Frederick Harris

Verified

Frederick verified their affiliation via an institutional email.

Learn more

Verified

Frederick verified their affiliation via an institutional email.

Learn more

• Doctor of Philosophy
• Foundation Professor at University of Nevada, Reno

Point cloud data from light detection and ranging (LiDAR) is often used for its spatial qualities, particularly in smart city projects involving vehicles and pedestrians. In this paper, the authors introduce a streaming and an on-demand pipeline for capturing LiDAR data from Velodyne Ultra Pucks placed along nine northern Nevada intersections known...

Transformers have achieved remarkable performance in multivariate time series(MTS) forecasting due to their capability to capture long-term dependencies. However, the canonical attention mechanism has two key limitations: (1) its quadratic time complexity limits the sequence length, and (2) it generates future values from the entire historical sequ...

Predicting valence and arousal values from EEG signals has been a steadfast research topic within the field of Affective Computing or Emotional AI. Although many valid techniques to predict valence and arousal values from EEG signals have been established and verified, the EEG data collection process itself is relatively undocumented. This creates...

Underground mining operations inherently involve significant risks, such as the collapse of surrounding rock or fires. While infrequent, the potentially catastrophic nature of these events highlights the essential need for swift and secure evacuation procedures, ensuring the safety and survival of mineworkers in such situations. The traditional sta...

Multivariate time series forecasting is a critical problem in many real-world scenarios. Recent advances in deep learning have significantly enhanced the ability to tackle such problems. However, a primary challenge in time series forecasting comes from the imbalanced time series data that include extreme events. Despite being a small fraction of t...

In many smart city projects, a common choice to capture spatial information is the inclusion of lidar data, but this decision will often invoke severe growing pains within the existing infrastructure. In this article, the authors introduce a data pipeline that orchestrates Apache NiFi (NiFi), Apache MiNiFi (MiNiFi), and several other tools as an au...

Predicting valence and arousal values from EEG signals has been a steadfast research topic within the field of affective computing or emotional AI. Although numerous valid techniques to predict valence and arousal values from EEG signals have been established and verified, the EEG data collection process itself is relatively undocumented. This crea...

Multivariate Time Series (MTS) forecasting entails the intricate process of modeling temporal dependencies within historical data records. Transformers have demonstrated remarkable performance in MTS forecasting due to their capability to capture long-term dependencies. However, prior work has been confined to modeling temporal dependencies at eith...

This paper presents a work-in-progress on a learning system that will provide robotics students with a personalized learning environment. This addresses both the scarcity of skilled robotics instructors, particularly in community colleges and the expensive demand for training equipment. The study of robotics at the college level represents a wide r...

Cloud computing is a concept introduced in the information technology era, with the main components being the grid, distributed, and valuable computing. The cloud is being developed continuously and, naturally, comes up with many challenges, one of which is scheduling. A schedule or timeline is a mechanism used to optimize the time for performing a...

The specific hiring needs render low-skill-based job-seeking invalid in coping with the nation's economic development. There needs to be more graduate readiness for the industry's needs. This paper explores the transformative potential of Artificial Intelligence (AI) in fostering a symbiotic relationship between academic curricula and industry dema...

Cloud computing is a concept introduced in the information technology era, with the main components being the grid, distributed, and valuable computing. The cloud is being developed continuously and, naturally, comes up with many challenges, one of which is scheduling. A schedule or timeline is a mechanism used to optimize the time for performing a...

span lang="EN-US">Dysphoria is a trigger point for maladjusted individuals who cannot cope with disappointments and crushed expectations, resulting in negative emotions if it is not detected early. Individuals who suffer from dysphoria tend to deny their mental state. They try to hide, suppress, or ignore the symptoms, making one feel worse, unwant...

This paper presents a work-in-progress on a learn-ing system that will provide robotics students with a personalized learning environment. This addresses both the scarcity of skilled robotics instructors, particularly in community colleges and the expensive demand for training equipment. The study of robotics at the college level represents a wide...

This paper presents a work-in-progress on a learning system that will provide robotics students with a personalized learning environment. This addresses both the scarcity of skilled robotics instructors, particularly in community colleges and the expensive demand for training equipment. The study of robotics at the college level represents a wide r...

Multivariate Time Series (MTS) forecasting involves modeling temporal dependencies within historical records. Transformers have demonstrated remarkable performance in MTS forecasting due to their capability to capture long-term dependencies. However, prior work has been confined to modeling temporal dependencies at either a fixed scale or multiple...

Data acquisition is an integral part in any intelligent system to ensure the data captured can be processed to a meaningful deduction. It is common for the researchers to use the third-party hardware to collect raw data but integrating the processes into a research workflow is always a challenge. This is especially so for individuals working with s...

