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2022

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Articles 3511 - 3540 of 3613

Full-Text Articles in Computer Sciences

Indoor And Outdoor Localization In An Unknown Environment With Window Detection For Unmanned Aerial Vehicles, Laphonchai Jirachuphun Jan 2022

Indoor And Outdoor Localization In An Unknown Environment With Window Detection For Unmanned Aerial Vehicles, Laphonchai Jirachuphun

Chulalongkorn University Theses and Dissertations (Chula ETD)

In this thesis, we design and build a system for unmanned aerial vehicles (UAVs). We combine, adjust and improve existing open-source algorithms for localization tasks in an indoor and outdoor environment with window detection for transitioning between the two environments. For outdoor localization, we mainly use GPS, while for indoor localization, we use Extended Kalman Filter (EKF). However, for the transitioning area where the GPS is unreliable and the environment has too few structures for EKf, we use an opening such as a window or a door for localization with a stereo camera. We compare our technique with GPS only, …

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Content And Community Based Hybrid Tag Recommendation, Umaporn Padungkiatwattana Jan 2022

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 …

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ปัจจัยที่ส่งผลต่อความตั้งใจใช้แอปพลิเคชันโทรเวชกรรม, มนัสวี ศรีราช Jan 2022

ปัจจัยที่ส่งผลต่อความตั้งใจใช้แอปพลิเคชันโทรเวชกรรม, มนัสวี ศรีราช

Chulalongkorn University Theses and Dissertations (Chula ETD)

งานวิจัยนี้เป็นการวิจัยเชิงสำรวจเพื่อวิเคราะห์ปัจจัยที่ส่งผลต่อความตั้งใจใช้แอปพลิเคชันโทรเวชกรรม ซึ่งเป็นแอปพลิเคชันที่เป็นสื่อกลางในการสื่อสารเนื้อหาทางการแพทย์จากแพทย์สู่ผู้เข้ารับบริการทางการแพทย์ ที่สามารถลดข้อจำกัดด้านเวลา ด้านสถานที่ รวมถึงเพิ่มความปลอดภัยจากโรคระบาด โดยศึกษาว่าปัจจัยใดบ้างที่ส่งผลต่อความตั้งใจใช้แอปพลิเคชันโทรเวชกรรมของคนไทย ซึ่งเกิดในปี พ.ศ. 2508 ถึง 2552 หรือครอบคลุมเจเนอเรชันเอ็กซ์ วาย และแซดที่ไม่มีประสบการณ์เข้ารับบริการจากแพทย์ผ่านแอปพลิเคชันโทรเวชกรรมมาก่อน โดยใช้หน่วยตัวอย่างจำนวน 500 คน เครื่องมือที่ใช้ในการเก็บข้อมูลคือแบบสอบถามออนไลน์ สถิติที่ใช้ในการวิเคราะห์ข้อมูล คือสถิติเชิงพรรณนา ได้แก่ ค่าเฉลี่ย ร้อยละ ส่วนเบี่ยงเบนมาตรฐาน และการวิเคราะห์สัมประสิทธิ์สหสัมพันธ์เชิงอันดับของสเปียร์แมน ผลการวิจัย พบว่า ปัจจัยที่ส่งผลเชิงบวกต่อความตั้งใจใช้แอปพลิเคชันโทรเวชกรรมมากที่สุดในภาพรวม ได้แก่ ปัจจัยอิทธิพลทางสังคม สำหรับผู้ตอบแบบสอบถามเจเนอเรชันเอ็กซ์ ได้แก่ ปัจจัยอิทธิพลทางสังคม สำหรับผู้ตอบแบบสอบถามเจเนอเรชันวาย ได้แก่ ปัจจัยลักษณะนิสัย และสำหรับเจเนอเรชันแซด ได้แก่ ปัจจัยความคาดหวังในชื่อเสียง ผู้วิจัยมีความคาดหวังว่าผลการวิเคราะห์จากงานวิจัยชิ้นนี้จะเป็นประโยชน์ต่อสถาบันหรือผู้พัฒนาที่เกี่ยวข้อง โดยนำผลลัพธ์การวิจัยไปใช้เพื่อพัฒนาแอปพลิเคชันโทรเวชกรรมให้มีการบริการที่สอดคล้องกับความต้องการของผู้ใช้ได้ในอนาคต

