建设项目取水许可延续取水水量评估的案例分析

建设项目取水许可延续是取水许可管理的重要环节,是落实最严格水资源管理制度的重要抓手.通过对新余水务集团延续取水申请用水合理性评估的案例分析,真实反映工程在实际运行过程中的用水水平、实际取水水量与许可水量的差距,为水行政主管部门复核落实取水许可量以及是否进行延续取水换发证提供科学依据.     

流域一体化下的生态文明先行示范区建设探索

以抚仙湖流域为研究区域,通过系统收集分析流域多年水量水质监测数据,诊断流域保护与发展面临的主要矛盾,并基于流域一体化管理思想,提出了流域保护与发展的可能路径:1创新抚仙湖流域生态文明示范区行政管理体制,从发展思路确立抚仙湖流域实施"严格环境保护、创新生态发展"的转型战略,真正树立和实现"大景区"环境保护和"大旅游"产业发展的生态文明建设理念;2在全面实现生态发展战略的前提下,建议将流域实施分区管控,调减农业用地面积,积极发展现代观光农业和旅游业;3通过生态搬迁,优化城乡布局,实施抚仙湖流域全域"大旅游景区"战略,实现生态资源-资产-资本的良性转化。     

高聚物分子定量构效关系的研究与进展

综述了国内外研究高聚物分子定量构效关系(QSAR)的发展;介绍了研究分子定量构效的3种数学模型的统计方法:逐步多元回归分析法、人工神经网法和偏最小二乘法;重点介绍了多维定量构效关系,同时简要介绍了分子等值面图以及QSAR/QSPR在研究表面活性剂中的应用;最后展望了分子构效的应用前景。     

强化石油企业财务管理的对策探讨

议论石油企业经济管理上存在的不足,对加强管理的措施提出了建设性建议.     

Knowledge transfer in IT offshoring relationships: the roles of social capital,efficacy and outcome expectations

Information technology (IT) development in global organisations relies heavily on the transfer of tacit and complex knowledge from onshore units to offshore subsidiaries. A central concern of such organisations is the development of social capital, which is known to facilitate the smooth transfer of knowledge. However, only a few studies in IS research have explicitly examined the role of social capital for knowledge transfer in an IT offshoring context. In this paper, we argue that such knowledge transfer mechanisms can be understood better by considering social capital in concert with knowledge senders' efficacy and outcome expectations, two of the potentially key motivational drivers of knowledge transfer. We develop our arguments through a qualitative case study of a large German multinational company. German IT developers in this firm provided in‐depth accounts of their experience with offshore colleagues in an Indian captive subsidiary unit. Drawing on our analysis, we develop a model that depicts the influence of social capital, efficacy and outcome expectations on onshore IT developers' ability and willingness to transfer knowledge to offshore colleagues. Through the model, we also explain how social capital, efficacy and outcome expectations are interrelated and generate three interlocked, self‐reinforcing circles of knowledge transfer success in IT offshoring relationships.     

A comprehensive approach to evaluating watershed models for predicting river flow regimes critical to downstream ecosystem services

Selection of strategies that help reduce riverine inputs requires numerical models that accurately quantify hydrologic processes. While numerous models exist, information on how to evaluate and select the most robust models is limited. Toward this end, we developed a comprehensive approach that helps evaluate watershed models in their ability to simulate flow regimes critical to downstream ecosystem services. We demonstrated the method using the Soil and Water Assessment Tool (SWAT), the Hydrological Simulation Program–FORTRAN (HSPF) model, and Distributed Large Basin Runoff Model (DLBRM) applied to the Maumee River Basin (USA). The approach helped in identifying that each model simulated flows within acceptable ranges. However, each was limited in its ability to simulate flows triggered by extreme weather events, owing to algorithms not being optimized for such events and mismatched physiographic watershed conditions. Ultimately, we found HSPF to best predict river flow, whereas SWAT offered the most flexibility for evaluating agricultural management practices.     

Challenges in real-time virtualization and predictable cloud computing

Cloud computing and virtualization technology have revolutionized general-purpose computing applications in the past decade. The cloud paradigm offers advantages through reduction of operation costs, server consolidation, flexible system configuration and elastic resource provisioning. However, despite the success of cloud computing for general-purpose computing, existing cloud computing and virtualization technology face tremendous challenges in supporting emerging soft real-time applications such as online video streaming, cloud-based gaming, and telecommunication management. These applications demand real-time performance in open, shared and virtualized computing environments. This paper identifies the technical challenges in supporting real-time applications in the cloud, surveys recent advancement in real-time virtualization and cloud computing technology, and offers research directions to enable cloud-based real-time applications in the future.     

MORM: A Multi-objective Optimized Replication Management strategy for cloud storage cluster

Effective data management is an important issue for a large-scale distributed environment such as data cloud. This can be achieved by using file replication, which efficiently reduces file service time and access latency, increases file availability and improves system load balancing. However, replication entails various costs such as storage and energy consumption for holding replicas. This article proposes a multi-objective offline optimization approach for replica management, in which we view the various factors influencing replication decisions such as mean file unavailability, mean service time, load variance, energy consumption and mean access latency as five objectives. It makes decisions of replication factor and replication layout with an improved artificial immune algorithm that evolves a set of solution candidates through clone, mutation and selection processes. The proposed algorithm named Multi-objective Optimized Replication Management (MORM) seeks the near optimal solutions by balancing the trade-offs among the five optimization objectives. The article reports a series of experiments that show the effectiveness of the MORM. Experimental results conclusively demonstrate that our MORM is energy effective and outperforms default replication management of HDFS (Hadoop Distributed File System) and MOE (Multi-objective Evolutionary) algorithm in terms of performance and load balancing for large-scale cloud storage cluster.     

Using ontology-based text classification to assist Job Hazard Analysis

The dangers of the construction industry due to the risk of fatal hazards, such as falling from extreme heights, being struck by heavy equipment or materials, and the possibility of electrocution, are well known. The concept of Job Hazard Analysis is commonly used to mitigate and control these occupational hazards. This technique analyzes the major tasks in a construction activity, identifies all potential task-related hazards, and suggests safe approaches to reduce or avoid each of these hazards. In this paper, the authors explore the possibility of leveraging existing construction safety resources to assist JHA, aiming to reduce the level of human effort required. Specifically, the authors apply ontology-based text classification (TC) to match safe approaches identified in existing resources with unsafe scenarios. These safe approaches can serve as initial references and enrich the solution space when performing JHA. Various document modification strategies are applied to existing resources in order to achieve superior TC effectiveness. The end result of this research is a construction safety domain ontology and its underlying knowledge base. A user scenario is also discussed to demonstrate how the ontology supports JHA in practice.