Journey With Ting Peng Liang In Pacific Asia Information Systems Field, J. Lee, J. Jiang, P. Chau, A. Kankanhalli, M. Nelson, W. Huang, K. Wei, C. Sia, D. Vogel, M. Myers, G. Gable, N. Shen, C. Wei, S. Hung, Keng Siau, D. Liang

Research Collection School Of Computing and Information Systems

Our respectful old friend Professor Ting-Peng Liang (in short, TP) whom we loved suddenly passed away on May 20, 2021. But we cannot forget his smile and passion, and his inerasable footprints in PACIS, PAJAIS, and AIS Community. He was the founder of PACIS, founding editor-in-chief of PAJAIS, and past president of AIS to list just a few. He was the pioneer who received the first AIS Fellow and the first LEO Award from Asia Pacific. That is why the leaders of the information systems field organized the first ever special tribute session in PACIS 2021 in memory of TP

Artificial Intelligence (Ai): The New Look Of Customer Service In A Cybersecurity World, Sharon L. Burton

Publications

Cybersecurity leaders are not adequately developed to guide the re-engineering of quality customer service (QCS) workflows, designed with automation and AI, that interrelate with people through customers’ perceptions. Realizing re-engineering processes should be a team effort with well-versed leadership and stakeholders guiding the successful design through a follow-up process. Leaders must shape compelling and straightforward needs to learn and teach employees and chat boxes indispensable customer service skills demonstrating patience, self-discipline, flexibility, and resourcefulness in communication with irritated customers or difficult circumstances. Whether the analysis, design, development, and implementation struggles are vacuums in cybersecurity knowledge, skill, and abilities or a …

Exploring Cyberterrorism, Topic Models And Social Networks Of Jihadists Dark Web Forums: A Computational Social Science Approach, Vivian Fiona Guetler

Graduate Theses, Dissertations, and Problem Reports (ETD)

This three-article dissertation focuses on cyber-related topics on terrorist groups, specifically Jihadists’ use of technology, the application of natural language processing, and social networks in analyzing text data derived from terrorists' Dark Web forums. The first article explores cybercrime and cyberterrorism. As technology progresses, it facilitates new forms of behavior, including tech-related crimes known as cybercrime and cyberterrorism. In this article, I provide an analysis of the problems of cybercrime and cyberterrorism within the field of criminology by reviewing existing literature focusing on (a) the issues in defining terrorism, cybercrime, and cyberterrorism, (b) ways that cybercriminals commit a crime in …

More Amazon Than Mafia: Analysing A Ddos Stresser Service As Organised Cybercrime, Roberto Musotto, David S. Wall

Research outputs 2014 to 2021

© 2020, The Author(s). The internet mafia trope has shaped our knowledge about organised crime groups online, yet the evidence is largely speculative and the logic often flawed. This paper adds to current knowledge by exploring the development, operation and demise of an online criminal group as a case study. In this article we analyse a DDoS (Distributed Denial of Service) stresser (also known as booter) which sells its services online to enable offenders to launch attacks. Using Social Network Analysis to explore the service operations and payment systems, our findings show a central business model that is similar to …

Machine Learning Land Cover And Land Use Classification Of 4-Band Satellite Imagery, Lorelei Turner, Torrey J. Wagner, Paul Auclair, Brent T. Langhals

Faculty Publications

Land-cover and land-use classification generates categories of terrestrial features, such as water or trees, which can be used to track how land is used. This work applies classical, ensemble and neural network machine learning algorithms to a multispectral remote sensing dataset containing 405,000 28x28 pixel image patches in 4 electromagnetic frequency bands. For each algorithm, model metrics and prediction execution time were evaluated, resulting in two families of models; fast and precise. The prediction time for an 81,000-patch group of predictions wasmodels, and >5s for the precise models, and there was not a significant change in prediction time when a …

Leveraging Natural Language Processing To Analyse The Temporal Behavior Of Extremists On Social Media, May El Barachi, Sujith Samuel Mathew, Farhad Oroumchian, Imene Ajala, Saad Lutfi, Rand Yasin

All Works

Aiming at achieving sustainability and quality of life for citizens, future smart cities adopt a data-centric approach to decision making in which assets, people, and events are constantly monitored to inform decisions. Public opinion monitoring is of particular importance to governments and intelligence agencies, who seek to monitor extreme views and attempts of radicalizing individuals in society. While social media platforms provide increased visibility and a platform to express public views freely, such platforms can also be used to manipulate public opinion, spread hate speech, and radicalize others. Natural language processing and data mining techniques have gained popularity for the …

