Computer Sciences Commons^™

Clustering Of Pain Dynamics In Sickle Cell Disease From Sparse, Uneven Samples, Gary K. Nave Jr, Swati Padhee, Amanuel Alambo, Tanvi Banerjee, Nirmish Shah, Daniel M. Abrams

Computer Science and Engineering Faculty Publications

Irregularly sampled time series data are common in a variety of fields. Many typical methods for drawing insight from data fail in this case. Here we attempt to generalize methods for clustering trajectories to irregularly and sparsely sampled data. We first construct synthetic data sets, then propose and assess four methods of data alignment to allow for application of spectral clustering. We also repeat the same process for real data drawn from medical records of patients with sickle cell disease -- patients whose subjective experiences of pain were tracked for several months via a mobile app. We find that different …

Efficient Load Balancing Algorithm In Long Term Evolution (Lte) Heterogeneous Network Based On Dynamic Cell Range Expansion Bias, Emmanuel Bakuza, Hashimu U. Iddi, Abdi T. Abdalla

Tanzania Journal of Science

The traditional scheme for load balancing in a homogeneous Long Term Evolution (LTE) Network where User Equipment (UEs) associate to a node with the strongest received signal strength is not practical for LTE Heterogeneous Network (LTE HetNet) due to power disparity between the nodes. Therefore, dynamic Cell Range Expansion (CRE) based load-balancing schemes were employed by several scholars to address the challenges in the LTE HetNet. However, the fairness index in achieving the desired average user throughput and UE offloading effect is relatively low. In this work, an efficient load-balancing algorithm for LTE HetNet based on dynamic Cell Range Expansion …

Mathematical Programming Model For The Two-Level Facility Location Problem: The Case Of Tanzanian Emergence Maize Distribution Network For 2004–2010 Maize Data, Said A. Sima

Tanzania Journal of Science

A two-level facility location problem (FLP) has been studied in the transportation network of emergence maize crop in Tanzania. The facility location problem is defined as the optimal location of facilities or resources so as to minimize costs in terms of money, time, distance and risks with the relation to supply and demand points. Distribution network design problems consist of determining the best way to transfer goods from the supply to the demand points by choosing the structure of the network such that the overall cost is minimized. The three layers, namely production centres (PCs), distribution centres (DCs) and customer …

Robust Trilateration Based Algorithm For Indoor Positioning Systems, Simeon Pande, Kwame S Ibwe

Tanzania Journal of Science

Indoor Positioning Systems (IPS) plays crucial roles in indoor environment items positioning used in self-navigating robots and helping hands. To obtain position information, positioning algorithms employing Received Signal Strength Indicator (RSSI) are of great benefits since they reuse the existing radio wireless infrastructures for indoor positioning. However, the changes in the indoor environment decrease the overall accuracy of the developed indoor positioning algorithms. To cope with the challenge of environmental dependency in indoor positioning, a robust algorithm using radio signal identification was developed. The algorithm uses circle expansion and reduction mechanism to achieve better RSSI-Distance relationship. The distances from RSSI-Distance …

Effect Of Lowering Tube Potential And Increase Iodine Concentration Of Contrast Medium On Radiation Dose And Image Quality In Computed Tomography Pulmonary Angiography Procedure: A Phantom Study, Justin E Ngaile, Peter K Msaki, Evarist M Kahuluda, Furaha M Chuma, Jerome M Mwimanzi, Ahmed M Jusabani

Tanzania Journal of Science

The aim of the study was to examine the effect of lowering tube potential and increase iodine concentration on image quality and radiation dose in computed tomography pulmonary angiography procedure. The pulmonary arteries were simulated by three syringes. The syringes were filled with 1:10 diluted solutions of 300 mg, 350 mg and 370 mg of iodine per millilitre concentration in three water-filled phantoms simulating thin, intermediate and thick patients. The phantoms were scanned at 80 kVp, 110 kVp and 130 kVp and 0.6 second rotation time using a 16 slice computed tomography (CT) scanner. The tube current was either fixed …

