Physical Sciences and Mathematics | Open Access Articles

ผลของรูปทรง ตำแหน่ง และอัตราการแสดงความคืบหน้า ต่อการตอบแบบสอบถามออนไลน์, ศุภสุตา มุ่ยห้วยแก้ว

Chulalongkorn University Theses and Dissertations (Chula ETD)

แบบสอบถามออนไลน์ เป็นเครื่องมือในการเก็บรวบรวมข้อมูลที่ง่ายและรวดเร็วในปัจจุบัน โดยประสิทธิภาพข้อมูลที่ได้ ขึ้นอยู่กับปริมาณข้อมูลที่ได้รับจากการตอบแบบสอบถามของหน่วยทดลอง ด้วยคำตอบที่สมบูรณ์ ครบถ้วน และเป็นความจริง การแสดงตัวชี้บอกความคืบหน้าเป็นหนึ่งในเครื่องมือที่ช่วยให้การตอบกลับแบบสอบถามเสร็จสมบูรณ์ได้ ผู้วิจัยจึงสนใจวิเคราะห์ถึงลักษณะของตัวชี้บอกความคืบหน้า โดยมุ่งเน้นวิเคราะห์ผลกระทบของ (1) รูปทรง (2) ตำแหน่ง และ (3) อัตราการแสดง ของตัวชี้บอกความคืบหน้า ต่อ อัตราการตอบกลับสมบูรณ์ ระยะเวลาในการตอบแบบสอบถาม และความจริงใจในการตอบแบบสอบถามออนไลน์บนโทรศัพท์มือถือ การศึกษานี้เป็นการทดลองในสภาพจริง การวิเคราะห์ข้อมูลพบว่า ผลกระทบของ (1) รูปทรง (2) ตำแหน่ง และ (3) อัตราการแสดง ของตัวชี้บอกความคืบหน้า ต่ออัตราการตอบกลับสมบูรณ์ไม่มีนัยสำคัญ นอกจากนี้ผลกระทบของทุกตัวแปรต้นต่อระยะเวลาในการตอบแบบสอบถาม และต่อความจริงใจในการตอบแบบสอบถามออนไลน์ ไม่มีนัยสำคัญเช่นกัน ข้อสรุปจากการศึกษานี้เป็นการต่อยอดองค์ความรู้ทางการวิจัยในบริบทของแบบสอบถามออนไลน์บนโทรศัพท์มือถือ

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Neighbourhood Structure Preserving Cross-Modal Embedding For Video Hyperlinking, Yanbin Hao, Chong-Wah Ngo, Benoit Huet

Research Collection School Of Computing and Information Systems

Video hyperlinking is a task aiming to enhance the accessibility of large archives, by establishing links between fragments of videos. The links model the aboutness between fragments for efficient traversal of video content. This paper addresses the problem of link construction from the perspective of cross-modal embedding. To this end, a generalized multi-modal auto-encoder is proposed.& x00A0;The encoder learns two embeddings from visual and speech modalities, respectively, whereas each of the embeddings performs self-modal and cross-modal translation of modalities. Furthermore, to preserve the neighbourhood structure of fragments, which is important for video hyperlinking, the auto-encoder is devised to model data …

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On Basing One-Way Permutations On Np-Hard Problems Under Quantum Reductions, Nai-Hui Chia, Sean Hallgren, Fang Song

Computer Science Faculty Publications and Presentations

A fundamental pursuit in complexity theory concerns reducing worst-case problems to average-case problems. There exist complexity classes such as PSPACE that admit worst-case to average-case reductions. However, for many other classes such as NP, the evidence so far is typically negative, in the sense that the existence of such reductions would cause collapses of the polynomial hierarchy(PH). Basing cryptographic primitives, e.g., the average-case hardness of inverting one-way permutations, on NP-completeness is a particularly intriguing instance. As there is evidence showing that classical reductions from NP-hard problems to breaking these primitives result in PH collapses, it seems unlikely to base cryptographic …

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Selectivity And Robustness Of Sparse Coding Networks, Dylan M. Paiton, Charles Frye, Sheng Y. Lundquist, Joel D. Bowen, Ryan Zarcone, Bruno A. Olshausen

Computer Science Faculty Publications and Presentations

We investigate how the population nonlinearities resulting from lateral inhibition and thresholding in sparse coding networks influence neural response selectivity and robustness. We show that when compared to pointwise nonlinear models, such population nonlinearities improve the selectivity to a preferred stimulus and protect against adversarial perturbations of the input. These findings are predicted from the geometry of the single-neuron iso-response surface, which provides new insight into the relationship between selectivity and adversarial robustness. Inhibitory lateral connections curve the iso-response surface outward in the direction of selectivity. Since adversarial perturbations are orthogonal to the iso-response surface, adversarial attacks tend to be …

