Aspect Sentiment Triplet Extraction Incorporating Syntactic Constituency Parsing Tree And Commonsense Knowledge Graph,
2022
Singapore Management University
Aspect Sentiment Triplet Extraction Incorporating Syntactic Constituency Parsing Tree And Commonsense Knowledge Graph, Zhenda Hu, Zhaoxia Wang, Yinglin Wang, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
The aspect sentiment triplet extraction (ASTE) task aims to extract the target term and the opinion term, and simultaneously identify the sentiment polarity of target-opinion pairs from the given sentences. While syntactic constituency information and commonsense knowledge are both important and valuable for the ASTE task, only a few studies have explored how to integrate them via flexible graph convolutional networks (GCNs) for this task. To address this gap, this paper proposes a novel end-to-end model, namely GCN-EGTS, which is an enhanced Grid Tagging Scheme (GTS) for ASTE leveraging syntactic constituency parsing tree and a commonsense knowledge graph based on …
Prompting For Multimodal Hateful Meme Classification,
2022
Singapore Management University
Prompting For Multimodal Hateful Meme Classification, Rui Cao, Roy Ka-Wei Lee, Wen-Haw Chong, Jing Jiang
Research Collection School Of Computing and Information Systems
Hateful meme classification is a challenging multimodal task that requires complex reasoning and contextual background knowledge. Ideally, we could leverage an explicit external knowledge base to supplement contextual and cultural information in hateful memes. However, there is no known explicit external knowledge base that could provide such hate speech contextual information. To address this gap, we propose PromptHate, a simple yet effective prompt-based model that prompts pre-trained language models (PLMs) for hateful meme classification. Specifically, we construct simple prompts and provide a few in-context examples to exploit the implicit knowledge in the pretrained RoBERTa language model for hateful meme classification. …
Expressiveness Of Real-Time Motion Captured Avatars Influences Perceived Animation Realism And Perceived Quality Of Social Interaction In Virtual Reality,
2022
Edith Cowan University
Expressiveness Of Real-Time Motion Captured Avatars Influences Perceived Animation Realism And Perceived Quality Of Social Interaction In Virtual Reality, Alan D. Fraser, Isabella Branson, Ross C. Hollett, Craig P. Speelman, Shane L. Rogers
Research outputs 2022 to 2026
Using motion capture to enhance the realism of social interaction in virtual reality (VR) is growing in popularity. However, the impact of different levels of avatar expressiveness on the user experience is not well understood. In the present study we manipulated levels of face and body expressiveness of avatars while investigating participant perceptions of animation realism and interaction quality when disclosing positive and negative experiences in VR. Moderate positive associations were observed between perceptions of animation realism and interaction quality. Post-experiment questions revealed that many of our participants (approximately 40 %) indicated the avatar with the highest face and body …
Conversation Disentanglement With Bi-Level Contrastive Learning,
2022
National University of Singapore
Conversation Disentanglement With Bi-Level Contrastive Learning, Chengyu Huang, Zheng Zhang, Hao Fei, Lizi Liao
Research Collection School Of Computing and Information Systems
Conversation disentanglement aims to group utterances into detached sessions, which is a fundamental task in processing multi-party conversations. Existing methods have two main drawbacks. First, they overemphasize pairwise utterance relations but pay inadequate attention to the utterance-to-context relation modeling. Second, a huge amount of human annotated data is required for training, which is expensive to obtain in practice. To address these issues, we propose a general disentangle model based on bi-level contrastive learning. It brings closer utterances in the same session while encourages each utterance to be near its clustered session prototypes in the representation space. Unlike existing approaches, our …
Scalable Distributional Robustness In A Class Of Non Convex Optimization With Guarantees,
2022
Singapore Management University
Scalable Distributional Robustness In A Class Of Non Convex Optimization With Guarantees, Avinandan Bose, Arunesh Sinha, Tien Mai
Research Collection School Of Computing and Information Systems
Distributionally robust optimization (DRO) has shown lot of promise in providing robustness in learning as well as sample based optimization problems. We endeavor to provide DRO solutions for a class of sum of fractionals, non-convex optimization which is used for decision making in prominent areas such as facility location and security games. In contrast to previous work, we find it more tractable to optimize the equivalent variance regularized form of DRO rather than the minimax form. We transform the variance regularized form to a mixed-integer second order cone program (MISOCP), which, while guaranteeing near global optimality, does not scale enough …
Interventional Training For Out-Of-Distribution Natural Language Understanding,
