scholarly journals The Relationship Exploration between Public Migration Attention and Population Migration from a Perspective of Search Query

2020 ◽  
Vol 17 (7) ◽  
pp. 2388
Author(s):  
Chun Li ◽  
Jianhua He ◽  
Xingwu Duan
Keyword(s):  
High Efficiency ◽  
Optimal Allocation ◽  
Critical Factor ◽  
Population Migration ◽  
Search Query ◽  
Public Attention ◽  
Urban Network ◽  
Large Scope ◽  
Regional Sustainable Development

Rapid population migration has been viewed as a critical factor impacting urban network construction and regional sustainable development. The supervision and analysis of population migration are necessary for guiding the optimal allocation of urban resources and for attaining the high efficiency development of region. Currently, the explorations of population migration are often restricted by the limitation of data. In the information era, search engines widely collect public attention, implying potential individual actions, and freely provide open, timelier, and large-scope search query data for helping explore regional phenomena and problems. In this paper, we endeavor to explore the possibility of adopting such data to depict population migration. Based on the search query from Baidu search engine, three migration attention indexes (MAIs) are constructed to capture public migration attention in cyber space. Taking three major urban agglomerations in China as case study, we conduct the correlation analysis among the cyber MAIs and population migration in geographical space. Results have shown that external-MAI and local-MAI can positively reflect the population migration inner regions and across regions from a holistic lens and that intercity-MAI can be a helpful supplement for the delineation of specific population flow. Along with the accumulation of cyber search query data, its potential in exploring population migration can be further reinforced.

scholarly journals A Case Study of a Large Unstable Mass Stabilization: “El Portalet” Pass at the Central Spanish Pyrenees

2021 ◽  
Vol 11 (16) ◽  
pp. 7176
Author(s):  
Guillermo Cobos ◽  
Miguel Ángel Eguibar ◽  
Francisco Javier Torrijo ◽  
Julio Garzón-Roca
Keyword(s):  
Water Table ◽  
Critical Factor ◽  
Slope Stabilization ◽  
Survey Techniques ◽  
Geotechnical Investigations ◽  
Spanish Pyrenees ◽  
Parking Lot ◽  
Unstable Slope ◽  
Total Stability

This case study presents the engineering approach conducted for stabilizing a landslide that occurred at “El Portalet” Pass in the Central Spanish Pyrenees activated due to the construction of a parking lot. Unlike common slope stabilization cases, measures projected here were aimed at slowing and controlling the landslide, and not completely stopping the movement. This decision was taken due to the slow movement of the landslide and the large unstable mass involved. The degree of success of the stabilization measures was assessed by stability analyses and data obtained from different geotechnical investigations and satellite survey techniques such as GB-SAR and DinSAR conducted by different authors in the area under study. The water table was found to be a critical factor in the landslide’s stability, and the tendency of the unstable slope for null movement (total stability) was related to the water table lowering process, which needs more than 10 years to occur due to regional and climatic issues. Results showed a good performance of the stabilization measures to control the landslide, demonstrating the effectiveness of the approach followed, and which became an example of a good response to the classical engineering duality cost–safety.

Electric Vehicle Charger Placement Optimization in Michigan Considering Monthly Traffic Demand and Battery Performance Variations

2021 ◽  
pp. 036119812098195
Author(s):  
Fatemeh Fakhrmoosavi ◽  
MohammadReza Kavianipour ◽  
MohammadHossein (Sam) Shojaei ◽  
Ali Zockaie ◽  
Mehrnaz Ghamami ◽  
...  
Keyword(s):  
Optimal Allocation ◽  
Critical Factor ◽  
Cold Weather ◽  
Contributing Factors ◽  
Modeling Framework ◽  
Long Distance ◽  
Charging Infrastructure ◽  
Traffic Demand ◽  
Adverse Weather ◽  
Performance Variations

