Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Institution
-
- Wright State University (178)
- University of Massachusetts Amherst (36)
- University of Wollongong (22)
- Southwestern Oklahoma State University (18)
- University of Rhode Island (16)
-
- Old Dominion University (13)
- Messiah University (8)
- Selected Works (8)
- University of Colorado Law School (4)
- University of the Pacific (4)
- Purdue University (3)
- Utah State University (3)
- Claremont Colleges (2)
- Dartmouth College (2)
- Montana Tech Library (2)
- University of Arkansas, Fayetteville (2)
- University of Connecticut (2)
- University of Nebraska - Lincoln (2)
- University of Nevada, Las Vegas (2)
- University of Texas at El Paso (2)
- Australian Council for Educational Research (ACER) (1)
- Bucknell University (1)
- Cedarville University (1)
- Central Washington University (1)
- Chapman University (1)
- Fort Hays State University (1)
- Georgia Southern University (1)
- Gettysburg College (1)
- Illinois Math and Science Academy (1)
- Linfield University (1)
- Publication Year
- Publication
-
- BITs and PCs Newsletter (157)
- Ethics in Science and Engineering National Clearinghouse (36)
- Browse all Theses and Dissertations (21)
- Australian Institute for Innovative Materials - Papers (18)
- Oklahoma Research Day Abstracts (18)
-
- Graduate School of Oceanography Faculty Publications (16)
- School of Science, Engineering & Health (SEH) Symposium (8)
- Engineering Management & Systems Engineering Faculty Publications (4)
- SMART Infrastructure Facility - Papers (4)
- The Rock (4)
- CCPO Publications (3)
- Civil and Environmental Engineering Faculty Publications (3)
- Bachelors Theses and Reports, 1928 - 1970 (2)
- Brookings Mountain West Publications (2)
- Computational Modeling & Simulation Engineering Faculty Publications (2)
- Computer Science Faculty Publications (2)
- Dartmouth Scholarship (2)
- Discovery Undergraduate Interdisciplinary Research Internship (2)
- Honors Scholar Theses (2)
- Open Access Theses & Dissertations (2)
- Aaron Adalja (1)
- All HMC Faculty Publications and Research (1)
- All Undergraduate Projects (1)
- Biennial Conference: The Social Practice of Human Rights (1)
- Biological and Agricultural Engineering Undergraduate Honors Theses (1)
- Branch Mathematics and Statistics Faculty and Staff Publications (1)
- Christopher N. Roman (1)
- City and Regional Planning -- Florida (1)
- Collaborative Librarianship (1)
- Department of Mathematics: Faculty Publications (1)
Articles 1 - 30 of 354
Full-Text Articles in Physical Sciences and Mathematics
Igniting Passion: A Detailed Journey Through Rocketry Course Activities, Krish M. Patel, Hannah Caycedo, Joshua Gage, Josi Maness, Kevin Park, Mufeng Shen
Igniting Passion: A Detailed Journey Through Rocketry Course Activities, Krish M. Patel, Hannah Caycedo, Joshua Gage, Josi Maness, Kevin Park, Mufeng Shen
SACAD: John Heinrichs Scholarly and Creative Activity Days
This course is a semester-long adventure in rocketry, led by Dr. Paul Adams. It covers everything about building and flying rockets, starting from the basics to more advanced rocketry. Students learn how to build rockets and use equipment used I payload systems like and altimeter and a GPS. We also learned about the importance of safety involved with building and launching rockets.
