Computer Sciences Commons^™

Covid-19 Pandemic: Role Of Technology In Transforming Business To The New Normal, Fiona Fui-Hoon Nah, Keng Siau

Research Collection School Of Computing and Information Systems

COVID-19 has disrupted our lives and the economy. In this paper, we outline approaches in which information technology can be used to implement business strategies to enhance resilience by coping with, adapting to, and recovering from adversity resulting from the COVID-19 pandemic. We discuss how information technology such as digital supply chain, data analytics, artificial intelligence, machine learning, robotics, digital commerce, and Internet of Things can be used to enhance resilience and continuity of business.

Keen2act: Activity Recommendation In Online Social Collaborative Platforms, Roy Ka-Wei Lee, Thong Hoang, Richard J. Oentaryo, David Lo

Research Collection School Of Computing and Information Systems

Social collaborative platforms such as GitHub and Stack Overflow have been increasingly used to improve work productivity via collaborative efforts. To improve user experiences in these platforms, it is desirable to have a recommender system that can suggest not only items (e.g., a GitHub repository) to a user, but also activities to be performed on the suggested items (e.g., forking a repository). To this end, we propose a new approach dubbed Keen2Act, which decomposes the recommendation problem into two stages: the Keen and Act steps. The Keen step identifies, for a given user, a (sub)set of items in which he/she …

A Systematic Media Frame Analysis Of 1.5 Million New York Times Articles From 2000 To 2017, Haewoon Kwak, Jisun An

Research Collection School Of Computing and Information Systems

Framing is an indispensable narrative device for news media because even the same facts may lead to conflicting understandings if deliberate framing is employed. Therefore, identifying media framing is a crucial step to understanding how news media influence the public. Framing is, however, difficult to operationalize and detect, and thus traditional media framing studies had to rely on manual annotation, which is challenging to scale up to massive news datasets. Here, by developing a media frame classifier that achieves state-of-the-art performance, we systematically analyze the media frames of 1.5 million New York Times articles published from 2000 to 2017. By …

Sentiment Analysis Over Collaborative Relationships In Open Source Software Projects, Lingjia Li, Jian Cao, David Lo

Research Collection School Of Computing and Information Systems

Sentiments and collaboration efficiency are key factors in the success of the open source software (OSS) development process. However, in the software engineering domain, no studies have been conducted to analyze the effect between collaborators' sentiments, and the role of sentiment in collaborative relationships during the development process. In this study, we apply sentiment analysis and statistical analysis on collaboration artifacts over five projects on GitHub. We use sentiment consistency to quantify the relation between sentiments in collaborative relationships. It is found that sentiment consistency is positively correlated with the closeness of collaborative relationships and collaborators' overall sentiment states. We …

Availability-Resilient Control Of Uncertain Linear Stochastic Networked Control Systems, Chandreyee Bhowmick, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

The resilient output feedback control of linear networked control (NCS) system with uncertain dynamics in the presence of Gaussian noise is presented under the denial of service (DoS) attacks on communication networks. The DoS attacks on the sensor-to-controller (S-C) and controller-to-actuator (C-A) networks induce random packet losses. The NCS is viewed as a jump linear system, where the linear NCS matrices are a function of induced losses that are considered unknown. A set of novel correlation detectors is introduced to detect packet drops in the network channels using the property of Gaussian noise. By using an augmented system representation, the …

Dynamic Trajectory Generation And A Robust Controller To Intercept A Moving Ball In A Game Setting, Ravi Prakash, Laxmidhar Behera, Santhakumar Mohan, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

Complex and interactive robot manipulation skills, such as playing a game of table tennis against a human opponent, are a novel problem with multifaceted challenges. Accurate dynamic trajectory generation in order to respond to the tennis ball from the opponent and a novel control scheme for robust and high-performance tracking of the ball in such dynamic situations is a prerequisite to winning the game. In this paper, the dynamic movement primitives (DMPs) are employed for the stable generation of dynamic trajectories in the presence of environmental uncertainties such as ball position and velocity, opponent position and velocity and so on. …

Towards A Cyber-Physical Manufacturing Cloud Through Operable Digital Twins And Virtual Production Lines, Md Rakib Shahriar

