Computer Sciences Commons^™

Smu Libraries – An Enabling Partner In Ai Information Literacy, Samantha Seah, Zhe Benedict Yeo, Lukas Tschopp

Research Collection Library

SMU Libraries plays a pivotal role in advancing AI information literacy within the larger need for digital literacy skills in the SMU community. In this presentation, participants will get an overview of SMU Libraries' engagement and partnerships with the academic community and will showcase initiatives and resources supporting AI literacy. This includes a discussion of insights from the scholarly literature, research findings and critical perspectives to inform teaching and learning practices related to AI. Speakers will share SMU Libraries’ contributions towards awareness and adoption of AI through a portfolio of successful collaborations and initiatives with partners and stakeholders within and …

Unearthing The Past: A Comprehensive Study Of Natural And Anthropogenic Changes At An Archaeological Site Through Hydrogeologic Connectivity Utilizing Gis, Mehlich Ii Phosphorus Extractant, And Ph, Dana L. F. Herren

Theses

This thesis aims to thoroughly analyze the Mehlich II Phosphorus Extractant and pH levels at the Bains Gap Village Site in Anniston, AL., while examining the impact of various environmental factors and human activities on them. Phosphorus is often used in archaeology as an indicator of human activity. Soil core samples were collected to analyze anomalies in phosphorus levels.

To establish any relationships, phosphorus and pH levels from soil cores were correlated with findings from past excavation units and features. The potential effects of hydrogeologic connectivity on soil phosphorus and pH levels were investigated. Geospatial technologies were used to manage …

Research On Word Segmentation Of Ancient Books Based On Domain Large Language Model, Danhao Zhu, Zhao Zhixiao, Na Wu, Xiyu Wang

Journal of Scientific Information Research

[Purpose/significance]In this paper, we take the automatic text segmentation of ancient books as an entry point, introduce the "Xunzi" series of large language models, and explore the performance of large language models on the task of word division of ancient texts. [Method/process]This paper constructs an instruction dataset based on the Zuozhuan, with data cleaning and organisation.on this basis, 1 000 pieces were extracted from it as test data, then 500, 1 000, 2 000, and 5 000 pieces of data were used as training data to fine-tune the instructions and test their performance, respectively. [Result/conclusion]The experimental results show that only …

Sentiment Analysis Of Online Healthy Community Based On Semantic Enhancement, Pu Han, Ye Dongyu

Journal of Scientific Information Research

[Purpose/significance]In order to make full use of the value of text dependent syntactic information and prior emotion knowledge in emotion analysis， a semantic enhanced online healthy community emotion analysis model was proposed. [Method/process]Firstly， feature vectors for pre-processed online health community data are generated by Word2Vec and BERT; then local and global information of online review text are extracted using TextCNN and BiLSTM respectively based on dual-channel idea; then sentiment knowledge and dependency grammar information are merged in graph attention networks for semantic enhancement; finally， dual-channel features are fused and perform online health community sentiment classification in fully connected layer. [Result/conclusion]The …

Research On The Construction Of Knowledge Graph Of Intangible Cultural Heritage From The Perspective Of Aigc, Yucheng Chen, Li Yang, Jiangfeng Liu, Fan Yang

Journal of Scientific Information Research

[Purpose/significance]Intangible cultural heritage is an important component of human civilization, which is of great significance for protecting and promoting national spirit, enhancing national identity and cohesion. [Method/process]This paper explores how to utilize the advantages of  AIGC, combined with traditional deep learning methods, then construct a comprehensive and efficient map of intangible cultural heritage knowledge. [Result/conclusion]In the classification study of intangible cultural heritage projects, the fine-tuned Baihuan-7B has the best effect, with an macro-F1 value of 0.7688. In the extraction of intangible cultural heritage attribute information, RoBERTa has the best effect, with an F1 value of 0.7085. The …

