Urban Open Space Study Based on Remote Sensing and Geographic Information Systems（GIS）

Open space is treated in many cultures as the common area where people conduct functional and ritual activities that bind a community in the normal routines of daily life or in penodic festivities.From the historical perspective,open space should be supportive,democratic,and meaningful.On the one hand,human culture shapes and reshapes its open spaces,whereas,on the other,open spaces can help to create a more humane culture.This duality suggests that the relationship of open space to public life is dynamic and reciprocal.New forms of public life require new spaces,and vice versa.

Delineation of groundwater potential zones using remote sensing and Geographic Information Systems(GIS)in Kadaladi region,Southern India

The primary objective of this research is to delineate potential groundwater recharge zones in the Kadaladi taluk of Ramanathapuram,Tamil Nadu,India,using a combination of remote sensing and Geographic Information Systems(GIS)with the Analytical Hierarchical Process(AHP).Various factors such as geology,geomorphology,soil,drainage,density,lineament density,slope,rainfall were analyzed at a specific scale.Thematic layers were evaluated for quality and relevance using Saaty's scale,and then inte-grated using the weighted linear combination technique.The weights assigned to each layer and features were standardized using AHP and the Eigen vector technique,resulting in the final groundwater potential zone map.The AHP method was used to normalize the scores following the assignment of weights to each criterion or factor based on Saaty's 9-point scale.Pair-wise matrix analysis was utilized to calculate the geometric mean and normalized weight for various parameters.The groundwater recharge potential zone map was created by mathematically overlaying the normalized weighted layers.Thematic layers indicating major elements influencing groundwater occurrence and recharge were derived from satellite images.2 Results indicate that approximately 21.8 km of the total area exhibits high potential for groundwater recharge.Groundwater recharge is viable in areas with moderate slopes,particularly in the central and southeastern regions.

Computation Tree Logic Model Checking of Multi-Agent Systems Based on Fuzzy Epistemic Interpreted Systems

Model checking is an automated formal verification method to verify whether epistemic multi-agent systems adhere to property specifications.Although there is an extensive literature on qualitative properties such as safety and liveness,there is still a lack of quantitative and uncertain property verifications for these systems.In uncertain environments,agents must make judicious decisions based on subjective epistemic.To verify epistemic and measurable properties in multi-agent systems,this paper extends fuzzy computation tree logic by introducing epistemic modalities and proposing a new Fuzzy Computation Tree Logic of Knowledge(FCTLK).We represent fuzzy multi-agent systems as distributed knowledge bases with fuzzy epistemic interpreted systems.In addition,we provide a transformation algorithm from fuzzy epistemic interpreted systems to fuzzy Kripke structures,as well as transformation rules from FCTLK formulas to Fuzzy Computation Tree Logic(FCTL)formulas.Accordingly,we transform the FCTLK model checking problem into the FCTL model checking.This enables the verification of FCTLK formulas by using the fuzzy model checking algorithm of FCTL without additional computational overheads.Finally,we present correctness proofs and complexity analyses of the proposed algorithms.Additionally,we further illustrate the practical application of our approach through an example of a train control system.

Enhancing Security and Privacy in Distributed Face Recognition Systems through Blockchain and GAN Technologies

The use of privacy-enhanced facial recognition has increased in response to growing concerns about data securityand privacy in the digital age. This trend is spurred by rising demand for face recognition technology in a varietyof industries, including access control, law enforcement, surveillance, and internet communication. However,the growing usage of face recognition technology has created serious concerns about data monitoring and userprivacy preferences, especially in context-aware systems. In response to these problems, this study provides a novelframework that integrates sophisticated approaches such as Generative Adversarial Networks (GANs), Blockchain,and distributed computing to solve privacy concerns while maintaining exact face recognition. The framework’spainstaking design and execution strive to strike a compromise between precise face recognition and protectingpersonal data integrity in an increasingly interconnected environment. Using cutting-edge tools like Dlib for faceanalysis,Ray Cluster for distributed computing, and Blockchain for decentralized identity verification, the proposedsystem provides scalable and secure facial analysis while protecting user privacy. The study’s contributions includethe creation of a sustainable and scalable solution for privacy-aware face recognition, the implementation of flexibleprivacy computing approaches based on Blockchain networks, and the demonstration of higher performanceover previous methods. Specifically, the proposed StyleGAN model has an outstanding accuracy rate of 93.84%while processing high-resolution images from the CelebA-HQ dataset, beating other evaluated models such asProgressive GAN 90.27%, CycleGAN 89.80%, and MGAN 80.80%. With improvements in accuracy, speed, andprivacy protection, the framework has great promise for practical use in a variety of fields that need face recognitiontechnology. This study paves the way for future research in privacy-enhanced face recognition systems, emphasizingthe significance of using cutting-edge technology to meet rising privacy issues in digital identity.

