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Full-Text Articles in Engineering

Prioritization Of Mutation Test Case Generation With Centrality Measures, ศุภชัย ทรัพย์มาก Jan 2021

Prioritization Of Mutation Test Case Generation With Centrality Measures, ศุภชัย ทรัพย์มาก

Chulalongkorn University Theses and Dissertations (Chula ETD)

การทดสอบการกลายพันธุ์สามารถนำไปใช้กับการประเมินคุณภาพของกรณีทดสอบได้ การจัดลำดับความสำคัญของการสร้างการทดสอบการกลายพันธุ์เป็นองค์ประกอบที่สำคัญของแนวปฏิบัติทางอุตสาหกรรมที่จะมีส่วนช่วยในการประเมินกรณีทดสอบ โดยทั่วไปแล้ว อุตสาหกรรมจะส่งมอบผลิตภัณฑ์ภายใต้เงื่อนไขของเวลาสู่ตลาด ดังนั้นจึงต้องเสียสละงานทดสอบซอฟต์แวร์อย่างหลีกเลี่ยงไม่ได้ แม้ว่าจะต้องใช้กรณีทดสอบจำนวนมากสำหรับการตรวจสอบซอฟต์แวร์ การใช้การวัดศูนย์กลางเครือข่ายสังคม เพื่อจัดลำดับความสำคัญของการสร้างการทดสอบการกลายพันธุ์ ซอร์สโค้ดที่มีค่าเพจแรงก์สูงสุด จะถูกเน้นก่อนเมื่อพัฒนากรณีทดสอบ เนื่องจากโมดูลเหล่านี้เสี่ยงต่อข้อบกพร่องหรือความผิดปกติซึ่งอาจทำให้เกิดข้อบกพร่องที่ตามมาในโมดูลที่เกี่ยวข้องอื่นๆ นอกจากนี้ แนวทางดังกล่าวจะช่วยระบุกรณีทดสอบที่ลดได้ในชุดทดสอบ โดยยังคงรักษาเกณฑ์เดียวกันกับจำนวนกรณีทดสอบเดิม


A General Framework For Characterizing And Evaluating Attacker Models For Cps Security Assessment, Christopher S. Deloglos, Christopher Deloglos Jan 2021

A General Framework For Characterizing And Evaluating Attacker Models For Cps Security Assessment, Christopher S. Deloglos, Christopher Deloglos

Theses and Dissertations

Characterizing the attacker’s perspective is essential to assessing the security posture and resilience of cyber-physical systems. The attacker’s perspective is most often achieved by cyber-security experts (e.g., red teams) who critically challenge and analyze the system from an adversarial stance. Unfortunately, the knowledge and experience of cyber-security experts can be inconsistent leading to situations where there are gaps in the security assessment of a given system. Structured security review processes (such as TAM, Mission Aware, STPA-SEC, and STPA-SafeSec) attempt to standardize the review processes to impart consistency across an organization or application domain. However, with most security review processes, the …


Deep Learning Assisted Intelligent Visual And Vehicle Tracking Systems, Liang Xu Jan 2021

Deep Learning Assisted Intelligent Visual And Vehicle Tracking Systems, Liang Xu

Theses and Dissertations

Sensor fusion and tracking is the ability to bring together measurements from multiple sensors of the current and past time to estimate the current state of a system. The resulting state estimate is more accurate compared with the direct sensor measurement because it balances between the state prediction based on the assumed motion model and the noisy sensor measurement. Systems can then use the information provided by the sensor fusion and tracking process to support more-intelligent actions and achieve autonomy in a system like an autonomous vehicle. In the past, widely used sensor data are structured, which can be directly …


Novel Fast Terminal Sliding Mode Controller With Current Constraint Forpermanent-Magnet Synchronous Motor, Yao Fang, Huifang Kong, Daoyuan Ding Jan 2021

Novel Fast Terminal Sliding Mode Controller With Current Constraint Forpermanent-Magnet Synchronous Motor, Yao Fang, Huifang Kong, Daoyuan Ding

