Digital Commons Network^™

Presenting A Product Design From Computer-Generated Imagery (Cgi), Mirjeta Mustafa

Theses and Dissertations

The purpose of this thesis is to determine a solution to overcome photography problems to present product design by using Computer Generated Imagery. CGI and virtual design now play a key role in the development of many materials, processes and products. Through this study has been explored, the impact of 3D render to exhibit the product design, as well as a brief history of photography and how it is used to present the product, the problems that have emerged during the use of photographs to present the product design have been discussed, and how new technologies have enabled us to …

Use Of Virtual Reality Technology In Medical Training And Patient Rehabilitation, Sankalp Mishra

Browse all Theses and Dissertations

Coaching patients to follow the rehabilitation routines correctly and timely after surgery is often a challenge due to the limited medical knowledge of patients and limited availability of clinicians. Similarly, it is also a challenge to train medical professionals with both the technical and communication skills required in their practices. The recent emergence of VR technologies shines the light on improving the current training practices. In this thesis research, I will look at the development and application of VR-based immersive training games for two particular cases: 1. Post hand surgery rehab; and, 2. Training for Social determinants of health (SDOH) …

Spatial-Aware Global Contrast Representation For Saliency Detection, Dan Xu, Shucheng Huang, Xin Zuo

Turkish Journal of Electrical Engineering and Computer Sciences

Deep learning networks have been demonstrated to be helpful when used in salient object detection and achieved superior performance than the methods that are based on low-level hand-crafted features. In this paper, we propose a novel spatial-aware contrast cube-based convolution neural network (CNN) which can further improve the detection performance. From this cube data structure, the contrast of the superpixel is extracted. Meanwhile, the spatial information is preserved during the transformation. The proposed method has two advantages compared to the existing deep learning-based saliency methods. First, instead of feeding the deep learning networks with raw image patches or pixels, we …

A Computational Study On Aging Effect For Facial Expression Recognition, Elena Sönmez

Turkish Journal of Electrical Engineering and Computer Sciences

This work uses newly introduced variations of the sparse representation-based classifier (SRC) to challenge the issue of automatic facial expression recognition (FER) with faces belonging to a wide span of ages. Since facial expression is one of the most powerful and immediate ways to disclose individuals? emotions and intentions, the study of emotional traits is an active research topic both in psychology and in engineering fields. To date, automatic FER systems work well with frontal and clean faces, but disturbance factors can dramatically decrease their performance. Aging is a critical disruption element, which is present in any real-world situation and …

U.S. Census Explorer: A Gui And Visualization Tool For The U.S. Census Data Api, Timothy Snyder

Williams Honors College, Honors Research Projects

U.S. Census Explorer is a software application that is designed to provide tools for intuitive exploration and analysis of United States census data for non-technical users. The application serves as an interface into the U.S. Census Bureau’s data API that enables a complete workflow from data acquisition to data visualization without the need for technical intervention from the user. The suite of tools provided include a graphical user interface for dynamically querying U.S. census data, geographic visualizations, and the ability to download your work to common spreadsheet and image formats for inclusion in external works.

Cloud Resource Optimization For Processing Multiple Streams Of Visual Data, Zohar Kapach, Andrew Ulmer, Daniel Merrick, Arshad Alikhan, Yung-Hsiang Lu, Anup Mohan, Ahmed S. Kaseb, George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

Hundreds of millions of network cameras have been installed throughout the world. Each is capable of providing a vast amount of real-time data. Analyzing the massive data generated by these cameras requires significant computational resources and the demands may vary over time. Cloud computing shows the most promise to provide the needed resources on demand. In this article, we investigate how to allocate cloud resources when analyzing real-time data streams from network cameras. A resource manager considers many factors that affect its decisions, including the types of analysis, the number of data streams, and the locations of the cameras. The …

We Have Always Been Virtual: Gilles Deleuze And The Computer-Generated Image, Hugh Mccabe

Conference papers

The use of computer-generated imagery is becoming increasingly ubiquitous across many fields including media, advertising, architecture and art. This represents a fundamental shift within visual culture, as imagery can now be produced routinely by means of rendering algorithms based on spatial representations. We propose that the account of the image provided by Gilles Deleuze in his books on cinema provides a rich philosophical framework for understanding such contemporary imaging practices. By providing a Deleuzian reading of James Kajiya's 1986 rendering equation we argue that there is a tacit ontology of the image underwriting both Deleuze’s work on cinema and current …

