Adaptive goal selection for agents in dynamic environments by Zhang, Huiliang, Luo, Xudong, Shen, Zhiqi, You, Jin, Miao, Chun Yan

“…In psychology, goal-setting theory, which has been studied by psychologists for over 35 years, reveals that goals play significant roles in incentive, action and performance for human beings. Based on this theory, a goal net model has been proposed to design intelligent agents that can be viewed as a soft copy of human being somehow. …”
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Emotional and spiritual quotient for sustainable education’s service quality by Mazni, Saad, Norliana, Ahmad Shah, Kamisah, Supian, Anita, Abdul Rani, Imaduddin, Abidin

“…Support for sustainable development goal (SDG-4) via EQ and SQ is now required in humanizing education to ensure academicians’ competency and well-being, particularly in the aftermath of the Corona Virus Disease-19 disruption. …”
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Formal contracts mitigate social dilemmas in multi-agent reinforcement learning by Haupt, Andreas, Christoffersen, Phillip, Damani, Mehul, Hadfield-Menell, Dylan

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Turning trash into treasure: exploring the potential of AI in municipal waste management - an in-depth review and future prospects by El Jaouhari, Asmae, Samadhiya, Ashutosh, Kumar, Anil, Mulat-Weldemeskel, Eyob, Luthra, Sunil, Kumar, Rajesh

“…Rapid urbanization, economic expansion, and population growth have increased waste generation in many nations worldwide. …”
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Geometry guided supervised representation learning for classification by Li, Yue

“…Machine learning is an essential part of artificial intelligence and a useful tool for data mining. Machine learning algorithms learn a mathematical model from the training dataset and use the model to make predictions on the test dataset without using the explicitly programming. …”
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Broadcast Performance Analysis and Improvements of the LTE-V2V Autonomous Mode at Road Intersection by Md. Noor-A-Rahim, G. G. Md. Nawaz Ali, Guan, Yong Liang, Ayalew, Beshah, Chong, Peter Han Joo, Pesch, Dirk

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From distraction to interaction: investigating learner engagement challenges in virtual classrooms by Irfan, Muhammad, Patel, Preeti, Hassan, Bilal

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Investigating fine-tuning of large language models for text summarisation by Khaliq, Usama, Patel, Preeti

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Semantic scene understanding on 3D point clouds by Dong, Shichao

“…With the rapid development of industry and intelligent systems, semantic scene understanding has become essential for robotic vision in smart manufacturing. …”
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Learning driver-specific behavior for overtaking : a combined learning framework by Lu, Chao, Wang, Huaji, Lv, Chen, Gong, Jianwei, Xi, Junqiang, Cao, Dongpu

“…Learning-based methods have gained increasing attention in the intelligent vehicle community for developing highly autonomous vehicles and advanced driving assistance systems (ADAS). …”
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FigurA11y: AI Assistance for Writing Scientific Alt Text by Singh, Nikhil, Wang, Lucy Lu, Bragg, Jonathan

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An integrated framework for multi-state driver monitoring using heterogeneous loss and attention-based feature decoupling by Hu, Zhongxu, Zhang, Yiran, Xing, Yang, Li, Qinghua, Lv, Chen

“…Multi-state driver monitoring is a key technique in building human-centric intelligent driving systems. This paper presents an integrated visual-based multi-state driver monitoring framework that incorporates head rotation, gaze, blinking, and yawning. …”
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Robotic conformal material extrusion 3D printing for appending structures on unstructured surfaces by Armstrong, Connor David, Montgomery, Stuart Macrae, Yue, Liang, Demoly, Frédéric, Zhou, Kun, Qi, Jerry H.

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Spatiotemporal-restricted A∗ algorithm as a support for lane-free traffic at intersections with mixed flows by Chi, Haifei, Cai, Pinlong, Fu, Daocheng, Zhai, Junda, Zeng, Yadan, Shi, Botian

“…However, it is challenging to apply efficient lane-free traffic to be compatible with the traditional intersection control mode for mixed flow composed of CAVs and Human-driving Vehicles (HVs). To address the research gap, this paper proposes a spatiotemporal-restricted A∗ algorithm to obtain efficient and flexible lane-free trajectories for CAVs. …”
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Can industry 5.0 technologies overcome supply chain disruptions? A perspective study on pandemics, war, and climate change issues by Agrawal, Shruti, Agrawal, Rohit, Kumar, Anil, Luthra, Sunil, Garza-Reyes, Jose Arturo

“…Industry 5.0 (I5.0) is the next industrial revolution that will leverage human intervention in collaboration with intelligent, logical, and smart machines to attain even more user-preferred and resource-efficient manufacturing and supply chain solutions. …”
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Renewable energy integration into smart grids : problems and solutions — Singapore experience by Koh, Leong Hai, Tan, Yen Kheng, Wang, Peng, Tseng, King Jet

“…Singapore being a city state with 712.4km2, 5.183million people, S$59,813 Gross Domestic Product (GDP) per capital, population density of 7,126 per square kilometer [1] and limited natural resources, identified her GHG emission as carbon dioxide (CO2) mainly from combustion of fossil fuels and natural gas to generate energy meeting development and human needs. By 2006 highly efficient combined cycle technology was deployed to generate 78% primary energy by burning natural gas [2]. …”
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Employee profiling via aspect-based sentiment and network for insider threats detection by Soh, Charlie, Yu, Sicheng, Narayanan, Annamalai, Duraisamy, Santhiya, Chen, Lihui

“…Existing works mainly focused on modeling the employees’ normal biometric behavior (e.g., human to device interaction pattern) to detect anomalous behavior which corresponds to the insider activity. …”
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Study on the impact of connected automated vehicle position on mixed traffic flow stability by Tan, Kenneth Chiao Wee

“…Because CAVs utilise vehicle controls such as Cooperative Adaptive Cruise Control (CACC) and Adaptive Cruise Control (ACC) while human-driven vehicles (HDV) utilise driving models such as Intelligent Driving Model (IDM), these vehicles controls and models are also being examined in this study. …”
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Goal modelling for deep reinforcement learning agents by Leung, Jonathan, Shen, Zhiqi, Zeng, Zhiwei, Miao, Chunyan

“…As agents become more intelligent, it is necessary to ensure that the agent’s goals are aligned with the goals of the agent designers to avoid unexpected or unwanted agent behavior. …”
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A feedforward neural network based indoor-climate control framework for thermal comfort and energy saving in buildings by Chaudhuri, Tanaya, Soh, Yeng Chai, Li, Hua, Xie, Lihua

“…The study is substantiated with extensive real human experiments in controlled thermal environment. …”
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