某高校既有建筑室内人员相关VOCs目标污染物的实测分析

为研究高校既有建筑室内人群散发对室内VOCs的影响，对高校不同人群样本的教室及会议室两类典型人群密集房间，共82个人群样本对象进行了VOCs采样分析，得到不同实际场景下的人员相关的VOCs浓度水平，并对其潜在的影响因素进行分析。结果表明，共确认了29种与室内人员相关的高检出率且较高浓度值的物质，包括芳香族化合物9种，烷烯烃类9种，酮类和醛类8种，醇酯类以及卤化物3种，并得到主要VOCs物质的浓度水平和I/O比。对影响因素的统计分析表明，室内人员密度、季节和房间类型对不同VOCs物质存在显著性影响，其中季节性因素对目标VOCs污染物影响最为广泛，其次是房间类型与室内人员密度。该研究可为进一步了解人员密集室内VOCs污染现状及控制策略提供一定的科学参考。     

因素空间理论下基点分类算法研究

目前，基于因素空间理论的背景基提取算法计算过程复杂，初始化必须依赖各因素极值，基点数量提取冗余等原因，未能在应用中取得很好效果。为此，结合内点判别法和知识可继承、可扩展的思想，提出一种计算简单、初始化独立、基点数量小的改进的背景基提取算法。然后，利用改进的背景基提取算法构造出一种全新的数据分类算法-基点分类算法，基点分类算法以提取每一类样本的背景基为预测模型，再通过新定义的λ-背景基，优化预测模型。数值实验表明:基点分类算法原理简单、构造难度小、分类模型泛化能力强，预测能力准确率高，同时严格的模型限定区域又能为识别新类别提供新方法。     

基于密集神经网络的灰度图像着色算法

针对在灰度图像着色领域中，传统算法信息提取率不高、着色效果不理想的问题，提出了基于密集神经网络的灰度图像着色算法，以实现改善着色效果，让人眼更好地观察图片信息的目的。利用密集神经网络的信息提取高效性，构建并训练了一个端到端的深度学习模型，对图像中的各类信息及特征进行提取。训练网络时与原图像进行对比，以逐渐减小网络输出结果的信息、分类等各类型的损失。训练完成后，只需向网络输入一张灰度图片，即可生成一张颜色饱满、鲜明逼真的彩色图片。实验结果表明，引入密集网络后，可有效改善着色过程中的漏色、细节信息损失、对比度低等问题，所提算法着色效果较基于VGG网络及U-Net、双流网络结构、残差网络（ResNet）等性能优异的先进着色算法而言取得了显著的改进。     

冷却塔免费供冷在高端酒店项目的应用及探讨

本文分析了在过渡季节如何利用冷却塔为国际高端酒店提供免费冷源,以及过渡季节通过冷却塔为酒店供冷的空调效果与经济效益,并通过具体实施项目案例证明了利用冷却塔提供免费冷源的可行性、经济性及对于节能环保的意义.     

某工业厂房主体结构安全性评定探讨

结构的安全性是结构防止破坏倒塌的能力,是结构工程重要的质量指标.老工业基地中的厂房主体结构安全性评价,对于厂房加固改造起到了关键性作用.文中通过对某工业厂房主体结构大量现场勘验、隐患排查及检测数据,结合结构验算,从承载能力、损伤等几方面对该老旧工业厂房的安全性进行了评价与分析,并详细介绍了检测鉴定的流程,为以后类似的老旧工业厂房的检测鉴定提供参考.     

