Integrative Biological Chemistry Program Includes The Use Of Informatics Tools, GIS And SAS Software Applications

Wesley College is a private, primarily undergraduate minority-serving institution located in the historic district of Dover, Delaware (DE). The College recently revised its baccalaureate biological chemistry program requirements to include a one-semester Physical Chemistry for the Life Sciences course and project-based experiential learning courses using instrumentation, data-collection, data-storage, statistical-modeling analysis, visualization, and computational techniques. In this revised curriculum, students begin with a traditional set of biology, chemistry, physics, and mathematics major core-requirements, a geographic information systems (GIS) course, a choice of an instrumental analysis course or a statistical analysis systems (SAS) programming course, and then, students can add major-electives that further add depth and value to their future post-graduate specialty areas. Open-sourced georeferenced census, health and health disparity data were coupled with GIS and SAS tools, in a public health surveillance system project, based on US county zip-codes, to develop use-cases for chronic adult obesity where income, poverty status, health insurance coverage, education, and age were categorical variables. Across the 48 contiguous states, obesity rates are found to be directly proportional to high poverty and inversely proportional to median income and educational achievement. For the State of Delaware, age and educational attainment were found to be limiting obesity risk-factors in its adult population. Furthermore, the 2004-2010 obesity trends showed that for two of the less densely populated Delaware counties; Sussex and Kent, the rates of adult obesity were found to be progressing at much higher proportions when compared to the national average

From SpaceStat to CyberGIS: Twenty Years of Spatial Data Analysis Software

This essay assesses the evolution of the way in which spatial data analytical methods have been incorporated into software tools over the past two decades. It is part retrospective and prospective, going beyond a historical review to outline some ideas about important factors that drove the software development, such as methodological advances, the open source movement and the advent of the internet and cyberinfrastructure. The review highlights activities carried out by the author and his collaborators and uses SpaceStat, GeoDa, PySAL and recent spatial analytical web services developed at the ASU GeoDa Center as illustrative examples. It outlines a vision for a spatial econometrics workbench as an example of the incorporation of spatial analytical functionality in a cyberGIS.

Reduced-rank spatio-temporal modeling of air pollution concentrations in the Multi-Ethnic Study of Atherosclerosis and Air Pollution

There is growing evidence in the epidemiologic literature of the relationship between air pollution and adverse health outcomes. Prediction of individual air pollution exposure in the Environmental Protection Agency (EPA) funded Multi-Ethnic Study of Atheroscelerosis and Air Pollution (MESA Air) study relies on a flexible spatio-temporal prediction model that integrates land-use regression with kriging to account for spatial dependence in pollutant concentrations. Temporal variability is captured using temporal trends estimated via modified singular value decomposition and temporally varying spatial residuals. This model utilizes monitoring data from existing regulatory networks and supplementary MESA Air monitoring data to predict concentrations for individual cohort members. In general, spatio-temporal models are limited in their efficacy for large data sets due to computational intractability. We develop reduced-rank versions of the MESA Air spatio-temporal model. To do so, we apply low-rank kriging to account for spatial variation in the mean process and discuss the limitations of this approach. As an alternative, we represent spatial variation using thin plate regression splines. We compare the performance of the outlined models using EPA and MESA Air monitoring data for predicting concentrations of oxides of nitrogen (NO$_x$)-a pollutant of primary interest in MESA Air-in the Los Angeles metropolitan area via cross-validated $R^2$. Our findings suggest that use of reduced-rank models can improve computational efficiency in certain cases. Low-rank kriging and thin plate regression splines were competitive across the formulations considered, although TPRS appeared to be more robust in some settings.Comment: Published in at http://dx.doi.org/10.1214/14-AOAS786 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