Graduate Theses and Dissertations

In last decade, the paradigm of Cyber-Physical Systems (CPS) has integrated industrial manufacturing systems with Cloud Computing technologies for Cloud Manufacturing. Up to 2015, there were many CPS-based manufacturing systems that collected real-time machining data to perform remote monitoring, prognostics and health management, and predictive maintenance. However, these CPS-integrated and network ready machines were not directly connected to the elements of Cloud Manufacturing and required human-in-the-loop. Addressing this gap, we introduced a new paradigm of Cyber-Physical Manufacturing Cloud (CPMC) that bridges a gap between physical machines and virtual space in 2017. CPMC virtualizes machine tools in cloud through web services …

Nonlinear Dimensionality Reduction For The Thermodynamics Of Small Clusters Of Particles, Aditya Dendukuri

Graduate Theses and Dissertations

This work employs tools and methods from computer science to study clusters comprising a small number N of interacting particles, which are of interest in science, engineering, and nanotechnology. Specifically, the thermodynamics of such clusters is studied using techniques from spectral graph theory (SGT) and machine learning (ML). SGT is used to define the structure of the clusters and ML is used on ensembles of cluster configurations to detect state variables that can be used to model the thermodynamic properties of the system. While the most fundamental description of a cluster is in 3N dimensions, i.e., the Cartesian coordinates of …

Graph-To-Tree Learning For Solving Math Word Problems, Jipeng Zhang, Lei Wang, Roy Ka-Wei Lee, Yi Bin, Yan Wang, Jie Shao, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

While the recent tree-based neural models have demonstrated promising results in generating solution expression for the math word problem (MWP), most of these models do not capture the relationships and order information among the quantities well. This results in poor quantity representations and incorrect solution expressions. In this paper, we propose Graph2Tree, a novel deep learning architecture that combines the merits of the graph-based encoder and tree-based decoder to generate better solution expressions. Included in our Graph2Tree framework are two graphs, namely the Quantity Cell Graph and Quantity Comparison Graph, which are designed to address limitations of existing methods by …

Zhvillimi I Një Ueb Aplikacioni E-Commerce Duke Përdorur Teknologjitë Gatsby Dhe React, Diart Novosella

Theses and Dissertations

Siç e dimë, sa i përket marrjes së informacionit, sa më shpejtë që informohemi, aq më të suksesshëm jemi dhe kur bëhet fjalë për kërkim të produkteve, rrobave apo çfarëdo që njerëzit kanë nevojë Interneti e ka lehtësuar shumë këtë. Prandaj, në ditët e sotme gjithçka që ndërtohet, çdo kompani, çdo person, sot ka një vlerë në Internet, qoftë si dhënës i informacionit apo si marrës i informacionit. Vet themelimi i ueb-it ishte arsye që komunikimi dhe marrja e informacioni të bëhet sa më shpejtë dhe sa më të saktë. Ekzistojnë shumë metodologji të ndryshme që sot përdoren për ndërtimin …

Klasifikimi I Lajmeve Me Ane Te Text Mining, Myhedin Zika

Theses and Dissertations

Në këtë punim trajtohet problemi se cili algoritëm funksionon më së miri në klasifikimin e tekstit shqip në kategori të caktuara. Arsyeja kryesore pse kam zgjedhur këte temë është për shkak se klasifikimi i tekstit në gjuhën shqipe mund të jetë pak me i komplikuar për shkak të gjuhës sonë. Rëndesia e ketij punimi është se mund të implementohen këto algoritme në krijimin e platformave e ndryshme qe implementojne keto algoritme, mirepo me fokus kryesisht me permbajtje në gjuhën shqipe.

