基于测绘地理信息技术的涉地税源风险识别模式应用研究

为解决沧州市涉地税源管理手段单一等问题,文中提出以测绘地理信息技术为支撑,通过对多源数据组织管理,建立风险分析指标,采用多种GIS空间分析方法构建了涉地风险税源识别模式并在沧州进行应用。结果表明:该模式能有效识别多种涉地风险,为涉地税源管理提供了支撑。     

Prediction of fish quality level with machine learning

In this study, sea bream, sea bass, anchovy and trout were captured and recorded using a digital camera during refrigerated storage for 7 days. In addition, their total viable counts (TVC) were determined on a daily basis. Based on the TVC, each fish was classified as ‘fresh’ when it was <5 log cfu per g, and as ‘not fresh’ when it was >7 log cfu per g. They were uploaded on a web-based machine learning software called Teachable Machine (TM), which was trained about the pupils and heads of the fish. In addition, images of each species from different angles were uploaded to the software in order to ensure the recognition of fish species by TM. The data of the study indicated that the TM was able to distinguish fish species with high accuracy rates and achieved over 86% success in estimating the freshness of the fish species tested.     

Cheese ripening in nonconventional conditions: A multiparameter study applied to Protected Geographical Indication Canestrato di Moliterno cheese

A multiparameter study was performed to evaluate the effect of fondaco, a traditional ripening cellar without any artificial temperature and relative humidity control, on the chemical, microbiological, and sensory characteristics of Protected Geographical Indication Canestrato di Moliterno cheese. Ripening in such a nonconventional environment was associated with lower counts of lactococci, lactobacilli, and total viable bacteria, and higher presence of enterococci, in comparison with ripening in a controlled maturation room. Moreover, fondaco cheese underwent accelerated maturation, as demonstrated by faster casein degradation, greater accumulation of free AA, and higher formation of volatile organic compounds. Secondary proteolysis, as assessed by liquid chromatography-mass spectrometry of free AA and low molecular weight peptides, did not show any qualitative difference among cheeses, but fondaco samples evidenced an advanced level of peptidolysis. On the other hand, significant qualitative differences were observed in the free fatty acid profiles and in the sensory characteristics. Principal component analysis showed a clear separation of the fondaco and control cheeses, indicating that ripening in the natural room conferred unique sensory features to the product.     

Development of a stakeholder identification and analysis method for human factors integration in work system design interventions – Change Agent Infrastructure

In any work system design intervention—for example, a physical workplace re-design, a work process change, or an equipment upgrade—it is often emphasized how important it is to involve stakeholders in the process of analysis and design, to gain their perspectives as input to the development, and ensure their future acceptance of the solution. While the users of an artifact or workplace are most often regarded as being the most important stakeholders in a design intervention, in a work-system context there may be additional influential stakeholders who influence and negotiate the design intervention's outcomes, resource allocation, requirements, and implementation. Literature shows that it is uncommon for empirical ergonomics and human factors (EHF) research to apply and report the use of any structured stakeholder identification method at all, leading to ad-hoc selections of whom to consider important. Conversely, other research fields offer a plethora of stakeholder identification and analysis methods, few of which seem to have been adopted in the EHF context. This article presents the development of a structured method for identification, classification, and qualitative analysis of stakeholders in EHF-related work system design intervention. It describes the method's EHF-related theoretical underpinnings, lessons learned from four use cases, and the incremental development of the method that has resulted in the current method procedure and visualization aids. The method, called Change Agent Infrastructure (abbreviated CHAI), has a mainly macroergonomic purpose, set on increasing the understanding of sociotechnical interactions that create the conditions for work system design intervention, and facilitating participative efforts.     

Identification and U-control of a state-space system with time-delay

This article presents a state-space model with time-delay to map the relationship between known input-output data for discrete systems. For the given input-output data, a model identification algorithm combining parameter estimation and state estimation is proposed in line with the causality constraints. Consequently, this article proposes a least squares parameter estimation algorithm, and analyzes its convergence for the studied systems to prove that the parameter estimation errors converge to zero under the persistent excitation conditions. In control system design, the U-model based control is introduced to provide a unilateral platform to improve the design efficiency and generality. A simulation portfolio from modeling to control is provided with computational experiments to validate the derived results.     

