Automating App Review Response Generation Based On Contextual Knowledge,
2022
Singapore Management University
Automating App Review Response Generation Based On Contextual Knowledge, Cuiyun Gao, Wenjie Zhou, Xin Xia, David Lo, Qi Xie, Michael R. Lyu
Research Collection School Of Computing and Information Systems
User experience of mobile apps is an essential ingredient that can influence the user base and app revenue. To ensure good user experience and assist app development, several prior studies resort to analysis of app reviews, a type of repository that directly reflects user opinions about the apps. Accurately responding to the app reviews is one of the ways to relieve user concerns and thus improve user experience. However, the response quality of the existing method relies on the pre-extracted features from other tools, including manually labelled keywords and predicted review sentiment, which may hinder the generalizability and flexibility of …
A Novel Handover Method Using Destination Prediction In 5g-V2x Networks,
2022
San Jose State University
A Novel Handover Method Using Destination Prediction In 5g-V2x Networks, Pooja Shyamsundar
Master's Projects
This paper proposes a novel approach to handover optimization in fifth generation vehicular networks. A key principle in designing fifth generation vehicular network technology is continuous connectivity. This makes it important to ensure that there are no gaps in communication for mobile user equipment. Handovers can cause disruption in connectivity as the process involves switching from one base station to another. Issues in the handover process include poor load management for moving traffic resulting in low bandwidth or connectivity gaps, too many hops resulting in multiple unneccessary handovers, short dwell times and ineffective base station selection resulting in delays and …
Taming The Data In The Internet Of Vehicles,
2022
California State University, Fresno
Taming The Data In The Internet Of Vehicles, Shahab Tayeb
Mineta Transportation Institute Publications
As an emerging field, the Internet of Vehicles (IoV) has a myriad of security vulnerabilities that must be addressed to protect system integrity. To stay ahead of novel attacks, cybersecurity professionals are developing new software and systems using machine learning techniques. Neural network architectures improve such systems, including Intrusion Detection System (IDSs), by implementing anomaly detection, which differentiates benign data packets from malicious ones. For an IDS to best predict anomalies, the model is trained on data that is typically pre-processed through normalization and feature selection/reduction. These pre-processing techniques play an important role in training a neural network to optimize …
Codis: Community Detection Via Distributed Seed-Set Expansion On Graph Streams,
2022
San Jose State University
Codis: Community Detection Via Distributed Seed-Set Expansion On Graph Streams, Austin Anderson
Master's Projects
Community detection has been and remains a very important topic in several fields. From marketing and social networking to biological studies, community detec- tion plays a key role in advancing research in many different fields. Research on this topic originally looked at classifying nodes into discrete communities, but eventually moved forward to placing nodes in multiple communities. Unfortunately, community detection has always been a time-inefficient process, and recent data sets have been simply to large to realistically process using traditional methods. Because of this, recent methods have turned to parallelism, but all these methods, while offering sig- nificant decrease in …
Hard Real-Time Linux On A Raspberry Pi For 3d Printing,
2022
San Jose State University
Hard Real-Time Linux On A Raspberry Pi For 3d Printing, Alvin Nguyen
Master's Projects
The project presents how a Raspberry Pi with hard real-time enabled Linux can control stepper motors to operate the kinematics of a 3D (three-dimensional) printer. The consistent performance of the Raspberry Pi with the PREEMPT-RT (real-time) patch can satisfy real hard-time requirements for 3D printing kinematics, without introducing dedicated microcontrollers. The Klipper 3D printer firmware enables one of the Raspberry Pi processors to act as the Klipper MCU, the primary controller for the hardware components. This project introduces a software implementation of the control logic for controlling the stepper motors, which utilizes the PCA9685 pwm driver and TB6612 motor drivers …
Dynamic Resource Management Of Fog-Cloud Computing For Iot Support,
2021
San Jose State University
Dynamic Resource Management Of Fog-Cloud Computing For Iot Support, Mariia Surmenok
Master's Projects
The internet of things (IoT) is an integrated part of contemporary life. It includes wearable devices, such as smart watches and cell phones, as well as sensors for Smart City. Fog computing can improve the efficiency and battery life of IoT devices by offloading tasks to fog cloud. It is important to have fog clusters near the IoT device for faster data offload. The goal of this project is to develop dynamic resource allocation for on-demand fog computing cluster to efficiently deploy tasks from IoT. This report studies the different research papers about the current state of resource management in …
Achieving Fairness Through Load-Balancing In Social Cloud Computing Networks,
2021
San Jose State University
Achieving Fairness Through Load-Balancing In Social Cloud Computing Networks, Kaiyi Huang
Master's Projects
Cloud-based computing networks have taken over the digital landscape. From small non-profits to large multinational corporations, more and more entities have been offloading computing effort to the cloud in order to take advantage of the increased cost-efficiency and scalability of cloud computing. One of the new types of cloud that have emerged is the P2P cloud, which disengages from a traditional datacenter setup by allowing users to instead share their own computing hardware into a cloud to take advantage of cloud computing’s advantages at an even lower cost. However, this new paradigm comes with a slew of challenges, notably, security …
Comparison Of Major Cloud Providers,
2021
Harrisburg University of Science and Technology
Comparison Of Major Cloud Providers, Justin Berman
Other Student Works
This paper will compare the following major cloud providers: Microsoft Azure, Amazon AWS, Google Cloud, and IBM Cloud. An introduction to the companies and their history, fundamentals and services, strengths and weaknesses, costs, and their security will be discussed throughout this writing.
