The Current Situation and Planning Strategy of Police Station Facilities in Megacities Under the Background of New Urbanization:A Case Study of Changping District in Beijing

In the process of new urbanization,the population of megacities is increasing rapidly,the scale of cities is expanding,and the supply of service facilities has been unable to meet the demand.As an important carrier of urban governance and urban management,the police station should properly deal with the existing problems in the urban police stations,and improve the quality of life of residents by optimizing urban service facilities,which is of great significance for the implementation of people-oriented new urbanization.Taking Changping District of Beijing as an example,this study pointed out that there were many problems in police stations in Changping District.For example,the area of land is not up to the standard,the service capacity is not up to the demand,and the facilities are not up to the demand.Then,three planning strategies:adjusting the planning standards of facilities,optimizing the spatial layout of facilities,and strengthening the later guarantee of facilities were put forward,so as to improve people’s satisfaction with life,promote the high-quality development of new urbanization,and provide reference for the supplement of service facilities in megacities.

A Possible Cause for Different Diurnal Variations of Warm Season Rainfall as Shown in Station Observations and TRMM 3B42 Data over the Southeastern Tibetan Plateau

In this study, records from a 3-yr intensified observational experiment at eight stations along the hillside of Seqilashan over the southeastern Tibetan Plateau were analyzed and combined with records at 28 routine observation stations in the Chinese National Meteorological Station Network to investigate the influences of station location on the different diurnal rainfall variations between station records and Tropical Rainfall Measuring Mission （TRMM） data products. The results indicate that the diurnal variation of warm season rainfall is closely related to location of stations. The prevailing nocturnal rainfall peak in observations at routine stations can be largely attributed to the relatively lower location of the stations, which are mostly situated in valleys. The records at Seqilashan stations on hillsides revealed an evident diurnal afternoon peak of warm season rainfall, similar to that indicated by TRMM data. The different diurnal phases between valley and hillside stations are closely related to the orographically induced regional circulations caused by the complex topography over the Tibetan Plateau. The results of this study indicate that the prevailing nocturnal rainfall associated with the relatively lower location of routine observation stations can partially explain the diurnal rainfall variations between observation station records and TRMM data.

A Two-Station Passive Locating Solution Independent of the Baseline Length

The two-station positioning system based on time difference and azimuth measurement has measurement redundancy. Therefore, not only can a positioning solution which is completely independent of the baseline length between two stations be derived, but also the baseline length can be solved as an unknown quantity. These findings not only enhance the performance of the two-station positioning system, but also provide a design basis for the construction of a self-organizing dynamic intelligent positioning system.

Automatic Driving Material Handling Vehicle Station Location and Scheduling Mathematical Modeling and Analysis

Traditional material handling vehicles often use internal combustion engines as their power source, which results in exhaust emissions that pollute the environment. In contrast, automated material handling vehicles have the advantages of zero emissions, low noise, and low vibration, thus avoiding exhaust pollution and providing a more comfortable working environment for operators. In order to achieve the goals of “peaking carbon emissions by 2030 and achieving carbon neutrality by 2060”, the use of environmentally friendly autonomous material handling vehicles for material transportation is an inevitable trend. To maximize the amount of transported materials, consider peak-to-valley electricity pricing, battery pack procurement, and the construction of charging and swapping stations while achieving “minimum daily transportation volume” and “lowest investment and operational cost over a 3-year settlement period” with the shortest overall travel distance for all material handling vehicles, this paper examines two different scenarios and establishes goal programming models. The appropriate locations for material handling vehicle swapping stations and vehicle battery pack scheduling schemes are then developed using the NSGA-II algorithm and ant colony optimization algorithm. The results show that, while ensuring a daily transportation volume of no less than 300 vehicles, the lowest investment and operational cost over a 3-year settlement period is approximately 24.1 million Yuan. The material handling vehicles follow the shortest path of 119.2653 km passing through the designated retrieval points and have two shortest routes. Furthermore, the advantages and disadvantages of the proposed models are analyzed, followed by an evaluation, deepening, and potential extension of the models. Finally, future research directions in this field are suggested.

