Artificial Intelligence and Robotics Commons^™

Identification Of Factors Contributing To Traffic Crashes By Analysis Of Text Narratives, Cristian D. Arteaga-Sanchez

UNLV Theses, Dissertations, Professional Papers, and Capstones

The fatalities, injuries, and property damage that result from traffic crashes impose a significant burden on society. Current research and practice in traffic safety rely on analysis of quantitative data from crash reports to understand crash severity contributors and develop countermeasures. Despite advances from this effort, quantitative crash data suffers from drawbacks, such as the limited ability to capture all the information relevant to the crashes and the potential errors introduced during data collection. Crash narratives can help address these limitations, as they contain detailed descriptions of the context and sequence of events of the crash. However, the unstructured nature …

A Mechanically Intelligent Hosing-Drone, Blake Hament

UNLV Theses, Dissertations, Professional Papers, and Capstones

This manuscript presents a ”mechanically intelligent” approach to designing a Hosing-Drone for heavy-duty pressure washing. Spraying a hose creates strong reaction forces and torques. Previously demonstrated spraying robots are over-engineered to be very massive with huge inertias. These high inertias ”wash out” the reaction from the spraying. In the proposed approach, the contributions from all observable fluid dynamics, fluid structure interactions, and aerodynamics are studied individually and for the coupled system. Experimental data is collected and fit to dynamic models. These models are used to design a smaller, lighter, more agile vehicle than has been previously demonstrated. An impedance controller …

On The Merge Of K-Nn Graph, Wan-Lei Zhao, Hui Wang, Peng-Cheng Lin, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

k-nearest neighbor graph is a fundamental data structure in many disciplines such as information retrieval, data-mining, pattern recognition, and machine learning, etc. In the literature, considerable research has been focusing on how to efficiently build an approximate k-nearest neighbor graph (k-NN graph) for a fixed dataset. Unfortunately, a closely related issue of how to merge two existing k-NN graphs has been overlooked. In this paper, we address the issue of k-NN graph merging in two different scenarios. In the first scenario, a symmetric merge algorithm is proposed to combine two approximate k-NN graphs. The algorithm facilitates large-scale processing by the …

Conversation Disentanglement With Bi-Level Contrastive Learning, Chengyu Huang, Zheng Zhang, Hao Fei, Lizi Liao

Research Collection School Of Computing and Information Systems

Conversation disentanglement aims to group utterances into detached sessions, which is a fundamental task in processing multi-party conversations. Existing methods have two main drawbacks. First, they overemphasize pairwise utterance relations but pay inadequate attention to the utterance-to-context relation modeling. Second, a huge amount of human annotated data is required for training, which is expensive to obtain in practice. To address these issues, we propose a general disentangle model based on bi-level contrastive learning. It brings closer utterances in the same session while encourages each utterance to be near its clustered session prototypes in the representation space. Unlike existing approaches, our …

Hard-Real-Time Computing Performance In A Cloud Environment, Alvin Cornelius Murphy

Engineering Management & Systems Engineering Theses & Dissertations

The United States Department of Defense (DoD) is rapidly working with DoD Services to move from multi-year (e.g., 7-10) traditional acquisition programs to a commercial industrybased approach for software development. While commercial technologies and approaches provide an opportunity for rapid fielding of mission capabilities to pace threats, the suitability of commercial technologies to meet hard-real-time requirements within a surface combat system is unclear. This research establishes technical data to validate the effectiveness and suitability of current commercial technologies to meet the hard-real-time demands of a DoD combat management system. (Moreland Jr., 2013) conducted similar research; however, microservices, containers, and container …

Towards Privacy And Security Concerns Of Adversarial Examples In Deep Hashing Image Retrieval, Yanru Xiao

Computer Science Theses & Dissertations

With the explosive growth of images on the internet, image retrieval based on deep hashing attracts spotlights from both research and industry communities. Empowered by deep neural networks (DNNs), deep hashing enables fast and accurate image retrieval on large-scale data. However, inheriting from deep learning, deep hashing remains vulnerable to specifically designed input, called adversarial examples. By adding imperceptible perturbations on inputs, adversarial examples fool DNNs to make wrong decisions. The existence of adversarial examples not only raises security concerns for real-world deep learning applications, but also provides us with a technique to confront malicious applications.