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Nft-Based Authentic Product Verification And Trading Platform, Natchapol Thongruang Jan 2022

Nft-Based Authentic Product Verification And Trading Platform, Natchapol Thongruang

Chulalongkorn University Theses and Dissertations (Chula ETD)

Counterfeit product has been a major problem to the economy for a while. The effect seems to be larger when it comes to the luxury product segment. When the consumers were unsure if the product that they are buying is genuine or not and its cost is very high, then the severity will become even greater. Among the countless number of attempts to fix this solution, utilizing blockchain technology is one of the most popular approaches for present days. In anti-counterfeit domain, associating an NFT token to a physical product is the most common approach. It allows us to unlock …

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Investigate The Possibility Of Using Smart Contracts And Digital Signatures To Create A Legally Binding Contract, And To Create A Prototype Opensource Web Application As A Proof Of Concept, Yosnai Chanatrutipan Jan 2022

Investigate The Possibility Of Using Smart Contracts And Digital Signatures To Create A Legally Binding Contract, And To Create A Prototype Opensource Web Application As A Proof Of Concept, Yosnai Chanatrutipan

Chulalongkorn University Theses and Dissertations (Chula ETD)

We investigated the possibility of using blockchain to create a legally binding contract. According to our study, blockchain can be used to authenticate the identities of the involved parties, to provide a cryptographically generated electronic signature used to sign a contract, and to automate and enforce the term of an agreement. The authentication and the signing are done using a blockchain-based self-sovereign identity framework called a decentralized identity and verifiable credentials. The term can be enforced by using a smart contract, a program that runs on the blockchain. Some contracts terms are too complex to be translated into a smart …

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Estimating Stock Price Based On Information From Financial Statement Using Machine Learning Approach, Thitikun Kunathananon Jan 2022

Estimating Stock Price Based On Information From Financial Statement Using Machine Learning Approach, Thitikun Kunathananon

Chulalongkorn University Theses and Dissertations (Chula ETD)

This study introduces a new tool for stock market investors and institutions constructed from Long Short-Term Memory (LSTM) for predicting stock prices. By effectively analyzing financial statements and stock market data, LSTM provides a fast, unbiased, low-cost solution for stock price prediction, intending to increase profits for investors and reduce losses. The study results indicate that LSTM can maintain effectively captures complex relationships in the data and predicts stock prices. This research highlights the potential of LSTM as a valuable and innovative tool for investors and institutions in the stock market.

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Combining Technical Analysis And Deep Learning Models For Stock Market Trading, Phurinut Pholsri Jan 2022

Combining Technical Analysis And Deep Learning Models For Stock Market Trading, Phurinut Pholsri

Chulalongkorn University Theses and Dissertations (Chula ETD)

The issuance of stocks constitutes a means by which ownership in a company is represented, and its distribution may vary depending on whether the company is limited or public. The stock market offers the potential for high returns, thereby serving as an attractive avenue for investment. Against this backdrop, the objective of this study is to develop a predictive model for stock prices that can facilitate profitable trading outcomes. To achieve this aim, the study focuses on intraday and hourly trading and utilizes a hybrid model that integrates Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Network (CNN) architectures, along …

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Real-Time Object Detection For Screening Cannabis Seed Gender, Prachya Boonsri Jan 2022

Real-Time Object Detection For Screening Cannabis Seed Gender, Prachya Boonsri

Chulalongkorn University Theses and Dissertations (Chula ETD)

Perception and understanding of cannabis are more expansive than they formerly were. Almost all growers are primarily interested in getting harvests of big flower buds from cannabis female plants since THC, CBD and other cannabinoids are found in female flowers and valuable for medical and industrial market segments. Selecting only female seeds to cultivate is thus an important step to produce THC, CBD profitably. Unfortunately, outdoor cultivation in Thailand traditionally grows regular cannabis seeds that grow up of mixed male and female plants. The male plants will be later spot and eliminated during the pre-flowering stage. This incurs the higher …

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A Comparative Study On Out Of Scope Detection For Chest X-Ray Images, Nuttapol Kamolkunasiri Jan 2022