Ggnb: Graph-Based Gaussian Naive Bayes Intrusion Detection System For Can Bus,
2021
University of Maryland - Baltimore County
Ggnb: Graph-Based Gaussian Naive Bayes Intrusion Detection System For Can Bus, Riadul Islam, Maloy K. Devnath, Manar D. Samad, Syed Md Jaffrey Al Kadry
Computer Science Faculty Research
The national highway traffic safety administration (NHTSA) identified cybersecurity of the automobile systems are more critical than the security of other information systems. Researchers already demonstrated remote attacks on critical vehicular electronic control units (ECUs) using controller area network (CAN). Besides, existing intrusion detection systems (IDSs) often propose to tackle a specific type of attack, which may leave a system vulnerable to numerous other types of attacks. A generalizable IDS that can identify a wide range of attacks within the shortest possible time has more practical value than attack-specific IDSs, which is not a trivial task to accomplish. In this …
Routing And Spectrum Allocation In Spectrum-Sliced Elastic Optical Path Networks: A Primal-Dual Framework,
2021
La Salle University
Routing And Spectrum Allocation In Spectrum-Sliced Elastic Optical Path Networks: A Primal-Dual Framework, Yang Wang, Chaoyang Li, Qian Hu, Jabree Flor, Maryam Jalalitabar
Department of Mathematics and Computer Science Faculty Work
The recent decade has witnessed a tremendous growth of Internet traffic, which is expected to continue climbing for the foreseeable future. As a new paradigm, Spectrum-sliced Elastic Optical Path (SLICE) networks promise abundant (elastic) bandwidth to address the traffic explosion, while bearing other inherent advantages including enhanced signal quality and extended reachability. The fundamental problem in SLICE networks is to route each traffic demand along a lightpath with continuously and consecutively available sub-carriers, which is known as the Routing and Spectrum Allocation (RSA) problem. Given its NP-Hardness, the solutions to the RSA problem can be classified into two categories: optimal …
System Design And Optimization For Efficient Flash-Based Caching In Data Centers,
2021
Louisiana State University and Agricultural and Mechanical College
System Design And Optimization For Efficient Flash-Based Caching In Data Centers, Jian Liu
LSU Doctoral Dissertations
Modern data centers are the backbone of today’s Internet-based services and applications. With the explosive growth of the Internet data and a wider range of data-intensive applications being deployed, it is increasingly challenging for data centers to satisfy the ever-increasing demand for high-quality data services. To relieve the heavy burden on data center systems and accelerate data processing, a popular cost-efficient solution is to deploy high-speed, large-capacity flash-based cache systems. However, we are facing multiple critical challenges from device hardware, systems, to application workloads. In this dissertation, we focus on designing highly efficient caching solutions to cope with the explosive …
Sofi: Reflection-Augmented Fuzzing For Javascript Engines,
2021
Singapore Management University
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. …
Representation Learning On Multi-Layered Heterogeneous Network,
2021
Singapore Management University
Representation Learning On Multi-Layered Heterogeneous Network, Delvin Ce Zhang, Hady W. Lauw
Research Collection School Of Computing and Information Systems
Network data can often be represented in a multi-layered structure with rich semantics. One example is e-commerce data, containing user-user social network layer and item-item context layer, with cross-layer user-item interactions. Given the dual characters of homogeneity within each layer and heterogeneity across layers, we seek to learn node representations from such a multi-layered heterogeneous network while jointly preserving structural information and network semantics. In contrast, previous works on network embedding mainly focus on single-layered or homogeneous networks with one type of nodes and links. In this paper we propose intra- and cross-layer proximity concepts. Intra-layer proximity simulates propagation along …
Learning Knowledge-Enriched Company Embeddings For Investment Management,
2021
Singapore Management University
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 …
Pruning Meta-Trained Networks For On-Device Adaptation,
2021
Singapore Management University
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 …
Cis 440 Unix,
2021
CUNY Borough of Manhattan Community College
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 …
Improving The Performance Of Transportation Networks: A Semi-Centralized Pricing Approach,
2021
Singapore Management University
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 …
Taxthemis: Interactive Mining And Exploration Of Suspicious Tax Evasion Group,
2021
Singapore Management University
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 …
Holistic Prediction For Public Transport Crowd Flows: A Spatio Dynamic Graph Network Approach,
2021
Singapore Management University
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,
2021
Singapore Management University
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 …