Optimization and regularization of complex task decomposition for blind removal of multi-factor degradation

Most existing image restoration methods based on deep neural networks are developed for images which only degraded by a single degradation mode and imaging under an ideal condition. They cannot be directly used to restore the images degraded by multi-factor coupling. A complex task decomposition regularization optimization strategy (TDROS) is proposed to solve the problem. The restoration of images degraded by multi-factor coupling is a complex task that can be solved by separating these multiple factors, that is, breaking the complex task into numbers of simpler tasks to make the entire complex problem be overcome more easily. Motivated by this idea, the TDROS decomposes the complex task of image restoration into two sub-task: the potential task constrained by regularization and the main task for reconstructing high-definition images. In TDROS, the front of the neural network is focused on the restoration of images degraded by additive noise, while the other part of the network is focused mainly on the restoration of images degraded by blur. We applied the TDROS to an 11-layer convolutional neural network (CNN) and compared it with initial CNNs from the aspects of restoration accuracy and generalization ability. Based on these results, we used TDROS to design a novel network model for the restoration of atmospheric turbulence-degraded images. The experimental results demonstrate that the proposed TDROS can improve the generalization ability of the existing network more effectively than current popular methods, offering a better solution for the problem of severely degraded image restoration. Moreover, the TDROS concept provides a flexible framework for low-level visual complex tasks and can be easily incorporated into existing CNNs.     

物料堆场智能化管理经验分享

华润水泥（罗定）有限公司根据物料储存需求，共有三个长堆棚分为9个室内料场堆放原材料及混合材，厂内有4台铲车无规则轮流在这8个料场内作业，同时外来运料货车、公司化验及验收人员也会不间断地进入不同堆棚。由于料场内空间狭窄，驾驶员视线不好，如果堆棚料场内铲车在作业时，有其他人员或车辆进入铲车工作区域共同作业，在没有检测装置对进入的人、车进行识别，提醒铲车驾驶员的情况下，容易发生碾压进入人员或车辆碰撞的安全事故。公司根据现场实际，自2020年起决定实施从堆场出入口智能红外感应技术、装载机车载识别系统、智能声光语音提醒、实时监控显示、照明、堆场硬件设施等五方面实施物料堆场车辆智能化安全预警系统项目。     

爆破工程安全评价初探

开展爆破工程安全评价可有效地减少各种危险和有害因素 ,减少爆破事故的发生 ,大型或特殊爆破工程均应进行安全评价。本文提出了对爆破工程开展安全评价的设想 ,并对爆破工程安全评价的内容和方法进行了探讨。文中指出 :根据爆破工程的特点 ,可采用事故树分析和预先危险性分析等方法进行爆破工程的安全评价     

WSN低功耗低时延路径式协同计算方法

针对云计算应用于无线传感器网络(Wireless Sensor Network,WSN)时延敏感型业务时存在的高传输时延问题,提出了一种WSN低功耗低时延路径式协同计算方法。该方法基于一种云雾网络架构开展研究,该架构利用汇聚节点组成雾计算层;在数据传输过程中基于雾计算层的计算能力分步骤完成任务计算,降低任务处理时延;由于汇聚节点计算能力较弱,时延降低将导致能耗增加,WSN工作寿命减短,为此提出能耗约束下的任务映射策略,并利用离散二进制粒子群优化(Binary Particle Swarm Optimization,BPSO)算法解决能耗约束下的时延优化问题。仿真结果表明,在相同的能耗约束下,对比其他算法,基于BPSO算法得出的映射方案能有效降低业务处理时延,满足时延敏感型业务的需求。     

公众食品药品网络谣言和虚假宣传辨识能力调查——以贵州省某少数民族自治地区为例

目的 了解公众对网络食品药品谣言信息及虚假宣传甄别能力和行为态度，探索防范谣言传播、维护社会稳定的有效措施和途径。方法 采用随机抽样研究方法，对贵州省某少数民族自治州公众开展食品药品网络谣言及虚假宣传辨识能力、行为态度问卷调查。结果 当地公众食品药品网络谣言及虚假宣传辨识能力总体较低，经济发展落后地区的青少年人群对网络谣言及虚假宣传的辨识能力较弱。大部分公众处理网络食品药品安全信息较为理性，更愿意通过国家监管部门权威网站了解信息，基本具备了确认信息真实性的主观意识，但辟除谣言的行动能力不高。结论 地方党委政府及有关部门应加强食品药品网络谣言和虚假宣传治理，加大当地谣言及虚假宣传的监测和系统性分析研究，有针对性、预判性地进行治理和科普宣传。