Limited charging infrastructure for electric vehicles (EVs) is one of the main barriers to adoption of these vehicles. In conjunction with limited battery range, the lack of charging infrastructure leads to range-anxiety, which may discourage many potential users. This problem is especially important for long-distance or intercity trips. Monthly traffic patterns and battery performance variations are two main contributing factors in defining the infrastructure needs of EV users, particularly in states with adverse weather conditions. Knowing this, the current study focuses on Michigan and its future needs to support the intercity trips of EVs across the state in two target years of 2020 and 2030, considering monthly traffic demand and battery performance variations. This study incorporates a recently developed modeling framework to suggest the optimal locations of fast EV chargers to be implemented in Michigan. Considering demand and battery performance variations is the major contribution of the current study to the proposed modeling framework by the same authors in the literature. Furthermore, many stakeholders in Michigan are engaged to estimate the input parameters. Therefore, the research study can be used by authorities as an applied model for optimal allocation of resources to place EV fast chargers. The results show that for charger placement, the reduced battery performance in cold weather is a more critical factor than the increased demand in warm seasons. To support foreseeable annual EV trips in Michigan in 2030, this study suggests 36 charging stations with 490 chargers and an investment cost of $23 million.

scholarly journals Optimal placement design for picking and packing in distribution centers

2021 ◽  
Vol 13 (4) ◽  
pp. 168781402110106
Author(s):  
John Rios ◽  
Rodrigo Linfati ◽  
Daniel Morillo-Torres ◽  
Iván Derpich ◽  
Gustavo Gatica
Keyword(s):  
Optimal Allocation ◽  
Programming Model ◽  
Operating Cost ◽  
Nonlinear Integer Programming ◽  
Operating Costs ◽  
Optimal Placement ◽  
Distribution Centers ◽  
Suitable Space ◽  
Efficient Distribution

An efficient distribution center (DC) is one that receives, stores, picks and packs products into new logistics units and then dispatches them to points of sale at the minimal operating cost. The picking and packing processes represent the highest operating cost of a DC, and both require a suitable space for their operation. An effective coordination between these zones prevents bottlenecks and has a direct impact on the DC’s operational results. In the existing literature, there are no studies that optimize the distribution of the picking and packing areas simultaneously while also reducing operating costs. This article proposes an integer nonlinear integer programming model that minimizes order preparation costs. It does so by predicting customer demand based on historical data and defining the ideal area for picking and packing activities. The model is validated through a real case study of seven clients and fifteen products. It achieves a [Formula: see text] reduction in operating costs when the optimal allocation of the picking and packing areas is made.

scholarly journals Neighborhood Energy Modeling and Monitoring: A Case Study

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3716
Author(s):  
Francesco Causone ◽  
Rossano Scoccia ◽  
Martina Pelle ◽  
Paola Colombo ◽  
Mario Motta ◽  
...  
Keyword(s):  
High Performance ◽  
High Efficiency ◽  
Early Stage ◽  
Energy Performance ◽  
Monitoring Plan ◽  
Performance Targets ◽  
Carrier Energy ◽  
Zero Carbon ◽  
Energy Grid

Cities and nations worldwide are pledging to energy and carbon neutral objectives that imply a huge contribution from buildings. High-performance targets, either zero energy or zero carbon, are typically difficult to be reached by single buildings, but groups of properly-managed buildings might reach these ambitious goals. For this purpose we need tools and experiences to model, monitor, manage and optimize buildings and their neighborhood-level systems. The paper describes the activities pursued for the deployment of an advanced energy management system for a multi-carrier energy grid of an existing neighborhood in the area of Milan. The activities included: (i) development of a detailed monitoring plan, (ii) deployment of the monitoring plan, (iii) development of a virtual model of the neighborhood and simulation of the energy performance. Comparisons against early-stage energy monitoring data proved promising and the generation system showed high efficiency (EER equal to 5.84), to be further exploited.