Turkish Journal of Electrical Engineering and Computer Sciences

Under the noncascade structure, the balance between q-axis current constraint and dynamic performance in permanent-magnet synchronous motor system has become a critical problem. On the one hand, large transient current is required to provide high torque to achieve fast dynamic performance. On the other hand, current constraint becomes a state constraint problem, instead of governing q-axis reference current in the cascade structure directly. Aiming at this issue, a novel fast terminal sliding mode control (FTSMC)-based controller with current constraint is developed in this paper. The novelty of this scheme is related to the proposed penalty function based on interior point …


Joint Optimization Of Target Wake Time Mechanism And Scheduling For Ieee802.11ax, Mehmet Karaca Jan 2021

Joint Optimization Of Target Wake Time Mechanism And Scheduling For Ieee802.11ax, Mehmet Karaca

Turkish Journal of Electrical Engineering and Computer Sciences

IEEE 802.11ax as the newest wireless local area networks (WLANs) standard brings enormous improvements in network throughput, coverage and energy efficiency in densely populated areas. Unlike previous IEEE 802.11 WLAN standards where power saving mechanisms have a limited capability and flexibility, 802.11ax comes with a different mechanism called target wake time (TWT) where stations (STAs) wake up only after each TWT interval and different STAs can wake up at different time instance depending on their application requirements. As an example, for a periodic data arrival occurring in IoT applications, STA can wake up by following the data period and go …


Impact Of Hybrid Power Generation On Voltage, Losses, And Electricity Cost Indistribution Networks, Yavuz Ateş, Tayfur Gökçek, Ahmet Yi̇ği̇t Arabul Jan 2021

Impact Of Hybrid Power Generation On Voltage, Losses, And Electricity Cost Indistribution Networks, Yavuz Ateş, Tayfur Gökçek, Ahmet Yi̇ği̇t Arabul

Turkish Journal of Electrical Engineering and Computer Sciences

Energy and its capacity has emerged as one of the biggest distribution challenges all over the world. The existing grid becomes insufficient along with the expansion of the consumption. Therefore, the number of distributed generation (DG) in distribution networks increases and it allows us to sell back the extra energy. However, the efficiency of energy must be maintained into optimal values from the grid to the end-users. In spite of a lot of advantages of DG units, there are some disadvantages like fluctuations in voltage, increments of power losses, wrong protection coordination, harmonic and energy quality issues etc.. If the …


Analysis And Simulation Of Efficiency Optimized Ipm Drives In Constant Torqueregion With Reduced Computational Burden, Mi̇kai̇l Koç, Selçuk Emi̇roğlu, Bünyami̇n Tamyürek Jan 2021

Analysis And Simulation Of Efficiency Optimized Ipm Drives In Constant Torqueregion With Reduced Computational Burden, Mi̇kai̇l Koç, Selçuk Emi̇roğlu, Bünyami̇n Tamyürek

Turkish Journal of Electrical Engineering and Computer Sciences

Moving from internal combustion engine based towards electric based transportation is crucial for wide societies as they facilitate the use of green energy technologies such as wind and solar. Interior mounted permanent magnet (IPM) machines, also known as salient brushless alternating current (AC) machines, are commonly employed in traction applications as they have superior features, such as high efficiency operation, high torque, and power densities. The efficiency optimization in IPM drives is achieved by obtaining and operating at accurate and unique current angle for a certain electromagnetic torque demand. In conventional drives, the optimum current angle is obtained by online …


Determination Of Pneumonia In X-Ray Chest Images By Using Convolutionalneural Network, Özlem Polat, Zümray Ölmez, Tamer Ölmez Jan 2021

Determination Of Pneumonia In X-Ray Chest Images By Using Convolutionalneural Network, Özlem Polat, Zümray Ölmez, Tamer Ölmez

