Deeprobot: A Hybrid Deep Neural Network Model For Social Bot Detection Based On User Profile Data,
2022
Zayed University
Deeprobot: A Hybrid Deep Neural Network Model For Social Bot Detection Based On User Profile Data, Kadhim Hayawi, Sujith Mathew, Neethu Venugopal, Mohammad M. Masud, Pin Han Ho
All Works
Use of online social networks (OSNs) undoubtedly brings the world closer. OSNs like Twitter provide a space for expressing one’s opinions in a public platform. This great potential is misused by the creation of bot accounts, which spread fake news and manipulate opinions. Hence, distinguishing genuine human accounts from bot accounts has become a pressing issue for researchers. In this paper, we propose a framework based on deep learning to classify Twitter accounts as either ‘human’ or ‘bot.’ We use the information from user profile metadata of the Twitter account like description, follower count and tweet count. We name ...
Opportunities And Challenges In Code Search Tools,
2022
Singapore Management University
Opportunities And Challenges In Code Search Tools, Chao Liu, Xin Xia, David Lo, Cuiying Gao, Xiaohu Yang, John Grundy
Research Collection School Of Computing and Information Systems
Code search is a core software engineering task. Effective code search tools can help developers substantially improve their software development efficiency and effectiveness. In recent years, many code search studies have leveraged different techniques, such as deep learning and information retrieval approaches, to retrieve expected code from a large-scale codebase. However, there is a lack of a comprehensive comparative summary of existing code search approaches. To understand the research trends in existing code search studies, we systematically reviewed 81 relevant studies. We investigated the publication trends of code search studies, analyzed key components, such as codebase, query, and modeling technique ...
Quantum Key-Length Extension,
2022
Georgia Institute of Technology
Quantum Key-Length Extension, Joseph Jaeger, Fang Song, Stefano Tessaro
Computer Science Faculty Publications and Presentations
Should quantum computers become available, they will reduce the effective key length of basic secret-key primitives, such as blockciphers. To address this we will either need to use blockciphers with inherently longer keys or develop key-length extension techniques to amplify the security of a blockcipher to use longer keys.
We consider the latter approach and revisit the FX and double encryption constructions. Classically, FX was proven to be a secure key-length extension technique, while double encryption fails to be more secure than single encryption due to a meet-in-the-middle attack. In this work we provide positive results, with concrete and tight ...
Which Neural Network Makes More Explainable Decisions? An Approach Towards Measuring Explainability,
2022
Singapore Management University
Which Neural Network Makes More Explainable Decisions? An Approach Towards Measuring Explainability, Mengdi Zhang, Jun Sun, Jingyi Wang
Research Collection School Of Computing and Information Systems
Neural networks are getting increasingly popular thanks to their exceptional performance in solving many real-world problems. At the same time, they are shown to be vulnerable to attacks, difficult to debug and subject to fairness issues. To improve people’s trust in the technology, it is often necessary to provide some human-understandable explanation of neural networks’ decisions, e.g., why is that my loan application is rejected whereas hers is approved? That is, the stakeholder would be interested to minimize the chances of not being able to explain the decision consistently and would like to know how often and how ...
Addressing Ethical Issues In The Design Of Smart Home Technology For Older Adults And People With Disabilities.,
2022
Technological University Dublin
Addressing Ethical Issues In The Design Of Smart Home Technology For Older Adults And People With Disabilities., Jonathan Turner, Dympna O'Sullivan, Damian Gordon, Yannis Stavrakakis, Brian Keegan, Emma Murphy
Articles
Unique ethical, privacy and safety implications arise for people who are reliant on home-based smart technology due to health conditions or disabilities. In this paper we highlight a need for a reflective, inclusive ethical framework that encompasses the life cycle of smart home technology. We present key ethical considerations for smart home technology for older adults and people with disabilities and argue for ethical frameworks which combine these key considerations with existing models of design and development.