A Comparative Study On Out Of Scope Detection For Chest X-Ray Images, Nuttapol Kamolkunasiri

Chulalongkorn University Theses and Dissertations (Chula ETD)

Image classification models in actual applications may receive input outside the intended data distribution. For crucial applications such as clinical decision-making, it is critical that a model can recognize and describe such out-of-distribution (OOD) inputs. The objective of this study is to investigate the efficacy of several approaches for OOD identification in medical images. We examine three classes of OOD detection methods (Classification models, Confidence-based models, and Generative models) on the data of X-ray images. We found that simple classification methods and HealthyGAN perform the best overall. However, HealthyGAN cannot generalize to unseen scenarios, while classification models still retain some …

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Xgboost For Prediction Of Ethereum Short-Term Returns Based On Technical Factor, Wipawee Nayam Jan 2022

Xgboost For Prediction Of Ethereum Short-Term Returns Based On Technical Factor, Wipawee Nayam

Chulalongkorn University Theses and Dissertations (Chula ETD)

Unlike traditional currencies that rely on centralized such as banks or governments, cryptocurrencies today have become popular due to its decentralized transactions. Decentralization takes advantage of no requirement for intermediaries, thus reducing transaction fees and processing time. However, investing in cryptocurrencies incurs risks and uncertainties due to price volatility and rapid changes. The fact that prediction of asset prices is complex due to the influence of multiple factors on price movements. This paper studied the technical factor to analyze the short-term returns of Ethereum in the periods of 1-10 days. The historical data containing Ethereum closing price are collected from …

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Class-Level And Token-Level Approaches For Test Impact Analysis, Alon Basin Jan 2022

Class-Level And Token-Level Approaches For Test Impact Analysis, Alon Basin

Chulalongkorn University Theses and Dissertations (Chula ETD)

The objective of the thesis is to examine the efficacy of test impact analysis in a setting of continuous testing, where automated test cases are routinely run to guarantee the integration of high-quality codes. While continuous testing can enhance code quality and minimize maintenance workload, it also leads to a notable rise in overhead for test execution. In our study on test impact analysis, we developed a novel static class level technique that utilizes JavaParser to create a dependency graph between test cases and source code classes based on abstract syntax trees. We applied this technique to seven Java systems …

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Y-X-Y Encoding For Identifying Types Of Sentence Similarity, Thanaporn Jinnovart Jan 2022

Y-X-Y Encoding For Identifying Types Of Sentence Similarity, Thanaporn Jinnovart

Chulalongkorn University Theses and Dissertations (Chula ETD)

The task of finding semantic similarity of any two arbitrary sentences consists of two main steps, which are encoding sentences to produce feature vectors of equal length and measuring the similarity, respectively. The quality of an encoding technique can determine the degree of success a model can achieve in measuring the similarity. This is because a good representation is subjected to how finely established the spectrum of similarities is. The clearer the definition of similarity is, the better the representations can be constructed. This, in turn, helps distinguish between types of sentences. Generally, all existing methods for measuring similarity were …

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การสร้างคำถามไวยากรณ์ภาษาอังกฤษแบบปรนัยโดยใช้ทรานส์ฟอร์เมอร์ถ่ายทอดชนิดข้อความถึงข้อความ, พีรวัชน์ ชมภูยอด Jan 2022

การสร้างคำถามไวยากรณ์ภาษาอังกฤษแบบปรนัยโดยใช้ทรานส์ฟอร์เมอร์ถ่ายทอดชนิดข้อความถึงข้อความ, พีรวัชน์ ชมภูยอด

Chulalongkorn University Theses and Dissertations (Chula ETD)