Turkish Journal of Electrical Engineering and Computer Sciences

Pneumonia is one of the major diseases that cause a lot of deaths all over the world. Determining pneumonia from chest X-ray (CXR) images is an extremely difficult and important image processing problem. The discrimination of whether pneumonia is of bacterium or virus origin has also become more important during the pandemic. Automatic determination of the presence and origin of pneumonia is crucial for speeding up the treatment process and increasing the patient's survival rate. In this study, a convolutional neural network (CNN) framework is proposed for detection of pneumonia from CXR images. Two different binary CNNs and a triple …


Power-Based Modelling And Control: Experimental Results On A Cart-Pole Doubleinverted Pendulum, Tuğçe Yaren, Selçuk Ki̇zi̇r Jan 2021

Power-Based Modelling And Control: Experimental Results On A Cart-Pole Doubleinverted Pendulum, Tuğçe Yaren, Selçuk Ki̇zi̇r

Turkish Journal of Electrical Engineering and Computer Sciences

This paper is concerned with the modeling framework based on power and control for a mechanical system that has nonlinear, unstable, and under-actuated characteristic features, based on an analogy, which is developed by using the Brayton and Moser's (BM) equations between mechanical and electrical systems. The analogy is based on a mixed-potential function generalized for BM. The mixed-potential function for a cart - pole double inverted pendulum (CPDIP) system is used as a new building block for modeling, analysis, and controller design. The analogy allows for the exact transfer of results from electrical circuit synthesis and analysis to the mechanical …


Control Synthesis For Parametric Timed Automata Under Reachability, Ebru Aydin Göl Jan 2021

Control Synthesis For Parametric Timed Automata Under Reachability, Ebru Aydin Göl

Turkish Journal of Electrical Engineering and Computer Sciences

Timed automata is a fundamental modeling formalism for real-time systems. During the design of such real-time systems, often the system information is incomplete, and design choices can vary. These uncertainties can be integrated to the model via parameters and labelled transitions. Then, the design can be completed by tuning the parameters and restricting the transitions via controller synthesis. These problems, namely parameter synthesis and controller synthesis, are studied separately in the literature. Herein, these are combined to generate an automaton satisfying the given specification by both parameter tuning and controller synthesis, thus exploring all design choices. First, it is shown …


Information Retrieval-Based Bug Localization Approach With Adaptive Attributeweighting, Mustafa Erşahi̇n, Semi̇h Utku, Deni̇z Kilinç, Buket Erşahi̇n Jan 2021

Information Retrieval-Based Bug Localization Approach With Adaptive Attributeweighting, Mustafa Erşahi̇n, Semi̇h Utku, Deni̇z Kilinç, Buket Erşahi̇n

Turkish Journal of Electrical Engineering and Computer Sciences

Software quality assurance is one of the crucial factors for the success of software projects. Bug fixing has an essential role in software quality assurance, and bug localization (BL) is the first step of this process. BL is difficult and time-consuming since the developers should understand the flow, coding structure, and the logic of the program. Information retrieval-based bug localization (IRBL) uses the information of bug reports and source code to locate the section of code in which the bug occurs. It is difficult to apply other tools because of the diversity of software development languages, design patterns, and development …


Novel Ofdm Transmission Scheme Using Generalized Prefix With Subcarrierindex Modulation, Yusuf Acar Jan 2021

Novel Ofdm Transmission Scheme Using Generalized Prefix With Subcarrierindex Modulation, Yusuf Acar

Turkish Journal of Electrical Engineering and Computer Sciences

The cyclic prefix (CP) is a prefix technique widely used in orthogonal frequency division multiplexing (OFDM) systems in order to eliminate the intersymbol interference (ISI) caused by the dispersion of wireless channels. However, CP reduces the number of symbols that can be transmitted in one OFDM symbol. Therefore, CP is one of the bottlenecks of OFDM systems limiting their spectral efficiency (SE). This limitation on the SE of the classical CP-based OFDM system is the main motivation for this work to introduce a novel method. In this paper, the design of a new CP structure, which is based on the …


