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Articles 181 - 210 of 272
Full-Text Articles in Software Engineering
Autism Searches: A Modern Search Engine For Asd Related Topics, Joshua Schappel, Jonathan Simone Bar-Eli, Sachin Mahashabde, Jeremy Suero
Autism Searches: A Modern Search Engine For Asd Related Topics, Joshua Schappel, Jonathan Simone Bar-Eli, Sachin Mahashabde, Jeremy Suero
Petersheim Academic Exposition
No abstract provided.
Devops: Lecture 1 - "Overview", Jeremy Andrews, Nyc Tech-In-Residence Corps
Devops: Lecture 1 - "Overview", Jeremy Andrews, Nyc Tech-In-Residence Corps
Open Educational Resources
Overview lecture for the "DevOps" course delivered at the City College of New York in Spring 2020 by Jeremy Andrews as part of the Tech-in-Residence Corps program.
Byod-Insure: A Security Assessment Model For Enterprise Byod, Melva Ratchford
Byod-Insure: A Security Assessment Model For Enterprise Byod, Melva Ratchford
Masters Theses & Doctoral Dissertations
As organizations continue allowing employees to use their personal mobile devices to access the organizations’ networks and the corporate data, a phenomenon called ‘Bring Your Own Device’ or BYOD, proper security controls need to be adopted not only to secure the corporate data but also to protect the organizations against possible litigation problems. Until recently, current literature and research have been focused on specific areas or solutions regarding BYOD. The information associated with BYOD security issues in the areas of Management, IT, Users and Mobile Device Solutions is fragmented. This research is based on a need to provide a holistic …
Devops: Architecting Your Infrastructure (Syllabus), Jeremy Andrews, Nyc Tech-In-Residence Corps
Devops: Architecting Your Infrastructure (Syllabus), Jeremy Andrews, Nyc Tech-In-Residence Corps
Open Educational Resources
Syllabus for the "DevOps" course delivered at the City College of New York in Spring 2020 by Jeremy Andrews as part of the Tech-in-Residence Corps program.
Designing A Smart Internet Of Things Solution For Point Of Use Water Filtration Management System In Residential, Commercial And Public Settings, Tristan Lim, Hwee-Pink Tan, Chin Sin Ong, Rahul Belani, Siddhant S. K. Agrawal
Designing A Smart Internet Of Things Solution For Point Of Use Water Filtration Management System In Residential, Commercial And Public Settings, Tristan Lim, Hwee-Pink Tan, Chin Sin Ong, Rahul Belani, Siddhant S. K. Agrawal
Research Collection School Of Computing and Information Systems
The use of water filtration Point-of-Use (POU) systems are extensive, ranging from water dispensers in public estates, to household POU water systems. Manufacturers typically recommend filtration cartridges to be changed (i) after their useful life, or (ii) when the water flow volume have exceeded certain capacity, whichever is earlier. However, filtration mechanisms are typically not changed with sufficient regularity. Overused filters can result in negative health effects, over and above the deterioration and loss of filtration benefits of the POU water system. Presently most existing water purification systems do not have smart connected Internet of Things (IoT) means of informing …
Gradual Program Analysis, Samuel Estep
Gradual Program Analysis, Samuel Estep
Senior Honors Theses
Dataflow analysis and gradual typing are both well-studied methods to gain information about computer programs in a finite amount of time. The gradual program analysis project seeks to combine those two techniques in order to gain the benefits of both. This thesis explores the background information necessary to understand gradual program analysis, and then briefly discusses the research itself, with reference to publication of work done so far. The background topics include essential aspects of programming language theory, such as syntax, semantics, and static typing; dataflow analysis concepts, such as abstract interpretation, semilattices, and fixpoint computations; and gradual typing theory, …
Techniques To Visualize Occluded Graph Elements For 2.5d Map Editing, Kazuyuki Fujita, Daigo Hayashi, Kotaro Hara, Kazuki Takashima, Yoshifumi Kitamura
Techniques To Visualize Occluded Graph Elements For 2.5d Map Editing, Kazuyuki Fujita, Daigo Hayashi, Kotaro Hara, Kazuki Takashima, Yoshifumi Kitamura
Research Collection School Of Computing and Information Systems
