Computer Sciences Commons^™

Cleanpage: Fast And Clean Document And Whiteboard Capture, Jane Courtney

Articles

The move from paper to online is not only necessary for remote working, it is also significantly more sustainable. This trend has seen a rising need for the high-quality digitization of content from pages and whiteboards to sharable online material. However, capturing this information is not always easy nor are the results always satisfactory. Available scanning apps vary in their usability and do not always produce clean results, retaining surface imperfections from the page or whiteboard in their output images. CleanPage, a novel smartphone-based document and whiteboard scanning system, is presented. CleanPage requires one button-tap to capture, identify, crop, and …

Chapter 3: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana

Open Educational Resources

No abstract provided.

Chapter 2: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana

Open Educational Resources

No abstract provided.

Chapter 5: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana

Open Educational Resources

No abstract provided.

Chapter 1: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana

Open Educational Resources

No abstract provided.

The Utility Of Multiple Structure Torsion Angle Alignment In Protein Active Site Description (Asd), Devaun L. Mcfarland

Theses and Dissertations

Proteins are responsible for various functions throughout organisms, or within the systems, they operate. Active-sites or functional/ binding sites are regions responsible for activity in a protein; they serve as a catalyst for reactions, attach or bind to other molecules (ligands), and maintain function. With the profusion of protein sequence and structure data, it's increasingly relevant to develop automated methods of identifying and investigating active-sites for proteins. Active-sites identification will have a direct impact: in better understanding molecular basis for diseases, assisting in drug design, the study of targeting mutants, and for functional annotation of unknown proteins. The proper knowledge …

Revisiting The Law Of Confidence In Singapore And A Proposal For A New Tort Of Misuse Of Private Information, Cheng Lim Saw, Zheng Wen Samuel Chan, Wen Min Chai

Research Collection Yong Pung How School Of Law

This article critically examines the recent Court of Appeal decision in I-Admin (Singapore) Pte Ltd v Hong Ying Ting [2020] 1 SLR 1130 and its implications for the law of confidence. The article begins by setting out the decision at first instance, and then on appeal. It argues that the Court of Appeal’s “modified approach” fails to meaningfully engage the plaintiff ’s wrongful gain interest and places the law’s emphasis primarily, if not wholly, on the plaintiff ’s wrongful loss interest. The new framework also appears to have been influenced by English jurisprudence, which has had a long but unhelpful …

Track My Ride, Cesar Padron Ramirez, Jady Silva Martins, Maria De La Luz Lagunas Modesto, Rodolfo Carvajal Marquez, Yuri Braga

ICT

Cycling has become more and more popular as a healthy activity and a transport option across many countries. This is not different in Ireland, a country where in April 2016, 56,837 people cycled to work; an increase of 43% since 2011 (Central statistics office, 2017).

Irish Government “committed to developing cycling as one of the most desirable modes of travel by 2020” as it plays an indispensable role in people’s lives (Sustainable transport division - department of transport, tourism and sport, 2009).

The “Balance” team managed to visualize that a strong cycling culture was becoming important in Ireland. Hence our …

Mysmartpi, Camila Pulz De Faria, Fernando Aires Da Silva, Jesus Colina Nunez, Reginaldo Pereira Dos Santos, Thenilde Borges

ICT

Nowadays, accessing the Internet in a secure way in a big concern for many people due to the increase of cybersecurity attacks and the vulnerability of the data that is transferred online. In order to address such vulnerabilities, the use of a Virtual Private Network is really important. Not only for security reasons, but also to access resources of the network, such as printers, files or web pages. Considering that many people, especially IT students, have curiosity and enjoy creating their own technologies, this project aims to create a user manual to teach how people can create their own VPN …

Student Meetup: An Ajs Project, Alejandro Zeballos, Suelen De Campos Fiorelo, James Harris

ICT

This report focuses on our perceived lack of applications that can assist students in finding suitable environments in which they can study together. Our research has shown that while there are applications that are dedicated to helping students to study, none that we have found help students connect with one another, for the sole purpose of studying.