2022
Singapore Management University
Interventional Training For Out-Of-Distribution Natural Language Understanding, Sicheng Yu, Jing Jiang, Hao Zhang, Yulei Niu, Qianru Sun, Lidong Bing
Research Collection School Of Computing and Information Systems
Out-of-distribution (OOD) settings are used to measure a model’s performance when the distribution of the test data is different from that of the training data. NLU models are known to suffer in OOD settings (Utama et al., 2020b). We study this issue from the perspective of causality, which sees confounding bias as the reason for models to learn spurious correlations. While a common solution is to perform intervention, existing methods handle only known and single confounder, but in many NLU tasks the confounders can be both unknown and multifactorial. In this paper, we propose a novel interventional training method called …
Vr Computing Lab: An Immersive Classroom For Computing Learning,
2022
Singapore Management University
Vr Computing Lab: An Immersive Classroom For Computing Learning, Shawn Pang, Kyong Jin Shim, Yi Meng Lau, Swapna Gottipati
Research Collection School Of Computing and Information Systems
In recent years, virtual reality (VR) is gaining popularity amongst educators and learners. If a picture is worth a thousand words, a VR session is worth a trillion words. VR technology completely immerses users with an experience that transports them into a simulated world. Universities across the United States, United Kingdom, and other countries have already started using VR for higher education in areas such as medicine, business, architecture, vocational training, social work, virtual field trips, virtual campuses, helping students with special needs, and many more. In this paper, we propose a novel VR platform learning framework which maps elements …
Towards Reinterpreting Neural Topic Models Via Composite Activations,
2022
Singapore Management University
Towards Reinterpreting Neural Topic Models Via Composite Activations, Jia Peng Lim, Hady Wirawan Lauw
Research Collection School Of Computing and Information Systems
Most Neural Topic Models (NTM) use a variational auto-encoder framework producing K topics limited to the size of the encoder’s output. These topics are interpreted through the selection of the top activated words via the weights or reconstructed vector of the decoder that are directly connected to each neuron. In this paper, we present a model-free two-stage process to reinterpret NTM and derive further insights on the state of the trained model. Firstly, building on the original information from a trained NTM, we generate a pool of potential candidate “composite topics” by exploiting possible co-occurrences within the original set of …
S-Prompts Learning With Pre-Trained Transformers: An Occam's Razor For Domain Incremental Learning,
2022
Singapore Management University
S-Prompts Learning With Pre-Trained Transformers: An Occam's Razor For Domain Incremental Learning, Yabin Wang, Zhiwu Huang, Xiaopeng. Hong
Research Collection School Of Computing and Information Systems
State-of-the-art deep neural networks are still struggling to address the catastrophic forgetting problem in continual learning. In this paper, we propose one simple paradigm (named as S-Prompting) and two concrete approaches to highly reduce the forgetting degree in one of the most typical continual learning scenarios, i.e., domain increment learning (DIL). The key idea of the paradigm is to learn prompts independently across domains with pre-trained transformers, avoiding the use of exemplars that commonly appear in conventional methods. This results in a win-win game where the prompting can achieve the best for each domain. The independent prompting across domains only …
Transmission Line Insulator Recognition Based On Artificial Images Data Expansion,
2022
1.Department of Automation, North China Electric Power University, Baoding 071003, China;
Transmission Line Insulator Recognition Based On Artificial Images Data Expansion, Yaru Wang, Kai Yang, Yongjie Zhai, Congbin Guo, Wenqing Zhao, Jie Su
Journal of System Simulation
Abstract: Deep learning method has developed rapidly in the field of computer vision, but relies on a large quantities of training data. In the task of transmission line insulator automatic detection, problems such as insufficient number of aerial insulator images and poor diversity affect the accuracy of insulator recognition. An artificial insulator images data expansion method is proposed. Artificial insulator images are created by modeling software, and a compensation network is constructed. The artificial images are compensated and optimized by compensation network, and the aerial insulator image data set is expanded by the compensated artificial insulator images. The insulator recognition …
Nonlinear System Identification Based On Combined Signal Sources,
2022
1.College of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou 213001, China;
Nonlinear System Identification Based On Combined Signal Sources, Tian Zheng, Feng Li, Naibao He, Ya Gu
Journal of System Simulation
