Digital Commons Network^™

Venture Capital And Its Role In Facilitating Better Development In China's Artificial Intelligence Industry, Randong Yuan

Bulletin of Chinese Academy of Sciences (Chinese Version)

The venture capital (VC) industry plays a crucial role in advancing the development of the artificial intelligence (AI) sector. As a key bridge between technological innovation and industrialization, VC not only provides financial support to AI startups but also empowers them in strategic planning, technological research and development, and market expansion. However, China's VC industry currently faces several challenges in supporting AI development, including an imbalance in the roles of state-owned and private capital, a short-term investment mindset, and the cyclical phenomenon of "herding" and abrupt market exits. These issues hinder the growth trajectories of Chinese AI enterprises and constrain …

Data Engineering: Building Software Efficiency In Medium To Large Organizations, Alessandro De La Torre

Whittier Scholars Program

The introduction of PoetHQ, a mobile application, offers an economical strategy for colleges, potentially ushering in significant cost savings. These savings could be redirected towards enhancing academic programs and services, enriching the educational landscape for students. PoetHQ aims to democratize access to crucial software, effectively removing financial barriers and facilitating a richer educational experience. By providing an efficient software solution that reduces organizational overhead while maximizing accessibility for students, the project highlights the essential role of equitable education and resource optimization within academic institutions.

Data-Driven Evidence-Based Syntactic Sugar Design, David Obrien, Robert Dyer, Tien N. Nguyen, Hridesh Rajan

School of Computing: Faculty Publications

Programming languages are essential tools for developers, and their evolution plays a crucial role in supporting the activities of developers. One instance of programming language evolution is the introduction of syntactic sugars, which are additional syntax elements that provide alternative, more readable code constructs. However, the process of designing and evolving a programming language has traditionally been guided by anecdotal experiences and intuition. Recent advances in tools and methodologies for mining open-source repositories have enabled developers to make datadriven software engineering decisions. In light of this, this paper proposes an approach for motivating data-driven programming evolution by applying frequent subgraph …

Social Order In Age Of Artificial Intelligence, Yongnian Zheng

Bulletin of Chinese Academy of Sciences (Chinese Version)

While the rapid development of artificial intelligence is empowering society, it is also posing serious threats to the continuation of the traditional social order. The "de-intellectualization" function of AI has given rise to the phenomenon of "artificial ignorance", referring to the self-inflicted intellectual harm caused by the uncontrolled and excessive misuse of AI-related tools, thus causing a profound impact on the social order. The technical structural characteristics and governance structural characteristics of AI contributed to the emergence of the phenomenon of "artificial ignorance". The technical structural characteristics of AI can be summarized as highly concentrated capabilities, highly centralized control, highly …

Impact Analysis Of Artificial Intelligence Technology On Employment And Income In China, Yan Lu, Lincui Gui

Bulletin of Chinese Academy of Sciences (Chinese Version)

With the continuous development of artificial intelligence technology, employment and income in China will undergo some new changes. It is necessary to explore the impact of artificial intelligence technology on employment and income distribution. The study finds that in terms of employment, the impact of artificial intelligence includes redefining the number and nature of jobs, affecting work patterns and work skills, and possibly triggering structural imbalances between supply and demand in the labor market, leading to employment inequality, increasing employment risks. In term of income distribution, artificial intelligence technology has a heterogeneous impact on the initial distribution of different fields, …

Open Governance And Innovation Directions Regulation: Research On Institutional Mechanisms For Promoting Development Of Artificial General Intelligence, Yuhao Jiang, Xinyi Zhang, Mingjie Dai

Bulletin of Chinese Academy of Sciences (Chinese Version)

In the field of artificial intelligence development, there is still a certain gap between China and the United States. The uncertain future of artificial general intelligence (AGI) decides that China should not only implement the "catch-up" strategy. Artificial intelligence is not a ‘linear innovation' development path, but there is overlap between basic research, applied research, and industrial transformation. This feature of innovation shows that diversified exploration can be realized based on tracking of international frontiers, breakthrough of basic research, and satisfaction of diverse application needs. China needs to adhere to the promotion of open governance, and regulate innovation directions of …

