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Articles 1 - 30 of 5948
Full-Text Articles in Databases and Information Systems
Creating The Capacity For Digital Government, Cheow Hoe Chan, Steven Miller
Creating The Capacity For Digital Government, Cheow Hoe Chan, Steven Miller
Asian Management Insights
This article explains how a well-thought-out data policy, supported by a tech stack and cloud infrastructure, an agile way of working, and coordinated whole-of-government leadership, are fundamental to successful government digital transformation efforts, as exemplified by the Singapore government’s digital journey. As part of explaining how to create the capacity for digital government, the main sections of this article cover:
- The origins of GovTech
- How thinking big, starting small and acting fast is a practical strategy for organisational learning
- The importance of horizontal platforms and other enablers of a horizontal approach
- Data architecture and policy
- “Shifting left” with internal technology …
Learning Comprehensive Global Features In Person Re-Identification: Ensuring Discriminativeness Of More Local Regions, Jiali Xia, Jianqiang Huang, Shibao Zheng, Qin Zhou, Bernt Schiele, Xian-Sheng Hua, Qianru Sun
Learning Comprehensive Global Features In Person Re-Identification: Ensuring Discriminativeness Of More Local Regions, Jiali Xia, Jianqiang Huang, Shibao Zheng, Qin Zhou, Bernt Schiele, Xian-Sheng Hua, Qianru Sun
Research Collection School Of Computing and Information Systems
Person re-identification (Re-ID) aims to retrieve person images from a large gallery given a query image of a person of interest. Global information and fine-grained local features are both essential for the representation. However, global embedding learned by naive classification model tends to be trapped in the most discriminative local region, leading to poor evaluation performance. To address the issue, we propose a novel baseline network that learns strong global feature termed as Comprehensive Global Embedding (CGE), ensuring more local regions of global feature maps to be discriminative. In this work, two key modules are proposed including Non-parameterized Local Classifier …
Online Hyperparameter Optimization For Class-Incremental Learning, Yaoyao Liu, Yingying Li, Bernt Schiele, Qianru Sun
Online Hyperparameter Optimization For Class-Incremental Learning, Yaoyao Liu, Yingying Li, Bernt Schiele, Qianru Sun
Research Collection School Of Computing and Information Systems
Class-incremental learning (CIL) aims to train a classification model while the number of classes increases phase-by-phase. An inherent challenge of CIL is the stability-plasticity tradeoff, i.e., CIL models should keep stable to retain old knowledge and keep plastic to absorb new knowledge. However, none of the existing CIL models can achieve the optimal tradeoff in different data-receiving settings—where typically the training-from-half (TFH) setting needs more stability, but the training-from-scratch (TFS) needs more plasticity. To this end, we design an online learning method that can adaptively optimize the tradeoff without knowing the setting as a priori. Specifically, we first introduce the …
Integrated Organizational Machine Learning For Aviation Flight Data, Michael J. Pritchard, Paul Thomas, Eric Webb, Jon Martin, Austin Walden
Integrated Organizational Machine Learning For Aviation Flight Data, Michael J. Pritchard, Paul Thomas, Eric Webb, Jon Martin, Austin Walden
National Training Aircraft Symposium (NTAS)
An increased availability of data and computing power has allowed organizations to apply machine learning techniques to various fleet monitoring activities. Additionally, our ability to acquire aircraft data has increased due to the miniaturization of small form factor computing machines. Aircraft data collection processes contain many data features in the form of multivariate time-series (continuous, discrete, categorical, etc.) which can be used to train machine learning models. Yet, three major challenges still face many flight organizations 1) integration and automation of data collection frameworks, 2) data cleanup and preparation, and 3) embedded machine learning framework. Data cleanup and preparation has …
Is A Pretrained Model The Answer To Situational Awareness Detection On Social Media?, Siaw Ling Lo, Kahhe Lee, Yuhao Zhang
Is A Pretrained Model The Answer To Situational Awareness Detection On Social Media?, Siaw Ling Lo, Kahhe Lee, Yuhao Zhang
Research Collection School Of Computing and Information Systems
Social media can be valuable for extracting information about an event or incident on the ground. However, the vast amount of content shared, and the linguistic variants of languages used on social media make it challenging to identify important situational awareness content to aid in decision-making for first responders. In this study, we assess whether pretrained models can be used to address the aforementioned challenges on social media. Various pretrained models, including static word embedding (such as Word2Vec and GloVe) and contextualized word embedding (such as DistilBERT) are studied in detail. According to our findings, a vanilla DistilBERT pretrained language …
Dual-View Preference Learning For Adaptive Recommendation, Zhongzhou Liu, Yuan Fang, Min Wu
