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Articles 5581 - 5610 of 11325

Full-Text Articles in Computer Sciences

Electronic Solid Waste Prediction Based On Intelligent Optimization Grey Model, Xiaoan Sun, Xiaoli Luan, Fei Liu Mar 2022

Electronic Solid Waste Prediction Based On Intelligent Optimization Grey Model, Xiaoan Sun, Xiaoli Luan, Fei Liu

Journal of System Simulation

Abstract: Aiming at the problems of complex modeling mechanism and low modeling accuracy in the prediction of electronic solid waste production, an intelligent modeling method combining fractional order multiple gray model and neural network compensation model is proposed. Particle swarm optimization is used to optimize the accumulative order and background parameters of the gray model to maximize the performance of the gray model. BP neural network is used to compensate the error of gray modeling and improve the prediction accuracy of solid waste production. The effectiveness of the proposed method is verified by Washington state electronic solid waste data. The …

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Job Shop Rescheduling Under Recessive Disturbance Based On Digital Twin, Dinghui Wu, Tongrui Zhang, Xiuli Zhang Mar 2022

Job Shop Rescheduling Under Recessive Disturbance Based On Digital Twin, Dinghui Wu, Tongrui Zhang, Xiuli Zhang

Journal of System Simulation

Abstract: A new shop rescheduling model driven by digital twin is proposed to solve the problems of disturbance cumulative rescheduling. A scheduling parameter updating method is proposed and a random probability distribution is used to describe the distribution of scheduling parameters to improve the accuracy of scheduling parameters. An implicit disturbance detection model is built based on Siamese Network using real-time data as input to realize the start time of rescheduling. The sample data for scheduling knowledge mining are extracted from the historical scheduling scenarios. Through the Pseudo-Siamese CNN, the mapping relationship between the Process state and machine state is …

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Research On Binocular Ranging System Based On Image Features, Jinghui Yang, Dekang Liu, Wanhe Du, Lining Xing Mar 2022

Research On Binocular Ranging System Based On Image Features, Jinghui Yang, Dekang Liu, Wanhe Du, Lining Xing

Journal of System Simulation

Abstract: Aiming at the problems of large measurement error, single image information, and poor real-time performance in binocular vision ranging, a binocular ranging method based on ORB (oriented fast and rotated brief) features is proposed. Median filtering is performed on the video frame, the ORB feature of the image is extracted, and the Hamming distance with the best matching effect is selected through experiments. The RANSAC (random sample consensus) model estimation is performed on the selected matching points, the mismatches are removed, the model relationship between parallax and true distance is analyzed, the optimal ranging model is constructed and verified …

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Research On Optimization Of Airport Cargo Business Based On Deep Reinforcement Learning, Hongwei Wang, Peng Yang Mar 2022

Research On Optimization Of Airport Cargo Business Based On Deep Reinforcement Learning, Hongwei Wang, Peng Yang

Journal of System Simulation

Abstract: An intelligent agent technology architecture is adopted to the simulation model development of airport cargo business. Aiming at the optimization of airport cargo resources, a decision support system framework combining deep reinforcement learning (DRL) and airport cargo business simulation model is proposed. The simulated results are applied as the training data of the DRL network, and the DRL is used to optimize operation parameter of the simulation model. The mature system can be run online, which can provide optimized operation order in real time. In order to verify the effectiveness of the architecture, model development and experiments are conducted …

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Research On Active Learning Method And Application Based On Covariance Matrix, Bowen Zhou, Weili Xiong Mar 2022

Research On Active Learning Method And Application Based On Covariance Matrix, Bowen Zhou, Weili Xiong

Journal of System Simulation

Abstract: Since the data collected from industrial processes often contain a large number of unlabeled samples, while the number of labeled samples is small and the cost of manual labeling is high, an active learning method based on covariance matrix is proposed. This method uses labeled samples to establish a Gaussian process regression model, and constructs the covariance matrix between the unlabeled samples, using the value of the determinant of the covariance matrix as an evaluation indicator. While selecting informative unlabeled samples, the similarity between samples is measured to avoid redundant addition of samples, which finally improves model prediction accuracy …

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Research On Algebraic Loop Of Synchronous Generator Simulation Based On Simulink, Shuang Wang, Zhaohui Gao, Siyu Chen, Xiao Tang, Zhan Xi Mar 2022

Research On Algebraic Loop Of Synchronous Generator Simulation Based On Simulink, Shuang Wang, Zhaohui Gao, Siyu Chen, Xiao Tang, Zhan Xi

