Gravity Model of Passenger and Mobility Fleet Origin–Destination Patterns with Partially Observed Service Data

2021 ◽  
pp. 036119812199207
Author(s):  
Brian Yueshuai He ◽  
Joseph Y. J. Chow
Keyword(s):  
Gravity Model ◽  
Large Scale ◽  
Smart Cities ◽  
Transportation Network ◽  
Real Data ◽  
Small Scale ◽  
Entropy Maximization ◽  
Limited Mobility ◽  
Mobility Data ◽  
City Agencies

Mobility-as-a-service systems are becoming increasingly important in the context of smart cities, with challenges arising for public agencies to obtain data from private operators. Only limited mobility data are typically provided to city agencies, which are not enough to support their decision-making. This study proposed an entropy-maximizing gravity model to predict origin–destination patterns of both passenger and mobility fleets with only partial operator data. An iterative balancing algorithm was proposed to efficiently reach the entropy maximization state. With different trip length distributions data available, two calibration applications were discussed and validated with a small-scale numerical example. Tests were also conducted to verify the applicability of the proposed model and algorithm to large-scale real data from Chicago transportation network companies. Both shared-ride and single-ride trips were forecast based on the calibrated model, and the prediction of single-ride has a higher level of accuracy. The proposed solution and calibration algorithms are also efficient to handle large scenarios. Additional analyses were conducted for north and south sub-areas of Chicago and revealed different travel patterns in these two sub-areas.

scholarly journals The Usefulness of Video Learning Analytics in Small Scale E-Learning Scenarios

2021 ◽  
Vol 11 (21) ◽  
pp. 10366
Author(s):  
César Córcoles ◽  
Germán Cobo ◽  
Ana-Elena Guerrero-Roldán
Keyword(s):  
Learning Process ◽  
Teaching And Learning ◽  
Large Scale ◽  
Real Data ◽  
Small Scale ◽  
E Learning ◽  
Learning Scenarios ◽  
Real Scenario ◽  
Teaching Learning ◽  
Learning Data

A variety of tools are available to collect, process and analyse learning data obtained from the clickstream generated by students watching learning resources in video format. There is also some literature on the uses of such data in order to better understand and improve the teaching-learning process. Most of the literature focuses on large scale learning scenarios, such as MOOCs, where videos are watched hundreds or thousands of times. We have developed a solution to collect clickstream analytics data applicable to smaller scenarios, much more common in primary, secondary and higher education, where videos are watched tens or hundreds of times, and to analyse whether the solution is useful to teachers to improve the learning process. We have deployed it in a real scenario and collected real data. Furthermore, we have processed and presented the data visually to teachers for those scenarios and have collected and analysed their perception of their usefulness. We conclude that the collected data are perceived as useful by teachers to improve the teaching and learning process.

scholarly journals Edge-Based Missing Data Imputation in Large-Scale Environments

Information ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 195
Author(s):  
Davide Andrea Guastella ◽  
Guilhem Marcillaud ◽  
Cesare Valenti
Keyword(s):  
Urban Environment ◽  
Large Scale ◽  
Smart Cities ◽  
Low Cost ◽  
Real Data ◽  
Missing Data Imputation ◽  
Large Scale Data ◽  
Iot Devices ◽  
Edge Based ◽  
The One

Smart cities leverage large amounts of data acquired in the urban environment in the context of decision support tools. These tools enable monitoring the environment to improve the quality of services offered to citizens. The increasing diffusion of personal Internet of things devices capable of sensing the physical environment allows for low-cost solutions to acquire a large amount of information within the urban environment. On the one hand, the use of mobile and intermittent sensors implies new scenarios of large-scale data analysis; on the other hand, it involves different challenges such as intermittent sensors and integrity of acquired data. To this effect, edge computing emerges as a methodology to distribute computation among different IoT devices to analyze data locally. We present here a new methodology for imputing environmental information during the acquisition step, due to missing or otherwise out of order sensors, by distributing the computation among a variety of fixed and mobile devices. Numerous experiments have been carried out on real data to confirm the validity of the proposed method.

scholarly journals Modeling and Observer-Based Monitoring of RAFT Homopolymerization Reactions

Processes ◽  
2019 ◽  
Vol 7 (10) ◽  
pp. 768 ◽  
Author(s):  
Patrick M. Lathrop ◽  
Zhaoyang Duan ◽  
Chen Ling ◽  
Yossef A. Elabd ◽  
Costas Kravaris
Keyword(s):  
Experimental Data ◽  
Large Scale ◽  
Raft Polymerization ◽  
Reaction Times ◽  
Real Data ◽  
Size Exclusion ◽  
Rate Coefficients ◽  
Small Scale ◽  
Late Reaction ◽  
Exclusion Chromatography

