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2022

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Articles 151 - 180 of 965

Full-Text Articles in Artificial Intelligence and Robotics

Review On Ecological Construction Of Domestic High-Performance Parallel Application Software In Post Moore Era, Chunye Gong, Jie Liu, Weimin Bao, Dongmei Pan, Xinbiao Gan, Shengguo Li, Xuguang Chen, Tiaojie Xiao, Bo Yang, Ruibo Wang Oct 2022

Review On Ecological Construction Of Domestic High-Performance Parallel Application Software In Post Moore Era, Chunye Gong, Jie Liu, Weimin Bao, Dongmei Pan, Xinbiao Gan, Shengguo Li, Xuguang Chen, Tiaojie Xiao, Bo Yang, Ruibo Wang

Journal of System Simulation

Abstract: Domestic high performance computing (HPC) system is world-leading and the system chip architectures are in varied forms. The system operation relied on National Supercomputing Center has a good development trend. Several technical key points of domestic high-performance parallel application software are word-leading and the application supporting environment is developing fast. But industrial software and team building are facing huge challenges. In post Moore era, based on the progress of human civilization, it is necessary to promote the ecological development of parallel application software, and from the viewpoint of software products the industrial software must be aim foreign commercial software …

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Research On Improved Feature Pyramid Algorithm Integrating Border Supervision Strategy, Hong Sun, Yuelan Ling, Yuxiang Zhang Oct 2022

Research On Improved Feature Pyramid Algorithm Integrating Border Supervision Strategy, Hong Sun, Yuelan Ling, Yuxiang Zhang

Journal of System Simulation

Abstract: Aiming at the inaccurate boundary division in semantic segmentation and the existence of multi-scale targets, an improved feature pyramid algorithm fused with boundary supervision strategies is proposed. By fusing the boundary supervision strategy and the improved feature pyramid algorithm, the problems of inaccurate boundary division and the existence of multi-scale targets are sloved respectively, and an attention mechanism is added in the upsampling process to further improve the segmentation effect. The experimental results show that the algorithm can reach 58.69% and 78.59% MIOU (mean intersection over union) indicators on the Camvid and PASCAL VOC2012 data sets respectively, and has …

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Real-Time Scheduling Method For Railway Passenger Station Operations Based On Digital Twin, Bisheng He, Peng Chen, Hongxiang Zhang, Gongyuan Lu, Chunhui Zhang Oct 2022

Real-Time Scheduling Method For Railway Passenger Station Operations Based On Digital Twin, Bisheng He, Peng Chen, Hongxiang Zhang, Gongyuan Lu, Chunhui Zhang

Journal of System Simulation

Abstract: To improve the operation scheduling of railway passenger stations and reduce the train delays, digital twin technology is used to establish a railway passenger station operation model. Through real-time data acquisition, based on the operation time prediction of random forest method, operation simulation and decision-making, a real-time scheduling method of railway passenger station operations based on digital twin is proposed, and applied in a real railway passenger station. The experimental results show that the method can effectively forecast and simulate the actual operation. Three kinds of digital twin scheduling rules have been used, which can reduce the delay time …

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A Quantum Krill Herd Fusion Algorithm And Its Application, Zengxi Feng, Jintong Zhao, Shiyan Li, Yalong Yang, Haiyue Chen, Cong Zhang Oct 2022

A Quantum Krill Herd Fusion Algorithm And Its Application, Zengxi Feng, Jintong Zhao, Shiyan Li, Yalong Yang, Haiyue Chen, Cong Zhang

Journal of System Simulation

Abstract: Aiming at the defects of krill herd algorithm and quantum evolutionary algorithm, a quantum krill herd fusion algorithm (QKH) is proposed. The algorithm uses double-chain real numbers to encode the krill position, which can speed up the convergence speed, and avoids the randomness and complexity of quantum observations. The dynamically adjusted quantum krill herd rotation phase update strategy improves the convergence accuracy, and the efficiency of determining the quantum rotation phase. The introduction of an improved quantum full interference crossover strategy can prevent the fusion algorithm from falling into a local optimum, and can improve the optimization efficienal. The …