Study On Constraints And Policy Responses For Production And Circulation Of Ai Training Data In China, Tao Lin

Bulletin of Chinese Academy of Sciences (Chinese Version)

The quantity and quality of training data are critical to the performance of artificial intelligence (AI) models. However, in China, the production of training data is hindered by issues such as insufficient quantity, low quality, and fragmented distribution, compounded by limitations stemming from commercial ecosystems, regulatory frameworks, and restricted development and utilization of public data. To address these challenges, this study proposes several policy recommendations, including incentivizing research institutions to generate open-source datasets, fostering AI application scenarios, adopting a "loose-in, focus-out" regulatory approach, introducing intellectual property exemption provisions, refining personal information protection guidelines, and expediting the establishment of a unified …

New System For Mobilizing Resources Nationwide To Promote Leapfrog Development Of Innovation Ecosystem Of Artificial Intelligence Enterprises: Mechanisms, Problems And Strategies, Yang Mei, Hao Niu, Han Jiang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Facing the unpredictable new features of top-down AI technological innovation and the new requirements on functions, this study proposes to re-examine the technological innovation of AI at the enterprise level from the perspective of the "a new system for mobilizing the resources nationwide" and with the enterprise innovation ecosystem as the carrier. On the basis of explaining the elements and operation logic of the new system at the enterprise level, compared to the "implicit national system" of the US, this study preliminarily compares the new system of AI in China and that in the US. It is proposed that the …

How China Leads Global Governance Of Artificial Intelligence: A Sustainable Development Approach Beyond Technological Competition, Xuanming Pan, Zhenzhen Chen, Shaoshan Liu

Bulletin of Chinese Academy of Sciences (Chinese Version)

In the context of great power competition and escalating geopolitical conflicts, the academic community generally holds a pessimistic view of AI international cooperation, believing that the space is shrinking. This perception mainly stems from conflicts in the cross-border supervision of AI data and algorithms among technologically advanced countries, while overlooking the strong willingness and potential for cooperation in energy conservation and emission reduction through AI technologies shown by Global South countries. Looking into the future of global governance, China, starting from leading the transformation of AI technologies, shall take lead in supporting these countries to transform the sustainable development consensus …

U.S.-Europe Artificial Intelligence Regulatory Cooperation, Divergence, And China's "Window Of Opportunity" For Strategic Breakthrough, Yang Mei, Jing Zeng, Yong Zhan

Bulletin of Chinese Academy of Sciences (Chinese Version)

The United States, Europe, and China have adopted completely different technological development paths in the era of artificial intelligence innovation, forming a model division of "development-driven governance", "stringent governance framework", and "coordinated governance model" The United States and Europe have respectively set strategic goals as "maintaining technological hegemony" and "competing for the soft power of international rules", forming an interactive model in which institutional supervision and industry independence parallel, and cooperation needs and policy divergence coexist. China has contributed a unique technological governance logic of "people-oriented" and "moral-oriented". Faced with the current technological "window of opportunity", China should adopt two …

Ai-Powered Learning: Blending Ai With Active Learning In The Information Literacy Classroom, Kevin J. Reagan, Wilhelmina Randtke

Georgia International Conference on Information Literacy

In 2016, the ACRL Framework for Information Literacy in Higher Education launched in response to more voluminous, less-vetted online information, including misinformation and content farms. Subsequently, the ACRL Framework has been widely adopted, and numerous high-quality lesson plans and resources for teaching the frames already exist, including published lesson plans and textbooks. Now, generative AI tools, such as ChatGPT and other chat bots present new challenges for information literacy educators. For instance, in addition to teaching students how to identify issues such as fake news, the information literacy professional has to address topics such as ethical AI use, AI hallucination …

