Principles and Concepts of Agent-Based Modelling for Developing Geospatial Simulations

The aim of this paper is to outline fundamental concepts and principles of the Agent-Based Modelling (ABM) paradigm, with particular reference to the development of geospatial simulations. The paper begins with a brief definition of modelling, followed by a classification of model types, and a comment regarding a shift (in certain circumstances) towards modelling systems at the individual-level. In particular, automata approaches (e.g. Cellular Automata, CA, and ABM) have been particularly popular, with ABM moving to the fore. A definition of agents and agent-based models is given; identifying their advantages and disadvantages, especially in relation to geospatial modelling. The potential use of agent-based models is discussed, and how-to instructions for developing an agent-based model are provided. Types of simulation / modelling systems available for ABM are defined, supplemented with criteria to consider before choosing a particular system for a modelling endeavour. Information pertaining to a selection of simulation / modelling systems (Swarm, MASON, Repast, StarLogo, NetLogo, OBEUS, AgentSheets and AnyLogic) is provided, categorised by their licensing policy (open source, shareware / freeware and proprietary systems). The evaluation (i.e. verification, calibration, validation and analysis) of agent-based models and their output is examined, and noteworthy applications are discussed.Geographical Information Systems (GIS) are a particularly useful medium for representing model input and output of a geospatial nature. However, GIS are not well suited to dynamic modelling (e.g. ABM). In particular, problems of representing time and change within GIS are highlighted. Consequently, this paper explores the opportunity of linking (through coupling or integration / embedding) a GIS with a simulation / modelling system purposely built, and therefore better suited to supporting the requirements of ABM. This paper concludes with a synthesis of the discussion that has proceeded. The aim of this paper is to outline fundamental concepts and principles of the Agent-Based Modelling (ABM) paradigm, with particular reference to the development of geospatial simulations. The paper begins with a brief definition of modelling, followed by a classification of model types, and a comment regarding a shift (in certain circumstances) towards modelling systems at the individual-level. In particular, automata approaches (e.g. Cellular Automata, CA, and ABM) have been particularly popular, with ABM moving to the fore. A definition of agents and agent-based models is given; identifying their advantages and disadvantages, especially in relation to geospatial modelling. The potential use of agent-based models is discussed, and how-to instructions for developing an agent-based model are provided. Types of simulation / modelling systems available for ABM are defined, supplemented with criteria to consider before choosing a particular system for a modelling endeavour. Information pertaining to a selection of simulation / modelling systems (Swarm, MASON, Repast, StarLogo, NetLogo, OBEUS, AgentSheets and AnyLogic) is provided, categorised by their licensing policy (open source, shareware / freeware and proprietary systems). The evaluation (i.e. verification, calibration, validation and analysis) of agent-based models and their output is examined, and noteworthy applications are discussed.Geographical Information Systems (GIS) are a particularly useful medium for representing model input and output of a geospatial nature. However, GIS are not well suited to dynamic modelling (e.g. ABM). In particular, problems of representing time and change within GIS are highlighted. Consequently, this paper explores the opportunity of linking (through coupling or integration / embedding) a GIS with a simulation / modelling system purposely built, and therefore better suited to supporting the requirements of ABM. This paper concludes with a synthesis of the discussion that has proceeded

Agile software development and service science

This paper shows the necessary steps, which should be taken in order to get the most out of agile software development in interdisciplinary settings involving scientific experts. If applied properly, Agile delivers increased productivity, higher quality and, last but not least, higher customer satisfaction. The task of developing high quality software is already difficult. Developing software for a new IT-enabled service in an interdisciplinary team however, is even more challenging. In interdisciplinary projects scientific experts from different fields need to work together with computer scientists, developers, testers, business analysts and domain experts. Software engineering is very time-consuming and scientific experts who have never been involved in a software project, often find it hard to understand why progress sometimes seems so slow. Therefore, it is important that they understand what it takes to write high- quality code, i.e. code that is clean, tested, documented and extendable at the right points. The best way to achieve this goal is to expand the software team, make the scientific experts an integral part of it and thus profit from their know-how

Evolution of the Modern ODE Course

The rapid development of technology in the latter part of the twentieth century has revolutionized the teaching of differential equations. In this paper we will try to trace the evolution of this important change. We tried to include the most important efforts in this regard, but we apologize in advance if some efforts have slipped our attention

Agile Software Development and Service Science How to develop IT-enabled Services in an Interdisciplinary Environment

This paper shows the necessary steps, which should be taken in order to get the most out of agile software development in interdisciplinary settings involving scientific experts. If applied properly, Agile delivers increased productivity, higher quality and, last but not least, higher customer satisfaction. The task of developing high quality software is already difficult. Developing software for a new IT-enabled service in an interdisciplinary team however, is even more challenging.In interdisciplinary projects scientific experts from different fields need to work together with computer scientists, developers, testers, business analysts and domain experts. Software engineering is very time-consuming and scientific experts who have never been involved in a software project, often find it hard to understand why progress sometimes seems so slow. Therefore, it is important that they understand what it takes to write high-quality code, i.e. code that is clean, tested, documented and extendable at the right points. The best way to achieve this goal is to expand the software team, make the scientific experts an integral part of it and thus profit from their know-how