คำถามปรนัยสำหรับทดสอบไวยากรณ์ภาษาอังกฤษสามารถสร้างแบบอัตโนมัติเพื่อลดระยะเวลาในการสร้างคำถาม ในอดีตงานวิจัยด้านนี้มุ่งเน้นไปที่การสร้างคำถามแบบกึ่งอัตโนมัติ โดยนำข้อความที่สร้างโดยมนุษย์มาแปลงให้เป็นคำถามปรนัย ส่งผลให้จำนวนคำถามที่สร้างได้ขึ้นอยู่กับจำนวนข้อความในคลังข้อมูลเท่านั้น วิทยานิพนธ์ฉบับนี้นำเสนอระบบสร้างคำถามปรนัยแบบอัตโนมัติที่นำเทคโนโลยีปัญญาประดิษฐ์มาประยุกต์ใช้ โดยนำปัญญาประดิษฐ์มาฝึกสอนให้สามารถสร้างข้อความอัตโนมัติแบบควบคุมคุณสมบัติของข้อความได้ แบบจำลองการเรียนรู้ของเครื่องที่นำมาฝึกในงานวิจัยนี้คือแบบจำลองทรานส์ฟอร์มเมอร์ชนิดข้อความถึงข้อความหรือทีไฟว์ ซึ่งเป็นแบบจำลองที่มีประสิทธิภาพในการสร้างข้อความอัตโนมัติ คุณลักษณะที่ใช้ฝึกแบบจำลองได้แก่ คำสำคัญ และแม่แบบ เพื่อควบคุมเนื้อหาและชนิดคำของข้อความที่สร้างขึ้น นอกจากการสร้างข้อความอัตโนมัติ วิทยานิพนธ์ฉบับนี้ได้เสนอกลวิธีแบบกฎเพื่อแปลงข้อความให้เป็นคำถามปรนัยสำหรับ 10 หัวข้อไวยากรณ์ ผลการทดลองของงานวิจัยนี้ชี้ให้เห็นว่าเมื่อนำคำถามที่สร้างขี้น มาประเมินผลด้วยผู้เชี่ยวชาญด้านภาษาอังกฤษแล้ว มีการยอมรับได้อยู่ที่ร้อยละ 86 ถึงแม้ว่าคำถามที่ถูกสร้างขึ้นทั้งหมดไม่สามารถนำไปทดสอบนักเรียนได้โดยตรง แต่ระบบสร้างคำถามอัตโนมัตินี้สามารถช่วยสนับสนุนคุณครูให้จัดเตรียมข้อสอบได้รวดเร็วขึ้น

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Hashtag Recommendation Based On Neural Topic Model, Thunchanok Tangpong Jan 2022

Hashtag Recommendation Based On Neural Topic Model, Thunchanok Tangpong

Chulalongkorn University Theses and Dissertations (Chula ETD)

Hashtag recommendation is a method that aims to recommend the relevant hashtag to the target microblog. The previous work applies a topic model for discovering the topic of users, words, and hashtags. Despite their progress, two problems remain unresolved. Firstly, the previous work infers topic distribution by using a non-neural network framework which is a non-linear function, limiting the model's ability to capture topic distribution complexly. Secondly, the representation of words and hashtags used in the prior model is merely the frequency of words, making the model to ignore not only word context but also the relation between word and …

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High Performance Data Acquisition And Analysis Routines For The Nab Experiment, David Mathews Jan 2022

High Performance Data Acquisition And Analysis Routines For The Nab Experiment, David Mathews

Theses and Dissertations--Physics and Astronomy

Probes of the Standard Model of particle physics are pushing further and further into the so-called “precision frontier”. In order to reach the precision goals of these experiments, a combination of elegant experimental design and robust data acquisition and analysis is required. Two experiments that embody this philosophy are the Nab and Calcium-45 experiments. These experiments are probing the understanding of the weak interaction by examining the beta decay of the free neutron and Calcium-45 respectively. They both aim to measure correlation parameters in the neutron beta decay alphabet, a and b. The parameter a, the electron-neutrino correlation coefficient, is …

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Partnering For Value Perfection And Business Sustainability In The Cloud Services Brokerage Market, Richard Shang, Robert John Kauffman Jan 2022

Partnering For Value Perfection And Business Sustainability In The Cloud Services Brokerage Market, Richard Shang, Robert John Kauffman

Research Collection School Of Computing and Information Systems

The cloud computing and services market has advanced in the past ten years. They now include most IT services from fundamental computing to cutting-edge AI capabilities. With the widespread adoption of cloud services, clients are facing the fact that they are utilizing cloud resources at a sub-optimal level. Cloud services brokers (CSBs) grew from the market to fill the needs for cloud resource management and risk mitigation. Based on analysis of the cloud market and the case of cloud services brokerage and related activities in North America, we offer theoretical analysis for how value creation works, its impacts on the …