Reversible addition–fragmentation chain–transfer (RAFT) polymerization of methyl methacrylate (MMA) is modeled and monitored using a multi-rate multi-delay observer in this work. First, to fit the RAFT reaction rate coefficients and the initiator efficiency in the model, in situ 1 H nuclear magnetic resonance (NMR) experimental data from small-scale (<2 mL) NMR tube reactions is obtained and a least squares optimization is performed. 1 H NMR and size exclusion chromatography (SEC) experimental data from large-scale (>400 mL) reflux reactions is then used to validate the fitted model. The fitted model accurately predicts the polymer properties of the large-scale reactions with slight discordance at late reaction times. Based on the fitted model, a multi-rate multi-delay observer coupled with an inter-sample predictor and dead time compensator is designed, to account for the asynchronous multi-rate measurements with non-constant delays. The multi-rate multi-delay observer shows perfect convergence after a few sampling times when tested against the fitted model, and is in fair agreement with the real data at late reaction times when implemented based on the experimental measurements.

scholarly journals Getting Real: The Challenge of Building and Validating a Large-Scale Digital Twin of Barcelona’s Traffic with Empirical Data

2021 ◽  
Vol 11 (1) ◽  
pp. 24
Author(s):  
Javier Argota Sánchez-Vaquerizo
Keyword(s):  
Big Data ◽  
Empirical Data ◽  
Large Scale ◽  
Smart Cities ◽  
Digital Twin ◽  
Fine Grained ◽  
Mobility Data ◽  
Digital Twins ◽  
Alternative Scenarios ◽  
Hourly Distribution

Large-scale microsimulations are increasingly resourceful tools for analysing in detail citywide effects and alternative scenarios of our policy decisions, approximating the ideal of ‘urban digital twins’. Yet, these models are costly and impractical, and there are surprisingly few published examples robustly validated with empirical data. This paper, therefore, presents a new large-scale agent-based traffic microsimulation for the Barcelona urban area using SUMO to show the possibilities and challenges of building these scenarios based on novel fine-grained empirical big data. It combines novel mobility data from real cell phone records with conventional surveys to calibrate the model comparing two different dynamic assignment methods for getting an operationally realistic and efficient simulation. Including through traffic and the use of a stochastic adaptive routing approach results in a larger 24-hour model closer to reality. Based on an extensive multi-scalar evaluation including traffic counts, hourly distribution of trips, and macroscopic metrics, this model expands and outperforms previous large-scale scenarios, which provides new operational opportunities in city co-creation and policy. The novelty of this work relies on the effective modelling approach using newly available data and the realistic robust evaluation. This allows the identification of the fundamental challenges of simulation to accurately capture real-world dynamical systems and to their predictive power at a large scale, even when fed by big data, as envisioned by the digital twin concept applied to smart cities.

scholarly journals BIG MOBILITY DATA ANALYTICS FOR TRAFFIC MONITORING AND CONTROL

2020 ◽  
Vol 19 (2) ◽  
pp. 087
Author(s):  
Natalija Stojanović ◽  
Dragan Stojanović
Keyword(s):  
Traffic Congestion ◽  
Large Scale ◽  
Smart Cities ◽  
Heavy Traffic ◽  
Traffic Monitoring ◽  
Monitoring And Control ◽  
Dynamic Configuration ◽  
Large Cities ◽  
Traffic Lights ◽  
Mobility Data

With the overpopulation of large cities, the problems with citizens’ mobility, transport inefficiency, traffic congestions and environmental pollution caused by the heavy traffic require advanced ITS solutions to be overcome. Recent advances and wide proliferation of mobile and Internet of Things (IoT) devices, carried by people, built in vehicles and integrated in a road infrastructure, enable collection of large scale data related to mobility and traffic in smart cities, still with a limited use in real world applications. In this paper, we propose the traffic monitoring, control and adaptation platform, named TrafficSense, based on Big Mobility Data processing and analytics. It provides a continuous monitoring of a traffic situation and detection of important traffic parameters, conditions and events, such as travel times along the street segments and traffic congestions in real time. Upon detecting a traffic congestion on an intersection, the TrafficSense application leverages the feedback control loop mechanism to provide a traffic adaptation based on the dynamic configuration of traffic lights duration in order to increase the traffic flows in critical directions at the intersections. We tested and evaluated the developed application on the distributed cloud computing infrastructure. By varying the streaming workload and the cluster parameters we show the feasibility and applicability of our approach and the platform.

