Physical Sciences and Mathematics Commons^™

Content And Community Based Hybrid Tag Recommendation, Umaporn Padungkiatwattana

Chulalongkorn University Theses and Dissertations (Chula ETD)

Personalized hashtag recommendations can provide relevant hashtags for a microblog. Despite performance improvement, three challenges remain unexplored. First, previous works construct user and hashtag representations based on relations from themselves. We argue that users and hashtags are influenced not only by their own relations (i.e., first-order relations) but also by the relations of a distant user/hashtag that is indirectly connected in multiple communities (i.e., high-order relations). Second, prior works perform personalization at the microblog level while ignoring the user aspects presented for each word in the microblog. Third, past studies capture correlations among hashtags in the same microblog by considering …

การนำกลับแมงกานีสจากแบตเตอรี่ปฐมภูมิที่ใช้งานแล้วโดยการตกตะกอนทางเคมีและเคมีไฟฟ้า, กัญญาณัฐ ก้อนเกตุ

Chulalongkorn University Theses and Dissertations (Chula ETD)

ปัจจุบันมีการใช้เครื่องมืออิเล็กทรอนิกส์อย่างแพร่หลายที่ใช้แบตเตอรี่แบบใช้งานได้ครั้งเดียวหรือไม่สามารถอัดประจุซ้ำได้ (Non-chargeable batteries) ซึ่งการกำจัดขยะแบตเตอรี่ในหลายพื้นที่ของประเทศนิยมทำด้วยวิธีการฝังกลบดิน (Landfill) ผสมกับขยะประเภทอื่น ๆ เนื่องจากเป็นวิธีที่ง่ายที่สุดแต่วิธีการนี้ก่อให้เกิดปัญหาทางด้านสิ่งแวดล้อมตามมา การนำแบตเตอรี่ที่ใช้งานแล้วกลับมาผ่านกระบวนการเพื่อนำวัสดุภายในกลับใช้ใหม่จึงเป็นทางออกที่เหมาะสมกว่า อีกทั้งเป็นการหมุนเวียนการใช้วัสดุให้เกิดประโยชน์สูงที่สุด ด้วยเหตุนี้งานวิจัยนี้จึงมุ่งเน้นไปที่การนำผงสารประกอบออกไซด์ของแมงกานีสจากขั้วบวกของทั้งแบตเตอรี่แอลคาไลน์และสังกะสี-คาร์บอนที่ใช้งานแล้ว ซึ่งอยู่ในรูปของผสมของสารประกอบหลายชนิดได้แก่ แมงกานีส (III) ออกไซด์ (Mn2O3) และ สังกะสี-แมงกานีส (III) ออกไซด์ (ZnMn2O4) มาผ่านกระบวนการสัณฐานโลหวิทยาความร้อนสูงและสารละลายเพื่อให้ได้เป็นสารประกอบใหม่คือ แมงกานีส (II) ออกไซด์ (MnO) แมงกานีส (II) ซัลเฟต (MnSO4) และแมงกานีสไดออกไซด์ (MnO2) ผลทดสอบโครงสร้างผลึกของสารด้วยเทคนิค X-ray diffraction (XRD) พบว่า MnO2 ที่ได้เป็นเฟสผสมของ แอลฟ่า เบต้า และแกรมม่า โดยมีร้อยละผลผลิตมากกว่า 95 เมื่อนำ MnO2 มาใช้เป็นผงขั้วบวกในแบตเตอรี่สังกะสี-ไอออน ได้ทำการทดสอบสมรรถนะทางเคมีไฟฟ้าด้วยเทคนิค Galvanostatic charge-discharge (GCD) ความหนาแน่นกระแสต่างกันได้แก่ 5 10 20 50 100 และ 200 มิลลิแอมแปร์ต่อกรัม พบว่าค่าความจุจำเพาะที่ได้ของ MnO2 ที่เตรียมได้จากผงแบตเตอรี่แอลคาไลน์ที่ใช้งานแล้วมีค่ามากกว่ากรณีที่เตรียมได้จากผงแบตเตอรี่สังกะสี-คาร์บอน โดยค่าความจุจำเพาะสูงสุดที่ได้มีค่าประมาณ 105.26 มิลลิแอมแปร์-ชั่วโมงต่อกรัม (รอบที่ 5) ที่ความหนาแน่นกระแส 5 มิลลิแอมแปร์ต่อกรัม