The Support Systems and Coping Strategies of Infertile Women Attending the Out-Patient Consultation Unit of CHRACERH Yaoundé, Cameroon: A Cross-Sectional Study

Background: Infertility is a complex disorder with significant psycho-social and economic consequences. It globally affects 10% - 15% of couples. In Cameroon, little is known about what women do to overcome the psychosocial aspects of the disease. Objectives: This study aimed to identify the support systems and coping strategies of infertile women attending the outpatient consultation unit of the Gynaecological Endoscopic Surgery and Reproductive Teaching Hospital (CHRACERH), Yaoundé, Cameroon. Methods: A hospital-based cross-sectional study was conducted from the 14th of March to the 6th of April 2023 at CHRACERH Yaoundé. A total of 190 participants were recruited using a convenience sampling method. Data regarding socio-demographic characteristics, support systems and coping strategies were collected using a pretested questionnaire. Descriptive and analytic statistics were conducted using SPSS version 25. Results: The mean age of participants was 39.52 ± 7.64 years. The majority 78.9% of participants were workers (public, private sector, or traders) and were Christians 95.8%. The most common source of psychological support was from family 76.8 and husbands 72.63%. Most of the participants 89.5% resorted to prayer and getting busy 48.4% as a coping strategy. There was no statistically significant relationship between coping strategies and psychological disorders p > 0.05. Conclusion: The main support system of participants was family, husband, and friends. Prayer, getting busy and adoption were the most common coping strategies. There is a need for the Ministry of Public Health and other stakeholders to put in place other support systems and coping strategies (FELICIA) used elsewhere and provide adequate health education and infection control to prevent infertility in Cameroon.

A Distributionally Robust Optimization Scheduling Model for Regional Integrated Energy Systems Considering Hot Dry Rock Co-Generation

Hot dry rock(HDR)is rich in reserve,widely distributed,green,low-carbon,and has broad development potential and prospects.In this paper,a distributionally robust optimization(DRO)scheduling model for a regionally integrated energy system(RIES)considering HDR co-generation is proposed.First,the HDR-enhanced geothermal system(HDR-EGS)is introduced into the RIES.HDR-EGS realizes the thermoelectric decoupling of combined heat and power(CHP)through coordinated operation with the regional power grid and the regional heat grid,which enhances the system wind power(WP)feed-in space.Secondly,peak-hour loads are shifted using price demand response guidance in the context of time-of-day pricing.Finally,the optimization objective is established to minimize the total cost in the RIES scheduling cycle and construct a DRO scheduling model for RIES with HDR-EGS.By simulating a real small-scale RIES,the results show that HDR-EGS can effectively promote WP consumption and reduce the operating cost of the system.

Control Strategies for Digital Twin Systems

With the continuous breakthrough in information technology and its integration into practical applications, industrial digital twins are expected to accelerate their development in the near future. This paper studies various control strategies for digital twin systems from the viewpoint of practical applications.To make full use of advantages of digital twins for control systems, an architecture of digital twin control systems, adaptive model tracking scheme, performance prediction scheme, performance retention scheme, and fault tolerant control scheme are proposed. Those schemes are detailed to deal with different issues on model tracking, performance prediction, performance retention, and fault tolerant control of digital twin systems. Also, the stability of digital twin control systems is analysed. The proposed schemes for digital twin control systems are illustrated by examples.

