OS and Networks Commons^™

Pruning Meta-Trained Networks For On-Device Adaptation, Dawei Gao, Xiaoxi He, Zimu Zhou, Yongxin Tong, Lothar Thiele

Research Collection School Of Computing and Information Systems

Adapting neural networks to unseen tasks with few training samples on resource-constrained devices benefits various Internet-of-Things applications. Such neural networks should learn the new tasks in few shots and be compact in size. Meta-learning enables few-shot learning, yet the meta-trained networks can be overparameterised. However, naive combination of standard compression techniques like network pruning with meta-learning jeopardises the ability for fast adaptation. In this work, we propose adaptation-aware network pruning (ANP), a novel pruning scheme that works with existing meta-learning methods for a compact network capable of fast adaptation. ANP uses weight importance metric that is based on the sensitivity …

Learning Knowledge-Enriched Company Embeddings For Investment Management, Gary Ang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Relationships between companies serve as key channels through which the effects of past stock price movements and news events propagate and influence future price movements. Such relationships can be implicitly found in knowledge bases or explicitly represented as knowledge graphs. In this paper, we propose KnowledgeEnriched Company Embedding (KECE), a novel multi-stage attentionbased dynamic network embedding model combining multimodal information of companies with knowledge from Wikipedia and knowledge graph relationships from Wikidata to generate company entity embeddings that can be applied to a variety of downstream investment management tasks. Experiments on an extensive set of real-world stock prices and news …

Sofi: Reflection-Augmented Fuzzing For Javascript Engines, Xiaoyu He, Xiaofei Xie, Yuekang Li, Jianwen Sun, Feng Li, Wei Zou, Yang Liu, Lei Yu, Jianhua Zhou, Wenchang Shi, Wei Huo

Research Collection School Of Computing and Information Systems

JavaScript engines have been shown prone to security vulnerabilities, which can lead to serious consequences due to their popularity. Fuzzing is an effective testing technique to discover vulnerabilities. The main challenge of fuzzing JavaScript engines is to generate syntactically and semantically valid inputs such that deep functionalities can be explored. However, due to the dynamic nature of JavaScript and the special features of different engines, it is quite challenging to generate semantically meaningful test inputs.We observed that state-of-the-art semantic-aware JavaScript fuzzers usually require manually written rules to analyze the semantics for a JavaScript engine, which is labor-intensive, incomplete and engine-specific. …

Unit 4 - Installing Packages And Shared Libraries On Ubuntu 20.04, George A. Nossa, Ahmet Kok

Open Educational Resources

This document details the steps necessary for Installing Packages and Shared Libraries on the Ubuntu 20.04 Operating System. This is a course lab of the CIS 440 UNIX course and this lab runs on a virtual machine installed on the student's home computer. The creation and configuration of this virtual machine is described in the Unit 1 document previously posted.

Taxthemis: Interactive Mining And Exploration Of Suspicious Tax Evasion Group, Yating Lin, Kamkwai Wong, Yong Wang, Rong Zhang, Bo Dong, Huamin Qu, Qinghua Zheng

Research Collection School Of Computing and Information Systems

Tax evasion is a serious economic problem for many countries, as it can undermine the government’s tax system and lead to an unfair business competition environment. Recent research has applied data analytics techniques to analyze and detect tax evasion behaviors of individual taxpayers. However, they have failed to support the analysis and exploration of the related party transaction tax evasion (RPTTE) behaviors (e.g., transfer pricing), where a group of taxpayers is involved. In this paper, we present TaxThemis, an interactive visual analytics system to help tax officers mine and explore suspicious tax evasion groups through analyzing heterogeneous tax-related data. A …

Improving The Performance Of Transportation Networks: A Semi-Centralized Pricing Approach, Zhiguang Cao, Hongliang Guo, Wen Song, Kaizhou Gao, Liujiang Kang, Xuexi Zhang, Qilun Wu

Research Collection School Of Computing and Information Systems

Improving the performance of transportation network is a crucial task in traffic management. In this paper, we start with a cooperative routing problem, which aims to minimize the chance of road network breakdown. To address this problem, we propose a subgradient method, which can be naturally implemented as a semi-centralized pricing approach. Particularly, each road link adopts the pricing scheme to calculate and adjust the local toll regularly, while the vehicles update their routes to minimize the toll costs by exploiting the global toll information. To prevent the potential oscillation brought by the subgradient method, we introduce a heavy-ball method …

Cis 440 Unix, George A. Nossa

Open Educational Resources

This document is a topical outline of the CIS 440 UNIX Course. This course is mostly based on lab assignments that are performed by students using their home computers (desktops or laptops). The home computers are configured as virtual machines by installing the Oracle Virtual Box Version 6.12 The Ubuntu Desktop Operating System (version 20.04) is then installed on these virtual machines, which are then used to run the course labs. The first Unit of the syllabus covers the virtual machine configuration for the lab environment and subsequent Units are a topical outline of the course. The detailed content is …

Unit 2 - Customizing The Ubuntu Desktop And Updating App Software, George A. Nossa

Open Educational Resources

This document demonstrates the steps to customize the Linux-Ubuntu 20.04 desktop and the steps to add a Media Player and a Video Editor to the desktop.

