Physical Sciences and Mathematics Commons^™

Thin-Layer Chromatography For Determination Of Phenolic Compound Profile And Antioxidant Activity Of Thai Honey, Pattraporn Chobpradit

Chulalongkorn University Theses and Dissertations (Chula ETD)

In this study, a small-scale method using thin-layer chromatography (TLC) was developed to determine profile and antioxidant activity value of Thai honey samples obtained from different flora sources. Prior to TLC analysis, the samples were prepared by solvent extraction with dichloromethane. Using 2, 2-diphenyl-1-picrylhydrazy radical (DPPH•) reacted with the samples extract prior to TLC spot and color detection with imageJ, half-maximal inhibitory concentration (IC50) values of seven honey samples was obtained in a range of 9 to 22 mg/mL in comparison with IC50 values of 0.13 mg/mL for L-ascorbic acid (LA), along with limit of detection (LOD) and limit of …

Flow-Through Reactor For Photomediated Synthesis Of Silver Nanoprisms, Thanasit Laisanguanngam

Chulalongkorn University Theses and Dissertations (Chula ETD)

Silver nanoprisms (AgNPrs) have been widely used due to their outstanding optical properties which is one of an important phenomenon that depends on their size, shape, and compositions with characteristic localized surface plasmon resonance (LSPR). The changes in LSPR of AgNPrs can be simply observed by the color changes of the AgNPrs colloidal solution, therefore, the AgNPrs have been mostly used as chemical sensors as they provide high sensitivity and capable to be functionalized to improve the detection selectivity. In this study, we report a photochemical technique to induce the shape conversion of the spherical silver nanoparticle to AgNPrs by …

Demand Forecasting In Production Planning For Dairy Products Using Machine Learning And Statistical Methods, Chayuth Vithisoontorn

Chulalongkorn University Theses and Dissertations (Chula ETD)

Demand forecasting is an essential task in manufacturing of every industry. Efficient forecasting relieves the excessive stock and out-of-stock problem, reducing revenue loss. This research performs a direct multistep forecast approach of demand forecasting on 8 dairy products of 5 different dairy production plants with 5-year data. Widely used traditional statistical method and the state of the art deep learning method for sequence problems are picked. ARIMA and LSTM. The models are compared in many aspects, monthly observations against weekly observations, univariate against multivariate, and statistical against deep learning using model error and business metrics. The result shows that both …

Conformance Checking And Discovery Of Information Service Request Process, Liam Khaosanoi

Chulalongkorn University Theses and Dissertations (Chula ETD)

Process mining is a form of business process analysis. The approach could support organizations in retrieving structured process information by using recorded process data to discover, monitor and improve the processes. In this work, the process mining technology is applied for conformance checking and discovering an organization’s Information Service Request process in reality as a case study. Currently, the reference model was drawn as a simple flow using Microsoft Word. The proposed method starts with writing a VBA script to extract traces from the drawing that enables the generation of XES file used for modeling the reference process in Petri …

Object Detection In Intelligent Billing System For Conveyor Belt Sushi Restaurant, Rangrak Maitriboriruks

Chulalongkorn University Theses and Dissertations (Chula ETD)

Organization must automate wherever and whenever they can, particularly during today’s global changes in daily lifestyles. Trends regarding the use of technology, especially AI has emerged as a key enabler for disruptive innovation. This thesis thus presents the application programming interface of object detector implemented with YOLOv4 and OpenCV for classifying the prices of sushi plates distinguished by colors. The object detector is part of the smart cross-platform mobile application to facilitate billing process for conveyor belt sushi business. The frontend is developed with Flutter to build single codebase for UIs. To handle the variants of image colors resulting from …

Travel Time Prediction With Graph Neural Network: A Case Study In Bangkok Thailand, Sathita Buapang

Chulalongkorn University Theses and Dissertations (Chula ETD)