Objective.Gg: Uniting Scholastic Esports, Douglas Beirne

Posters - 2024

Objective.gg is a startup recruitment platform within the scholastic esports scene that seeks to unite esports prospects with collegiate esports programs in an effective manner. Objective.gg seeks to accomplish its mission by operating an online platform that allows prospects and collegiate coaches to create their own profiles and connect with one another, building a community in the process. This platform will begin with a free tier, but additional features will be offered through a subscription-based model with two additional pricing tiers to choose from. The online platform will be supported by free online and paid in-person tournaments for Objective.gg platform …

Atlas, James P . Clark

Posters - 2024

• Problem: Hard for new gym goers to know how to achieve their goals.
• Motivation: I had a hard time figuring out how to achieve the goals I wanted in the gym. A lot of it was just not knowing what to do or how to do it.
• Solution: I want to create an application that will display some basic information, such as maintenance calories and current weight. It will be able to assist with calculations that need to take place to achieve a certain fitness goal.

My Github Sponsors Profile Is Live!": Investigating The Impact Of Twitter/X Mentions On Github Sponsors, Youmei Fan, Tao Xiao, Hideaki Hata, Christoph Treude, Kenichi Matsumoto

Research Collection School Of Computing and Information Systems

GitHub Sponsors was launched in 2019, enabling donations to opensource software developers to provide financial support, as per GitHub’s slogan: “Invest in the projects you depend on”. However, a 2022 study on GitHub Sponsors found that only two-fifths of developers who were seeking sponsorship received a donation. The study found that, other than internal actions (such as offering perks to sponsors), developers had advertised their GitHub Sponsors profiles on social media, such as Twitter (also known as X). Therefore, in this work, we investigate the impact of tweets that contain links to GitHub Sponsors profiles on sponsorship, as well as …

Lyraquist: Language Learning Via Music App, Vivian D'Souza, Siri Avula, Mahi Patel, Tanvi Singh, Ashley Bickham

Senior Theses

Lyraquist is a new language learning mobile app that encourages the practice of a foreign language through music. Language learners can connect their Spotify Premium account to Lyraquist to listen to music in their target languages and utilize tools such as translation and vocabulary lists to facilitate language practice. Through integration with Spotify, users can import and create Spotify playlists and search the service’s entire catalog. By combining daily listening habits with several tasks associated with language learning in one place, Lyraquist hopes to be a useful language learning tool.

Discovering Significant Topics From Legal Decisions With Selective Inference, Jerrold Tsin Howe Soh

Research Collection Yong Pung How School Of Law

We propose and evaluate an automated pipeline for discovering significant topics from legal decision texts by passing features synthesized with topic models through penalized regressions and post-selection significance tests. The method identifies case topics significantly correlated with outcomes, topic-word distributions which can be manually interpreted to gain insights about significant topics, and case-topic weights which can be used to identify representative cases for each topic. We demonstrate the method on a new dataset of domain name disputes and a canonical dataset of European Court of Human Rights violation cases. Topic models based on latent semantic analysis as well as language …

Editorial: Emerging On-Demand Passenger And Logistics Systems: Modelling, Optimization, And Data Analytics, Jintao Ke, Hai Wang, Neda Masoud, Maximilian Schiffer, Goncalo H. A. Correia

Research Collection School Of Computing and Information Systems

The proliferation of smart personal devices and mobile internet access has fueled numerous advancements in on-demand transportation services. These services are facilitated by online digital platforms and range from providing rides to delivering products. Their influence is transforming transportation systems and leaving a mark on changing individual mobility, activity patterns, and consumption behaviors. For instance, on-demand transportation companies such as Uber, Lyft, Grab, and DiDi have become increasingly vital for meeting urban transportation needs by connecting available drivers with passengers in real time. The recent surge in door-to-door food delivery (e.g., Uber Eats, DoorDash, Meituan); grocery delivery (e.g., Amazon Fresh, …

W4-Groups: Modeling The Who, What, When And Where Of Group Behavior Via Mobility Sensing, Akansha Atrey, Camellia Zakaria, Rajesh Krishna Balan, Prashant Shenoy

Research Collection School Of Computing and Information Systems

Human social interactions occur in group settings of varying sizes and locations, depending on the type of social activity. The ability to distinguish group formations based on their purposes transforms how group detection mechanisms function. Not only should such tools support the effective detection of serendipitous encounters, but they can derive categories of relation types among users. Determining who is involved, what activity is performed, and when and where the activity occurs are critical to understanding group processes in greater depth, including supporting goal-oriented applications (e.g., performance, productivity, and mental health) that require sensing social factors. In this work, we …