In this dissertation, we …

Expressiveness Of Real-Time Motion Captured Avatars Influences Perceived Animation Realism And Perceived Quality Of Social Interaction In Virtual Reality, Alan D. Fraser, Isabella Branson, Ross C. Hollett, Craig P. Speelman, Shane L. Rogers

Research outputs 2022 to 2026

Using motion capture to enhance the realism of social interaction in virtual reality (VR) is growing in popularity. However, the impact of different levels of avatar expressiveness on the user experience is not well understood. In the present study we manipulated levels of face and body expressiveness of avatars while investigating participant perceptions of animation realism and interaction quality when disclosing positive and negative experiences in VR. Moderate positive associations were observed between perceptions of animation realism and interaction quality. Post-experiment questions revealed that many of our participants (approximately 40 %) indicated the avatar with the highest face and body …

Divide-And-Conquer Distributed Learning: Privacy-Preserving Offloading Of Neural Network Computations, Lewis C.L. Brown

Graduate Theses and Dissertations

Machine learning has become a highly utilized technology to perform decision making on high dimensional data. As dataset sizes have become increasingly large so too have the neural networks to learn the complex patterns hidden within. This expansion has continued to the degree that it may be infeasible to train a model from a singular device due to computational or memory limitations of underlying hardware. Purpose built computing clusters for training large models are commonplace while access to networks of heterogeneous devices is still typically more accessible. In addition, with the rise of 5G networks, computation at the edge becoming …

Data-Driven Deep Learning-Based Analysis On Thz Imaging, Haoyan Liu

Graduate Theses and Dissertations

Breast cancer affects about 12.5% of women population in the United States. Surgical operations are often needed post diagnosis. Breast conserving surgery can help remove malignant tumors while maximizing the remaining healthy tissues. Due to lacking effective real-time tumor analysis tools and a unified operation standard, re-excision rate could be higher than 30% among breast conserving surgery patients. This results in significant physical, physiological, and financial burdens to those patients. This work designs deep learning-based segmentation algorithms that detect tissue type in excised tissues using pulsed THz technology. This work evaluates the algorithms for tissue type classification task among freshly …

Movie Reviews Sentiment Analysis Using Bert, Gibson Nkhata

Graduate Theses and Dissertations

Sentiment analysis (SA) or opinion mining is analysis of emotions and opinions from texts. It is one of the active research areas in Natural Language Processing (NLP). Various approaches have been deployed in the literature to address the problem. These techniques devise complex and sophisticated frameworks in order to attain optimal accuracy with their focus on polarity classification or binary classification. In this paper, we aim to fine-tune BERT in a simple but robust approach for movie reviews sentiment analysis to provide better accuracy than state-of-the-art (SOTA) methods. We start by conducting sentiment classification for every review, followed by computing …

An Investigation Into Whitening Loss For Self-Supervised Learning, Xi Weng, Lei Huang, Lei Zhao, Rao Muhammad Anwer, Salman Khan, Fahad Shahbaz Khan

Computer Vision Faculty Publications

A desirable objective in self-supervised learning (SSL) is to avoid feature collapse. Whitening loss guarantees collapse avoidance by minimizing the distance between embeddings of positive pairs under the conditioning that the embeddings from different views are whitened. In this paper, we propose a framework with an informative indicator to analyze whitening loss, which provides a clue to demystify several interesting phenomena as well as a pivoting point connecting to other SSL methods. We reveal that batch whitening (BW) based methods do not impose whitening constraints on the embedding, but they only require the embedding to be full-rank. This full-rank constraint …

Contribution Rate Calculation Method To System-Of-Systems Based On Interval-Valued Intuitionistic Fuzzy Number Anp, Zejian Ding, Songtao Sun, Zhiwen He, Fei Liu

Journal of System Simulation

Abstract: Contribution rate to system-of-systems (CRSoS) is mainly used to measure the contribution of an equipment to system of systems (SoS) in system construction. In order to solve some problems in the calculation of CRSoS, a multi-level equipment indicator architecture of "task-ability-indicator- equipment" is proposed. At the same time, considering the characteristics of the equipment indicator architecture, ANP (analytic network process) and IVIFN (interval-valued intuitionistic fuzzy number), a IVIF-ANP calculation method is proposed to obtain more accurate CRSoS. Experiments show that this method can not only solve the problem of the calculation formula of CRSoS, but also obtain more …

Simulation And Effectiveness Evaluation System For Joint Delivery Mission Planning Of Airlift Fleets, Guochen Wang

Journal of System Simulation

Abstract: Airlift fleet plays an important role in modern war. Compared with other countries such as the USA and Russia, China's airlift fleet still has obvious shortcomings and deficiencies. To analysis and optimize the future fleet alternatives, a software tool is established with the modules of model construction and management, scenarios editing, mission planning, simulation deduction, effectiveness analysis. This tool mainly focuses on the interactive relationship between the transport aircraft and cargo, airport and so on, as well as the cooperative relationship of different types of aircraft, which can realize the functions of automatic generation of loading schemes, automatic planning …

Research On Key Technology Of Uavs Autonomous Landing Based On Relative Precise Point Position, Guohua Kang, Teng Zhao, Yao Fu, Weizheng Xu, Jianyu Wei, Yuhuan Qiu, Junfeng Wu

