Near-Unity Broadband Omnidirectional Emissivity
Via Femtosecond Laser Surface Processing,
2021
University of Nebraska - Lincoln
Near-Unity Broadband Omnidirectional Emissivity Via Femtosecond Laser Surface Processing, Andrew Reicks, Alfred Tsubaki, Mark Anderson, Jace Wieseler, Larousse Khosravi Khorashad, Jeffrey E. Shield, George Gogos, Dennis Alexander, Christos Argyropoulos, Craig Zuhlke
Department of Electrical and Computer Engineering: Faculty Publications
It is very challenging to achieve near perfect absorption or emission that is both broadband and omnidirectional while utilizing a scalable fabrication process. Femtosecond laser surface processing is an emerging low-cost and large-scale manufacturing technique used to directly and permanently modify the surface properties of a material. The versatility of this technique to produce tailored surface properties has resulted in a rapidly growing number of applications. Here, we demonstrate near perfect, broadband, omnidirectional emissivity from aluminum surfaces by tuning the laser surface processing parameters including fluence, pulse count, and the ambient gas. Full-wave simulations and experimental results prove that the …
Are Entrepreneurial Capabilities And Prior Knowledge The Silver Bullet For The Generation Of New Digital Venture Ideas In A Digital Context?,
2021
Old Dominion University
Are Entrepreneurial Capabilities And Prior Knowledge The Silver Bullet For The Generation Of New Digital Venture Ideas In A Digital Context?, Meifang Yao, Dan Ye, Gao Yang, Hui Shi, Xianrong Zheng
Information Technology & Decision Sciences Faculty Publications
Digital technology has had an important impact on entrepreneurship. It has changed the uncertain nature of the process of new venture idea generation, and it has also brought unprecedented opportunities for the generation of new digital venture ideas. In order to explore how startups can deal with major challenges brought by digital technology and create new digital venture ideas, this paper focuses on micro level entrepreneurial actions and constructs a theoretical model of the relationship among networking capabilities, IT capabilities, prior knowledge, and new digital venture ideas. Furthermore, through the hierarchical linear regression analysis of 278 sample data, the paper …
Localization Algorithms For Gnss-Denied And Challenging Environments,
2021
West Virginia University
Localization Algorithms For Gnss-Denied And Challenging Environments, Chizhao Yang
Graduate Theses, Dissertations, and Problem Reports (ETD)
In this dissertation, the problem about localization in GNSS-denied and challenging environments is addressed. Specifically, the challenging environments discussed in this dissertation include two different types, environments including only low-resolution features and environments containing moving objects. To achieve accurate pose estimates, the errors are always bounded through matching observations from sensors with surrounding environments. These challenging environments, unfortunately, would bring troubles into matching related methods, such as "fingerprint" matching, and ICP. For instance, in environments with low-resolution features, the on-board sensor measurements could match to multiple positions on a map, which creates ambiguity; in environments with moving objects included, the …
On The Usage And Vulnerabilities Of Api Systems,
2021
William & Mary
On The Usage And Vulnerabilities Of Api Systems, Conner D. Yu
Cybersecurity Undergraduate Research Showcase
To some, Application Programming Interface (API) is one of many buzzwords that seem to be blanketed in obscurity because not many people are overly familiar with this term. This obscurity is unfortunate, as APIs play a crucial role in today’s modern infrastructure by serving as one of the most fundamental communication methods for web services. Many businesses use APIs in some capacity, but one often overlooked aspect is cybersecurity. This aspect is most evident in the 2018 misuse case by Facebook, which led to the leakage of 50 million users’ records.1 During the 2018 Facebook data breach incident, threat actors …
Optimizing Peer Selection Among Internet Service Providers (Isps),
2021
University of Central Florida
Optimizing Peer Selection Among Internet Service Providers (Isps), Shahzeb Mustafa
Electronic Theses and Dissertations, 2020-2023
Connections among Internet Service Providers (ISPs) form the backbone of the Internet. This enables communications across the globe. ISPs are represented as Autonomous Systems (ASes) in the global Internet and inter-ISP traffic exchange takes place via inter-AS links, which are formed based on inter-ISP connections and agreements. In addition to customer-provider agreements, a crucial type of inter-ISP agreement is peering. ISP administrators use various platforms like AP-NIC and NANOG networking events for establishing new peering connections in accordance with their business and technical needs. Such methods are often inefficient and slow, potentially resulting in missed opportunities or sub-optimal routes. The …
Appointment Scheduling System,
2021
Central Washington University
Appointment Scheduling System, Guzaloi Noori
Undergraduate Honors Theses
Appointment Scheduling System designed for universities so that students can schedule appointments with their university’s faculty and staff regarding academic, employment, immigration, or personal issues. The scheduling system has the ability of being embedded to the Computer Science Capstone project iAcademic, which I took part in as a front-end developer.