FogGIS: Fog Computing for Geospatial Big Data Analytics

Cloud Geographic Information Systems (GIS) has emerged as a tool for analysis, processing and transmission of geospatial data. The Fog computing is a paradigm where Fog devices help to increase throughput and reduce latency at the edge of the client. This paper developed a Fog-based framework named Fog GIS for mining analytics from geospatial data. We built a prototype using Intel Edison, an embedded microprocessor. We validated the FogGIS by doing preliminary analysis. including compression, and overlay analysis. Results showed that Fog computing hold a great promise for analysis of geospatial data. We used several open source compression techniques for reducing the transmission to the cloud.Comment: 6 pages, 4 figures, 1 table, 3rd IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics (09-11 December, 2016) Indian Institute of Technology (Banaras Hindu University) Varanasi, Indi

Ontological Foundations for Geographic Information Science

We propose as a UCGIS research priority the topic of “Ontological Foundations for Geographic Information.” Under this umbrella we unify several interrelated research subfields, each of which deals with different perspectives on geospatial ontologies and their roles in geographic information science. While each of these subfields could be addressed separately, we believe it is important to address ontological research in a unitary, systematic fashion, embracing conceptual issues concerning what would be required to establish an exhaustive ontology of the geospatial domain, issues relating to the choice of appropriate methods for formalizing ontologies, and considerations regarding the design of ontology-driven information systems. This integrated approach is necessary, because there is a strong dependency between the methods used to specify an ontology, and the conceptual richness, robustness and tractability of the ontology itself. Likewise, information system implementations are needed as testbeds of the usefulness of every aspect of an exhaustive ontology of the geospatial domain. None of the current UCGIS research priorities provides such an integrative perspective, and therefore the topic of “Ontological Foundations for Geographic Information Science” is unique

A Review on the Application of Natural Computing in Environmental Informatics

Natural computing offers new opportunities to understand, model and analyze the complexity of the physical and human-created environment. This paper examines the application of natural computing in environmental informatics, by investigating related work in this research field. Various nature-inspired techniques are presented, which have been employed to solve different relevant problems. Advantages and disadvantages of these techniques are discussed, together with analysis of how natural computing is generally used in environmental research.Comment: Proc. of EnviroInfo 201