Traffic prediction is an essential and challenging task for traffic management and commercial purposes. Machine learning methods for traffic prediction usually treat traffic conditions as time-series due to obvious temporal patterns. Recently, spatial relationships among roads in a road network have also been used to improve traffic prediction. This study proposes a novel method to predict traffic conditions such as speed using a graph convolutional neural network with a spectral adjacency matrix (GCN-Spectral). Unlike a spatial adjacency matrix representing physical connections between road segments, a spectral matrix represents the correlation between road segments regarding traffic conditions. The GCN-Spectral model is …

Classification Of Abusive Thai Messages In Social Networks Using Deep Learning, Ruangsung Wanasukapunt

Chulalongkorn University Theses and Dissertations (Chula ETD)

Social media has improved on traditional news sources by allowing increased access to information. However, the anonymity social media provides can lead to abusive and hateful speech without detection or repercussion from individuals with malicious intentions. This research develops a binomial and a multinomial classification model for classifying Thai social media text for five categories of abusive content detection in social media that include Rude, Figurative, Dirty, Offensive and Non-Abusive. The experiments demonstrated that DistilBERT achieved the highest F1 score with 0.8510 for the binomial model and 0.9067 for the multinomial model. BiLSTM performed second best with an F1 score …

Thai Variable-Length Question Classification For E-Commerce Platform Using Machine Learning With Topic Modeling Feature, Wasu Chunhasomboon

Chulalongkorn University Theses and Dissertations (Chula ETD)

Nowadays, e-commerce platform continuously grows every year and becomes a part of our daily life. However, the application changes from time to time. Either new users or experienced users could face a problem. Several channels, which are FAQ, email, live chat, and call, are provided by e-commerce platform to cope with the problem. FAQ is usually ignored because it is hard to search for the desired answer. The rest channels are applicable. However, the huge number of users causes a bottleneck especially in the special events which delays the users to receive help because customer service agent can reply to …

Consultation Summary For Proposed Declared Pest Rates 2021/2022, Department Of Primary Industries And Regional Development, Western Australia

Biosecurity published reports

In accordance with the Biosecurity and Agriculture Management (Declared Pest Account) Regulations 2014, the Minister for Agriculture and Food carries out consultation on Declared Pest Rates, to be considered prior to the rates being determined and gazetted.

This document is the Department of Primary Industries and Regional Development's response to the submissions received.

Reflection And Transmission Of Electromagnetic Pulses At A Planar Dielectric Interface: Theory And Quantum Lattice Simulations, Abhay K. Ram, George Vahala, Linda Vahala, Min Soe

Electrical & Computer Engineering Faculty Publications

There is considerable interest in the application of quantum information science to advance computations in plasma physics. A particular point of curiosity is whether it is possible to take advantage of quantum computers to speed up numerical simulations relative to conventional computers. Many of the topics in fusion plasma physics are classical in nature. In order to implement them on quantum computers, it will require couching a classical problem in the language of quantum mechanics. Electromagnetic waves are routinely used in fusion experiments to heat a plasma or to generate currents in the plasma. The propagation of electromagnetic waves is …

Simulation Studies On The Interactions Of Electron Beam With Wastewater, X. Li, S. Wang, Helmut Baumgart, G. Ciovati, F. Hannon

Electrical & Computer Engineering Faculty Publications

The manufactured chemical pollutants, like 1,4 dioxane and PFAS (per- and polyfluroralkyl substances), found in the underground water and/or drinking water are challenging to be removed or biodegraded. Energetic electrons are capable of mediating and removing them. This paper utilizes FLUKA code to evaluate the beam-wastewater interaction effects with different energy, space and divergence distributions of the electron beam. With 8 MeV average energy, the electron beam exits from a 0.0127 cm thick titanium window, travels through a 4.3 cm distance air and a second 0.0127 cm thick stainless water container window with 2.43 cm radius, and finally is injected …