Dual-View Preference Learning For Adaptive Recommendation, Zhongzhou Liu, Yuan Fang, Min Wu
Research Collection School Of Computing and Information Systems
While recommendation systems have been widely deployed, most existing approaches only capture user preferences in the , i.e., the user's general interest across all kinds of items. However, in real-world scenarios, user preferences could vary with items of different natures, which we call the . Both views are crucial for fully personalized recommendation, where an underpinning macro-view governs a multitude of finer-grained preferences in the micro-view. To model the dual views, in this paper, we propose a novel model called Dual-View Adaptive Recommendation (DVAR). In DVAR, we formulate the micro-view based on item categories, and further integrate it with the …
Graphsearchnet: Enhancing Gnns Via Capturing Global Dependencies For Semantic Code Search, Shangqing Liu, Xiaofei Xie, Jjingkai Siow, Lei Ma, Guozhu Meng, Yang Liu
Graphsearchnet: Enhancing Gnns Via Capturing Global Dependencies For Semantic Code Search, Shangqing Liu, Xiaofei Xie, Jjingkai Siow, Lei Ma, Guozhu Meng, Yang Liu
Research Collection School Of Computing and Information Systems
Code search aims to retrieve accurate code snippets based on a natural language query to improve software productivity and quality. With the massive amount of available programs such as (on GitHub or Stack Overflow), identifying and localizing the precise code is critical for the software developers. In addition, Deep learning has recently been widely applied to different code-related scenarios, ., vulnerability detection, source code summarization. However, automated deep code search is still challenging since it requires a high-level semantic mapping between code and natural language queries. Most existing deep learning-based approaches for code search rely on the sequential text ., …
Survey On Sentiment Analysis: Evolution Of Research Methods And Topics, Jingfeng Cui, Zhaoxia Wang, Seng-Beng Ho, Erik Cambria
Survey On Sentiment Analysis: Evolution Of Research Methods And Topics, Jingfeng Cui, Zhaoxia Wang, Seng-Beng Ho, Erik Cambria
Research Collection School Of Computing and Information Systems
Sentiment analysis, one of the research hotspots in the natural language processing field, has attracted the attention of researchers, and research papers on the field are increasingly published. Many literature reviews on sentiment analysis involving techniques, methods, and applications have been produced using different survey methodologies and tools, but there has not been a survey dedicated to the evolution of research methods and topics of sentiment analysis. There have also been few survey works leveraging keyword co-occurrence on sentiment analysis. Therefore, this study presents a survey of sentiment analysis focusing on the evolution of research methods and topics. It incorporates …
Governing Smart Cities As Knowledge Commons - Introduction, Chapter 1 & Conclusion, Brett M. Frischmann, Michael J. Madison, Madelyn Sanfilippo
Governing Smart Cities As Knowledge Commons - Introduction, Chapter 1 & Conclusion, Brett M. Frischmann, Michael J. Madison, Madelyn Sanfilippo
Book Chapters
Smart city technology has its value and its place; it isn’t automatically or universally harmful. Urban challenges and opportunities addressed via smart technology demand systematic study, examining general patterns and local variations as smart city practices unfold around the world. Smart cities are complex blends of community governance institutions, social dilemmas that cities face, and dynamic relationships among information and data, technology, and human lives. Some of those blends are more typical and common. Some are more nuanced in specific contexts. This volume uses the Governing Knowledge Commons (GKC) framework to sort out relevant and important distinctions. The framework grounds …
Android Security: Analysis And Applications, Raina Samuel
Android Security: Analysis And Applications, Raina Samuel
Dissertations
The Android mobile system is home to millions of apps that offer a wide range of functionalities. Users rely on Android apps in various facets of daily life, including critical, e.g., medical, settings. Generally, users trust that apps perform their stated purpose safely and accurately. However, despite the platform’s efforts to maintain a safe environment, apps routinely manage to evade scrutiny. This dissertation analyzes Android app behavior and has revealed several weakness: lapses in device authentication schemes, deceptive practices such as apps covering their traces, as well as behavioral and descriptive inaccuracies in medical apps. Examining a large corpus of …
Using Materialized Views For Answering Graph Pattern Queries, Michael Lan
Using Materialized Views For Answering Graph Pattern Queries, Michael Lan
Dissertations
Discovering patterns in graphs by evaluating graph pattern queries involving direct (edge-to-edge mapping) and reachability (edge-to-path mapping) relationships under homomorphisms on data graphs has been extensively studied. Previous studies have aimed to reduce the evaluation time of graph pattern queries due to the potentially numerous matches on large data graphs.