Language, Coded Instructions And The Interaction With Thermodynamics, Andy C. Mcintosh
Language, Coded Instructions And The Interaction With Thermodynamics, Andy C. Mcintosh
Proceedings of the International Conference on Creationism
The theme of the 9th ICC is Developing and Systematizing the Creation Model of Origins. Following this theme, the proposed paper seeks to establish a rigorous and systematic approach to the important area of information and its interface with the substrate on which the information is expressed. This must first involve the understanding of the laws of thermodynamics not only for isolated systems but for closed (where only energy is allowed to cross the boundary) and open systems (where both matter and energy are allowed to cross the boundary). This is particularly an issue with the second law of …
Rubber Band Car Activity, Admin Stem For Success, Natalie Wilson
Rubber Band Car Activity, Admin Stem For Success, Natalie Wilson
STEM for Success Showcase
Student learn about forces and engineering by designing a car powered by rubber bands
Fuzzing Php Interpreters By Automatically Generating Samples, Jacob S. Baumgarte
Fuzzing Php Interpreters By Automatically Generating Samples, Jacob S. Baumgarte
Browse all Theses and Dissertations
Modern web development has grown increasingly reliant on scripting languages such as PHP. The complexities of an interpreted language means it is very difficult to account for every use case as unusual interactions can cause unintended side effects. Automatically generating test input to detect bugs or fuzzing, has proven to be an effective technique for JavaScript engines. By extending this concept to PHP, existing vulnerabilities that have since gone undetected can be brought to light. While PHP fuzzers exist, they are limited to testing a small quantity of test seeds per second. In this thesis, we propose a solution for …
Enhancing Graph Convolutional Network With Label Propagation And Residual For Malware Detection, Aravinda Sai Gundubogula
Enhancing Graph Convolutional Network With Label Propagation And Residual For Malware Detection, Aravinda Sai Gundubogula
Browse all Theses and Dissertations
Malware detection is a critical task in ensuring the security of computer systems. Due to a surge in malware and the malware program sophistication, machine learning methods have been developed to perform such a task with great success. To further learn structural semantics, Graph Neural Networks abbreviated as GNNs have emerged as a recent practice for malware detection by modeling the relationships between various components of a program as a graph, which deliver promising detection performance improvement. However, this line of research attends to individual programs while overlooking program interactions; also, these GNNs tend to perform feature aggregation from neighbors …
Anomaly Detection In Multi-Seasonal Time Series Data, Ashton Taylor Williams
Anomaly Detection In Multi-Seasonal Time Series Data, Ashton Taylor Williams
Browse all Theses and Dissertations
Most of today’s time series data contain anomalies and multiple seasonalities, and accurate anomaly detection in these data is critical to almost any type of business. However, most mainstream forecasting models used for anomaly detection can only incorporate one or no seasonal component into their forecasts and cannot capture every known seasonal pattern in time series data. In this thesis, we propose a new multi-seasonal forecasting model for anomaly detection in time series data that extends the popular Seasonal Autoregressive Integrated Moving Average (SARIMA) model. Our model, named multi-SARIMA, utilizes a time series dataset’s multiple pre-determined seasonal trends to increase …
Unsupervised-Based Distributed Machine Learning For Efficient Data Clustering And Prediction, Vishnu Vardhan Baligodugula
Unsupervised-Based Distributed Machine Learning For Efficient Data Clustering And Prediction, Vishnu Vardhan Baligodugula
Browse all Theses and Dissertations
Machine learning techniques utilize training data samples to help understand, predict, classify, and make valuable decisions for different applications such as medicine, email filtering, speech recognition, agriculture, and computer vision, where it is challenging or unfeasible to produce traditional algorithms to accomplish the needed tasks. Unsupervised ML-based approaches have emerged for building groups of data samples known as data clusters for driving necessary decisions about these data samples and helping solve challenges in critical applications. Data clustering is used in multiple fields, including health, finance, social networks, education, and science. Sequential processing of clustering algorithms, like the K-Means, Minibatch K-Means, …
Data-Driven Strategies For Disease Management In Patients Admitted For Heart Failure, Ankita Agarwal
Data-Driven Strategies For Disease Management In Patients Admitted For Heart Failure, Ankita Agarwal
Browse all Theses and Dissertations
