Digital Commons Network^™

Antioxidant Potential Of Sutherlandia Frutescens And Its Protective Effects Against Oxidative Stress In Various Cell Cultures, Shakila Tobwala, Weili Fan, Connor J. Hines, William Robert Folk, Nuran Ercal

Chemistry Faculty Research & Creative Works

Sutherlandia frutescens (L.) R.Br. (SF) is a South African plant that is widely used to treat stress, infections, cancer, and chronic diseases, many of which involve oxidative stress. The aim of the study was to quantitatively assess the antioxidant potential of SF extracts in cell-free system as well as in cell lines. Dried SF vegetative parts were extracted using six different solvents, and the extracts were assessed for total phenolic and flavonoid contents, total reducing power, iron chelating capacity, and free radical scavenging power, including, scavenging of hydroxyl radicals, superoxide anions, nitric oxide, and hydrogen peroxide. We further investigated the …

Four-Dimensional Reflectivity Data Comparison Between Two Ground-Based Radars: Methodology And Statistical Analysis, Bong Chul Seo, Witold F. Krajewski, James A. Smith

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

A methodology is proposed to compare radar reflectivity data obtained from two partially overlapping ground-based radars in order to explain relative differences in radar-rainfall products and establish sound merging procedures for multi-radar observing networks. To identify radar calibration differences, radar reflectivity is compared for well-matched radar sampling volumes viewing common meteorological targets. Temporal separation and three-dimensional matching of two different sampling volumes were considered based on the original polar coordinates of radar observation. Since the proposed method assumes radar beam propagation under standard atmospheric conditions, anomalous propagation cases were eliminated from the analysis. The reflectivity comparison results show systematic differences …

Analysis And Optimization Of A Protocol For Mobile Element Discovery In Sensor Networks, Francesco Restuccia, Giuseppe Anastasi, Marco Conti, Sajal K. Das

Computer Science Faculty Research & Creative Works

Recent studies have demonstrated that mobile elements (MEs) are an efficient solution to help decrease dramatically energy consumption in wireless sensor networks (WSNs). However, in most of cases, sensors use duty cycle schemes to save energy, and unless the ME mobility pattern is deterministic, each sensor node has to discover the presence of the ME in the nearby area before starting to exchange data with it. Therefore, in such wireless sensor networks with mobile elements (in short, WSN-MEs), the definition and analysis of a protocol for efficient ME discovery becomes of fundamental importance. In this paper, we propose an extensive …

Impact Of Location History Collection Schemes On Observed Human Mobility Features, Alicia Rodriguez-Carrion, Sajal K. Das, Celeste Campo, Carlos Garcia-Rubio

Computer Science Faculty Research & Creative Works

Human mobility knowledge is key for urban planning or mobility model's design. Therefore, estimating reliable mobility parameters is crucial to lay an unbiased foundation. However, most works estimating such features rely on datasets made up of the history of mobile network cells where the user is located when she makes active use of the network, known as Call Data Records (CDRs), or every time their device connects to a new cell, without taking into account cell changes not caused by movement. Could we accurately characterize human mobility with such datasets? In this work we consider three approaches to collect network-based …

Exploring Optimization And Caching For Efficient Collection Operations, Venkata Krishna Suhas Nerella, Swetha Surapaneni, Sanjay K. Madria, Thomas Weigert

Computer Science Faculty Research & Creative Works

Many large programs operate on collection types. Extensive libraries are available in many programming languages, such as the C++ Standard Template Library, which make programming with collections convenient. Extending programming languages to provide collection queries as first-class constructs in the language would not only allow programmers to write queries explicitly in their programs but it would also allow compilers to leverage the wealth of experience available from the database domain to optimize such queries. This paper describes an approach to reduce the run time of programs involving explicit collection queries by performing run time query optimization that is effective for …

An Access Point To Device Association Technique For Optimized Data Transfer In Mobile Grids, Ansuman Banerjee, Himadri Sekhar Paul, Arijit Mukherjee, Pubali Datta, Sajal K. Das

Computer Science Faculty Research & Creative Works

In a mobile grid computing framework where mobile devices are used as computing resources, minimizing the task offloading time remains an important issue. A task is an independent unit of execution consisting of a input data volume for execution and optionally a target-specific executable. We consider a mobile grid infrastructure where mobile devices are connected via Wi-Fi network and the grid infrastructure has a set of tasks (i.e. a set of data volumes) to be transferred to a subset of the mobile devices. In a Wi-Fi network, mobile devices usually associate themselves to the access points (APs) having the strongest …