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Control Of Quadruped Robot Based On Impedance And Virtual Model, Chikun Gong, Xunwei Wu, Lipeng Yuan Oct 2022

Control Of Quadruped Robot Based On Impedance And Virtual Model, Chikun Gong, Xunwei Wu, Lipeng Yuan

Journal of System Simulation

Abstract: In order to improve the motion stability of quadruped robot, a control method based on impedance and virtual model is proposed. The force-based impedance control method is used to control the leg swing phase to realize the more accurate trajectory tracking and leg compliance control. The virtual model control method is used to control the support phase to realize the attitude control of the robot body and the stable walking of the quadruped robot. Combined with the lateral stride strategy and the yaw angle control strategy based on virtual model, a robot anti-lateral impact control method is proposed, which …

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Adaptive Crowd Evacuation Simulation Model Based On Bounded Rationality Constraints, Liqiang Zhao, Mengqian Guo, Shuixiong Tang, Jinjin Tang Oct 2022

Adaptive Crowd Evacuation Simulation Model Based On Bounded Rationality Constraints, Liqiang Zhao, Mengqian Guo, Shuixiong Tang, Jinjin Tang

Journal of System Simulation

Abstract: To effectively improve the accuracy of evacuation simulation of a crowded environment, an adaptive crowd evacuation simulation model based on social force model and bounded rationality constraints is proposed. The desired direction and desired speed of the self-driving force that affects the pedestrian movement in the traditional social force model is improved. The adaptive calculation is used in the optimization of direction and speed of pedestrian in an obstacle avoidance situation. The rational route decision mechanism is proposed to describe the route selection behavior of pedestrians in a congested state more accurately. The results show that the proposed model …

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Research On Modeling And Simulation Of Optimization Deployment For Cooperative Localization By Multiple Detection Sensors In Complex Environment, Gongguo Xu, Libing Cai, Peibing Du, Yu Liu Oct 2022

Research On Modeling And Simulation Of Optimization Deployment For Cooperative Localization By Multiple Detection Sensors In Complex Environment, Gongguo Xu, Libing Cai, Peibing Du, Yu Liu

Journal of System Simulation

Abstract: Aiming at the difficulty of accurate cooperative localization by multi-sensor network in complex environment, an optimization deployment method is proposed. The GDOP evaluation index of target positioning accuracy is constructed based on PCRLB. The influence of undulating terrain, clutter jamming and illumination on sensor detection and positioning ability in complex environment is analyzed. An optimization deployment model of multi-sensor cooperative location is built and the intelligent optimization algorithm is used to quickly solve the model. Simulation results show that the proposed method can effectively improve the cooperative localization ability of multi-sensor network and can guide the multi-sensor cooperative …

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Tactical Maneuver Strategy Learning From Land Wargame Replay Based On Convolutional Neural Network, Jiale Xu, Haidong Zhang, Donghai Zhao, Wancheng Ni Oct 2022

Tactical Maneuver Strategy Learning From Land Wargame Replay Based On Convolutional Neural Network, Jiale Xu, Haidong Zhang, Donghai Zhao, Wancheng Ni

Journal of System Simulation

Abstract: Aiming at collecting the high valuable knowledge of action decisions in "man-in-the-loop" wargame's replay data, a method of using convolutional neural network to learn the tactical maneuver strategy model from the replay data of wargame is proposed. In this method, the tactical maneuver strategy is modeled as a classification problem of making a good choice from the target candidate locations under the influence of current situation. The key factors affecting commander's decision-making are summarized, and the basic situation features are defined, which are composed of seven attributes such as "maneuverability range and observation range". The feature dataset with positive …

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Weighted Local Complexity Invariance For Time Series Classification, Yitong Li, Xiaotao Liu, Jing Liu, Kai Wu Oct 2022

Weighted Local Complexity Invariance For Time Series Classification, Yitong Li, Xiaotao Liu, Jing Liu, Kai Wu