Spatial Uncertainty Propagation Analysis With The Spup R Package, Kasia Sawicka, Gerard B.M. Heuvelink, Dennis J.J. Walvoort

The R Journal

Many environmental and geographical models, such as those used in land degradation, agroecological and climate studies, make use of spatially distributed inputs that are known imperfectly. The R package spup provides functions for examining the uncertainty propagation from input data and model parameters onto model outputs via the environmental model. The functions include uncertainty model specification, stochastic simulation and propagation of uncertainty using Monte Carlo (MC) techniques. Uncertain variables are described by probability distributions. Both numerical and categorical data types are handled. The package also accommodates spatial auto-correlation within a variable and cross-correlation between variables. The MC realizations may be …

Toward Real-Time Flip Fluid Simulation Through Machine Learning Approximations, Javid Kennon Pack

Theses and Dissertations

Fluids in computer generated imagery can add an impressive amount of realism to a scene, but are particularly time-consuming to simulate. In an attempt to run fluid simulations in real-time, recent efforts have attempted to simulate fluids by using machine learning techniques to approximate the movement of fluids. We explore utilizing machine learning to simulate fluids while also integrating the Fluid-Implicit-Particle (FLIP) simulation method into machine learning fluid simulation approaches.

Predicting Visual Context For Unsupervised Event Segmentation In Continuous Photo-Streams, Ana García Del Molino, Joo-Hwee Lim, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Segmenting video content into events provides semantic structures for indexing, retrieval, and summarization. Since motion cues are not available in continuous photo-streams, and annotations in lifelogging are scarce and costly, the frames are usually clustered into events by comparing the visual features between them in an unsupervised way. However, such methodologies are ineffective to deal with heterogeneous events, e.g. taking a walk, and temporary changes in the sight direction, e.g. at a meeting. To address these limitations, we propose Contextual Event Segmentation (CES), a novel segmentation paradigm that uses an LSTM-based generative network to model the photo-stream sequences, predict their …

Teaching Adult Learners On Software Architecture Design Skills, Eng Lieh Ouh, Yunghans Irawan

Research Collection School Of Computing and Information Systems

Software architectures present high-level views ofsystems, enabling developers to abstract away the unnecessarydetails and focus on the overall big picture. Designing a softwarearchitecture is an essential skill in software engineering and adultlearners are seeking this skill to further progress in their career.With the technology revolution and advancements in this rapidlychanging world, the proportion of adult learners attendingcourses for continuing education are increasing. Their learningobjectives are no longer to obtain good grades but the practicalskills to enable them to perform better in their work and advancein their career. Teaching software architecture to upskill theseadult learners requires contending with the problem of …

Orecchio: Extending Body-Language Through Actuated Static And Dynamic Auricular Postures, Da-Yuan Huang, Teddy Seyed, Jun Gong, Zhihao Yao, Yuchen Jiao, Xiang Anthony Chen, Xing-Dong Yang

Dartmouth Scholarship

In this paper, we propose using the auricle – the visible part of the ear – as a means of expressive output to extend body language to convey emotional states. With an initial exploratory study, we provide an initial set of dynamic and static auricular postures. Using these results, we examined the relationship between emotions and auricular postures, noting that dynamic postures involving stretching the top helix in fast (e.g., 2Hz) and slow speeds (1Hz) conveyed intense and mild pleasantness while static postures involving bending the side or top helix towards the center of the ear were associated with intense …

Supporting Accurate Interpretation Of Self-Administered Medical Test Results For Mobile Health: Assessment Of Design, Demographics, And Health Condition, Jess C. Hohenstein, Eric P.S. Baumer, Lindsay Reynolds, Elizabeth L. Murnane, Dakota O'Dell, Seoho Lee, Shion Guha, Yu Qi, Erin Rieger, Geri K. Gay

Mathematics, Statistics and Computer Science Faculty Research and Publications

Background: Technological advances in personal informatics allow people to track their own health in a variety of ways, representing a dramatic change in individuals’ control of their own wellness. However, research regarding patient interpretation of traditional medical tests highlights the risks in making complex medical data available to a general audience.