Cylindrical Magnetron Development For Nb₃Sn Deposition Via Magnetron Sputtering, Md. Nizam Sayeed, Hani Elsayed-Ali, C. Côté, M. A. Farzad, A. Sarkissian, G. V. Eremeev, A-M. Valente-Feliciano

Electrical & Computer Engineering Faculty Publications

Due to its better superconducting properties (critical temperature Tc~ 18.3 K, superheating field H_sh~ 400 mT), Nb₃Sn is considered as a potential alternative to niobium (Tc~ 9.25 K, H_sh~ 200 mT) for superconducting radiofrequency (SRF) cavities for particle acceleration. Magnetron sputtering is an effective method to produce superconducting Nb₃Sn films. We deposited superconducting Nb₃Sn films on samples with magnetron sputtering using co-sputtering, sequential sputtering, and sputtering from a stoichiometric target. Nb₃Sn films produced by magnetron sputtering in our previous experiments have achieved DC superconducting critical temperature up to …

Matters Of Biocybersecurity With Consideration To Propaganda Outlets And Biological Agents, Xavier-Lewis Palmer, Ernestine Powell, Lucas Potter, Thaddeus Eze (Ed.), Lee Speakman (Ed.), Cyril Onwubiko (Ed.)

Electrical & Computer Engineering Faculty Publications

The modern era holds vast modalities in human data utilization. Within Biocybersecurity (BCS), categories of biological information, especially medical information transmitted online, can be viewed as pathways to destabilize organizations. Therefore, analysis of how the public, along with medical providers, process such data, and the methods by which false information, particularly propaganda, can be used to upset the flow of verified information to populations of medical professionals, is important for maintenance of public health. Herein, we discuss some interplay of BCS within the scope of propaganda and considerations for navigating the field.

Improving Stock Trading Decisions Based On Pattern Recognition Using Machine Learning Technology, Yaohu Lin, Shancun Liu, Haijun Yang, Harris Wu, Bingbing Jiang

Information Technology & Decision Sciences Faculty Publications

PRML, a novel candlestick pattern recognition model using machine learning methods, is proposed to improve stock trading decisions. Four popular machine learning methods and 11 different features types are applied to all possible combinations of daily patterns to start the pattern recognition schedule. Different time windows from one to ten days are used to detect the prediction effect at different periods. An investment strategy is constructed according to the identified candlestick patterns and suitable time window. We deploy PRML for the forecast of all Chinese market stocks from Jan 1, 2000 until Oct 30, 2020. Among them, the data from …

Stock Trend Prediction Using Candlestick Charting And Ensemble Machine Learning Techniques With A Novelty Feature Engineering Scheme, Yaohu Lin, Shancun Liu, Haijun Yang, Harris Wu

Information Technology & Decision Sciences Faculty Publications

Stock market forecasting is a knotty challenging task due to the highly noisy, nonparametric, complex and chaotic nature of the stock price time series. With a simple eight-trigram feature engineering scheme of the inter-day candlestick patterns, we construct a novel ensemble machine learning framework for daily stock pattern prediction, combining traditional candlestick charting with the latest artificial intelligence methods. Several machine learning techniques, including deep learning methods, are applied to stock data to predict the direction of the closing price. This framework can give a suitable machine learning prediction method for each pattern based on the trained results. The investment …

Generic Design Methodology For Smart Manufacturing Systems From A Practical Perspective, Part I—Digital Triad Concept And Its Application As A System Reference Model, Zhuming Bi, Wen-Jun Zhang, Chong Wu, Chaomin Luo, Lida Xu

Information Technology & Decision Sciences Faculty Publications

Rapidly developed information technologies (IT) have continuously empowered manufacturing systems and accelerated the evolution of manufacturing system paradigms, and smart manufacturing (SM) has become one of the most promising paradigms. The study of SM has attracted a great deal of attention for researchers in academia and practitioners in industry. However, an obvious fact is that people with different backgrounds have different expectations for SM, and this has led to high diversity, ambiguity, and inconsistency in terms of definitions, reference models, performance matrices, and system design methodologies. It has been found that the state of the art SM research is limited …

