Computer Engineering Commons^™

Modeling Energy Consumption Of High-Performance Applications On Heterogeneous Computing Platforms, Gary D. Lawson Jr.

Computational Modeling & Simulation Engineering Theses & Dissertations

Achieving Exascale computing is one of the current leading challenges in High Performance Computing (HPC). Obtaining this next level of performance will allow more complex simulations to be run on larger datasets and offer researchers better tools for data processing and analysis. In the dawn of Big Data, the need for supercomputers will only increase. However, these systems are costly to maintain because power is expensive. Thus, a better understanding of power and energy consumption is required such that future hardware can benefit.

Available power models accurately capture the relationship to the number of cores and clock-rate, however the relationship …

Development Of A Data Acquisition System For Unmanned Aerial Vehicle (Uav) System Identification, Donald Joseph Lear

Mechanical & Aerospace Engineering Theses & Dissertations

Aircraft system identification techniques are developed for fixed wing Unmanned Aerial Vehicles (UAV). The use of a designed flight experiment with measured system inputs/outputs can be used to derive aircraft stability derivatives. This project set out to develop a methodology to support an experiment to model pitch damping in the longitudinal short-period mode of a UAV. A Central Composite Response Surface Design was formed using angle of attack and power levels as factors to test for the pitching moment coefficient response induced by a multistep pitching maneuver.

Selecting a high-quality data acquisition platform was critical to the success of the …

An Empirical Study To Investigate The Effect Of Air Density Changes On The Dsrc Performance, Mostafa El-Said, Vijay Bhuse, Alexander Arendsen

Peer-Reviewed Publications

The primary role of Intelligent Transportation Systems (ITS) system is to implement Advanced Driver Assistance Services (ADAS) such as pedestrian detection, fog detection and collisions avoidance. These services rely on detecting and communicating the environment conditions such as heavy rain or snow with nearby vehicles to improve the driver's visibility. ITS systems rely on DSRC to communicate this information via a Vehicle-to-Vehicle (V2V) or Vehicle-to-Infrastructure (V2I) communications architectures. DSCR performance may be susceptible to environmental changes such as air density, gravitation (gravitational acceleration), air temperature, atmospheric pressure, humidity, and precipitation.

The goal of this research is to investigate whether the …

Rate Based Impact Analysis, Nishant Sharma

School of Computing: Dissertations, Theses, and Student Research

Impact Analysis (IA) identifies control and data dependencies to determine the system components that could be affected by a change. Changes to robotic systems as they are updated often alter the flow of control and sensor data. Changes to the rates at which data is published from sensors, controllers, and other parts of the system are particularly subtle and difficult to detect. These rate changes, even if minor (e.g. lowering the frame rate of a camera), can propagate throughout the system and have broad impacts. However, for robotic systems, these changes in flow rate cannot be precisely tracked by just …

K-Bit-Swap: A New Operator For Real-Coded Evolutionary Algorithms, Aram Ter-Sarkisov, Stephen Marsland

Articles

There has been a variety of crossover operators proposed for Real-Coded Genetic Algorithms (RCGAs), which recombine values from the same location in pairs of strings. In this article we present a recombination operator for RC- GAs that selects the locations randomly in both parents, and compare it to mainstream crossover operators in a set of experiments on a range of standard multidimensional optimization problems and a clustering problem. We present two variants of the operator, either selecting both bits uniformly at random in the strings, or sampling the second bit from a normal distribution centered at the selected location in …

Event And Time-Triggered Control Module Layers For Individual Robot Control Architectures Of Unmanned Agricultural Ground Vehicles, Tyler Troyer

Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research

Automation in the agriculture sector has increased to an extent where the accompanying methods for unmanned field management are becoming more economically viable. This manifests in the industry’s recent presentation of conceptual cab-less machines that perform all field operations under the high-level task control of a single remote operator. A dramatic change in the overall workflow for field tasks that historically assumed the presence of a human in the immediate vicinity of the work is predicted. This shift in the entire approach to farm machinery work provides producers increased control and productivity over high-level tasks and less distraction from operating …

2017 (Fall) Ensi Informer Magazine, Morehead State University. Engineering Sciences Department

ENSI Informer Magazine Archive

The ENSI Informer Magazine published in the fall of 2017.

Understanding The Determinants Affecting The Continuance Intention To Use Cloud Computing, Shailja Tripathi Dr.

