Compositional Coding For Collaborative Filtering,
2019
Singapore Management University
Compositional Coding For Collaborative Filtering, Chenghao Liu, Tao Lu, Xin Wang, Zhiyong Cheng, Jianling Sun, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
Efficiency is crucial to the online recommender systems, especially for the ones which needs to deal with tens of millions of users and items. Because representing users and items as binary vectors for Collaborative Filtering (CF) can achieve fast user-item affinity computation in the Hamming space, in recent years, we have witnessed an emerging research effort in exploiting binary hashing techniques for CF methods. However, CF with binary codes naturally suffers from low accuracy due to limited representation capability in each bit, which impedes it from modeling complex structure of the data. In this work, we attempt to improve the …
Redpc: A Residual Error-Based Density Peak Clustering Algorithm,
2019
Singapore Management University
Redpc: A Residual Error-Based Density Peak Clustering Algorithm, Milan Parmar, Di Wang, Xiaofeng Zhang, Ah-Hwee Tan, Chunyan Miao, You Zhou
Research Collection School Of Computing and Information Systems
The density peak clustering (DPC) algorithm was designed to identify arbitrary-shaped clusters by finding density peaks in the underlying dataset. Due to its aptitudes of relatively low computational complexity and a small number of control parameters in use, DPC soon became widely adopted. However, because DPC takes the entire data space into consideration during the computation of local density, which is then used to generate a decision graph for the identification of cluster centroids, DPC may face difficulty in differentiating overlapping clusters and in dealing with low-density data points. In this paper, we propose a residual error-based density peak clustering …
Towards Understanding Android System Vulnerabilities: Techniques And Insights,
2019
Singapore Management University
Towards Understanding Android System Vulnerabilities: Techniques And Insights, Daoyuan Wu, Debin Gao, Eric K. T. Cheng, Yichen Cao, Jintao Jiang, Robert H. Deng
Research Collection School Of Computing and Information Systems
As a common platform for pervasive devices, Android has been targeted by numerous attacks that exploit vulnerabilities in its apps and the operating system. Compared to app vulnerabilities, systemlevel vulnerabilities in Android, however, were much less explored in the literature. In this paper, we perform the first systematic study of Android system vulnerabilities by comprehensively analyzing all 2,179 vulnerabilities on the Android Security Bulletin program over about three years since its initiation in August 2015. To this end, we propose an automatic analysis framework, upon a hierarchical database structure, to crawl, parse, clean, and analyze vulnerability reports and their publicly …
Semantic Patches For Java Program Transformation,
2019
Singapore Management University
Semantic Patches For Java Program Transformation, Hong Jin Kang, Ferdian Thung, Julia Lawall, Gilles Muller, Lingxiao Jiang, David Lo
Research Collection School Of Computing and Information Systems
Developing software often requires code changes that are widespread and applied to multiple locations.There are tools for Java that allow developers to specify patterns for program matching and source-to-source transformation. However, to our knowledge, none allows for transforming code based on its control-flow context. We prototype Coccinelle4J, an extension to Coccinelle, which is a program transformation tool designed for widespread changes in C code, in order to work on Java source code. We adapt Coccinelle to be able to apply scripts written in the Semantic Patch Language (SmPL), a language provided by Coccinelle, to Java source files. As a case …
The Impact Of Changes Mislabeled By Szz On Just-In-Time Defect Prediction,
2019
Singapore Management University
The Impact Of Changes Mislabeled By Szz On Just-In-Time Defect Prediction, Yuanrui Fan, Xin Xia, Daniel A. Costa, David Lo, Ahmed E. Hassan, Shanping Li
Research Collection School Of Computing and Information Systems
Just-in-Time (JIT) defect prediction—a technique which aims to predict bugs at change level—has been paid more attention. JIT defect prediction leverages the SZZ approach to identify bug-introducing changes. Recently, researchers found that the performance of SZZ (including its variants) is impacted by a large amount of noise. SZZ may considerably mislabel changes that are used to train a JIT defect prediction model, and thus impact the prediction accuracy. In this paper, we investigate the impact of the mislabeled changes by different SZZ variants on the performance and interpretation of JIT defect prediction models. We analyze four SZZ variants (i.e., B-SZZ, …
Resilient Collaborative Intelligence For Adversarial Iot Environments,
2019
Singapore Management University
Resilient Collaborative Intelligence For Adversarial Iot Environments, Dulanga Weerakoon, Kasthuri Jayarajah, Randy Tandriansyah, Archan Misra
Research Collection School Of Computing and Information Systems
Many IoT networks, including for battlefield deployments, involve the deployment of resource-constrained sensors with varying degrees of redundancy/overlap (i.e., their data streams possess significant spatiotemporal correlation). Collaborative intelligence, whereby individual nodes adjust their inferencing pipelines to incorporate such correlated observations from other nodes, can improve both inferencing accuracy and performance metrics (such as latency and energy overheads). Using realworld data from a multicamera deployment, we first demonstrate the significant performance gains (up to 14% increase in accuracy) from such collaborative intelligence, achieved through two different approaches: (a) one involving statistical fusion of outputs from different nodes, and (b) another involving …