An intersemiotic translation of normative utterances to machine language

Programming Languages (PL) effectively performs an intersemiotic translation from a natural language to machine language. PL comprises a set of instructions to implement algorithms, i.e., to perform (computational) tasks. Similarly to Normative Languages (NoL), PLs are formal languages that can perform both regulative and constitutive functions. The paper presents the first results of interdisciplinary research aimed at highlighting the similarities between NoL (social sciences) and PL (computer science) through everyday life examples, exploiting Object-Oriented Programming Language tools and an Internet of Things (IoT) system as a case study. Given the pandemic emergency, the urge to move part of our social life to the digital world arose, together with the need to effectively transpose regulative rules and constitutive rules through different strategies for translating a normative utterance expressed in natural language

PROMOTING THE USE OF MOBILE DEVICES FOR E-LEARNING SOLUTIONS: DEVELOPING AN ANDROID APP FOR NATIONAL OPEN UNIVERSITY OF NIGERIA

E-Learning is a broad and relatively novel concept that covers the use of electronic devices in delivering formal education. This research work aims to consider some of the diversities entailed and some of the specific ways that electronic devices can promote learning. Of particular interest is the use of mobile devices, considering the contemporary surge in smartphones and the roles these can play in individualized learning. The shift in possibilities, as well as the seemingly endless options available, are some of the concepts explored in this work. The android app developed is primarily to show the prospects of establishments such as National Open University of Nigeria (NOUN) which offer strictly open and distance learning that mobile devices can be used to promote learning. This will be shown to be innumerable and could easily validate many more studies in this field. The application (app) developed in this project was for an android device, which by far is the most common mobile operating system available presently. The procedure involved the use of android studio which provides an environment for coding and testing apps on an android phone. The widespread preference, as well as the ubiquitous occurrence of android based smartphones, was the factor behind this platform choice

Multisensor Data Fusion Implementation for a Sensor Based Fertilizer Application System

"Mapping systems" (“mapping approach”), real-time sensor-actuator systems ("sensor approach") or the combination of both (“Real-time approach with map overlay”) determine the process control in mobile application systems for spatially variable fertilization. Within the integrated research project “Information Systems Precision Farming Duernast” (IKB Duernast) the implementation of the “Real-time approach with map overlay” was done for intensive nitrogen fertilization. The bottom line of this sophisticated approach is a comprehensive situation assessment, a typical multisensor data fusion task. Based on a functional and procedural modelling of the multisensor data fusion and decision making process, it could be pointed out that an expert system is an adequate fusion paradigm and algorithm. Therefore, a software simulation with an expert system as core element was implemented to fuse on-line sensor technology measurements (REIP), maps (yield, EM38, environmental constraints, draft force) and user inputs in order to derive an application set point in real-time. The development of an expert system can be viewed as a structured transformation in five levels from the “specification level”, the “task level”, the “problem solving level” and the “knowledge base level” to the “tool level”. In the “tool level” the hybrid expert system shell JESS (Java Expert System Shell) was selected for implementation due to the results of preceding levels. Knowledge acquisition was done within another IKB-subproject by the means of data mining. Typical and maximal times of 10 ms and 60 ms for one fusion cycle were measured running this application on a 32-bit processor hardware (Intel Pentium III Mobile, 1 GHz)

BiplotGUI: Interactive Biplots in R

Biplots simultaneously provide information on both the samples and the variables of a data matrix in two- or three-dimensional representations. The BiplotGUI package provides a graphical user interface for the construction of, interaction with, and manipulation of biplots in R. The samples are represented as points, with coordinates determined either by the choice of biplot, principal coordinate analysis or multidimensional scaling. Various transformations and dissimilarity metrics are available. Information on the original variables is incorporated by linear or non-linear calibrated axes. Goodness-of-fit measures are provided. Additional descriptors can be superimposed, including convex hulls, alpha-bags, point densities and classification regions. Amongst the interactive features are dynamic variable value prediction, zooming and point and axis drag-and-drop. Output can easily be exported to the R workspace for further manipulation. Three-dimensional biplots are incorporated via the rgl package. The user requires almost no knowledge of R syntax.

Evolution of Software Engineering in the Changing Scenario of Modern Hardware Architecture, Semantic Web and Cloud Computing Platform

Traditional way of software engineering is no longer fully suitable in the changing scenario of modern hardwareand software architecture of parallel and distributed computing on Semantic web and Cloud computing platform. A parallelhardware architecture can support high performance computing but needs changes in programming style. Also the capabilityof Semantic web can link everything on the internet making an interoperable intelligent system. And with this capabilitymany beneficial business models like Web services and Cloud computing platform have been conceptualized. Cloudcomputing is the most anticipated future trend of computing. These changes in hardware and software architecture means weneed to re-visit the traditional software engineering process models meant for a single computer system. This paper firstsurveys the evolution of hardware architecture, newer business models, newer software applications and then analyses theneed for changes in software engineering process models to leverage all the benefits of the newer business models. Thispaper also emphasizes the vulnerability of the web applications and cloud computing platform in terms of risk managementof web applications in general and privacy and security of customer information in shared cloud platform which maythreaten the adoption of the cloud platform.Keywords/Index Terms— Agile Process Model , Cloud Computing Platform, Privacy and Security Issues, RiskManagement, Semantic Web, Software Evolution