Objective: This study aimed to explore how people interpret medical test results, examined in the context of a mobile blood testing system developed to enable self-care and health management.

Methods: In a preliminary investigation and main study, we presented 27 and 303 adults, respectively, with hypothetical results from several …

Component Tree Analysis Of Cystovirus Φ6 Nucleocapsid Cryo-Em Single Particle Reconstructions, Lucas Oliveira, Ze Ye, Al Katz, Alexandra Alimova, Hui Wei, Gabor T. Herman, Paul Gottlieb

Publications and Research

The 3-dimensional structure of the nucleocapsid (NC) of bacteriophage φ6 is described utilizing component tree analysis, a topological and geometric image descriptor. The component trees are derived from density maps of cryo-electron microscopy single particle reconstructions. Analysis determines position and occupancy of structure elements responsible for RNA packaging and transcription. Occupancy of the hexameric nucleotide triphosphorylase (P4) and RNA polymerase (P2) are found to be essentially complete in the NC. The P8 protein lattice likely fixes P4 and P2 in place during maturation. We propose that the viral procapsid (PC) is a dynamic structural intermediate where the P4 and P2 …

Smart Cities And Urban Management, Singapore Management University

Research Collection Office of Research

In this booklet, read about SMU’s research and initiatives related to smart cities and urban management, and how we strive to make meaningful impact on business, government and society for Singapore and beyond.

Contents:

Liveability and quality of life

• Community participation through mobile crowdsourcing
• Smarter, healthier eating with Food AI
• Data-driven community eldercare platform for sustainable ageing-in-place
• A date with AI
• Smart mobility accessibility for barrier-free access
• Food security

Optimisation and resource management

• Collaborative urban delivery optimisation
• Seat occupancy detection through capacitance sensing
• Large-scale crowd simulation based on real-world data
• Gaining insights through Wi-Fi technology
• Taxi driver guidance system
• Efficiency …

Visual Analytics Of Cascaded Bottlenecksin Planar Flow Networks, Tobias Post, Thomas Wischgoll, Bernd Hamann, Hans Hagen

Computer Science and Engineering Faculty Publications

Finding bottlenecks and eliminating them to in-crease the overall flow of a network often appears in real world applications, such as production planning, factory layout, flowrelated physical approaches, and even cyber security. In many cases, several edges can form a bottleneck (cascaded bottlenecks). This work presents a visual analytics methodology to analyze these cascaded bottlenecks. The methodology consists of multiple steps: identification of bottlenecks, identification of potential improvements, communication of bottlenecks, interactive adaption of bottlenecks, and a feedback loop that allows users to adapt flow networks and their resulting bottlenecks until they are satisfied with the flow network configuration. To …

An Uncertainty-Aware Visual System For Image Pre-Processing, Christina Gillmann, Pablo Arbelaez, Jose Tiberio Hernandez, Hans Hagen, Thomas Wischgoll

Computer Science and Engineering Faculty Publications

Due to image reconstruction process of all image capturing methods, image data is inherently affected by uncertainty. This is caused by the underlying image reconstruction model, that is not capable to map all physical properties in its entirety. In order to be aware of these effects, image uncertainty needs to be quantified and propagated along the entire image processing pipeline. In classical image processing methodologies, pre-processing algorithms do not consider this information. Therefore, this paper presents an uncertainty-aware image pre-processing paradigm, that is aware of the input image’s uncertainty and propagates it trough the entire pipeline. To accomplish this, we …

Towards An Image-Based Indicator For Pad Classification And Localization, Christina Gillmann, Johh H. Matsuura, Hans Hagen, Thomas Wischgoll

Computer Science and Engineering Faculty Publications

Peripheral Artery Disease (PAD) is an often occurring problem caused by narrowed veins. With this type of disease, mostly the legs receive an insufficient supply of blood to sustain their functions. This can result in an amputation of extremities or strokes. In order to quantify the risks, doctors onsult a classification table which is based on the pain response of a patient. This classification is subjective and does not indicate the exact origin of the PAD symptoms. Resulting from this, complications can occur unprompted. We present the first results for an image-based indicator assisting medical doctors in estimating the stage …