Research on the Accurate Location of the 2007 M_S6.4 Ning'er, Yunnan Earthquake

Five mobile digital seismic stations were set up by the Earthquake Administration of Yunnan Province near the epicenter of the main shock after the Ning＇er M6. 4 earthquake on June 3, 2007. In this paper, the aftershock sequence of the Ning＇er M6. 4 earthquake is relocated by using the double difference earthquake location method. The data is from the 5 mobile digital seismic stations and the permanent Simao seismic station. The results show that the length of the aftershock sequence is 40kin and the width is 30km, concentrated obviously at the lateral displacement area between the Pu＇er fault and the NNE-trending faults, with the majority occurring on the Pu＇er fault around the main shock. The depths of aftershocks are from 2kin to 12km, and the predominant distribution is in the depth of 8 ~ 10km. The mean depth is 7. 9kin. The seismic fault dips to the northwest revealed from the profile parallel to this aftershock sequence, which is identical to the dip of the secondary fault of the NE-trending Menglian-Mojiang fault in the earthquake area. There are more earthquakes concentrated in the northwest segment than in the southeast segment, which is perhaps related to the underground medium and faults. The depth profile of the earthquake sequence shows that the relocated earthquakes are mainly located near the Pu＇er fault and the seismic faults dip to the southwest, consistent with the dip of the west branch of the Pu＇er fault. In all, the fault strike revealed by earthquake relocations matches well with the strike in the focal mechanism solutions. The main shock is in the top of the aftershock sequence and the aftershocks are symmetrically distributed, showing that faulting was complete in both the NE and SW directions.

A Multi-Objective Optimization for Locating Maintenance Stations and Operator Dispatching of Corrective Maintenance

In this study,we introduce a novel multi-objective optimization model tailored for modern manufacturing,aiming to mitigate the cost impacts of operational disruptions through optimized corrective maintenance.Central to our approach is the strategic placement of maintenance stations and the efficient allocation of personnel,addressing a crucial gap in the integration of maintenance personnel dispatching and station selection.Our model uniquely combines the spatial distribution of machinery with the expertise of operators to achieve a harmonious balance between maintenance efficiency and cost-effectiveness.The core of our methodology is the NSGA Ⅲ+Dispatch,an advanced adaptation of the Non-Dominated Sorting Genetic Algorithm Ⅲ(NSGA-Ⅲ),meticulously designed for the selection of maintenance stations and effective operator dispatching.This method integrates a comprehensive coding process,crossover operator,and mutation operator to efficiently manage multiple objectives.Rigorous empirical testing,including a detailed analysis from a taiwan region electronic equipment manufacturer,validated the effectiveness of our approach across various scenarios of machine failure frequencies and operator configurations.The findings reveal that the proposed model significantly outperforms current practices by reducing response times by up to 23%in low-frequency and 28.23%in high-frequency machine failure scenarios,leading to notable improvements in efficiency and cost reduction.Additionally,it demonstrates significant improvements in oper-ational efficiency,particularly in selective high-frequency failure contexts,while ensuring substantial manpower cost savings without compromising on operational effectiveness.This research significantly advances maintenance strategies in production environments,providing the manufacturing industry with practical,optimized solutions for diverse machine malfunction situations.Furthermore,the methodologies and principles developed in this study have potential applications in various other sectors,including healthcare,transportation,and energy,where maintenance efficiency and resource optimization are equally critical.

An envelope-based machine learning workflow for locating earthquakes in the southern Sichuan Basin

The development of machine learning technology enables more robust real-time earthquake monitoring through automated implementations. However, the application of machine learning to earthquake location problems faces challenges in regions with limited available training data. To address the issues of sparse event distribution and inaccurate ground truth in historical seismic datasets, we expand the training dataset by using a large number of synthetic envelopes that closely resemble real data and build an earthquake location model named ENVloc. We propose an envelope-based machine learning workflow for simultaneously determining earthquake location and origin time. The method eliminates the need for phase picking and avoids the accumulation of location errors resulting from inaccurate picking results. In practical application, ENVloc is applied to several data intercepted at different starting points. We take the starting point of the time window corresponding to the highest prediction probability value as the origin time and save the predicted result as the earthquake location. We apply ENVloc to observed data acquired in the southern Sichuan Basin, China, between September 2018 and March 2019. The results show that the average difference with the catalog in latitude, longitude, depth, and origin time is 0.02°,0.02°, 2 km, and 1.25 s, respectively. These suggest that our envelope-based method provides an efficient and robust way to locate earthquakes without phase picking, and can be used in earthquake monitoring in near-real time.

Location and Capacity Determination Method of Electric Vehicle Charging Station Based on Simulated Annealing Immune Particle Swarm Optimization

As the number of electric vehicles(EVs)continues to grow and the demand for charging infrastructure is also increasing,how to improve the charging infrastructure has become a bottleneck restricting the development of EVs.In other words,reasonably planning the location and capacity of charging stations is important for development of the EV industry and the safe and stable operation of the power system.Considering the construction and maintenance of the charging station,the distribution network loss of the charging station,and the economic loss on the user side of the EV,this paper takes the node and capacity of charging station planning as control variables and the minimum cost of system comprehensive planning as objective function,and thus proposes a location and capacity planning model for the EV charging station.Based on the problems of low efficiency and insufficient global optimization ability of the current algorithm,the simulated annealing immune particle swarm optimization algorithm(SA-IPSO)is adopted in this paper.The simulated annealing algorithm is used in the global update of the particle swarm optimization(PSO),and the immune mechanism is introduced to participate in the iterative update of the particles,so as to improve the speed and efficiency of PSO.Voronoi diagram is used to divide service area of the charging station,and a joint solution process of Voronoi diagram and SA-IPSO is proposed.By example analysis,the results show that the optimal solution corresponding to the optimisation method proposed in this paper has a low overall cost,while the average charging waiting time is only 1.8 min and the charging pile utilisation rate is 75.5%.The simulation comparison verifies that the improved algorithm improves the operational efficiency by 18.1%and basically does not fall into local convergence.

