Databases and Information Systems Commons^™

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

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

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

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 …

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 ., …

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 …

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 …

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 …

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

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

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

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 …

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 …

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 …

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 …

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 …

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 …

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

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

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 …