An Efficient Mathematical Model to Process Data of Smart City

2014 ◽  
Author(s):  
Ye Li
Keyword(s):  
Mathematical Model ◽  
Smart City ◽  
Process Data

N-Tuple Algebra as a Unifying System to Process Data and Knowledge

2019 ◽  
pp. 602-615
Author(s):  
Boris Alexandrovich Kulik ◽  
Alexander Yakovlevich Fridman
Keyword(s):  
Mathematical Model ◽  
General Theory ◽  
Information Technologies ◽  
Heterogeneous Data ◽  
Process Data ◽  
Modeling Uncertainties ◽  
Unify Representation ◽  
Theoretical Generalization ◽  
Universal Structure

Information technologies for analysis and processing heterogeneous data often face the necessity to unify representation of such data. To solve this problem, it seems reasonable to search for a universal structure that would allow for reducing different formats of data and knowledge to a single mathematical model with unitized manipulation methods. The concept of relation looks very prospective in this sense. So, with a view to developing a general theory of relations, the authors propose n-tuple algebra (NTA) developed as a theoretical generalization of structures and methods applicable in intelligence systems. NTA allows for formalizing a wide set of logical problems (deductive, abductive and modified reasoning, modeling uncertainties, and so on).

scholarly journals Adaptación del sistema táctico de inteligencia para la toma de decisiones militares ante una pandemia

2021 ◽  
Vol 12 (26) ◽  
pp. 14-22
Author(s):  
Eider Yovanny Vargas
Keyword(s):  
Mathematical Model ◽  
Decision Maker ◽  
Administrative Support ◽  
Decision Makers ◽  
Rapid Adaptation ◽  
Process Data ◽  
The Face ◽  
Toma De Decisiones ◽  
The Military ◽  
Available Resources

The purpose of this work is to identify a tool that allows a military decision maker at the tactical level to manage the military resources available in the event of a pandemic. The research focused on finding and adapting an epidemiological mathematical model to process data collected in a military jurisdiction and with it the development of prospective scenarios in a military jurisdiction in the event of a pandemic. The results indicate that in the face of a pandemic, military decision makers must have a model of prospective scenarios and the adaptation of the intelligence process, especially the means of searching for information and the recording and analysis instruments to diligently manage the available resources. It is concluded that, given the appearance of a pandemic in a place with geographical conditions that hinder rapid accessibility and administrative support, military decision makers require a procedure that allows rapid adaptation to the new tactical scenario.

Smart City: The State of the Art, Definitions, Characteristics and Dimensions

2019 ◽  
Vol 16 (8) ◽  
pp. 3525-3531 ◽  
Author(s):  
Hemalata Vasudavan ◽  
Saraswathy Shamini Gunasekaran ◽  
Sumathi Balakrishnan
Keyword(s):  
Smart City ◽  
Smart Cities ◽  
Living Standard ◽  
Systematic Research ◽  
Process Data ◽  
Sustainable Living ◽  
Scarce Resources ◽  
Physical Infrastructure ◽  
Multidimensional Process ◽  
Universal Standard

The notion of smart city embrace from urbanization with the unceasing boom of population in a city. The rising population in cities require high demand on living standard, facilities and social sustainability, in fact, it is challenging for the existing scarce resources and services to complement the citizen’s needs and demand. Thus, the model of smart city emerges as a solution to strategically integrate people, process, data and computing technology. Technologies such as Internet of Things, Big Data and Cloud Computing can be integrated with physical infrastructure to support efficient resourceful services and assure sustainable living standard for the citizens. To transform a city into a smart city it involves a complex and multidimensional process which rapidly changes according to the citizen’s needs. Conversely, there is a lack of universal standard route in being smart and various cities has implemented many methods in understanding a smart city. This paper aims to produce a systematic research to comprehend the fundamental concept of smart city’s characteristics and dimensions. This research presents various literature definitions of smart cities, followed by commonly discussed smart city characteristics and dimensions.

N-Tuple Algebra as a Unifying System to Process Data and Knowledge

2018 ◽  
pp. 1995-2005
Author(s):  
Boris Alexandrovich Kulik ◽  
Alexander Yakovlevich Fridman
Keyword(s):  
Mathematical Model ◽  
General Theory ◽  
Information Technologies ◽  
Heterogeneous Data ◽  
Process Data ◽  
Modeling Uncertainties ◽  
Unify Representation ◽  
Theoretical Generalization ◽  
Universal Structure

Information technologies for analysis and processing heterogeneous data often face the necessity to unify representation of such data. To solve this problem, it seems reasonable to search for a universal structure that would allow for reducing different formats of data and knowledge to a single mathematical model with unitized manipulation methods. The concept of relation looks very prospective in this sense. So, with a view to developing a general theory of relations, the authors propose n-tuple algebra (NTA) developed as a theoretical generalization of structures and methods applicable in intelligence systems. NTA allows for formalizing a wide set of logical problems (deductive, abductive and modified reasoning, modeling uncertainties and so on).