With our application, we intend to create a platform that will enable students to connect with each other, on both a website and a mobile application. We hope to give students the ability to create and join study sessions, as well as provide …

[Chain Up Group] Applied Technology Group Project, Maria Beluz Suarez, Haein Kim

ICT

This document presents the draft of the introductory chapter as well as the research and planning aspects of developing a text hosting service application based on block chain technology named‘Chain UP. This report represents part I of the continuous assessment of the year-module named Applied Technology Group Project for the 3rd year of the Information Technology course at CCT College Dublin. This chapter contains an introduction to Blockchain’s concepts and an overview of its benefits and the latest industry applications of this technology, specifically the financial services industry and the data security industry. In the next chapters, we will discuss …

Applied Technology Group Project Documentation For Nls-Project, Cauê Duarte, Felipe Mantovani, Olga Kiseleva, Taras Boreyko

ICT

Loyalty systems are commonly used to build and improve relationships between business and customers. Throughout history they evolved and became almost essential for small businesses such as coffee shops or small local stores. In this paper we will analyze existing loyalty systems that are presented in the world and Irish market, how they are used in the coffee shop industry and how new technologies can change and shape this industry. We examined multiple coffee shops brands present in Ireland and their rewards systems. We compared their loyalty systems using alternative methodologies and theoretical lenses in order to find new ways …

Smart Wearable Device For Reduction Of Parkinson’S Disease Hand-Tremor, Bruno Ribeiro, Leopoldo Medeiros, Rodrigo Aguiar, Juan Carlos

ICT

Parkinson's disease is a neurodegenerative disorder that affects over 10 million people worldwide (Health Unlocked, 2017). People diagnosed with Parkinson's Disease can experience tremors, muscular rigidity and slowness of movement. Tremor is the most common symptom and external agents like stress and anxiety can make it worse, which may cause complications to complete simple day-to-day tasks.

Therefore Bio Protech proposes the development of a smart wearable device for reduction of the hand-tremors based on medical evidence that by applying vibration to the wrist may result in a reduction of the involuntary tremor. The device imitates the shape of a wristwatch …

The Wall: A Mobile App To Identify And Store Social Events From A Digital Image Using Computer Vision, Akhill Chandran, Ana Julia Ortiz, Eliezer Maia Barbosa, Maura Carola Tangara, Raquel Martini

ICT

Social events, promoted in print media using posters, flyers and banners often fail to attract an audience because we frequently forget the details of the event when we pass-by the promotion on the street. Smaller venues or artists often rely on low-cost, street-level marketing campaigns in areas of high foot traffic areas to develop interest in an event. These venues or artist are often without a budget for online marketing or have a target demographic outside the typical Social Media consumer which makes attracting an audience difficult.

This project aimed to solve the problem of storing and reminding the user …

Lecture - Csci 275: Linux Systems Administration And Security, Moe Hassan, Nyc Tech-In-Residence Corps

Open Educational Resources

Lecture for CSCI 275: Linux Systems Administration and Security

Message From The General Co-Chairs And The Program Co-Chairs, Christoph Treude, Hongyu Zhang, Kelly Blincoe, Zhenchang Xing

Research Collection School Of Computing and Information Systems

Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record.

The Impact Of Dynamics Of Collaborative Software Engineering On Introverts: A Study Protocol, Ingrid Nunes, Christoph Treude, Fabio Calefato

Research Collection School Of Computing and Information Systems

Background: Collaboration among software engineers through face-to-face discussions in teams has been promoted since the adoption of agile methods. However, these discussions might demote the contribution of software engineers who are introverts, possibly leading to sub-optimal solutions and creating work environments that benefit extroverts. Objective: We aim to evaluate whether providing software engineers with time to work individually and reason about a collective problem is a setting that makes introverts more comfortable to interact and contribute more, ultimately leading to better solutions. Method: We plan to conduct a between-subjects study, with teams in a control group that design a software …

Fakepolisher: Making Deepfakes More Detection-Evasive By Shallow Reconstruction, Yihao Huang, Felix Juefei-Xu, Run Wang, Qing Guo, Lei Ma, Xiaofei Xie, Jianwen Li, Weikai Miao, Yang Liu, Geguang Pu

Research Collection School Of Computing and Information Systems

At this moment, GAN-based image generation methods are still imperfect, whose upsampling design has limitations in leaving some certain artifact patterns in the synthesized image. Such artifact patterns can be easily exploited (by recent methods) for difference detection of real and GAN-synthesized images. However, the existing detection methods put much emphasis on the artifact patterns, which can become futile if such artifact patterns were reduced.Towards reducing the artifacts in the synthesized images, in this paper, we devise a simple yet powerful approach termed FakePolisher that performs shallow reconstruction of fake images through a learned linear dictionary, intending to effectively and …

Deeprhythm: Exposing Deepfakes With Attentional Visual Heartbeat Rhythms, Hua Qi, Qing Guo, Felix Juefei-Xu, Xiaofei Xie, Lei Ma, Wei Feng, Yang Liu, Jianjun Zhao