基于感知评价的Internet语音终端流量控制

分析了影响因特网语音通信质量的主要因素，根据实时传输控制协议计算延迟、丢包率等网络参数，并利用RBF神经网络将参数映射为语音质量评分，根据评分值的变化动态地调整语音终端的编码速率，在保证一定语音质量的同时，缓解网络拥塞。实验证明了该方法的有效性。     

多层住宅双循环太阳热水系统方案探讨及技术经济分析

提出了用于多层住宅的双循环太阳热水系统设计方案。与每户独立安装的太阳热水器和单循环太阳热水系统相比,双循环太阳热水系统的太阳集热器统一布置设计,可使建筑外观更加整齐,双循环设计使系统具备承压能力高、防冻及防结垢功能等技术特点。根据双循环太阳热水系统初投资较高、使用费低的特点,引入了将初投资、使用寿命期内运行费用、银行存款年利率统一折现为系统运行起始年能源价格的“综合能源价格现值”概念,并使用此概念对双循环太阳热水系统与常规热水系统在相同使用寿命期内的经济性进行了比较分析。     

Frequency Insertion Strategy for Channel Assignment Problem

This paper presents a new heuristic method for quickly finding a good feasible solution to the channel assignment problem (CAP). Like many other greedy-type heuristics for CAP, the proposed method also assigns a frequency to a call, one at a time. Hence, the method requires computational time that increases only linear to the number of calls. However, what distinguishes the method from others is that it starts with a narrow enough frequency band so as to provoke violations of constraints that we need to comply with in order to avoid radio interference. Each violation is then resolved by inserting frequencies at the most appropriate positions so that the band of frequencies expands minimally. An extensive computational experiment using a set of randomly generated problems as well as the Philadelphia benchmark instances shows that the proposed method perform statistically better than existing methods of its kind and even yields optimum solutions to most of Philadelphia benchmark instances among which two cases are reported for the first time ever, in this paper. Won-Young Shin was born in Busan, Korea in 1978. He received B.S. in industrial engineering from Pohang University of Science and Technology (POSTECH) in 2001 and M.S in operation research and applied statistics from POSTECH in 2003. Since 2003 he has been a researcher of Agency for Defense Development (ADD) in Korea. He is interested in optimization of communication system and applied statistics. Soo Y. Chang is an associate professor in the Department of Industrial Engineering at Pohang University of Science and Technology (POSTECH), Pohang, Korea. He teaches linear programming, discrete optimization, network flows and operations research courses. His research interests include mathematical programming and scheduling. He has published in several journals including Discrete Applied Mathematics, Computers and Mathematics with Application, IIE Transactions, International Journal of Production Research, and so on. He is a member of Korean IIE, and ORMSS. Jaewook Lee is an assistant professor in the Department of Industrial Engineering at Pohang University of Science and Technology (POSTECH), Pohang, Korea. He received the B.S. degree in mathematics with honors from Seoul National University, and the Ph.D. degree from Cornell University in applied mathematics in 1993 and 1999, respectively. He is currently an assistant professor in the department of industrial engineering at the Pohang University of Science and Technology (POSTECH). His research interests include nonlinear systems, neural networks, nonlinear optimization, and their applications to data mining and financial engineering. Chi-Hyuck Jun was born in Seoul, Korea in 1954. He received B.S. in mineral and petroleum engineering from Seoul National University in 1977, M.S. in industrial engineering from Korea Advanced Institute of Science and Technology in 1979 and Ph.D. in operations research from University of California, Berkeley, in 1986. Since 1987 he has been with the department of industrial engineering, Pohang University of Science and Technology (POSTECH) and he is now a professor and the department head. He is interested in performance analysis of communication and production systems. He has published in several journals including IIE Transactions, IEEE Transactions, Queueing Systems and Chemometrics and Intelligent Laboratory Systems. He is a member of IEEE, INFORMS and ASQ.     

缓冲区分析在河流沉积相正演研究中的应用

研究区域的沉积相图，是沉积相研究的重要成果。实际工作中，沉积相图的绘制是在综合分析各种地质参数的基础上产生的。应用GIS分析中的缓冲区原理，对影响沉积相的各种参数进行分析研究，并在Microsoft Visual Stdio.NET编程环境中完成缓冲区算法。最后，根据某油田各种实际地质参数数据，应用该方法实现了河道沉积相形成的快速正演模拟，取得了很好效果。