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Complex Systems Analysis In Selected Domains: Animal Biosecurity & Genetic Expression, Luke Trinity

Graduate College Dissertations and Theses

I first broadly define the study of complex systems, identifying language to describe and characterize mechanisms of such systems which is applicable across disciplines. An overview of methods is provided, including the description of a software development methodology which defines how a combination of computer science, statistics, and mathematics are applied to specified domains. This work describes strategies to facilitate timely completion of robust and adaptable projects which vary in complexity and scope. A biosecurity informatics pipeline is outlined, which is an abstraction useful in organizing the analysis of biological data from cells. This is followed by specific applications of …

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Co-Optimization Of A Robot's Body And Brain Via Evolution And Reinforcement Learning, Jack Felag

Graduate College Dissertations and Theses

Agents are often trained to perform a task via optimization algorithms. One class of algorithms used is evolution, which is ``survival of the fitness'' used to pick the best agents for the objective, and slowly changing the best over time to find a good solution. Evolution, or evolutionary algorithms, have been commonly used to automatically select for a better body of the agent, which can outperform hand-designed models. Another class of algorithms used is reinforcement learning. Through this strategy, agents learn from prior experiences in order to maximize some reward. Generally, this reward is how close the objective is to …

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Some Results On A Set Of Data Driven Stochastic Wildfire Models, Maxfield E. Green

Graduate College Dissertations and Theses

Across the globe, the frequency and size of wildfire events are increasing. Research focused on minimizing wildfire is critically needed to mitigate impending humanitarian and environmental crises. Real-time wildfire response is dependent on timely and accurate prediction of dynamic wildfire fronts. Current models used to inform decisions made by the U.S. Forest Service, such as Farsite, FlamMap and Behave do not incorporate modern remotely sensed wildfire records and are typically deterministic, making uncertainty calculations difficult. In this research, we tested two methods that combine artificial intelligence with remote sensing data. First, a stochastic cellular automata that learns algebraic expressions was …

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Extremal/Saturation Numbers For Guessing Numbers Of Undirected Graphs, Jo Ryder Martin

Graduate College Dissertations and Theses

Hat guessing games—logic puzzles where a group of players must try to guess the color of their own hat—have been a fun party game for decades but have become of academic interest to mathematicians and computer scientists in the past 20 years. In 2006, Søren Riis, a computer scientist, introduced a new variant of the hat guessing game as well as an associated graph invariant, the guessing number, that has applications to network coding and circuit complexity. In this thesis, to better understand the nature of the guessing number of undirected graphs we apply the concept of saturation to guessing …

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Process Based Analysis Of Fluvial Stratigraphic Record: Middle Pennsylvanian Allegheny Formation, North-Central Wv, Oluwasegun O. Abatan

Graduate Theses, Dissertations, and Problem Reports

Fluvial deposits represent some of the best hydrocarbon reservoirs, but the quality of fluvial reservoirs varies depending on the reservoir architecture, which is controlled by allogenic and autogenic processes. Allogenic controls, including paleoclimate, tectonics, and glacio-eustasy, have long been debated as dominant controls in the deposition of fluvial strata. However, recent research has questioned the validity of this cyclicity and may indicate major influence from autogenic controls. To further investigate allogenic controls on stratal order, I analyzed the facies architecture, geomorphology, paleohydrology, and the stratigraphic framework of the Middle Pennsylvanian Allegheny Formation (MPAF), a fluvial depositional system in the Appalachian …

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Representation Learning With Adversarial Latent Autoencoders, Stanislav Pidhorskyi M.S.

Graduate Theses, Dissertations, and Problem Reports

A large number of deep learning methods applied to computer vision problems require encoder-decoder maps. These methods include, but are not limited to, self-representation learning, generalization, few-shot learning, and novelty detection. Encoder-decoder maps are also useful for photo manipulation, photo editing, superresolution, etc. Encoder-decoder maps are typically learned using autoencoder networks.
Traditionally, autoencoder reciprocity is achieved in the image-space using pixel-wise
similarity loss, which has a widely known flaw of producing non-realistic reconstructions. This flaw is typical for the Variational Autoencoder (VAE) family and is not only limited to pixel-wise similarity losses, but is common to all methods relying upon …