We propose an interface with two novel techniques to visualize occluded graph nodes and edges that help the user edit map data with a 2.5D geographical structure (e.g., multi-floor indoor maps). We first design a visualization technique —Repel Signification— that employs micro-animation to signify the graph elements that are overlapping with each other (and potentially erroneous). We also design a technique that enables the user to edit the occluded components with Expansion Interaction, which simultaneously visualizes both in-floor and across-floor occluded connections between the map elements. The combination of the two methods would enable the map editors (non-experts) to effectively …
Understanding The Relation Between Repeat Developer Interactions And Bug Resolution Times In Large Open Source Ecosystems: A Multisystem Study, Subhajit Datta, Reshma Roychoudhuri, Subhashis Majumder
Understanding The Relation Between Repeat Developer Interactions And Bug Resolution Times In Large Open Source Ecosystems: A Multisystem Study, Subhajit Datta, Reshma Roychoudhuri, Subhashis Majumder
Research Collection School Of Computing and Information Systems
Large‐scale software systems are being increasingly built by distributed teams of developers who interact across geographies and time zones. Ensuring smooth knowledge transfer and the percolation of skills within and across such teams remain key challenges for organizations. Towards addressing this challenge, organizations often grapple with questions around whether and how repeat collaborations between members of a team relate to outcomes of important activities. In the context of this paper, the word ‘repeat interaction’ does not imply a greater number of interactions; it refers to repeat interaction between a pair of developers who have collaborated before. In this paper, we …
A Generalized Formal Semantic Framework For Smart Contracts, Jiao Jiao, Shang-Wei Lin, Jun Sun
A Generalized Formal Semantic Framework For Smart Contracts, Jiao Jiao, Shang-Wei Lin, Jun Sun
Research Collection School Of Computing and Information Systems
Smart contracts can be regarded as one of the most popular blockchain-based applications. The decentralized nature of the blockchain introduces vulnerabilities absent in other programs. Furthermore, it is very difficult, if not impossible, to patch a smart contract after it has been deployed. Therefore, smart contracts must be formally verified before they are deployed on the blockchain to avoid attacks exploiting these vulnerabilities. There is a recent surge of interest in analyzing and verifying smart contracts. While most of the existing works either focus on EVM bytecode or translate Solidity contracts into programs in intermediate languages for analysis and verification, …
Neural Network Pruning For Ecg Arrhythmia Classification, Isaac E. Labarge
Neural Network Pruning For Ecg Arrhythmia Classification, Isaac E. Labarge
Master's Theses
Convolutional Neural Networks (CNNs) are a widely accepted means of solving complex classification and detection problems in imaging and speech. However, problem complexity often leads to considerable increases in computation and parameter storage costs. Many successful attempts have been made in effectively reducing these overheads by pruning and compressing large CNNs with only a slight decline in model accuracy. In this study, two pruning methods are implemented and compared on the CIFAR-10 database and an ECG arrhythmia classification task. Each pruning method employs a pruning phase interleaved with a finetuning phase. It is shown that when performing the scale-factor pruning …
Google Summer Of Code: Student Motivations And Contributions, Jefferson O. Silva, Igor Scaliante Wiese, Daniel M. Germán, Christoph Treude, Marco Aurélio Gerosa, Igor Steinmacher
Google Summer Of Code: Student Motivations And Contributions, Jefferson O. Silva, Igor Scaliante Wiese, Daniel M. Germán, Christoph Treude, Marco Aurélio Gerosa, Igor Steinmacher
Research Collection School Of Computing and Information Systems
Several open source software (OSS) projects participate in engagement programs like Summers of Code expecting to foster newcomers’ onboarding and receive contributions. However, scant empirical evidence identifies why students join such programs. In this paper, we study the well-established Google Summer of Code (GSoC), which is a 3-month OSS engagement program that offers stipends and mentorship to students willing to contribute to OSS projects. We combined a survey (of students and mentors) and interviews (of students) to understand what motivates students to enter GSoC. Our results show that students enter GSoC for an enriching experience, and not necessarily to become …
How To And How Much? Teaching Ethics In An Interaction Design Course, Bimlesh Wadhwa, Eng Lieh Ouh, Benjamin Gan
How To And How Much? Teaching Ethics In An Interaction Design Course, Bimlesh Wadhwa, Eng Lieh Ouh, Benjamin Gan
Research Collection School Of Computing and Information Systems