High Speed Hill Climbing Algorithm For Portfolio Optimization, Collether John

Tanzania Journal of Science

Portfolio can be defined as a collection of investments. Portfolio optimization usually is about maximizing expected return and/or minimising risk of a portfolio. The mean-variance model makes simplifying assumptions to solve portfolio optimization problem. Presence of realistic constraints leads to a significant different and complex problem. Also, the optimal solution under realistic constraints cannot always be derived from the solution for the frictionless market. The heuristic algorithms are alternative approaches to solve the extended problem. In this research, a heuristic algorithm is presented and improved for higher efficiency and speed. It is a hill climbing algorithm to tackle the extended …

Multi-Vehicle Speed Estimation Algorithm Based On Real-Time Inter-Frame Tracking Technique, Ernest Kisingo, Ndyetabura Hamisi, Hashim U. Iddi, Baraka J. Maiseli

Tanzania Journal of Science

Inappropriate vehicle speeding remains a central factor that causes road accidents claiming millions of lives every year. This challenge has raised concerns for vehicle speed estimation as an attempt to promote speed enforcement methods. Traditionally, radar and lidar systems have widely been used for this purpose, despite their several shortfalls: cosine error effects, need for direct line-of-sight, and inability to simultaneously and accurately measure speed from multiple vehicles. The current work proposes an algorithm and a multi-vehicle speed estimation system in a multi-lane road environment to address multi-vehicle speed estimation shortfalls. The proposed solution exploits image processing and computer vision …

Is Australia Really Lost In Space?, Brett Biddington

Research outputs 2014 to 2021

Australia is one of the world's most wealthy nations. Yet to the surprise and puzzlement of many observers, Australian governments over many years steadfastly refused to become involved in space activities in ways judged to be commensurate to the nation's wealth and place in the world. Repeated calls to establish a space agency were ignored or firmly rejected and civil and commercial investment in space activities was limited. In the past decade, there have been substantial developments and new investments in the policy, national security, civil and commercial domains. Perhaps the salient feature is the establishment of the Australian Space …

Sediqa: Sound Emitting Document Image Quality Assessment In A Reading Aid For The Visually Impaired, Jane Courtney

Articles

For visually impaired people (VIPs), the ability to convert text to sound can mean a new level of independence or the simple joy of a good book. With significant advances in optical character recognition (OCR) in recent years, a number of reading aids are appearing on the market. These reading aids convert images captured by a camera to text which can then be read aloud. However, all of these reading aids suffer from a key issue—the user must be able to visually target the text and capture an image of sufficient quality for the OCR algorithm to function—no small task …

A Sgx-Based And Quantum-Resitant Secure Cloud Storage System, Hexuan Yu

Student Theses and Dissertations

Data outsourcing is a promising approach in the cloud era for efficiently providing a large amount of storage to many remote clients. However, storing data on untrusted servers raise security concerns and data privacy is one of the most fundamental dilemmas in those data outsourcing infrastructures. Applying encryption to data may provide data confidentiality, but it is not sufficient to address such concerns. Recent cyberattacks targeting cloud applications (e.g., Apple iCloud, LinkedIn, Verizon), in which the privacy of millions of customers was compromised, have demonstrated the importance of preserving data secrecy in the untrusted execution environment. The the main research …

Sharcs: Secure Hierarchical Adaptive Reliable Cloud Storage Systems, Chaoyu Zhang

Student Theses and Dissertations

The recent development of cloud technology provides an on-demand availability of storage and computing resource without purchasing expensive hardware. However, traditional cloud storage services encountered challenges in data security, network communications, and system performance to emerging applications. Furthermore, these challenges have a significant influence when the massive IoT devices access cloud and the outsourcing data loss of physical control. Therefore, we design the SHARCS (Secure Hierarchical Adaptive Reliable Cloud Storage) systems to implement the multi-layer cloud storage that outsources parallelized ABE (Attribute-Based Encryption) to fog servers and equip IoT devices with TrustZone. This study aims to provide a general-purpose solution …

Data-Driven Based Automatic Routing Planning For Mass, Qingwu Wang

Maritime Safety & Environment Management Dissertations (Dalian)

No abstract provided.