From Community to Public Familiarity: Neighborhood, Sociability, and Belonging in the Neoliberal City

2021 ◽  
pp. 107808742110215
Author(s):  
Felipe Link ◽  
Andrés Señoret ◽  
Felipe Valenzuela
Keyword(s):  
Social Relations ◽  
Sense Of Belonging ◽  
Regression Models ◽  
Secondary Data ◽  
Critical Factor ◽  
Urban Morphology ◽  
Demographic Characteristics ◽  
Logistic Regression Models ◽  
Pedestrian Space

Current urban neoliberalism processes have shaped and changed contemporary cities, including the local scale’s built environment and social relations. This article aims to study how such transformations affect local sociability by analyzing the effects of neighborhoods’ morphology and socio-demographic characteristics on different forms of interactions and how they affect the sense of belonging. Taking the Metropolitan Area of Santiago, Chile, as a case study, we gathered secondary data on urban morphology and surveyed ten neighborhoods to measure sociability patterns. The results obtained from multilevel logistic regression models show that time living in the neighborhood and public pedestrian space is the most critical factor affecting neighborhood sociability. Moreover, instead of local ties, public familiarity is the form of sociability with the most substantial effects on a sense of belonging. We conclude that recent neighborhoods, formed by neoliberal urbanization, tend to discourage neighborhood sociability and a sense of belonging.

scholarly journals Visualising Ostia’s Processional Landscape Through a Multi-Layered Computational Approach: Case Study of the Cult of the Magna Mater

2019 ◽  
Vol 5 (1) ◽  
pp. 444-467
Author(s):  
Katherine A. Crawford
Keyword(s):  
Network Analysis ◽  
Computational Approach ◽  
Urban Network ◽  
Agent Based ◽  
Agent Based Modelling ◽  
Existing Problems ◽  
Layered Approach ◽  
Religious Landscape ◽  
Insight Into

AbstractOstia, the ancient port of Rome, had a rich religious landscape. How processional rituals further contributed to this landscape, however, has seen little consideration. This is largely due to a lack of evidence that attests to the routes taken by processional rituals. The present study aims to address existing problems in studying processions by questioning what factors motivated processional movement routes. A novel computational approach that integrates GIS, urban network analysis, and agent-based modelling is introduced. This multi-layered approach is used to question how spectators served as attractors in the creation of a processional landscape using Ostia’s Campo della Magna Mater as a case study. The analysis of these results is subsequently used to gain new insight into how a greater processional landscape was created surrounding the sanctuary of the Magna Mater.

scholarly journals Equitable Allocation of Blue and Green Water Footprints Based on Land-Use Types: A Case Study of the Yangtze River Economic Belt

2018 ◽  
Vol 10 (10) ◽  
pp. 3556 ◽  
Author(s):  
Gang Liu ◽  
Lu Shi ◽  
Kevin Li
Keyword(s):  
Land Use ◽  
Water Resources ◽  
Agricultural Land ◽  
Optimal Allocation ◽  
Water Footprint ◽  
Agricultural Water ◽  
Land Area ◽  
Lexicographic Optimization ◽  
The Impact

This paper develops a lexicographic optimization model to allocate agricultural and non-agricultural water footprints by using the land area as the influencing factor. An index known as the water-footprint-land density (WFLD) index is then put forward to assess the impact and equity of the resulting allocation scheme. Subsequently, the proposed model is applied to a case study allocating water resources for the 11 provinces and municipalities in the Yangtze River Economic Belt (YREB). The objective is to achieve equitable spatial allocation of water resources from a water footprint perspective. Based on the statistical data in 2013, this approach starts with a proper accounting for water footprints in the 11 YREB provinces. We then determined an optimal allocation of water footprints by using the proposed lexicographic optimization approach from a land area angle. Lastly, we analyzed how different types of land uses contribute to allocation equity and we discuss policy changes to implement the optimal allocation schemes in the YREB. Analytical results show that: (1) the optimized agricultural and non-agricultural water footprints decrease from the current levels for each province across the YREB, but this decrease shows a heterogeneous pattern; (2) the WFLD of 11 YREB provinces all decline after optimization with the largest decline in Shanghai and the smallest decline in Sichuan; and (3) the impact of agricultural land on the allocation of agricultural water footprints is mainly reflected in the land use structure of three land types including arable land, forest land, and grassland. The different land use structures in the upstream, midstream, and downstream regions lead to the spatial heterogeneity of the optimized agricultural water footprints in the three YREB segments; (4) In addition to the non-agricultural land area, different regional industrial structures are the main reason for the spatial heterogeneity of the optimized non-agricultural water footprints. Our water-footprint-based optimal water resources allocation scheme helps alleviate the water resources shortage pressure and achieve coordinated and balanced development in the YREB.

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