Cybersecurity Continuous Learning Towards Fulfilling National Cybersecurity Strategic Plan Mandates, Saleh Hamad Aldaajeh

Thesis/ Dissertation Defenses

This dissertation delves into enhancing cybersecurity education by aligning academic curricula with national cybersecurity strategic plan (NCSP) objectives, emphasizing the crucial role of Higher Education Institutions (HEIs) in developing a skilled cybersecurity workforce. Analyzing ten NCSPs, it identifies strategic themes and gaps between national goals and HEI offerings. The study reviews NCSP guidelines, international cybersecurity indices, and literature, including the NICE-NIST framework, to develop a framework that bridges the educational gap, improving learning outcomes and arming students with vital skills, knowledge, and competencies. Furthermore, it introduces a platform for continuous cybersecurity learning, employing micro-credentials, blockchain technology, and AI-driven systems. Based …

Andrews University Pre-Professional Students Preparedness For A Future With Artificial Intelligence, Zachary Alignay

Honors Theses

Artificial Intelligence technology has advanced considerably over the past four years. With such rapid technological development, the question has to be asked if students are adequately educated on the implications and abilities of artificial intelligence. Are Andrews University pre-professional students prepared for future careers with artificial intelligence? To approach this question, a survey of students across multiple perspectives was conducted to sample if there was a consensus, or lack thereof, on the perception of ethics regarding artificial intelligence, to ask students how using artificial intelligence has changed their education, what purposes it can be used or cannot be used, personal …

Subject Analysis Ex Machina: Developing A Subject Heading Recommendation Service For Jmu Libraries, Steven W. Holloway

Libraries

Results of a 2022 evaluation of ANNIF, open-source software designed to generate controlled vocabulary subject headings, using James Madison University Libraries resources.

A Design Science Approach To Investigating Decentralized Identity Technology, Janelle Krupicka

Cybersecurity Undergraduate Research Showcase

The internet needs secure forms of identity authentication to function properly, but identity authentication is not a core part of the internet’s architecture. Instead, approaches to identity verification vary, often using centralized stores of identity information that are targets of cyber attacks. Decentralized identity is a secure way to manage identity online that puts users’ identities in their own hands and that has the potential to become a core part of cybersecurity. However, decentralized identity technology is new and continually evolving, which makes implementing this technology in an organizational setting challenging. This paper suggests that, in the future, decentralized identity …

A Research Proposal Investigating The Geopolitical And Economic Impact Resulting From The Development Of Artificial General Intelligence (Agi), Tobia Donadon, Kristen Migliano

Student Publications and Presentations

Artificial General Intelligence (AGI) represents the next step in the development of AI, a huge step in the quest for artificial intelligence. AGI aims to create machines capable of understanding, learning, and applying knowledge across various tasks, much like humans.

This research proposal focuses on advancements and potential effects, with an objective to bridge the gap between narrow AI applications and the broader cognitive capabilities of AGI. This study explores the transformative potential of AGI while addressing the societal impacts. The research looks into the relationship between the development of AGI and geopolitical affairs.

Drawing on recent discoveries in mathematical …

Ai’S Carbon Shadow: An Exploration Of The Energy Dilemma And Earth’S Future, Olga Roussos

Student Publications and Presentations

As artificial intelligence continues to advance, more processing power and energy usage are required. This increase in energy consumption by AI leads to increased carbon emissions in the atmosphere as well as rapid resource depletion. The effects of AI’s growing energy consumption can have severe negative impacts on global climate, biodiversity, sustainability, and other aspects of the environment. This research aims to highlight the volume of energy that artificial intelligence uses, the expected environmental effects of artificial intelligence’s expansion, as well as the potential innovative solutions and sustainable practices that can be implemented to decrease energy usage and preserve the …

Sign-A-Mander: A Mobile App That Enhances Asl Learning With Computer Vision, Sandrine Adap