Auditory Vigilance Decrement In Drivers Of A Partially Automated Vehicle: A Pilot Study Using A High-Fidelity Driving Simulator, Luca Brooks, Jeffrey Glassman, Yusuke Yamani

Undergraduate Research Symposium

Vigilance decrement is the decline in the ability to monitor and detect behaviorally important signals over time, a phenomenon that can arise even after 30 minutes of watch (Mackworth, 1948). Recently, McCarley & Yamani (2021) found bias shifts, sensitivity losses, and attentional lapses contribute to vigilance decrement, but when each effect is isolated, there was little evidence that sensitivity loss affected vigilance decrement. With the introduction of partially autonomous vehicles, vigilance decrement may be problematic for drivers who must monitor the autonomous system for failures and takeover requests. Thus, this pilot study aims to extend McCarley and Yamani (2021) and …

Improving Educational Delivery And Content In Juvenile Detention Centers, Yomna Elmousalami

Undergraduate Research Symposium

Students in juvenile detention centers have the greatest need to receive improvements in educational delivery and content; however, they are one of the “truly disadvantaged” populations in terms of receiving those improvements. This work presents a qualitative data analysis based on a focus group meeting with stakeholders at a local Juvenile Detention Center. The current educational system in juvenile detention centers is based on paper worksheets, single-room style teaching methods, outdated technology, and a shortage of textbooks and teachers. In addition, detained students typically have behavioral challenges that are deemed "undesired" in society. As a result, many students miss classes …

Icolc Statement On Ai In Licensing, International Coalition Of Library Consortia

Copyright, Fair Use, Scholarly Communication, etc.

The International Coalition of Library Consortia (ICOLC) statement on artifical intelligence in licensing.

Algorithmic Harms In Child Welfare: Uncertainties In Practice, Organization, And Street-Level Decision-Making, Devansh Saxena, Shion Guha

Health Services and Informatics Research

Algorithms in public services such as child welfare, criminal justice, and education are increasingly being used to make high-stakes decisions about human lives. Drawing upon findings from a two-year ethnography conducted at a child welfare agency, we highlight how algorithmic systems are embedded within a complex decision-making ecosystem at critical points of the child welfare process. Caseworkers interact with algo rithms in their daily lives where they must collect information about families and feed it to algorithms to make critical decisions. We show how the interplay between systemic mechanics and algorithmic decision making can adversely impact the fairness of the …

Development Demand, Power Energy Consumption And Green And Low-Carbon Transition For Computing Power In China, Xiaohong Chen, Liaoying Cao, Jiaolong Chen, Jinghui Zhang, Wenzhi Cao, Yangjie Wang

Bulletin of Chinese Academy of Sciences (Chinese Version)

As a critical digital infrastructure, computing power has become the core productivity and a new engine driving economic growth in the digital economy. Nevertheless, the power-hungry nature of computing/data centers, representing the computing infrastructure, consumes a significant amount of electrical energy. Currently, China’s economy is transitioning from high-speed growth to high-quality development. It is imperative to study how to coordinate the development of computing power while ensuring its safety and achieving green and low-carbon goals. Based on an overview of the current status of computing power development, this study predicts the future demand for computing power in China, analyzes the …

Editorials For Spencial Topic “Scientific Focus: Open Source Innovation And Open Source Paradigm”

Bulletin of Chinese Academy of Sciences (Chinese Version)

No abstract provided.