Image Source Identification Using Convolutional Neural Networks In Iot Environment, Yan Wang, Qindong Sun, Dongzhu Rong, Shancang Li, Li Da Xu

Information Technology & Decision Sciences Faculty Publications

Digital image forensics is a key branch of digital forensics that based on forensic analysis of image authenticity and image content. The advances in new techniques, such as smart devices, Internet of Things (IoT), artificial images, and social networks, make forensic image analysis play an increasing role in a wide range of criminal case investigation. This work focuses on image source identification by analysing both the fingerprints of digital devices and images in IoT environment. A new convolutional neural network (CNN) method is proposed to identify the source devices that token an image in social IoT environment. The experimental results …

Exploring Cybersecurity Education At The K-12 Level, Weiru Chen, Yuming He, Xin Tian, Wu He, E. Langran (Ed.), D. Rutledge (Ed.)

Information Technology & Decision Sciences Faculty Publications

K-12 cybersecurity education is receiving growing attention with the growing number of cyberattacks and a shortage of cybersecurity professionals. However, there are many barriers for teachers to implement effective cybersecurity education in formal classroom environments. This study conducts a systematic literature review to examine the current state-of-the-art on K-12 cybersecurity education. Through the systematic literature review, we identified 20 closely relevant papers and recognized that a well-designed curriculum in cybersecurity education at the K-12 level is strongly needed to motivate students to pursue cybersecurity pathways and careers. The challenge and suggestions of curriculum design, teaching strategy, and learning assessment are …

A Literature Review Of Quantum Education In K-12 Level, Yuming He, Shenghua Zha, Wu He, Theo Bastiaens (Ed.)

Information Technology & Decision Sciences Faculty Publications

Quantum computing is an emerging technology paradigm of computing and has the potential to solve computational problems intractable using today’s classical computers or digital technology. Quantum computing is expected to be disruptive for many industries. The power of quantum computing technologies is based on the fundamentals of quantum mechanics, such as quantum superposition, quantum entanglement, or the no-cloning theorem. To build a highly trained and skilled quantum workforce that meets future industry needs, there is a need to introduce quantum concepts early on in K-12 schools since the learning of quantum is a lengthy process. As fundamental quantum concepts derive …

Potentiometric Biosensing Of Ascorbic Acid, Uric Acid, And Cysteine In Microliter Volumes Using Miniaturized Nanoporous Gold Electrodes, Christopher J. Freeman, Borkat Ullah, Md. Shafiul Islam, Maryanne M. Collinson

Chemistry & Biochemistry Faculty Publications

Potentiometric redox sensing is a relatively inexpensive and passive approach to evaluate the overall redox state of complex biological and environmental solutions. The ability to make such measurements in ultra-small volumes using high surface area, nanoporous electrodes is of particular importance as such electrodes can improve the rates of electron transfer and reduce the effects of biofouling on the electrochemical signal. This work focuses on the fabrication of miniaturized nanoporous gold (NPG) electrodes with a high surface area and a small footprint for the potentiometric redox sensing of three biologically relevant redox molecules (ascorbic acid, uric acid, and cysteine) in …

Recently Developed Carbohydrate Based Gelators And Their Applications, Joedian Morris, Jonathan Bietsch, Kristen Bashaw, Guijun Wang

Chemistry & Biochemistry Faculty Publications

Carbohydrate based low molecular weight gelators have been an intense subject of study over the past decade. The self-assembling systems built from natural products have high significance as biocompatible materials and renewable resources. The versatile structures available from naturally existing monosaccharides have enriched the molecular libraries that can be used for the construction of gelators. The bottom-up strategy in designing low molecular weight gelators (LMWGs) for a variety of applications has been adopted by many researchers. Rational design, along with some serendipitous discoveries, has resulted in multiple classes of molecular gelators. This review covers the literature from 2017-2020 on monosaccharide …

