Enhancement of process modelling and simulation evaluation by deploying a test for assessment and feedback individualisation

This paper demonstrates a novel approach for a computer-based course assessment. A test is introduced in which computers are deployed. This significantly contributes to the enhancement of the marking consistency, individual performance distinction and feedbacks, and widen the questions range for computer-based modules. The proposed test method, for the first time, uses the simulation files marking for individualised evaluation purposes. The methodology has successfully been implemented in practice for three modules including Process Simulation (CE2105), Advanced Process Simulation (CE4023), and Process Computation (CE3021) at Aston University (UK) over three academic years, from 2016 to 2019. The effectiveness of the proposed approach has been evaluated using several factors, including final marks, consistency multiple academic years, and mark distribution. In contrast to the common teamwork assessments, individualised feedback became possible. While ASPEN has been used for CE4023 and CE2105 tests, MATLAB has been applied as the computation platform for CE3021 module. This reveals the applicability of different software in proposed methodology. The number of students in the cohorts studied was from 52 to 204, demonstrating the applicability of the method for various cohort sizes. Even though the methodology has been demonstrated based on the chemical engineering discipline modules, it allows digitalising the delivery and assessment of a wide range of simulation techniques in many disciplines.     

Use of a smartphone-based Student Response System in large active-learning Chemical Engineering Thermodynamics classrooms

Smartphones are a promising tool as student response systems (SRS) for interactive teaching due to their widespread diffusion. Here, the main purpose is to assess the efficacy of smartphone-based SRS in large classroom settings of undergraduate Thermodynamics, as representative of engineering courses requiring high-level cognitive skills for problem solving. Four sets of multiple-choice questions were presented during the course. Overall, the results refer to 1055 students between control and SRS classes, each corresponding to a3 years period.One of the main results of this work is the strong linear correlation between the average questionnaire score and the final exam grade (R² = 0.91). A similar correlation, although with a lower value of R², is already found in the first questionnaire, thus showing the SRS high predictive power of class performance. The results of this study provide guidance for a quantitative use of smartphone-based SRS in teaching basic disciplines. The SRS monitoring capability allows early detection of struggling students, thus paving the way to personalized tutoring and improved student engagement in active learning practices. This approach is especially important in emergency situations, such as the SARS-Cov-2 pandemic, when distance learning is widely adopted, and remote interactive tools are highly needed.     

基于双时间点检测的毫米波雷达人流量监测方法

针对现有基于视频监控的人流量统计方案成本高、算法复杂且不利于个人隐私保护的局限性，利用毫米波雷达体积小、成本低、分辨率高的特点，提出了一种基于双时间点检测的人流量监测方法。该方法先获取人体目标散射点位置和多普勒频移信息来构成点云数据，然后根据多普勒频移正负来判断人体的运动方向，并筛选具有高多普勒频移值的点云数据以降低干扰点对聚类结果的影响；在双时间点对特定区域内人员数量进行统计，并根据双时间点之间所获取的点云数据聚类结果对所统计人员数据进行修正。实验结果表明，该方法能够用匿名的方式以较高的正确率统计人员进出。     

碳中和背景下配电网差异化节能降耗潜力评估分

为了提高配电网差异化节能降耗效果，解决现有潜力评估方法存在的应用性能差的问题，提出碳中和背景下配电网差异化节能降耗潜力优化评估方法。根据配电网的空间结构，构建相应的等值电路模型。在该模型下，从设备损耗和运行附加损耗2个方面计算配电网的损耗量。根据损耗量计算结果，确定配电网差异化碳中和节能降耗方式。从静态和动态2个角度设置潜力评估指标，通过指标数据处理、指标权重求解等步骤，得出配电网差异化节能降耗潜力的综合量化评估结果。将设计潜力评估方法应用到配电网的差异化节能降耗改造工作中，能够有效降低配电网的实际线损量、降低区域损耗费用，并具有较高的应用价值。     

基于CiteSpace的旅游服务设计研究可视化分析

目的 旅游服务设计发展态势良好，从旅游服务设计的角度进行文献可视化分析，可从中获得当前领域的知识结构、研究热点和发展态势，为未来提供旅游服务设计研究和旅游产业的服务设计参考。方法 从CNKI和Web of Science数据库收集1990—2020年国内外的相关数据，运用CiteSpace对旅游服务设计的文献发表时间、高度被引用的文献、研究热点和研究前沿进行可视化分析，比较国内外研究差异。结论 在1990—2020年国内外旅游服务设计研究皆呈上升趋势。国外的研究热度、被引频次高于国内，以跨学科领域研究尤为突出，研究重点在建筑环境和交通相关策略;而国内研究以产品服务系统为主，偏向于技术的实现方式。综观研究现状和趋势，本文从智慧科技旅游、可持续发展和全域旅游进行深入探讨，提出旅游服务设计新发展趋势。     