Journal of System Simulation

Abstract: In complex sea conditions with wind and waves, the relative motion between unmanned aerial vehicles (UAVs) requiring autonomous landing and ships is highly uncertain. In order to improve the accuracy of relative positioning and control during autonomous landing, and to ensure the safety and reliability of autonomous landing, a relative precise point positioning (RPPP) technique based on differential tropospheric error is proposed. The technology only relies on data link and carrier satellite positioning receiver to eliminate the same error of satellite positioning in the same environment and obtain accurate relative positioning. The combination of proportional navigation and linear quadratic …

Robust Optimal Configuration Of Pv-Energy Storage In Industrial Parks Considering The Uncertainty Of Photovoltaics, Guiting Xue, Boya Shan, Ti Wang, Xiao Wang, Wei Xing, Weiqing Sun

Journal of System Simulation

Abstract: Research on using rooftop resources in industrial parks to develop photovoltaic projects and reasonable configuration of energy storage will help improve the park's energy economy. To obtain the optimal PV-storage configuration scheme, an industrial park with three types of load demand, namely, cold, heat and electricity, is selected, and a robust optimization allocation model of park PV-storage is established with optimal operating profit as the objective function, considering the increased cost of power purchase caused by the PV uncertainty. The model uses the box uncertainty set in robust optimization for PV intensity, and linearizes the model using pairwise …

Evacuation Model Considering The Restricted View Of The Sign, Yinghua Song, Zheqian Zhang, Feizhou Huo, Danhui Fang

Journal of System Simulation

Abstract: In order to study the influence of restricted vision on the process of pedestrian evacuation, a cellular automata model of pedestrian evacuation under restricted vision is established. In the model, the evacuation space is divided into three different areas according to the field of view radius, pedestrians have different ways of moving in different areas. Different income parameters are defined to calculate the pedestrian movement income matrix and determine the target position of the pedestrian in the next time step. An evacuation scene is established to simulate the initial density of different pedestrians, the change of the field of …

Simulation Of O2o Platform Transaction Considering The Constituted Information, Wen Zheng, Ke Shi, Jingyi Zhu

Journal of System Simulation

Abstract: In the transactions concluded with the help of APP, the information intervenes into the transaction process in the form of constituted information. The constituted information is classified into three degrees in a two-sided market. By introducing the three degrees of the constituted information: information acceptance (IA), information diversity (ID) and information loss (IL), the Swarm Class Library and the interactive Agents are designed to construct a systematic O2O (online to offline)platform transaction model, which encapsulates the Consumer/Seller/PlatformAgents. The constituted information acts as the systematic conditions of invoking and judging, and the graphical user interface (GUI) outputs the …

Multi-Uav Trajectory Planning Based On Adaptive Segmented Potential Field Method, Guangjian Tian, Jiyang Dai, Jin Ying, Ning Wang

Journal of System Simulation

Abstract: To solve the problems that the traditional artificial potential field method is prone to fall into the local extreme value, target unreachability and excessive curvature of the planned trajectory curvature in the application of UAV trajectory planning, on the basis of the layered potential field method, a method of adding a second local attractive field at the target point and an attractive set composed of the target attractive field is proposed. This method overcomes the defects of unreachable targets and easy falling into local extremes. In addition, a piecewise function is introduced into the original layered potential field method, …

Nonlinear System Identification Based On Combined Signal Sources, Tian Zheng, Feng Li, Naibao He, Ya Gu

Journal of System Simulation

Abstract: Aiming at the interference of noise in the nonlinear system, the identification modeling method of the neuro-fuzzy Hammerstein output error nonlinear system is considered. The combined signal sources are used to realize the parameter identification separation of the linear block and the nonlinear block. The correlation analysis method and the recursive least square identification method based on auxiliary model technique are derived to estimate the parameters of dynamic linear block and nonlinear block, which can effectively suppress the interference of system output noise. Compared with least square algorithm, polynomial model and multi-innovation method, the simulation results demonstrate that the …

A Real-Time Ultrasound Simulation Platform Using Ray Tracing And Its Integration With Virtual Reality, Bo Peng, Qiang Wang, Ruibing Qing, Lixue Yin, Jingfeng Jiang

Journal of System Simulation

Abstract: In order to further improve the efficacy of ultrasound training and reduce the cost. An ultrasound training system that is integrated with a VR environment is developed. The main contribution of this study is to incorporate the Ray-tracing based ultrasound image simulation approach into a virtual reality environment, taking advantage of immersive VR experience for medical ultrasound training. The simulated ultrasound images obtained by the proposed method are then compared to images that are simulated using a generative adversarial network (GAN) technique and Field II ultrasound simulator. The data show that the ultrasound simulator can produce high-quality simulated …