Research Collection School Of Computing and Information Systems

As the GAN-based face image and video generation techniques, widely known as DeepFakes, have become more and more matured and realistic, there comes a pressing and urgent demand for effective DeepFakes detectors. Motivated by the fact that remote visual photoplethysmography (PPG) is made possible by monitoring the minuscule periodic changes of skin color due to blood pumping through the face, we conjecture that normal heartbeat rhythms found in the real face videos will be disrupted or even entirely broken in a DeepFake video, making it a potentially powerful indicator for DeepFake detection. In this work, we propose DeepRhythm, a DeepFake …

Amora: Black-Box Adversarial Morphing Attack, Run Wang, Felix Juefei-Xu, Qing Guo, Yihao Huang, Xiaofei Xie, Lei Ma, Yang Liu

Research Collection School Of Computing and Information Systems

Nowadays, digital facial content manipulation has become ubiquitous and realistic with the success of generative adversarial networks (GANs), making face recognition (FR) systems suffer from unprecedented security concerns. In this paper, we investigate and introduce a new type of adversarial attack to evade FR systems by manipulating facial content, called adversarial morphing attack (a.k.a. Amora). In contrast to adversarial noise attack that perturbs pixel intensity values by adding human-imperceptible noise, our proposed adversarial morphing attack works at the semantic level that perturbs pixels spatially in a coherent manner. To tackle the black-box attack problem, we devise a simple yet effective …

Deepsonar: Towards Effective And Robust Detection Of Ai-Synthesized Fake Voices, Run Wang, Felix Juefei-Xu, Yihao Huang, Qing Guo, Xiaofei Xie, Lei Ma, Yang Liu

Research Collection School Of Computing and Information Systems

With the recent advances in voice synthesis, AI-synthesized fake voices are indistinguishable to human ears and widely are applied to produce realistic and natural DeepFakes, exhibiting real threats to our society. However, effective and robust detectors for synthesized fake voices are still in their infancy and are not ready to fully tackle this emerging threat. In this paper, we devise a novel approach, named DeepSonar, based on monitoring neuron behaviors of speaker recognition (SR) system, i.e., a deep neural network (DNN), to discern AI-synthesized fake voices. Layer-wise neuron behaviors provide an important insight to meticulously catch the differences among inputs, …

Regression Testing Of Massively Multiplayer Online Role-Playing Games, Yuechen Wu, Yingfeng Chen, Xiaofei Xie, Bing Yu, Changjie Fan, Lei Ma

Research Collection School Of Computing and Information Systems

Regression testing aims to check the functionality consistency during software evolution. Although general regression testing has been extensively studied, regression testing in the context of video games, especially Massively Multiplayer Online Role-Playing Games (MMORPGs), is largely untouched so far. One big challenge is that game testing requires a certain level of intelligence in generating suitable action sequences among the huge search space, to accomplish complex tasks in the MMORPG. Existing game testing mainly relies on either the manual playing or manual scripting, which are labor-intensive and time-consuming. Even worse, it is often unable to satisfy the frequent industrial game evolution. …

Annapurna: An Automated Smartwatch-Based Eating Detection And Food Journaling System, Sougata Sen, Vigneshwaran Subbaraju, Archan Misra, Rajesh Krishna Balan, Youngki Lee

Research Collection School Of Computing and Information Systems

Maintaining a food journal can allow an individual to monitor eating habits, including unhealthy eating sessions, food items causing severe reactions, or portion size related information. However, manually maintaining a food journal can be burdensome. In this paper, we explore the vision of a pervasive, automated, completely unobtrusive, food journaling system using a commodity smartwatch. We present a prototype system — Annapurna— which is composed of three key components: (a) a smartwatch-based gesture recognizer that can robustly identify eating-specific gestures occurring anywhere, (b) a smartwatch-based image captor that obtains a small set of relevant images (containing views of the food …

Tpr: Text-Aware Preference Ranking For Recommender Systems, Yu-Neng Chuang, Chih-Ming Chen, Chuan-Ju Wang, Ming-Feng Tsai, Yuan Fang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Textual data is common and informative auxiliary information for recommender systems. Most prior art utilizes text for rating prediction, but rare work connects it to top-N recommendation. Moreover, although advanced recommendation models capable of incorporating auxiliary information have been developed, none of these are specifically designed to model textual information, yielding a limited usage scenario for typical user-to-item recommendation. In this work, we present a framework of text-aware preference ranking (TPR) for top-N recommendation, in which we comprehensively model the joint association of user-item interaction and relations between items and associated text. Using the TPR framework, we construct a joint …