Private And Federated Deep Learning: System, Theory, And Applications For Social Good, Han Hu

Dissertations

During the past decade, drug abuse continues to accelerate towards becoming the most severe public health problem in the United States. The ability to detect drug­abuse risk behavior at a population scale, such as among the population of Twitter users, can help to monitor the trend of drug­abuse incidents. However, traditional methods do not effectively detect drug­abuse risk behavior in tweets, mainly due to the sparsity of such tweets and the noisy nature of tweets. In the first part of this dissertation work, the task of classifying tweets as containing drug­abuse risk behavior or not, is studied. Millions of public …

A Novel Arabic Corpus For Text Classification Using Deep Learning And Word Embedding, Roua A. Abou Khachfeh, Islam El Kabani, Ziad Osman

BAU Journal - Science and Technology

Over the last years, Natural Language Processing (NLP) for Arabic language has obtained increasing importance due to the massive textual information available online in an unstructured text format, and its capability in facilitating and making information retrieval easier. One of the widely used NLP task is “Text Classification”. Its goal is to employ machine learning technics to automatically classify the text documents into one or more predefined categories. An important step in machine learning is to find suitable and large data for training and testing an algorithm. Moreover, Deep Learning (DL), the trending machine learning research, requires a lot of …

What Interactive Web Features Are Most Used, Travis Tyler

Experiential Learning Projects

The use of interactive features in websites has become common place on the internet. People use these tools to help navigate and understand the content related to that website. However, due the large variety of websites it can be tricky to understand what features are best to utilize based on the topic of your site. This paper seeks to address this issue by researching how users interact and utilized different features on different websites. Research is gathered via scholarly articles and direct data gathered from volunteers. This data shows users tend to favor more interactive tools to help with navigation, …

Teaching Computer Science Csc 222, Harrison Dekker

Library Impact Statements

No abstract provided.

Development Experience Of International Open Source And Its Enlightenment To Construction Of Open Source Innovation System In China, Yuntao Long, Xiaoming Wang, Rong Gu, Yungang Bao

Bulletin of Chinese Academy of Sciences (Chinese Version)

Open source has become an essential innovation model for global technological progress and the construction of an open source innovation system is an important path for China to achieve self-reliance and self-improvement in science and technology. As an indispensable part of the global software value chain and high-tech industry chain, China needs to improve its open source innovation ecosystem. The paper, based on a systematic review of the related development policies and successful experiences on the open source work in US and Europe, puts forward a series of policy suggestions to solve the practical problems faced by the construction of …

Introduction To Using Python In The Digital Humanities, Elisabeth Shook

Library Faculty Publications and Presentations

The materials here are from the Python for Digital Humanities Workshop taught on December 13, 2021 for the Boise State University Digital Humanities Group. This 3-hour workshop was created to provide both a very brief introduction to the various capabilities of Python and a small lesson in using Python to pull meaningful insight out of text files.

Exploring The Impact Of Social Influence Mechanisms And Network Density On Societal Polarization, Justin Mittereder

Departmental Honors & Graduate Capstone Projects

I present an agent-based model, inspired by the opinion dynamics
(OD) literature, to explore the underlying behaviors that may induce
societal polarization. My agents interact on a social network, in which
adjacent nodes can influence each other, and each agent holds an array
of continuous opinion values (on a 0-1 scale) on a number of separate
issues. I use three measures as a proxy for the virtual society’s “po-
larization:” the average assortativity of the graph with respect to the
agents’ opinions, the number of non-uniform issues, and the number
of distinct opinion buckets in which agents have the same …

Proquest Tdm Studio: A Text And Data Mining Solution, Anamika Megwalu, Anne Marie Engelsen

Faculty Research, Scholarly, and Creative Activity

TDM Studio is an integrated platform offered by ProQuest for data and text mining. TDM stands for text and data mining. This cloud-based, all-in-one innovative product is designed to offer researchers a clean interface with rights-cleared content, Jupyter notebook, and data visualization tools. As a result, researchers can now search Pro-Quest databases, create large datasets, import data to Jupyter notebook for analysis, and download results within a day.