scholarly journals Composting of mushroom substrate in a fermentation tunnel: compost parameters and a mathematical model

1994 ◽  
Vol 42 (4) ◽  
pp. 271-292 ◽  
Author(s):  
J.J.C. Van Lier ◽  
J.T. Van Ginkel ◽  
G. Straatsma ◽  
J.P.G. Gerrits ◽  
L.J.L.D. Van Griensven
Keyword(s):  
Mathematical Model ◽  
Time Course ◽  
Calculated Data ◽  
Oxygen Demand ◽  
Conductive Heat ◽  
Actual Process ◽  
Process Data ◽  
Continuous Simulation ◽  
Weight Losses ◽  
Air Stream

Phase II of composting of mushroom substrate was studied in bulk fermentation tunnels. Compost data are given on heat production, settling and mass reduction, porosity and thermal conductivity. Mass and moisture determinations at the end of the process indicated slightly positive gradients in the direction of the air stream. The highest rate of degradation occurred during the first 2 days. A mathematical model of mass and heat transfers was devised. Differential equations were solved with time-dependent analysis using a Continuous Simulation and Modelling Program (CSMP). In the calculations, the substrate was divided into theoretical layers of equal thickness but of different density and porosity. The model predicts the time-course of the process taking into account the moisture content and the filling height of the compost, and the amounts of supplied fresh air and recirculated air. The calculated data include the oxygen demand, the water and dry matter losses, the temperatures in the various layers, and the loss of conductive heat through the walls of the containers in the tunnel. Calculated data corresponded with actual process data. Temp. were correct within 3 degrees C and weight losses within 5%.

scholarly journals Mathematical model of evaluating the quality of “smart city” transport interchanges functioning

2019 ◽  
Vol 97 ◽  
pp. 01006 ◽  
Author(s):  
Margarita Panteleeva ◽  
Svetlana Borozdina
Keyword(s):  
Mathematical Model ◽  
Development Strategy ◽  
Transport System ◽  
Russian Federation ◽  
Smart City ◽  
System Development ◽  
General System ◽  
Management Decision ◽  
Uniform Motion ◽  
The Russian Federation

The analysis of government policy documents conducted by the authors allowed to establish that the Russian Federation Transport System Development Strategy until 2020, developed back in 2004, does not have a comprehensive and detailed toolkit for the implementation of all the goals and objectives presented in it, in particular, there are no current models of management decision-making at the Russian transport system development in a “smart city. The authors found that the effective management of traffic in a “smart city” should provide load transport network on the brink of its capacity and to maintain a continuous uniform motion, including the relatively low speeds, and increase the level of social development. This formulation of the problem proposed by the authors is fundamentally changing the construction of transport management systems, control algorithms and thus the model on which they are based, are not needed “smart city.” Thus, the authors of the article developed a mathematical model for evaluating the efficiency of transport interchanges in the general system of transport development in the Russian Federation, taking into account the requirements of the “smart city” concept and the growing social effect.

scholarly journals Spatio-temporal Bayesian Learning for Mobile Edge Computing Resource Planning in Smart Cities

2021 ◽  
Vol 21 (3) ◽  
pp. 1-21
Author(s):  
Laha Ale ◽  
Ning Zhang ◽  
Scott A. King ◽  
Jose Guardiola
Keyword(s):  
Smart City ◽  
Smart Cities ◽  
Resource Planning ◽  
Edge Computing ◽  
Mobile Edge Computing ◽  
Core Network ◽  
Process Data ◽  
Real World Data ◽  
Spatio Temporal ◽  
Iot Devices

A smart city improves operational efficiency and comfort of living by harnessing techniques such as the Internet of Things (IoT) to collect and process data for decision-making. To better support smart cities, data collected by IoT should be stored and processed appropriately. However, IoT devices are often task-specialized and resource-constrained, and thus, they heavily rely on online resources in terms of computing and storage to accomplish various tasks. Moreover, these cloud-based solutions often centralize the resources and are far away from the end IoTs and cannot respond to users in time due to network congestion when massive numbers of tasks offload through the core network. Therefore, by decentralizing resources spatially close to IoT devices, mobile edge computing (MEC) can reduce latency and improve service quality for a smart city, where service requests can be fulfilled in proximity. As the service demands exhibit spatial-temporal features, deploying MEC servers at optimal locations and allocating MEC resources play an essential role in efficiently meeting service requirements in a smart city. In this regard, it is essential to learn the distribution of resource demands in time and space. In this work, we first propose a spatio-temporal Bayesian hierarchical learning approach to learn and predict the distribution of MEC resource demand over space and time to facilitate MEC deployment and resource management. Second, the proposed model is trained and tested on real-world data, and the results demonstrate that the proposed method can achieve very high accuracy. Third, we demonstrate an application of the proposed method by simulating task offloading. Finally, the simulated results show that resources allocated based upon our models’ predictions are exploited more efficiently than the resources are equally divided into all servers in unobserved areas.

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