Many applications in industrial mining rely on large manually operated trucks to transport materials around the mine. These trucks are often enormous, with very limited visibility for the driver. The combination of limited visibility and a truck with a substantial amount of weight is a recipe for accidents resulting in severe property destruction o...

One of the most significant reliable and renewable energy sources is wave energy which has the most energy density among the renewable energy sources. Significant Wave Height (SWH) plays a major role in wave energy and hence this study aims to predict wave height using time series of wave characteristics as input to various machine learning approac...

Background The advance in single-cell RNA sequencing technology has enhanced the analysis of cell development by profiling heterogeneous cells in individual cell resolution. In recent years, many trajectory inference methods have been developed. They have focused on using the graph method to infer the trajectory using single-cell data, and then cal...

Reducing the number of link crossings in a network drawn on the plane such as a wiring board is a well-known problem, and especially the calculation of the minimum number of such crossings: this is the crossing number problem. It has been shown that finding a general solution to the crossing number problem is NP-hard. So, this problem is addressed...

The bijective connection graph encompasses a family of cube-based topologies, and $n$ -dimensional bijective connection graphs include the hypercube and almost all of its variants with the order $2^{n}$ and the degree $n$ . Hence, it is important to design and implement algorithms that work in bijective connection graphs. The set-to-set disjo...

Human error in medicine – medical error – has been identified as the third leading cause of death within the United States. Analyses of deaths attributable to medical error conclude that faulty communication plays a central role in medical error. Patient handoffs, the transfer of patient care from one medical professional to another, are frequently...

Recently artificial intelligence (AI) and machine learning (ML) models have demonstrated remarkable progress with applications developed in various domains. It is also increasingly discussed that AI and ML models and applications should be transparent, explainable, and trustworthy. Accordingly, the field of Explainable AI (XAI) is expanding rapidly...

Virtual worlds have the potential to mirror many aspects of real life. Immersive virtual worlds constructed through the use of Virtual Reality (VR) are useful in simulating the technology, equipment, and practices of many different fields. In the medical field, VR can be heavily relied upon to circumvent a wide variety of tools, human resources, an...

Internet service providers are offering shared data plans where multiple users may buy and sell their overage data in a secondary market managed by the ISP. We propose a game-theoretic approach to a software-defined network for modeling this wireless data exchange market: a fully connected, non-cooperative network. We identify and define the rules...

In many different kinds of complex forms (financial, job applications, etc.), information button widgets are used to give context-specific information to enable users to fill out forms completely. However, in longer forms, “decision fatigue” can set in, leading to the user not absorbing these helpful tips but rather rushing through and possibly mak...

Cloud computing is one of the most significant trends in the information technology evolution, as it has created new opportunities that were never possible before. It is utilized and adopted by individuals and businesses on all scales, from a cloud-storage service such as Google Drive for normal users, to large scale integrated servers for online s...

In geophysics, the slant stack transform is a method used to align signals from different sensors. We focus on the use of the transform within passive refraction microtremor (ReMi) surveys, in order to produce high resolution slowness-frequency plots for use as samples in a machine learning model. Running on a single central processing unit (CPU) t...

With the big data boom, recommender systems that make intelligent recommendations for users have been playing an important role in today’s industry. However, existing recommender systems often overlook scalability, flexibility, and portability. They also commonly lack in-situ visualizations. To solve these problems, we present CARS: A Containerized...

In this paper, we use graphics processing units(GPU) to accelerate sparse and arbitrary structured neural networks. Sparse networks have nodes in the network that are not fully connected with nodes in preceding and following layers, and arbitrary structure neural networks have different number of nodes in each layers. Sparse Neural networks with ar...

Communication and situational awareness, among other "human factors," are critical skills needed within high-reliability organizations (HROs). HROs are challenged to develop an effective methodology for the systematic assessment of these skills. Virtual reality (VR) simulation technology offers a promising approach to meet this challenge. By utiliz...

Due to the complexity and heterogeneity inherent to the hydrologic cycle, the modeling of physical water processes has historically and inevitably been characterized by a broad spectrum of disciplines including data management, visualization, and statistical analyses. This is further complicated by the sub-disciplines within the water science commu...

This paper studies how to improve the accuracy of hydrologic models using machine-learning models as post-processors and presents possibilities to reduce the workload to create an accurate hydrologic model by removing the calibration step. It is often challenging to develop an accurate hydrologic model due to the time-consuming model calibration pr...

Many complex real world systems can be represented as correlated high dimensional vectors (up to 20,501 in this paper). While univariate analysis is simpler, it does not account for correlations between variables. This omission often misleads researchers by producing results based on unrealistic assumptions. As the generation of large correlated da...

