Digital Commons Network^™

Rip Curl: Community Activism For The Coast (The Ux Phase, Rip Curl And Sustainability, The Ui Phase), John Delacruz

Assignment Prompts

ADV 132 enables students to explore the craft and process of user experience and user interface design. They develop their skills within the context of a specific brief. The aim is to offer students the opportunity to immerse themselves in a particular problem and come up with creative solutions that will come to life on digital media platforms.

Self-Regulation For Semantic Segmentation, Dong Zhang, Hanwang Zhang, Jinhui Tang, Xian-Sheng Hua, Qianru Sun

Research Collection School Of Computing and Information Systems

In this paper, we seek reasons for the two major failure cases in Semantic Segmentation (SS): 1) missing small objects or minor object parts, and 2) mislabeling minor parts of large objects as wrong classes. We have an interesting finding that Failure-1 is due to the underuse of detailed features and Failure-2 is due to the underuse of visual contexts. To help the model learn a better trade-off, we introduce several Self-Regulation (SR) losses for training SS neural networks. By “self”, we mean that the losses are from the model per se without using any additional data or supervision. By …

Uncovering Patterns In Reviewers' Feedback To Scene Description Authors, Rosiana Natalie, Jolene Kar Inn Loh, Huei Suen Tan, Joshua Shi-Hao Tseng, Hernisa Kacorri, Kotaro Hara

Research Collection School Of Computing and Information Systems

Audio descriptions (ADs) can increase access to videos for blind people. Researchers have explored different mechanisms for generating ADs, with some of the most recent studies involving paid novices; to improve the quality of their ADs, novices receive feedback from reviewers. However, reviewer feedback is not instantaneous. To explore the potential for real-time feedback through automation, in this paper, we analyze 1,120 comments that 40 sighted novices received from a sighted or a blind reviewer. We find that feedback patterns tend to fall under four themes: (i) Quality; commenting on different AD quality variables, (ii) Speech Act; the utterance or …

Rotten With Prediction, Serena Raquel Hicks

UNLV Theses, Dissertations, Professional Papers, and Capstones

This project focuses on the relationship between religion and technology as it is portrayed in Science Fiction (SF). This thesis explores the SF genre rhetorically by examining the 2002 movie Minority Report (MR), which signaled the importance of surveillance and the need to predict future crimes following 9/11. The events of 9/11 played a significant role in post 9/11 SF films, which reflect and critique our communal and cultural values. 9/11 created a new relationship between the U.S justice system, predictive technologies (PTs), and data gathering. Through the Bush Doctrine of “preemptive action,” the U.S government attempted to use Dataism, …

Uncertainty-Aware Visualization In Medical Imaging - A Survey, Christina Gillmann, Dorothee Saur, Thomas Wischgoll, Gerik Scheuermann

Computer Science and Engineering Faculty Publications

Medical imaging (image acquisition, image transformation, and image visualization) is a standard tool for clinicians in order to make diagnoses, plan surgeries, or educate students. Each of these steps is affected by uncertainty, which can highly influence the decision-making process of clinicians. Visualization can help in understanding and communicating these uncertainties. In this manuscript, we aim to summarize the current state-of-the-art in uncertainty-aware visualization in medical imaging. Our report is based on the steps involved in medical imaging as well as its applications. Requirements are formulated to examine the considered approaches. In addition, this manuscript shows which approaches can be …

Pedestrian Attribute Recognition Using Two-Branch Trainable Gabor Wavelets Network, Imran N. Junejo

All Works

Keeping an eye on pedestrians as they navigate through a scene, surveillance cameras are everywhere. With this context, our paper addresses the problem of pedestrian attribute recognition (PAR). This problem entails recognizing attributes such as age-group, clothing style, accessories, footwear style etc. This multi-label problem is extremely challenging even for human observers and has rightly garnered attention from the computer vision community. Towards a solution to this problem, in this paper, we adopt trainable Gabor wavelets (TGW) layers and cascade them with a convolution neural network (CNN). Whereas other researchers are using fixed Gabor filters with the CNN, the proposed …

Social Media User Relationship Framework (Smurf), Anne David, Sarah Morris, Gareth Appleby-Thomas

Journal of Digital Forensics, Security and Law

The use of social media has spread through many aspects of society, allowing millions of individuals, corporate as well as government entities to leverage the opportunities it affords. These opportunities often end up being exploited by a small percentage of the user community who use it for objectionable or unlawful activities; for example, trolling, cyber bullying, grooming, luring. In some cases, these unlawful activities result in investigations where swift retrieval of critical evidence required in order to save a life.