Determining Overfitting And Underfitting In Generative Adversarial Networksusing Fréchet Distance, Enes Eken Jan 2021

Determining Overfitting And Underfitting In Generative Adversarial Networksusing Fréchet Distance, Enes Eken

Turkish Journal of Electrical Engineering and Computer Sciences

Generative adversarial networks (GANs) can be used in a wide range of applications where drawing samples from a data probability distribution without explicitly representing it is essential. Unlike the deep convolutional neural networks (CNNs) trained for mapping an input to one of the multiple outputs, monitoring the overfitting and underfitting in GANs is not trivial since they are not classifying but generating a data. While training set and validation set accuracy give a direct sense of success in terms of overfitting and underfitting for CNNs during the training process, evaluating the GANs mainly depends on the visual inspection of the …


A Case Study On Player Selection And Team Formation In Football With Machinelearning, Di̇dem Abi̇di̇n Jan 2021

A Case Study On Player Selection And Team Formation In Football With Machinelearning, Di̇dem Abi̇di̇n

Turkish Journal of Electrical Engineering and Computer Sciences

Machine learning has been widely used in different domains to extract information from raw data. Sports is one of the popular domains for researchers to work on recently. Although score prediction for matches is the most preferred application area for artificial intelligence, player selection, and team formation is also an application area worth working on. There are some studies in the literature about player selection and team formation which are examined in this study. The study has two important contributions: First one is to apply seven different machine learning algorithms on our dataset to find the best player combination for …


Analysis Of Optical Gyroscopes With Vertically Stacked Ring Resonators, Dooyoung Hah Jan 2021

Analysis Of Optical Gyroscopes With Vertically Stacked Ring Resonators, Dooyoung Hah

Turkish Journal of Electrical Engineering and Computer Sciences

Without any moving part, optical gyroscopes exhibit superior reliability and accuracy in comparison to mechanical sensors. Microring-resonator-based optical gyroscopes emerged as alternatives for bulky conventional Sagnac interferometer sensors, especially attractive for applications with limited footprints. Previously, it has been reported that planar incorporation of multiple resonators does not bring about improvement in sensitivity for a given area because the increase in Sagnac phase accumulation does not outrun the increase of area. Therefore, it was naturally suggested to consider vertical stacking of ring resonators because then, the resonators can share the same footprint. In this work, sensitivity performances of such configurations …


Adaptation Of Metaheuristic Algorithms To Improve Training Performance Of Aneszsl Model, Şi̇fa Özsari, Mehmet Serdar Güzel, Gazi̇ Erkan Bostanci, Ayhan Aydin Jan 2021

Adaptation Of Metaheuristic Algorithms To Improve Training Performance Of Aneszsl Model, Şi̇fa Özsari, Mehmet Serdar Güzel, Gazi̇ Erkan Bostanci, Ayhan Aydin

Turkish Journal of Electrical Engineering and Computer Sciences

Zero-shot learning (ZSL) is a recent promising learning approach that is similar to human vision systems. ZSL essentially allows machines to categorize objects without requiring labeled training data. In principle, ZSL proposes a novel recognition model by specifying merely the attributes of the category. Recently, several sophisticated approaches have been introduced to address the challenges regarding this problem. Embarrassingly simple approach to zeroshot learning (ESZSL) is one of the critical of those approaches that basically proposes a simple but efficient linear code solution. However, the performance of the ESZSL model mainly depends on parameter selection. Metaheuristic algorithms are considered as …


A New Approach: Semisupervised Ordinal Classification, Ferda Ünal, Derya Bi̇rant, Özlem Şeker Jan 2021

A New Approach: Semisupervised Ordinal Classification, Ferda Ünal, Derya Bi̇rant, Özlem Şeker