This is a course lab in the CIS 440 UNIX course.

Unit 3 - Displaying Hardware And Data Files, George A. Nossa, Ahmet Kok

Open Educational Resources

This document is a lab assignment of the CIS 440 UNIX Course. This course is mostly based on lab assignments that are performed by students using their home computers (desktops or laptops). The home computers are configured as virtual machines by installing the Oracle Virtual Box Version 6.12 The Ubuntu Desktop Operating System (version 20.04) is then installed on these virtual machines, which are then used to run the course labs.

This lab assignment titled “Unit 3 - Displaying Hardware and Data Files” was originally developed by the National Information Security and Geospatial Technologies Consortium (NISGTC)and is licensed under …

Feeder Vessel Routing And Transshipment Coordination At A Congested Hub Port, Jiangang Jin, Qiang Meng, Hai Wang

Research Collection School Of Computing and Information Systems

With increasing container-shipping traffic, congestion at transshipment hub ports happens from time to time incurring longer-than-expected waiting time for vessels and loss of transshipment connections. This situation is even worse for feeder companies, due to their relatively lower berthing priority. It is essential to design the feeder vessel routes and schedules in response to hub port congestion while ensuring efficient transshipment connection with their connecting long-haul services. In this paper, we study the vessel routing and transshipment coordination problem for a feeder liner company where only limited choices of berthing time slots are available at the hub port. We proposed …

Holistic Prediction For Public Transport Crowd Flows: A Spatio Dynamic Graph Network Approach, Bingjie He, Shukai Li, Chen Zhang, Baihua Zheng, Fugee Tsung

Research Collection School Of Computing and Information Systems

This paper targets at predicting public transport in-out crowd flows of different regions together with transit flows between them in a city. The main challenge is the complex dynamic spatial correlation of crowd flows of different regions and origin-destination (OD) paths. Different from road traffic flows whose spatial correlations mainly depend on geographical distance, public transport crowd flows significantly relate to the region’s functionality and connectivity in the public transport network. Furthermore, influenced by commuters’ time-varying travel patterns, the spatial correlations change over time. Though there exist many works focusing on either predicting in-out flows or OD transit flows of …

Adversarial Attacks And Mitigation For Anomaly Detectors Of Cyber-Physical Systems, Yifan Jia, Jingyi Wang, Christopher M. Poskitt, Sudipta Chattopadhyay, Jun Sun, Yuqi Chen

Research Collection School Of Computing and Information Systems

The threats faced by cyber-physical systems (CPSs) in critical infrastructure have motivated research into a multitude of attack detection mechanisms, including anomaly detectors based on neural network models. The effectiveness of anomaly detectors can be assessed by subjecting them to test suites of attacks, but less consideration has been given to adversarial attackers that craft noise specifically designed to deceive them. While successfully applied in domains such as images and audio, adversarial attacks are much harder to implement in CPSs due to the presence of other built-in defence mechanisms such as rule checkers (or invariant checkers). In this work, we …

Unit 1 - Virtual Machine Creation And Configuration, George A. Nossa

Open Educational Resources

The COVID pandemic has challenged us in continuing our instructional mission and provide high quality learning activities remotely. A key requirement for advanced technology courses is to duplicate the BMCC Computer Lab environment on the student's home computers.

This document provides detailed instructions for creating a "virtual machine" on the student's home computer. This document assumes the home computer is a PC desktop or laptop but this document will also work on computers running MacOS with an Intel X86 compatible chip,

Once the virtual machine is created, this document details the steps to install and configure an Ubuntu 20.04 Operating …

An Automated Method To Enrich Consumer Health Vocabularies Using Glove Word Embeddings And An Auxiliary Lexical Resource, Mohammed Ibrahim, Susan Gauch, Omar Salman, Mohammed Alqahtani

Computer Science and Computer Engineering Faculty Publications and Presentations

Background

Clear language makes communication easier between any two parties. A layman may have difficulty communicating with a professional due to not understanding the specialized terms common to the domain. In healthcare, it is rare to find a layman knowledgeable in medical terminology which can lead to poor understanding of their condition and/or treatment. To bridge this gap, several professional vocabularies and ontologies have been created to map laymen medical terms to professional medical terms and vice versa.