Journal of International Technology and Information Management

Cloud computing has been progressively implemented in the organizations. The purpose of the paper is to understand the fundamental factors influencing the senior manager’s continuance intention to use cloud computing in organizations. A conceptual framework was developed by using the Technology Acceptance Model (TAM) as a base theoretical model. A questionnaire was used to collect the data from several companies in IT, manufacturing, finance, pharmaceutical and retail sectors in India. The data analysis was done using structural equation modeling technique. Perceived usefulness and perceived ubiquity are identified as important factors that affect continuance intention to use cloud computing. In addition, …

Table Of Contents Jitim Vol 26 Issue 3, 2017

Journal of International Technology and Information Management

Table of Contents

Spatio-Temporal Analysis And Prediction Of Cellular Traffic In Metropolis, Xu Wang, Zimu Zhou, Zheng Yang, Yunhao Liu, Chunyi Peng

Research Collection School Of Computing and Information Systems

Understanding and predicting cellular traffic at large-scale and fine-granularity is beneficial and valuable to mobile users, wireless carriers and city authorities. Predicting cellular traffic in modern metropolis is particularly challenging because of the tremendous temporal and spatial dynamics introduced by diverse user Internet behaviours and frequent user mobility citywide. In this paper, we characterize and investigate the root causes of such dynamics in cellular traffic through a big cellular usage dataset covering 1.5 million users and 5,929 cell towers in a major city of China. We reveal intensive spatio-temporal dependency even among distant cell towers, which is largely overlooked in …

Simple Implementation Of An Elgamal Digital Signature And A Brute Force Attack On It, Valeriia Laryoshyna

Student Works

This study is an attempt to show a basic mathematical usage of the concepts behind digital signatures and to provide a simple approach and understanding to cracking basic digital signatures. The approach takes on simple C programming of the ElGamal digital signature to identify some limits that can be encountered and provide considerations for making more complex code. Additionally, there is a literature review of the ElGamal digital signature and the brute force attack.

The research component of this project provides a list of possible ways to crack the basic implementations and classifies the different approaches that could be taken …

Semantic Reasoning In Zero Example Video Event Retrieval, M. H. T. De Boer, Yi-Jie Lu, Hao Zhang, Klamer Schutte, Chong-Wah Ngo, Wessel Kraaij

Research Collection School Of Computing and Information Systems

Searching in digital video data for high-level events, such as a parade or a car accident, is challenging when the query is textual and lacks visual example images or videos. Current research in deep neural networks is highly beneficial for the retrieval of high-level events using visual examples, but without examples it is still hard to (1) determine which concepts are useful to pre-train (Vocabulary challenge) and (2) which pre-trained concept detectors are relevant for a certain unseen high-level event (Concept Selection challenge). In our article, we present our Semantic Event Retrieval Systemwhich (1) shows the importance of high-level concepts …

Modeling Dormant Fruit Trees For Agricultural Automation, Henry Medeiros, Donghun Kim, Jianxin Sun, Hariharan Seshadri, Shayan A. Akbar, Noha M. Elfiky, Johnny Park

Electrical and Computer Engineering Faculty Research and Publications

Dormant pruning of fruit trees is one of the most costly and labor‐intensive activities in specialty crop production. We present a system that solves the first step in the process of automated pruning: accurately measuring and modeling the fruit trees. Our system employs a laser sensor to collect observations of fruit trees from multiple perspectives, and it uses these observations to measure parameters needed for pruning. A split‐and‐merge clustering algorithm divides the collected data into three sets of points: trunk candidates, junction point candidates, and branches. The trunk candidates and junction point candidates are then further refined by a robust …

Optimization Of Patch Antennas Via Multithreaded Simulated Annealing Based Design Exploration, James Richie, Cristinel Ababei

Electrical and Computer Engineering Faculty Research and Publications

In this paper, we present a new software framework for the optimization of the design of microstrip patch antennas. The proposed simulation and optimization framework implements a simulated annealing algorithm to perform design space exploration in order to identify the optimal patch antenna design. During each iteration of the optimization loop, we employ the popular MEEP simulation tool to evaluate explored design solutions. To speed up the design space exploration, the software framework is developed to run multiple MEEP simulations concurrently. This is achieved using multithreading to implement a manager-workers execution strategy. The number of worker threads is the same …

Dynamic Energy Management For Chip Multi-Processors Under Performance Constraints, Milad Ghorbani Moghaddam, Cristinel Ababei

Electrical and Computer Engineering Faculty Research and Publications

We introduce a novel algorithm for dynamic energy management (DEM) under performance constraints in chip multi-processors (CMPs). Using the novel concept of delayed instructions count, performance loss estimations are calculated at the end of each control period for each core. In addition, a Kalman filtering based approach is employed to predict workload in the next control period for which voltage-frequency pairs must be selected. This selection is done with a novel dynamic voltage and frequency scaling (DVFS) algorithm whose objective is to reduce energy consumption but without degrading performance beyond the user set threshold. Using our customized Sniper based CMP …

Cross-Modal Recipe Retrieval With Rich Food Attributes, Jingjing Chen, Chong-Wah Ngo, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Food is rich of visible (e.g., colour, shape) and procedural (e.g., cutting, cooking) attributes. Proper leveraging of these attributes, particularly the interplay among ingredients, cutting and cooking methods, for health-related applications has not been previously explored. This paper investigates cross-modal retrieval of recipes, specifically to retrieve a text-based recipe given a food picture as query. As similar ingredient composition can end up with wildly different dishes depending on the cooking and cutting procedures, the difficulty of retrieval originates from fine-grained recognition of rich attributes from pictures. With a multi-task deep learning model, this paper provides insights on the feasibility of …

Grasp Evaluation Method For Applying Static Loads Leading To Beam Failure, Mahyar Abdeetedal, Mehrdad Kermani Ph.D., P.Eng.