Heart failure is a syndrome which effects a patient’s quality of life adversely. It can be caused by different underlying conditions or abnormalities and involves both cardiovascular and non-cardiovascular comorbidities. Heart failure cannot be cured but a patient’s quality of life can be improved by effective treatment through medicines and surgery, and lifestyle management. As effective treatment of heart failure incurs cost for the patients and resource allocation for the hospitals, predicting length of stay of these patients during each hospitalization becomes important. Heart failure can be classified into two types: left sided heart failure and right sided heart failure. …
Solidity Compiler Version Identification On Smart Contract Bytecode, Lakshmi Prasanna Katyayani Devasani
Solidity Compiler Version Identification On Smart Contract Bytecode, Lakshmi Prasanna Katyayani Devasani
Browse all Theses and Dissertations
Identifying the version of the Solidity compiler used to create an Ethereum contract is a challenging task, especially when the contract bytecode is obfuscated and lacks explicit metadata. Ethereum bytecode is highly complex, as it is generated by the Solidity compiler, which translates high-level programming constructs into low-level, stack-based code. Additionally, the Solidity compiler undergoes frequent updates and modifications, resulting in continuous evolution of bytecode patterns. To address this challenge, we propose using deep learning models to analyze Ethereum bytecodes and infer the compiler version that produced them. A large number of Ethereum contracts and the corresponding compiler versions is …
Efficient Cloud-Based Ml-Approach For Safe Smart Cities, Niveshitha Niveshitha
Efficient Cloud-Based Ml-Approach For Safe Smart Cities, Niveshitha Niveshitha
Browse all Theses and Dissertations
Smart cities have emerged to tackle many critical problems that can thwart the overwhelming urbanization process, such as traffic jams, environmental pollution, expensive health care, and increasing energy demand. This Master thesis proposes efficient and high-quality cloud-based machine-learning solutions for efficient and sustainable smart cities environment. Different supervised machine-learning models for air quality predication (AQP) in efficient and sustainable smart cities environment is developed. For that, ML-based techniques are implemented using cloud-based solutions. For example, regression and classification methods are implemented using distributed cloud computing to forecast air execution time and accuracy of the implemented ML solution. These models are …
Path-Safe :Enabling Dynamic Mandatory Access Controls Using Security Tokens, James P. Maclennan
Path-Safe :Enabling Dynamic Mandatory Access Controls Using Security Tokens, James P. Maclennan
Browse all Theses and Dissertations
Deploying Mandatory Access Controls (MAC) is a popular way to provide host protection against malware. Unfortunately, current implementations lack the flexibility to adapt to emergent malware threats and are known for being difficult to configure. A core tenet of MAC security systems is that the policies they are deployed with are immutable from the host while they are active. This work looks at deploying a MAC system that leverages using encrypted security tokens to allow for redeploying policy configurations in real-time without the need to stop a running process. This is instrumental in developing an adaptive framework for security systems …
The Open Charge Point Protocol (Ocpp) Version 1.6 Cyber Range A Training And Testing Platform, David Elmo Ii
The Open Charge Point Protocol (Ocpp) Version 1.6 Cyber Range A Training And Testing Platform, David Elmo Ii
Browse all Theses and Dissertations
The widespread expansion of Electric Vehicles (EV) throughout the world creates a requirement for charging stations. While Cybersecurity research is rapidly expanding in the field of Electric Vehicle Infrastructure, efforts are impacted by the availability of testing platforms. This paper presents a solution called the “Open Charge Point Protocol (OCPP) Cyber Range.” Its purpose is to conduct Cybersecurity research against vulnerabilities in the OCPP v1.6 protocol. The OCPP Cyber Range can be used to enable current or future research and to train operators and system managers of Electric Charge Vehicle Supply Equipment (EVSE). This paper demonstrates this solution using three …
Data-Driven Strategies For Pain Management In Patients With Sickle Cell Disease, Swati Padhee
Data-Driven Strategies For Pain Management In Patients With Sickle Cell Disease, Swati Padhee
Browse all Theses and Dissertations
This research explores data-driven AI techniques to extract insights from relevant medical data for pain management in patients with Sickle Cell Disease (SCD). SCD is an inherited red blood cell disorder that can cause a multitude of complications throughout an individual’s life. Most patients with SCD experience repeated, unpredictable episodes of severe pain. Arguably, the most challenging aspect of treating pain episodes in SCD is assessing and interpreting the patient’s pain intensity level due to the subjective nature of pain. In this study, we leverage multiple data-driven AI techniques to improve pain management in patients with SCD. The proposed approaches …
Contributors To Pathologic Depolarization In Myotonia Congenita, Jessica Hope Myers