Journal of System Simulation

Abstract: Aiming at the misclassification of existing algorithms for long or unevenly distributed time series, the local complexity information is extracted and weighted local complexity-invariant distance (WLCID) is proposed, which includes the local complexity representation model and the weighted global complexity integration model. Sliding window is used to split up time series, and combined with the complexity-invariant distance, the local complexity information can be extracted. As to the class representation model, the integration weights are quantified with the normalized cumulative between-class distance, with the perspective that the subsequence contributes more greatly with larger between-class distance. Compared with other …

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A K-Modes Clustering Method Based On Maximal Information Coefficient Data Preprocessing, Mingmei Li, Chenglin Wen, Shaolin Hu Oct 2022

A K-Modes Clustering Method Based On Maximal Information Coefficient Data Preprocessing, Mingmei Li, Chenglin Wen, Shaolin Hu

Journal of System Simulation

Abstract: The existing k-modes clustering method ignores the weak correlation of variable attributes, which often results in poor clustering performance in practical applications. A new k-modes clustering method that includes the weak correlation of attributes is proposed. Maximum information coefficient (MIC) is introduced to measure the correlation of variable attributes in the data set. The obtained MIC value is merged with the original distance to establish a new measurement method containing weak attribute correlation information to enhance the completeness of related information of variable attributes, and a more refined k-modes clustering method is established. Three different data sets are used …

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Research On Satellite Navigation Confrontation Deduction Model For Wargame System, Runqing Yang, Xi Wu Oct 2022

Research On Satellite Navigation Confrontation Deduction Model For Wargame System, Runqing Yang, Xi Wu

Journal of System Simulation

Abstract: Following the increasing reliance on space-based time-space metric of information warfare, satellite navigation confrontation becomes the major combat operation of competing for superiority in space-based position, navigation, and timing. Aiming at building a satellite navigation operation deduction model, on the basis of analyzing the relevant research, the navigation information environment computing model and the navigation deduction operation simulation model are designed, and the way to realize the visualization of navigation information environment of the wargame system and a substitution of high-resolution simulation computing model low-resolution probability effect model are explored, which support the pre-war planning and wartime evaluation …

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Wind Power Primary Frequency Regulation Simulation Based On Wind Speed Prediction Model, Zhenyu Zhao, Xu Ma, Geriletu Bao Oct 2022

Wind Power Primary Frequency Regulation Simulation Based On Wind Speed Prediction Model, Zhenyu Zhao, Xu Ma, Geriletu Bao

Journal of System Simulation

Abstract: To furtherly improve the accuracy of wind speed prediction, considering the coupled comprehensive features of data internal structure external influencing factors, and the characteristics of wind turbines power, a BP-ARIMA combined prediction model is constructed and the wind speed of wind farms is simulated. Compared with the actual data, the high prediction accuracy of the model is verified. Bases on the curve of typical power characteristic of wind turbine, the optimal configuration of energy storage device capacity and the stability of wind turbine are considered, and the MATLAB-SIMULINK platform is applied to simulate the primary frequency regulation of …

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Multi-Sensory Fusion Method For Power Transformer Virtual Assembly, Xuqiang Shao, Haowei Zhang, Xiaohua Feng Oct 2022

Multi-Sensory Fusion Method For Power Transformer Virtual Assembly, Xuqiang Shao, Haowei Zhang, Xiaohua Feng

Journal of System Simulation

Abstract: Virtual assembly technology is to truly restore the equipments and physical scenarios. In the real world, people can interact with the physical world through visual, auditory, tactile and other sense organ. Aiming at the existing virtual assembly system being limited the single sense human-computer interaction mode, so a multi-sense fusion information interaction method is proposed to improve the sense of immersion and operability. An improved AABB Octree bounding box collision detection algorithm of large size diffidence component to be assembled is proposed, which can greatly reduce the amount of calculation and improve the calculation accuracy. The experimental result verifies …

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Reinforcement-Learning-Based Adaptive Tracking Control For A Space Continuum Robot Based On Reinforcement Learning, Da Jiang, Zhiqin Cai, Zhongzhen Liu, Haijun Peng, Zhigang Wu Oct 2022