Novel Alert Visualization: The Development Of A Visual Analytics Prototype For Mitigation Of Malicious Insider Cyber Threats, Karla A. Clarke

CCAC Theses and Dissertations

Cyber insider threat is one of the most difficult risks to mitigate in organizations. However, innovative validated visualizations for cyber analysts to better decipher and react to detected anomalies has not been reported in literature or in industry. Attacks caused by malicious insiders can cause millions of dollars in losses to an organization. Though there have been advances in Intrusion Detection Systems (IDSs) over the last three decades, traditional IDSs do not specialize in anomaly identification caused by insiders. There is also a profuse amount of data being presented to cyber analysts when deciphering big data and reacting to data …

Volumetric 3d Reconstruction Of Real Objects Using Voxel Mapping Approach In A Multiple-Camera Environment, Tushar Jadhav, Kulbir Singh, Aditya Abhyankar

Turkish Journal of Electrical Engineering and Computer Sciences

Extracting 3D information from 2D images is an inverse estimation problem and a challenging task in itself. The aim of 2D to 3D reconstruction is to generate either a volume or a surface representing the object from multiple views. This paper presents a simple and accurate multiple-view volumetric 3D reconstruction method using an integrated approach based on homography estimation and voxel mapping. The homography-based approaches give accurate estimates but do not provide system dynamics. The voxel-based volumetric reconstruction methods provide system dynamics that are essential for system modeling. However, they face challenges while modeling the concavities. This paper presents a …

An Adaptive Machine Learning-Based Qoe Approach In Sdn Context For Video-Streaming Services, Asma Ben Letaifa

Turkish Journal of Electrical Engineering and Computer Sciences

In data service applications over the Internet, user perception and satisfaction can be assessed by quality of experience (QoE) metrics. QoE depends both on the users' perception and the used service, which together form end-to-end metrics. While network optimization has traditionally focused on optimizing network properties such as QoS, we focus in this work on optimizing end-to-end QoE metrics with the aim to deliver to the client a good QoE that can be monitored in real time. We argue that end-user QoE is a relevant measurement for network operators and service providers. In this paper, we present a machine learning …

Intersection Of Art And Science Ii, Petronio Bendito, Tim Korb

Lawson Building Exhibitions on the Intersection of Art and Science

The Intersection of Art and Science exhibition is an interdisciplinary educational project that examines a wide range of expressive approaches explored by international artists working at the intersection of art, mathematics, computer science, and technology. It is a joint collaboration between the Department of Computer Science and the Patti and Rusty Rueff School of Visual and Performing Arts at Purdue University. Featured artists: Manuel Baez, Sarah Berube, Robert Bosch, Sage Jenson, Jean-Marc Castera, Marc Chamberland, Marion Chamberland, Laura De Decker, Bathsheba Grossman, Colin Liotta, Vincent J. Matsko, Kerry Mitchell, Janna Schimka, Rolf Schmuck, and Markus Schwehm. The exhibition was curated …

Consuming Digital Debris In The Plasticene, Stephen R. Parks

Theses and Dissertations

Claims of customization and control by socio-technical industries are altering the role of consumer and producer. These narratives are often misleading attempts to engage consumers with new forms of technology. By addressing capitalist intent, material, and the reproduction limits of 3-D printed objects’, I observe the aspirational promise of becoming a producer of my own belongings through new networks of production. I am interested in gaining a better understanding of the data consumed that perpetuates hyper-consumptive tendencies for new technological apparatuses. My role as a designer focuses on the resolution of not only the surface of the object through 3-D …

Sensory Seduction And Narrative Pull, Nina Lyons, Matt Smith, Hugh Mccabe

Conference papers

User experience design is a process that has been defined, developed and refined over the last few decades. It is a process of shaping a user's movements through a website or mobile application. It is user-focussed, prioritising utility, ease-of-use and efficiency. It is widely used and has helped advance the way in which users interact with websites and mobile applications, making it far less frustrating. User experience design is a key element in how the internet and mobile technology have become ubiquitous in our daily lives. Given this success, it would seem that continuing to use this process for new …

Analisis Desain Website Bni, Bukopin, J.Co Donuts Dan Mcdonals Menurut Buku "The Principles Of Beautiful Web Design", Fitria Ekarini

