Impact Analysis Of Artificial Intelligence Technology On Employment And Income In China,
Chinese Academy of Sciences
Impact Analysis Of Artificial Intelligence Technology On Employment And Income In China, Yan Lu
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, …
Gambaran Generasi Z Yang Kesepian Dalam Penggunaan Chat Ai Sebagai Pemenuhan Kebutuhan “Someone To Talk”,
Universitas Indonesia
Gambaran Generasi Z Yang Kesepian Dalam Penggunaan Chat Ai Sebagai Pemenuhan Kebutuhan “Someone To Talk”, Ikhwanul Armalid, Febty Arsiwi, Ratri Syahida, Qisthi Fathiyyah
Jurnal Psikologi Sosial
This study aims to understand the experiences of Generation Z individuals who experience loneliness in utilizing Chat AI to fulfill their need for someone to talk to within a socio-emotional context. The study employed a qualitative approach using a phenomenological method involving six Generation Z participants aged 18 to 25 who had used Chat AI for emotional sharing or venting. Data were collected through semi-structured interviews and analyzed using thematic analysis. The thematic analysis yielded six main themes: the dynamics of Generation Z social interactions, experiences of loneliness in social life, patterns of Chat AI usage, Chat AI as a …
Charging Facility Layouts Based On Charging Selection Behavior,
China Simulation Federation
Charging Facility Layouts Based On Charging Selection Behavior, Lixiao Wang, Zhonghui Wang
Journal of System Simulation
Abstract: A charging facility layout method based on charging selection behavior is proposed for the current uncoordinated development of electric vehicles and charging infrastructure and the low utilization of public charging facilities. The influence of the charging selection behavior of electric vehicle users' trips on the charging facility layout is considered, and a charging selection behavior model is built and applied to the charging demand prediction. Based on the study of charging selection behavior and charging demands, a charging facility layout model with the minimization of total travel time as the objective function is built, and the reciprocal feedback between …
Survey On Learning-Based Dynamic Fault Localization: From Traditional Machine Learning To Large Language Models,
Singapore Management University
Survey On Learning-Based Dynamic Fault Localization: From Traditional Machine Learning To Large Language Models
Research Collection School Of Computing and Information Systems
Learning-based dynamic fault localization techniques play a crucial role in the field of software engineering. These techniques dynamically execute test cases to meticulously extract useful knowledge from the execution information in the program, with the aim of identifying fault locations by leveraging machine learning, deep learning, and large language models. Currently, there is already a flourishing body of research that is intensely focused on learning-based dynamic fault localization. Research literature can be categorized into two main aspects for learning-based dynamic fault localization: data-based enhancements (i.e., the datasets) and model-based enhancements (i.e., the suspiciousness algorithms). Thus, we conduct an extensive literature …
How China Leads Global Governance Of Artificial Intelligence: A Sustainable Development Approach Beyond Technological Competition,
Chinese Academy of Sciences
How China Leads Global Governance Of Artificial Intelligence: A Sustainable Development Approach Beyond Technological Competition, Zhenzhen Chen, Xuanming Pan
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 …
Online Control Of Adaptive Large Neighborhood Search Using Deep Reinforcement Learning,
Singapore Management University
Online Control Of Adaptive Large Neighborhood Search Using Deep Reinforcement Learning, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
The Adaptive Large Neighborhood Search (ALNS) algorithm has shown considerable success in solving combinatorial optimization problems (COPs). Nonetheless, the performance of ALNS relies on the proper configuration of its selection and acceptance parameters, which is known to be a complex and resource-intensive task. To address this, we introduce a Deep Reinforcement Learning (DRL) based approach called DR-ALNS that selects operators, adjusts parameters, and controls the acceptance criterion throughout the search. The proposed method aims to learn, based on the state of the search, to configure ALNS for the next iteration to yield more effective solutions for the given optimization problem. …
The Psychological Impacts Of Algorithmic And Ai-Driven Social Media On Teenagers: A Call To Action,
Dakota State University
The Psychological Impacts Of Algorithmic And Ai-Driven Social Media On Teenagers: A Call To Action, John Hastings, Sunil Arora, Sahil Arora
Research & Publications
This study investigates the meta-issues surrounding social media, which, while theoretically designed to enhance social interactions and improve our social lives by facilitating the sharing of personal experiences and life events, often results in adverse psychological impacts. Our investigation reveals a paradoxical outcome: rather than fostering closer relationships and improving social lives, the algorithms and structures that underlie social media platforms inadvertently contribute to a profound psychological impact on individuals, influencing them in unforeseen ways. This phenomenon is particularly pronounced among teenagers, who are disproportionately affected by curated online personas, peer pressure to present a perfect digital image, and the …
Chatgpt In Higher Education: Considerations For Academic Integrity And Student Learning,
Edith Cowan University
Chatgpt In Higher Education: Considerations For Academic Integrity And Student Learning, Andrew Kelly, Miriam Sullivan, Paul Mclaughlan
Research outputs 2022 to 2026
The release of ChatGPT has sparked significant academic integrity concerns in higher education. However, some commentators have pointed out that generative artificial intelligence (AI) tools such as ChatGPT can enhance student learning, and consequently, academics should adapt their teaching and assessment practices to embrace the new reality of living, working, and studying in a world where AI is freely available. Despite this important debate, there has been very little academic literature published on ChatGPT and other generative AI tools. This article uses content analysis to examine news articles (N=100) about how ChatGPT is disrupting higher education, concentrating specifically on Australia, …
Weakly-Supervised Semantic Segmentation With Image-Level Labels: From Traditional Models To Foundation Models,
Singapore Management University
Weakly-Supervised Semantic Segmentation With Image-Level Labels: From Traditional Models To Foundation Models, Qianru Sun, Zhaozheng Chen
Research Collection School Of Computing and Information Systems
The rapid development of deep learning has driven significant progress in image semantic segmentation—a fundamental task in computer vision. Semantic segmentation algorithms often depend on the availability of pixel-level labels (i.e., masks of objects), which are expensive, time consuming, and labor intensive. Weakly supervised semantic segmentation (WSSS) is an effective solution to avoid such labeling. It utilizes only partial or incomplete annotations and provides a cost-effective alternative to fully supervised semantic segmentation. In this article, our focus is on the WSSS with image-level labels, which is the most challenging form of WSSS. Our work has two parts. First, we conduct …
Cooperative Controller Design For Redundant Dual Arm Robot,
China Simulation Federation
Cooperative Controller Design For Redundant Dual Arm Robot
Journal of System Simulation
Abstract: Cooperative operation for a redundant dual arm robot can be divided into three modes, namely, independent mode, full constrained cooperative working mode and partly constrained cooperative working mode. The dynamic equations of both dual arms and the interactions between dual arms and the operating objects were established and derived based on the three modes, and a unified formulation was obtained. With focus on motion and force of the desired task being operated, a unified controller was designed which could be carried out based on two dynamic model based controllers, namely feedforward controller and computer torque controller. Simulations of dual …
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