Reinforcement-Learning-Based Adaptive Tracking Control For A Space Continuum Robot Based On Reinforcement Learning, Da Jiang, Zhiqin Cai, Zhongzhen Liu, Haijun Peng, Zhigang Wu

Journal of System Simulation

Abstract: Aiming at the tracking control for three-arm space continuum robot in space active debris removal manipulation, an adaptive sliding mode control algorithm based on deep reinforcement learning is proposed. Through BP network, a data-driven dynamic model is developed as the predictive model to guide the reinforcement learning to adjust the sliding mode controller's parameters online, and finally realize a real-time tracking control. Simulation results show that the proposed data-driven predictive model can accurately predict the robot's dynamic characteristics with the relative error within ±1% to random trajectories. Compared with the fixed-parameter sliding mode controller, the proposed adaptive controller …

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Simulation Research On Aerodynamic Characteristics Of A Miniature Munition, Haisen Wang, Junfang Fan Oct 2022

Simulation Research On Aerodynamic Characteristics Of A Miniature Munition, Haisen Wang, Junfang Fan

Journal of System Simulation

Abstract: Aiming at the existing constraints of layout design of miniature munition, a new layout optimization scheme is proposed. Based on the normal layout structure, a three-dimensional aerodynamic model of munition is established, and the aerodynamic hydrodynamics simulation of miniature munition is carried out, and the influence of wing size on static stability of munition is studied. To verify the feasibility of the design scheme, the aerodynamic simulation calculation is carried out, and the lift, drag and pitching moment parameters of miniature munition are obtained through simulated aerodynamic calculation under different flight conditions, and the lift-drag ratio …

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Fatigue Detection Method Based On Facial Features And Head Posture, Rongxiu Lu, Bihao Zhang, Zhenlong Mo Oct 2022

Fatigue Detection Method Based On Facial Features And Head Posture, Rongxiu Lu, Bihao Zhang, Zhenlong Mo

Journal of System Simulation

Abstract: Aiming at the of the single fatigue characteristics, low robustness and inability to customize fatigue thresholds for different drivers of fatigue detection methods, a method based on facial features and head posture is proposed. In face detection and face key point positioning HOG feature operator and regression tree algorithm are used. In head posture estimation, head posture Euler angle is estimated by combining the face key points with the coordinate system transformation. In fatigue feature extraction, a deep residual neural network model is established to extract the eye fatigue features, which the eye, mouth aspect ratio and head posture …

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Task Allocation Method For Multi-Uav Cooperative Reconnaissance In Complex Environment, Fuzhen Zhang, Yaoqin Zhu Oct 2022

Task Allocation Method For Multi-Uav Cooperative Reconnaissance In Complex Environment, Fuzhen Zhang, Yaoqin Zhu

Journal of System Simulation

Abstract: The existing cooperative planning methods of multiple UAVs often carry out path planning and task allocation separatly, which causes the cooperative scheme not being the best in a complex environment. The cost matrix of multi-UAV cooperative reconnaissance on heterogeneous targets is established. Aiming at the various obstacle constraints and the characteristics of UAV motion and track in complex environment, an improved PSO-AFSA is used to solve the single UAV track planning model. Hungarian algorithm is used to complete the cooperative allocation of reconnaissance tasks of UAVs. The simulation results show that the algorithm can make the flying range of …

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Simulation Of Emergency Medical Materials Collaborative Distribution Considering Supplier Clustering, Zhe Wang, Hongyuan Shao, Zihao Cong, Wenwen Ma Oct 2022

Simulation Of Emergency Medical Materials Collaborative Distribution Considering Supplier Clustering, Zhe Wang, Hongyuan Shao, Zihao Cong, Wenwen Ma

Journal of System Simulation

Abstract: Aiming at the insufficient local government medical material reserves and low distribution efficiency to public health emergencies, consider supplier clustering a two-stage emergency medical supplies public-private collaborative location and alloation model is designed. In for disaster preparedness, fuzzy clustering algorithm to realize supplier clustering, and a cooperation mechanism with the government is establish realize the joint storage of emergency medical supplies; In the early stage of rescue, relying on the government and various suppliers' material storage and transportation capabilities, a location allocation simulation model to minimize the weighted sum of total logistics cost and demand unsatisfied rate is …