Abstract: Aiming at the interference of noise in the nonlinear system, the identification modeling method of the neuro-fuzzy Hammerstein output error nonlinear system is considered. The combined signal sources are used to realize the parameter identification separation of the linear block and the nonlinear block. The correlation analysis method and the recursive least square identification method based on auxiliary model technique are derived to estimate the parameters of dynamic linear block and nonlinear block, which can effectively suppress the interference of system output noise. Compared with least square algorithm, polynomial model and multi-innovation method, the simulation results demonstrate that the …
Multi-Market Coupling Trading Simulation Of Electricity Green Certificate And Excess Consumption Under New Renewable Portfolio Standard,
2022
1.North China Electric Power University, Beijing 102206, China;2.Beijing Key Laboratory of New Energy and Low-Carbon Development (North China Electric Power University), Beijing 102206, China;
Multi-Market Coupling Trading Simulation Of Electricity Green Certificate And Excess Consumption Under New Renewable Portfolio Standard, Peng Wang, Xiaohua Song, Haowen Yang, Xiaoying Zhai, Jingjing Han, Liwei Ju
Journal of System Simulation
Abstract: In order to clarify the multi-scale market coupling interaction relationship of electricity, green certificate, excess consumption under the renewable portfolio standards (RPS), the system dynamics is introduced, and the interactive trading model is constructed and simulated. Taking the logistics transformation of three market transaction targets as the clue, this paper designs a multi-scale market coupling transaction framework, constructs the complex causality of coupling transaction based on system dynamics method, and analyzes the impact of RPS on the revenue or cost of market participants. Simulation results show that under the new RPS, the electricity price will gradually decline, the …
Research On Key Technology Of Uavs Autonomous Landing Based On Relative Precise Point Position,
2022
School of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;
Research On Key Technology Of Uavs Autonomous Landing Based On Relative Precise Point Position, Guohua Kang, Teng Zhao, Yao Fu, Weizheng Xu, Jianyu Wei, Yuhuan Qiu, Junfeng Wu
Journal of System Simulation
Abstract: In complex sea conditions with wind and waves, the relative motion between unmanned aerial vehicles (UAVs) requiring autonomous landing and ships is highly uncertain. In order to improve the accuracy of relative positioning and control during autonomous landing, and to ensure the safety and reliability of autonomous landing, a relative precise point positioning (RPPP) technique based on differential tropospheric error is proposed. The technology only relies on data link and carrier satellite positioning receiver to eliminate the same error of satellite positioning in the same environment and obtain accurate relative positioning. The combination of proportional navigation and linear quadratic …
Research On Network Public Opinion Transmission Mechanism Of Inversion Event Based On Integrating Improved Sir Model,
2022
School of Business, Jiangnan University, Wuxi 214122, China;
Research On Network Public Opinion Transmission Mechanism Of Inversion Event Based On Integrating Improved Sir Model, Jianrong Tang, Jiatong Bao
Journal of System Simulation
Abstract: In order to identify the spreading rules of rumors in vicious news reversal events and make more targeted guiding decisions, a short-term prediction model is proposed to simulate the spread of virus information. This paper improves the traditional susceptible infected removed (SIR) model and solves the problem that the conversion rate is fixed and single due to the limitation of Markov chain when it is combined with systems dynamics (SD) model. The data is validated with the example of "asthmatic girls" . The results show that the model not only effectively simulates the crisis of public opinion communication in …
A Wind Turbine Fault Diagnosis Method Based On Siamese Deep Neural Network,
2022
College of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China;
A Wind Turbine Fault Diagnosis Method Based On Siamese Deep Neural Network, Jiarui Liu, Guotian Yang, Xiaowei Wang
Journal of System Simulation
Abstract: In order to effectively extract the fault features of time series data in supervisory control and data acquisition (SCADA), considering the advantages of one-dimensional convolutional neural network (1-D CNN) for extracting local time series features and the advantages of long-term memory (LSTM) which can extract long-term dependent features, a method for fault diagnosis of wind turbines based on 1-D CNN-LSTM is proposed. To solve the problem of the scarcity of fault samples of wind turbines based on the siamese network architecture, a wind fault diagnosis method based on siamese 1-D CNN-LSTM is proposed. The proposed siamese 1-D CNN-LSTM …
Multi-Uav Trajectory Planning Based On Adaptive Segmented Potential Field Method,
2022
School of Information Engineering, Nanchang Hang Kong University, Nanchang 330063, China;
Multi-Uav Trajectory Planning Based On Adaptive Segmented Potential Field Method, Guangjian Tian, Jiyang Dai, Jin Ying, Ning Wang
Journal of System Simulation