Towards Locality-Aware Meta-Learning Of Tail Node Embeddings On Networks, Zemin Liu, Wentao Zhang, Yuan Fang, Xinming Zhang, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Network embedding is an active research area due to the prevalence of network-structured data. While the state of the art often learns high-quality embedding vectors for high-degree nodes with abundant structural connectivity, the quality of the embedding vectors for low-degree or tail nodes is often suboptimal due to their limited structural connectivity. While many real-world networks are long-tailed, to date little effort has been devoted to tail node embedding. In this paper, we formulate the goal of learning tail node embeddings as a few-shot regression problem, given the few links on each tail node. In particular, since each node resides …

Towards Systematically Deriving Defence Mechanisms From Functional Requirements Of Cyber-Physical Systems, Cheah Huei Yoong, Venkata Reddy Palleti, Arlindo Silva, Christopher M. Poskitt

Research Collection School Of Computing and Information Systems

The threats faced by cyber-physical systems (CPSs) in critical infrastructure have motivated the development of different attack detection mechanisms, such as those that monitor for violations of invariants, i.e. properties that always hold in normal operation. Given the complexity of CPSs, several existing approaches focus on deriving invariants automatically from data logs, but these can miss possible system behaviours if they are not represented in that data. Furthermore, resolving any design flaws identified in this process is costly, as the CPS is already built. In this position paper, we propose a systematic method for deriving invariants before a CPS is …

Gym Usage Behavior & Desired Digital Interventions: An Empirical Study, Meeralakshmi Radhakrishnan, Archan Misra, Rajesh Krishna Balan, Youngki Lee

Research Collection School Of Computing and Information Systems

Understanding individual’s exercise motives, participation patterns in a gym and reasons for dropout are essential for designing strategies to help gym-goers with long-term exercise adherence. In this work, we derive insights on various exercise-related behaviors of gymgoers, including evidence of a significant number of individuals exhibiting early dropout and also describing their attitudes towards digital technologies for sustained gym participation. By utilizing gym visitation data logs of 6513 individuals over a longitudinal period of 16 months in a campus gym, we show the retention and dropout rates of gym-goers. Our data indicates that 32% of the people quit their gym …

The Future Of Work Now: Ai-Driven Transaction Surveillance At Dbs Bank, Thomas H. Davenport, Steven M. Miller

Research Collection School Of Computing and Information Systems

One of the most frequently-used phrases at business events these days is “the future of work.” It’s increasingly clear that artificial intelligence and other new technologies will bring substantial changes in work tasks and business processes. But while these changes are predicted for the future, they’re already present in many organizations for many different jobs. The job and incumbents described below are an example of this phenomenon. Steve Miller of Singapore Management University and I co-authored the story.

Peer-Inspired Student Performance Prediction In Interactive Online Question Pools With Graph Neural Network, Haotian Li, Huan Wei, Yong Wang, Yangqiu Song, Huamin. Qu

Research Collection School Of Computing and Information Systems

Student performance prediction is critical to online education. It can benefit many downstream tasks on online learning platforms, such as estimating dropout rates, facilitating strategic intervention, and enabling adaptive online learning. Interactive online question pools provide students with interesting interactive questions to practice their knowledge in online education. However, little research has been done on student performance prediction in interactive online question pools. Existing work on student performance prediction targets at online learning platforms with predefined course curriculum and accurate knowledge labels like MOOC platforms, but they are not able to fully model knowledge evolution of students in interactive online …

Gesture Enhanced Comprehension Of Ambiguous Human-To-Robot Instructions, Weerakoon Mudiyanselage Dulanga Kaveesha Weerakoon, Vigneshwaran Subbaraju, Nipuni Karumpulli, Minh Anh Tuan Tran, Qianli Xu, U-Xuan Tan, Joo Hwee Lim, Archan Misra

Research Collection School Of Computing and Information Systems

This work demonstrates the feasibility and benefits of using pointing gestures, a naturally-generated additional input modality, to improve the multi-modal comprehension accuracy of human instructions to robotic agents for collaborative tasks.We present M2Gestic, a system that combines neural-based text parsing with a novel knowledge-graph traversal mechanism, over a multi-modal input of vision, natural language text and pointing. Via multiple studies related to a benchmark table top manipulation task, we show that (a) M2Gestic can achieve close-to-human performance in reasoning over unambiguous verbal instructions, and (b) incorporating pointing input (even with its inherent location uncertainty) in M2Gestic results in a significant …