How much is sufficient and how should one teach ethics in an Interaction Design curriculum in undergraduate computing program has been a point of dilemma for many HCI educators. We conducted a preliminary study using a mixed method to gather perception on ethics in our interaction design courses at two of the leading Singapore Universities. We answer three research questions specific to an undergraduate HCI course: Is there a need for ethics? Is there sufficient ethics coverage? and how to teach ethics? We surveyed 140 students and interviewed six teachers in two Singapore Universities. Our findings suggest that 92% of …
Maptransfer: Urban Air Quality Map Generation For Downscaled Sensor Deployments, Yun Cheng, Xiaoxi He, Zimu Zhou, Lothar Thiele
Maptransfer: Urban Air Quality Map Generation For Downscaled Sensor Deployments, Yun Cheng, Xiaoxi He, Zimu Zhou, Lothar Thiele
Research Collection School Of Computing and Information Systems
Dense deployments of commodity air quality sensors have proven effective to provide spatially-resolved information on urban air pollution in real-time. However, long-term operation of a dense sensor deployment incurs enormous maintenance expenses and efforts. A cost-effective alternative is to first collect measurements with an initial dense deployment and then rely on a small subset of sensors for air quality map generation. To avoid dramatic accuracy degradation in air quality maps generated using the downscaled sparse deployment, we design MapTransfer, an air quality map generation scheme which augments the current sensor measurements from the downscaled sparse deployment with appropriate historical data …
Voicecoach: Interactive Evidence-Based Training For Voice Modulation Skills In Public Speaking, Xingbo Wang, Haipeng Zeng, Yong Wang, Aoyu Wu, Zhida Sun, Xiaojuan Ma, Qu Huamin
Voicecoach: Interactive Evidence-Based Training For Voice Modulation Skills In Public Speaking, Xingbo Wang, Haipeng Zeng, Yong Wang, Aoyu Wu, Zhida Sun, Xiaojuan Ma, Qu Huamin
Research Collection School Of Computing and Information Systems
The modulation of voice properties, such as pitch, volume, and speed, is crucial for delivering a successful public speech. However, it is challenging to master different voice modulation skills. Though many guidelines are available, they are often not practical enough to be applied in different public speaking situations, especially for novice speakers. We present VoiceCoach, an interactive evidence-based approach to facilitate the effective training of voice modulation skills. Specifically, we have analyzed the voice modulation skills from 2623 high-quality speeches (i.e., TED Talks) and use them as the benchmark dataset. Given a voice input, VoiceCoach automatically recommends good voice modulation …
Dfseer: A Visual Analytics Approach To Facilitate Model Selection For Demand Forecasting, Dong Sun, Zezheng Feng, Yuanzhe Chen, Yong Wang, Jia Zeng, Mingxuan Yuan, Ting-Chuen Pong, Huamin Qu
Dfseer: A Visual Analytics Approach To Facilitate Model Selection For Demand Forecasting, Dong Sun, Zezheng Feng, Yuanzhe Chen, Yong Wang, Jia Zeng, Mingxuan Yuan, Ting-Chuen Pong, Huamin Qu
Research Collection School Of Computing and Information Systems
Selecting an appropriate model to forecast product demand is critical to the manufacturing industry. However, due to the data complexity, market uncertainty and users’ demanding requirements for the model, it is challenging for demand analysts to select a proper model. Although existing model selection methods can reduce the manual burden to some extent, they often fail to present model performance details on individual products and reveal the potential risk of the selected model. This paper presents DFSeer, an interactive visualization system to conduct reliable model selection for demand forecasting based on the products with similar historical demand. It supports model …
Sliver: Simulation-Based Logic Bomb Identification/Verification For Unmanned Aerial Vehicles, Jake M. Magness
Sliver: Simulation-Based Logic Bomb Identification/Verification For Unmanned Aerial Vehicles, Jake M. Magness
Theses and Dissertations
This research introduces SLIVer, a Simulation-based Logic Bomb Identification/Verification methodology, for finding logic bombs hidden within Unmanned Aerial Vehicle (UAV) autopilot code without having access to the device source code. Effectiveness is demonstrated by executing a series of test missions within a high-fidelity software-in-the-loop (SITL) simulator. In the event that a logic bomb is not detected, this methodology defines safe operating areas for UAVs to ensure to a high degree of confidence the UAV operates normally on the defined flight plan. SLIVer uses preplanned flight paths as the baseline input space, greatly reducing the input space that must be searched …