Synthesis Of Carbohydrate Based Macrolactones And Their Applications As Receptors For Ion Recognition And Catalysis, Surya B. Adhikari, Anji Chen, Guijun Wang

Chemistry & Biochemistry Faculty Publications

Glycomacrolactones exhibit many interesting biological properties, and they are also important in molecular recognitions and for supramolecular chemistry. Therefore, it is important to be able to access glycomacrocycles with different sizes and functionality. A new series of carbohydrate-based macrocycles containing triazole and lactone moieties have been designed and synthesized. The synthesis features an intramolecular nucleophilic substitution reaction for the macrocyclization step. In this article, the effect of some common sulfonate leaving groups is evaluated for macrolactonization. Using tosylate gave good selectivity for monolactonization products with good yields. Fourteen different macrocycles have been synthesized and characterized, of which eleven macrocycles are …

Line-Of-Sight Winds And Doppler Effect Smearing In Ace-Fts Solar Occultation Measurements, Chris D. Boone, Johnathen Steffen, Jeff Crouse, Peter F. Bernath

Chemistry & Biochemistry Faculty Publications

Line-of-sight wind profiles are derived from Doppler shifts in infrared solar occultation measurements from the Atmospheric Chemistry Experiment Fourier transform spectrometers (ACE-FTS), the primary instrument on SCISAT, a satellite-based mission for monitoring the Earth’s atmosphere. Comparisons suggest a possible eastward bias from 20 m/s to 30 m/s in ACE-FTS results above 80 km relative to some datasets but no persistent bias relative to other datasets. For instruments operating in a limb geometry, looking through a wide range of altitudes, smearing of the Doppler effect along the line of sight can impact the measured signal, particularly for saturated absorption lines. Implications …

Photodynamic Therapy Of Inorganic Complexes For The Treatment Of Cancer, Chloe B. Smith, Lindsay C. Days, Duaa R. Alajroush, Khadija Faye, Yara Khodour, Stephen J. Beebe, Alvin Holder

Chemistry & Biochemistry Faculty Publications

Photodynamic therapy (PDT) is a medicinal tool that uses a photosensitiser and a light source to treat several conditions, including cancer. PDT uses reactive oxygen species (ROS) such as cytotoxic singlet oxygen ¹O₂ to induce cell death in cancer cells. Chemotherapy has historically utilized the cytotoxic effects of many metals, especially transition-metal complexes. However, chemotherapy is a systemic treatment so all cells in a patient's body are exposed to the same cytotoxic effects. Transition metal complexes have also shown high cytotoxicity as PDT agents. PDT is a potential localized method for treating several cancer types by using inorganic …

Structual Analysis Of The Cl-Par-4 Tumor Suppressor As A Function Of Ionic Environment, Krishna K. Raut, Komala Ponniah, Steven M. Pascal

Chemistry & Biochemistry Faculty Publications

Prostate apoptosis response-4 (Par-4) is a proapoptotic tumor suppressor protein that has been linked to a large number of cancers. This 38 kilodalton (kDa) protein has been shown to be predominantly intrinsically disordered in vitro. In vivo, Par-4 is cleaved by caspase-3 at Asp-131 to generate the 25 kDa functionally active cleaved Par-4 protein (cl-Par-4) that inhibits NF-κB-mediated cell survival pathways and causes selective apoptosis in tumor cells. Here, we have employed circular dichroism (CD) spectroscopy and dynamic light scattering (DLS) to assess the effects of various monovalent and divalent salts upon the conformation of cl-Par-4 in vitro. We have …

The Role Of Oxygen In Stimulating Methane Production In Wetlands, Jared L. Wilmoth, Jeffra K. Schaefer, Danielle R. Schlesinger, Spencer W. Roth, Patrick G. Hatcher, Julie K. Shoemaker, Xinning Zhang