Contributors To Pathologic Depolarization In Myotonia Congenita, Jessica Hope Myers
Browse all Theses and Dissertations
Myotonia congenita is an inherited skeletal muscle disorder caused by loss-of-function mutation in the CLCN1 gene. This gene encodes the ClC-1 chloride channel, which is almost exclusively expressed in skeletal muscle where it acts to stabilize the resting membrane potential. Loss of this chloride channel leads to skeletal muscle hyperexcitability, resulting in involuntary muscle action potentials (myotonic discharges) seen clinically as muscle stiffness (myotonia). Stiffness affects the limb and facial muscles, though specific muscle involvement can vary between patients. Interestingly, respiratory distress is not part of this disease despite muscles of respiration such as the diaphragm muscle also carrying this …
Encryption And Compression Classification Of Internet Of Things Traffic, Mariam Najdat M Saleh
Encryption And Compression Classification Of Internet Of Things Traffic, Mariam Najdat M Saleh
Browse all Theses and Dissertations
The Internet of Things (IoT) is used in many fields that generate sensitive data, such as healthcare and surveillance. Increased reliance on IoT raised serious information security concerns. This dissertation presents three systems for analyzing and classifying IoT traffic using Deep Learning (DL) models, and a large dataset is built for systems training and evaluation. The first system studies the effect of combining raw data and engineered features to optimize the classification of encrypted and compressed IoT traffic using Engineered Features Classification (EFC), Raw Data Classification (RDC), and combined Raw Data and Engineered Features Classification (RDEFC) approaches. Our results demonstrate …
Effective Systems For Insider Threat Detection, Muhanned Qasim Jabbar Alslaiman
Effective Systems For Insider Threat Detection, Muhanned Qasim Jabbar Alslaiman
Browse all Theses and Dissertations
Insider threats to information security have become a burden for organizations. Understanding insider activities leads to an effective improvement in identifying insider attacks and limits their threats. This dissertation presents three systems to detect insider threats effectively. The aim is to reduce the false negative rate (FNR), provide better dataset use, and reduce dimensionality and zero padding effects. The systems developed utilize deep learning techniques and are evaluated using the CERT 4.2 dataset. The dataset is analyzed and reformed so that each row represents a variable length sample of user activities. Two data representations are implemented to model extracted features …
A Secure And Efficient Iiot Anomaly Detection Approach Using A Hybrid Deep Learning Technique, Bharath Reedy Konatham
A Secure And Efficient Iiot Anomaly Detection Approach Using A Hybrid Deep Learning Technique, Bharath Reedy Konatham
Browse all Theses and Dissertations
The Industrial Internet of Things (IIoT) refers to a set of smart devices, i.e., actuators, detectors, smart sensors, and autonomous systems connected throughout the Internet to help achieve the purpose of various industrial applications. Unfortunately, IIoT applications are increasingly integrated into insecure physical environments leading to greater exposure to new cyber and physical system attacks. In the current IIoT security realm, effective anomaly detection is crucial for ensuring the integrity and reliability of critical infrastructure. Traditional security solutions may not apply to IIoT due to new dimensions, including extreme energy constraints in IIoT devices. Deep learning (DL) techniques like Convolutional …
Merit Study Of Battery Or Hydrogen Energy Storage For Large Scale, Combined Wind And Solar Electricity Generation, Ashley K. Moore
Merit Study Of Battery Or Hydrogen Energy Storage For Large Scale, Combined Wind And Solar Electricity Generation, Ashley K. Moore
Browse all Theses and Dissertations
In the past several years, the energy sector has experienced a rapid increase in renewable energy installations due to declining capital costs for wind turbines, solar panels, and batteries. Wind and solar electricity generation are intermittent in nature which must be considered in an economic analysis if a fair comparison is to be made between electricity supplied from renewables and electricity purchased from the grid. Energy storage reduces curtailment of wind and solar and minimizes electricity purchases from the grid by storing excess electricity and deploying the energy at times when demand exceeds the renewable energy supply. The objective of …
Accelerating Precision Station Keeping For Automated Aircraft, James D. Anderson
Accelerating Precision Station Keeping For Automated Aircraft, James D. Anderson
Browse all Theses and Dissertations
Automated vehicles pose challenges in various research domains, including robotics, machine learning, computer vision, public safety, system certification, and beyond. These vehicles autonomously handle navigation and locomotion, often requiring minimal user interaction, and can operate on land, in water, or in the air. In the context of aircraft, one specific application is Automated Aerial Refueling (AAR). Traditional aerial refueling involves a "tanker" aircraft using a mechanism, such as a rigid boom arm or a flexible hose, to transfer fuel to another aircraft designated as the "receiver". For AAR, the boom arm may be maneuvered automatically, or in certain instances the …