Model-Based Systems Engineering Approach to Design a Human Settlement to Better Serve Displaced People

The challenge of transitioning from temporary humanitarian settlements to more sustainable human settlements is due to a significant increase in the number of forcibly displaced people over recent decades, difficulties in providing social services that meet the required standards, and the prolongation of emergencies. Despite this challenging context, short-term considerations continue to guide their planning and management rather than more integrated, longer-term perspectives, thus preventing viable, sustainable development. Over the years, the design of humanitarian settlements has not been adapted to local contexts and perspectives, nor to the dynamics of urbanization and population growth and data. In addition, the current approach to temporary settlement harms the environment and can strain limited resources. Inefficient land use and ad hoc development models have compounded difficulties and generated new challenges. As a result, living conditions in settlements have deteriorated over the last few decades and continue to pose new challenges. The stakes are such that major shortcomings have emerged along the way, leading to disruption, budget overruns in a context marked by a steady decline in funding. However, some attempts have been made to shift towards more sustainable approaches, but these have mainly focused on vague, sector-oriented themes, failing to consider systematic and integration views. This study is a contribution in addressing these shortcomings by designing a model-driving solution, emphasizing an integrated system conceptualized as a system of systems. This paper proposes a new methodology for designing an integrated and sustainable human settlement model, based on Model-Based Systems Engineering and a Systems Modeling Language to provide valuable insights toward sustainable solutions for displaced populations aligning with the United Nations 2030 agenda for sustainable development.

Energy Storage Systems Technologies, Evolution and Applications

Energy in its varied forms and applications has become the main driver of today’s modern society. However, recent changes in power demand and climatic changes (decarbonization policy) has awakened the need to rethink through the current energy generating and distribution system. This led to the exploration of other energy sources of which renewable energy (like thermal, solar and wind energy) is fast becoming an integral part of most energy system. However, this innovative and promising energy source is highly unreliable in maintaining a constant peak power that matches demand. Energy storage systems have thus been highlighted as a solution in managing such imbalances and maintaining the stability of supply. Energy storage technologies absorb and store energy, and release it on demand. This includes gravitational potential energy (pumped hydroelectric), chemical energy (batteries), kinetic energy (flywheels or compressed air), and energy in the form of electrical (capacitors) and magnetic fields. This paper provides a detailed and comprehensive overview of some of the state-of-the-art energy storage technologies, its evolution, classification, and comparison along with various area of applications. Also highlighted in this paper is a plethora of power electronic Interface technologies that plays a significant role in enabling optimum performance and utilization of energy storage systems in different areas of application.

Analysis of the Design and Implementation of a GIS System Incorporating Intelligent Recognition Models

The rapid economic growth,urbanization,and industrialization have led to a scarcity of land resources in coastal areas,exacerbating the conflict between humans and the environment.In order to promote economic development,attention has turned to the sea,and various coastal engineering projects have been undertaken,sparking a wave of land reclamation.However,while these efforts bring economic and social benefits,they also have implications for ecological relationships.To respond to and plan for changes in the coastline and land cover in a timely manner,this paper proposes and constructs a GIS system that integrates remote sensing image recognition models.The system combines geographic information system development technology with image recognition technology,streamlining the processing and identification of image data.This approach is particularly advantageous for marine management departments in their long-term monitoring and dynamic management of coastal lines,ensuring a more effective and efficient response.

An Optimized Method for Accounting Information in Logistic Systems

In the era of rapid information development,with the popularity of computers,the advancement of science and technology,and the ongoing expansion of IT technology and business,the enterprise resource planning(ERP)system has evolved into a platform and a guarantee for the fulfilment of company management procedures after long-term operations.Because of developments in information technology,most manual accounting procedures are being replaced by computerized Accounting Information Systems(AIS),which are quicker and more accurate.The primary factors influencing the decisions of logistics firm trading parties are investigated in order to enhance the design of decision-supporting modules and to improve the performance of logistics enterprises through AIS.This paper proposed a novel approach to calculate the weights of each information element in order to establish their important degree.The main purpose of this research is to present a quantitative analytic approach for determining the important information of logistics business collaboration response.Furthermore,the idea of total orders and the significant degrees stated above are used to identify the optimal order of all information elements.Using the three ways of marginal revenue,marginal cost,and business matching degree,the information with cumulative weights is which is deployed to form the data from the intersection of the best order.It has the ability to drastically reduce the time and effort required to create a logistics business control/decision-making system.

