Delivery Service Management System Using Google Maps for SMEs in Emerging Countries

This paper proposes a Delivery Service Management(DSM)system for Small and Medium Enterprises(SMEs)that own a delivery fleet of pickup trucks to manage Business-to-Business(B2B)delivery services.The proposed DSM system integrates four systems:Delivery Location Positioning(DLP),Delivery Route Planning(DRP),Arrival Time Prediction(ATP),and Communication and Data Sharing(CDS)systems.These systems are used to pinpoint the delivery locations of customers,plan the delivery route of each truck,predict arrival time(with an interval)at each delivery location,and communicate and share information among stakeholders,respectively.The DSM system deploys Google applications,a GPS tracking system,Google Map APIs,ATP algorithms(embedded in Excel Macros),Line,and Telegram as supporting tools.To improve the accuracy of the ATP system,three tech-niques are applied considering driver behaviors.The proposed DSM system has been implemented in a Thai SME.From the process perspective,the DSM system is a systematic procedure for end-to-end delivery services.It allows the interactions between planner-driver decisions and supporting tools.The supporting tools are simple,can be easily used with little training,and require low capital expenditure.The statistical analysis shows that the ATP algorithm with the three techniques provides high accuracy.Thus,the proposed DSM system is beneficial for practitioners to manage delivery services,especially for SMEs in emerging countries.

Visualization Techniques viaMLBS for Personnel Management in Major Events

Mobile location-based services(MLBS)refer to services around geographic location data.Mobile terminals use wireless communication networks(or satellite positioning systems)to obtain users’geographic location coordinate information based on spatial databases and integrate with other information to provide users with required location-related services.The development of systems based on MLBS has significance and practical value.In this paper a visualization management information system for personnel in major events based on microservices,namely MEPMIS,is designed and implemented by using MLBS.The system consists of a server and a client app,and it has some functions including map search and query,personnel positioning and scheduling,location management,messaging,and location service.Managers of the events can quickly search and locate the staff on the specific area of the map in real-time,and make broadcasting messages to the staff,and manage the staff.The client app is developed on the Android system,by which staff users can send the positions information to the server timely.The client users can search fuzzily near their peers and list their locations,and also call near peers through sending messages or query the history record of staff locations.In the design of the system,several new proposed techniques,including visual annotation method for overlapping locations,correcting trajectory drift algorithm,microservices-based overall system architecture methodology and other new techniques,which are applied to the implementation of the system.Also,HTML5,JQuery,MLBS APIs(Application Program Interfaces)related programming techniques have been used and combined with loading Ajax asynchronously and Json data encapsulation,map marker optimization techniques,that can improve the positioning accuracy and the performance of the system.The developed system with practical functions can enhance the efficiencies of the organization and management of major events.

Decoding the inconsistency of six cropland maps in China

Accurate cropland information is critical for agricultural planning and production,especially in foodstressed countries like China.Although widely used medium-to-high-resolution satellite-based cropland maps have been developed from various remotely sensed data sources over the past few decades,considerable discrepancies exist among these products both in total area and in spatial distribution of croplands,impeding further applications of these datasets.The factors influencing their inconsistency are also unknown.In this study,we evaluated the consistency and accuracy of six cropland maps widely used in China in circa 2020,including three state-of-the-art 10-m products(i.e.,Google Dynamic World,ESRI Land Cover,and ESA WorldCover)and three 30-m ones(i.e.,GLC_FCS30,GlobeLand 30,and CLCD).We also investigated the effects of landscape fragmentation,climate,and agricultural management.Validation using a ground-truth sample revealed that the 10-m-resolution WorldCover provided the highest accuracy(92.3%).These maps collectively overestimated Chinese cropland area by up to 56%.Up to 37%of the land showed spatial inconsistency among the maps,concentrated mainly in mountainous regions and attributed to the varying accuracy of cropland maps,cropland fragmentation and management practices such as irrigation.Our work shed light on the promotion of future cropland mapping efforts,especially in highly inconsistent regions.

A multi-layered policy generation and management engine for semantic policy mapping in clouds

The long awaited cloud computing concept is a reality now due to the transformation of computer generations.However,security challenges have become the biggest obstacles for the advancement of this emerging technology.A well-established policy framework is defined in this paper to generate security policies which are compliant to requirements and capabilities.Moreover,a federated policy management schema is introduced based on the policy definition framework and a multi-level policy application to create and manage virtual clusters with identical or common security levels.The proposed model consists in the design of a well-established ontology according to security mechanisms,a procedure which classifies nodes with common policies into virtual clusters,a policy engine to enhance the process of mapping requests to a specific node as well as an associated cluster and matchmaker engine to eliminate inessential mapping processes.The suggested model has been evaluated according to performance and security parameters to prove the efficiency and reliability of this multilayered engine in cloud computing environments during policy definition,application and mapping procedures.