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Research On High-Performance Emulation Technology Of Starlink Constellation Based On Cloud Platform, Yuan Liu, Xinyi Xue, Xiaofeng Wang Oct 2022

Research On High-Performance Emulation Technology Of Starlink Constellation Based On Cloud Platform, Yuan Liu, Xinyi Xue, Xiaofeng Wang

Journal of System Simulation

Abstract: Network emulation on Starlink constellation is an important verification and evaluation tool for the design and construction of low earth orbit constellations in the future. Aiming at the characteristics of large-scale and complex structure of the Starlink network, a high-performance satellite network emulation system is designed. Based on the distributed network emulation architecture of cloud platform, through the development of STK Engine underlying interface, satellite model library storage optimization and asynchronous message transmission technology, the rapid deployment of Starlink constellation is carried out, and has good scalability. The experimental results show that the proposed method can carry out …

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Analysis And Research On End-To-End Optical Image Quality Of Large Aperture Off-Axis Space Telescope, Zhang Ban, Xiaobo Li, Xun Yang, Yuxi Jiang Oct 2022

Analysis And Research On End-To-End Optical Image Quality Of Large Aperture Off-Axis Space Telescope, Zhang Ban, Xiaobo Li, Xun Yang, Yuxi Jiang

Journal of System Simulation

Abstract: In order to evaluate the image quality of space on orbit telescope under the comprehensive constraints, the chain calculation analysis method is adopted. The main error factors of the optical image quality degradation are divided into six static errors and two dynamic errors. After calculation, the optical system wavefront aberration under the static loading error is reduced to 0.057λ on average. Under the influence of the static and dynamic errors, the 80% energy concentration of point spread function increases gradually. The method can be used to analyze and evaluate the influence of image stabilization control and precise temperature …

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Agglomerative Hierarchical Clustering With Dynamic Time Warping For Household Load Curve Clustering, Fadi Almahamid, Katarina Grolinger Oct 2022

Agglomerative Hierarchical Clustering With Dynamic Time Warping For Household Load Curve Clustering, Fadi Almahamid, Katarina Grolinger

Electrical and Computer Engineering Publications

Energy companies often implement various demand response (DR) programs to better match electricity demand and supply by offering the consumers incentives to reduce their demand during critical periods. Classifying clients according to their consumption patterns enables targeting specific groups of consumers for DR. Traditional clustering algorithms use standard distance measurement to find the distance between two points. The results produced by clustering algorithms such as K-means, K-medoids, and Gaussian Mixture Models depend on the clustering parameters or initial clusters. In contrast, our methodology uses a shape-based approach that combines Agglomerative Hierarchical Clustering (AHC) with Dynamic Time Warping (DTW) to classify …

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An Investigation Of The Reconstruction Capacity Of Stacked Convolutional Autoencoders For Log-Mel-Spectrograms, Anastasia Natsiou, Luca Longo, Seán O'Leary Oct 2022

An Investigation Of The Reconstruction Capacity Of Stacked Convolutional Autoencoders For Log-Mel-Spectrograms, Anastasia Natsiou, Luca Longo, Seán O'Leary

Conference Papers

In audio processing applications, the generation of expressive sounds based on high-level representations demonstrates a high demand. These representations can be used to manipulate the timbre and influence the synthesis of creative instrumental notes. Modern algorithms, such as neural networks, have inspired the development of expressive synthesizers based on musical instrument timbre compression. Unsupervised deep learning methods can achieve audio compression by training the network to learn a mapping from waveforms or spectrograms to low-dimensional representations. This study investigates the use of stacked convolutional autoencoders for the compression of time-frequency audio representations for a variety of instruments for a single …

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Tutorial: Neuro-Symbolic Ai For Mental Healthcare, Kaushik Roy, Usha Lokala, Manas Gaur, Amit Sheth Oct 2022

Tutorial: Neuro-Symbolic Ai For Mental Healthcare, Kaushik Roy, Usha Lokala, Manas Gaur, Amit Sheth