Turkish Journal of Electrical Engineering and Computer Sciences

Semisupervised learning is a type of machine learning technique that constructs a classifier by learning from a small collection of labeled samples and a large collection of unlabeled ones. Although some progress has been made in this research area, the existing semisupervised methods provide a nominal classification task. However, semisupervised learning for ordinal classification is yet to be explored. To bridge the gap, this study combines two concepts ?semisupervised learning? and "ordinal classification" for the categorical class labels for the first time and introduces a new concept of "semisupervised ordinal classification". This paper proposes a new algorithm for semisupervised learning …


Cybersecurity Leaders: Knowledge Driving Human Capital Development, Sharon L. Burton Jan 2021

Cybersecurity Leaders: Knowledge Driving Human Capital Development, Sharon L. Burton

Publications

Cybersecurity leaders must be able to use critical reading and thinking skills, exercise judgment when policies are not distinct and precise, and have the knowledge, skills, and abilities to tailor technical and planning data to diverse customers’ levels of understanding. Ninety-three percent of cybersecurity leaders do not report directly to the chief operating officer. While status differences influence interactions amid groups, attackers are smarter. With the aim of protecting organizations and reducing risk, knowledge about security must increase. Understanding voids are costly and increased breach chances are imminent. Burning questions exist. What are needed technological learnings for cybersecurity leaders to …


Disaster Analysis Using Satellite Image Data With Knowledge Transfer And Semi-Supervised Learning Techniques, Palavi Jain Jan 2021

Disaster Analysis Using Satellite Image Data With Knowledge Transfer And Semi-Supervised Learning Techniques, Palavi Jain

Reports

With the increase in frequency of disasters and crisis situations like floods, earthquake and hurricanes, the requirement to handle the situation efficiently through disaster response and humanitarian relief has increased. Disasters are mostly unpredictable in nature with respect to their impact on people and property. Moreover, the dynamic and varied nature of disasters makes it difficult to predict their impact accurately for advanced preparation of responses [104]. It is also notable that the economical loss due to natural disasters has increased in recent years, and it, along with the pure humanitarian need, is one of the reasons to research innovative …


Knowledge Infused Policy Gradients With Upper Confidence Bound For Relational Bandits, Kaushik Roy, Qi Zhang, Manas Gaur, Amit Sheth Jan 2021

Knowledge Infused Policy Gradients With Upper Confidence Bound For Relational Bandits, Kaushik Roy, Qi Zhang, Manas Gaur, Amit Sheth

Publications

Contextual Bandits find important use cases in various real-life scenarios such as online advertising, recommendation systems, healthcare, etc. However, most of the algorithms use at feature vectors to represent context whereas, in the real world, there is a varying number of objects and relations among them to model in the context. For example, in a music recommendation system, the user context contains what music they listen to, which artists create this music, the artist albums, etc. Adding richer relational context representations also introduces a much larger context space making exploration-exploitation harder. To improve the efficiency of exploration-exploitation knowledge about the …


Development Of A Real Time Human Face Recognition Software System, Askar Boranbayev, Seilkhan Boranbayev, Mukhamedzhan Amirtaev, Malik Baimukhamedov, Askar Nurbekov Jan 2021

Development Of A Real Time Human Face Recognition Software System, Askar Boranbayev, Seilkhan Boranbayev, Mukhamedzhan Amirtaev, Malik Baimukhamedov, Askar Nurbekov

Physics & Astronomy Faculty Publications

In this study, a system for real-time face recognition was built using the Open Face tools of the Open CV library. The article describes the methodology for creating the system and the results of its testing. The Open CV library has various modules that perform many tasks. In this paper, Open CV modules were used for face recognition in images and face identification in real time. In addition, the HOG method was used to detect a person by the front of his face. After performing the HOG method, 128 face measurements were obtained using the image encoding method. A convolutional …


Testing And Validation Framework For Autonomous Aerial Vehicles, Mustafa I. Akbas Jan 2021

Testing And Validation Framework For Autonomous Aerial Vehicles, Mustafa I. Akbas