Comparative Adjudication Of Noisy And Subjective Data Annotation Disagreements For Deep Learning, Scott David Williams
Comparative Adjudication Of Noisy And Subjective Data Annotation Disagreements For Deep Learning, Scott David Williams
Browse all Theses and Dissertations
Obtaining accurate inferences from deep neural networks is difficult when models are trained on instances with conflicting labels. Algorithmic recognition of online hate speech illustrates this. No human annotator is perfectly reliable, so multiple annotators evaluate and label online posts in a corpus. Labeling scheme limitations, differences in annotators' beliefs, and limits to annotators' honesty and carefulness cause some labels to disagree. Consequently, decisive and accurate inferences become less likely. Some practical applications such as social research can tolerate some indecisiveness. However, an online platform using an indecisive classifier for automated content moderation could create more problems than it solves. …
Winter Dynamics Of Storm Water Management Ponds And Winter Tolerance In Three Aquatic Plant Species, Patrick Strzalkowski
Winter Dynamics Of Storm Water Management Ponds And Winter Tolerance In Three Aquatic Plant Species, Patrick Strzalkowski
Theses and Dissertations (Comprehensive)
The vast majority of the research into the performance of stormwater management ponds (SWMPs) has been performed in warm regions or during the warmer seasons in temperate regions. It is presumed that SWMPs are inactive in the winter as any potential stormwater is trapped in snow and ice. The main goal of this thesis was to test this presumption and to study the dynamics and performance of three SWMPs during the winter. Remote water level loggers were installed into the three SWMPs and daily grab samples from the influents and effluents were taken and analyzed for total phosphorus (TP), chloride, …
Climate Justice In Engineering Education, Tyler J. Morgan, Donna Riley, Caroline M. Camfield
Climate Justice In Engineering Education, Tyler J. Morgan, Donna Riley, Caroline M. Camfield
Discovery Undergraduate Interdisciplinary Research Internship
The goal of this research is to design a learning module for Purdue first-year engineering (FYE) students to learn climate fundamentals, and the role of engineers in responding to climate justice challenges. There is a lack of climate material within these classes currently, leading to a lack of climate conscious engineers in the future. The project entailed reviewing and synthesizing a wide variety of previous research on climate change education in engineering, including key learning objectives and their assessment. Because one of the key foci of the first-year engineering sequence relates to data analysis and management, we focused our work …
Machine Learning In Requirements Elicitation: A Literature Review, Cheligeer Cheligeer, Jingwei Huang, Guosong Wu, Nadia Bhuiyan, Yuan Xu, Yong Zeng
Machine Learning In Requirements Elicitation: A Literature Review, Cheligeer Cheligeer, Jingwei Huang, Guosong Wu, Nadia Bhuiyan, Yuan Xu, Yong Zeng
Engineering Management & Systems Engineering Faculty Publications
A growing trend in requirements elicitation is the use of machine learning (ML) techniques to automate the cumbersome requirement handling process. This literature review summarizes and analyzes studies that incorporate ML and natural language processing (NLP) into demand elicitation. We answer the following research questions: (1) What requirement elicitation activities are supported by ML? (2) What data sources are used to build ML-based requirement solutions? (3) What technologies, algorithms, and tools are used to build ML-based requirement elicitation? (4) How to construct an ML-based requirements elicitation method? (5) What are the available tools to support ML-based requirements elicitation methodology? Keywords …
A Probabilistic Perspective Of Human-Machine Interaction, Mustafa Canan, Mustafa Demir, Samuel Kovacic
A Probabilistic Perspective Of Human-Machine Interaction, Mustafa Canan, Mustafa Demir, Samuel Kovacic
Engineering Management & Systems Engineering Faculty Publications
Human-machine interaction (HMI) has become an essential part of the daily routine in organizations. Although the machines are designed with state-of-the-art Artificial Intelligence applications, they are limited in their ability to mimic human behavior. The human-human interaction occurs between two or more humans; when a machine replaces a human, the interaction dynamics are not the same. The results indicate that a machine that interacts with a human can increase the mental uncertainty that a human experiences. Developments in decision sciences indicate that using quantum probability theory (QPT) improves the understanding of human decision-making than merely using classical probability theory (CPT). …