Për zgjedhjen e ketij problemi kemi marrur dy algoritme për krahasim, njëri prej tyre Naive Bayes dhe tjetri SVM. Kemi …

Algorithmic Robot Design: Label Maps, Procrustean Graphs, And The Boundary Of Non-Destructiveness, Shervin Ghasemlou

Theses and Dissertations

This dissertation is focused on the problem of algorithmic robot design. The process of designing a robot or a team of robots that can reliably accomplish a task in an environment requires several key elements. How the problem is formulated can play a big role in the design process. The ability of the model to correctly reflect the environment, the events, and different pieces of the problem is crucial. Another key element is the ability of the model to show the relationship between different designs of a single system. These two elements can enable design algorithms to navigate through the …

Smart Sensing Enabled Secure And Usable Pairing And Authentication, Xiaopeng Li

Theses and Dissertations

Internet of Things (IoT) technologies have made our lives more convenient and better informed by sensing and monitoring our surroundings. Security applications, such as device pairing and user authentication, are the fundamentals for building a trustworthy smart environment. A secure and convenient pairing approach is critical to IoT enabled applications, as pairing is to establish a secure wireless communication channel for devices. Besides, a smart environment usually has multiple people (e.g., patients and doctors in a hospital), who have physical access to the deployed IoT devices and sensitive dumb objects (e.g., a cabinet storing medical records); but not all of …

Power-Over-Tether Uas Leveraged For Nearly-Indefinite Meteorological Data Acquisition, Daniel Rico, Carrick Detweiler, Francisco Muñoz-Arriola

School of Computing: Dissertations, Theses, and Student Research

Use of unmanned aerial systems (UASs) in agriculture has risen in the past decade. These systems are key to modernizing agriculture. UASs collect and elucidate data previously difficult to obtain and used to help increase agricultural efficiency and production. Typical commercial off-the-shelf (COTS) UASs are limited by small payloads and short flight times. Such limits inhibit their ability to provide abundant data at multiple spatiotemporal scales. In this paper, we describe the design and construction of the tethered aircraft unmanned system (TAUS), which is a novel power-over-tether UAS leveraging the physical presence of the tether to launch multiple sensors along …

Addressing Parameter Uncertainty In Sd Models With Fit-To-History And Monte-Carlo Sensitivity Methods, Wayne Wakeland, Jack Homer

Complex Systems Faculty Publications and Presentations

We present a practical guide, including a step-by-step flowchart, for establishing uncertainty intervals for key model outcomes in the face of uncertain parameters. The process starts with Powell optimization (e.g., using VensimTM) to find a set of uncertain parameters (the “optimum” parameter set or OPS) that minimize the model fitness error relative to available reference behavior data. The optimization process also helps in refinement of assumed parameter uncertainty ranges. Next, Markov Chain Monte Carlo (MCMC) or conventional Monte Carlo (MC) randomization is used to create a sample of parameter sets that fit the reference behavior data nearly as well as …

Application Of Siem/Ueba/Soar/Soc (Cyber Suss) Concepts On Mscs 6560 Computer Lab, Kunal Singh

Master's Theses (2009 -)

Increased Cyber-attacks on the IT infrastructure is a grave concern for organizations. Cyber defense and cyber threat remediation have become topmost priority of organizations. This thesis explains the core concepts of SIEM, UEBA, SOAR and SOC (SUSS) and explains the details of an experimental solution to which was applied MSCS 6560 lab computers for real time cyber threat detection and remediations. To test and validate SUSS concepts, these technologies were successfully applied to a small lab environment in the MSCS infrastructure for the graduate class on the Principle of Service Management and System Administration. Lab machines in this class were …

Busting Myths And Dispelling Doubts About Covid-19, Mark Findlay

Research Collection Yong Pung How School Of Law

The Centre for AI and Data Governance (CAIDG) at Singapore Management University (SMU) has embarked over past months on a programme of research designed to confront concerns about the pandemic and its control. Our interest is primarily directed to the ways in which AI-assisted technologies and mass data sharing have become a feature of pandemic control strategies. We want to know what impact these developments are having on community confidence and health safety. In developing this work, we have come across many myths that need busting.

A Web-Based User-Interface For Internet Of Things Device Management, Leena Mansour Alghamdi

Theses and Dissertations

With the growing advances in the Internet of Things (IoT) technology, which combines various devices with distinct functions, capabilities, and communication protocols, it is essential to provide a platform that enables IoT users to interact with their IoT devices directly and be able to manage them effortlessly via that platform from various locations at any time in order to protect their privacy when using IoT devices. In this study, we are aiming to provide a web-based user interface that can address that challenges and provide real-time data control; hence, we have created a user interface prototype, which can demonstrate the …

Email Data Breach Analysis And Prevention Using Hook And Eye System, Shubhankar Jayant Jathar