Topic Maps Based Project Knowledge Management

Based on topic maps, a preprocessing scheme using similarity comparision is presented and applied in knowledge management. Topic and occurrence-ofiented merging algorithm is also introduced to implement knowledge integration for the sub-system. AnOm- nigator-supported example from an aeroaustic institute is utilised to validate the preprocessing method and the result indicates it can speed up the research schedule.

Management Tasks of Assessing Subjective Road Traffic Noise With Using Acoustic Maps—A New Approach

At present,acoustic maps are used in management tasks of assessing the acoustic climate of the environment.The methods of modeling and simulation of noise assessment indices are used for this purpose.These indicators represent the quantitative spatial distribution of the sound level.Research on the perception of sounds has been carried out for many years and it has been found out that subjective acoustic impressions are of significant importance.This paper proposes a quantitative and qualitative approach to the assessment of noise in the urbanized environment using acoustic maps.The features of sound quality and their importance in the modeling of noise annoyance assessment have been described.Acoustic measurements were made on the example of the selected case study in the environment.The results of modeling physical indicators of road noise in the environment with the use of acoustic maps are presented.Based on the registered acoustic measurements,the results of the sound quality features of the acoustic signals in the time and frequency domain are presented below.The determined values of sound quality features are a valuable source of information in the field of noise perception assessment.A model for assessing road noise has been proposed.It includes sound quality features which can be used in acoustic maps.As part of the discussion of the results,it was found that the obtained results of quantitative and qualitative analysis of the acoustic signal parameters can be the basis for the development of the road traffic noise annoyance assessment model using acoustic maps technology.

European Broad-Scale Seabed Habitat Maps Support Implementation of Ecosystem-Based Management

We have analyzed the development of “Broad-Scale Seabed Habitat Maps” (BSHM) and their potential use in a European context with regard to the EU Marine Strategy Framework Directive (MSFD) implementation, MPA designation and network assessment as well as other applications of BSHMs. The analyses are anchored in BSHMs developed by a series of interlinked EU projects (e.g. UKSeaMap, BALANCE, MESH, Mesh Atlantic, EUSeaMap 2012, and EUSeaMap 2016) and all maps are based on environmental data. Some EU Member States have used BSHMs as part of their MSFD Initial Assessments published in 2012. However, we conclude that BSHMs are a prerequisite for another key MSFD activity, i.e. mapping of potentially cumulative effects of multiple human stressors. Further, BSHMs seem to play a growing role with regard to evidence-based assessments of MPAs. With the upcoming second round of MSFD Initial Assessments due in 2018, including assessment of potentially cumulative pressures, there seems to be an increasing need for more BSHMs nationally, regionally and on a European scale.

Remote Monitoring of Wheat Streak Mosaic Progression Using Sub-Pixel Classification of Landsat 5 TM Imagery for Site Specific Disease Management in Winter Wheat

Wheat streak mosaic (WSM), caused by Wheat streak mosaic virus is a viral disease that affects wheat (Triticum aestivum L.), other grains, and numerous grasses over large geographical areas around the world. To improve disease management and crop production, it is essential to have adequate methods for monitoring disease epidemics at various scales and multiple times. Remote sensing has become an essential tool for monitoring and quantifying crop stress due to biotic and abiotic factors. The objective of our study was to explore the utility of Landsat 5 TM imagery for detecting, quantifying, and mapping the occurrence of WSM in irrigated commercial wheat fields. The infection and progression of WSM was biweekly assessed in the Texas Panhandle during the 2007-2008 crop years. Diseased-wheat was separated from uninfected wheat on the images using a sub-pixel classifier. The overall classification accuracies were >91% with kappa coefficient between 0.80 and 0.94 for disease detection were achieved. Omission errors varied between 2% and 14%, while commission errors ranged from 1% to 21%. These results indicate that the TM image can be used to accurately detect and quantify disease for site-specific WSM management. Remote detection of WSM using geospatial imagery may substantially improve monitoring, planning, and management practices by overcoming some of the shortcomings of the ground-based surveys such as observer bias and inaccessibility. Remote sensing techniques for accurate disease mapping offer a unique set of advantages including repeatability, large area coverage, and cost-effectiveness over the ground-based methods. Hence, remote detection is particularly and practically critical for repeated disease mo- nitoring and mapping over time and space during the course of a growing season.