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Crowdsourcing Image Extraction And Annotation: Software Development And Case Study, Ana Jofre, Vincent Berardi, Kathleen P.J. Brennan, Aisha Cornejo, Carl Bennett, John Harlan

Psychology Faculty Articles and Research

We describe the development of web-based software that facilitates large-scale, crowdsourced image extraction and annotation within image-heavy corpora that are of interest to the digital humanities. An application of this software is then detailed and evaluated through a case study where it was deployed within Amazon Mechanical Turk to extract and annotate faces from the archives of Time magazine. Annotation labels included categories such as age, gender, and race that were subsequently used to train machine learning models. The systemization of our crowdsourced data collection and worker quality verification procedures are detailed within this case study. We outline a data …

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A Framework Of Multi-Dimensional And Multi-Scale Modeling With Applications, Zilong Li

Doctoral Dissertations

In this dissertation, a framework for multi-dimensional and multi-scale modeling is proposed. The essential idea is based on oriented space curves, which can be represented as a 3D slender object or 1D step parameters. SMILES and Masks provide functionalities that extend slender objects into branched and other objects. We treat the conversion between 1D, 2D, 3D, and 4D representations as data unification. A mathematical analysis of different methods applied to helices (a special type of space curves) is also provided. Computational implementation utilizes Model-ViewController design principles to integrate data unification with graphical visualizations to create a dashboard. Applications of multi-dimensional …

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Fast Decision-Making Under Time And Resource Constraints, Kyle Gabriel Lassak

Graduate Theses, Dissertations, and Problem Reports

Practical decision makers are inherently limited by computational and memory resources as well as the time available in which to make decisions. To cope with these limitations, humans actively seek methods which limit their resource demands by exploiting structure within the environment and exploiting a coupling between their sensing and actuation to form heuristics for fast decision-making. To date, such behavior has not been replicated in artificial agents. This research explores how heuristics may be incorporated into the decision-making process to quickly make high-quality decisions through the analysis of a prominent case study: the outfielder problem. In the outfielder problem, …

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Physical Sciences and Mathematics Commons^™

Full-Text Articles in Physical Sciences and Mathematics

ผลของรูปทรง ตำแหน่ง และอัตราการแสดงความคืบหน้า ต่อการตอบแบบสอบถามออนไลน์, ศุภสุตา มุ่ยห้วยแก้ว

Chulalongkorn University Theses and Dissertations (Chula ETD)

Neighbourhood Structure Preserving Cross-Modal Embedding For Video Hyperlinking, Yanbin Hao, Chong-Wah Ngo, Benoit Huet

Research Collection School Of Computing and Information Systems

On Basing One-Way Permutations On Np-Hard Problems Under Quantum Reductions, Nai-Hui Chia, Sean Hallgren, Fang Song

Computer Science Faculty Publications and Presentations

Selectivity And Robustness Of Sparse Coding Networks, Dylan M. Paiton, Charles Frye, Sheng Y. Lundquist, Joel D. Bowen, Ryan Zarcone, Bruno A. Olshausen

Computer Science Faculty Publications and Presentations

Complex Systems Analysis In Selected Domains: Animal Biosecurity & Genetic Expression, Luke Trinity

Graduate College Dissertations and Theses

Co-Optimization Of A Robot's Body And Brain Via Evolution And Reinforcement Learning, Jack Felag

Graduate College Dissertations and Theses

Some Results On A Set Of Data Driven Stochastic Wildfire Models, Maxfield E. Green

Graduate College Dissertations and Theses

Extremal/Saturation Numbers For Guessing Numbers Of Undirected Graphs, Jo Ryder Martin

Graduate College Dissertations and Theses

Process Based Analysis Of Fluvial Stratigraphic Record: Middle Pennsylvanian Allegheny Formation, North-Central Wv, Oluwasegun O. Abatan

Graduate Theses, Dissertations, and Problem Reports

Representation Learning With Adversarial Latent Autoencoders, Stanislav Pidhorskyi M.S.

Graduate Theses, Dissertations, and Problem Reports

Crowdsourcing Image Extraction And Annotation: Software Development And Case Study, Ana Jofre, Vincent Berardi, Kathleen P.J. Brennan, Aisha Cornejo, Carl Bennett, John Harlan

Psychology Faculty Articles and Research

A Framework Of Multi-Dimensional And Multi-Scale Modeling With Applications, Zilong Li

Doctoral Dissertations

Fast Decision-Making Under Time And Resource Constraints, Kyle Gabriel Lassak

Graduate Theses, Dissertations, and Problem Reports