Semantic Patches For Java Program Transformation (Artifact),
2019
Singapore Management University
Semantic Patches For Java Program Transformation (Artifact), Hong Jin Kang, Thung Ferdian, Julia Lawall, Gilles Muller, Lingxiao Jiang, David Lo
Research Collection School Of Computing and Information Systems
The program transformation tool Coccinelle is designed for making changes that is required in many locations within a software project. It has been shown to be useful for C code and has been been adopted for use in the Linux kernel by many developers. Over 6000 commits mentioning the use of Coccinelle have been made in the Linux kernel. Our artifact, Coccinelle4J, is an extension to Coccinelle in order for it to apply program transformations to Java source code. This artifact accompanies our experience report “Semantic Patches for Java Program Transformation”, in which we show a case study of applying …
Deephunter: A Coverage-Guided Fuzz Testing Framework For Deep Neural Networks,
2019
Singapore Management University
Deephunter: A Coverage-Guided Fuzz Testing Framework For Deep Neural Networks, Xiaofei Xie, Lei Ma, Felix Juefei-Xu, Minhui Xue, Hongxu Chen, Yang Liu, Jianjun Zhao, Bo Li, Jianxiong Yin, Simon See
Research Collection School Of Computing and Information Systems
The past decade has seen the great potential of applying deep neural network (DNN) based software to safety-critical scenarios, such as autonomous driving. Similar to traditional software, DNNs could exhibit incorrect behaviors, caused by hidden defects, leading to severe accidents and losses. In this paper, we propose DeepHunter, a coverage-guided fuzz testing framework for detecting potential defects of general-purpose DNNs. To this end, we first propose a metamorphic mutation strategy to generate new semantically preserved tests, and leverage multiple extensible coverage criteria as feedback to guide the test generation. We further propose a seed selection strategy that combines both diversity-based …
Toward Human-Like Summaries Generated From Heterogeneous Software Artefacts,
2019
Singapore Management University
Toward Human-Like Summaries Generated From Heterogeneous Software Artefacts, Mahfouth Alghamdi, Christoph Treude, Markus Wagner
Research Collection School Of Computing and Information Systems
Automatic text summarisation has drawn considerable interest in the field of software engineering. It can improve the efficiency of software developers, enhance the quality of products, and ensure timely delivery. In this paper, we present our initial work towards automatically generating human-like multi-document summaries from heterogeneous software artefacts. Our analysis of the text properties of 545 human-written summaries from 15 software engineering projects will ultimately guide heuristics searches in the automatic generation of human-like summaries.
Evaluating The Readability Of Force Directed Graph Layouts: A Deep Learning Approach,
2019
Singapore Management University
Evaluating The Readability Of Force Directed Graph Layouts: A Deep Learning Approach, Hammad Haleem, Yong Wang, Abishek Puri, Sahil Wadhwa, Huamin Qu
Research Collection School Of Computing and Information Systems
Existing graph layout algorithms are usually not able to optimize all the aesthetic properties desired in a graph layout. To evaluate how well the desired visual features are reflected in a graph layout, many readability metrics have been proposed in the past decades. However, the calculation of these readability metrics often requires access to the node and edge coordinates and is usually computationally inefficient, especially for dense graphs. Importantly, when the node and edge coordinates are not accessible, it becomes impossible to evaluate the graph layouts quantitatively. In this paper, we present a novel deep learning-based approach to evaluate the …
High-Performance Computing Frameworks For Large-Scale Genome Assembly,
2019
Louisiana State University and Agricultural and Mechanical College
High-Performance Computing Frameworks For Large-Scale Genome Assembly, Sayan Goswami
LSU Doctoral Dissertations
Genome sequencing technology has witnessed tremendous progress in terms of throughput and cost per base pair, resulting in an explosion in the size of data. Typical de Bruijn graph-based assembly tools demand a lot of processing power and memory and cannot assemble big datasets unless running on a scaled-up server with terabytes of RAMs or scaled-out cluster with several dozens of nodes. In the first part of this work, we present a distributed next-generation sequence (NGS) assembler called Lazer, that achieves both scalability and memory efficiency by using partitioned de Bruijn graphs. By enhancing the memory-to-disk swapping and reducing the …
Decentralise Me,
2019
Singapore Management University
Decentralise Me, Paul Robert Griffin
MITB Thought Leadership Series
If you are in need of a reminder of the levels of hype surrounding blockchain, then look no further than Japan’s J-Pop sensation Kasotsuka Shojo, otherwise known as the Virtual Currency Girls who, with their debut track “The Moon and Cryptocurrencies and Me”, aim to educate fans about cryptocurrencies in an entertaining way.