Intelligent Management Systems For Energy Efficiency In Buildings: A Survey, Alessandra De Paola, Marco Ortolani, Giuseppe Lo Re, Giuseppe Anastasi, Sajal K. Das

Computer Science Faculty Research & Creative Works

In recent years, reduction of energy consumption in buildings has increasingly gained interest among researchers mainly due to practical reasons, such as economic advantages and long-term environmental sustainability. Many solutions have been proposed in the literature to address this important issue from complementary perspectives, which are often hard to capture in a comprehensive manner. This survey article aims at providing a structured and unifying treatment of the existing literature on intelligent energy management systems in buildings, with a distinct focus on available architectures and methodology supporting a vision transcending the well-established smart home vision, in favor of the novel Ambient …

Data Pattern Based Electromagnetic Interference Modeling For Ic Packaging, Nick K.H. Huang, Tao Wang, Li (Lijun) Jun Jiang, X. Y. Xiong

Electrical and Computer Engineering Faculty Research & Creative Works

Electromagnetic interference (EMI) is becoming more serious when the data rate of the digital system continues increasing. However, its modeling and analysis are very challenging. In this paper, a novel electromagnetic superposition method is developed to model the IC packaging electromagnetic emission. It employs the equivalence principle to obtain the electromagnetic field response over a broad spectrum. Then it uses the linear property of the passive parasitic system to superpose the contribution of different signals on the packaging. As a result, with certain pre-calculations, it is convenient to compute the electromagnetic emission efficiently from different signals with various data pattern …

Differential-Forms-Motivated Discretizations Of Electromagnetic Differential And Integral Equations, Qi I. Dai, Weng Cho Chew, Li (Lijun) Jun Jiang, Yumao Wu

Electrical and Computer Engineering Faculty Research & Creative Works

In this letter, we present a differential-forms-motivated procedure to unify and guide discretizations of differential and integral equations in computational electromagnetics (CEM). In order to solve such equations accurately, it is crucial to find an appropriate matrix representation of the governing differential or integral operator. Differential forms theory inspires a general procedure of selecting both expansion and test functions wisely. Many well-functioning discretizations in finite element method (FEM) and boundary element method (BEM) can be reinterpreted with this theory. Moreoever, our approach offers guidance for discretizing complicated problems where straightforward discretizations may not be available. © 2014 IEEE.

Robust And Resilient State-Dependent Control Of Continuous-Time Nonlinear Systems With General Performance Criteria, Xin Wang, Edwin E. Yaz, James Long

Electrical and Computer Engineering Faculty Research and Publications

A novel state-dependent control approach for continuous-time nonlinear systems with general performance criteria is presented in this paper. This controller is optimally robust for model uncertainties and resilient against control feedback gain perturbations in achieving general performance criteria to secure quadratic optimality with inherent asymptotic stability property together with quadratic dissipative type of disturbance reduction. For the system model, unstructured uncertainty description is assumed, which incorporates commonly used types of uncertainties, such as norm-bounded and positive real uncertainties as special cases. By solving a state-dependent linear matrix inequality at each time, sufficient condition for the control solution can be found …

Admissions Viewbook, 2014-2015, Illinois State University, Office Of Admissions

Admissions Viewbook

Recruitment booklet created by Illinois State University's Office of Admissions

Laboratory Schools Annual Report, 2013-2014, Laboratory Schools, Illinois State University

Annual Reports – Laboratory Schools

Illinois State University Laboratory Schools annual report

Leadership In Sustainability: Creating An Interface Between Creativity And Leadership Theory In Dealing With "Wicked Problems", Renee Newman-Storen

Research outputs 2014 to 2021

Fundamental to Leadership in Sustainability, a course in the Masters in Sustainability and Climate Policy (coursework) offered through Curtin University Sustainability Policy (CUSP) Institute, is that the complexity, flexibility and vitality of sustainability are precisely why sustainability practitioners commit themselves to finding new and innovative solutions to complex problems. The course asks the student to "think differently" and to engage in debate that inspires and encourages creative thinking strategies for the planning and development of our cities and communities. This paper details what the course is about, how it is structured and what the connections are between creativity, sustainability and …