Satellite remote-sensing technologies used in forest fire management

Satellite remote sensing has become a primary data source for fire danger rating prediction, fuel and fire mapping, fire monitoring, and fire ecology research. This paper summarizes the research achievements in these research fields, and discusses the future trend in the use of satellite remote-sensing techniques in wildfire management. Fuel-type maps from remote-sensing data can now be produced at spatial and temporal scales quite adequate for operational fire management applications. US National Oceanic and Atmospheric Administration (NOAA) and Moderate Resolution Imaging Spectroradiometer (MODIS) satellites are being used for fire detection worldwide due to their high temporal resolution and ability to detect fires in remote regions. Results can be quickly presented on many Websites providing a valuable service readily available to fire agency. As cost-effective tools, satellite remote-sensing techniques play an important role in fire mapping. Improved remote-sensing techniques have the potential to date older fire scars and provide estimates of burn severity. Satellite remote sensing is well suited to assessing the extent of biomass burning, a prerequisite for estimating emissions at regional and global scales, which are needed for better understanding the effects of fire on climate change. The types of satellites used in fire research are also discussed in the paper. Suggestions on what remote-sensing efforts should be completed in China to modernize fire management technology in this country are given.

A Practical Group Key Management Algorithm for Cloud Data Sharing with Dynamic Group

Cloud data sharing service, which allows a group of people to work together to access and modify the shared data, is one of the most popular and efficient working styles in the enterprises. However, the cloud server is not completely trusted, and its security could be compromised by monetary reasons or caused by hacking and hardware errors. Therefore, despite of having advantages of scalability and flexibility, cloud storage service comes with privacy and the security concerns. A straightforward method to protect the user's privacy is to encrypt the data stored at the cloud. To enable the authenticated users to access the encrypted cloud data, a practical group key management algorithm for the cloud data sharing application is highly desired. The existing group key management mechanisms presume that the server is trusted. But, the cloud data service mode does not always meet this condition. How to manage the group keys to support the scenario of the cloud storage with a semi-trusted cloud server is still a challenging task. Moreover, the cloud storage system is a large-scale and open application, in which the user group is dynamic. To address this problem, we propose a practical group key management algorithm based on a proxy re-encryption mechanism in this paper. We use the cloud server to act as a proxy tore-encrypt the group key to allow authorized users to decrypt and get the group key by their private key. To achieve the hierarchical access control policy, our scheme enables the cloud server to convert the encrypted group key of the lower group to the upper group. The numerical analysis and experimental results further validate the high efficiency and security of the proposed scheme.

International Cooperation on Space-Based Information for Disaster Management:Status and Perspectives

With the development of space technology, space-based information has become one of the important information resources for decision makers, and as such has played a key role during the major disasters which occurred worldwide in recent years. With global climate change and frequently occurring disasters, space-based

基于Teigha.NET和MapWinGIS的多源异构测绘数据管理系统设计与实现

遥感和计算机技术为传统测绘行业带来了新的发展机遇,测绘观测手段的多样化使得测绘数据种类逐渐增加,形成了海量的多源异构数据。传统数据存储管理方式难以有效支撑大数据的存储和高效处理分析,为解决这一难题,本研究提出了一种多源异构数据统一整合方法。采用C#语言、PostgreSQL数据库、MapWinGIS二次开发和Teigha.NET二次开发等多种开发手段,并结合混合编程方式开发了多源异构测绘数据管理系统。系统完全使用开源软件进行二次开发,脱离了AutoCAD等商业软件环境,针对不同空间基准、不同格式的测绘数据,实现了多源异构数据的结构转换及坐标转换,对多源异构测绘数据的存储和有效利用具有一定的参考价值。

一种使用Flash阵列存储数据的方法研究

在航空航天领域,随着飞行器性能的提升,研制过程中试验所需的数据存储量和数据存储速度也在不断提高。该文基于高速大容量数据存储的目的,利用FPGA的强大数据处理能力,进行Flash存储阵列及流水线管理的设计,并针对Flash阵列坏块检测和突发坏块提出了对应处理方法。通过对不同组合方式的存储阵列速度及存储容量进行研究对比,得到了一种使用Flash阵列进行高速数据存储的设计方法。相较单片存储,设计的存储阵列数据存储容量和速度成倍增加,且存储阵列的有效块利用率在99%以上。