Publications

Artificial Intelligence (AI) systems for mental healthcare (MHCare) have been ever-growing after realizing the importance of early interventions for patients with chronic mental health (MH) conditions. Social media (SocMedia) emerged as the go-to platform for supporting patients seeking MHCare. The creation of peer-support groups without social stigma has resulted in patients transitioning from clinical settings to SocMedia supported interactions for quick help. Researchers started exploring SocMedia content in search of cues that showcase correlation or causation between different MH conditions to design better interventional strategies. User-level Classification-based AI systems were designed to leverage diverse SocMedia data from various MH conditions, …

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Visual Object Tracking With Discriminative Filters And Siamese Networks: A Survey And Outlook, Sajid Javed, Martin Danelljan, Fahad Shahbaz Khan, Muhammad Haris Khan, Michael Felsberg, Jiri Matas Oct 2022

Visual Object Tracking With Discriminative Filters And Siamese Networks: A Survey And Outlook, Sajid Javed, Martin Danelljan, Fahad Shahbaz Khan, Muhammad Haris Khan, Michael Felsberg, Jiri Matas

Computer Vision Faculty Publications

Accurate and robust visual object tracking is one of the most challenging and fundamental computer vision problems. It entails estimating the trajectory of the target in an image sequence, given only its initial location, and segmentation, or its rough approximation in the form of a bounding box. Discriminative Correlation Filters (DCFs) and deep Siamese Networks (SNs) have emerged as dominating tracking paradigms, which have led to significant progress. Following the rapid evolution of visual object tracking in the last decade, this survey presents a systematic and thorough review of more than 90 DCFs and Siamese trackers, based on results in …

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Ps-Arm: An End-To-End Attention-Aware Relation Mixer Network For Person Search, Mustansar Fiaz, Hisham Cholakkal, Sanath Narayan, Rao Anwer, Fahad Shahbaz Khan Oct 2022

Ps-Arm: An End-To-End Attention-Aware Relation Mixer Network For Person Search, Mustansar Fiaz, Hisham Cholakkal, Sanath Narayan, Rao Anwer, Fahad Shahbaz Khan

Computer Vision Faculty Publications

Person search is a challenging problem with various real-world applications, that aims at joint person detection and re-identification of a query person from uncropped gallery images. Although, previous study focuses on rich feature information learning, it’s still hard to retrieve the query person due to the occurrence of appearance deformations and background distractors. In this paper, we propose a novel attention-aware relation mixer (ARM) module for person search, which exploits the global relation between different local regions within RoI of a person and make it robust against various appearance deformations and occlusion. The proposed ARM is composed of a relation …

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Artificial Intelligence And The Situational Rationality Of Diagnosis: Human Problem-Solving And The Artifacts Of Health And Medicine, Michael W. Raphael Oct 2022

Artificial Intelligence And The Situational Rationality Of Diagnosis: Human Problem-Solving And The Artifacts Of Health And Medicine, Michael W. Raphael

Publications and Research

What is the problem-solving capacity of artificial intelligence (AI) for health and medicine? This paper draws out the cognitive sociological context of diagnostic problem-solving for medical sociology regarding the limits of automation for decision-based medical tasks. Specifically, it presents a practical way of evaluating the artificiality of symptoms and signs in medical encounters, with an emphasis on the visualization of the problem-solving process in doctor-patient relationships. In doing so, the paper details the logical differences underlying diagnostic task performance between man and machine problem-solving: its principle of rationality, the priorities of its means of adaptation to abstraction, and the effects …

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Hyperfast Second-Order Local Solvers For Efficient Statistically Preconditioned Distributed Optimization, Pavel Dvurechensky, Dmitry Kamzolov, Aleksandr Lukashevich, Soomin Lee, Erik Ordentlich, César A. Uribe, Alexander Gasnikov Oct 2022

Hyperfast Second-Order Local Solvers For Efficient Statistically Preconditioned Distributed Optimization, Pavel Dvurechensky, Dmitry Kamzolov, Aleksandr Lukashevich, Soomin Lee, Erik Ordentlich, César A. Uribe, Alexander Gasnikov