Honors Theses

Several machine learning researchers have developed algorithms recognizing American Sign Language (ASL), but few have applied the algorithms to real-world situations, such as with portable ASL learning applications. This project develops a beta version of a mobile application designed to allow beginner ASL learners to practice basic ASL vocabulary and receive feedback about their signing accuracy. Building on Dongxu Li et al.’s I3D sign language recognition algorithm and 2000-word dataset, the app seeks to determine whether the I3D algorithm can sufficiently recognize a user’s motions when recorded from a mobile device and accurately classify whether or not the user signed …

Implementation Of Python Based High Voltage Tests For Gem Detectors, John Paul Hernandez

Aerospace, Physics, and Space Science Student Publications

The Compact Muon Solenoid, CMS, and other detectors at LHC are in the process of being upgraded for the HL-LHC (High-Luminosity Large Hadron Collider) which will produce more than 5 times the particle interactions than of the current LHC. One upgrade to CMS is the introduction of new GEM detectors (Gaseous Electron Multiplier), GE2/1 and ME0 shown at right are new detectors to CMS and therefore must be tested thoroughly prior to being installed.

Use Of Deep Learning In Content-Based Image Retrieval (Cbir), Angelina Das

ATU Scholars Symposium

In the world of computer vision and data retrieval, a crucial task is finding images within a database based on their visual content. This is known as content-based image retrieval (CBIR). As the number of digital images explodes across fields like online shopping, healthcare, and social media, the need for powerful and precise CBIR systems becomes ever more critical. Early CBIR methods depended on features crafted by hand, like color distributions, texture descriptions, and shape characteristics. However, these techniques often have difficulty capturing the true meaning of an image and might not handle very large datasets effectively. With the rise …

Optimizing Keyboard Layouts For English Text, David Sommerfield

Research & Creative Achievement Day

QWERTY has been the de facto layout for English text input since its invention in 1874. Its continued usage has led to concerns about its ergonomic shortcomings. Previous attempts at layout creation have usually relied on manual observations of typing data rather than a predictive model. To address this issue, we propose a methodology that incorporates both corpus data from 22 million English websites and 8,228 hours of real-world typing data from participants. The corpus data is processed into bigrams and their number of occurrences. The typing data is preprocessed to exclude user-made typos, and then each bigram is tabulated …

Binder, Tyler A. Peaster, Lindsey M. Davenport, Madelyn Little, Alex Bales

ATU Scholars Symposium

Binder is a mobile application that aims to introduce readers to a book recommendation service that appeals to devoted and casual readers. The main goal of Binder is to enrich book selection and reading experience. This project was created in response to deficiencies in the mobile space for book suggestions, library management, and reading personalization. The tools we used to create the project include Visual Studio, .Net Maui Framework, C#, XAML, CSS, MongoDB, NoSQL, Git, GitHub, and Figma. The project’s selection of books were sourced from the Google Books repository. Binder aims to provide an intuitive interface that allows users …

Jsper (Just Stablediffusion Plus Easy Retraining), Adam Rusterholz, Meghan Finn, Zach Zolliecoffer, Zach Judy

ATU Scholars Symposium

JSPER is an an AI art generation Web Application that is both flexible and accessible. Our goal is to enable anyone to create and use their own customized art models, regardless of technical skill level. These models can be trained on almost anything, from a person, to an animal, to a specific object, or even style. The user only has to upload a handful of images of their subject. Then, training settings get optimized at the push of a button to match the type of subject the user is training. After training, their customized model can be used to generate …

Optimizing Campus Chat-Bot Experience Using Puaa: Integrating Large Language Model (Llm) Into University Ai Assistants, Sijan Panday, Zurab Sabakhtarishvili, Clayton Jensen