Western Australian Graduate Diploma Of Education (Primary) Students' Perceptions Of Sustainability, Judith Clare Odgaard

Theses: Doctorates and Masters

In late 2011, the researcher investigated a cohort of Western Australian (WA) Graduate Diploma of Education Primary (GDE-P) students’ perceptions of Sustainability across a broad range of biophysical/natural, social and cultural, economic and political spheres. The study occurred during the seventh year of UNESCO’s Decade of Education for Sustainability Development, and when Sustainability Education became one of three cross-curriculum priorities of the new Australian Curriculum. Importantly, the students’ perceptions were interpreted during the context of the Post Global Financial Crisis and after Julia Gillard replaced Kevin Rudd as the Labor Prime Minister. The intense political context was often supported by …

Elliott Carter And His Use Of Metric And Temporal Modulaton In His Eight Pieces For Four Timpani : An Examination Into The Application Of Click Tracks During The Preparation And Performance Of These Works, Tegan Lebrun

Theses : Honours

Elliott Carter’s Eight Pieces for Four Timpani have become integral works in the solo timpani repertoire. They continue to offer technical and musical challenges to both developing and professional players and have influenced the development of the solo timpani genre to date. These pieces contain metric and temporal modulation – musical processes which alter certain performance parameters concerning pulse and subdivision tempi.

This dissertation investigates Carter’s use of metric and temporal modulation in his Eight Pieces for Four Timpani and examines the effects click track application has on the performance of these works. A brief biography of Carter and his …

Financial Statement Analysis, Steelman Library

Syllabus Repository

No abstract provided.

Biology I Lab, Sheila Prabhakar Abraham Dr.

Syllabus Repository

No abstract provided.

Biology I Lab, Todd Schraw

Syllabus Repository

No abstract provided.

Biology Ii Lab, Todd Schraw

Syllabus Repository

No abstract provided.

Biol 208l Anatomy And Physiology I Lab Syllabus, Steelman Library, A Franklin Dr

Syllabus Repository

No abstract provided.

General Genetics Lab, Steelman Library, Todd Schraw Dr.

Syllabus Repository

No abstract provided.

Why Penetration Testing Is A Limited Use Choice For Sound Cyber Security Practice, Craig Valli, Andrew J. Woodward, Peter Hannay, Michael N. Johnstone

Research outputs 2014 to 2021

Penetration testing of networks is a process that is overused when demonstrating or evaluating the cyber security posture of an organisation. Most penetration testing is not aligned with the actual intent of the testing, but rather is driven by a management directive of wanting to be seen to be addressing the issue of cyber security. The use of penetration testing is commonly a reaction to an adverse audit outcome or as a result of being penetrated in the first place. Penetration testing used in this fashion delivers little or no value to the organisation being tested for a number of …

Application Of Cellular Neural Networks And Naive Bayes Classifier In Agriculture, Oluleye H. Babatunde, Leisa Armstrong, Jinsong Leng, Dean Diepeveen

Research outputs 2014 to 2021

This article describes the use of Cellular Neural Networks (a class of Ordinary Differential Equation (ODE)), Fourier Descriptors (FD) and NaiveBayes Classifier (NBC) for automatic identification of images of plant leaves. The novelty of this article is seen in the use of CNN for image segmentation and a combination FDs with NBC. The main advantage of the segmentation method is the computation speed compared with other edge operators such as canny, sobel, Laplacian of Gaussian (LoG). The results herein show the potential of the methods in this paper for examining different agricultural images and distinguishing between different crops and weeds …

Mobile Applications For Indian Agriculture Sector: A Case Study, Pratik Shah, Niketa Gandhi, Leisa Armstrong

Research outputs 2014 to 2021

Government, private agencies and the general public are often interested in the decisions made by the Indian farmers as they have large influences beyond the farm boundary. Over many years, the process of adoption of new technologies and policies in the Indian agricultural sector has received considerable academic attention highlighting the role of many social, financial and other influences on their decision making. The Indian government and other development agencies promote income generating projects as a way of encouraging growth through increased agricultural production and the protection of the natural resource base. The impact of new technology to economic growth …