Machine Learning Faculty Publications

Statistical preconditioning enables fast methods for distributed large-scale empirical risk minimization problems. In this approach, multiple worker nodes compute gradients in parallel, which are then used by the central node to update the parameter by solving an auxiliary (preconditioned) smaller-scale optimization problem. The recently proposed Statistically Preconditioned Accelerated Gradient (SPAG) method [1] has complexity bounds superior to other such algorithms but requires an exact solution for computationally intensive auxiliary optimization problems at every iteration. In this paper, we propose an Inexact SPAG (InSPAG) and explicitly characterize the accuracy by which the corresponding auxiliary subproblem needs to be solved to guarantee …

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A Survey On Multimodal Disinformation Detection, Firoj Alam, Stefano Cresci, Tanmoy Chakraborty, Fabrizio Silvestri, Dimitar Dimitrov, Giovanni Da San Martino, Shaden Shaar, Hamed Firooz, Preslav Nakov Oct 2022

A Survey On Multimodal Disinformation Detection, Firoj Alam, Stefano Cresci, Tanmoy Chakraborty, Fabrizio Silvestri, Dimitar Dimitrov, Giovanni Da San Martino, Shaden Shaar, Hamed Firooz, Preslav Nakov

Natural Language Processing Faculty Publications

Recent years have witnessed the proliferation of offensive content online such as fake news, propaganda, misinformation, and disinformation. While initially this was mostly about textual content, over time images and videos gained popularity, as they are much easier to consume, attract more attention, and spread further than text. As a result, researchers started leveraging different modalities and combinations thereof to tackle online multimodal offensive content. In this study, we offer a survey on the state-of-the-art on multimodal disinformation detection covering various combinations of modalities: text, images, speech, video, social media network structure, and temporal information. Moreover, while some studies focused …

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Noisy Label Regularisation For Textual Regression, Yuxia Wang, Timothy Baldwin, Karin Verspoor Oct 2022

Noisy Label Regularisation For Textual Regression, Yuxia Wang, Timothy Baldwin, Karin Verspoor

Natural Language Processing Faculty Publications

Training with noisy labelled data is known to be detrimental to model performance, especially for high-capacity neural network models in low-resource domains. Our experiments suggest that standard regularisation strategies, such as weight decay and dropout, are ineffective in the face of noisy labels. We propose a simple noisy label detection method that prevents error propagation from the input layer. The approach is based on the observation that the projection of noisy labels is learned through memorisation at advanced stages of learning, and that the Pearson correlation is sensitive to outliers. Extensive experiments over real-world human-disagreement annotations as well as randomly-corrupted …

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Lemurs Optimizer: A New Metaheuristic Algorithm For Global Optimization, Ammar Kamal Abasi, Sharif Naser Makhadmeh, Mohammed Azmi Al-Betar, Osama Ahmad Alomari, Mohammed A. Awadallah, Zaid Abdi Alkareem Alyasseri, Iyad Abu Doush, Ashraf Elnagar, Eman H. Alkhammash, Myriam Hadjouni Oct 2022

Lemurs Optimizer: A New Metaheuristic Algorithm For Global Optimization, Ammar Kamal Abasi, Sharif Naser Makhadmeh, Mohammed Azmi Al-Betar, Osama Ahmad Alomari, Mohammed A. Awadallah, Zaid Abdi Alkareem Alyasseri, Iyad Abu Doush, Ashraf Elnagar, Eman H. Alkhammash, Myriam Hadjouni

Machine Learning Faculty Publications

The Lemur Optimizer (LO) is a novel nature-inspired algorithm we propose in this paper. This algorithm’s primary inspirations are based on two pillars of lemur behavior: leap up and dance hub. These two principles are mathematically modeled in the optimization context to handle local search, exploitation, and exploration search concepts. The LO is first benchmarked on twenty-three standard optimization functions. Additionally, the LO is used to solve three real-world problems to evaluate its performance and effectiveness. In this direction, LO is compared to six well-known algorithms: Salp Swarm Algorithm (SSA), Artificial Bee Colony (ABC), Sine Cosine Algorithm (SCA), Bat Algorithm …

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