Journal of Aviation/Aerospace Education & Research

Autonomous aerial vehicles (AAV) have the potential to have market disruptions for various industries such as ground delivery and aerial transportation. Hence, the USAF has called for increased level of autonomy. There has been a significant progress in artificial intelligence engines, complex and non-deterministic system components, which are at the core of the autonomous aerial platforms. Traditional testing and validation methods fall short of satisfying the requirement of testing such complex systems. Therefore, to achieve highly or fully autonomous capabilities, a major leap forward in the validation is required. The key challenges are the localization of problems, development of object …


Save-T: Safety Analysis Visualization And Evaluation Tool, Yuan Zhu, Sami Demiroluk, Kaan Ozbay, Kun Xie, Hong Yang, Di Sha Jan 2021

Save-T: Safety Analysis Visualization And Evaluation Tool, Yuan Zhu, Sami Demiroluk, Kaan Ozbay, Kun Xie, Hong Yang, Di Sha

Civil & Environmental Engineering Faculty Publications

Traffic crashes are one of the biggest issues which constitute a threat to lives of the motorists and disrupt operations of the transportation system. To reduce the number of crashes and alleviate their impacts, it is necessary to scrutinize the factors contributing to the risk of traffic crashes. Lately, visual analytics tools become very popular for data exploration and obtaining insights from the data. In this paper, a new web-based data visualization tool called Safety Analysis Visualization and Evaluation Tool (SAVE-T) was introduced. This tool enables users to interactively create queries and visually explore the results. By utilizing an online …


Evaluation Of Supervised Deep-Learning For Improved Pneumonia Diagnosis, Andrew Kalaani Jan 2021

Evaluation Of Supervised Deep-Learning For Improved Pneumonia Diagnosis, Andrew Kalaani

College of Graduate Studies: Theses & Dissertations

Pneumonia is one of the leading causes of infections in the lung area and deaths worldwide. The mortality rate is 24.8% for patients over 70 years of age due to other health complications present along with it. In least fortunate countries, pneumonia can often times go untreated because of how cost extensive it is to diagnose, especially severe cases that cannot be seen by a plain X-ray. Other scanning methods can find the lung abnormality but are time-extensive and not cost effective. An autonomous approach however can help aid diagnosing pneumonia with a plain X-ray scan due to the structural …


Learning Adl Daily Routines With Spatiotemporal Neural Networks, Shan Gao, Ah-Hwee Tan, Rossi Setchi Jan 2021

Learning Adl Daily Routines With Spatiotemporal Neural Networks, Shan Gao, Ah-Hwee Tan, Rossi Setchi

Research Collection School Of Computing and Information Systems

The activities of daily living (ADLs) refer to the activities performed by individuals on a daily basis and are the indicators of a person’s habits, lifestyle, and wellbeing. Learning an individual’s ADL daily routines has significant value in the healthcare domain. Specifically, ADL recognition and inter-ADL pattern learning problems have been studied extensively in the past couple of decades. However, discovering the patterns performed in a day and clustering them into ADL daily routines has been a relatively unexplored research area. In this paper, a self-organizing neural network model, called the Spatiotemporal ADL Adaptive Resonance Theory (STADLART), is proposed for …


On The Mandelbrot Set For I**2 = ±1 And Imaginary Higgs Fields, Jonathan Blackledge Jan 2021

On The Mandelbrot Set For I**2 = ±1 And Imaginary Higgs Fields, Jonathan Blackledge

Articles

We consider the consequence of breaking with a fundamental result in complex analysisby lettingi2=±1wherei=√−1is the basic unit of all imaginary numbers. An analysis of theMandelbrot set for this case shows that a demarcation between a Fractal and a Euclidean object ispossible based oni2=−1andi2= +1, respectively. Further, we consider the transient behaviourassociated with the two cases to produce a range of non-standard sets in which a Fractal geometricstructure is transformed into a Euclidean object. In the case of the Mandelbrot set, the Euclideanobject is a square whose properties are investigate. Coupled with the associated Julia sets and othercomplex plane mappings, this …