Treatment Effects Of Modafinil For Cocaine Use Disorders: A Retrospective Analysis Of Aggregated Clinical Trial Data From Three Cocaine Treatment Studies, Daniel Ruskin
Honors Scholar Theses
Approximately 913,000 individuals in the United States meet the diagnostic criteria for cocaine use disorder (CUD). The widespread usage of cocaine, along with the negative cardiac and neurological effects associated with the drug, has made cocaine one of the top three drugs associated with overdose deaths in the United States. This epidemic has brought cocaine dependency into the public spotlight and has prompted extensive research into treatment strategies. However, at the time of writing, no drugs have been approved by the United States Food and Drug Administration (FDA) for use in treating CUD. The purpose of this study is to …
Graph Classification With Kernels, Embeddings And Convolutional Neural Networks, Monica Golahalli Seenappa, Katerina Potika, Petros Potikas
Graph Classification With Kernels, Embeddings And Convolutional Neural Networks, Monica Golahalli Seenappa, Katerina Potika, Petros Potikas
Faculty Publications, Computer Science
In the graph classification problem, given is a family of graphs and a group of different categories, and we aim to classify all the graphs (of the family) into the given categories. Earlier approaches, such as graph kernels and graph embedding techniques have focused on extracting certain features by processing the entire graph. However, real world graphs are complex and noisy and these traditional approaches are computationally intensive. With the introduction of the deep learning framework, there have been numerous attempts to create more efficient classification approaches. We modify a kernel graph convolutional neural network approach, that extracts subgraphs (patches) …
Finding Music In Chaos: Designing And Composing With Virtual Instruments Inspired By Chaotic Equations, Landon P. Viator
Finding Music In Chaos: Designing And Composing With Virtual Instruments Inspired By Chaotic Equations, Landon P. Viator
LSU Doctoral Dissertations
Using chaos theory to design novel audio synthesis engines has been explored little in computer music. This could be because of the difficulty of obtaining harmonic tones or the likelihood of chaos-based synthesis engines to explode, which then requires re-instantiating of the engine to proceed with sound production. This process is not desirable when composing because of the time wasted fixing the synthesis engine instead of the composer being able to focus completely on the creative aspects of composition. One way to remedy these issues is to connect chaotic equations to individual parts of the synthesis engine instead of relying …
Automated Tool Support - Repairing Security Bugs In Mobile Applications, Larry Singleton
Automated Tool Support - Repairing Security Bugs In Mobile Applications, Larry Singleton
UNO Student Research and Creative Activity Fair
Cryptography is often a critical component in secure software systems. Cryptographic primitive misuses often cause several vulnerability issues. To secure data and communications in applications, developers often rely on cryptographic algorithms and APIs which provide confidentiality, integrity, and authentication based on solid mathematical foundations. While many advanced crypto algorithms are available to developers, the correct usage of these APIs is challenging. Turning mathematical equations in crypto algorithms into an application is a difficult task. A mistake in cryptographic implementations can subvert the security of the entire system. In this research, we present an automated approach for Finding and Repairing Bugs …
Black Box Analysis Of Android Malware Detectors, Guruswamy Nellaivadivelu, Fabio Di Troia, Mark Stamp
Black Box Analysis Of Android Malware Detectors, Guruswamy Nellaivadivelu, Fabio Di Troia, Mark Stamp
Faculty Publications, Computer Science
If a malware detector relies heavily on a feature that is obfuscated in a given malware sample, then the detector will likely fail to correctly classify the malware. In this research, we obfuscate selected features of known Android malware samples and determine whether these obfuscated samples can still be reliably detected. Using this approach, we discover which features are most significant for various sets of Android malware detectors, in effect, performing a black box analysis of these detectors. We find that there is a surprisingly high degree of variability among the key features used by popular malware detectors.