Computer Vision Applications For Autonomous Aerial Vehicles, Burak Kakillioglu

Dissertations - ALL

Undoubtedly, unmanned aerial vehicles (UAVs) have experienced a great leap forward over the last decade. It is not surprising anymore to see a UAV being used to accomplish a certain task, which was previously carried out by humans or a former technology. The proliferation of special vision sensors, such as depth cameras, lidar sensors and thermal cameras, and major breakthroughs in computer vision and machine learning fields accelerated the advance of UAV research and technology. However, due to certain unique challenges imposed by UAVs, such as limited payload capacity, unreliable communication link with the ground stations and data safety, UAVs …

Partially Speaker-Dependent Automatic Speech Recognition Using Deep Neural Networks, Christopher J. Li, Michelle Spigner

Journal of the South Carolina Academy of Science

No abstract provided.

The Accuracy Of Artificial Intelligence (Ai) Chatbots In Telemedicine, Robert K. Swick

Journal of the South Carolina Academy of Science

No abstract provided.

Unit 1 - Virtual Machine Creation And Configuration, George A. Nossa

Open Educational Resources

The COVID pandemic has challenged us in continuing our instructional mission and provide high quality learning activities remotely. A key requirement for advanced technology courses is to duplicate the BMCC Computer Lab environment on the student's home computers.

This document provides detailed instructions for creating a "virtual machine" on the student's home computer. This document assumes the home computer is a PC desktop or laptop but this document will also work on computers running MacOS with an Intel X86 compatible chip,

Once the virtual machine is created, this document details the steps to install and configure an Ubuntu 20.04 Operating …

Software For The Frontiers Of Quantum Chemistry: An Overview Of Developments In The Q-Chem 5 Package, Evgeny Epifanovsky, Andrew T.B. Gilbert, Xintian Feng, Joonho Lee, Yuezhi Mao, Narbe Mardirossian, Pavel Pokhilko, Alec F. White, Marc P. Coons, Adiran L. Dempwolff, Zhengting Gan, Diptarka Hait, Paul R. Horn, Leif D. Jacobson, Ilya Kaliman, Jorg Kussmann, Adrian W. Lange, Ka Un Lao, Daniel S. Levine, Jie Liu, Simon C. Mckenzie, Adrian F. Morrison, Kaushik D. Nanda, Felix Plasser, Dirk R. Rehn, Marta L. Vidal, Zhi-Qiang You, Ying Zhu, Bushra Alam, Benjamin J. Albrecht, Abdulrahman Aldossary

Chemistry and Biochemistry Faculty Research

This article summarizes technical advances contained in the fifth major release of the Q-Chem quantum chemistry program package, covering developments since 2015. A comprehensive library of exchange–correlation functionals, along with a suite of correlated many-body methods, continues to be a hallmark of the Q-Chem software. The many-body methods include novel variants of both coupled-cluster and configuration-interaction approaches along with methods based on the algebraic diagrammatic construction and variational reduced density-matrix methods. Methods highlighted in Q-Chem 5 include a suite of tools for modeling core-level spectroscopy, methods for describing metastable resonances, methods for computing vibronic spectra, the nuclear–electronic orbital method, and …

Transfer Learning For Low-Resource Part-Of-Speech Tagging, Jeffrey Zhou, Neha Verma

The Yale Undergraduate Research Journal

Neural network approaches to Part-of-Speech tagging, like other supervised neural network tasks, benefit from larger quantities of labeled data. However, in the case of low-resource languages, additional methods are necessary to improve the performances of POS taggers. In this paper, we explore transfer learning approaches to improve POS tagging in Afrikaans using a neural network. We investigate the effect of transferring network weights that were originally trained for POS tagging in Dutch. We also test the use of pretrained word embeddings in our POS tagger, both independently and in conjunction with the transferred weights from a Dutch POS tagger. We …

Discriminative Region-Based Multi-Label Zero-Shot Learning, Sanath Narayan, Akshita Gupta, Salman Khan, Fahad Shahbaz Khan, Ling Shao, Mubarak Shah