A Prediction Method of Charging Station Planning Based on BP Neural Network

The construction of charging service facilities is a very important factor in the popularization of electric vehicles. Therefore, the planning problems of electric vehicle charging station are urgent to be solved. Considering the standard of natural environment, society, traffic, power grid and economy, an evaluation system is created for electric vehicle charging station project through 15 sub-standards. Planning model of charging station is constructed based on BP neural network adopted in the analysis. It is used for location and capacity prediction of charging station planning. By analyzing the model with data samples, a stable network structure is established and the feasibility of the model is verified in the charging station planning.

Assessment of Locational Compliance Status of Petroleum Products Handling Facilities in Niger Delta Region, Nigeria

This study was aimed at assessing the locational compliance status of petroleum handling facilities in the Niger Delta to the specifications of the Nigerian Upstream Petroleum Regulatory Commission (NUPRC) locational standards. A cross-sectional research design was employed using a Standard checklist of seventeen compliance specifications of NUPRC. A walk-through survey was carried out in 118 identified facilities in three locations: Eket in Akwa-Ibom State, Port Harcourt in Rivers State and Warri in Delta State, respectively. The data obtained were analyzed using inferential and descriptive statistics, Kendall Tau-B and Principal Component analyses. The results indicate that the Petroleum Product facilities complied with 6 (35.29%) out of 17 specifications while 11 (64.70%) specifications were violated. Locations compliance of stations in the Niger Delta region is generally poor, but Stations in Port Harcourt recorded a higher compliance rate compared to Eket and Warri. Results of Kendall’s tau-b and Principal Component analysis indicated positive association between all the land space locational compliances. This study attributes the poor compliance rate to rapid urbanization, overpopulation, proliferation of filling stations and poor monitoring by regulatory agencies. It is recommended that, NUPRC should improve its monitoring and enforce regulatory operational specifications.

Location correction technique based on mobile communication base station for earthquake population heat map

China has mobile phone penetration rate of over 96.2%.Mobile phone has become the largest Internet terminal for Chinese Internet users.Population geographic distribution in earthquake zones can be got based on mobile phone positioning and map matching.For reducing earthquake black-box stage,we propose a real-time collection,correction and schedule algorithm of population position data by four stream processing environments(Redis,Hbase,Kafka,and Spark Streaming)in this paper.For labeling precisely population geographic distribution on the network map,matching of population geographic coordinates and map coordinates are optimized by sample comparison based on location data of mobile communication base stations and prefecture level cities.The test result shows the proposed system is high efficient and can rapidly respond to any emerging parallel tasks during the earthquake.A high-precision heat map of affected population can be produced and published on-line within 2 min after the devastating earthquake happened.

A Two-Objective Integer Programming Model for the Location of Waste Transfer Station and Landfill in IoT Environment: Shenzhen City is Taken as an Example

In the traditional environment, the factors for considering the location of the waste transfer station and the landfill are relatively fixed, and the scale of the problem is small. But in Internet of Things(IoT) environment, the waste storage in the household waste can be monitored in real time, the environmental data can be collected by means of emerging information technology, and the residents are more sensitive to the environmental pollution of the waste. Under such conditions, the method for location of traditional waste disposal facilities needs to be redeveloped to obtain a waste transfer station and landfill site that are suitable for the IoT environment. For this reason, a two-objective integer programming model is designed. The two objectives are lowest cost and minimum impact of waste on residents. The expectations of city managers and residents are considered into the modeling. Through the simulation experiments on different scale problems, the integration method for integer programming model and simulation system is verified to solve the location of waste transfer stations in IoT environment.

基于大数据和无线网络的采摘机器人定位技术研究

分析了5G无线网络定位原理,提出了单基站定位技术和加权质心的5G定位技术,设计了采摘机器人定位系统硬件部分,并基于大数据和无线网络实现了采摘机器人定位系统。试验结果表明:系统具有较好的定位精度,优于单基站定位方法精度,且其定位曲线与北斗定位设备曲线拟合度非常高,稳定性较好。

Bilevel Optimal Infrastructure Planning Method for the Inland Battery Swapping Stations and Battery-Powered Ships