In this work, the concept of the summary graph is developed to improve the evaluation of tree pattern queries and graph pattern queries. The summary graph first filters out candidate matches which violate certain reachability constraints, and then finds local matches of query edges. This reduces redundancy in the representation …
Big Data Technology Enabling Legal Supervision, Qingjie Liu, Shuo Liu, Yirong Wu, Yueqiang Weng, Yihao Wen, Ming Li
Big Data Technology Enabling Legal Supervision, Qingjie Liu, Shuo Liu, Yirong Wu, Yueqiang Weng, Yihao Wen, Ming Li
Bulletin of Chinese Academy of Sciences (Chinese Version)
Legal supervision plays an important role in the national governance system and capacity. In the era of digital revolution, the rapid development of digital procuratorial work with big data legal supervision as the core promotes to reshape the legal supervision and governance system. In this study, the inherent need of legal supervision for active prosecution in the new era, and the innovative role of new public interest litigation in comprehensive social governance, are firstly analyzed. Then, the core meaning and reshaping role of big-data-enabling-legalsupervision and supervision-promoting-national-governance of digital prosecution are discussed. After summarizing the practical experiences and challenges of big …
Hybrid Life Cycles In Software Development, Eric Vincent Schoenborn
Hybrid Life Cycles In Software Development, Eric Vincent Schoenborn
Culminating Experience Projects
This project applied software specification gathering, architecture, work planning, and development to a real-world development effort for a local business. This project began with a feasibility meeting with the owner of Zeal Aerial Fitness. After feasibility was assessed the intended users, needed functionality, and expected user restrictions were identified with the stakeholders. A hybrid software lifecycle was selected to allow a focus on base functionality up front followed by an iterative development of expectations of the stakeholders. I was able to create various specification diagrams that express the end projects goals to both developers and non-tech individuals using a standard …
Hybrid Life Cycles In Software Development, Eric Vincent Schoenborn
Hybrid Life Cycles In Software Development, Eric Vincent Schoenborn
Culminating Experience Projects
This project applied software specification gathering, architecture, work planning, and development to a real-world development effort for a local business. This project began with a feasibility meeting with the owner of Zeal Aerial Fitness. After feasibility was assessed the intended users, needed functionality, and expected user restrictions were identified with the stakeholders. A hybrid software lifecycle was selected to allow a focus on base functionality up front followed by an iterative development of expectations of the stakeholders. I was able to create various specification diagrams that express the end projects goals to both developers and non-tech individuals using a standard …
Devops: Course Development, James Lee Vanderzouwen
Devops: Course Development, James Lee Vanderzouwen
Culminating Experience Projects
DevOps has become somewhat of a buzzword amongst software engineers in the industry. Often developers do not have a dedicated DevOps engineer let alone a DevOps team. Developers benefit when they know what happens between ‘works on my machine’ and production. Making sure those steps make sense and are safe benefits the operations team. From compliance to code review to regression testing, understanding the full SDLC, employing DevOps concepts, and minimizing overhead from dependencies is quickly becoming a pre-requisite for the modern software engineer. This project attempts to bridge the gap between buzzword and best practice by developing a college-level …
Curriculum Development In Technical Education For Boys And Girls Club, Damanpreet Singh
Curriculum Development In Technical Education For Boys And Girls Club, Damanpreet Singh
Culminating Experience Projects
Technical education has been and will continue to be more and more important to succeed in the future. The Boys and Girls Club, founded in 1860, is a national organization of local chapters which provide voluntary after-school programs for young individuals. The Boys and Girls Club have life-changing programs that prepare the young individuals in the club for their future whether it’s for college, career, or life. The perfect way to prepare best prepare these kids for the future is to develop their technical education. Unfortunately, the boys and girls club of Muskegon has a lack of educational resources for …
Notebooks Web Application, Vivekananda Marellali
Notebooks Web Application, Vivekananda Marellali
Culminating Experience Projects
In our day-to-day activities we often need to make quick short notes related to our work, study, or other activities. Later, those notes should be easy to access, modify, delete, share with others, or create PDF documents as and when required. It is ideal if the note content is rich text format such as HTML, as it provides many text formatting options and provide better view and readability. The Notes are better organized if they are grouped into notebooks where each notebook consists of related topic note pages and multiple users can create such notebooks and share with other users …