Improving Performance And Flexibility Of Fabric-Attached Memory Systems,
2021
University of Central Florida
Improving Performance And Flexibility Of Fabric-Attached Memory Systems, Vamsee Reddy Kommareddy
Electronic Theses and Dissertations, 2020-2023
As demands for memory-intensive applications continue to grow, the memory capacity of each computing node is expected to grow at a similar pace. In high-performance computing (HPC) systems, the memory capacity per compute node is decided upon the most demanding application that would likely run on such a system, and hence the average capacity per node in future HPC systems is expected to grow significantly. However, diverse applications run on HPC systems with different memory requirements and memory utilization can fluctuate widely from one application to another. Since memory modules are private for a corresponding computing node, a large percentage …
Are We In The Digital Dark Times? How The Philosophy Of Hannah Arendt Can Illuminate Some Of The Ethical Dilemmas Posed By Modern Digital Technologies,
2021
Technological University Dublin
Are We In The Digital Dark Times? How The Philosophy Of Hannah Arendt Can Illuminate Some Of The Ethical Dilemmas Posed By Modern Digital Technologies, Damian Gordon, Anna Becevel
Conference Papers
Philosophers are not generally credited with being clairvoyant, and yet because they recognise, record and reflect on trends in their society, their observations can often appear prescient. In the field of the ethics of technology, there is, perhaps, no philosopher whose perspective on these issues is worth examining in detail more than that of Hannah Arendt, who can offer real perspective on the challenges we are facing with technologies in the twenty-first century. Arendt, a thinker of Jewish-German origin, student of Martin Heidegger and Karl Jaspers, encountered her life turning point when she was forced into becoming a refugee as …
Utilizing Resonant Scattering Signal Characteristics Via Deep Learning For Improvedclassification Of Complex Targets,
2021
TÜBİTAK
Utilizing Resonant Scattering Signal Characteristics Via Deep Learning For Improvedclassification Of Complex Targets, Tuğçe Toprak, Mustafa Alper Selver, Mustafa Seçmen, Emi̇ne Yeşi̇m Zoral
Turkish Journal of Electrical Engineering and Computer Sciences
Object classification using late-time resonant scattering electromagnetic signals is a significant problem found in different areas of application. Due to their unique properties, spherical objects play an essential role in this field both as a challenging target and a resource of analytical late-time resonant scattering electromagnetic signals. Although many studies focus on their detailed analysis, the challenges associated with target classification by resonant late-time resonant scattering electromagnetic signals from multilayer spheres have not been investigated in detail. Moreover, existing studies made the simplifying assumption that the objects having (one or more) layers constitute equal permeability values at the core and …
An Improved Version Of Multi-View K-Nearest Neighbors (Mvknn) For Multipleview Learning,
2021
TÜBİTAK
An Improved Version Of Multi-View K-Nearest Neighbors (Mvknn) For Multipleview Learning, Eli̇fe Öztürk Kiyak, Derya Bi̇rant, Kökten Ulaş Bi̇rant
Turkish Journal of Electrical Engineering and Computer Sciences
Multi-view learning (MVL) is a special type of machine learning that utilizes more than one views, where views include various descriptions of a given sample. Traditionally, classification algorithms such as k-nearest neighbors (KNN) are designed for learning from single-view data. However, many real-world applications involve datasets with multiple views and each view may contain different and partly independent information, which makes the traditional single-view classification approaches ineffective. Therefore, this article proposes an improved MVL algorithm, called multi-view k-nearest neighbors (MVKNN), based on the existing KNN algorithm. The experimental results conducted in this research show that a significant improvement is achieved …
Scalable Approaches For Auditing The Completeness Of Biomedical Ontologies,
2021
University of Kentucky
Scalable Approaches For Auditing The Completeness Of Biomedical Ontologies, Fengbo Zheng
Theses and Dissertations--Computer Science
