转制国有地矿企业人力资源开发管理问题思考

党的十八大以来，全国各省区地矿局系统转企改制加速推进。“脱胎”于事业体制、诞生于新时代的国有地矿企业，要在激烈的市场竞争中站稳脚跟，需要按企业机制补短板、强弱项，其中，人力资源开发与管理便是一个急需补齐的短板。为做好这方面工作，本文从国有地矿单位历史与现实、当前和未来的视角，在对人力资源开发与管理对地矿企业的重要性和紧迫性、地矿企业人力资源开发与管理存在的主要问题进行分析思考的基础上，提出了必须紧扣企业战略目标抓好人力资源规划、围绕留才用才聚才抓好员工职业生涯管理、着眼可持续发展抓好人力资源管理创新，迅速补齐地矿企业人力资源开发与管理短板的建议。     

新入职高校教师课堂教学问题及对策

新入职高校教师课堂教学质量的问题主要集中在对科研重视不够、没有充分发挥学生在教学中的主体地位、教学环节完整性不足、教学重难点不够突出四个方面,从这四方面着手提高质量才能解决问题。     

A genetic algorithm for the uncapacitated single allocation planar hub location problem

Given a set of n interacting points in a network, the hub location problem determines location of the hubs (transfer points) and assigns spokes (origin and destination points) to hubs so as to minimize the total transportation cost. In this study, we deal with the uncapacitated single allocation planar hub location problem (PHLP). In this problem, all flow between pairs of spokes goes through hubs, capacities of hubs are infinite, they can be located anywhere on the plane and are fully connected, and each spoke must be assigned to only one hub. We propose a mathematical formulation and a genetic algorithm (PHLGA) to solve PHLP in reasonable time. We test PHLGA on simulated and real life data sets. We compare our results with optimal solution and analyze results for special cases of PHLP for which the solution behavior can be predicted. Moreover, PHLGA results for the AP and CAB data set are compared with other heuristics.     

Hybridizing firefly algorithms with a probabilistic neural network for solving classification problems

Classification is one of the important tasks in data mining. The probabilistic neural network (PNN) is a well-known and efficient approach for classification. The objective of the work presented in this paper is to build on this approach to develop an effective method for classification problems that can find high-quality solutions (with respect to classification accuracy) at a high convergence speed. To achieve this objective, we propose a method that hybridizes the firefly algorithm with simulated annealing (denoted as SFA), where simulated annealing is applied to control the randomness step inside the firefly algorithm while optimizing the weights of the standard PNN model. We also extend our work by investigating the effectiveness of using Lévy flight within the firefly algorithm (denoted as LFA) to better explore the search space and by integrating SFA with Lévy flight (denoted as LSFA) in order to improve the performance of the PNN. The algorithms were tested on 11 standard benchmark datasets. Experimental results indicate that the LSFA shows better performance than the SFA and LFA. Moreover, when compared with other algorithms in the literature, the LSFA is able to obtain better results in terms of classification accuracy.     

Environmental economic dispatch in multi-area power system employing improved differential evolution with fuzzy selection

In a deregulated multi-area electrical power system the objective is to determine the most economical generation dispatch strategy that could satisfy the area load demands, the tie-line limits and other operating constraints. Usually, economic dispatch (ED) deals only with the cost minimization, but minimization of emission content has also become an equally important concern due to the mandatory requirement of pollution reduction for environmental protection. Environmental economic dispatch (EED) is a complex multi-objective optimization (MOO) problem with conflicting goals. Normally a fuzzy ranking is employed to rank the large number of Pareto solutions obtained after solving a MOO problem. But in this paper the preference of the decision maker (DM) is used to guide the search and to select the population for the next generation. An improved differential evolution (DE) method is proposed where the selection operation is modified to reduce the complexity of multi-attribute decision making with the help of a fuzzy framework. Solutions are assigned a fuzzy rank on the basis of their level of satisfaction for different objectives before the population selection and then the fuzzy rank is used to select and pass on better solutions to the next generation. A well distributed Pareto-front is obtained which presents a large number of alternate trade-off solutions for the power system operator. A momentum operation is also included to prevent stagnation and to create Pareto diversity. Studies are carried out on three test cases and results obtained are found to be better than some previous literature.     

电厂汽轮机组振动问题分析与解决对策

电厂中的汽轮发电机组在其中所占据的地位极为关键重要。在日常运行中,汽轮机组系统或多或少的存在一定程度的振动问题,此振动问题在一定参数值范围内也是能够允许的。但如果振动问题一旦超过其所允许的范围,则会对整个汽轮机组的工作及电厂的顺利运行带来极为不利的影响。文章首先对电厂汽轮机组振动问题的特点进行了阐述说明,之后结合实例着重对其发生原因及相关的解决对策进行了全面化的分析研究。     

Does cyberbullying overlap with school bullying when taking modality of involvement into account?

Education professionals and researchers are concerned by school bullying and cyberbullying because of its repercussions on students’ health and the school climate. However, only a few studies investigating the impact of school versus cyberbullying have systematically explored whether student victims and perpetrators are involved in school bullying only, cyberbullying only, or both. The aim of the present study was thus to examine the possible overlap, as well as the similarities and/or differences, between these two forms of bullying when taking modality of involvement into account. Individual interviews were conducted with 1422 junior high- and high-school students (girls = 43%, boys = 57%, mean age = 14.3 ± 2.7 years). Results showed that cyberbullying and school bullying overlapped very little. The majority of students involved in cyberbullying were not simultaneously involved in school bullying. Moreover, results indicated that psychosocial problems (psychological distress, social disintegration, general aggression) varied according to the form of bullying. Victims of school bullying had greater internalizing problems than cybervictims, while school bullies were more aggressive than cyberbullies. Given the sizable proportion of adolescents involved in bullying (school and cyber) and its significant relationship with mental health, the issue warrants serious attention from school and public health authorities.     

一种解决非光滑伪凸优化问题的新型神经网络

针对带有不等式约束条件的非光滑伪凸优化问题，提出了一种基于微分包含理论的新型递归神经网络模型，根据目标函数与约束条件设计出随着状态向量变化而变化的罚函数，使得神经网络的状态向量始终朝着可行域方向运动，确保神经网络状态向量可在有限时间内进入可行域，最终收敛到原始优化问题的最优解。最后，用两个仿真实验用来验证神经网络的有效性与准确性。与现有神经网络相比，它是一种新型的神经网络模型，模型结构简单，无需计算精确的罚因子，最重要的是无需可行域有界。     

A discontinuous least-squares finite-element method for second-order elliptic equations

In this paper, a discontinuous least-squares (DLS) finite-element method is introduced. The novelty of this work is twofold, to develop a DLS formulation that works for general polytopal meshes and to provide rigorous error analysis for it. This new method provides accurate approximations for both the primal and the flux variables. We obtain optimal-order error estimates for both the primal and the flux variables. Numerical examples are tested for polynomials up to degree 4 on non-triangular meshes, i.e. on rectangular and hexagonal meshes.