Objective

Many of the presented vocabularies are built manually or semi-automatically requiring large investments of time and human effort and consequently the …

Independent Reinforcement Learning For Weakly Cooperative Multiagent Traffic Control Problem, Chengwei Zhang, Shan Jin, Wanli Xue, Xiaofei Xie, Shengyong Chen, Rong Chen

Research Collection School Of Computing and Information Systems

The adaptive traffic signal control (ATSC) problem can be modeled as a multiagent cooperative game among urban intersections, where intersections cooperate to counter the city's traffic conditions. Recently, reinforcement learning (RL) has achieved marked successes in managing sequential decision making problems, which motivates us to apply RL in the ATSC problem. One of the largest challenges of this problem is that the observation of intersection is typically partially observable, which limits the learning performance of RL algorithms. Considering the large scale of intersections in an urban traffic environment, we use independent RL to solve ATSC problem in this study. We …

An Empirical Study Of Gui Widget Detection For Industrial Mobile Games, Jiaming Ye, Ke Chen, Xiaofei Xie, Lei Ma, Ruochen Huang, Yingfeng Chen, Yinxing Xue, Jianjun Zhao

Research Collection School Of Computing and Information Systems

With the widespread adoption of smartphones in our daily life, mobile games experienced increasing demand over the past years. Meanwhile, the quality of mobile games has been continuously drawing more and more attention, which can greatly affect the player experience. For better quality assurance, general-purpose testing has been extensively studied for mobile apps. However, due to the unique characteristic of mobile games, existing mobile testing techniques may not be directly suitable and applicable. To better understand the challenges in mobile game testing, in this paper, we first initiate an early step to conduct an empirical study towards understanding the challenges …

Ava: Adversarial Vignetting Attack Against Visual Recognition, Binyu Tian, Felix Juefei-Xu, Qing Guo, Xiaofei Xie, Xiaohong Li, Yang Liu

Research Collection School Of Computing and Information Systems

Vignetting is an inherent imaging phenomenon within almost all optical systems, showing as a radial intensity darkening toward the corners of an image. Since it is a common effect for photography and usually appears as a slight intensity variation, people usually regard it as a part of a photo and would not even want to post-process it. Due to this natural advantage, in this work, we study the vignetting from a new viewpoint, i.e., adversarial vignetting attack (AVA), which aims to embed intentionally misleading information into the vignetting and produce a natural adversarial example without noise patterns. This example can …

Forecasting Interaction Order On Temporal Graphs, Wenwen Xia, Yuchen Li, Jianwei Tian, Shenghong Li

Research Collection School Of Computing and Information Systems

Link prediction is a fundamental task for graph analysis and the topic has been studied extensively for static or dynamic graphs. Essentially, the link prediction is formulated as a binary classification problem about two nodes. However, for temporal graphs, links (or interactions) among node sets appear in sequential orders. And the orders may lead to interesting applications. While a binary link prediction formulation fails to handle such an order-sensitive case. In this paper, we focus on such an interaction order prediction (IOP) problem among a given node set on temporal graphs. For the technical aspect, we develop a graph neural …

Estimating Homophily In Social Networks Using Dyadic Predictions, George Berry, Antonio Sirianni, Ingmar Weber, Jisun An, Michael Macy

Research Collection School Of Computing and Information Systems

Predictions of node categories are commonly used to estimate homophily and other relational properties in networks. However, little is known about the validity of using predictions for this task. We show that estimating homophily in a network is a problem of predicting categories of dyads (edges) in the graph. Homophily estimates are unbiased when predictions of dyad categories are unbiased. Node-level prediction models, such as the use of names to classify ethnicity or gender, do not generally produce unbiased predictions of dyad categories and therefore produce biased homophily estimates. Bias comes from three sources: sampling bias, correlation between model errors …

An Improved Learnable Evolution Model For Solving Multi-Objective Vehicle Routing Problem With Stochastic Demand, Yunyun Niu, Detian Kong, Rong Wen, Zhiguang Cao, Jianhua Xiao

Research Collection School Of Computing and Information Systems

The multi-objective vehicle routing problem with stochastic demand (MO-VRPSD) is much harder to tackle than other traditional vehicle routing problems (VRPs), due to the uncertainty in customer demands and potentially conflicted objectives. In this paper, we present an improved multi-objective learnable evolution model (IMOLEM) to solve MO-VRPSD with three objectives of travel distance, driver remuneration and number of vehicles. In our method, a machine learning algorithm, i.e., decision tree, is exploited to help find and guide the desirable direction of evolution process. To cope with the key issue of "route failure" caused due to stochastic customer demands, we propose a …