Unobtrusive Assessment Of Student Engagement Levels In Online Classroom Environment Using Emotion Analysis, Sasirekha Anbusegaran Jan 2021

Unobtrusive Assessment Of Student Engagement Levels In Online Classroom Environment Using Emotion Analysis, Sasirekha Anbusegaran

College of Graduate Studies: Theses & Dissertations

Measuring student engagement has emerged as a significant factor in the process of learning and a good indicator of the knowledge retention capacity of the student. As synchronous online classes have become more prevalent in recent years, gauging a student's attention level is more critical in validating the progress of every student in an online classroom environment. This paper details the study on profiling the student attentiveness to different gradients of engagement level using multiple machine learning models. Results from the high accuracy model and the confidence score obtained from the cloud-based computer vision platform - Amazon Rekognition were then …


Video Analysis And Verification Of Direct Head Impacts Recorded By Wearable Sensors In Junior Rugby League Players, Lauchlan Carey, Douglas P. Terry, Andrew S. Mcintosh, Peter Stanwell, Grant L. Iverson, Andrew J. Gardner Jan 2021

Video Analysis And Verification Of Direct Head Impacts Recorded By Wearable Sensors In Junior Rugby League Players, Lauchlan Carey, Douglas P. Terry, Andrew S. Mcintosh, Peter Stanwell, Grant L. Iverson, Andrew J. Gardner

Research outputs 2014 to 2021

Background: Rugby league is a high-intensity collision sport that carries a risk of concussion. Youth athletes are considered to be more vulnerable and take longer to recover from concussion than adult athletes. Purpose: To review head impact events in elite-level junior representative rugby league and to verify and describe characteristics of X-patchTM-recorded impacts via video analysis. Study Design: Observational case series. Methods: The X-patchTM was used on twenty-one adolescent players (thirteen forwards and eight backs) during a 2017 junior representative rugby league competition. Game-day footage, recorded by a trained videographer from a single camera, was synchronised with X-patchTM-recorded timestamped events. …


Subsumption Reduces Dataset Dimensionality Without Decreasing Performance Of A Machine Learning Classifier, Donald C. Wunsch, Daniel B. Hier Jan 2021

Subsumption Reduces Dataset Dimensionality Without Decreasing Performance Of A Machine Learning Classifier, Donald C. Wunsch, Daniel B. Hier

Chemistry Faculty Research & Creative Works

When Features in a High Dimension Dataset Are Organized Hierarchically, There is an Inherent Opportunity to Reduce Dimensionality. Since More Specific Concepts Are Subsumed by More General Concepts, Subsumption Can Be Applied Successively to Reduce Dimensionality. We Tested Whether Sub-Sumption Could Reduce the Dimensionality of a Disease Dataset Without Impairing Classification Accuracy. We Started with a Dataset that Had 168 Neurological Patients, 14 Diagnoses, and 293 Unique Features. We Applied Subsumption Repeatedly to Create Eight Successively Smaller Datasets, Ranging from 293 Dimensions in the Largest Dataset to 11 Dimensions in the Smallest Dataset. We Tested a MLP Classifier on All …


Scheduling Based Optimization In Software Defined Radio And Wireless Networks, Nathan Daniel Price Jan 2021

Scheduling Based Optimization In Software Defined Radio And Wireless Networks, Nathan Daniel Price

Doctoral Dissertations

"The objective of this work is to enable dynamic sharing of software-defined radio (SDR) transceivers through the concepts of hardware virtualization and real-time resource management. SDR is a way to build a digital radio that consists of a software back-end for digital signal processing (DSP) and an analog front-end transceiver for waveform generation and reception. This work proposes the use of a virtualization layer to decouple back-end SDR software from front-end transceivers. With this arrangement, front-ends are said to be virtualized, and it becomes possible to share a limited number of front-ends among many SDR back-ends through different multiplexing techniques. …