Forecasting Building Energy Consumption With Deep Learning: A Sequence To Sequence Approach,
2019
Western University
Forecasting Building Energy Consumption With Deep Learning: A Sequence To Sequence Approach, Ljubisa Sehovac, Cornelius Nesen, Katarina Grolinger
Electrical and Computer Engineering Publications
Energy Consumption has been continuously increasing due to the rapid expansion of high-density cities, and growth in the industrial and commercial sectors. To reduce the negative impact on the environment and improve sustainability, it is crucial to efficiently manage energy consumption. Internet of Things (IoT) devices, including widely used smart meters, have created possibilities for energy monitoring as well as for sensor based energy forecasting. Machine learning algorithms commonly used for energy forecasting such as feedforward neural networks are not well-suited for interpreting the time dimensionality of a signal. Consequently, this paper uses Recurrent Neural Networks (RNN) to capture time …
Enhancing The Study Of Art History Utilizing Computational Thinking: Focus, Abstraction In Art (Modern),
2019
CUNY New York City College of Technology
Enhancing The Study Of Art History Utilizing Computational Thinking: Focus, Abstraction In Art (Modern), Douglas L. Moody, Sandra Cheng
Open Educational Resources
No abstract provided.
Keylime,
2019
California Polytechnic State University, San Luis Obispo
Keylime, Eli William Partker
Computer Engineering
Josh, Matt and I knew we wanted to develop a mobile app for our senior project because that is what we found ourselves to be most passionate about during our time here at Cal Poly. We started to think of problems we wanted to solve using an application and we came up with a couple ideas but chose to expand on one. Students come to Cal Poly every year new to the area and the food options San Luis Obispo provides. Many of the restaurants in SLO offer a variety of deals to the community and most of them to …
Reach - A Community Service Application,
2019
California Polytechnic State University, San Luis Obispo
Reach - A Community Service Application, Samuel Noel Magana
Computer Engineering
Communities are familiar threads that unite people through several shared attributes and interests. These commonalities are the core elements that link and bond us together. Many of us are part of multiple communities, moving in and out of them depending on our needs. These common threads allow us to support and advocate for each other when facing a common threat or difficult situation. Healthy and vibrant communities are fundamental to the operation of our society. These interactions within our communities define the way we as individuals interact with each other, and society at large. Being part of a community helps …
Robot Reporter Website Development,
2019
California Polytechnic State University, San Luis Obispo
Robot Reporter Website Development, Samuel Verkruyse
Computer Engineering
The Robot Reporter Website Development project created a front end interface for interacting with news stories generated by the Robot Reporter script that was originally developed for the Digital Democracy institute at Cal Poly. Various graphs, videos, and other interesting content is displayed to the user in order to create an automated news website focusing on activity in state legislatures.
Radish: A Cross Platform Meal Prepping App For Beginner Weightlifters,
2019
California Polytechnic State University, San Luis Obispo
Radish: A Cross Platform Meal Prepping App For Beginner Weightlifters, Spoorthy S. Vemula, Tanay Gottigundala, Cory Baxes
Computer Science and Software Engineering
With the increasing ease of access and decreasing price of most food, obesity rates in the developing world have risen dramatically in recent years. As of March 23rd, 2019, obesity rates had reached 39.6%, a 6% increase in just 8 years. Research has shown that people with obesity have a significantly increased risk of heart disease, stroke, type 2 diabetes, and certain cancers, among other life-threatening diseases. In addition, 42% of people who begin weightlifting quit because it’s too difficult to follow a diet or workout regimen.
We created Radish in an attempt to tackle these problems. Radish makes it …
Snoring: A Noise Defect Prediction Datasets,
2019
California Polytechnic State University, San Luis Obispo
Snoring: A Noise Defect Prediction Datasets, Aalok Ahluwalia
Master's Theses
Defect prediction aims at identifying software artifacts that are likely to exhibit a defect. The main purpose of defect prediction is to reduce the cost of testing and code review, by letting developers focus on specific artifacts. Several researchers have worked on improving the accuracy of defect estimation models using techniques such as tuning, re-balancing, or feature selection. Ultimately, the reliability of a prediction model depends on the quality of the dataset. Therefore effort has been spent in identifying sources of noise in the datasets, and how to deal with them, including defect misclassification and defect origin. A key component …
Accessible And Responsive Website Design For Cal Poly Dbs Marine Education Program,
2019
California Polytechnic State University, San Luis Obispo
Accessible And Responsive Website Design For Cal Poly Dbs Marine Education Program, Charles W. Alexander
Computer Engineering
In this project, I demonstrate how accessible and responsive designs are followed in order to implement a modern, multi-page website which both adapts to the size of the screen as well as has the logical, semantic structure needed for accessible technologies to accurately use the site. This website is designed for a marine education program, Dive Beneath the Surface, which hosts live streams of scientific divers as they interact in real time with students many miles away. Although this site will not be the streaming platform, it needs to host a repository of videos and lessons for those students and …