This paper presents a proof of concept (PoC) framework for social media user attribution. The framework aims to provide digital …

Visualizing The Range Of Glaciers: Science, Art And Narrative, Claire E. Waichler

Honors Theses

Glaciers are sensitive indicators and data keepers of climatic change. The glaciers of the North Cascades, Washington, also have significant economic and cultural value as they are enmeshed in hydroelectricity generation, terrestrial and aquatic ecology, and human communities. My project approaches the current climate crisis by examining the past, present and future of the glaciers of the North Cascades through the two lenses of art and science. I review and contextualize the last century of glacier research in the North Cascades to identify patterns of glacier change and how this affects ecological and human communities. Overlaid upon my literature review, …

A Novel Hybrid Decision-Based Filter And Universal Edge-Based Logical Smoothingadd-On To Remove Impulsive Noise, Rajanbir Singh Ghumaan, Prateek Jeet Singh Sohi, Nikhil Sharma, Bharat Garg

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents a novel hybrid filter along with a universal extension to remove salt and pepper noise even at a very high noise density. The proposed filter initially specifies a threshold and then denoises the image using a combination of linear, nonlinear, and probabilistic techniques. Furthermore, to improve the quality, a universal add-on is presented which uses edge detection and smoothening techniques to brush out fine details from the restored image. To evaluate the efficacy, the proposed and existing filtering techniques are implemented in MATLAB and simulated with benchmark images. The simulation results show that the proposed filter is …

Efficient Hybrid Passive Method For The Detection And Localization Of Copy-Moveand Spliced Images, Navneet Kaur, Neeru Jindal, Kulbir Singh

Turkish Journal of Electrical Engineering and Computer Sciences

Digital passive image forgery methods are extensively used to verify the authenticity and integrity of images.Splicing and copy-move are the most common types of passive digital image forgeries. Several approaches have beenproposed to detect these forgeries separately, but very few approaches are available that can detect them simultaneously.However, a more e?icient method is still in demand to meet the day-to-day challenges to detect these forgeries at thesame time. So, a passive hybrid approach based on discrete fractional cosine transform (DFrCT) and local binarypattern (LBP) is proposed to detect copy-move and splicing forgeries simultaneously. The extra parameter i.e. fractionalparameter of DFrCT …

An Evolutionary-Based Image Classification Approach Through Facial Attributes, Seli̇m Yilmaz, Cemi̇l Zalluhoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

With the recent developments in technology, there has been a significant increase in the studies on analysisof human faces. Through automatic analysis of faces, it is possible to know the gender, emotional state, and even theidentity of people from an image. Of them, identity or face recognition has became the most important task whichhas been studied for a long time now as it is crucial to take measurements for public security, credit card verification,criminal identification, and the like. In this study, we have proposed an evolutionary-based framework that relies ongenetic programming algorithm to evolve a binary- and multilabel image classifier …

Learning Multiview Deep Features From Skeletal Sign Language Videos Forrecognition, Ashraf Ali Shaik, Venkata Durga Prasad Mareedu, Venkata Vijaya Kishore Polurie

Turkish Journal of Electrical Engineering and Computer Sciences

The most challenging objective in machine translation of sign language has been the machine?s inability tolearn interoccluding finger movements during an action process. This work addresses the problem of teaching a deeplearning model to recognize differently oriented skeletal data. The multi-view 2D skeletal sign language video data isobtained using 3D motion-captured system. A total of 9 signer views were used for training the proposed network andthe 6 for testing and validation. In order to obtain multi-view deep features for recognition, we proposed an end-to-endtrainable multistream convolutional neural network (CNN) with late feature fusion. The fused multiview features arethen inputted to …