Data requirements for improving the Quantitative Risk Assessment of liquid hydrogen storage systems

Quantitative Risk Assessment (QRA) supports the development of risk-informed safety codes and standards which are employed to enable the safe deployment of hydrogen technologies essential to decarbonize the transportation sector. System reliability data is a necessary input for rigorous QRA. The lack of reliability data for bulk liquid hydrogen (LH₂) storage systems located on site at fueling stations limits the use of QRAs. In turn, this hinders the ability to develop the necessary safety codes and standards that enable worldwide deployment of these stations. Through a QRA-based analysis of a LH₂ storage system, this work focuses on identifying relevant scenario and probability data currently available and ascertaining future data collection requirements regarding risks specific to liquid hydrogen releases. The work developed consists of the analysis of a general bulk LH₂ storage system design located at a hydrogen fueling station. Failure Mode and Effect Analysis (FMEA) and traditional QRA modeling tools such as Event Sequence Diagrams (ESD) and Fault Tree Analysis (FTA) are employed to identify, rank, and model risk scenarios related to the release of LH₂. Based on this analysis, scenario and reliability data needs to add LH₂-related components to QRA are identified with the purpose of improving the future safety and risk assessment of these systems.     

就诊等待服务APP适老化设计研究

目的 将数字化服务融入老年患者就诊流程，建立适老化就诊等待服务系统，在APP开发设计研究中实现软件流程优化。方法 依据ERG理论对老年患者在就诊等待过程中的需求点进行分类整理和层次划分。调研目标用户将分析结果融入服务设计理论，为指导软件开发所涉及的医院就诊流程、用户需求痛点，提出系统性的解决策略。基于交互设计原则展开APP界面设计。结论 构建了以老年患者为中心的就诊等待服务系统，帮助提升其等待过程中的自我效能。完善了基于产品使用方式层级的适老化就诊等待服务APP设计策略，为适老化、数字化产品研发提供了新思路;最终产出APP设计实例，提高了老年群体社会参与度，鼓励老年患者自主就诊，帮助其更加轻松地享受信息化时代带来的红利。     

基于纸浆纤维的贵重物品内包装塑造系统研究

为解决贵重物品与其内包装“契合度”不高的问题，提出基于纸浆纤维的贵重物品内包装塑造系统。系统通过三维扫描获取待包装物品的点云信息，经主控计算机进行数据处理，以下位机为执行中枢，辅之其他外部设备，利用纸浆纤维为贵重物品塑造“量身定制”的内包装，提升内包装契合度，增强保护效果，绿色环保，安全稳定。     

SRS: Spatial-tagged radio-mapping system combining LiDAR and mobile-phone data for indoor location-based services

One of the most challenging issues in radio received signal strength (RSS)-based localization systems is the generation and distribution of a radio map with a coordinate system linked with spatial information in a large indoor space. This study proposes a novel spatial-tagged radio-mapping system (SRS) that effectively combines the heterogeneous properties of LiDAR and mobile phones to simultaneously perform both spatial and radio mappings. The SRS consists of synchronization, localization, and map building processes, and enables real-time spatial and radio mapping. In the synchronization process, the distance range, motion data, and radio signals obtained through the LiDAR and mobile phone are collected in nodal units according to the sensing time. In the localization process, a feature variance filter is used to control the number of features generated from LiDAR and estimate the positions at which the nodes are generated in real time according to the motion data and radio signals. In map building, the estimated positions of the nodes are used to extract spatial and radio maps by using a unified location coordinate system. To ensure mobility, the SRS is manufactured in the form of a backpack supporting LiDAR and a mobile phone; the usefulness of the system is experimentally verified. The experiments are performed in a large indoor shopping mall with a complex structure. The experimental results demonstrated that a common coordinate system could be used to build spatial and radio maps with high accuracy and efficiency in real time. In addition, the field applicability of the SRS to location-based services is experimentally verified by applying the constructed radio map to well-known fingerprinting algorithms using the heterogeneous mobile phones.     

5G核心网业务模型的智能化预测研究

摘 要：核心网业务模型的建立是5G网络容量规划和网络建设的基础，通过现有方法得到的理论业务模型是静态不可变的且与实际网络存在偏离。为了克服现有5G核心网业务模型与现网模型适配性较差以及规划设备无法满足用户实际业务需求的问题，提出了一种长短期记忆（long short-term memory，LSTM）网络与卷积LSTM （convolution LSTM，ConvLSTM）网络双通道融合的 5G 核心网业务模型预测方法。该方法基于人工智能（artificial intelligence，AI）技术以实现高质量的核心网业务模型的智能预测，形成数据反馈闭环，实现网络自优化调整，助力网络智能化建设。