Journal of System Simulation

Abstract: The problem of algebraic loop is common in Simulink simulation. The existence of algebraic loop will reduce the speed and accuracy of simulation, and even lead to errors in simulation results. Taking the simulation of synchronous generator as an example, the problem of algebraic loop and its elimination method in Simulink simulation are discussed. Starting from the analysis of the basic equations of synchronous generator, the cause of algebraic loop in simulation is discussed, the influence of the algebraic loop on the system simulation is pointed out, using disassembly method and transformation method, focusing on eliminating the algebraic loop, …

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An Improved Atomic Search Algorithm, Jianfeng Li, Di Lu, Hexiang Li Mar 2022

An Improved Atomic Search Algorithm, Jianfeng Li, Di Lu, Hexiang Li

Journal of System Simulation

Abstract: The atom search algorithm (ASO) is a new optimization algorithm proposed by imitating the movement of atoms in the natural world. An improved atomic search algorithm (IASO) is proposed to address the problems of prematureness and slow convergence of ASO in solving complex functions. IASO adds the binding force generated by the historical optimal solution of individual atoms to correct the acceleration of ASO and enhance the global search capability. The two multiplier coefficients are adaptively updated to coordinate the algorithm's global search and local development capabilities. The Gaussian mutation strategy is used to re-update the atomic position and …

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Research On The Simulation Method Of Urban Rail Transit Feedback Assignment, Jianpeng Hu, Xia Luo Mar 2022

Research On The Simulation Method Of Urban Rail Transit Feedback Assignment, Jianpeng Hu, Xia Luo

Journal of System Simulation

Abstract: Based on the characteristics of a large number of transfer routes in rail transit network, an improved depth first search algorithm is proposed to get the effective travel time of transfer routes between stations. Based on passenger entry and exit timing obtained from the automatic fare collection (AFC) data, the connect relationship between passengers and trains in time and route is obtained from the arrival time and route selection behavior of passengers. Considering the difference of route choice behavior between departure passenger and transfer passenger, the two are distinguished from each other. The dynamically updated travel …

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Simulation Of Robust Optimal Synchronization Control For Direct Drive H-Type Motion Platform, Limei Wang, Hongyan Yao, Kang Zhang Mar 2022

Simulation Of Robust Optimal Synchronization Control For Direct Drive H-Type Motion Platform, Limei Wang, Hongyan Yao, Kang Zhang

Journal of System Simulation

Abstract: Cell manufacturing is an important organizational form of modern production systems. In scheduling of cell manufacturing systems, machine failures or interruptions are very common in practice, meanwhile the waste due to energy consumption during machine idle time cannot be ignored. Hence the relevant research is with strong significance. This paper considers the problems of machine interruption and energy consumption in cell scheduling, and developed an integer programming model to minimize the makespan as well as the cost of energy consumption during machine idling and the interruption cost. A mixed optimization method is proposed based on improved wolf pack algorithm …

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Modeling Time Series Using Multi-Modality Fuzzy Cognitive Maps, Guoliang Feng, Wei Lu, Jianhua Yang Mar 2022

Modeling Time Series Using Multi-Modality Fuzzy Cognitive Maps, Guoliang Feng, Wei Lu, Jianhua Yang

Journal of System Simulation

Abstract: A multi-modality modeling method for time series data based on fuzzy cognitive maps is proposed to address the problem that a single model is difficult to accurately reflect the multi-modal characteristics of time series.The bootstrap method is used to select multiple sub-sequences from the original time serieswhich contain the diverse modality in the original time series. The fuzzy cognitive map sub-models are constructed on each sub-sequencesrespectively. The formed sub-models are further merged by means of granular computing method and the merging performance with different weighting strategies is analyzed. The developed multi-modal model not only has prediction abilities at …

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Research On Information Flow Integrated M&S Method For Project Type Manufacturing Process, Mindong Liu, Longjun Wu, Mingchao Tang, Mei Meng Mar 2022

Research On Information Flow Integrated M&S Method For Project Type Manufacturing Process, Mindong Liu, Longjun Wu, Mingchao Tang, Mei Meng

Journal of System Simulation

Abstract: The project type manufacturing process is quite common in shipbuilding and construction industries. Aiming at the problem that the existing discrete manufacturing system modeling and simulation method for flow shop cannot effectively express and imitate this process, taking shipyard dock shop hoisting process as an example, we analyze its components structure, propose a working network-centric, information flow and work flow integrated simulation modelling method, and design a dedicated simulation algorithm with the task process interactive idea. A prototype simulation program is developed with Python language, and the effectiveness of the proposed modelling and simulation method is verified through …

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Research On Optimization Of Network Resource Utilization In Static Segment Of Flexray Bus, Xinhang He, Erkang Li, Hongchao Zhang Mar 2022

Research On Optimization Of Network Resource Utilization In Static Segment Of Flexray Bus, Xinhang He, Erkang Li, Hongchao Zhang