Chemistry & Biochemistry Faculty Publications

Methane (CH₄), a potent greenhouse gas, is the second most important greenhouse gas contributor to climate change after carbon dioxide (CO₂). The biological emissions of CH₄ from wetlands are a major uncertainty in CH₄ budgets. Microbial methanogenesis by Archaea is an anaerobic process accounting for most biological CH₄ production in nature, yet recent observations indicate that large emissions can originate from oxygenated or frequently oxygenated wetland soil layers. To determine how oxygen (O₂) can stimulate CH₄ emissions, we used incubations of Sphagnum peat to demonstrate that the temporary exposure of …

A Dual Nanostructured Approach To Sers Substrates Amenable To Large-Scale Production, Kory Brian Castro, Cicely Rathmell, John Cooper

Chemistry & Biochemistry Faculty Publications

Surface enhanced Raman spectroscopy (SERS), although popular in research, has not yet been adopted in industrial applications. This is largely due to the challenge of manufacturing cost-effective, reproducible SERS substrates in volume that can be read by a compact reader for practical deployment in the field. Here we demonstrate and characterize a new dual-nanostructured SERS substrate approach that could be amenable to large-scale production. This dual-nanostructured surface combines long-range ordering of silver nanowires (AgNWs) with dense non-ordered decoration via silver nanoparticles (AgNPs) to improve on the SERS response characteristics of the individual structures, using fabrication methods that could be scaled …

Labilization And Diversification Of Pyrogenic Dissolved Organic Matter By Microbes, Aleksandar I. Goranov, Andrew S. Wozniak, Kyle W. Bostick, Andrew R. Zimmerman, Siddhartha Mitra, Patrick G. Hatcher

Chemistry & Biochemistry Faculty Publications

With the increased occurrence of forest fires around the world, interest in the chemistry of pyrogenic organic matter (pyOM) and its fate in the environment has increased. Upon leaching from soils by rain events, significant amounts of dissolved pyOM (pyDOM) enter the aquatic environment and interact with microbial communities that are essential for cycling organic matter within the different biogeochemical cycles. To evaluate the bio-reactivity of pyDOM, aqueous extracts of laboratory-produced chars were incubated with soil microbes and the molecular changes to the composition of pyDOM were probed using ultrahigh resolution mass spectrometry (Fourier transform – ion cyclotron resonance – …

Coherence And Identity Learning For Arbitrary-Length Face Video Generation, Shuquan Ye, Chu Han, Jiaying Lin, Guoqiang Han, Shengfeng He

Research Collection School Of Computing and Information Systems

Face synthesis is an interesting yet challenging task in computer vision. It is even much harder to generate a portrait video than a single image. In this paper, we propose a novel video generation framework for synthesizing arbitrary-length face videos without any face exemplar or landmark. To overcome the synthesis ambiguity of face video, we propose a divide-and-conquer strategy to separately address the video face synthesis problem from two aspects, face identity synthesis and rearrangement. To this end, we design a cascaded network which contains three components, Identity-aware GAN (IA-GAN), Face Coherence Network, and Interpolation Network. IA-GAN is proposed to …

Software Engineering In Australasia, Sherlock A. Licorish, Christoph Treude, John Grundy, Kelly Blincoe, Stephen Macdonell, Chakkrit Tantithamthavorn, Li Li, Jean-Guy Schneider

Research Collection School Of Computing and Information Systems

Six months ago an important call was made for researchers globally to provide insights into the way Software Engineering is done in their region. Heeding this call, we hereby outline the position Software Engineering in Australasia (New Zealand and Australia). This article first considers the software development methods, practices and tools that are popular in the Australasian software engineering community. We then briefly review the particular strengths of software engineering researchers in Australasia. Finally, we make an open call for collaborators by reflecting on our current position and identifying future opportunities.