets, satisfying their prescribed priorities. Due to the NP-Complete complexity, the minimum subset of directional sensors is approximated by using a genetic algorithm. Simulation results reveal the effects of multiple factors on the size of the resulting subset.     

Modeling the impact of spectral sensor configurations on the FLD retrieval accuracy of sun-induced chlorophyll fluorescence

Chlorophyll fluorescence is related to photosynthesis and can serve as a remote sensing proxy for estimating photosynthetic energy conversion and carbon uptake. Recent advances in sensor technology allow remote measurements of the sun-induced chlorophyll fluorescence signal (Fs) at leaf and canopy scale. The commonly used Fraunhofer Line Depth (FLD) principle exploits spectrally narrow atmospheric oxygen absorption bands and relates Fs to the difference of the absorption feature depth of a fluorescensing and a non-fluorescensing surface. However, due to the nature of these narrow bands, Fs retrieval results depend not only on vegetation species type or environmental conditions, but also on instrument technology and processing algorithms. Thus, an evaluation of all influencing factors and their separate quantification is required to further improve Fs retrieval and to allow a reproducible interpretation of Fs signals.Here we present a modeling study that isolates and quantifies the impacts of sensor characteristics, such as spectral sampling interval (SSI), spectral resolution (SR), signal to noise ratio (SNR), and spectral shift (SS) on the accuracy of Fs measurements in the oxygen A band centered at 760 nm (O₂-A). Modeled high resolution radiance spectra associated with known Fs were spectrally resampled, taking into consideration the various sensor properties. Fs was retrieved using the three most common FLD retrieval methods, namely the original FLD method (sFLD), the modified FLD (3FLD) and the improved FLD (iFLD). The analysis investigates parameter ranges, which are representative for field and airborne instruments currently used in Fs research (e.g., ASD FieldSpec, OceanOptics HR, AirFLEX, AISA, APEX, CASI, and MERIS).Our results show that the most important parameter affecting the retrieval accuracy is SNR, SR accounts for ≤ 40% of the error, the SSI for ≤ 12%, and SS for ≤ 7% of the error. A trade-off study revealed that high SR can partly compensate for low SNR. There is a strong interrelation between all parameters and the impact of specific parameters can compensate or amplify the influence of others. Hence, the combination of all parameters must be considered by the evaluation of sensors and their potential for Fs retrieval. In general, the standard FLD method strongly overestimates Fs, while 3FLD and iFLD provide a more accurate estimation of Fs. We conclude that technical sensor specifications and the retrieval methods cause a significant variability in retrieved Fs signals. Results are intended to be one relevant component of the total uncertainty budget of Fs retrieval and have to be considered in the interpretation of retrieved Fs signals.     

Directional neighbor discovery in 60 GHz indoor wireless networks

Signal propagation in the 60 GHz band significantly differs from that in the 2.4 and 5 GHz bands. In particular, the signals are often reflected in indoor settings in this band. Directional antennas can help limit the impact of reflection, but make the process of neighbor discovery complex. We consider this problem in this paper. We examine two approaches (a) direct discovery where each node explicitly discovers its neighbors, and (b) gossip-based discovery where nodes exchange information about their already discovered neighbors. We analyze the two approaches and validate our models via simulations. We examine the impact of system parameters such as varying beamwidth and node density.     

Frequency domain regularization of d-dimensional structure tensor-based directional fields

The present work is intended to address two of the major difficulties that can be found when tackling the estimation of the local orientation of the data in a scene, a task which is usually accomplished by means of the computation of the structure tensor-based directional field. On one hand, the orientation information only exists in the non-homogeneous regions of the dataset, while it is zero in the areas where the gradient (i.e. the first-order intensity variation) remains constant. Due to this lack of information, there are many cases in which the overall shape of the represented objects cannot be precisely inferred from the directional field. On the other hand, the orientation estimation is highly dependent on the particular choice of the averaging window used for its computation (since a collection of neighboring gradient vectors is needed to obtain a dominant orientation), typically resulting in vector fields which vary from very irregular (thus yielding a noisy estimation) to very uniform (but at the expense of a loss of angular resolution). The proposed solution to both drawbacks is the regularization of the directional field; this process extends smoothly the previously computed vectors to the whole dataset while preserving the angular information of relevant structures. With this purpose, the paper introduces a suitable mathematical framework and deals with the d-dimensional variational formulation which is derived from it. The proposed formulation is finally translated into the frequency domain in order to obtain an increase of insight on the regularization problem, which can be understood as a low-pass filtering of the directional field. The frequency domain point of view also allows for an efficient implementation of the resulting iterative algorithm. Simulation experiments involving datasets of different dimensionality prove the validity of the theoretical approach.