Elinvo (Electronics, Informatics, and Vocational Education)

Paper ini bertujuan untuk mengetahui hasil analisis desain beberapa tampilan website berdasarkan teori "The Principle Beautiful Web Design" menggunakan tujuh variabel antara lain Defining good Design, Web Page Anatomy, Grid Theory, Balance, Unity, Bread and Butter Layout dan Fresh Trends. Penelitian ini membandingkan empat website yang terdiri 2 jenis website perbankan dan 2 jenis food company. yaitu website BNI, website Bank BUKOPIN, website Jco Donuts, dan website McDonals. Hasilnya didapatkan bahwa website food company lebih baik dalam desain tampilan websitenya dibandingan dengan website perbankan. Dalam website food company hampir seluruh variabel digunakan dalam mendesain tampilan websitenya.

A Data Hiding Scheme Based On Chaotic Map And Pixel Pairs, Sengul Dogan Sd

Journal of Digital Forensics, Security and Law

Information security is one of the most common areas of study today. In the literature, there are many algorithms developed in the information security. The Least Significant Bit (LSB) method is the most known of these algorithms. LSB method is easy to apply however it is not effective on providing data privacy and robustness. In spite of all its disadvantages, LSB is the most frequently used algorithm in literature due to providing high visual quality. In this study, an effective data hiding scheme alternative to LSB, 2LSBs, 3LSBs and 4LSBs algorithms (known as xLSBs), is proposed. In this method, random …

Marketing The Mountain State: A Large N Study Of User Engagement On Twitter, Kirk Richardson

Capstone Projects – Politics and Government

Much of the evolving research on the use of social media in destination marketing emphasizes how information diffusion influences the reputational image of place. The present study uses Twitter data to focus on the relative differences in user engagement across discrete account types. Specifically, this is done to examine how the official destination marketing organization of Montana—the Montana Office of Tourism (MTOT)—performs relative to other account types. Several regression analyses conducted on Twitter data associated with an ongoing MTOT place branding campaign reveal that tweets sent from ‘official’ accounts are more likely to be retweeted, and are estimated to receive …

Pre-Processing Techniques To Improve Hevc Subjective Quality, D. G. Fernández, A. A. Del Barrio, Guillermo Botella, Uwe Meyer-Baese, Anke Meyer-Baese, Christos Grecos

All Faculty Scholarship for the College of the Sciences

Nowadays, HEVC is the cutting edge encoding standard being the most efficient solution for transmission of video content. In this paper a subjective quality improvement based on pre-processing algorithms for homogeneous and chaotic regions detection is proposed and evaluated for low bit-rate applications at high resolutions. This goal is achieved by means of a texture classification applied to the input frames. Furthermore, these calculations help also reduce the complexity of the HEVC encoder. Therefore both the subjective quality and the HEVC performance are improved.

Whitelisting System State In Windows Forensic Memory Visualizations, Joshua A. Lapso, Gilbert L. Peterson, James S. Okolica

Faculty Publications

Examiners in the field of digital forensics regularly encounter enormous amounts of data and must identify the few artifacts of evidentiary value. One challenge these examiners face is manual reconstruction of complex datasets with both hierarchical and associative relationships. The complexity of this data requires significant knowledge, training, and experience to correctly and efficiently examine. Current methods provide text-based representations or low-level visualizations, but levee the task of maintaining global context of system state on the examiner. This research presents a visualization tool that improves analysis methods through simultaneous representation of the hierarchical and associative relationships and local detailed data …

Case Study On Wavelet Choice Based On Statistical Image Quality Measures, Igor Vujovic, Ivica Kuzmanic

Turkish Journal of Electrical Engineering and Computer Sciences

Surveillance applications are under many negative influences, which should be suppressed, because these negative influences result in incorrectness of the motion mask. Suppression of several conflicting requirements can be optimized by a multiobjective approach. This paper proposes a multiobjective approach to selection of wavelets based on two main objectives: statistical image quality measures and execution time. Execution time is a measure of wavelets complexity. Segmentation is the final goal in order to insure precise operation of any surveillance algorithm. This paper presents a case study considering one, two, three, and four goals for wavelet selection comparison. Different wavelets are found …