Electrical and Computer Engineering Publications

This paper deals with the problem of purposefully failing or yielding an object by a robotic gripper. We propose a grasp quality measure fabricated for robotic harvesting in which picking a crop from its stem is desired. The proposed metric characterizes a suitable grasp configuration for systematically controlling the failure behavior of an object to break it at the desired location while avoiding damage on other areas. Our approach is based on failure task information and gripper wrench insertion capability. Failure task definition is accomplished using failure theories. Gripper wrench insertion capability is formulated by modeling the friction between the …

Development And Grasp Analysis Of A Sensorized Underactuated Finger, Mahyar Abdeetedal, Mehrdad Kermani Ph.D., P.Eng.

Electrical and Computer Engineering Publications

No abstract provided.

Improvement Of Phylogenetic Method To Analyze Compositional Heterogeneity, Zehua Zhang, Kecheng Guo, Gaofeng Pan, Jijun Tang, Fei Guo

Faculty Publications

Background: Phylogenetic analysis is a key way to understand current research in the biological processes and detect theory in evolution of natural selection. The evolutionary relationship between species is generally reflected in the form of phylogenetic trees. Many methods for constructing phylogenetic trees, are based on the optimization criteria. We extract the biological data via modeling features, and then compare these characteristics to study the biological evolution between species.

Results: Here, we use maximum likelihood and Bayesian inference method to establish phylogenetic trees; multi-chain Markov chain Monte Carlo sampling method can be used to select optimal phylogenetic tree, resolving local …

Developing Grounded Goals Through Instant Replay Learning, Lisa Meeden, Douglas S. Blank

Computer Science Faculty Research and Scholarship

This paper describes and tests a developmental architecture that enables a robot to explore its world, to find and remember interesting states, to associate these states with grounded goal representations, and to generate action sequences so that it can re-visit these states of interest. The model is composed of feed-forward neural networks that learn to make predictions at two levels through a dual mechanism of motor babbling for discovering the interesting goal states and instant replay learning for developing the grounded goal representations. We compare the performance of the model with grounded goal representations versus random goal representations, and find …

When Big Data Gets Too Big

SIGNED: The Magazine of The Hong Kong Design Institute

Computer modelling has long been used as a design tool, and big data is a massive resource on which to build these models. But when the datasets get too big for computers to handle, innovative design solutions are needed. And the urge to play has driven technology forward

A Location-Aware Middleware Framework For Collaborative Visual Information Discovery And Retrieval, Andrew J.M. Compton

Theses and Dissertations

This work addresses the problem of scalable location-aware distributed indexing to enable the leveraging of collaborative effort for the construction and maintenance of world-scale visual maps and models which could support numerous activities including navigation, visual localization, persistent surveillance, structure from motion, and hazard or disaster detection. Current distributed approaches to mapping and modeling fail to incorporate global geospatial addressing and are limited in their functionality to customize search. Our solution is a peer-to-peer middleware framework based on XOR distance routing which employs a Hilbert Space curve addressing scheme in a novel distributed geographic index. This allows for a universal …

A Novel Real-Time Non-Invasive Hemoglobin Level Detection Using Video Images From Smartphone Camera, Golam Mushih Tanimul Ahsan, Md. O. Gani, Md Kamrul Hasan, Sheikh Iqbal Ahamed, William Chu, Mohammad Adibuzzaman, Joshua Field

Electrical and Computer Engineering Faculty Research and Publications

Hemoglobin level detection is necessary for evaluating health condition in the human. In the laboratory setting, it is detected by shining light through a small volume of blood and using a colorimetric electronic particle counting algorithm. This invasive process requires time, blood specimens, laboratory equipment, and facilities. There are also many studies on non-invasive hemoglobin level detection. Existing solutions are expensive and require buying additional devices. In this paper, we present a smartphone-based non-invasive hemoglobin detection method. It uses the video images collected from the fingertip of a person. We hypothesized that there is a significant relation between the fingertip …

Making Software, Making Regions: Labor Market Dualization, Segmentation, And Feminization In Austin, Portland And Seattle, Dillon Mahmoudi

Dissertations and Theses

Through mixed-methods research, this dissertation details the regionally variegated and place-specific software production processes in three second-tier US software regions. I focus on the relationship between different industrial, firm, and worker production configurations and broad-based economic development, prosperity, and inequality. I develop four main empirical findings.