Computer Vision Faculty Publications

Multi-label zero-shot learning (ZSL) is a more realistic counter-part of standard single-label ZSL since several objects can co-exist in a natural image. However, the occurrence of multiple objects complicates the reasoning and requires region-specific processing of visual features to preserve their contextual cues. We note that the best existing multi-label ZSL method takes a shared approach towards attending to region features with a common set of attention maps for all the classes. Such shared maps lead to diffused attention, which does not discriminatively focus on relevant locations when the number of classes are large. Moreover, mapping spatially-pooled visual features to …

Laser Surface Treatment And Laser Powder Bed Fusion Additive Manufacturing Study Using Custom Designed 3d Printer And The Application Of Machine Learning In Materials Science, Hao Wen

LSU Doctoral Dissertations

Selective Laser Melting (SLM) is a laser powder bed fusion (L-PBF) based additive manufacturing (AM) method, which uses a laser beam to melt the selected areas of the metal powder bed. A customized SLM 3D printer that can handle a small quantity of metal powders was built in the lab to achieve versatile research purposes. The hardware design, electrical diagrams, and software functions are introduced in Chapter 2. Several laser surface engineering and SLM experiments were conducted using this customized machine which showed the functionality of the machine and some prospective fields that this machine can be utilized. Chapter 3 …

Forest Park Trail Monitoring, Adan Robles, Colton S. Maybee, Erin Dougherty

REU Final Reports

Forest Park, one of the largest public parks in the United States with over 40 trails to pick from when planning a hiking trip. One of the main problems this park has is that there are too many trails, and a lot of the trails extend over 3 miles. Due to these circumstances’ trails are not checked frequently and hikers are forced to hike trails in the area with no warnings of potential hazards they can encounter. In this paper I researched how Forest Park currently monitors its trails and then set up a goal to solve the problem. We …

Digitally Reporting Trail Obstructions In Forest Park, Colton S. Maybee

REU Final Reports

The inclusion of technology on the trail can lead to better experiences for everyone involved in the hobby. Hikers can play a more prominent role in the maintenance of the trails by being able to provide better reports of obstructions while directly on the trail. This paper goes into the project of revamping the obstruction report system applied at Forest Park in Portland, Oregon. Most of my contributions to the project focus on mobile app development with some research into path planning algorithms related to the continuations of this project.

Research On Hybrid Deployment Strategy And Model For Key Position Air-Defense Based On Multi-Weapon Platforms, Jiaqing Wan, Pengfei Wang, Junlin Tang, Zhang Dong, Xinguo Li

Journal of System Simulation

Abstract: Multi-platform cooperative air-defense is the development direction of air-defense and antimissile warfare, and the hybrid deployment strategy and model are the important research content. Based on the background of key position air-defense research, the deployment strategy, principle and form of multi-platform cooperative air-defense are studied. The operational scenario and operational process of typical air defense are established. The principles, influencing factors and deployment methods of hybrid deployment are studied. A typical hybrid deployment strategy is proposed and a mathematical model is established. It provides support for the multi platform cooperative air defense and key position defense deployment.

Co-Simulation Of Parallel Computing Of Disc Temperature Distributed Parameter System Cooling Rate Control, Shengdong Gao, Yu Xin

Journal of System Simulation

Abstract: Aiming at the problem of large number of grids and long computation time in numerical simulation of complex engineering problems, combining the User-defined Function (UDF) parallel computing principle with UDP (User Datagram Protocol) communication in Fluent, the data transfer of the parallel calculation between Fluent and the visual simulation tool (Simulink) is completed by embedding UDF and S function in UDP communication. And the parallel calculation and simulation platform of the disk and billet gas impingement jet quenching is built. The serial and parallel calculation of the same model are carried out, and the comparative analysis of the numerical …

Research On Integrated Optimization Approach For Car-Sharing Systems, Tang Jie, Jinxin Cao