Electronic Theses, Projects, and Dissertations

Due to the recent COVID-19 outbreak, there were a lot of data leaks from the health sector. This project is about the increase in data breach incidents that are taking place. In this project, There is an analysis of different types of breaches that are found online and are practiced to steal valuable information. Talking about different aspects that lead to data breaches and which are the main sector or main epicenter for data leaks. The analysis tells that most of the data breaches are done using emails and to overcome this limitation a system has been designed that will …

An Improved Bone Age Assessment Using Advanced Image Processing And Deep Learning Approach, Kim Meng Liang

Student Works (2020-2029)

Pediatricians often apply bone age assessment to measure the skeletal maturity of children and to predict the future height. These discrepancies are good indicators for diagnosing growth disorders. Normally, left hand skeletal is employed in this assessment. The low quality of ossification sites of carpals deteriorates the pediatrician’s visibility in inspecting the pertinent radiographic manifestations. This in turn affects the bone age assessment. Therefore, we have to enhance the quality before assessing them. Histogram equalization is one of the contrast enhancement techniques that suit this type of enhancement. Existing histogram equalizations, however, are confronting with problems in preserving the brightness …

Automatic Android Deprecated-Api Usage Update By Learning From Single Updated Example, Stefanus A. Haryono, Ferdian Thung, Hong Jin Kang, Lucas Serrano, Gilles Muller, Julia Lawall, David Lo, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Due to the deprecation of APIs in the Android operating system, developers have to update usages of the APIs to ensure that their applications work for both the past and current versions of Android. Such updates may be widespread, non-trivial, and time-consuming. Therefore, automation of such updates will be of great benefit to developers. AppEvolve, which is the state-of-the-art tool for automating such updates, relies on having before- and after-update examples to learn from. In this work, we propose an approach named CocciEvolve that performs such updates using only a single after-update example. CocciEvolve learns edits by extracting the relevant …

Psc2code: Denoising Code Extraction From Programming Screencasts, Lingfeng Bao, Zhenchang Xing, Xin Xia, David Lo, Minghui Wu, Xiaohu Yang

Research Collection School Of Computing and Information Systems

Programming screencasts have become a pervasive resource on the Internet, which help developers learn new programming technologies or skills. The source code in programming screencasts is an important and valuable information for developers. But the streaming nature of programming screencasts (i.e., a sequence of screen-captured images) limits the ways that developers can interact with the source code in the screencasts. Many studies use the Optical Character Recognition (OCR) technique to convert screen images (also referred to as video frames) into textual content, which can then be indexed and searched easily. However, noisy screen images significantly affect the quality of source …

Automated Synthesis Of Local Time Requirement For Service Composition, Étienne André, Tian Huat Tan, Manman Chen, Shuang Liu, Jun Sun, Yang Liu, Jin Song Dong

Research Collection School Of Computing and Information Systems

Service composition aims at achieving a business goal by composing existing service-based applications or components. The response time of a service is crucial, especially in time-critical business environments, which is often stated as a clause in service-level agreements between service providers and service users. To meet the guaranteed response time requirement of a composite service, it is important to select a feasible set of component services such that their response time will collectively satisfy the response time requirement of the composite service. In this work, we use the BPEL modeling language that aims at specifying Web services. We extend it …

Objsim: Efficient Testing Of Cyber-Physical Systems, Jun Sun, Zijiang Yang

Research Collection School Of Computing and Information Systems

Cyber-physical systems (CPSs) play a critical role in automating public infrastructure and thus attract wide range of attacks. Assessing the effectiveness of defense mechanisms is challenging as realistic sets of attacks to test them against are not always available. In this short paper, we briefly describe smart fuzzing, an automated, machine learning guided technique for systematically producing test suites of CPS network attacks. Our approach uses predictive ma- chine learning models and meta-heuristic search algorithms to guide the fuzzing of actuators so as to drive the CPS into different unsafe physical states. The approach has been proven effective on two …

Recovering Fitness Gradients For Interprocedural Boolean Flags In Search-Based Testing, Yun Lin, Jun Sun, Gordon Fraser, Ziheng Xiu, Ting Liu, Jin Song Dong