Computer Enabled Interventions To Communication And Behavioral Problems In Collaborative Work Environments, Ashutosh Shivakumar
Computer Enabled Interventions To Communication And Behavioral Problems In Collaborative Work Environments, Ashutosh Shivakumar
Browse all Theses and Dissertations
Task success in co-located and distributed collaborative work settings is characterized by clear and efficient communication between participating members. Communication issues like 1) Unwanted interruptions and 2) Delayed feedback in collaborative work based distributed scenarios have the potential to impede task coordination and significantly decrease the probability of accomplishing task objective. Research shows that 1) Interrupting tasks at random moments can cause users to take up to 30% longer to resume tasks, commit up to twice the errors, and experience up to twice the negative effect than when interrupted at boundaries 2) Skill retention in collaborative learning tasks improves with …
Modernization Of Scienttific Mathematics Formula In Technology, Iwasan D. Kejawa Ed.D, Prof. Iwasan D. Kejawa Ed.D
Modernization Of Scienttific Mathematics Formula In Technology, Iwasan D. Kejawa Ed.D, Prof. Iwasan D. Kejawa Ed.D
Department of Mathematics: Faculty Publications
Abstract
Is it true that we solve problem using techniques in form of formula? Mathematical formulas can be derived through thinking of a problem or situation. Research has shown that we can create formulas by applying theoretical, technical, and applied knowledge. The knowledge derives from brainstorming and actual experience can be represented by formulas. It is intended that this research article is geared by an audience of average knowledge level of solving mathematics and scientific intricacies. This work details an introductory level of simple, at times complex problems in a mathematical epidermis and computability and solvability in a Computer Science. …
Characterizing Students’ Engineering Design Strategies Using Energy3d, Jasmine Singh, Viranga Perera, Alejandra Magana, Brittany Newell
Characterizing Students’ Engineering Design Strategies Using Energy3d, Jasmine Singh, Viranga Perera, Alejandra Magana, Brittany Newell
Discovery Undergraduate Interdisciplinary Research Internship
The goals of this study are to characterize design actions that students performed when solving a design challenge, and to create a machine learning model to help future students make better engineering design choices. We analyze data from an introductory engineering course where students used Energy3D, an open source computer-aided design software, to design a zero-energy home (i.e. a home that consumes no net energy over a period of a year). Student design actions within the software were recorded into text files. Using a sample of over 300 students, we first identify patterns in the data to assess how students …
Effect Of Cloud Cover On Optimum Orientations Of Fixed Solar Panels For Maximum Yearly Energy Collection, Prethew Prasad
Effect Of Cloud Cover On Optimum Orientations Of Fixed Solar Panels For Maximum Yearly Energy Collection, Prethew Prasad
Browse all Theses and Dissertations
The amount of cloud cover present in the sky is a significant factor when determining the solar radiation impinging on a solar panel. The optimum tilt required to achieve maximum energy impingement on a surface is also influenced by the amount of cloud cover. This work presents a method for determining the optimum tilt angle for a fixed solar panel when a set amount of cloud cover is present in the sky. Fixed tilt angles that have the most incident solar energy over the course of a year as a function of cloud cover, latitude, and azimuthal angle orientation are …
Covid-19_Umaine News_Umaine Students Get Immersive Experience In Engineering Education, University Of Maine Division Of Marketing And Communications
Covid-19_Umaine News_Umaine Students Get Immersive Experience In Engineering Education, University Of Maine Division Of Marketing And Communications
Division of Marketing & Communications
Screenshot of UMaine News press release regarding Asli Sezen-Barrie, associate professor of curriculum, assessment and instruction in the University of Maine College of Education and Human Development redesigning her class on Teaching Science in the Secondary School to provide more opportunities for preservice teachers at UMaine to learn about engineering concepts and meet with engineers.
Promoting The Sustainable Utilization Of Groundwater Resources In Ethiopia Using The Integrated Groundwater Footprint Index, Xinyu Lin
Honors Scholar Theses
The country of Ethiopia is highly vulnerable to human-caused climate change and is already suffering from the effects. The predominately rural population relies heavily on small-scale agriculture, with 78% of households having at least one member engaged in the field, yet staple crops are highly susceptible to droughts and other weather shocks. Total and agricultural GDP growth in the country have been strongly linked to inter-annual rainfall variability, of which Ethiopia has among the highest in sub-Saharan Africa. A decrease in rainfall since the 1970s has been one of the primary causes of low crop yields, and stresses the immediate …