恒压下GIS固体绝缘界面气隙缺陷放电严重程度评估

为了研究GIS绝缘子界面气隙缺陷的放电发展过程,文中设计了空洞气隙缺陷模型,搭建了一套GIS气隙缺陷放电长期测试平台。基于缺陷模型的击穿电压对带有缺陷的试品施加90%Ub、60%Ub、30%Ub的交流恒压,使用UHF检测系统采集放电数据直至试品击穿。提取放电次数、放电幅值、放电时间间隔分析放电状态特征,发现GIS气隙缺陷放电发展过程存在两个阶段,前期放电幅值缓慢增大,放电脉冲逐渐稀疏,放电发展较为平稳;后期放电幅值急剧减小,放电脉冲密集,放电发展剧烈,采用k⁃means聚类算法及BP神经网络建立了气隙缺陷局放发展阶段的划分规则。研究表明,放电次数、放电幅值、放电时间间隔3种统计参量呈现阶段式单调性的趋势,可以用3种统计参量前向差分绝对值作为特征参量来评估GIS气隙放电严重程度;对GIS恒压试验进行聚类分析将放电过程划分为平稳劣化阶段和加速劣化阶段,随着外施电压水平的降低,平稳劣化阶段被压缩,加速劣化阶段占比升高。

Reply: Comment on “Geological mapping and mining prospecting in the Aouli inlier (Eastern Meseta, Morocco) based on remote sensing and geographic information systems (GIS)” by Benaissi et al. (China Geology, 5 (2022))

We have been pleased that our paper Geological mapping and mining prospecting in the Aouli inlier(Eastern Meseta,Morocco) based on remote sensing and geographic information systems(GIS) was of interest to our colleagues who commented it in China Geology 5(2022) 1–4.

直流电压下GIS盆式绝缘子表面电荷及电场分布特性仿真研究

GIS中盆式绝缘子表面在外施直流电压时会积聚大量电荷使得沿面闪络电压大幅降低,从而引发一系列电气设备故障。基于上述问题,文中分析了盆式绝缘子表面电荷的来源与传导途径,采用有限元仿真计算方法构建了二维轴对称仿真模型以及设定相关参数,研究了电压极性、不同电压幅值以及电压极性反转对盆式绝缘子表面电荷分布的影响。结果表明,在直流电压下,凹面主要积聚与外施直流电压极性相反的电荷,凸面主要积聚与直流电压极性相同的电荷,且凹面积聚的电荷密度更大;在极性反转后-100 kV直流电压下,盆式绝缘子表面原先积聚的电荷密度呈现先增大后逐渐减小的趋势,随后转换极性并达到饱和,电场在靠近高压端以及盆式绝缘子沿面0~20 mm处的畸变程度较为明显。电场在盆式绝缘子表面电荷极性发生变化前出现峰值,相比较电荷达到饱和状态,此时盆式绝缘子凹面最大场强增加46%,凸面最大场强增加5.4%。该研究可为直流电压下盆式绝缘子表面电荷分布特性提供指导。

基于双回路反馈的光纤干涉式GIS局部放电超声传感系统研究

光纤干涉式GIS局部放电超声传感系统受到环境干扰,会导致超声检测灵敏度降低。基于单回路反馈的传感系统能够抑制振动干扰,但长时间工作仍会出现工作点漂移。文中首先分析了单回路反馈传感系统工作点漂移的原因,指出了压电陶瓷迟滞效应的影响;其次,搭建了基于双回路反馈的光纤干涉式GIS局部放电超声传感系统,引入了二次反馈回路以补偿一次反馈回路累积的低频相位调制误差;再次,通过振动干扰下的超声检测试验和GIS局部放电检测试验,证明了双回路反馈传感系统能够长时间保持稳定的超声检测灵敏度;最后,搭建了真型126 kV GIS局部放电检测试验平台,利用双回路反馈传感系统成功检测到了金属颗粒引发的局部放电和跳动声信号,检测到的最小视在放电量为5.2 pC。