Incorporating Digital Ethics Throughout The Software Development Process, Michael Collins, Damian Gordon, Anna Becevel, William O'Mahony
Incorporating Digital Ethics Throughout The Software Development Process, Michael Collins, Damian Gordon, Anna Becevel, William O'Mahony
Conference papers
The media is reporting scandals associated with computer companies with increasing regularity; whether it is the misuse of user data, breach of privacy concerns, the use of biased artificial intelligence, or the problems of automated vehicles. Because of these complex issues, there is a growing need to equip computer science students with a deep appreciation of ethics, and to ensure that in the future they will develop computer systems that are ethically-based. One particularly useful strand of their education to incorporate ethics into is when teaching them about the formal approaches to developing computer systems.
There are a number of …
A Virtual Machine Introspection Based Multi-Service, Multi-Architecture, High-Interaction Honeypot For Iot Devices, Cory A. Nance
A Virtual Machine Introspection Based Multi-Service, Multi-Architecture, High-Interaction Honeypot For Iot Devices, Cory A. Nance
Masters Theses & Doctoral Dissertations
Internet of Things (IoT) devices are quickly growing in adoption. The use case for IoT devices runs the gamut from household applications (such as toasters, lighting, and thermostats) to medical, battlefield, or Industrial Control System (ICS) applications used in life or death situations. A disturbing trend is that for IoT devices is that they are not developed with security in mind. This lack of security has led to the creation of massive botnets that conduct nefarious acts. A clear understanding of the threat landscape IoT devices face is needed to address these security issues. One technique used to understand threats …
Iot-Hass: A Framework For Protecting Smart Home Environment, Tarig Mudawi
Iot-Hass: A Framework For Protecting Smart Home Environment, Tarig Mudawi
Masters Theses & Doctoral Dissertations
While many solutions have been proposed for smart home security, the problem that no single solution fully protects the smart home environment still exists. In this research we propose a security framework to protect the smart home environment. The proposed framework includes three engines that complement each other to protect the smart home IoT devices. The first engine is an IDS/IPS module that monitors all traffic in the home network and then detects, alerts users, and/or blocks packets using anomaly-based detection. The second engine works as a device management module that scans and verifies IoT devices in the home network, …
Network Traffic Analysis Framework For Cyber Threat Detection, Meshesha K. Cherie
Network Traffic Analysis Framework For Cyber Threat Detection, Meshesha K. Cherie
Masters Theses & Doctoral Dissertations
The growing sophistication of attacks and newly emerging cyber threats requires advanced cyber threat detection systems. Although there are several cyber threat detection tools in use, cyber threats and data breaches continue to rise. This research is intended to improve the cyber threat detection approach by developing a cyber threat detection framework using two complementary technologies, search engine and machine learning, combining artificial intelligence and classical technologies.