Turkish Sign Language Recognition Based On Multistream Data Fusion, Cemi̇l Gündüz, Hüseyi̇n Polat

Turkish Journal of Electrical Engineering and Computer Sciences

Sign languages are nonverbal, visual languages that hearing- or speech-impaired people use for communication.Aside from hands, other communication channels such as body posture and facial expressions are also valuable insign languages. As a result of the fact that the gestures in sign languages vary across countries, the significance ofcommunication channels in each sign language also differs. In this study, representing the communication channels usedin Turkish sign language, a total of 8 different data streams-4 RGB, 3 pose, 1 optical flow-were analyzed. Inception3D was used for RGB and optical flow; and LSTM-RNN was used for pose data streams. Experiments were conductedby …

Coordination, Adaptation, And Complexity In Decision Fusion, Weiqiang Dong

Dissertations

A parallel decentralized binary decision fusion architecture employs a bank of local detectors (LDs) that access a commonly-observed phenomenon. The system makes a binary decision about the phenomenon, accepting one of two hypotheses (H0 (“absent”) or H1 (“present”)). The k 1 LD uses a local decision rule to compress its local observations yk into a binary local decision uk; uk = 0 if the k 1 LD accepts H0 and uk = 1 if it accepts H1. The k 1 LD sends its decision uk over a noiseless dedicated channel to a Data Fusion Center (DFC). The DFC combines the …

A Hydrologic Model Of The Northern Limb Of The San Luis Obispo Valley Aquifer By Use Of Comsol Multiphysics® Simulation Software, Claire Momberger

Master of Science in Environmental Sciences and Management Projects

The passage of the Sustainable Groundwater Management Act in 2014 by the State of California was the first of its kind in the State’s history to legislate the management of groundwater resources. This legislation is state-governed but locally and regionally implemented. The Sustainable Groundwater Management Act requires local water management agencies to create their own sustainable management plans for groundwater resources that meet state-defined sustainability goals 20 years after implementation. Such plans require hydrologic conceptual models that describe flow within the groundwater basin setting, predict use, and anticipate demand. The high-level detail of the hydrologic conceptual models requires the power …

Research And Application Of A Lightweight Real-Time Human Posture Detection Model, Hongkun Zhu, Jiawei Yin, Wenyu Feng, Hua Liang, Minrui Fei, Kun Zhang

Journal of System Simulation

Abstract: The traditional OpenPose model has good accuracy but slow speed in human posture detection. In order to accelerate the detection speed and reduce the model on condition of the detection precision, based on the traditional OpenPose model, the residual network with second-order term fusion is used to extract the low-level features, the weights of the trained model are pruned by the L1 norm weight, and an improved OpenPose model is proposed. Experiments show that when the detection accuracy is approximately equal to original model, the model size reduces to about 8%, the parameters reduces by nearly 83%, and the …

Fast 3d Medical Image Registration Based On Geometric Feature Invariants, Juping Gu, Tianyu Cheng, Jianping Wang, Hua Liang, Fengshen Zhao, Jiang Ling

Journal of System Simulation

Abstract: Aiming at the of large amount of computational data and low registration efficiency in 3D cranial medical image registration, a fast registration method based on geometric feature space constraints is proposed. The algorithm extracts three-dimensional contour point clusters, and proposes a feature construction method based on the optimal fitting ring of point clusters. The feature rings and the centroids of each layer are used as feature quantities, and the fast registration is completed by using Iterative Closest Point (ICP) method. The experimental results show that the method has less computation amount, high satisfactory registration accuracy and much faster registration …

Communicating Uncertain Information From Deep Learning Models In Human Machine Teams, Harishankar V. Subramanian, Casey I. Canfield, Daniel Burton Shank, Luke Andrews, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