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Steps Before Syntax: Helping Novice Programmers Solve Problems Using The Pcdit Framework, Oka Kurniawan, Cyrille Jegourel, Norman Tiong Seng Lee, Matthieu De Mari, Christopher M. Poskitt Jan 2022

Steps Before Syntax: Helping Novice Programmers Solve Problems Using The Pcdit Framework, Oka Kurniawan, Cyrille Jegourel, Norman Tiong Seng Lee, Matthieu De Mari, Christopher M. Poskitt

Research Collection School Of Computing and Information Systems

Novice programmers often struggle with problem solving due to the high cognitive loads they face. Furthermore, many introductory programming courses do not explicitly teach it, assuming that problem solving skills are acquired along the way. In this paper, we present 'PCDIT', a non-linear problem solving framework that provides scaffolding to guide novice programmers through the process of transforming a problem specification into an implemented and tested solution for an imperative programming language. A key distinction of PCDIT is its focus on developing concrete cases for the problem early without actually writing test code: students are instead encouraged to think about …

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On Discovering Motifs And Frequent Patterns In Spatial Trajectories With Discrete Fréchet Distance, Bo Tang, Man Lung Yiu, Kyriakos Mouratidis, Jiahao Zhang, Kai Wang Jan 2022

On Discovering Motifs And Frequent Patterns In Spatial Trajectories With Discrete Fréchet Distance, Bo Tang, Man Lung Yiu, Kyriakos Mouratidis, Jiahao Zhang, Kai Wang

Research Collection School Of Computing and Information Systems

The discrete Fréchet distance (DFD) captures perceptual and geographical similarity between two trajectories. It has been successfully adopted in a multitude of applications, such as signature and handwriting recognition, computer graphics, as well as geographic applications. Spatial applications, e.g., sports analysis, traffic analysis, etc. require discovering similar subtrajectories within a single trajectory or across multiple trajectories. In this paper, we adopt DFD as the similarity measure, and study two representative trajectory analysis problems, namely, motif discovery and frequent pattern discovery. Due to the time complexity of DFD, these tasks are computationally challenging. We address that challenge with a suite of …

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Accessibility In Software Practice: A Practitioner's Perspective, Tingting Bi, Xin Xia, David Lo, John C. Grundy, Thomas Zimmermann, Denae Ford Jan 2022

Accessibility In Software Practice: A Practitioner's Perspective, Tingting Bi, Xin Xia, David Lo, John C. Grundy, Thomas Zimmermann, Denae Ford

Research Collection School Of Computing and Information Systems

Being able to access software in daily life is vital for everyone, and thus accessibility is a fundamental challenge for software development. However, given the number of accessibility issues reported by many users, e.g., in app reviews, it is not clear if accessibility is widely integrated into current software projects and how software projects address accessibility issues. In this article, we report a study of the critical challenges and benefits of incorporating accessibility into software development and design. We applied a mixed qualitative and quantitative approach for gathering data from 15 interviews and 365 survey respondents from 26 countries across …

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Temporal Disambiguation Of Relative Temporal Expressions In Clinical Texts Using Temporally Fine-Tuned Contextual Word Embeddings., Amy L. Olex Jan 2022

Temporal Disambiguation Of Relative Temporal Expressions In Clinical Texts Using Temporally Fine-Tuned Contextual Word Embeddings., Amy L. Olex

Theses and Dissertations

Temporal reasoning is the ability to extract and assimilate temporal information to reconstruct a series of events such that they can be reasoned over to answer questions involving time. Temporal reasoning in the clinical domain is challenging due to specialized medical terms and nomenclature, shorthand notation, fragmented text, a variety of writing styles used by different medical units, redundancy of information that has to be reconciled, and an increased number of temporal references as compared to general domain texts. Work in the area of clinical temporal reasoning has progressed, but the current state-of-the-art still has a ways to go before …

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Learning Robot Motion From Creative Human Demonstration, Charles C. Dietzel Jan 2022