A Comparison Of Imbalanced Data Handling Methods For Pre-Trained Model In Multi-Label Classification Of Stack Overflow, Arisa Umparat

Chulalongkorn University Theses and Dissertations (Chula ETD)

Tag classification is essential in Stack Overflow. Instead of combining through pages or replies of irrelevant information, users can easily and quickly pinpoint relevant posts and answers using tags. Since User-submitted posts can have multiple tags, classifying tags in Stack Overflow can be challenging. This results in an imbalance problem between labels in the whole labelset. Pretrained deep learning models with small datasets can improve tag classification accuracy. Common multi-label resampling techniques with machine learning classifiers can also fix this issue. Still, few studies have explored which resampling technique can improve the performance of pre-trained deep models for predicting tags. …

Whole File Chunk Based Deduplication Using Reinforcement Learning, Xincheng Yuan

Master's Projects

Deduplication is the process of removing replicated data content from storage facilities like online databases, cloud datastore, local file systems, etc., which is commonly performed as part of data preprocessing to eliminate redundant data that requires unnecessary storage spaces and computing power. Deduplication is even more specifically essential for file backup systems since duplicated files will presumably consume more storage space, especially with a short backup period like daily [8]. A common technique in this field involves splitting files into chunks whose hashes can be compared using data structures or techniques like clustering. In this project we explore the possibility …

Poriferal Vision: Deep Transfer Learning-Based Sponge Spicules Identification & Taxonomic Classification, Sudhin Domala

Master's Projects

The phylum Porifera includes the aquatic organisms known as sponges. Sponges are classified into four classes: Calcarea, Hexactinellida, Demospongiae, and Homoscleromorpha. Within Demospongiae and Hexactinellida, sponges’ skeletons are needle-like spicules made of silica. With a wide variety of shapes and sizes, these siliceous spicules’ morphology plays a pivotal role in assessing and understanding sponges' taxonomic diversity and evolution. In marine ecosystems, when sponges die their bodies disintegrate over time, but their spicules remain in the sediments as fossilized records that bear ample taxonomic information to reconstruct the evolution of sponge communities and sponge phylogeny.

Traditional methods of identifying spicules from …

Contextualized Vector Embeddings For Malware Detection, Vinay Pandya

Master's Projects

Malware classification is a technique to classify different types of malware which form an integral part of system security. The aim of this project is to use context dependant word embeddings to classify malware. Tansformers is a novel architecture which utilizes self attention to handle long range dependencies. They are particularly effective in many complex natural language processing tasks such as Masked Lan- guage Modelling(MLM) and Next Sentence Prediction(NSP). Different transfomer architectures such as BERT, DistilBert, Albert, and Roberta are used to generate context dependant word embeddings. These embeddings would help in classifying different malware samples based on their similarity …

Virtual Machine For Spartangold, William Wang

Master's Projects

The field of blockchain and cryptocurrencies can be both difficult to grasp and improve upon, which makes aids that can assist in these tasks very useful. SpartanGold is a simplified blockchain-based cryptocurrency created at San Jose State University as a learning aid for blockchain and cryptocurrencies. In its current state, it closely resembles Bitcoin, and it is also easily expandable to implement other features.

This project extends SpartanGold with a virtual machine resembling the Ethereum Virtual Machine. Implementing this feature results in SpartanGold having Ethereum- related features, which would allow the cryptocurrency to both be a helpful learning aid for …

Cloud Provisioning And Management With Deep Reinforcement Learning, Alexandru Tol

Master's Projects

The first web applications appeared in the early nineteen nineties. These applica- tions were entirely hosted in house by companies that developed them. In the mid 2000s the concept of a digital cloud was introduced by the then CEO of google Eric Schmidt. Now in the current day most companies will at least partially host their applications on proprietary servers hosted at data-centers or commercial clouds like Amazon Web Services (AWS) or Heroku.

This arrangement seems like a straight forward win-win for both parties, the customer gets rid of the hassle of maintaining a live server for their applications and …

Towards An Active Foveated Approach To Computer Vision, Dario Dematties, Silvio Rizzi, George K. Thiruvathukal, Alejandro Javier Wainselboim

Computer Science: Faculty Publications and Other Works

In this paper, a series of experimental methods are presented explaining a new approach towards active foveated Computer Vision (CV). This is a collaborative effort between researchers at CONICET Mendoza Technological Scientific Center from Argentina, Argonne National Laboratory (ANL), and Loyola University Chicago from the US. The aim is to advance new CV approaches more in line with those found in biological agents in order to bring novel solutions to the main problems faced by current CV applications. Basically this work enhance Self-supervised (SS) learning, incorporating foveated vision plus saccadic behavior in order to improve training and computational efficiency without …