Co-Design To Support Engagement In Activities Of Daily Living And Meaningful Activities For People Living With Dementia,
2022
Dundalk Institute of Technology
Co-Design To Support Engagement In Activities Of Daily Living And Meaningful Activities For People Living With Dementia, Michael Wilson, Julie Doyle, Ann Marron, Jonathan Turner, Ciaran Nugent, Dympna O'Sullivan
Articles
Dementia is a chronic and progressive neurodegenerative illness, which can lead to significant difficulties in a person’s capacity to perform activities of daily living and engage in meaningful activities. The Smart Dementia Care project aims to establish an understanding of how best to design digital tools that persons with dementia and their carers will find useful and usable for care planning and goal setting. This paper discusses the first phase of this project and describes how co-design is being used to support engagement in activities of daily living and meaningful activities for people living with the early stages of ...
A Mean-Field Markov Decision Process Model For Spatial Temporal Subsidies In Ride-Sourcing Markets,
2022
Singapore Management University
A Mean-Field Markov Decision Process Model For Spatial Temporal Subsidies In Ride-Sourcing Markets, Zheng Zhu, Jintao Ke, Hai Wang
Research Collection School Of Computing and Information Systems
Ride-sourcing services are increasingly popular because of their ability to accommodate on-demand travel needs. A critical issue faced by ride-sourcing platforms is the supply-demand imbalance, as a result of which drivers may spend substantial time on idle cruising and picking up remote passengers. Some platforms attempt to mitigate the imbalance by providing relocation guidance for idle drivers who may have their own self-relocation strategies and decline to follow the suggestions. Platforms then seek to induce drivers to system-desirable locations by offering them subsidies. This paper proposes a mean-field Markov decision process (MF-MDP) model to depict the dynamics in ride-sourcing markets ...
Time Dependent Orienteering Problem With Time Windows And Service Time Dependent Profits,
2022
Singapore Management University
Time Dependent Orienteering Problem With Time Windows And Service Time Dependent Profits, M. Khodadadian, A. Divsalar, C. Verbeeck, Aldy Gunawan, P. Vansteenwegen
Research Collection School Of Computing and Information Systems
This paper addresses the time dependent orienteering problem with time windows and service time dependent profits (TDOPTW-STP). In the TDOPTW-STP, each vertex is assigned a minimum and a maximum service time and the profit collected at each vertex increases linearly with the service time. The goal is to maximize the total collected profit by determining a subset of vertices to be visited and assigning appropriate service time to each vertex, considering a given time budget and time windows. Moreover, travel times are dependent of the departure times. To solve this problem, a mixed integer linear model is formulated and a ...
Are You Really Muted?: A Privacy Analysis Of Mute Buttons In Video Conferencing Apps,
2022
University of Wisconsin - Madison
Are You Really Muted?: A Privacy Analysis Of Mute Buttons In Video Conferencing Apps, Yucheng Yang, Jack West, George K. Thiruvathukal, Neil Klingensmith, Kassem Fawaz
Computer Science: Faculty Publications and Other Works
In the post-pandemic era, video conferencing apps (VCAs) have converted previously private spaces — bedrooms, living rooms, and kitchens — into semi-public extensions of the office. And for the most part, users have accepted these apps in their personal space, without much thought about the permission models that govern the use of their personal data during meetings. While access to a device’s video camera is carefully controlled, little has been done to ensure the same level of privacy for accessing the microphone. In this work, we ask the question: what happens to the microphone data when a user clicks the mute ...
Digbug—Pre/Post-Processing Operator Selection For Accurate Bug Localization,
2022
Singapore Management University
Digbug—Pre/Post-Processing Operator Selection For Accurate Bug Localization, Kisub Kim, Sankalp Ghatpande, Kui Liu, Anil Koyuncu, Dongsun Kim, Tegawendé F. Bissyande, Jacques Klein, Yves Le Traon
Research Collection School Of Computing and Information Systems
Bug localization is a recurrent maintenance task in software development. It aims at identifying relevant code locations (e.g., code files) that must be inspected to fix bugs. When such bugs are reported by users, the localization process become often overwhelming as it is mostly a manual task due to incomplete and informal information (written in natural languages) available in bug reports. The research community has then invested in automated approaches, notably using Information Retrieval techniques. Unfortunately, reported performance in the literature is still limited for practical usage. Our key observation, after empirically investigating a large dataset of bug reports ...