The role of human-machine teams in society is increasing, as big data and computing power explode. One popular approach to AI is deep learning, which is useful for classification, feature identification, and predictive modeling. However, deep learning models often suffer from inadequate transparency and poor explainability. One aspect of human systems integration is the design of interfaces that support human decision-making. AI models have multiple types of uncertainty embedded, which may be difficult for users to understand. Humans that use these tools need to understand how much they should trust the AI. This study evaluates one simple approach for communicating …

Automated Discussion Analysis - Framework For Knowledge Analysis From Class Discussions, Swapna Gottipati, Venky Shankararaman, Mallikan Gokarn Nitin

Research Collection School Of Computing and Information Systems

This research full paper, describes knowledge management of class discussions using an analytics based framework. Discussions, either live classroom or through online forums, when used as a teaching method can help stimulate critical thinking. It allows the teacher to explore in-depth the key concepts covered in the course, motivates students to articulate their ideas clearly and challenge the students to think more deeply. Analysing the discussions helps instructors gain better insights on the personal and collaborative learning behaviour of students. However, knowledge from in-class discussions and online forums is not effectively captured and mined due to lack of appropriate automated …

Establishing Topological Data Analysis: A Comparison Of Visualization Techniques, Tanmay J. Kotha

USF Tampa Graduate Theses and Dissertations

When visualizing data, we would like to convey both the data and the uncertainty associated with it. There are many incentives to do this, ranging from hurricane path projection to geographical surveys. Important decision making tasks rely upon humans perceiving a clear picture of the data and having confidence in their decisions. Topological Data Analysis has the potential to visualize the data as features or hierarchies in ways that are familiar to human intuition, and thus could help us convey the variation associated with uncertainty.

In this thesis, we evaluate four visualization techniques: color maps, isocontours, Reeb graphs, and persistence …

Strategies For Preparing And Delivering An Effective Online Presentation, Kenneth L. Brown, Claire L. Mcleod

Geology and Environmental Geoscience Faculty Publications

No abstract provided.

Virtual Viewpoint Synthesis Based On Grid Mapping, Yao Li, Qiongying Wu, Xu Hui

Journal of System Simulation

Abstract: Due to imperfect depth maps, occlusion and the illumination difference between reference images, annoying artifacts, such as holes and ghost edges, appearing in the rendering image by DIBR, holes filling being time-consuming, triangle mesh based on the depth contour and maps mesh triangles with energy constrains were created. Image fusion algorithm merged different viewpoint images and got final virtual viewpoint image. While DIBR warped the image with pixels, triangles were mapped with. Compared with the traditional DIBR, the proposed algorithm has a faster processing speed than the traditional pixel based processing method in the same image quality.

Gpu-Accelerated Cloth Animation Based On Module Division, Kun Zhou, Liu Zhen, Gaoqi He, Chen Tian, Tingting Liu, Cuijuan Liu

Journal of System Simulation

Abstract: In order to improve the simulation speed of cloth animation, a module division parallel computing method was proposed by studying two kinds of cloth simulation models with dynamics and position based dynamics (PBD). A computing task was divided into a plurality of independent blocks by the way of data block. GPU parallel computing was used within the data block to improve the real-time performance and robustness of the cloth simulation. The applicability and effectiveness of the algorithm were verified under different scenarios and stochastic wind field. Experimental results show that under the same conditions, the proposed method can effectively …

Title Medical Image Fusion Based On Multi-Scale Coefficient Decomposition Framework, Kaifeng Wen, Bingjian Li

Journal of System Simulation

Abstract: The main purpose of medical image fusion is to obtain a high resolution image with as much details as possible for diagnosis. Magnetic resonance (MR) and computed tomography (CT) medical images has special sophisticated and complementary characteristics which are required for accurate diagnosis of disease. Based on this, a new medical fusion approach for MR and CT images based on multi-scale coefficient decomposition framework was proposed. The proposed approach used a combination of discrete wavelet and non-subsampled shearlet transforms for the initial multi-scale decompositions firstly. The decomposition multi-scale coefficients were fused twice using various local activity measures. The …