Muse: A Genetic Algorithm For Musical Chord Progression Generation, Griffin Going
Muse: A Genetic Algorithm For Musical Chord Progression Generation, Griffin Going
Culminating Experience Projects
Foundational to our understanding and enjoyment of music is the intersection of harmony and movement. This intersection manifests as chord progressions which themselves underscore the rhythm and melody of a piece. In musical compositions, these progressions often follow a set of rules and patterns which are themselves frequently broken for the sake of novelty. In this work, we developed a genetic algorithm which learns these rules and patterns (and how to break them) from a dataset of 890 songs from various periods of the Billboard Top 100 rankings. The algorithm learned to generate increasingly valid, yet interesting chord progressions via …
Exploring Coral Reefs With Interactive Geospatial Visualizations, David Nicolas Tonning
Exploring Coral Reefs With Interactive Geospatial Visualizations, David Nicolas Tonning
Culminating Experience Projects
This project uses geospatial data to generate custom polygons in an interactive setting to represent the size and location of coral reefs to extract insights from coral reef-centered data sets. Historically, the data used by the Reef Restoration Group Bonaire exists in disparate sources, making it difficult to track and analyze the outcomes of their restoration work. Additionally, this information is not available in a digestible format for other audiences who would be interested in this data, such as citizen scientists seeking coral reef health statistics, the general public wanting to better understand the coral reefs surrounding Bonaire or recreational …
Building A Deep Model For Multi-Class Coral Species Discrimination, Hyeong Gyu Jang
Building A Deep Model For Multi-Class Coral Species Discrimination, Hyeong Gyu Jang
Culminating Experience Projects
The goal of this qualitative research project is to develop and optimize a multi-class discrimination model to identify different species of coral based on their digital images. Currently, there are artificial intelligence (AI) models that can distinguish between coral and other undersea objects such as sand or rocks, but to our knowledge the problem of multi-species classification has not yet been addressed. Given that coral reefs are a good indicator of overall ocean health, it is important to develop models that can classify the presence of different species in underwater images as a way to monitor the effects of climate …
Travel Dashboard, Naveen Kumar Lalam
Travel Dashboard, Naveen Kumar Lalam
Culminating Experience Projects
Travel Dashboard is a one stop solution for all the travel needs of travelers and tourists visiting a new place. In today’s world travel has become a part of everyone’s life and we love to travel whenever there is a holiday or long a weekend. Earlier, the travel industry was mostly dictated by tour operators who used to plan and organize tours with standard itinerary, while tourists had very limited choices and needed to pick one of the itineraries given by operator as there was no other option left for them. Time have changed now as travelers love to plan …
Covid-19 Prediction Using Machine Learning, Parashuram Singaraveni
Covid-19 Prediction Using Machine Learning, Parashuram Singaraveni
Culminating Experience Projects
All around the globe, humankind faces a disastrous situation that witnessed COVID-19 outbreak. The COVID-19 pandemic caused severe loss of human life across the world. Most of the countries had been socially and economically weakened. The health sector faced lots of challenges in diagnosing the COVID patients, vaccinating the people, identifying the people who are infected by the virus. At the earlier stage, it has been difficult to identify the symptoms in infected person that is caused by the virus. Months later, symptoms were identified and, disease detecting machines were invented. But still, time taking for the results from the …
Malware Detection And Analysis, Namratha Suraneni
Malware Detection And Analysis, Namratha Suraneni
Culminating Experience Projects
Malicious software poses a serious threat to the cybersecurity of network infrastructures and is a global pandemic in the form of computer viruses, Trojan horses, and Internet worms. Studies imply that the effects of malware are deteriorating. The main defense against malware is malware detectors. The methods that such a detector employ define its level of quality. Therefore, it is crucial that we research malware detection methods and comprehend their advantages and disadvantages. Attackers are creating malware that is polymorphic and metamorphic and has the capacity to modify their source code as they spread. Furthermore, existing defenses, which often utilize …
Big Data Analytics Of Medical Data, Ashwin Rajasankar
Big Data Analytics Of Medical Data, Ashwin Rajasankar
Culminating Experience Projects