Learning Robot Motion From Creative Human Demonstration, Charles C. Dietzel

Theses and Dissertations

This thesis presents a learning from demonstration framework that enables a robot to learn and perform creative motions from human demonstrations in real-time. In order to satisfy all of the functional requirements for the framework, the developed technique is comprised of two modular components, which integrate together to provide the desired functionality. The first component, called Dancing from Demonstration (DfD), is a kinesthetic learning from demonstration technique. This technique is capable of playing back newly learned motions in real-time, as well as combining multiple learned motions together in a configurable way, either to reduce trajectory error or to generate entirely …

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Smart City Management Using Machine Learning Techniques, Mostafa Zaman Jan 2022

Smart City Management Using Machine Learning Techniques, Mostafa Zaman

Theses and Dissertations

In response to the growing urban population, "smart cities" are designed to improve people's quality of life by implementing cutting-edge technologies. The concept of a "smart city" refers to an effort to enhance a city's residents' economic and environmental well-being via implementing a centralized management system. With the use of sensors and actuators, smart cities can collect massive amounts of data, which can improve people's quality of life and design cities' services. Although smart cities contain vast amounts of data, only a percentage is used due to the noise and variety of the data sources. Information and communication technology (ICT) …

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Computational Analysis Of Drug Targets And Prediction Of Protein-Compound Interactions, Sina Ghadermarzi Jan 2022

Computational Analysis Of Drug Targets And Prediction Of Protein-Compound Interactions, Sina Ghadermarzi

Theses and Dissertations

Computational prediction of compound-protein interactions generated a substantial amount of interest in the recent years owing to the importance of the knowledge of these interaction for drug discovery and drug repurposing efforts. Research suggests that the currently known drug targets constitute only a fraction of a complete set of drug targets, limiting our ability to identify suitable targets to develop new drugs or to repurpose current drugs for new diseases. These efforts are further thwarted by our limited knowledge of protein-drug (and more generally protein-compound) interactions, where only a subset of drug targets is typically known for the currently used …

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Contextual Documentation Referencing On Stack Overflow, Sebastian Baltes, Christoph Treude, Martin P. Robillard Jan 2022

Contextual Documentation Referencing On Stack Overflow, Sebastian Baltes, Christoph Treude, Martin P. Robillard

Research Collection School Of Computing and Information Systems

Software engineering is knowledge-intensive and requires software developers to continually search for knowledge, often on community question answering platforms such as Stack Overflow. Such information sharing platforms do not exist in isolation, and part of the evidence that they exist in a broader software documentation ecosystem is the common presence of hyperlinks to other documentation resources found in forum posts. With the goal of helping to improve the information diffusion between Stack Overflow and other documentation resources, we conducted a study to answer the question of how and why documentation is referenced in Stack Overflow threads. We sampled and classified …

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Github Repositories With Links To Academic Papers: Public Access, Traceability, And Evolution, Supatsara Wattanakriengkrai, Bodin Chinthanet, Hideaki Hata, Raula Kula, Christoph Treude, Jin Guo, Kenichi Matsumoto Jan 2022

Github Repositories With Links To Academic Papers: Public Access, Traceability, And Evolution, Supatsara Wattanakriengkrai, Bodin Chinthanet, Hideaki Hata, Raula Kula, Christoph Treude, Jin Guo, Kenichi Matsumoto

Research Collection School Of Computing and Information Systems

Traceability between published scientific breakthroughs and their implementation is essential, especially in the case of open-source scientific software which implements bleeding-edge science in its code. However, aligning the link between GitHub repositories and academic papers can prove difficult, and the current practice of establishing and maintaining such links remains unknown. This paper investigates the role of academic paper references contained in these repositories. We conduct a large-scale study of 20 thousand GitHub repositories that make references to academic papers. We use a mixed-methods approach to identify public access, traceability and evolutionary aspects of the links. Although referencing a paper is …

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A Survey On Deep Learning For Software Engineering, Yanming Yang, Xin Xia, David Lo Jan 2022

A Survey On Deep Learning For Software Engineering, Yanming Yang, Xin Xia, David Lo

