Subspace Clustering for Situation Assessment in Aquatic Drones: A Sensitivity Analysis for State-Model Improvement

Abstract

In this paper, we propose the use of subspace clustering to detect the states of dynamical systems from sequences of observations. In particular, we generate sparse and interpretable models that relate the states of aquatic drones involved in autonomous water monitoring to the properties (e.g., statistical distribution) of data collected by drone sensors. The subspace clustering algorithm used is called SubCMedians. A quantitative experimental analysis is performed to investigate the connections between i) learning parameters and performance, ii) noise in the data and performance. The clustering obtained with this analysis outperforms those generated by previous approaches.     

Determining what is important for sustainability: scoping processes of sustainability assessments

Over recent decades, there has been a significant proliferation of types of impact assessments. While some argue that this is threatening future use of impact assessments, sustainability assessments have emerged as a potential approach to bridge these diverse approaches. This research focuses on examining sustainability assessments at the project level, looking specifically at scoping practices key to integration. Nine multinational enterprises operating within Indonesia are studied, utilising a case study methodology with semi-structured interviews with 32 respondents. Findings emphasise that while these multinationals sought to address key regulatory requirements through their scoping practices, international standards and global sustainability platforms were critical in informing the practices of these organisations. The recognition of these standards and guidelines saw them addressing a broad range of key sustainability issues; also using prescribed techniques to engage with stakeholders and identify the most critical sustainability issues to focus on in assessment. There was integration of scoping processes through different levels and across the organisations, which were generally managed by teams providing sustainability expertise, including through affiliate personnel for local contextualisation.

Abbreviation AMDAL - Analisis Mengenai Dampak Lingkungan (EIA); BAPEDALDA - provincial/regional-level of the Environmental Impact Management Agency; CAQDAS – computer assisted data analysis software; CSR – corporate social responsibility; EIA – environmental impact assessment; EU – European Union; FDI – foreign direct investment; GRI – Global Reporting Initiative; ILO – International Labour Organization; MCA – multicriteria analysis; MNE – multinational enterprise; MOE - Ministry of Environment (now Ministry of Environment and Forestry); NGO – non-government organisation; OECD – Organisation for Economic Cooperation and Development; OH&S – occupational health and safety; SPPL - Letter of Statement on Environmental Management Effort; UKL – Environmental Management Effort; UN – United Nations; UNGC – United Nations Global Compact; UPL - Environmental Controlling Effort.     

非平稳条件下基于贝叶斯网络的内涝风险评估和管理方法

受非平稳条件因素(如气候变化、城市化)的影响,近几年内涝灾害频发。以Z市某地块为研究区域,借助地理信息系统(ArcGIS)和暴雨雨洪管理模型(SWMM)实现研究区排水管网的水动力模拟。在不同降雨情境下,比较分析现状系统及不同改造方案下的系统溢流量等信息,计算内涝风险指数。采用贝叶斯网络分析工具(Bayes Server)对引发内涝风险的主要因素进行推理、识别和分析,进而构建内涝风险评估模型。该模型便于决策者根据设计需求,结合各因素的不确定性范围和发生概率值,综合选取最适合的改造措施,优化市政排水防涝规划,为市政基础设施建设提供了依据。     

地热系统碳酸钙垢形成原因及定量化评价

碳酸钙垢是我国喜马拉雅构造带高温地热系统开发利用面临的主要问题之一,其直接原因是流体中Ca²⁺和CO₃^2- 的活度积大于当前温度下的平衡常数,通常与pH值增大有关。导致pH值增大的过程包括井筒内的沸腾作用促进CO₂脱气,套管腐蚀消耗质子,流体上升过程中的减压作用以及其他气体的侵入导致的CO₂逃逸,主控因素是沸腾作用。本文建立了一套系统评价地热流体结垢趋势、位置和规模的方法。首先基于地热流体经历的地球化学过程（如沸腾、混合、结垢等）,利用井口或者泉口样品的数据和地球化学程序重建储层流体的化学组分;利用水文地球化学模拟程序或者雷兹诺指数,计算碳酸钙的饱和指数,评价其发生结垢的趋势。其次利用井径测井或者井筒模拟和地球化学模拟,定量给出发生结垢的深度及范围。此外,储层和井口流体Ca²⁺ 浓度差异和平衡模拟方法以及碳酸钙结垢厚度评价方法可用于定量计算一定开采时间内的结垢量,其结果与实际情况具有可比性;对于川西某结垢地热井,48 h内的结垢量达151 ~ 300 kg或结垢厚度为1 ~ 3 cm。碳酸钙形成原因分析和定量化评价可为下一步的防垢或者除垢设计提供科学依据。     

Quality-by-design approach for the development of telmisartan potassium tablets

A quality-by-design approach was adopted to develop telmisartan potassium (TP) tablets, which were bioequivalent with the commercially available Micardis^® (telmisartan free base) tablets. The dissolution pattern and impurity profile of TP tablets differed from those of Micardis^® tablets because telmisartan free base is poorly soluble in water. After identifying the quality target product profile and critical quality attributes (CQAs), drug dissolution, and impurities were predicted to be risky CQAs. To determine the exact range and cause of risks, we used the risk assessment (RA) tools, preliminary hazard analysis and failure mode and effect analysis to determine the parameters affecting drug dissolution, impurities, and formulation. The range of the design space was optimized using the face-centered central composite design among the design of experiment (DOE) methods. The binder, disintegrant, and kneading time in the wet granulation were identified as X values affecting Y values (disintegration, hardness, friability, dissolution, and impurities). After determining the design space with the desired Y values, the TP tablets were formulated and their dissolution pattern was compared with that of the reference tablet. The selected TP tablet formulated using design space showed a similar dissolution to that of Micardis^® tablets at pH 7.5. The QbD approach TP tablet was bioequivalent to Micardis^® tablets in beagle dogs.     

水电工程下泄生态基流常用计算方法及软件开发

为了分析及确立生态基流,为水电工程环境影响评价提供依据,针对水电工程生态基流估算及决策过程繁复等问题,以2001—2015年水电工程环境影响评价及相关法律法规为基础,分析我国生态基流管理实践中使用最广泛的4种计算方法,即Tennant法、月基本流量法、最小流量法及7Q10法,并编制生态基流决策支持软件,并应用软件在汉江流域进行实例验证。结果表明,该软件能够提供多种计算方法及对比分析功能,可为水电工程下泄生态基流计算及决策提供计算平台。4种计算方法在汉江流域计算结果差异较大。总体而言,干流适合最小流量法及Tennant法,支流适合Tennant法。研究成果具有较大的实际应用和推广价值。     

Quality assessment for color correction-based stitched images via bi-directional matching

With the deepening of social information, the panoramic image has drawn a significant interest of viewers and researchers as it can provide a very wide field of view (FoV). Since panoramic images are usually obtained by capturing images with the overlapping regions and then stitching them together, image stitching plays an important role in generating panoramic images. In order to effectively evaluate the quality of stitched images, a novel quality assessment method based on bi-directional matching is proposed for stitched images. Specifically, dense correspondences between the testing and benchmark stitched images are first established by bi-directional SIFT-flow matching. Then, color-aware, geometric-aware and structure-aware features are respectively extracted and fused via support vector regression (SVR) to obtain the final quality score. Experiments on our newly constructed database and ISIQA database demonstrate that the proposed method can achieve comparable performance compared with the conventional blind quality metrics and the quality metrics specially designed for stitched images.