Irrelevant Pixels Are Everywhere: Find And Exclude Them For More Efficient Computer Vision,
2022
Purdue University
Irrelevant Pixels Are Everywhere: Find And Exclude Them For More Efficient Computer Vision, Caleb Tung, Abhinav Goel, Xiao Hu, Nick Eliopoulos, Emmanuel Amobi, George K. Thiruvathukal, Vipin Chaudhary, Yung-Hisang Lu
Computer Science: Faculty Publications and Other Works
Computer vision is often performed using Convolutional Neural Networks (CNNs). CNNs are compute-intensive and challenging to deploy on power-constrained systems such as mobile and Internet-of-Things (IoT) devices. CNNs are compute-intensive because they indiscriminately compute many features on all pixels of the input image. We observe that, given a computer vision task, images often contain pixels that are irrelevant to the task. For example, if the task is looking for cars, pixels in the sky are not very useful. Therefore, we propose that a CNN be modified to only operate on relevant pixels to save computation and energy. We propose a ...
Single-Pass Inline Pipeline 3d Reconstruction Using Depth Camera Array,
2022
University of Nebraska-Lincoln
Single-Pass Inline Pipeline 3d Reconstruction Using Depth Camera Array, Zhexiong Shang, Zhigang Shen
Faculty Publications in Construction Engineering & Management
A novel inline inspection (ILI) approach using depth cameras array (DCA) is introduced to create high-fidelity, dense 3D pipeline models. A new camera calibration method is introduced to register the color and the depth information of the cameras into a unified pipe model. By incorporating the calibration outcomes into a robust camera motion estimation approach, dense and complete 3D pipe surface reconstruction is achieved by using only the inline image data collected by a self-powered ILI rover in a single pass through a straight pipeline. The outcomes of the laboratory experiments demonstrate one-millimeter geometrical accuracy and 0.1-pixel photometric accuracy ...
Decomposing Generation Networks With Structure Prediction For Recipe Generation,
2022
Singapore Management University
Decomposing Generation Networks With Structure Prediction For Recipe Generation, Hao Wang, Guosheng Lin, Steven C. H. Hoi, Chunyan Miao
Research Collection School Of Computing and Information Systems
Recipe generation from food images and ingredients is a challenging task, which requires the interpretation of the information from another modality. Different from the image captioning task, where the captions usually have one sentence, cooking instructions contain multiple sentences and have obvious structures. To help the model capture the recipe structure and avoid missing some cooking details, we propose a novel framework: Decomposing Generation Networks (DGN) with structure prediction, to get more structured and complete recipe generation outputs. Specifically, we split each cooking instruction into several phases, and assign different sub-generators to each phase. Our approach includes two novel ideas ...
Meaningful Activity Replacement Recommendations In Dementia,
2022
Technological University Dublin
Meaningful Activity Replacement Recommendations In Dementia, Jonathan Turner, Michael Wilson, Ciaran Nugent, Damon Berry, Julie Doyle, Dympna O'Sullivan
Articles
Exercise of meaningful activities is important for people living with dementia, both for quality of life and to maintain the necessary basic activities of daily living. A method is proposed for recommendation of replacements for lost meaningful activities that accounts for the need to maintain activities of daily living.
Challenges In Migrating Imperative Deep Learning Programs To Graph Execution: An Empirical Study,
2022
CUNY Graduate Center
Challenges In Migrating Imperative Deep Learning Programs To Graph Execution: An Empirical Study, Tatiana Castro Vélez, Raffi T. Khatchadourian, Mehdi Bagherzadeh, Anita Raja
Publications and Research
Efficiency is essential to support responsiveness w.r.t. ever-growing datasets, especially for Deep Learning (DL) systems. DL frameworks have traditionally embraced deferred execution-style DL code that supports symbolic, graph-based Deep Neural Network (DNN) computation. While scalable, such development tends to produce DL code that is error-prone, non-intuitive, and difficult to debug. Consequently, more natural, less error-prone imperative DL frameworks encouraging eager execution have emerged at the expense of run-time performance. While hybrid approaches aim for the "best of both worlds," the challenges in applying them in the real world are largely unknown. We conduct a data-driven analysis of challenges ...