Data has become a huge part of modern decision making. With the improvements in computing performance and storage in the past two decades, storing large amounts of data has become much easier. Analyzing large amounts of data and creating data models with them can help organizations obtain insights and information which helps their decision making. Big data analytics has become an integral part of many fields such as retail, real estate, education, and medicine. In the project, the goal is to understand the working of Apache Spark and its different storage methods and create a data warehouse to analyze data. …
College Job Portal, Harikrishna Gonuguntla
College Job Portal, Harikrishna Gonuguntla
Culminating Experience Projects
Through this project, I am producing a portal called "College Job Portal" that will make life easier for students, colleges, and the companies who hire the students by handling the hiring process. On-campus job placements are a crucial component in contemporary educational institutions. By entering information about their educational history, grades, technological abilities, and CV, students would register with the portal. Like students, companies would sign up with the site by supplying basic details like their address and contact information for human resources. The college would be the portal's administrator. Companies can advertise job openings using this site by including …
Full-Text Search Using Elasticsearch, Akash Shrestha
Full-Text Search Using Elasticsearch, Akash Shrestha
Culminating Experience Projects
Search engines have changed the way we use the internet. They can search or filter out relevant and valuable content of interest to the users. But many of the applications we use today lack search or are just poor. So how can we leverage the same power of search engines in our applications? This project aims to look at “Full-Text Search” which allows us to do a text-based search in text-intensive data. The search will be performed by matching any, or all words of the query exactly or with some relevancy against the indexes created by the searching tool. The …
Docker Container Image – Vulnerability Scanning, Joseph U. Ohaeche
Docker Container Image – Vulnerability Scanning, Joseph U. Ohaeche
Culminating Experience Projects
The technology landscape for container adoption has greatly evolved over the years from the first known Unix U7 container concept introduced in 1979 to the most utilized docker container concept which emerged in 2013. Docker container image is essentially a lightweight, standalone executable software package with capabilities to run an application. It is important to know that container images become containers when deployed, and simultaneously docker container images become docker containers when deployed on Docker Engine. This project paper aims, evaluates, and presents a methodology useful in vulnerability scanning of docker container images and suggests possible fixes based on OWASP …
Lawrence County Archives Website, Brianna Hawkins, Areeb Mohammed, David Niederweis, Mary-Kate Rynders
Lawrence County Archives Website, Brianna Hawkins, Areeb Mohammed, David Niederweis, Mary-Kate Rynders
Honors Capstone Projects and Theses
No abstract provided.
A Maturity Model Of Data Modeling In Self-Service Business Intelligence Software, Anna Kurenkov
A Maturity Model Of Data Modeling In Self-Service Business Intelligence Software, Anna Kurenkov
Master of Science in Information Technology Theses
Although Self-Service Business Intelligence (SSBI) is continually being adopted in various industries, there is a lack of research focused on data modeling in SSBI. This research aims to fill that research gap and propose a maturity model for SSBI data modeling which is generalizeable between different software and applicable for users of all technical backgrounds. Through extensive literature review, a five-tier maturity model was proposed, explained, and instantiated in PowerBI and Tableau. The testing of the model was found to be simple and intuitive, and the research concludes that the model is applicable to enterprise SSBI environments. This research is …
Payload-Byte: A Tool For Extracting And Labeling Packet Capture Files Of Modern Network Intrusion Detection Datasets, Yasir Farrukh, Irfan Khan, Syed Wali, David A. Bierbrauer, John Pavlik, Nathaniel D. Bastian
Payload-Byte: A Tool For Extracting And Labeling Packet Capture Files Of Modern Network Intrusion Detection Datasets, Yasir Farrukh, Irfan Khan, Syed Wali, David A. Bierbrauer, John Pavlik, Nathaniel D. Bastian
ACI Journal Articles
Adapting modern approaches for network intrusion detection is becoming critical, given the rapid technological advancement and adversarial attack rates. Therefore, packet-based methods utilizing payload data are gaining much popularity due to their effectiveness in detecting certain attacks. However, packet-based approaches suffer from a lack of standardization, resulting in incomparability and reproducibility issues. Unlike flow-based datasets, no standard labeled dataset exists, forcing researchers to follow bespoke labeling pipelines for individual approaches. Without a standardized baseline, proposed approaches cannot be compared and evaluated with each other. One cannot gauge whether the proposed approach is a methodological advancement or is just being benefited …