Journal of System Simulation

Abstract: Effective scheduling and routing of employees and vehicles determines the efficiency of car-sharing systems. Aiming at the scheduling of shared cars within one day, with the objective of minimizing the total system costs and personnel costs, a bi-level optimization model for multiple traveling salesman problem with time windows is established. A genetic algorithm with multi-chromosome coding and the optimized complex mutation operator are developed for the problem solution. From the comprehensive computational experiments, it can be concluded that the total numbers of vehicles and employees with the joint routing plans satisfying the order constraints can be obtained in …

The Allocation Of Jamming Resources Based On Double Q-Learning Algorithm, Xingyuan Huang, Yanyi Li

Journal of System Simulation

Abstract: In modern warfare, the multifunctional trend of radars, even multiple radars detecting targets together, enhances the anti-jamming capability of radars. However, the traditional jamming system still follows a fixed jamming strategy, and the real-time performance of decision-making facing large numbers of radars is poor. And the cognitive jamming study is urgent. The concept of reinforcement learning is explained and the difference between Q learning algorithm and double Q learning algorithm is compared. The reinforcement learning algorithm is used to establish a model based on cognitive electronic warfare to realize the allocation of radar jamming strategies. The simulation of the …

The Challenges Of Applying Computational Legal Analysis To Mhealth Security And Privacy Regulations, Brian Tung

McKelvey School of Engineering Graduate Student Theses & Dissertations

As our world has grown in complexity, so have our laws. By one measure, the United States Code has grown over 30x as long since 1935, and the 186,000-page Code of Federal Regulations has grown almost 10x in length since 1938. Our growing legal system is too complicated; it’s impossible for people to know all the laws that apply to them. However, people are still subject to the law, even if they are unfamiliar with it. Therein lies the need for computational legal analysis. Tools of computation (e.g., data visualization, algorithms, and artificial intelligence) have the potential to transform civic …

Exploiting Block Structures Of Kkt Matrices For Efficient Solution Of Convex Optimization Problems, Zafar Iqbal, Saeid Nooshabadi, Ichitaro Yamazaki, Stanimire Tomov, Jack Dongarra

Michigan Tech Publications, Part 1

Convex optimization solvers are widely used in the embedded systems that require sophisticated optimization algorithms including model predictive control (MPC). In this paper, we aim to reduce the online solve time of such convex optimization solvers so as to reduce the total runtime of the algorithm and make it suitable for real-time convex optimization.We exploit the property of the Karush–Kuhn–Tucker (KKT) matrix involved in the solution of the problem that only some parts of the matrix change during the solution iterations of the algorithm. Our results show that the proposed method can effectively reduce the runtime of the solvers.

Relationship Between Suspension Damping And Stability Of Vehicle Hunting Motion, Yan Yong, Zeng Jing, Kun Xu, Feiyan Zhao

Journal of System Simulation

Abstract: In order to avoid or restrain the primary hunting stability of rail vehicles, correlation between the primary hunting stability and suspension damping parameters under the damping ratio of 0 and 5% is calculated based on the analysis of suspension parameters on the vehicle modal frequency. The method to improve the stability of vehicle hunting motion by optimizing suspension parameters is obtained. The results show that when selecting different damping ratios to calculate the critical stability, the range of damping parameters varies greatly. The lateral damping parameter in a certain range or a larger vertical damping is beneficial to keep …

A Signal Decomposition Method Based On Multi-Layer Iteration Structured Singular Spectrum Analysis, Yumiao Wei, Zhili Zhang, Hongguang Li, Shuqing Li

Journal of System Simulation

Abstract: To process the complex signals with concentrated frequency distribution, an adaptive decomposition method based on singular spectrum analysis with multi-layer iteration structure is researched. The traditional singular spectrum analysis is improved by frequency band subdivision and iterative filtering approach. A high-precision decomposition algorithm base on recursive structure is therefore designed, solving the problems such as insufficient adaptive capability and unsatisfied decomposition. Simulation results show that adaptive decomposition capability of the proposed method is effectively enhanced. For the multi-mode vibration signal with 0.2% ratio of spitting frequency to center frequency, the components are all accurately extracted, and consistent well …