ATU Scholars Symposium

The advent of large language models (LLMs) such as Chat-GPT and Bard marks a significant milestone in knowledge acquisition, offering a streamlined alternative to the traditionally labor-intensive process of navigating through multiple checkpoints on the web. This emerging trend in LLMs renders the prevalent rule-based chatbots, commonly utilized by universities, increasingly outdated and subpar. This research project proposes integrating LLM technology into university websites, specifically targeting the needs of students seeking information about their institutions by introducing PUAA (Personal University AI Assistant). Our approach involves using the Retrieval-Augmented Generation (RAG) framework, leveraging the capabilities of the LlamaIndex in conjunction with …

Techniques To Detect Fake Profiles On Social Media Using The New Age Algorithms – A Survey, A K M Rubaiyat Reza Habib, Edidiong Elijah Akpan

ATU Scholars Symposium

This research explores the growing issue of fake accounts in Online Social Networks [OSNs]. While platforms like Twitter, Instagram, and Facebook foster connections, their lax authentication measures have attracted many scammers and cybercriminals. Fake profiles conduct malicious activities, such as phishing, spreading misinformation, and inciting social discord. The consequences range from cyberbullying to deceptive commercial practices. Detecting fake profiles manually is often challenging and causes considerable stress and trust issues for the users. Typically, a social media user scrutinizes various elements like the profile picture, bio, and shared posts to identify fake profiles. These evaluations sometimes lead users to conclude …

Spoton, Corey A. Naegle, Caleb Mcclure, Chase M. Tallon, Holden J. O'Neal

ATU Scholars Symposium

SpotOn is a project developed to solve problems with owners losing their pets. The project is in short a solar-powered dog harness with GPS capability with its own application for mobile devices.

Enhancing R2l Intrusion Detection Using Decision Trees, Stephen Sommer

Research & Creative Achievement Day

In the age of advancing technology, artificial intelligence, and big data, Remote to Local (R2L) attacks are increasingly threatening cloud computing environments, heightening concerns about security and privacy. Intrusion detection systems (IDS) using Artificial Intelligence play a role in safeguarding data integrity within databases by swiftly identifying and isolating suspicious records. Furthermore, machine learning techniques enhance the effectiveness of these IDS by continuously adapting to new attack patterns and improving accuracy. This research investigates the use of Decision Tree, a Machine Learning Algorithm for enhancing Remote to Local (R2L) intrusion detection capabilities, utilizing the KDD Cup 1999 dataset and the …

Genetic Association In Entylia Carinata Using Random Forest Classification, Caden J. Harper

Research & Creative Achievement Day

The goal of this research was to identify locations in the genome of the Entylia carinata, known as the treehopper, that are associated with anomalous behavior exhibited by the species. Treehoppers are phytophagous insects and are shown to feed, reproduce, and rear their young on specific aster species. Observation has shown that the insects will disregard potential mates in close proximity in favor of those that originate from the same plant species as themselves. This behavior suggests genetic separation in the species based on plant nativity and warrants genetic analysis. Machine learning offers an effective genetic association technique due to …

Anomaly Detection With Spiking Neural Networks (Snn), Shruti Bhandari, Vyshnavi Gogineni

ATU Scholars Symposium

Abstract:

Anomaly detection, the identification of rare or unusual patterns that deviate from normal behavior, is a fundamental task with wide-ranging applications across various domains. Traditional machine learning techniques often struggle to effectively capture the complex temporal dynamics present in real-world data streams. Spiking Neural Networks (SNNs), inspired by the spiking nature of biological neurons, offer a promising approach by inherently modeling temporal information through precise spike timing. In this study, we investigate the use of Spiking Neural Networks (SNNs) for detecting anomalies or unusual patterns in data. We propose an SNN model that can learn what constitutes normal …

Innovating Inventory And Alert Systems With Object Tracking, Juan Harmse, Esther Peden

Campus Research Month

Security system users require safeguarding inventory from potential theft while reducing manual tracking of physical objects. Our contribution harnesses the power of artificial intelligence and computer vision with YOLO to automate the process of tracking inventory items. The system sends alerts to the inventory manager when it detects particular events. Our approach was evaluated with KernProf profiling, interference, and orientation tests. The results were overall positive in these testing areas.