基于多层融合振动数据分析的GIS设备机械缺陷诊断方法研究

气体绝缘金属封闭开关设备(gas insulated metal enclosed switchgear,GIS)机械缺陷是导致设备故障的重要因素,针对单测点、单证据机械缺陷诊断模型信息缺失和精度不足问题,该文提出一种多层融合振动数据分析的GIS设备机械缺陷诊断方法。首先,基于真型GIS设备振动模拟平台试验研究测点位置与缺陷类型对振动行为的影响特性;然后,联合统计分析、模态分解、尺度变换方法提出机械振动信号整体与局部信息关注的复合参数分析方法,引入主成分分析开展多测点振动信息的特征层融合降维;最后,提出改进放缩权重的Dempster-Shafer(DS)证据理论和Bagging投票机制的强/弱基学习器决策层融合机制,联合构建多层融合振动数据分析的GIS设备机械缺陷诊断模型。结果表明:不同类型机械缺陷信号的响应幅值、特征频点和畸变程度存在显著差异,复合特征参量大小及分散程度各不相同;同时,测点位置对缺陷信号的复合振动特征参量的表现形式及分布区间也具有一定影响;基于多层融合数据分析的诊断模型实现缺陷有效识别,辨识准确率为98.66%,相比单一分类器诊断效果提升5.83%。该文可为GIS设备机械缺陷诊断方法提供有价值的参考。

基于GIS的农田墒情管理系统应用研究

以农田土壤墒情监测过程和数据分析与管理过程为研究对象,建立农田土壤墒情监测和数据分析过程模型,对当前农田土壤墒情监测过程中的不足进行分析,并结合无线网络传输技术和GIS地理信息技术构建农田墒情管理系统功能模块,实现土壤墒情数据采集、分析处理及管理输出。农田墒情管理系统运行结果表明:系统能够实时快速对农田土壤含水量进行监测,同时能够对土壤水分含量数据动态变化过程进行管理,便于土壤水分含量变化趋势的预测。

基于GIS的宁夏枸杞花期冻害风险分析与区划

宁夏具有独特的地理环境和气候条件,是我国重要的枸杞产区。宁夏枸杞具有品质优良、营养丰富的特点,但枸杞花期冻害是影响其产量和品质的重要因素之一。采用GIS技术,结合气象数据、地形地貌数据、土壤数据等,对宁夏枸杞花期冻害风险进行分析与区划,为宁夏枸杞产业防灾减灾体系建设提供参考。

基于情绪计算的GIS硕士面试成绩预测

针对组织GIS专业学生面试带来人力资源与时间成本大的问题,本研究基于真实面试的视频数据和专家综合打分数据,通过人脸情绪识别与构建特征工程,使用包括偏最小二乘回归、支持向量回归、随机森林回归和梯度提升回归树的4种机器学习模型进行回归模型构建,探究情绪特征与面试成绩的关系。结果表明偏最小二乘回归模型的稳定性和泛化能力在本应用中更好,模型的决定系数为0.486。进一步分析发现,基本情绪中,我们定义的“负面情绪”与面试成绩呈显著负相关;而中性情绪、积极情绪与面试成绩呈显著正相关。本研究为GIS人才面试评估的自动化做出了有益的探索。

基于GIS与大数据分析的矿压监测预警平台

为响应国家关于加快煤矿智能化发展的号召,针对煤矿GIS“一张图”中巷道路径不能实现精确计算,矿压数据不能实现高效甄别、有效提取的问题,以及矿压预警需要实现在线推演、可视化展示的需求,提出建立基于GIS与大数据分析的矿压监测预警平台。采用GIS“一张图”、巷道结点-路径拓扑算法、多源异构监测数据处理技术、矿压大数据分析技术,搭建成能够实现矿井下复杂情况切实反映、矿压监测数据有效提取、采掘风险在线预测、可视化程度高的矿压监测预警平台。通过在李雅庄矿的实际应用,表明该系统运行稳定可靠,可有效提升煤矿的矿压风险监测预警。