An ontology provides a formalized representation of knowledge within a domain. In biomedicine, ontologies have been widely used in modern biomedical applications to enable semantic interoperability and facilitate data exchange. Given the important roles that biomedical ontologies play, quality issues such as incompleteness, if not addressed, can affect the quality of downstream ontology-driven applications. However, biomedical ontologies often have large sizes and complex structures. Thus, it is infeasible to uncover potential quality issues through manual effort. In this dissertation, we introduce automated and scalable approaches for auditing the completeness of biomedical ontologies. We mainly focus on two incompleteness issues -- …
Analysis Of Classifier Weaknesses Based On Patterns And Corrective Methods,
2021
Wright State University
Analysis Of Classifier Weaknesses Based On Patterns And Corrective Methods, Nicholas Skapura
Browse all Theses and Dissertations
Classification is an important branch of machine learning that impacts many areas of modern life. Many classification algorithms (classifiers for short) have been developed. They have highly different levels of sophistication and classification accuracy. Classification problems often have highly different levels of hardness and complexity. Practitioners of classification modeling need better understanding of those algorithms in order to select the optimal algorithm for given classification problems. Researchers of classification need new insight on how given classifiers are weak and how they can be improved by correcting their classification errors. This dissertation introduces new tools and concepts to analyze classifier weakness …
Data Driven Analysis And Characterization Of Modern Android Malware,
2021
Dartmouth College
Data Driven Analysis And Characterization Of Modern Android Malware, Qian Han
Dartmouth College Ph.D Dissertations
Google’s Android operating system was first announced to the public in 2007 and was installed on more than three billion mobile devices by 2019. With the prevalence of Android OS, Android malware has since proliferated. Android malware is malicious software designed to exploit Android operating systems running on smart devices. Some variants of Android malware have the capability of disabling the device, allowing a malicious actor to remotely control the device, track the user’s activity, lock the device, and so on. Moreover, the evolution and sophistication of modern Android malware obfuscation and detection bypassing methods have significantly improved in recent …
Long Short-Term Memory With Spin-Based Binary And Non-Binary Neurons,
2021
University of Central Florida
Long Short-Term Memory With Spin-Based Binary And Non-Binary Neurons, Meghana Reddy Vangala
Electronic Theses and Dissertations, 2020-2023
Research in the field of neural networks has shown advancement in the device technology and machine learning application platforms of use. Some of the major applications of neural network prominent in recent scenarios include image recognition, machine translation, text classification and object categorization. With these advancements, there is a need for more energy-efficient and low area overhead circuits in the hardware implementations. Previous works have concentrated primarily on CMOS technology-based implementations which can face challenges of high energy consumption, memory wall, and volatility complications for standby modes. We herein developed a low-power and area-efficient hardware implementation for Long Short-Term Memory …
Spectral And Latent Representation Distortion For Tts Evaluation,
2021
Faculty of Engineering
Spectral And Latent Representation Distortion For Tts Evaluation, Thananchai Kongthaworn
Chulalongkorn University Theses and Dissertations (Chula ETD)
One of the main problems in the development of text-to-speech (TTS) systems is its reliance on subjective measures, typically the Mean Opinion Score (MOS). MOS requires a large number of people to reliably rate each utterance, making the development process slow and expensive. Recent research on speech quality assessment tends to focus on training models to estimate MOS, which requires a large number of training data, something that might not be available in low-resource languages. We propose an objective assessment metric based on the DTW distance using the spectrogram and the high-level features from an Automatic Speech Recognition (ASR) model …
Improved Secure And Low Computation Authentication Protocol For Wireless Body Area Network With Ecc And 2d Hash Chain,
2021
South Dakota State University
Improved Secure And Low Computation Authentication Protocol For Wireless Body Area Network With Ecc And 2d Hash Chain, Soohyeon Choi
Electronic Theses and Dissertations