Controlling Framing Effects For Web-Based Group Decision Support Systems, Badria Sulaiman Alfurhood

Theses and Dissertations

The way the proposal and the available alternatives are presented or framed for a group decision may alter the ultimate group decision. Strategic framing is an attack method used to manipulate people into irrationally preferring a particular alternative. The adverse effects of framing threaten the trustworthiness and results of the group decision support systems (GDSSs). Nonetheless, the avoidance or reduction of framing effects is possible. Negative framing effects arise when users are not consistent with their choices if framing is applied for a collaborative decision using GDSSs. In this interdisciplinary research, human-computer interaction (HCI) informed methods, cognitive science, and political …

Simulation Of Dongba Art Style Painting, Wenhua Qian, Xu Dan, Xu Jin, He Lei, Zhang Bo

Journal of System Simulation

Abstract: An interactive technique that can generate the Dongba art paintings from 2D images is proposed. A Dongba painting line drawing system is designed and developed which adopts the interactive selection method to obtain the smooth and continuous line drawings. To produce the foreground image of the Dongba styles, a multi-frequency noise integral convolution algorithm is utilized to simulate the block texture color of the Dongba paintings. Texture synthesis algorithm is used to generate the image of large sizes from samples to simulate the background image. Based on the layer-mapping technique and local color transmission methods, the final artistic style …

Real-Time Simulation On Virtual Dressing Based On Virtual Human Body Model, Chuanyu Xue, Hongwei Dong, Mingmin Zhang, Zhigeng Pan

Journal of System Simulation

Abstract: In this paper we put forward a real-time method of virtual dressing using a single Kinect device. Virtual dressing using a low-cost device has very important application, but classic 3D human body dressing algorithms cannot work in real time. We need to generate 3D human body model before virtual dressing using Kinect. In this paper, we use a method which is based on body's basic information to build human body model, and the method is optimized to enhance the local simulation results.This paper presents a tracking ellipsoid modeland applies GPU parallel computing to decrease the amount of calculation …

Progressive Image Denoising Algorithm, Haiyang Li, Weiguo Cao, Shirui Li, Kelu Tao, Li Hua

Journal of System Simulation

Abstract: Currently almost all denoising algorithms are implemented by processing original noisy image itself simply, which could not enhance the performance further by combining original noisy image with the denoised image. To solve the problem, a framework of progressive image denoising method was proposed. The framework is based on the block matching and 3D collaborative filtering (BM3D) algorithm, which has the most remarkable denoising effect. It includes three layers and two fusions. Each layer is implemented by BM3D and denoises the fused image generated from the previous layers. Adequate statistical results show that under the same noise condition, our proposed …

Tools For Analyzing R Code The Tidy Way, Lucy D'Agostino Mcgowan, Sean Kross, Jeffrey Leek

The R Journal

With the current emphasis on reproducibility and replicability, there is an increasing need to examine how data analyses are conducted. In order to analyze the between researcher variability in data analysis choices as well as the aspects within the data analysis pipeline that contribute to the variability in results, we have created two R packages: matahari and tidycode. These packages build on methods created for natural language processing; rather than allowing for the processing of natural language, we focus on R code as the substrate of interest. The matahari package facilitates the logging of everything that is typed in the …

Image Subset Communication For Resource-Constrained Applications In Wirelesssensor Networks, Sajid Nazir, Omar Alzubi, Mohammad Kaleem, Hassan Hamdoun

Turkish Journal of Electrical Engineering and Computer Sciences

JPEG is the most widely used image compression standard for sensing, medical, and security applications. JPEG provides a high degree of compression but field devices relying on battery power must further economize on data transmissions to prolong deployment duration with particular use cases in wireless sensor networks. Transmitting a subset of image data could potentially enhance the battery life of power-constrained devices and also meet the application requirements to identify the objects within an image. Depending on an application's needs, after the first selected subset is received at the base station, further transmissions of the image data for successive refinements …