Small-Scale Science to Large-Scale Profession

2000 ◽  
Vol 45 (4) ◽  
pp. 396-398
Author(s):  
Roger Smith
Keyword(s):  
Large Scale ◽  
Small Scale

Development of Physics Learning Module Based on Guided Inquiry with Light Wave Material in Class XI of Senior High School

2020 ◽  
Vol 1 (1) ◽  
pp. 1-10
Author(s):  
Evi Rahmawati ◽  
Irnin Agustina Dwi Astuti ◽  
N Nurhayati
Keyword(s):  
Large Scale ◽  
Learning Strategy ◽  
Student Response ◽  
Average Score ◽  
Small Scale ◽  
Design Development ◽  
Teacher Response ◽  
Student Responses ◽  
Analysis Design ◽  
Scientific Skills

IPA Integrated is a place for students to study themselves and the surrounding environment applied in daily life. Integrated IPA Learning provides a direct experience to students through the use and development of scientific skills and attitudes. The importance of integrated IPA requires to pack learning well, integrated IPA integration with the preparation of modules combined with learning strategy can maximize the learning process in school. In SMP 209 Jakarta, the value of the integrated IPA is obtained from 34 students there are 10 students completed and 24 students are not complete because they get the value below the KKM of 68. This research is a development study with the development model of ADDIE (Analysis, Design, Development, Implementation, and Evaluation). The use of KPS-based integrated IPA modules (Science Process sSkills) on the theme of rainbow phenomenon obtained by media expert validation results with an average score of 84.38%, average material expert 82.18%, average linguist 75.37%. So the average of all aspects obtained by 80.55% is worth using and tested to students. The results of the teacher response obtained 88.69% value with excellent criteria. Student responses on a small scale acquired an average score of 85.19% with highly agreed criteria and on the large-scale student response gained a yield of 86.44% with very agreed criteria. So the module can be concluded receiving a good response by the teacher and students.

Planetary gentrification and urban (re)development

2019 ◽  
Vol 61 (1) ◽  
pp. 5-13 ◽  
Author(s):  
Loretta Lees
Keyword(s):  
Low Income ◽  
Policy Making ◽  
Large Scale ◽  
Urban Redevelopment ◽  
Urban Transformation ◽  
Small Scale ◽  
Income Groups ◽  
Low Income Groups

Abstract Gentrification is no-longer, if it ever was, a small scale process of urban transformation. Gentrification globally is more often practised as large scale urban redevelopment. It is state-led or state-induced. The results are clear – the displacement and disenfranchisement of low income groups in favour of wealthier in-movers. So, why has gentrification come to dominate policy making worldwide and what can be done about it?

AGRICULTURAL PRODUCTION OF CA DONG PEOPLE IN RESETTLEMENT AREA OF TRANH RIVER HYDROPOWER NUMBER 2: CURRENT SITUATION AND IMPACT FACTORS

2020 ◽  
Vol 9 (2) ◽  
Author(s):  
Bùi Thị Bích Lan
Keyword(s):  
Social Relations ◽  
Agricultural Production ◽  
Large Scale ◽  
Transition Process ◽  
Impact Factors ◽  
Small Scale ◽  
Scale Production ◽  
Technical Application ◽  
Production Models ◽  
Role Of The State

In Vietnam, the construction of hydropower projects has contributed significantly in the cause of industrialization and modernization of the country. The place where hydropower projects are built is mostly inhabited by ethnic minorities - communities that rely primarily on land, a very important source of livelihood security. In the context of the lack of common productive land in resettlement areas, the orientation for agricultural production is to promote indigenous knowledge combined with increasing scientific and technical application; shifting from small-scale production practices to large-scale commodity production. However, the research results of this article show that many obstacles in the transition process are being posed such as limitations on natural resources, traditional production thinking or the suitability and effectiveness of scientific - technical application models. When agricultural production does not ensure food security, a number of implications for people’s lives are increasingly evident, such as poverty, preserving cultural identity, social relations and resource protection. Since then, it has set the role of the State in researching and building appropriate agricultural production models to exploit local strengths and ensure sustainability.

Managing the impacts of mining on Ghana’s water resources from a legal perspective

2018 ◽  
Vol 1 (3) ◽  
pp. 156-165 ◽  
Author(s):  
Nasirudeen Abdul Fatawu
Keyword(s):  
Surface Water ◽  
Water Resources ◽  
Environmental Protection Agency ◽  
Large Scale ◽  
Small Scale ◽  
Mining Activities ◽  
Protection Agency ◽  
Environmental Laws ◽  
Mining Areas ◽  
Legal Perspective

Recent floods in Ghana are largely blamed on mining activities. Not only are lives lost through these floods, farms andproperties are destroyed as a result. Water resources are diverted, polluted and impounded upon by both large-scale minersand small-scale miners. Although these activities are largely blamed on behavioural attitudes that need to be changed, thereare legal dimensions that should be addressed as well. Coincidentally, a great proportion of the water resources of Ghana arewithin these mining areas thus the continual pollution of these surface water sources is a serious threat to the environmentand the development of the country as a whole. The environmental laws need to be oriented properly with adequate sanctionsto tackle the impacts mining has on water resources. The Environmental Impact Assessment (EIA) procedure needs to bestreamlined and undertaken by the Environmental Protection Agency (EPA) and not the company itself.

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