Since technologies have been developing rapidly, Wireless Body Area Network (WBAN) has emerged as a promising technique for healthcare systems. People can monitor patients’ body condition and collect data remotely and continuously by using WBAN with small and compact wearable sensors. These sensors can be located in, on, and around the patient’s body and measure the patient’s health condition. Afterwards sensor nodes send the data via short-range wireless communication techniques to an intermediate node. The WBANs deal with critical health data, therefore, secure communication within the WBAN is important. There are important criteria in designing a security protocol for a …
Dales Objects: A Large Scale Benchmark Dataset For Instance Segmentation In Aerial Lidar,
2021
University of Dayton
Dales Objects: A Large Scale Benchmark Dataset For Instance Segmentation In Aerial Lidar, Nina M. Singer, Vijayan K. Asari
Electrical and Computer Engineering Faculty Publications
We present DALES Objects, a large-scale instance segmentation benchmark dataset for aerial lidar. DALES Objects contains close to half a billion hand-labeled points, including semantic and instance segmentation labels. DALES Objects is an extension of the DALES (Varney et al., 2020) dataset, adding additional intensity and instance segmentation annotation. This paper provides an overview of the data collection, preprocessing, hand-labeling strategy, and final data format. We propose relevant evaluation metrics and provide insights into potential challenges when evaluating this benchmark dataset. Finally, we provide information about how researchers can access the dataset for their use at go.udayton.edu/dales3d.
Energy-Aware Real-Time Scheduling On Heterogeneous And Homogeneous Platforms In The Era Of Parallel Computing,
2021
University of Central Florida
Energy-Aware Real-Time Scheduling On Heterogeneous And Homogeneous Platforms In The Era Of Parallel Computing, Ashik Ahmed Bhuiyan
Electronic Theses and Dissertations, 2020-2023
Multi-core processors increasingly appear as an enabling platform for embedded systems, e.g., mobile phones, tablets, computerized numerical controls, etc. The parallel task model, where a task can execute on multiple cores simultaneously, can efficiently exploit the multi-core platform's computational ability. Many computation-intensive systems (e.g., self-driving cars) that demand stringent timing requirements often evolve in the form of parallel tasks. Several real-time embedded system applications demand predictable timing behavior and satisfy other system constraints, such as energy consumption. Motivated by the facts mentioned above, this thesis studies the approach to integrating the dynamic voltage and frequency scaling (DVFS) policy with real-time …
A Comparison Of Artificial Neural Networks And The Statistical Methods In Predicting Mba Student’S Academic Performance,
2021
California State University, Fresno
A Comparison Of Artificial Neural Networks And The Statistical Methods In Predicting Mba Student’S Academic Performance, Ojoung Kwon, Harry Hui Xia, Serin Zhang
Journal of International Technology and Information Management
MBA has become one of the most popular and vital professional degrees internationally. The MBA program admission process’s essential task is to choose the best analysis tools to accurately predict applicants’ academic performance potential based on the evaluation criteria in making admission decisions. Prior research finds that the Graduate Management Admission Test (GMAT) and undergraduate grade point average (UGPA) are common predictors of MBA academic performance indicated by graduate grade point average (GGPA). Using a sample of 250 MBA students enrolled in a state university with AACSB accreditation from Fall 2010 to Fall 2017, we test and compare the effectiveness …
An Integrated View Of Knowledge Management Enablers, Components, And Benefits: Comprehensive Literature Review,
2021
Morgan State University
An Integrated View Of Knowledge Management Enablers, Components, And Benefits: Comprehensive Literature Review, Shuaibu Hassan Usman, Jigish Zaveri, Aminu Hamza
Journal of International Technology and Information Management
The key to success in the 21st century, knowledge-based economy, will be the effective and efficient management of knowledge. Knowledge Management (KM) has a direct impact on organizational success. KM in a knowledge-based economy entails growth, value, and improving living standards through knowledge creation, storage, and dissemination. This study aims to integrate KM enablers, components, and benefits into a single view through a comprehensive literature search. The integrative view of these three factors would facilitate the understanding of KM initiatives within organizations. This paper performs a comprehensive literature review to explain the KM enablers, components, and benefits. From the …