Benchmarking Newsql Database Voltdb, Kevin Schumacher

Master's Projects

NewSQL is a type of relational database that is able to horizontally scale while retaining linearizable consistency. This is an improvement over a traditional SQL relational database because SQL databases cannot effectively scale across multiple machines. This is also an improvement over NoSQL databases because NewSQL databases are designed from the ground up to be consistent and have ACID guarantees. However, it should be noted that NewSQL databases are not a one size fits all type of database, each specific database is designed to perform well on specific workloads. This project will evaluate a NewSQL database, VoltDB, with a focus …

Annual Summary Of Weather Data For Parsons - 2021, M. Knapp, C. A. Redmond

Kansas Agricultural Experiment Station Research Reports

This report includes the annual summary of precipitation and temperatures from 2021 at the research locations represented in the 2021 Southeast Research and Extension Center Agricultural Research Report.

Magnetization Dynamics In A Modified Square Artificial Spin Ice, Amrit Kaphle

Theses and Dissertations--Physics and Astronomy

Artificial spin ices are magnetic metamaterials consisting of nanomagnet arrays in a 2-D lattice. Typically, these nanomagnet arrays are binary macrospins that can only be in an up or down state similar to the Ising spins. They have been intensively used to study magnetic frustration and ordering phenomena in a controlled environment. The hexagonal artificial spin ice and square artificial spin ice are among the most heavily studied systems. In this dissertation, we designed a modified square artificial spin ice system by an ordered substitution of a double-segment for a nanomagnet array in the unit cell of square artificial spin …

Extraction Of Deep Inelastic Cross Sections Using A 10.4 Gev Electron Beam And A Polarized Helium-3 Target, Murchhana Roy

Theses and Dissertations--Physics and Astronomy

Experiment E12-06-121 at Jefferson Lab aims to do a precision measurement of the neutron spin structure function g₂ using inclusive inelastic scattering of electrons over a large kinematic range of x and Q². The third moment of the linear combination of the spin structure functions g₁ and g₂, d₂, is one of the cleanest higher twist observables and contains information on quark-gluon correlations. It is connected to the "color polarizability" or "color Lorentz force" of the nucleon. The experimental data taking was successfully conducted in Hall C using a longitudinally polarized electron …

Cryogenic Magnetic Field Monitoring System In The Sns Neutron Edm Experiment, Umit Hasan Coskun

Theses and Dissertations--Physics and Astronomy

A permanent neutron electric dipole moment (nEDM), d_n, would violate charge-conjugation and parity (CP) symmetry. The neutron electric dipole moment currently has a global limit of d_n < 1.8 x 10^-26 e cm (90% CL). This limit is intended to be improved by two orders of magnitude by the nEDM experiment at the Spallation Neutron Source (SNS nEDM), d_n ~ 10^-28 e cm. The magnetic field non-uniformities within the experimental region must be precisely monitored and managed in order to suppress systematic effects in the experiment caused by magnetic field gradients. The estimation of magnetic field components within …

Stellar Parameter Determination For The Mastar Stellar Library, Daniel J. Lazarz

Theses and Dissertations--Physics and Astronomy

Empirical libraries of stellar spectra represent a key ingredient needed for modeling the integrated spectra of stellar populations, such as galaxies, through a process called stellar population synthesis (SPS). In order to make use of such libraries, accurate stellar atmospheric parameter estimates are required. Here, I present a methodology that was developed to build a stellar parameter catalog to accompany the MaNGA stellar library (MaStar), a comprehensive collection of empirical, medium-resolution stellar spectra. This parameter catalog was constructed using a multicomponent χ² fitting approach to match the MaStar spectra to models generated by interpolating the ATLAS9-based BOSZ models. The …

An Analysis On Network Flow-Based Iot Botnet Detection Using Weka, Cian Porteous

Dissertations

Botnets pose a significant and growing risk to modern networks. Detection of botnets remains an important area of open research in order to prevent the proliferation of botnets and to mitigate the damage that can be caused by botnets that have already been established. Botnet detection can be broadly categorised into two main categories: signature-based detection and anomaly-based detection. This paper sets out to measure the accuracy, false-positive rate, and false-negative rate of four algorithms that are available in Weka for anomaly-based detection of a dataset of HTTP and IRC botnet data. The algorithms that were selected to detect botnets …