Open Source In China: Opportunities In New Era, Qigang Zhu, Guofeng Zhang, Caihua Zhu, Yi Zhang

Bulletin of Chinese Academy of Sciences (Chinese Version)

China has rapidly experienced industrialization and informatization, entering the era of digital economy. The combination of new productive forces represented by artificial intelligence, non-exclusive production factors represented by knowledge, and open source related relationships may form a new model. From the perspective of social practices of open source innovation, open source lacks systematic preparedness at theoretical, institutional, and talent levels. China should seize the historical opportunity to complete theoretical updates and cultural reconstruction those are adapted to it. Open source and openness also have conditions for China to create a global paradigm of cooperation, sharing, and innovation in the digital …

Thoughts On Ai Innovation And Open Source Development: Lessons From Deepseek, Yanjun Wu

Bulletin of Chinese Academy of Sciences (Chinese Version)

At a critical moment of intense competition in the artificial intelligence (AI) field, DeepSeek has released foundational large language models (LLM) such as V3/R1, with performance comparable to leading international organizations like OpenAI. This not only demonstrates China’s technological innovation capabilities in AI but also provides a Chinese innovative pathway for global AI development. Firstly, through low-cost training and inference, break the monopolistic barriers of high-end computing power and lower research and development thresholds. Secondly, through full-stack and comprehensive open-source strategies, support customizable and local deployment that benefits various industries. This technological innovation and open-source practice from DeepSeek deserves in-depth …

Exploration And Practice Of New Industry-Academia-Research Collaboration Mechanism Based On Open-Source Model, Yungang Bao

Bulletin of Chinese Academy of Sciences (Chinese Version)

DeepSeek has rapidly expanded globally on a large scale through the open-source model, prompting various sectors to reflect on the value and significance of open-source. This study argues that open-source is an effective way to build consensus and organize high-density talent, as it is supported by objective laws. These include sociological principles such as breaking knowledge monopolies and promoting knowledge dissemination, as well as economic principles like “transaction cost” and the “Jevons effect”. Furthermore, this study suggests that open-source is also an effective approach to establish efficient collaborative mechanisms among industry, academia, and research. Two specific cases are introduced—the Open-Source …

Current Status, Trends, And Policy Recommendations For Global Open Source Ecosystem Development, Xue Guo

Bulletin of Chinese Academy of Sciences (Chinese Version)

Open source, as an innovative production model characterized by openness and sharing, has become a core driving force for innovation, openness, sharing, and sustainable development in the digital economy. This study explores the significant value of open source from four dimensions: technological innovation, industrial development, economic contribution, and social sustainability. The current global open source ecosystem is showing a positive development trend, with a continuous increase in the number of open source projects and the scale of contributors. In China, open source efforts are gradually gaining momentum in emerging technology fields. Looking ahead, open source projects are expected to follow …

On Global Security Governance’S New Trends And China’S Responses From Perspective Of Scientific And Technological Revolution, Haoguang Liang, Linman Wu, Zhujun Liu, Yaojun Zhang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Due to the new round of sci-tech revolution and industrial transformation, the relation between scientific progress and national security has been upgraded to an unprecedented strategic height. Therefore, it is vitally important to explore the current situation and future trajectory of the relation between the two. This study discusses the new trends between global scientific progress and the security of sovereign countries. It believes that scientific progress has catalyzed the new geopolitical contests, development contradiction and hegemonic tools in global security governance, thereby enlightening China’s approach to national security. To maintain holistic national security, China should formulate an overall strategic …

Breaking Through “Data Bottleneck” Of Ai Large Models—Reflections On Building A National Corpus Operation Platform, Xingteng Li, Feng Feng, Liqiang Huang

Bulletin of Chinese Academy of Sciences (Chinese Version)

At present, the competition within the global artificial intelligence (AI) large model industry is intensifying, and corpus resources emerging as a critical determinant for enhancing the technical performance and practical efficacy of AI systems. Nevertheless, China’s corpus development faces dual challenges in both quantity and quality, struggling to meet the escalating training demands of the rapidly evolving AI large model sector. Internationally, nations are ramping up efforts to develop their corpus infrastructures, particularly prioritizing the creation and deployment of high-quality linguistic datasets. In this context, through comparative analysis of international benchmarks and domestic conditions, this study proposes a strategic framework …

Challenges On Public Security System In Ai Era—Preface For Special Column “Artificial Intelligence And Public Security”, Juan Cao, Qiang Sheng, Guojie Li

Bulletin of Chinese Academy of Sciences (Chinese Version)

The rapid development of artificial intelligence generated content (AIGC) technology has triggered new public security risks, posing a serious threat to national security and social stability. This study exhibits the recent advances of artificial intelligence (AI) content generation and detection techniques, points out the challenges of detection techniques in real-world scenarios, and advocates that it is necessary to develop AIGC detection technology for public security needs and build a whole-process detection technology system from generative models to online platforms, which supports AIGC to be labeled at the generation phase, identifiable during dissemination and source-traceable after the incident occurs.