思维导图联合清单式管理在原发性下肢静脉曲张围术期病人中的应用

目的:探讨思维导图联合清单式管理在原发性下肢静脉曲张围术期病人中的应用效果。方法:选取2022年4月—12月某三级甲等医院血管外科原发性下肢静脉曲张行手术治疗的124例病人作为研究对象,采用随机数字表法将病人分为观察组和对照组各62例;对照组实施下肢静脉曲张常规护理,观察组病人采用思维导图联合清单式管理进行专科护理及健康宣教;两组病人均于术后12周填写护理满意度调查问卷、慢性静脉功能不全病人生活质量问卷(CIVIQ-14),比较两组病人术后12周护理满意度及生活质量的变化。结果:术后12周观察组病人护理满意度高于对照组(P=0.008),疼痛、身体体能、心理维度及生活质量总分均高于对照组(P<0.01)。结论:思维导图联合清单式管理在原发性下肢静脉曲张围术期病人中应用有良好的效果,能有效提升病人满意度及术后生活质量。

基于多码对照的物资管理系统对低值医用耗材全链条精细化管理研究

目的:构建基于多码对照的物资管理系统,实现低值医用耗材采购、入库、出库、科室使用和计费之间联动统一。方法:分析低值医用耗材管理中存在的问题、原因及现状,采用物资编码、价表编码和医保编码对照统一的方法,设置出入库管理、采购管理、查询统计及智能监控等模块,构建基于多码对照的物资管理系统,以科室出库联动计价规范低值医用耗材收费。选取2022年7月解放军总医院普通外科、重症医学科等临床科室的300名医护人员进行问卷调查,对比基于多码对照的物资管理系统应用前后低值医用耗材请领准确性、目录管理标准化、计价与出库对照准确性、库存管理便捷性和数据监管精确性的评分差异性。结果:基于多码对照的物资管理系统实现了低值医用耗材采购、入库、出库、科室出库和计价之间的联动统一。系统应用后的请领准确性、目录管理标准化、计价与出库对照准确性、库存管理便捷性和数据监管精确性平均评分分别为(4.12±0.67)分、(4.78±0.52)分、(4.48±0.63)分、(4.78±0.33)分和(4.66±0.52)分,均高于应用前,差异有统计学意义(t=4.13、7.22、5.12、8.12、7.56,P<0.05)。结论:基于多码对照的物资管理系统应用能够实现低值医用耗材全链条精细化管理,提高耗材使用效率,规范低值医用耗材收费,降低耗材成本。

基于高精度地图的智能网联技术师资培训探究——以《交通管理与控制》为例

在智能化、网联化的大环境下,随着相关政策落地和人才市场的需求,导致高校教师理论和实践技能遇到新的挑战,因此交通智能技术领域的教育教学改革也将成为必然的趋势。据此,文章首先简要介绍了基于高精度地图的智能网联技术的发展现状,随后围绕该新型技术对人才的需求探讨了该专业教学领域师资现状以及存在的问题,最后结合交通工程专业核心课程《交通管理与控制》对教师队伍的建设和培训给予了建议和意见,为更好地构建以高精度地图为基础的智能网联技术专业师资队伍提供借鉴。

水利信息管理平台设计与实现

随着信息化的发展,在面对海量信息管理方面,传统管理方式和手段已无法胜任。本文以启东市为例,采用HTML5+GIS构建了水利信息管理平台,通过平台对多源数据进行综合管理、分析,快速、全面地掌握水利设施的分布情况、运行状态,使水利管理人员能够更加方便地对各种水利设施空间信息进行可视化管理,并结合水利管理业务和技术应用需要,为水利管理决策分析提供科学依据。

新时期基础测绘规划省市县联动协同编研刍议

基础测绘是基础性、公益性事业,国家对基础测绘实行分级管理。立足于机构改革后基础测绘在自然资源管理格局中的职责定位、工作重点,以及如何更好地履行新《测绘法》赋予的法定职责,分析了新形势下基础测绘的发展现状和面临的形势,提出了基础测绘“十四五”规划省市县一体化协同编研的主要遵循和具体思路,据此明确了工作重点和任务举措,相关观点已在广东省、惠州市及其各县区基础测绘“十四五”规划编制中得到了应用。

上海农用地一张图精准化管理系统研究与实现

根据国家乡村振兴战略和上海农业数字化转型工作的要求,本文分析了上海农用地一张图精准化管理的需求,设计了相应的管理更新流程,并基于天地图上海的相关数据资源研究和实现了包含农用地一张图信息的收集、上报、审核和更新等功能的精准化管理系统,实现了农用地一张图的实时化、精准化的管理。