Image super-resolution based on multi-space sparse representation

Sparse representation provides a new method of generating a super-resolution image from a single low resolution input image. An over-complete base for sparse representation is an essential part of such methods. However, discovering the over-complete base with efficient representation from a large amount of image patches is a difficult problem. In this paper, we propose a super-resolution construction based on multi-space sparse representation to efficiently solve the problem. In the representation, image patches are decomposed into a structure component and a texture component represented by the over-complete bases of their own spaces so that their high-level features can be captured by the bases. In the implementation, a prior knowledge about low resolution images generation is combined to the typical base construction for high construction quality. Experiment results demonstrate that the proposed method significantly improves the PSNR, SSIM and visual quality of reconstructed high-resolution image.     

Know by a handful the whole sack: efficient sampling for top-k influential user identification in large graphs

Influence Maximization aims to find the top-K influential individuals to maximize the influence spread within a social network, which remains an important yet challenging problem. Most existing greedy algorithms mainly focus on computing the exact influence spread, leading to low computational efficiency and limiting their application to real-world social networks. While in this paper we show that through supervised sampling, we can efficiently estimate the influence spread at only negligible cost of precision, thus significantly reducing the execution time. Motivated by this, we propose ESMCE, a power-law exponent supervised Monte Carlo estimation method. In particular, ESMCE exploits the power-law exponent of the social network to guide the sampling, and employs multiple iterative steps to guarantee the estimation accuracy. Moreover, ESMCE shows excellent scalability and well suits large-scale social networks. Extensive experiments on six real-world social networks demonstrate that, compared with state-of-the-art greedy algorithms, ESMCE is able to achieve almost two orders of magnitude speedup in execution time with only negligible error (2.21 % on average) in influence spread.     

管材超声波分层缺陷检测中盲区的构成探析

管材超声波分层检测作为控制产品质量的关键步骤,必须引起相关从业人员的重视,特别是要重点分析分层缺陷检测中盲区的构成原因和分布特征。只有这样,才能切实保证检测结果的准确性,更好地控制管材质量。通过对超声波分层缺陷检测的重要性进行阐释,分析了其中盲区的构成和分布等问题。     

壳聚糖固定化脲酶生物传感器选择性测定铜离子

基于重金属对脲酶的抑制作用,研制了用于测定铜离子的生物传感器。该生物传感器的制备以壳聚糖为载体,将脲酶固定于pH电极表面。由于壳聚糖对Cu2+的富集,该生物传感器展现出高灵敏度。在样品溶液中加入5 mmol/L NaI,可以消除Hg2+和Ag+的干扰,从而实现Cu2+的选择性检测。在0.005～0.5μg/mL的浓度范围内,脲酶活性的抑制率与Cu2+浓度的对数呈良好的线性响应关系,其检出限为0.002μg/mL。将使用后的生物传感器浸泡于0.5 mmol/L的EDTA溶液再生5 min,被Cu2+抑制的脲酶的活性可以得到恢复。     

Photoelectric conversion of photosynthetic reaction center in multilayered films fabricated by layer-by-layer assembly

Multilayered protein films which contained ordered layers of photosynthetic reaction center (RC) from Rhodobacter Sphaeroides (RS601) were assembled by means of alternate electrostatic adsorption with positively charged poly(diallyldimethylammonium chloride) (PDDA). The assembly of RC was monitored by spectrometry and photocurrent measurement. Linear film growth was observed up to about 20 cycles of adsorption. For the monolayer film, the photocurrent was about 8.5 nA cm⁻². For the multilayered film, the total photocurrent was about 77 nA cm⁻² for the 24-layer RC film, while the average photocurrent increment per adsorption cycle was about 3.2 nA cm⁻². The overall light-to-electricity conversion efficiency for a 24-layer film was about eight times higher than that for the monolayer one. The effects of electrode potential and pH on the photocurrent were also measured to illustrate the light-to-electric converting mechanism.     

Coordination between strategic forest management and tactical logistic and production planning in the forestry supply chain

In this paper, we study the coordination mechanism in the forestry supply chain between strategic forest management and tactical production planning. We first formulate an integrated model to establish a theoretical benchmark for performance of the entire supply chain. It is a mixed integer programming model that involves harvesting, bucking, transportation, production, and sales decisions for both tactical and strategic planning levels. We then present two sequential approaches S‐A and S‐B where the coordination is done through internal pricing. S‐A is the approach currently used in practice where harvesting in the forest is the main driver of the supply chain activities and internal pricing is introduced to control bucking decision in a separate stage. In contrast, S‐B takes downstream demand information into consideration and internal pricing directly influences harvesting decision in the first stage. In order to find the appropriate setting of internal pricing that leads to the system optimum, we suggest two heuristics H‐I and H‐II. The internal pricing in H‐I is based on dual values and in H‐II, it is derived from a Lagrangian decomposition. A real‐life case study in the Chilean forestry industry is used to compare the results of different approaches. It is shown that the new sequential approach S‐B generates as good feasible solution as that obtained from the integrated approach but in much less time. Both heuristics H‐I and H‐II bring about near‐optimal feasible solutions. H‐II also provides optimistic bound of the optimal objective function value, which can be used as a measure of the solution quality.     

数据加密技术在计算机安全中的应用

随着计算机网络技术的不断发展,计算机互联网在人们的生活中应用越来越广泛,网络安全问题也随之而来。目前的计算机安全存在着诸多因素的威胁,研究人员也在致力于这方面的研究与发展,应用先进的技术来保证计算机安全,为计算机用户的信息安全提供更高的保障。本文将针对计算机安全问题进行分析,探讨数据加密技术在计算机安全中的应用。     

Companion robots for older adults: Rodgers’ evolutionary concept analysis approach

Intelligent Service Robotics - This study aims to analyze the concept of companion robots for older adults from the perspective of nursing. This study employed a concept analysis. The literature...