Headspace fingerprinting approach to identify the major pathway influencing volatile patterns of vinasse-cured duck processed by high pressure,as well as its impact on physicochemical and sensory attributes

As a decisive attribute, flavour could be influenced by HP treatments through multiple physical and chemical pathways within the high pressure (HP)-assisted meat curing process. This investigation aimed to identify the major pathway influencing volatile flavour patterns of two representative vinasse-cured duck (VCD) products with HP treatments (150–300 MPa/15 min), including wet and dry types, by employing headspace fingerprinting as an untargeted approach. Results suggested that HP treatments greatly lowered moisture contents and increased Warner-Bratzler shear force and thiobarbituric acid reactive substances of the cured samples. According to multivariate models, the volatile flavour patterns of the HP-processed VCD could be clearly separated from the unprocessed samples, but the VCD pressurised at different intensities represented similar volatile fingerprinting, which was validated by e-nose analysis. The discriminant analysis (OPLS-DA) model outlined vinasse-derived ethanol, acetic acid, 3-methyl-1-butanol, 2-methyl-1-butanol, phenethyl alcohol and 2-methyl-3-octanone as the major discriminant aromas across the unpressurised and pressurised samples.     

融合创意产业的民族手工艺品发展策略

文章首先介绍湖南、贵州等地少数民族手工艺产品的当代状况,并从传统工艺的文化的传承和资本的流动的角度进行了分析。之后,文章简介了台湾省内对于创意产业的发展的部分经验,总结融合创意产业发展少数民族手工艺产品的发展策略。     

Improvement of constructive heuristics using variable neighbourhood descent for scheduling a flow shop with sequence dependent setup time

This paper deals with the problem of scheduling a flow shop operating in a sequence dependent setup time environment. The objective is to determine the sequence that minimises the makespan. Two efficient neighbourhood search-based heuristics have been developed and tested using 960 problems, and the results obtained reveal their usefulness. The algorithms make use of two existing constructive heuristics. A neighbourhood search known as variable neighbourhood descent is used to improve the two constructive heuristics. Experimentation is carried out on the 96 groups of problems with 10 problem instances in each group. Performance analysis is carried out using the relative performance improvement of each heuristic. The analysis shows a consistently better performance of the neighbourhood-based improvement heuristics. A paired comparison test is used for validating the superiority of the proposed heuristics. The statistical analysis reveals that the performance of the neighbourhood-based heuristics is very much dependent on the initial constructive heuristics used.     

一种结合共享最近邻法和粒度支持向量机的混合模型

粒度支持向量机GSVM(Granular Support Vector Machine)在处理大规模数据集时,粒的划分对其模型的训练效能、泛化能力等有很大的影响。然而传统划分方法的随机性,严重影响着其模型的训练效果。针对这个问题提出一种结合共享最近邻法和粒度支持向量机的混合模型(GSVM-SNN)。利用共享最近邻法将样本点自动划分成若干个信息粒,从中提取出关键信息。由于支持向量点大都分布在信息粒的边缘,提出一种KNN连通度,通过计算连通度提取纯粒边缘点并融合关键信息建立最终决策模型。实验结果表明,与传统的GSVM相比,该方法在分类时间、分类准确率上都有一定的优越性。     

Energy-efficient communication in wireless cable sensor networks

In this paper, we introduce a new type of sensor: cable sensor. Unlike traditional point sensors, this type of sensor has a rectangular sensing region with a processor installed on it to do processing and communication. The wireless network formed by this kind of sensor is called wireless cable sensor network (WCSN). We study energy-efficient communication algorithms in WCSNs. We address it in two ways: one is through reducing the total transmission power of processors while maintaining the connectivity of the network and the other is through scheduling cable sensors to let them take turns to go to sleep without affecting the coverage and connectivity of the network. In the first approach, we initially develop a distributed algorithm called DTRNG based on the relative neighbourhood graph. Later we enhance it to Algorithm determine the transmission power by removing the largest edge in CYCles (DTCYC). Mathematical proofs show that Algorithm DTCYC provides an optimal solution that can not only minimise the total processor transmission power but maintain the connectivity of the network as well. In the second approach, we propose a cable mode transition algorithm which determines the minimum number of active sensors to maintain K-coverage as well as K-connectivity required by the application. We discuss the relationship between coverage and connectivity and prove the theorems that lay the foundation for our algorithm. Simulation results demonstrate that our algorithm is efficient in saving energy.     

民族地区高校计算机教学体系的改革与探讨

针对民族地区高等院校计算机教育的特点与面临的困难,提出相应的解决对策和改革方向。探讨如何构建现代人才素质需求与地方民族特色相结合的计算机教学体系,从而促进民族地区计算机人才的培养。     

A two-phase variable neighbourhood search algorithm for assembly line worker assignment and balancing problem type-II: an industrial case study

The assembly line worker assignment and balancing problem type-II (ALWABP-2) occurs when workers and tasks (where task times depend on workers’ skills) are to be simultaneously assigned to a fixed number of workstations with the goal of minimising the cycle time. In this study, a two-phase variable neighbourhood search (VNS) algorithm is proposed to solve the ALWABP-2 due to the NP-hard nature of this problem. In the first phase of the algorithm, a VNS approach is applied to assign tasks to workstations with the aim of minimising the cycle time while in the second phase, a variable neighbourhood descent method is applied to assign workers to workstations. The performance of the proposed algorithm is tested on well-known benchmark instances. In addition, the proposed algorithm has been used to solve a real case study from a consumer electronics company that manufactures LCD TVs. The results show that the algorithm is superior to the methods reported in the literature in terms of its higher efficiency and robustness. Furthermore, the algorithm is easy to implement and significantly improves the performance of the final assembly line for the investigated LCD TV real case study.     

抗干扰的运动目标检测算法

针对改进族群进化算法(EGEA)中对族群模式的有效采样问题,提出以竞争指数为选择指标的常规选择、以族群为选择单位的常规选择以及基于竞争指数的模拟退火排序选择3种选择机制,并通过多维函数优化问题进行实验分析,结果表明3种选择机制都能够在一定程度上提高EGEA的搜索效率,且基于竞争指数的模拟退火排序选择算子的实现更简便,对EGEA综合性能的提高也更明显。     

Lower and upper bounds for the two-echelon capacitated location-routing problem

In this paper, we introduce two algorithms to address the two-echelon capacitated location-routing problem (2E-CLRP). We introduce a branch-and-cut algorithm based on the solution of a new two-index vehicle-flow formulation, which is strengthened with several families of valid inequalities. We also propose an adaptive large-neighbourhood search (ALNS) meta-heuristic with the objective of finding good-quality solutions quickly. The computational results on a large set of instances from the literature show that the ALNS outperforms existing heuristics. Furthermore, the branch-and-cut method provides tight lower bounds and is able to solve small- and medium-size instances to optimality within reasonable computing times.     

一种保边缘的图像去噪方法

提出一种保边缘的去噪方法。该方法利用4个方向核卷积检测图像中的噪声点和非噪声点,对非噪声点不进行处理。在噪声点的3×3邻域中选择距离最小的非噪声点,若无非噪声点则邻域扩大为5×5,若有非噪声点则用这些点的中值替换噪声点,否则用邻域中距离最远像素点的均值替换噪声点。实验结果表明,该方法不仅能有效去除图像的噪声,且能较好地保护图像边缘。