Analysis of the recycling system for aluminum cans,focusing on collection,transportation, and the intermediate processing methods

In this article, the systems for the collection and intermediate processing of used beverage cans (UBCs) are compared and analyzed, focusing on the time taken and the cost of processing, the energy consumption, and the emissions of CO₂, SO _x , and NO _x , during the process. We found that cases where the UBCs were crushed in the discharging process gave better results, and how the UBCs were collected was the most important factor. It was more desirable to treat UBCs in one place than in two places. When the transportation distance was longer, the pressed form of UBCs was more convenient. When the transportation distance was short, the original form, the crushed form, and the shredded form of UBCs were all suitable. That is, the contribution of the transportation process to the evaluation was large when the transport distance was long, and the contribution of the treatment process was large when the transport distance was short.     

我国地震应急指挥技术体系初探

地震应急指挥技术系统是防震减灾建设的核心内容。”十五”期间,将建设中国地震应急指挥技术系统。目前我国在这方面的研究和建设尚处于初级阶段,其体系结构,关键构成、设计和实现还有许多问题值得进一步研究和探讨。根据所从事的项目建设过程,对地震应急指挥技术系统的体系结构进行了阐述,介绍了在此基础上开展的首都圈地震应急指挥系统建设工作,并就今后的发展进行了讨论。     

浙江省废纸再生产业的经验、问题及对策

文章分析了浙江省在废纸再生方面的3个典型模式的经验，指出了存在的问题并提出了建议对策。     

环境物探技术在岩溶勘察中的应用及其效果

将高密度电阻率法及工程地震映像法两种环境物探技术同时应用于实际的地质灾害(岩溶)勘察中,结果表明:对于岩溶这样的地质灾害,单一环境物探技术虽然能清楚反映其埋深、规模和发育情况,但各有缺陷。而多种环境物探技术的综合使用,相互补充,将能大大提高岩溶勘察的准确性,提高勘察效果和效率。     

数字隐写技术及发展趋势

笔者通过强调数字隐写算法和隐写分析算法间的矛盾统一,介绍数字隐写算法的发展历程和趋势以及国内外的研究现状。重点介绍具有代表性的空域LSB隐写算法和频域JPEG图像隐写算法。通过基本算法、对基本算法的分析方法、基本算法改进措施的顺序,介绍算法的发展历程,分析算法的性能。对当前实验研究的进展和数字隐写技术存在的问题进行说明,并提出一些建设性意见,对隐写技术的发展前景和方向进行展望,指出数字隐写技术会成为密码术的重要补充,在信息安全传输方面发挥巨大的作用。     

基于设备网(DeviceNet)总线技术的矿井瓦斯传感器的设计

介绍瓦斯传感器的国内外研究现状,给出以设备网(DeviceNet)总线构成的瓦斯传感器检测网络结构。简要分析了DeviceNet总线协议特点以及其关键技术,提出具有DeviceNet总线规范的矿井瓦斯传感器的设计及实现方案。硬件电路主要由信号调理电路、数字信号处理器,以及能实现DeviceNet网络通信的接口电路构成,用对象建模的方法构建了矿井瓦斯传感器的对象模型,并用模块化编程技术实现了矿井瓦斯传感器作为一个网络从设备的应用层的软件设计。该传感器作为从设备和带有PCI-CAN网卡的计算机组成主/从连接网络,能对多个矿井瓦斯传感器的数据实现远距离的控制。     

石英砂加工企业职业病危害防护措施与管理对策研究

通过对安徽省石英砂加工企业生产工艺流程和现场进行调查分析,得出矽尘和噪声是两种最主要的职业病危害因素,发现石英砂生产企业矽尘和噪声危害十分严重,生产作业现场未配备任何防护装备和个人防护用品,作业人员接触职业病危害的比率非常高。分析了石英砂加工企业在职业病危害防护与管理方面的欠缺与不足,提出了针对矽尘和噪声危害因素的具体工程防护措施与管理对策,从源头控制和消除职业病危害,保护劳动者的生命安全与健康。     

大渡河上游丹巴地区地质灾害的地貌分维特征解析

地貌对地质灾害的分布、类型、规模与危害等特征具有重要的影响,宏观及微观地貌指标均能在一定程度上刻画其作用特征。应用高分辨率遥感影像详细解译崩塌和滑坡灾害,采用高精度DEM和滑动窗口技术提取地貌分维特征,并用其解析灾害分布的地貌特征。结果表明:灾害体的内部与后壁、前缘、侧壁和邻区均表现出较为明显的分异性,崩塌的微地貌分异特征较之滑坡显著,大型、厚层、老(古)崩塌及滑坡分异特征更为突出。计算地貌分维值可有效识别与其同时期的或更早的地质灾害,也可间接挖掘新发生灾害的微地貌复杂性和离散性。     

A data-driven narratives skeleton pattern recognition from accident reports dataset for human-and-organizational-factors analysis

Accidents in the process industry involve several interacting factors, including human and organizational factors (HOFs). A long-standing obstacle to HOFs analysis is lack of data. Accident reports are an essential data source to learn from the past and contain HOFs-related data, but they are usually unstructured text in a not standardized format. Some studies have explored the extraction of information automatically from accident reports based on Natural Language Processing (NLP) techniques. However, they were not dedicated to HOFs. Risk communication is considered an essential pillar in safety and risk science. This research develops a HOFs-focused risk communication framework based on the NLP techniques that can support risk assessment and mitigation. The proposed approach automatically extracts the target groups oriented “Who, When, Where, Why” (4Ws) information from accident reports.This framework was applied to explore the eMARS database. The results show that the “4Ws” skeleton of narratives has appreciated performance in pattern recognition and holistic information analysis. The graphical representation interfaces are designed to display the features of HOFs-related accidents, which can better be communicated to the sharp-end operators and decision-makers.     

基于无人机影像的城市植被精细分类

针对传统植被资源调查方法工作量大、成本高、效率低的问题,利用高分辨率无人机遥感影像,联合地物光谱-纹理-空间信息,构建了一种适用于描述城市不同植被种类的多维特征空间,在此基础上对三种应用广泛的分类算法(基于像素的、面向对象的支持向量机及深度学习Mobile-Unet语义分割模型)开展了对比分析研究.结果表明:本文提出的联合地物光谱-纹理-空间信息的特征空间构建方法能够有效地描述城市不同类型植被的特征差异,提升影像分割、植被分类的精度;在分类精度上,基于像素和面向对象的支持向量机分类结果的总体精度均超过90%,深度学习方法的总体分类精度为84%;在算法效率上,传统机器学习方法也优于深度学习方法.因此,得出结论针对城市小区域、小样本的植被精细分类,传统机器学习分类方法比深度学习方法效果更好.