A Tool For Rejuvenating Feature Logging Levels Via Git Histories And Degree Of Interest,
2022
CUNY Graduate Center
A Tool For Rejuvenating Feature Logging Levels Via Git Histories And Degree Of Interest, Yiming Tang, Allan Spektor, Raffi T. Khatchadourian, Mehdi Bagherzadeh
Publications and Research
Logging is a significant programming practice. Due to the highly transactional nature of modern software applications, a massive amount of logs are generated every day, which may overwhelm developers. Logging information overload can be dangerous to software applications. Using log levels, developers can print the useful information while hiding the verbose logs during software runtime. As software evolves, the log levels of logging statements associated with the surrounding software feature implementation may also need to be altered. Maintaining log levels necessitates a significant amount of manual effort. In this paper, we demonstrate an automated approach that can rejuvenate feature log ...
Editorial Board,
2022
Karbala International Journal of Modern Science
Simulating Photo-Disintegration Of 137cs Radioactive Waste Using Various Energies Of Gamma Photons,
2022
Ph.D. student, Department of physics, collage of science, University of Baghdad.
Simulating Photo-Disintegration Of 137cs Radioactive Waste Using Various Energies Of Gamma Photons, Hassanain H. Alkazzaz, Asia H. Al-Mashhadani, Kamal H. Lateef
Karbala International Journal of Modern Science
In this study, the possibility of using gamma-ray in photo-disintegration method was examined so that it can be used in the remediation of 137Cs radionuclides waste materials by nuclear transmutation to convert long-lived nuclides to other isotopes nuclides, which are shorter half-life (or stable), by different photo-nuclear reaction channels (γ,n), (γ,2n), (γ,p), (γ, a), (γ,d). A simulation code has been written using MATLAB for conducting calculations of reduction and residual. The results showed that gamma-ray fluxes below 1017 [cm-2 s-1] are not adequate to perform effective incinera-tion of 137Cs, and as for gamma flux of 1018 ...
Engineering Of A Multi-Epitope Subunit Vaccine Against Sasrs-Cov-2 Through The Viroinformatic Approach,
2022
Virology and Immunology, Division of Microbiology, Faculty of Veterinary Medicine, Universitas Airlangga, Surabaya, Indonesia.
Engineering Of A Multi-Epitope Subunit Vaccine Against Sasrs-Cov-2 Through The Viroinformatic Approach, Aamir Shehzada, Christijogo Sumartono, Jusak Nugraha, Helen Susilowatid, Andi Yasmin Wijayab, Hafiz Ishfaq Ahmad, Wiwiek Tyasningsih, Fedik Abdul Rantam
Karbala International Journal of Modern Science
The COVID-19 outbreak has infected millions of people worldwide, but no vaccine has been discovered to combat it efficiently. This research aims to design a multi-epitope vaccine using highly efficient B- and T-cell epitopes from the SARS-CoV-2 Surabaya isolate through a viroinformatic approach. First, the putative epitopes were linked together to develop tertiary structures and then docked with toll-like receptor 4 (TLR-4) that demonstrated a robust interaction with a low eigenvalue of 4.816138 e-06. Furthermore, the structure's high immunogenic response was observed and successfully cloned into the expression vector pET28a (+). This implies that the designed vaccine can prove ...
Understanding The Influence Of Perceptual Noise On Visual Flanker Effects Through Bayesian Model Fitting,
2022
University of Birmingham
Understanding The Influence Of Perceptual Noise On Visual Flanker Effects Through Bayesian Model Fitting, Jordan Deakin, Dietmar Heinke
MODVIS Workshop
No abstract provided.