Research On Artificial Intelligence Crime And China’S Countermeasures, Jianxin Gao, Jinping Sun, Yukun Cai, Chongpeng Wang, Yanyan Yang, Kaiyue Wang

Bulletin of Chinese Academy of Sciences (Chinese Version)

The rapid development of artificial intelligence technology has constantly given rise to new scenarios, models, and markets, changing the way information and knowledge are generated. Nevertheless, the security risks exposed by technology, such as algorithm bias, data leakage, false content generation, and improper use, are also prone to trigger various new types of crimes. There are still loopholes in legal regulation and technological prevention under the current situation, which poses severe challenges to crime crackdown. In order to effectively meet the new challenges of China’s artificial intelligence (AI) crime, we should supplement and improve the existing legal norms, improve the …

Intelligent Algorithm Safety: Concepts, Scientific Problems And Prospects, Xueqi Cheng, Wei Chen, Huawei Shen, Shiguang Shan, Xilin Chen, Guojie Li

Bulletin of Chinese Academy of Sciences (Chinese Version)

Intelligent algorithms refer to the methods embodied in the computational processes that realize intelligence. These methods are often characterized by being data-driven, involving uncertain computations, and with unexplainable model inferences. These characteristics simultaneously introduce potential safety risks to the application of intelligent algorithms and AI. This study firstly explores the concepts of intelligent algorithm safety. Specifically, intelligent algorithm safety, based on the degree of human-machine integration, extends from the univariate safety of the algorithm itself to the bivariate applicational safety when the algorithm serves humans, and finally evolves into the multivariate systemic safety arises within complex socio-technical systems of human-machine …

Embodied Artificial Intelligence Security And Governance, Wenyuan Xu, Xiaoyu Ji, Chen Yan, Yushi Cheng

Bulletin of Chinese Academy of Sciences (Chinese Version)

Embodied artificial intelligence (EAI) is progressively integrated into the fabric of our daily lives, enhancing various sectors such as industrial production, healthcare, and national defense. Nevertheless, the diverse range of hardware devices, software algorithms, and data communications that constitute these complex systems may contain vulnerabilities that could be exploited by attackers, posing a serious threat to personal, social, and national security. Thus, this study examines the security implications and proposes a security framework of EAI, from the perspectives of the information domain, physical domain, and social domain, focusing on its ontological security, interaction security, and application security. To mitigate these …

Suggestions On Building China’S Artificial Intelligence Open Source Innovation Ecosystem, Yuntao Long, Haibo Liu, Zheping Xu, Yungang Bao, Yanjun Wu

Bulletin of Chinese Academy of Sciences (Chinese Version)

With the release and application of open-source large language models (LLMs) represented by DeepSeek, open-source innovation has played an increasingly important role in the rapid development of global artificial intelligence (AI) technology. Through technological innovation, cost reduction, performance improvement, and application demonstration, DeepSeek has opened up a disruptive innovation path and improved the research and application level of AI in China and its international influence. In order to further promote the construction of China’s AI open source innovation ecosystem and promote the continuous innovation and iteration of AI technology, this study analyzes the outstanding problems in China’s AI innovation ecosystem …

Discussion On Open-Source And Closed-Source Technology Models In Era Of Artificial Intelligence, Xiaolong Zheng, Jiatong Li

Bulletin of Chinese Academy of Sciences (Chinese Version)

This article presents the advantages and disadvantages of open-source and closed-source models in technology innovation and ecosystem construction in the era of artificial intelligence. We explore some current cutting-edge controversies between the two technology models, and puts forward some basic ideas for breaking the deadlock, which can provide some significant insights into promoting the healthy development of artificial intelligence technologies.