Machine Learning For Stock Prediction Based On Fundamental Analysis, Yuxuan Huang, Luiz Fernando Capretz, Danny Ho

Electrical and Computer Engineering Publications

Application of machine learning for stock prediction is attracting a lot of attention in recent years. A large amount of research has been conducted in this area and multiple existing results have shown that machine learning methods could be successfully used toward stock predicting using stocks’ historical data. Most of these existing approaches have focused on short term prediction using stocks’ historical price and technical indicators. In this paper, we prepared 22 years’ worth of stock quarterly financial data and investigated three machine learning algorithms: Feed-forward Neural Network (FNN), Random Forest (RF) and Adaptive Neural Fuzzy Inference System (ANFIS) for …

Developing A Practice In Remote Sensing For Next-Generation Human Rights Researchers, Theresa Harris, Jonathan Drake, Umesh K. Haritashya, Wumi Asubiaro Dada, Fredy Cumes

Biennial Conference: The Social Practice of Human Rights

Remote sensing is increasingly recognized as an important tool for documenting human rights abuses. When used alongside interviews, case studies, surveys, forensic science, and other well-established research methods in human rights and humanitarian practice, remotely sensed data can effectively geolocate and establish chronologies for mass graves, forced displacement, destruction of cultural heritage sites, and other violations. But as a highly technical field of science that relies on ever-changing technologies, remote sensing and geospatial analysis are not readily accessible for human rights and humanitarian practitioners. The community of practice grew out of innovative work by practitioners at NGOs and specialized inter-governmental …

Ready, Willing, And Able, Gerry Boyle

Colby Magazine

So what gives? How, after four years on Mayflower Hill, do these Colby alumni have an outsized impact in a fintech company that is focused on, for example, changing the way municipal bonds are traded? What makes them able to dive in and figure it out? “That’s part of the liberal arts education,” said Associate Professor of History John Turner, who taught Tagg Martin ’13, history major turned MarketAxess go-to analyst. “You’re always learning. … You are always going to be mastering something, as opposed to having mastered.”

Studying Users Interactions And Behavior In Social Media Using Natural Language Processing, Sultan Alshamrani

Electronic Theses and Dissertations, 2020-2023

Social media platforms have been growing at a rapid pace, attracting users' engagement with the online content due to their convenience facilitated by many useful features. Such platforms provide users with interactive options such as likes, dislikes as well as a way of expressing their opinions in the form of text (i.e., comments). As more people engage in different social media platforms, such platforms will increase in both size and importance. This growth in social media data is becoming a vital new area for scholars and researchers to explore this new form of communication. The huge data from social media …

Interval Estimates: How To Make Them More Adequate And How To Use Them In Economic Analysis And Decision Making, Laura Adriana Berrout-Ramos

Open Access Theses & Dissertations

In many real-life situations, we need to make decisions in situations when we do not have full information about the consequences of different decisions. In particular, instead of the exact values of the relevant quantities, we only know lower and upper bounds on these values – i.e., we know an interval that contains the actual (unknown) value. These interval estimates often come from experts. This fact naturally leads to the following important questions: How should we make decisions under such interval uncertainty? How to gauge the quality of the resulting decisions? And if this quality is not sufficient – because …

Risk-Based Machine Learning Approaches For Probabilistic Transient Stability, Umair Shahzad

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Power systems are getting more complex than ever and are consequently operating close to their limit of stability. Moreover, with the increasing demand of renewable wind generation, and the requirement to maintain a secure power system, the importance of transient stability cannot be overestimated. Considering its significance in power system security, it is important to propose a different approach for enhancing the transient stability, considering uncertainties. Current deterministic industry practices of transient stability assessment ignore the probabilistic nature of variables (fault type, fault location, fault clearing time, etc.). These approaches typically provide a conservative criterion and can result in expensive …

Examining The Effects Of Information And Communication Technologies In The Legal Representation Of Latin American Asylum Seekers, Victor M. Portillo Ochoa

Open Access Theses & Dissertations

The purpose of this thesis was to explore how legal defense nonprofit organizations (NPO) are using Information and Communication Technologies (ICT) to provide legal defense for asylum seekers and improve the conditions of immigrants at detention centers. In addition, this research explored the impact of ICTs on legal defense NPOs, bottlenecks, and security implications when supporting vulnerable communities. ICTs profoundly impacted the way we interact in a post-pandemic world, and it presents new challenges and possibilities for legal defense nonprofit organizations that are helping vulnerable communities. This study consists of staff and volunteers from different legal defense nonprofit organizations NPOs …

Data-Driven Operational And Safety Analysis Of Emerging Shared Electric Scooter Systems, Qingyu Ma

Computational Modeling & Simulation Engineering Theses & Dissertations

The rapid rise of shared electric scooter (E-Scooter) systems offers many urban areas a new micro-mobility solution. The portable and flexible characteristics have made E-Scooters a competitive mode for short-distance trips. Compared to other modes such as bikes, E-Scooters allow riders to freely ride on different facilities such as streets, sidewalks, and bike lanes. However, sharing lanes with vehicles and other users tends to cause safety issues for riding E-Scooters. Conventional methods are often not applicable for analyzing such safety issues because well-archived historical crash records are not commonly available for emerging E-Scooters.