Green shipping and electrification have been the main topics in the shipping industry.In this process,the pure battery-powered ship is developed,which is zero-emission and well-suited for inland shipping.Currently,battery swapping stations and ships are being explored since battery charging ships may not be feasible for inland long-distance trips.However,improper infrastructure planning for battery swapping stations and ships will increase costs and decrease operation efficiency.Therefore,a bilevel optimal infrastructure planning method is proposed in this paper for battery swapping stations and ships.First,the energy consumption model for the battery swapping ship is established considering the influence of the sailing environment.Second,a bilevel optimization model is proposed to minimize the total cost.Specifically,the battery swapping station(BSS)location problem is investigated at the upper level.The optimization of battery size in each battery swapping station and ship and battery swapping scheme are studied at the lower level based on speed and energy optimization.Finally,the bilevel self-adaptive differential evolution algorithm(BlSaDE)is proposed to solve this problem.The simulation results show that total cost could be reduced by 5.9%compared to the original results,and the effectiveness of the proposed method is confirmed.

Malicious Base Station and Detecting Malicious Base Station Signal

This paper introduces the background,illustrates the hardware structure and software features of malicious base station,explains its work principle,presents a method of detecting malicious base station,analyses the experiment and evaluates the experimental results to verify the reliability of this method.Finally proposes the future work.

P2P &LBS Technology-Based Mobile Police System Design

With the coverage by the mobile network and the popularization of mobile phone communication software, the traditional voice communication, short message service and even the interconnection service have gradually been replaced by mobile terminal equipment. Confronted with the ever-increasingly serous information explosion, police authorities meet with new challenges in their daily police work. This paper establishes a mobile police application system integrating office work, early warning, publicity and surveillance through careful study of the Peer to Peer and Location Based technology, striving to transform the traditional idea, break the traditional mode, expand the tradition scope so as to better exercise the social supervision function, publicize precaution information and crack down on crime.

A Doppler Location Method Based on Virtual Path Difference

This paper presents a Doppler passive location method for moving targets with fixed single station using the Doppler frequency shift and time difference information.First,based on the relationship between frequency shift and path difference,the virtual path difference is calculated from the measured value of Doppler frequency shift by means of mean value correction.Then,under the assumption that the target is moving at a constant speed along a straight line,two coaxial virtual double base arrays are constructed by using the moving track of the moving target based on the method of fixed period time difference.On this basis,the moving distance of the moving target can be calculated by using the ratio relationship between the frequency difference and the radial distance between the two adjacent detection points in the middle of the array,and the linear solution of the two double base path difference positioning equations.At this point,the relative coordinate position of the moving target can be obtained by directly using the linear solution of the double base path difference positioning equation again.

基于鲁棒优化的电动汽车充电站点流融合选址模型

随着电池技术的发展,电动汽车续航里程日益增长,用户充电行为从在途充电逐渐向目的地充电转变,形成了以点需求为主、流需求为辅的综合需求模式。因此,规划充电设施选址需同时考虑点需求和流需求,以便设施布局与充电需求模式能够充分匹配,提高设施利用率。将经典选址理论中的集合覆盖模型与截流模型相结合,提出了一种能够服务综合充电需求的点流融合选址模型。考虑到充电需求的不确定性,采用鲁棒优化方法,以最小化充电设施建设和电力设备扩容总成本为目标,建立了需求不确定情形下的鲁棒选址模型,并通过对模型做等价对偶转换进行求解。最后,针对两个路网算例开展了数值分析,结果表明,与传统单一需求选址模型相比,本文提出的点流融合模型能在充分覆盖不同类型充电需求的情形下有效降低充电设施的总体规划成本。

多机动站交叉定位系统精度分析及优化

针对多机动站交叉定位系统观测站具有机动能力的应用特点,从测向交叉定位技术的定位原理入手,分析了影响定位精度的因素,以4站交叉定位系统为例,按目标大致分布区域已知且布设阵地条件不受限制、基于任务需求观测站需机动的随机布站两种典型应用场景,提出了根据目标分布区域优化布站阵型、根据既定阵型优化数据处理算法两种定位优化方法。在不额外增加观测站的条件下,有效提升定位精度、增大有效定位区域。该方法成本代价小、技术难度低、定位效果好,具有较好的应用推广价值。

计及电能量-备用耦合的配电网与光储充电站协调优化调度方法

针对光储充电站大规模接入给配电网带来的调控压力,提出一种计及电能量和备用耦合的配电网与光储充电站协调优化调度方法。首先,建立基于随机机会约束的光储充电站经济调度模型,得到光储充电站与配电网的电能交互方案和备用需求;随后,采用鲁棒经济调度-线性潮流方法,建立计及不确定性的配电网优化调度模型,并根据Karush-Kuhn-Tucker(KKT)条件推导得到配电节点边际电价和节点备用边际电价,通过电能量和备用价格引导光储充电站友好互动,挖掘站内储能在削峰填谷和备用调节上的潜力。最后,通过算例分析验证了所提方法的有效性。