Location-Aware Scheduling and Control of Linear Projects: Introducing Space-Time Float Prisms

Key scientific and application questions concern the relationships between individual-level activities and their effects on broader human phenomena, such as transportation systems and cities. Continuing advances in geographic information science, location-aware technologies, and geosimulation methods offer great potential for observational and simulation studies of human activities at high levels of spatiotemporal resolution. The author contributes by developing rigorous statements of the necessary space–time conditions for human interaction by extending a measurement theory for time geography. The extended measurement theory identifies necessary conditions both for physical and for virtual interaction. The theory suggests elegant and tractable solutions that can be derived from data available from location-aware technologies or geosimulation methods. These conditions and their solutions could be used to infer the possibilities for human interaction from detailed space–time trajectories and prisms generated from observation or simulation studies.

Download Full-text

Estimation and control performance for space-time point-process observations

IEEE Transactions on Automatic Control ◽

10.1109/tac.1977.1101534 ◽

1977 ◽

Vol 22 (3) ◽

pp. 338-346 ◽

Cited By ~ 24

Author(s):

I. Rhodes ◽

D. Snyder

Keyword(s):

Point Process ◽

Space Time ◽

Control Performance ◽

Estimation And Control ◽

And Control ◽

Time Point

Download Full-text

Global neural network for automated air space-time allocation and control

Proceedings of the 2004 IEEE International Conference on Computational Intelligence for Homeland Security and Personal Safety, 2004. CIHSPS 2004. ◽

10.1109/cihsps.2004.1360211 ◽

2004 ◽

Cited By ~ 4

Author(s):

B.N. Iordanova

Keyword(s):

Neural Network ◽

Time Allocation ◽

Space Time ◽

Air Space ◽

And Control

Download Full-text

Spatio-Temporal Patterns of Dengue Incidence in Medan City, North Sumatera, Indonesia

Tropical Medicine and Infectious Disease ◽

10.3390/tropicalmed6010030 ◽

2021 ◽

Vol 6 (1) ◽

pp. 30

Author(s):

Ayodhia Pitaloka Pasaribu ◽

Tsheten Tsheten ◽

Muhammad Yamin ◽

Yulia Maryani ◽

Fahmi Fahmi ◽

...

Keyword(s):

Control Strategies ◽

Public Health Problem ◽

Temporal Patterns ◽

Space Time ◽

Scan Statistic ◽

Cold Spots ◽

Spatio Temporal ◽

Dengue Control ◽

And Control ◽

Time Scan

Dengue has been a perennial public health problem in Medan city, North Sumatera, despite the widespread implementation of dengue control. Understanding the spatial and temporal pattern of dengue is critical for effective implementation of dengue control strategies. This study aimed to characterize the epidemiology and spatio-temporal patterns of dengue in Medan City, Indonesia. Data on dengue incidence were obtained from January 2016 to December 2019. Kulldorff’s space-time scan statistic was used to identify dengue clusters. The Getis-Ord Gi* and Anselin Local Moran’s I statistics were used for further characterisation of dengue hotspots and cold spots. Results: A total of 5556 cases were reported from 151 villages across 21 districts in Medan City. Annual incidence in villages varied from zero to 439.32 per 100,000 inhabitants. According to Kulldorf’s space-time scan statistic, the most likely cluster was located in 27 villages in the south-west of Medan between January 2016 and February 2017, with a relative risk (RR) of 2.47. Getis-Ord Gi* and LISA statistics also identified these villages as hotpot areas. Significant space-time dengue clusters were identified during the study period. These clusters could be prioritized for resource allocation for more efficient prevention and control of dengue.

Download Full-text

Fine-Scale Space-Time Cluster Detection of COVID-19 in Mainland China Using Retrospective Analysis

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18073583 ◽

2021 ◽

Vol 18 (7) ◽

pp. 3583

Author(s):

Min Xu ◽

Chunxiang Cao ◽

Xin Zhang ◽

Hui Lin ◽

Zhong Yao ◽

...

Keyword(s):

Retrospective Analysis ◽

Disease Incidence ◽

Mainland China ◽

Scale Space ◽

Space Time ◽

The Family ◽

Family Level ◽

The Usa ◽

Spatio Temporal ◽

And Control

Exploring spatio-temporal patterns of disease incidence can help to identify areas of significantly elevated or decreased risk, providing potential etiologic clues. The study uses the retrospective analysis of space-time scan statistic to detect the clusters of COVID-19 in mainland China with a different maximum clustering radius at the family-level based on case dates of onset. The results show that the detected clusters vary with the clustering radius. Forty-three space-time clusters were detected with a maximum clustering radius of 100 km and 88 clusters with a maximum clustering radius of 10 km from 2 December 2019 to 20 June 2020. Using a smaller clustering radius may identify finer clusters. Hubei has the most clusters regardless of scale. In addition, most of the clusters were generated in February. That indicates China’s COVID-19 epidemic prevention and control strategy is effective, and they have successfully prevented the virus from spreading from Hubei to other provinces over time. Well-developed provinces or cities, which have larger populations and developed transportation networks, are more likely to generate space-time clusters. The analysis based on the data of cases from onset may detect the start times of clusters seven days earlier than similar research based on diagnosis dates. Our analysis of space-time clustering based on the data of cases on the family-level can be reproduced in other countries that are still seriously affected by the epidemic such as the USA, India, and Brazil, thus providing them with more precise signals of clustering.

Download Full-text

Scheduling and control of linear projects

Canadian Journal of Civil Engineering ◽

10.1139/l94-025 ◽

1994 ◽

Vol 21 (2) ◽

pp. 219-230 ◽

Cited By ~ 18

Author(s):

Neil N. Eldin ◽

Ahmed B. Senouci

Keyword(s):

Dynamic Programming ◽

Programming Approach ◽

State Variables ◽

Project Schedule ◽

Numerical Illustration ◽

Total Cost ◽

Dynamic Programming Approach ◽

Completion Date ◽

And Control ◽

Linear Projects

A two-state-variable, N-stage dynamic programming approach to scheduling and control of linear projects is presented. This approach accounts for practical considerations related to work continuity, interruptions, and lags between successive activities. In the dynamic programming formulation, stages represent project activities and state variables represent possible activity resources and interruptions at each location. The objective of the dynamic programming solution is to provide for the selection of resources, interruptions, and lags for production activities that lead to the minimum project total cost. In addition, the presented system produces a graphical presentation of the optimum project schedule and updates the original schedule based on update information input by the user. The updated schedule determines the new completion date, and forecasts the project new total cost based on the current project performance. A small linear project is provided as a numerical illustration of the system. Key words: dynamic programming, linear projects, scheduling systems, optimization of cost and scheduling durations.

Download Full-text