A Network That Really Works - The Application Of Artificial Neural Networks To Improve Yield Predictions And Nitrogen Management In Western Australia, Jinsong Leng, Andreas Neuhaus, Leisa Armstrong

Research outputs 2014 to 2021

Yield predictions are notorious for being difficult due to many interdependent factors such as rainfall, soil properties, plant health, plant density etc. This study is based upon the author’s previously published work and extends its findings by further investigating the best mathematical solution to this dilemma. Artificial intelligence (AI) techniques have been applied to a large set of soil, plant, rainfall, and yield data from CSBP’s field research trial program. Here we further differentiate by investigate two ANN techniques, a genetic algorithm with back propagation neural networks (GA-BP-NN) and a particle swarm optimization with back propagation neural networks (PSO-BP-NN). Results …

An Artificial Neural Network For Predicting Crops Yield In Nepal, Tirtha Ranjeet, Leisa Armstrong

Research outputs 2014 to 2021

This paper examines the application of artificial neural networks (ANNs) for predicting crop yields for an agricultural region in Nepal. The neural network algorithm has become an effective data mining tool and the outcome produced by this algorithm is considered to be less error prone than other computer science techniques. The backpropagation algorithm which iteratively finds a suitable weight value is considered for computing the error derivative. Agricultural data was collected from thirteen years from paddy field cultivation in the Siraha district, an eastern region in Nepal, and used for this investigation of neural networks. Additionally, climatic parameters including rainfall, …

Role Of Icts In Improving Drought Scenario Management In India, Shubhangi S. Wankhede, Niketa Gandhi, Leisa Armstrong

Research outputs 2014 to 2021

Drought is a natural phenomenon that affects social, economic and environmental sectors. It is caused due to low or no rainfall in the specific region and for some duration of time. Reduced soil moisture and ground water level are the other causes for drought. Based on its intensity, drought has impacts on various sectors like agriculture, transportation, forest fire, environment and many more. Agriculture is the major sector being affected by drought resulting in low crop production and having great detriment to economy of the country. In this paper, an attempt is made to study the different causes and effects …

Small To Medium Enterprise Cyber Security Awareness: An Initial Survey Of Western Australian Business, Craig Valli, Ian C. Martinus, Michael N. Johnstone

Research outputs 2014 to 2021

Small to Medium Enterprises (SMEs) represent a large proportion of a nation’s business activity. There are studies and reports reporting the threat to business from cyber security issues resulting in computer hacking that achieve system penetration and information compromise. Very few are focussed on SMEs. Even fewer are focussed on directly surveying the actual SMEs themselves and attempts to improve SME outcomes with respect to cyber security. This paper represents research in progress that outlines an approach being undertaken in Western Australia with SMEs in the northwest metropolitan region of Perth, specifically within the large local government catchments of Joondalup …

Methods For Multimodal Analysis And Representation Of Teaching-Learning Interactions In Primary Science Lessons Captured On Video, Mark W. Hackling, Karen J. Murcia, Khadeeja Ibrahim-Didi, Susan M. Hill

Research outputs 2014 to 2021

Video-based classroom research is opening-up exciting new insights into how teachers generate productive opportunities for student engagement in quality learning, reasoning and the development of their scientific literacy. The significant role played by multimodal representations in learning and teaching becomes evident through the medium of video and its analysis. Classroom research that is framed from social constructivist, sociocultural, activity theory and social semiotic perspectives highlights the social interactions involving multimodal representations which are used to communicate science ideas and also act as semiotic resources for meaning making. Social and cognitive processes of co-constructing meaning are mediated by talk, embodied representations …

Integrating Soil And Plant Tissue Tests And Using An Artificial Intelligence Method For Data Modelling Is Likely To Improve Decisions For In-Season Nitrogen Management, Andreas Neuhaus, Leisa Armstrong, Jinsong Leng, Dean Diepeveen, Geoff Anderson

Research outputs 2014 to 2021

This paper hypothesizes that there is value in combining soil, climate and plant tissue data to give more reliable advice on nitrogen top-ups in-season when compared with models that are currently available. The benefit of soil and climate data is to factor in N mineralisation and potential yield while plant test data is a more direct approach of yield estimates when considering firstly plant N uptake from the whole soil profile and secondly biomass (important yield component). Plant test data are closer to yield in time and space than soil test data, shortening the time period for any yield prognosis …