Research Collection School Of Computing and Information Systems

In Search-based Software Testing (SBST), test generation is guided by fitness functions that estimate how close a test case is to reach an uncovered test goal (e.g., branch). A popular fitness function estimates how close conditional statements are to evaluating to true or false, i.e., the branch distance. However, when conditions read Boolean variables (e.g., if(x && y)), the branch distance provides no gradient for the search, since a Boolean can either be true or false. This flag problem can be addressed by transforming individual procedures such that Boolean flags are replaced with numeric comparisons that provide better guidance for …

Global Pac Bounds For Learning Discrete Time Markov Chains, Hugo Bazille, Blaise Genest, Cyrille Jegourel, Jun Sun

Research Collection School Of Computing and Information Systems

Learning models from observations of a system is a powerful tool with many applications. In this paper, we consider learning Discrete Time Markov Chains (DTMC), with different methods such as frequency estimation or Laplace smoothing. While models learnt with such methods converge asymptotically towards the exact system, a more practical question in the realm of trusted machine learning is how accurate a model learnt with a limited time budget is. Existing approaches provide bounds on how close the model is to the original system, in terms of bounds on local (transition) probabilities, which has unclear implication on the global behavior. …

What Was Written Vs. Who Read It: News Media Profiling Using Text Analysis And Social Media Context, Ramy Baly, Georgi Karadzhov, Jisun An, Haewoon Kwak, Yoan Dinkov, Ahmed Ali, James Glass, Preslav. Nakov

Research Collection School Of Computing and Information Systems

Predicting the political bias and the factuality of reporting of entire news outlets are critical elements of media profiling, which is an understudied but an increasingly important research direction. The present level of proliferation of fake, biased, and propagandistic content online has made it impossible to fact-check every single suspicious claim, either manually or automatically. Thus, it has been proposed to profile entire news outlets and to look for those that are likely to publish fake or biased content. This makes it possible to detect likely “fake news” the moment they are published, by simply checking the reliability of their …

Active Fuzzing For Testing And Securing Cyber-Physical Systems, Yuqi Chen, Bohan Xuan, Christopher M. Poskitt, Jun Sun, Fan Zhang

Research Collection School Of Computing and Information Systems

Cyber-physical systems (CPSs) in critical infrastructure face a pervasive threat from attackers, motivating research into a variety of countermeasures for securing them. Assessing the effectiveness of these countermeasures is challenging, however, as realistic benchmarks of attacks are difficult to manually construct, blindly testing is ineffective due to the enormous search spaces and resource requirements, and intelligent fuzzing approaches require impractical amounts of data and network access. In this work, we propose active fuzzing, an automatic approach for finding test suites of packet-level CPS network attacks, targeting scenarios in which attackers can observe sensors and manipulate packets, but have no existing …

Expertise Style Transfer: A New Task Towards Better Communication Between Experts And Laymen, Yixin Cao, Ruihao Shui, Liangming Pan, Min-Yen Kan, Zhiyuan Lu, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

The curse of knowledge can impede communication between experts and laymen. We propose a new task of expertise style transfer and contribute a manually annotated dataset with the goal of alleviating such cognitive biases. Solving this task not only simplifies the professional language, but also improves the accuracy and expertise level of laymen descriptions using simple words. This is a challenging task, unaddressed in previous work, as it requires the models to have expert intelligence in order to modify text with a deep understanding of domain knowledge and structures. We establish the benchmark performance of five state-of-the-art models for style …

Improving Event Detection Via Open-Domain Event Trigger Knowledge, Meihan Tong, Bin Xu, Shuai Wang, Yixin Cao, Lei Hou, Juanzi Li, Jun Xie

Research Collection School Of Computing and Information Systems

Event Detection (ED) is a fundamental task in automatically structuring texts. Due to the small scale of training data, previous methods perform poorly on unseen/sparsely labeled trigger words and are prone to overfitting densely labeled trigger words. To address the issue, we propose a novel Enrichment Knowledge Distillation (EKD) model to leverage external open-domain trigger knowledge to reduce the in-built biases to frequent trigger words in annotations. Experiments on benchmark ACE2005 show that our model outperforms nine strong baselines, is especially effective for unseen/sparsely labeled trigger words. The source code is released on https://github.com/shuaiwa16/ekd.git.