New Strategies For Groundwater Litigation In Texas, Amy Hardberger

William & Mary Environmental Law and Policy Review

This Article evaluates the evolution of the understanding of groundwater rights since the Day decision and assesses the relative power of property rights in groundwater that have emerged and what can be done to equalize resulting inequities. Part I reviews the current state of groundwater ownership rights and includes a brief history of litigation that led to that point. Part II explains the authority and obligations of groundwater conservation districts, which create a regulatory overlay on the common law vested rights through permitting rules and the statewide planning process. Part III summarizes the history of constitutional challenges litigated after the …

Drones In The Coastal Zone, Center For Coastal Resources Management, Virginia Institute Of Marine Science

Reports

Rivers & Coast is a periodic publication of the Center for Coastal Resources Management, Virginia Institute of Marine Science. The goal of Rivers & Coast is to keep readers well informed of current scientific understanding behind key environmental issues related to watershed rivers and coastal ecosystems of the Chesapeake Bay.

Overview On Gplates: Focus On Plate Reconstruction, Shatavisa Chatterjee, Soumyajit Mukherjee

Turkish Journal of Earth Sciences

Plate tectonic reconstructions have been employed in geosciences since 1970s, in the context of hydrocarbon exploration, regional geology and paleobiology. Such studies have given valuable inputs for climate and geodynamic computations, present-day mantle structure, models of plate motion, and the interpretation of the drift of hotspots, true polar wander (TPW), sea level and stratigraphic signals. However, geodynamic models generated in the past by incorporating global plate tectonic reconstructions have limitations. To overcome this, GPlates software brings forward a new era of interactive plate tectonic reconstruction software integrated with GIS databases that incorporates a wide variety of geological and geophysical data. …

Naturally Occurring And Introduced Tracers For Examining Water Pathways In Urban Environments, Elizabeth Avery

Theses and Dissertations--Earth and Environmental Sciences

Naturally occurring stable isotopes of water and introduced water tracers allow researchers to examine water pathways and better understand spatial and temporal variability in water sources. Trends in naturally occurring stable isotope values can function not only as a tracer for precipitation patterns and moisture recycling but also as a confirmation of municipal data. Additionally, these data can provide an early signal for the effects of climate change on these sources, reducing uncertainty from physical measurements. To further assess water pathways, introduced tracers can be used to investigate surface and below ground surface flow for streams and rivers.

In chapter …

Assessing Machine Learning Utility In Predicting Hydrologic And Nitrate Dynamics In Karst Agroecosystems, Timothy Mcgill

Theses and Dissertations--Biosystems and Agricultural Engineering

Seasonal hypoxia in the Gulf of Mexico and harmful algal blooms experienced in many inland freshwater bodies is partially driven due to excessive nitrogen loading seen from agricultural watersheds. Within the Mississippi/Atchafalaya River Basin, many areas are underlain with karst features, and efforts to reduce nitrogen contributions from these areas have had varying success, due to lacking a complete understanding of nutrient dynamics in karst agricultural systems. To improve the understanding of nitrogen cycling in these systems, 35 months of high resolution in situ water quality and atmospheric data were collected and fed into a two-hidden layer extreme learning machine …

Unique Lifting To A Functor, Mark Myers

West Chester University Master’s Theses

We develop a functorial approach to quotient constructions, defining morphisms quotient relative to a functor and the dual concept of unique liftings relative to a functor. Various classes of epimorphism are given detailed analysis and their relationship to quotient morphisms characterized. The behavior of unique lifting morphisms with respect to products, equalizers, and general limits in a category are studied. Applications to generalized covering space theory, coreflective subcategories of topological spaces, topological groups and rings, and Galois theory are explored. Finally, we give conditions for the product of two quotient morphisms to be quotient in a braided monoidal closed category.