Perceiving the growth of such a micro-mobility …

Ai And The Future Of Work: What We Know Today, Steven M. Miller, Thomas H. Davenport

Research Collection School Of Computing and Information Systems

To contribute to a better understanding of the contemporary realities of AI workplace deployments, the authors recently completed 29 case studies of people doing their everyday work with AI-enabled smart machines. Twenty-three of these examples were from North America, mostly in the US. Six were from Southeast Asia, mostly in Singapore. In this essay, we compare our findings on job and workplace impacts to those reported in the MIT Task Force on the Work of the Future report, as we consider that to be the most comprehensive recent study on this topic.

Spurring Digital Transformation In Singapore's Legal Industry, Xin Juan Chua, Steven M. Miller

Research Collection School Of Computing and Information Systems

COVID-19 has transformed the way we live and work. It has caused the processes and operations of businesses and organisations to be restructured, as well as transformed business models. A 2020 McKinsey Global survey reported that companies all over the world claim they have accelerated the digitalisation of their customer and supply-chain interactions, as well as their internal operations, by three to four years. They also said they thought the share of digital or digitally enabled products in their portfolios has advanced by seven years. While technology transformation is not new to the legal profession, COVID-19 has cemented the importance …

Context-Aware Graph Convolutional Network For Dynamic Origin-Destination Prediction, Juan Nathaniel, Baihua Zheng

Research Collection School Of Computing and Information Systems

A robust Origin-Destination (OD) prediction is key to urban mobility. A good forecasting model can reduce operational risks and improve service availability, among many other upsides. Here, we examine the use of Graph Convolutional Net-work (GCN) and its hybrid Markov-Chain (GCN-MC) variant to perform a context-aware OD prediction based on a large-scale public transportation dataset in Singapore. Compared with the baseline Markov-Chain algorithm and GCN, the proposed hybrid GCN-MC model improves the prediction accuracy by 37% and 12% respectively. Lastly, the addition of temporal and historical contextual information further improves the performance of the proposed hybrid model by 4 –12%.

Integration Of Blockchain Technology Into Automobiles To Prevent And Study The Causes Of Accidents, John Kim

Electronic Theses, Projects, and Dissertations

Automobile collisions occur daily. We now live in an information-driven world, one where technology is quickly evolving. Blockchain technology can change the automotive industry, the safety of the motoring public and its surrounding environment by incorporating this vast array of information. It can place safety and efficiency at the forefront to pedestrians, public establishments, and provide public agencies with pertinent information securely and efficiently. Other industries where Blockchain technology has been effective in are as follows: supply chain management, logistics, and banking. This paper reviews some statistical information regarding automobile collisions, Blockchain technology, Smart Contracts, Smart Cities; assesses the feasibility …

Introduction To Malware Analysis, Harrison Dekker

Library Impact Statements

No abstract provided.

Analysis And Strategy Of Ai Ethical Problems, Zhaoxiang Zhang, Jiyu Zhang, Tieniu Tan

Bulletin of Chinese Academy of Sciences (Chinese Version)

Artificial intelligence (AI) is the core of the fourth industrial revolution, and it has brought challenges to ethics and social governance. On the basis of explaining the current ethical risks of artificial intelligence, the study furtherly analyzes the current consensus on ethics, governance principles, and governance approaches of artificial intelligence. Moreover, the study also proposes to take "co-construction, co-governance and sharing" as the guiding theory to gradually build a multi-dimensional ethical governance system, including education reform, ethical norms, technical supports, legal regulations, and international cooperation.

The Spatial Effects Of Elderly Population Presence On Covid -19 Incidence In Dki Jakarta Before, During, And After Large-Scale Social Restriction, Chotib Chotib, I G A A Karishma Maharani Raijaya Mrs., Ahmad Aki Aki Muhaimin Mr., Novani Saputri

Smart City

ABSTRACT

Infected cases and suspect cases of covid-19 are increasing more and more daily. This increment happens either in whole regions of Indonesia and DKI Jakarta as a capital city. The purpose of this research is to seek the pattern in spatial of Covid-19 incidence with 3 different periods of before, during, and after large-scale social restriction, and to identify the influence of the presence of the elderly and other factors. One of the scopes of this study is the presence of the elderly because the elderly population is considered as influencing the increase of Covid-19 incidence. The analysis method …

From The Editors, Ahmad Gamal

Smart City

No abstract provided.