Abstract: To solve the problems that the traditional artificial potential field method is prone to fall into the local extreme value, target unreachability and excessive curvature of the planned trajectory curvature in the application of UAV trajectory planning, on the basis of the layered potential field method, a method of adding a second local attractive field at the target point and an attractive set composed of the target attractive field is proposed. This method overcomes the defects of unreachable targets and easy falling into local extremes. In addition, a piecewise function is introduced into the original layered potential field method, …
Robust Optimal Configuration Of Pv-Energy Storage In Industrial Parks Considering The Uncertainty Of Photovoltaics,
2022
1.State Grid Beijing Haidian Electric Power Supply Company, Beijing 100195, China;
Robust Optimal Configuration Of Pv-Energy Storage In Industrial Parks Considering The Uncertainty Of Photovoltaics, Guiting Xue, Boya Shan, Ti Wang, Xiao Wang, Wei Xing, Weiqing Sun
Journal of System Simulation
Abstract: Research on using rooftop resources in industrial parks to develop photovoltaic projects and reasonable configuration of energy storage will help improve the park's energy economy. To obtain the optimal PV-storage configuration scheme, an industrial park with three types of load demand, namely, cold, heat and electricity, is selected, and a robust optimization allocation model of park PV-storage is established with optimal operating profit as the objective function, considering the increased cost of power purchase caused by the PV uncertainty. The model uses the box uncertainty set in robust optimization for PV intensity, and linearizes the model using pairwise …
Evacuation Model Considering The Restricted View Of The Sign,
2022
1.China Center for Emergency Management Research, Wuhan University of Technology, Wuhan 430070, China;2.School of Safety Science and Emergency Management, Wuhan University of Technology, Wuhan 430070, China;
Evacuation Model Considering The Restricted View Of The Sign, Yinghua Song, Zheqian Zhang, Feizhou Huo, Danhui Fang
Journal of System Simulation
Abstract: In order to study the influence of restricted vision on the process of pedestrian evacuation, a cellular automata model of pedestrian evacuation under restricted vision is established. In the model, the evacuation space is divided into three different areas according to the field of view radius, pedestrians have different ways of moving in different areas. Different income parameters are defined to calculate the pedestrian movement income matrix and determine the target position of the pedestrian in the next time step. An evacuation scene is established to simulate the initial density of different pedestrians, the change of the field of …
A Real-Time Ultrasound Simulation Platform Using Ray Tracing And Its Integration With Virtual Reality,
2022
1.School of Computer Science, Southwest Petroleum University, Chengdu 610500, China;2.Dept. of Echo-cardiology and Non-invasive Cardiology, Sichuan Academy of Medical Science, Sichuan Provincial People's Hospital, Chengdu 610072, China;3.Sichuan Academy of Medical Sciences·Sichuan Provincial People's Hospital, Sichuan Provincial Key Laboratory of Echocardiography and Biomechanics, Chengdu 610072, China;
A Real-Time Ultrasound Simulation Platform Using Ray Tracing And Its Integration With Virtual Reality, Bo Peng, Qiang Wang, Ruibing Qing, Lixue Yin, Jingfeng Jiang
Journal of System Simulation
Abstract: In order to further improve the efficacy of ultrasound training and reduce the cost. An ultrasound training system that is integrated with a VR environment is developed. The main contribution of this study is to incorporate the Ray-tracing based ultrasound image simulation approach into a virtual reality environment, taking advantage of immersive VR experience for medical ultrasound training. The simulated ultrasound images obtained by the proposed method are then compared to images that are simulated using a generative adversarial network (GAN) technique and Field II ultrasound simulator. The data show that the ultrasound simulator can produce high-quality simulated …
Design And Simulation-Based Evaluation Of Taxiway Operation Scheme For Multi-Runway Airport Maneuvering Area,
2022
Civil Aviation Flight University of China, Guanghan 618300, China;
Design And Simulation-Based Evaluation Of Taxiway Operation Scheme For Multi-Runway Airport Maneuvering Area, Xinping Zhu, Chuan Xu, Jingjing Qu, Tingwen Su
Journal of System Simulation
Abstract: The operational scheme of the taxiway system is very important to promote the efficient utilization of airfield resources in multi-runway airports. The design and simulation evaluation methods of the taxiway operation scheme for multi-runway airports are studied. The design principles of "fixed, unidirectional, compliant and circular" taxiway operation scheme and the design paradigm of the operation scheme are presented, and the concepts of taxiway space occupancy index and potential conflict index are proposed. Using Haikou Meilan International Airport as the application scenario, the corresponding optimization scheme of the taxiway system in the maneuvering area is given based on …