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

Solution of the problem to optimize two-stage allocation of the material flows

Purpose is to elaborate innovative and computationally efficient algorithm to solve a problem of two-stage allocation of the resource occupying continuously the specified area as well as to demonstrate the behaviour of the corresponding software developed with the application of advanced geoinformation resources. Methods. The paper involves mathematical models of continuous problems of optimal set partitioning with additional connections to describe two-stage problems of the material resource location-allocation. Methodological approach to the solution of such problems is based on the idea of their reducing to the problem of infinite-dimensional mathematical programming for which it is possible to obtain optimal solution in the analytical form with the help of the duality theory apparatus. Findings. Mathematical and algorithmic apparatus to solve continuous problems applied for the fuel and energy complex enterprises has been developed making it possible to obtain partitioning of the deposit area into the zones, which are allocated to the first-stage enterprises exclusively. The algorithm operation is demonstrated in terms of the model problem solution. It has been defined that the benefit of such an approach is in the reducing of the infinite-dimensional programming problem to the problem of finite-dimensional nonsmoth optimization since the obtained computational formulas contain the parameters which determination requires solving the auxiliary problem of the nondifferentiable function optimization. Originality. Contrary to the previously developed one, the proposed algorithm does not stipulate solution of the linear programming problem of transport type at each step of the iteration process. Such a problem is solved only once to find the volumes of product transportation between the first-stage and second-stage enterprises after defining all the optimal solution components. Practical implications. Software implementation of the algorithm on the basis of the advanced geoinformation technologies and resources, in terms of the solution of raw material flow allocation, makes it possible to reduce total costs for the management of material flows and their accompanying service flows throughout the whole logistic chain beginning from the flow origin up to its arrival to the end user.Мета. Розробка нового, ефективного з обчислювальної точки зору, алгоритму вирішення двоетапної задачі розподілу ресурсу, що безперервно займає задану область, а також демонстрація роботи відповідного програмного забезпечення, створеного із застосуванням сучасних геоінформаційних ресурсів. Методика. У роботі використано математичні моделі безперервних задач оптимального розбиття множин з додатковими зв’язками для опису двоетапних задач розміщення-розподілу матеріальних ресурсів. Методичний підхід вирішення таких задач заснований на ідеї зведення їх до задач нескінченномірного математичного програмування, для яких, в свою чергу, за допомогою застосування апарату теорії подвійності оптимальне рішення вдається отримати в аналітичному вигляді. Результати. Розроблено математичний і алгоритмічний апарати вирішення безперервних задач у застосуванні до підприємств паливно-енергетичного комплексу, що дозволяє отримувати розбиття району родовища на зони, за якими підприємства першого етапу закріплюються монопольно. Робота алгоритму показана на прикладі вирішення модельної задачі. Визначено, що виграшем описаного підходу є зведення задачі нескінченномірного програмування до задачі кінцево-мірної негладкою оптимізації, оскільки отримані розрахункові формули містять параметри, для визначення яких потрібно вирішити допоміжну задачу оптимізації недиференційованої функції. Наукова новизна. Представлений алгоритм, на відміну від раніше розробленого, не передбачає вирішення задачі лінійного програмування транспортного типу на кожному кроці ітераційного процесу. Така задача вирішується лише один раз для відшукання обсягів перевезень продукції між підприємствами першого і другого етапів після того, як знайдені інші компоненти оптимального рішення. Практична значимість. Програмна реалізація алгоритму на основі сучасних геоінформаційних технологій і ресурсів на прикладі сировинних потоків дозволяє зменшити сукупність витрат, пов’язаних з управлінням матеріальними і супутніми їм сервісними потоками по всьому логістичному ланцюгу, від моменту зародження потоку до надходження його кінцевому споживачеві.Цель. Разработка нового, эффективного с вычислительной точки зрения, алгоритма решения двухэтапной задачи распределения ресурса, непрерывно занимаемого заданную область, а также демонстрация работы соответствующего программного обеспечения, созданного с применением современных геоинформационных ресурсов. Методика. В работе использованы математические модели непрерывных задач оптимального разбиения множеств с дополнительными связями для описания двухэтапных задач размещения-распределения материальных ресурсов. Методический подход решения таких задач основан на идее сведения их к задачам бесконечномерного математического программирования, для которых, в свою очередь, с помощью применения аппарата теории двойственности оптимальное решение удается получить в аналитическом виде. Результаты. Разработан математический и алгоритмический аппарат решения непрерывных задач в применении к предприятиям топливно-энергетического комплекса, который позволяет получать разбиение района месторождения на зоны, за которыми предприятия первого этапа закрепляются монопольно. Работа алгоритма показана на примере решения модельной задачи. Определено, что выигрышем описанного подхода является сведение задачи бесконечномерного программирования к задаче конечномерной негладкой оптимизации, поскольку полученные расчетные формулы содержат параметры, для определения которых нужно решить вспомогательную задачу оптимизации недифференцируемой функции. Научная новизна. Представленный алгоритм, в отличие от ранее разработанного, не предусматривает решения задачи линейного программирования транспортного типа на каждом шаге итерационного процесса. Такая задача решается лишь один раз для отыскания объемов перевозок продукции между предприятиями первого и второго этапов после того, как найдены остальные компоненты оптимального решения. Практическая значимость. Программная реализация алгоритма на основе современных геоинформационных технологий и ресурсов на примере решения задачи распределения сырьевых потоков позволяет уменьшить совокупность издержек, связанных с управлением материальными и сопутствующими им сервисными потоками по всей логистической цепи, от момента зарождения потока до поступления его конечному потребителю.The study has been carried out in terms of the support, provision with the initial data (for correct problem statement and search for optimal solution), and cooperation of research scientists of the Institute of Geotechnical Mechanics named by N. Poljakov of National Academy of Sciences of Ukraine and the Department of System Analysis and Control of Dnipro University of Technology