Measuring And Comparing Social Bias In Static And Contextual Word Embeddings, Alan Cueva Mora

Dissertations

Word embeddings have been considered one of the biggest breakthroughs of deep learning for natural language processing. They are learned numerical vector representations of words where similar words have similar representations. Contextual word embeddings are the promising second-generation of word embeddings assigning a representation to a word based on its context. This can result in different representations for the same word depending on the context (e.g. river bank and commercial bank). There is evidence of social bias (human-like implicit biases based on gender, race, and other social constructs) in word embeddings. While detecting bias in static (classical or non-contextual) word …

Approximating Bayesian Optimal Sequential Designs Using Gaussian Process Models Indexed On Belief States, Joseph Burris

Theses and Dissertations

Fully sequential optimal Bayesian experimentation can offer greater utility than both traditional Bayesian designs and greedy sequential methods, but practically cannot be solved due to numerical complexity and continuous outcome spaces. Approximate solutions can be found via approximate dynamic programming, but rely on surrogate models of the expected utility at each trial of the experiment with hand-chosen features or use methods which ignore the underlying geometry of the space of probability distributions. We propose the use of Gaussian process models indexed on the belief states visited in experimentation to provide utility-agnostic surrogate models for approximating Bayesian optimal sequential designs which …

Oakland

United States Data - California

Relevant Publications

2022 Data Summary

Airborne Fungal Spore Review, New Advances And Automatisation, Moisés Martínez-Bracero, Emma Markey, Jerry Hourihane Clancy, Eoin Mcgillicuddy, Gavin Sewell, David J. O'Connor

Articles

Fungal spores make up a significant portion of Primary Biological Aerosol Particles (PBAPs) with large quantities of such particles noted in the air. Fungal particles are of interest because of their potential to affect the health of both plants and humans. They are omnipresent in the atmosphere year-round, with concentrations varying due to meteorological parameters and location. Equally, differences between indoor and outdoor fungal spore concentrations and dispersal play an important role in occupational health. This review attempts to summarise the different spore sampling methods, identify the most important spore types in terms of negative effects on crops and the …

Using Feature Selection With Machine Learning For Generation Of Insurance Insights, Ayman Taha, Bernard Cosgrave, Susan Mckeever

Articles

Insurance is a data-rich sector, hosting large volumes of customer data that is analysed to evaluate risk. Machine learning techniques are increasingly used in the effective management of insurance risk. Insurance datasets by their nature, however, are often of poor quality with noisy subsets of data (or features). Choosing the right features of data is a significant pre-processing step in the creation of machine learning models. The inclusion of irrelevant and redundant features has been demonstrated to affect the performance of learning models. In this article, we propose a framework for improving predictive machine learning techniques in the insurance sector …

Ga Pilot Perceptions Of Speech Systems To Transcribe And Submit Pireps, Deborah S. Carstens Ph.D., Pmp, Michael S. Harwin, J.D., M.S., Tianhua Li, Ph.D., Brandon J. Pitts, Ph.D., Mel Futrell, M.A., Barrett Caldwell, Ph.D.

International Journal of Aviation, Aeronautics, and Aerospace

Flying into hazardous weather can be a cause of aviation incidents and accidents. Accidents involving general aviation (GA) pilots who are not instrument rated who fly into instrument meteorological conditions (IMC) are often fatal. Pilot weather reports (PIREPs) can increase the accuracy and timeliness of current and forecasted weather conditions. They are an essential tool used by pilots to avoid flying into hazardous weather as well as meteorologists to develop and update aviation forecasts. Thus, a large number of accurate PIREPs with the best source of current weather coming from pilots and air traffic controllers are needed. Pilots are often …

Automated Chest X-Ray Analysis: Biomedical/Non-Biomedical Foreign Object Detection, Shotabdi Roy

Dissertations and Theses

The presence of non-biomedical foreign objects (NBFO) such as coins, buttons, jewelry, etc. and biomedical foreign objects (BFO) such as medical tubes, and devices in Chest X-Rays (CXRs) make accurate interpretation difficult as they do not indicate known biological abnormalities like excess fluids, Tuberculosis (TB) or cysts. Accurate diagnosis and screening, require these NBFO and BFO to be detected, categorized as either NBFO or BFO, and removed from CXR or highlighted in CXR for effective abnormality analysis. During an automated CXR screening process, NBFOs can adversely impact the process as typical machine learning algorithms would consider these objects to be …

Finite Index Right-Angled Mock Artin Groups In Right-Angled Mock Reflection Groups, Zachary Marcum

Murray State Theses and Dissertations

Associated to any graph Γ are several groups where their presentations are encoded by Γ. Two such groups are right-angled Coxeter groups and right-angled Artin groups. By introducing more structure to Γ, what we call "local involutions," the graph Γ becomes a right-angled mock reflection system and encodes the presentation of two more groups: right-angled mock reflection groups and right-angled mock Artin groups.

Here we show that every right-angled mock Artin group associated with an n-gon graph with local involutions is a finite index subgroup in some right-angled mock reflection group. We employ a strategy similar to the one Davis …