Capsule Networks are an emerging extension of the traditional multilayer perceptron model, providing classification and estimated pose parameters through extra computational data models such as vectors and matrices. With extra data comes extra processing and meticulous data manipulation and this paper presents a scalable GPU optimization for the tr...

Image analysis is an important area in many fields of research, such as sensor networks, where webcams have become an increasingly popular addition. Sensor network webcams gather images frequently and, as such, a need for processing large image streams has occurred. In this paper, we test a variety of OpenCV functions on image streams from sensor n...

Missing data may be one of the biggest problems hindering modern research science. It occurs frequently, for various reasons, and slows down crucial data analytics required to answer important questions related to global issues like climate change and water management. The modern answer to this problem of missing data is data imputation. Specifical...

While quantum computing has shown great promise in the field of computer science, a lack of actual practical quantum hardware means that mainstream research must rely on simulations. As such, a wide number of quantum computing simulation libraries have been developed, each with their own strengths and weaknesses. A good simulator must not just be a...

In aviation there can be little room for error. This paper explores software arbitration of two joysticks controlled by two pilots, where each joystick is independent of the other and each pilot's actions are potentially equally valid. In such scenarios, it can be difficult to know which commands are valid, and which commands should be ignored. Ins...

The physically-based environmental model is a crucial tool used in many scientific inquiries. With physical modeling, different models are used to simulate real world phenomena and most environmental scientists use their own devices to execute the models. A complex simulation can be time-consuming with limited computing power. Also, sharing a scien...

This paper studies how to improve the accuracy of hydrologic models using machine learning models as post-processors and presents possibilities to reduce the workload to create an accurate hydrologic model by removing the calibration step. It is often challenging to develop an accurate hydrologic model, due to the time-consuming model calibration p...

In this paper, we introduce Music in a Universal Sound Environment(MUSE), a system for gesture recognition in the domain of musical conducting. Our system captures conductors’ musical gestures to drive a MIDI-based music generation system allowing a human user to conduct a fully synthetic orchestra. Moreover, our system also aims to further improve...

In this paper we present a parallel system that retrieves and parses Form 4 documents from the Securities and Exchange Commission’s Electronic Data Gathering, Analysis and Retrieval database (EDGAR). This information is very important for investors looking at insider trading information to make investment decisions. However, the information’s usefu...

Software architecture is an essential phase of the software development process, as it significantly increases the success rate of software projects and enables achieving their quality attributes and goals. However, implementing software architecture is not a straightforward process, and requires specialized expertise and knowledge -in both domain...

In this paper, we present a novel and accessible approach to time-series data validation: the Near-Real Time Autonomous Quality Control (NRAQC) system. The design, implementation, and impacts of this software are explored in detail within this paper. This software system, created in close conference with environmental scientists, leverages microser...

In traditional software projects development, there were mandatory activities that should be carried out during the software development life cycle (SDLC). These activities were time-consuming and expensive. They were either performed manually or in basic approaches by different roles. Some of these activities include: version control, project stru...

Compression is widely used in both scientific research and industry. The most common use is that people compress the backup data and infrequently used data to save spaces. Compression is significantly meaningful for big data because it will save a lot of resources with the help of a good compression algorithm. There are two criteria for a good comp...

Background: Networks provide effective models to study complex biological systems, such as gene and protein interaction networks. With the advent of new sequencing technologies, many life scientists are grasping for user-friendly methods and tools to examine biological components at the whole-systems level. Gene co-expression network analysis appr...

Finding the maximum clique in a graph is useful for solving problems in many real world applications. However the problem is classified as NP-hard, thus making it very difficult to solve for large and dense graphs. This paper presents one of the only exact maximum clique solvers that takes advantage of the parallelism of Graphical Processing Units...

Since the introduction of the Modern Portfolio Theory by Markowitz in the Journal of Finance in 1952, it has been the underlying theory in several portfolio optimization techniques. With the advancement of computers, most portfolio optimization are done by CPUs. Over the years, there have been papers that introduce various optimization methods incl...

Go is a fascinating game that has yet to be played well by a computer program due to its large board size and exponential time complexity. This paper presents a GPU implementation of PV-Split, a parallel implementation of a widely used game tree search algorithm for two-player zero-sum games. With many game trees, it often takes too much time to tr...

Currently, there are limited, commercially available video games for people with disabilities. Sim-Assist is a software system that aims to allow people with disabilities to interface with a three-dimensional simulation game of Air Hockey. This is accomplished through various integrated assistive technologies, such as brain-computer interfacing, vo...

The creation and simulation of ion channel models using continuous-time Markov processes is a powerful and well-used tool in the field of electrophysiology and ion channel research. While several software packages exist for the purpose of ion channel modeling, most are GUI based, and none are available as a Python library. In an attempt to provide...