Research Collection School Of Computing and Information Systems

In 2006, Geoffrey Hinton proposed the concept of training "Deep Neural Networks (DNNs)" and an improved model training method to break the bottleneck of neural network development. More recently, the introduction of AlphaGo in 2016 demonstrated the powerful learning ability of deep learning and its enormous potential. Deep learning has been increasingly used to develop state-of-the-art software engineering (SE) research tools due to its ability to boost performance for various SE tasks. There are many factors, e.g., deep learning model selection, internal structure differences, and model optimization techniques, that may have an impact on the performance of DNNs applied in …

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Comparison Of The Mental Burden On Nursing Care Providers With And Without Mat-Type Sleep State Sensors At A Nursing Home In Tokyo, Japan: Quasi-Experimental Study, Sakiko Itoh, Hwee-Pink Tan, Kenichi Kudo, Yasuko Ogata Jan 2022

Comparison Of The Mental Burden On Nursing Care Providers With And Without Mat-Type Sleep State Sensors At A Nursing Home In Tokyo, Japan: Quasi-Experimental Study, Sakiko Itoh, Hwee-Pink Tan, Kenichi Kudo, Yasuko Ogata

Research Collection School Of Computing and Information Systems

Background: Increasing need for nursing care has led to the increased burden on formal caregivers, with those in nursing homes having to deal with exhausting labor. Although research activities on the use of internet of things devices to support nursing care for older adults exist, there is limited evidence on the effectiveness of these interventions among formal caregivers in nursing homes. Objective: This study aims to investigate whether mat-type sleep state sensors for supporting nursing care can reduce the mental burden of formal caregivers in a nursing home. Methods: This was a quasi-experimental study at a nursing home in Tokyo, …

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Approximate K-Nn Graph Construction: A Generic Online Approach, Wan-Lei Zhao, Hui Wang, Chong-Wah Ngo Jan 2022

Approximate K-Nn Graph Construction: A Generic Online Approach, Wan-Lei Zhao, Hui Wang, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Nearest neighbor search and k-nearest neighbor graph construction are two fundamental issues that arise from many disciplines such as multimedia information retrieval, data-mining, and machine learning. They become more and more imminent given the big data emerge in various fields in recent years. In this paper, a simple but effective solution both for approximate k-nearest neighbor search and approximate k-nearest neighbor graph construction is presented. These two issues are addressed jointly in our solution. On one hand, the approximate k-nearest neighbor graph construction is treated as a search task. Each sample along with its k-nearest neighbors is joined into the …

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Learning From Web Recipe-Image Pairs For Food Recognition: Problem, Baselines And Performance, Bin Zhu, Chong-Wah Ngo, Wing-Kwong Chan Jan 2022

Learning From Web Recipe-Image Pairs For Food Recognition: Problem, Baselines And Performance, Bin Zhu, Chong-Wah Ngo, Wing-Kwong Chan

Research Collection School Of Computing and Information Systems

Cross-modal recipe retrieval has recently been explored for food recognition and understanding. Text-rich recipe provides not only visual content information (e.g., ingredients, dish presentation) but also procedure of food preparation (cutting and cooking styles). The paired data is leveraged to train deep models to retrieve recipes for food images. Most recipes on the Web include sample pictures as the references. The paired multimedia data is not noise-free, due to errors such as pairing of images containing partially prepared dishes with recipes. The content of recipes and food images are not always consistent due to free-style writing and preparation of food …

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Secure Cloud Data Deduplication With Efficient Re-Encryption, Haoran Yuan, Xiaofeng Chen, Jin Li, Tao Jiang, Jianfeng Wang, Robert H. Deng Jan 2022

Secure Cloud Data Deduplication With Efficient Re-Encryption, Haoran Yuan, Xiaofeng Chen, Jin Li, Tao Jiang, Jianfeng Wang, Robert H. Deng

Research Collection School Of Computing and Information Systems

Data deduplication technique has been widely adopted by commercial cloud storage providers, which is both important and necessary in coping with the explosive growth of data. To further protect the security of users' sensitive data in the outsourced storage mode, many secure data deduplication schemes have been designed and applied in various scenarios. Among these schemes, secure and efficient re-encryption for encrypted data deduplication attracted the attention of many scholars, and many solutions have been designed to support dynamic ownership management. In this paper, we focus on the re-encryption deduplication storage system and show that the recently designed lightweight rekeying-aware …

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