哈代诗歌中人与自然合二为一的艺术表现形式

英国诗人哈代在其诗歌中用细腻温婉的笔触描绘了尘世中的种种真情 ,表现出对大自然的无限敬意 ;人与自然融为一体成为其诗歌的精神支柱和情感升华的象征。     

全球经济萧条与生产据点向中国的转移--21世纪亚洲工业化的新阶段

20世纪后期是亚洲工业化第一阶段,中国经济迅速发展,成为世界经济增长中心.外国资本纷纷投入中国市场,中国国内改革进入新的阶段.这对形成中国在内的亚洲经济圈,进入亚洲工业化第二阶段是至关重要的.     

多媒体计算机实践教学网络机房的维护技术

本文详细介绍了当前高校多媒体计算机实践教学网络机房常用的几种技术雏护手段,包括硬盘写保护技术、“克隆“技术、网络技术、注册表技术等并结合实际维护工作进行了比较分析.     

平面交叉口的安全设计

本文对平面交叉口的类型选择,设计时应考虑的因素,设计过程和设计原则等方面进行了较为详细的阐述,旨在说明如何设计交叉口才能最大限度地保证交通安全,提高通行能力.     

管理信息系统教学刍议

企业管理的发展变化和计算机信息技术的迅猛发展,给管理信息系统的教学提出了更高的要求,要求管理信息系统的教学体系要不断完善、教学内容要不断充实,教学方式要不断改进。从预备知识的重要性、教学内容的更新、强化案例教学、加强实践环节等方面进行探讨,探索出一条真正有效、切实可行的教学改革之路。     

一类非线性规划问题的等价性证明

给出了非线性规划问题中目标函数单调变换前后的一个等价性证明.     

Research on consistency measurement and weight estimation approach of hybrid uncertain comparison matrix

The consistency measurement and weight estimation approach of the hybrid uncertain comparison matrix in the analytic hierarchy process （AHP） are studied. First, the decision-making satisfaction membership function is defined based on the decision making＇s allowable error. Then, the weight model based on the maximal satisfactory consistency idea is suggested, and the consistency index is put forward. Moreover, the weight distributing value model is developed to solve the decision making misleading problem since the multioptimization solutions in the former model. Finally, the weights are ranked based on the possibility degree approach to obtain the ultimate order.     

一种基于段的基音检测算法

作为语音信号处理领域一项基本、关键的技术,基音检测在语音信号处理中扮演着重要的角色,一直是语音信号处理的一个研究热点.首先对传统的基于短时自相关函数法的基音检测进行了研究;在此基础上提出了一种能同时检测一段语音信号基音周期的方法,有效地克服了传统基音检测算法只能检测一帧语音信号基音的缺点.进行了实验仿真,结果表明通过去野点,中值平滑等后处理的基于段的基音检测算法比传统的基于帧的基音检测算法具有更好的抗噪性.     

改善20CrMnTiH淬透性的研究

莱钢特钢厂20CrMnTiH钢材成分波动较大,淬透性带HRC8～10,范围较大,制约了齿轮钢质量的进一步提高.通过研究,发现铸坯中心偏析尤其是碳偏析为主要问题.通过工艺优化采取各项措施,尤其增加电磁搅拌后,中心碳偏析得到明显改善;C控制在0.19%～0.20%的炉次达到了95.6%;淬透性带控制在HRC6内的达到了92.1%;在HRC4内的达到了86.2%;提高了产品质量,满足了用户需求.     

Finding finer functions for partially characterized proteins by protein-protein interaction networks

Based on high-throughput data, numerous algorithms have been designed to find functions of novel proteins. However, the effectiveness of such algorithms is currently limited by some fundamental factors, including (1) the low a-priori probability of novel proteins participating in a detailed function; (2) the huge false data present in high-throughput datasets; (3) the incomplete data coverage of functional classes; (4) the abundant but heterogeneous negative samples for training the algorithms; and (5) the lack of detailed functional knowledge for training algorithms. Here, for partially characterized proteins, we suggest an approach to finding their finer functions based on protein interaction sub-networks or gene expression patterns, defined in function-specific subspaces. The proposed approach can lessen the above-mentioned problems by properly defining the prediction range and functionally filtering the noisy data, and thus can efficiently find proteins’ novel functions. For thousands of yeast and human proteins partially characterized, it is able to reliably find their finer functions (e.g., the translational functions) with more than 90% precision. The predicted finer functions are highly valuable both for guiding the follow-up wet-lab validation and for providing the necessary data for training algorithms to learn other proteins.