First, I argue for a periodization of software production that tracks with changes in software laboring activity, software technologies, and wage-employment relationships. Through a GIS-based method, I use the IPUMS-USA to extensively measure the amount and type of software labor in industries across the US between 1970 and 2015. I map the uneven geography …

Micro-Contacts Testing Using A Micro-Force Sensor Compatible With Biological Systems, Ronald A. Coutu Jr., Dushyant Tomer

Electrical and Computer Engineering Faculty Research and Publications

This paper presents the performance and reliability testing of microelectromechanical systems (MEMS) switches by using a micro-force sensor which was originally designed/used to conduct mechanical testing of biological cells. MEMS switches are key components for radio frequency (RF) applications due to their extremely low power consumption and small geometries over conventional technologies. However, unstable electrical contact resistance severely degrades the performance and reliability of such micro-switches. Therefore, our focus is to improve the performance and reliability of “cold” switched micro-contacts by using novel contact materials and engineered micro-contact surfaces. The contact metallurgies considered in this work are “similar” thin film …

Selfie-Takers Prefer Left Cheeks: Converging Evidence From The (Extended) Selfiecity Database, Lev Manovich, Vera Ferrari, Nicola Bruno

Publications and Research

According to previous reports, selfie takers in widely different cultural contexts prefer poses showing the left cheek more than the right cheek. This posing bias may be interpreted as evidence for a right-hemispheric specialization for the expression of facial emotions. However, earlier studies analyzed selfie poses as categorized by human raters, which raises methodological issues in relation to the distinction between frontal and three-quarter poses. Here, we provide converging evidence by analyzing the (extended) selfiecity database which includes automatic assessments of head rotation and of emotional expression. We confirm a culture- and sex-independent left-cheek bias and report stronger expression of …

The Use Of Persistent Explorer Artificial Ants To Solve The Car Sequencing Problem, Kieran O'Sullivan

Dissertations

Ant Colony Optimisation is a widely researched meta-heuristic which uses the behaviour and pheromone laying activities of foraging ants to find paths through graphs. Since the early 1990’s this approach has been applied to problems such as the Travelling Salesman Problem, Quadratic Assignment Problem and Car Sequencing Problem to name a few. The ACO is not without its problems it tends to find good local optima and not good global optima. To solve this problem modifications have been made to the original ACO such as the Max Min ant system. Other solutions involve combining it with Evolutionary Algorithms to improve …

Probabilistic Graphical Models Follow Directly From Maximum Entropy, Anh H. Ly, Francisco Zapata, Olac Fuentes, Vladik Kreinovich

Departmental Technical Reports (CS)

Probabilistic graphical models are a very efficient machine learning technique. However, their only known justification is based on heuristic ideas, ideas that do not explain why exactly these models are empirically successful. It is therefore desirable to come up with a theoretical explanation for these models' empirical efficiency. At present, the only such explanation is that these models naturally emerge if we maximize the relative entropy; however, why the relative entropy should be maximized is not clear. In this paper, we show that these models can also be obtained from a more natural -- and well-justified -- idea of maximizing …

Impulse, Matt Schmidt, Lora Berg, Christine Delfanian, Dave Graves, Heidi Kronaizl, Emily Weber, Micayla Standish

Impulse (Jerome J. Lohr College of Engineering Publication)

[Page] 2 Better Equipped
[Page] 4 Flashback Summer Scholars
[Page] 6 Biomedical Engineering
Ryan Mahutga is the third mechanical engineering graduate in five years to receive a prestigious National Science Foundation Graduate Research Fellowship.
Nigerian native John Asiruwa is working with associate professor Stephen Gent on a mechanical engineering project to help Sanford Health build better heart stents.
Electrical engineering graduate Bruce Lutz has selected the biomedical engineering program as a target for his future giving.
[Page] 9 Programs Accredited
[Page] 10 Fast Wheels
[Page] 12 Five Unforgettable Weeks
[Page] 14 Second in the Nation
[Page] 16 Athletes and Engineering …

Can Deep Learning Techniques Improve The Risk Adjusted Returns From Enhanced Indexing Investment Strategies, Anthony Grace

Dissertations

Deep learning techniques have been widely applied in the field of stock market prediction particularly with respect to the implementation of active trading strategies. However, the area of portfolio management and passive portfolio management in particular has been much less well served by research to date. This research project conducts an investigation into the science underlying the implementation of portfolio management strategies in practice focusing on enhanced indexing strategies. Enhanced indexing is a passive management approach which introduces an element of active management with the aim of achieving a level of active return through small adjustments to the portfolio weights. …