In this design science research, several artifacts such as a custom search engine library, a machine learning-based engine and different algorithms have been developed to build a new cyber threat detection framework based …
Heartquake: Accurate Low-Cost Non-Invasive Ecg Monitoring Using Bed-Mounted Geophones, Jaeyeon Park, Hyeon Cho, Rajesh Krishna Balan, Jeonggil Ko
Heartquake: Accurate Low-Cost Non-Invasive Ecg Monitoring Using Bed-Mounted Geophones, Jaeyeon Park, Hyeon Cho, Rajesh Krishna Balan, Jeonggil Ko
Research Collection School Of Computing and Information Systems
This work presents HeartQuake, a low cost, accurate, non-intrusive, geophone-based sensing system for extracting accurate electrocardiogram (ECG) patterns using heartbeat vibrations that penetrate through a bed mattress. In HeartQuake, cardiac activity-originated vibration patterns are captured on a geophone and sent to a server, where the data is filtered to remove the sensor's internal noise and passed on to a bidirectional long short term memory (Bi-LSTM) deep learning model for ECG waveform estimation. To the best of our knowledge, this is the first solution that can non-intrusively provide accurate ECG waveform characteristics instead of more basic abstract features such as the …
Ifix: Fixing Concurrency Bugs While They Are Introduced, Zan Wang, Haichi Wang, Shuang Liu, Jun Sun, Haoyu Wang, Junjie Chen
Ifix: Fixing Concurrency Bugs While They Are Introduced, Zan Wang, Haichi Wang, Shuang Liu, Jun Sun, Haoyu Wang, Junjie Chen
Research Collection School Of Computing and Information Systems
Concurrency bugs are notoriously hard to identify and fix. A systematic way of avoiding concurrency bugs is to design and implement a locking policy that consistently guards all shared variables. Concurrency bugs thus can be viewed as the result of an illy-designed or poorly implemented locking policy. The trouble is that the locking policy is often not documented, which makes debugging concurrency bugs clueless. We argue that it is too late to debug concurrency bugs after programming is done and we instead detect and fix them while they are being implemented. In this work, we propose an approach named IFIX …
An Empirical Study On Correlation Between Coverage And Robustness For Deep Neural Networks, Yizhen Dong, Peixin Zhang, Jingyi Wang, Shuang Liu, Jun Sun, Jianye Hao, Xinyu Wang, Li Wang, Jinsong Dong, Ting Dai
An Empirical Study On Correlation Between Coverage And Robustness For Deep Neural Networks, Yizhen Dong, Peixin Zhang, Jingyi Wang, Shuang Liu, Jun Sun, Jianye Hao, Xinyu Wang, Li Wang, Jinsong Dong, Ting Dai
Research Collection School Of Computing and Information Systems
Deep neural networks (DNN) are increasingly applied in safety-critical systems, e.g., for face recognition, autonomous car control and malware detection. It is also shown that DNNs are subject to attacks such as adversarial perturbation and thus must be properly tested. Many coverage criteria for DNN since have been proposed, inspired by the success of code coverage criteria for software programs. The expectation is that if a DNN is well tested (and retrained) according to such coverage criteria, it is more likely to be robust. In this work, we conduct an empirical study to evaluate the relationship between coverage, robustness and …
Learning Fault Models Of Cyber Physical Systems, Teck Ping Khoo, Jun Sun, Sudipta Chattopadhyay
Learning Fault Models Of Cyber Physical Systems, Teck Ping Khoo, Jun Sun, Sudipta Chattopadhyay
Research Collection School Of Computing and Information Systems
Cyber Physical Systems (CPSs) comprise sensors and actuators which interact with the physical environment over a computer network to achieve some control objective. Bugs in CPSs can have severe consequences as CPSs are increasingly deployed in safety-critical applications. Debugging CPSs is therefore an important real world problem. Traces from a CPS can be lengthy and are usually linked to different parts of the system, making debugging CPSs a complex and time-consuming undertaking. It is challenging to isolate a component without running the whole CPS. In this work, we propose a model-based approach to debugging a CPS. For each CPS property, …
Capacitor-Based Activity Sensing For Kinetic-Powered Wearable Iots, Guohao Lan, Dong Ma, Weitao Xu, Mahbub Hassan, Wen Hu
Capacitor-Based Activity Sensing For Kinetic-Powered Wearable Iots, Guohao Lan, Dong Ma, Weitao Xu, Mahbub Hassan, Wen Hu
Research Collection School Of Computing and Information Systems
We propose the use of the conventional energy storage component, i.e., capacitor, in the kinetic-powered wearable IoTs as the sensor to detect human activities. Since activities accumulate energy in the capacitor at different rates, the charging rate of the capacitor can be used to detect the activities. The key advantage of the proposed capacitor-based activity sensing mechanism, called CapSense, is that it obviates the need for sampling the motion signal at a high rate, and thus, significantly reduces power consumption of the wearable device. The challenge we face is that capacitors are inherently non-linear energy accumulators, which leads to significant …