Journal of System Simulation

Abstract: In order to improve the utilization of the network resources of the FlexRay bus, the network is optimized for static segment scheduling. The FlexRay communication mechanism is analyzed, the message model is established and the calculation method of bandwidth loss is derived, while considering the protocol overhead and network idling, taking the number of static frames and the length of the static frame payload as design variables, the overall optimal packaging scheme is obtained by solving this multi-objective optimization problem. This solution is finally applied to the vehicle chassis integrated control system for simulation analysis and verification. The results …

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Research On Joint Optimization Of Energy-Saving Distributed Manufacturing And Preventive Maintenance For Semiconductor Wafers, Jun Dong, Chunming Ye Mar 2022

Research On Joint Optimization Of Energy-Saving Distributed Manufacturing And Preventive Maintenance For Semiconductor Wafers, Jun Dong, Chunming Ye

Journal of System Simulation

Abstract: Aiming at the joint optimization problem of energy-saving distributed manufacturing and preventive maintenance for semiconductor wafers, a two-stage green scheduling model considering both the manufacturing stage and the inspection and repair stage is established to minimize the makespan, the total carbon emissions and the total preventive maintenance cost. An improved hybrid multi-objective grey wolf optimization (IHMGWO)algorithm is proposed. The decoding schemes of factory allocation strategy, machine allocation strategy and synchronous scheduling maintenance strategy considering the flexibility of maintenance workers are designed in IHMGWO. By designing the initial population fusion strategy, predation behavior search strategy, and sub-population mutation strategy, the …

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Research On The Construction Method Of Simulation Evaluation Index Of Operation Effectiveness Operation Concept Traction, Ziwei Zhang, Liang Li, Zhiming Dong, Yifei Wang, Li Duan Mar 2022

Research On The Construction Method Of Simulation Evaluation Index Of Operation Effectiveness Operation Concept Traction, Ziwei Zhang, Liang Li, Zhiming Dong, Yifei Wang, Li Duan

Journal of System Simulation

Abstract: Agents are difficult to be directly modeled and simulated due to the complexity of their own interaction and learning behaviors. Aiming at the common problems in the discrete simulation of the agent, the event transfer mechanism of the discrete event system specification (DEVS) atomic model is applied to express the interaction and learning of an agent. Through the interaction mode of the agent, the transfer control of multi-state external events, the port connection mode, as well as the introduction of reinforcement learning event transfer representation, a discrete simulation construction method of the agent based on the DEVS atomic model …

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Path-Based Model For The Heterogeneous-Fleet Electric Vehicle Routing Problem With Partial Linear Recharging, Weiquan Wang, Ding Ding, Linsha Yan Mar 2022

Path-Based Model For The Heterogeneous-Fleet Electric Vehicle Routing Problem With Partial Linear Recharging, Weiquan Wang, Ding Ding, Linsha Yan

Journal of System Simulation

Abstract: The heterogeneous-fleet electric vehicle routing problem with partial linear recharging is studied for realistic logistics distribution scenarios using multiple electric vehicle fleets with different transport capacities, driving ranges and acquisition costs. A path-based mixed integer linear model is proposed. The model enumerates the paths visited by all vehicle types between any non-charging nodes, eliminates the infeasible paths through capacity constraints and time window constraints, and eliminates the dominated paths by the dominance criterion. Compared with the traditional charging station replica-based model, this model eliminates the need to set the number of charging station replicas. The results show that the …

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Chatgpt Goes To Law School, Jonathan H. Choi, Kristin E. Hickman, Amy B. Monahan, Daniel Schwarcz Mar 2022

Chatgpt Goes To Law School, Jonathan H. Choi, Kristin E. Hickman, Amy B. Monahan, Daniel Schwarcz

Journal of Legal Education

No abstract provided.

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Objective Measure Of Working Memory Capacity Using Eye Movements, James Owens, Gavindya Jayawardena, Yasasi Abeysinghe, Vikas G. Ashok, Sampath Jayarathna Mar 2022

Objective Measure Of Working Memory Capacity Using Eye Movements, James Owens, Gavindya Jayawardena, Yasasi Abeysinghe, Vikas G. Ashok, Sampath Jayarathna

Undergraduate Research Symposium

Human-autonomy teaming (HAT) has become an important area of research due to the autonomous systems being developed for different applications, such as remotely controlled aircraft. Many remotely controlled vehicles will be controlled by automated systems, with a human monitor that may be monitoring multiple vehicles simultaneously. The attention and working memory capacity of operators of remote-controlled vehicles must be maintained at appropriate levels during operation. However, there is currently no direct method of determining working memory capacity, which is important because it is a measure for how memory is being stored for a short term and interacting with long term …

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Two-Stage Transfer Learning For Facial Expression Classification In Children, Gregory Hubbard, Megan Witherow, Khan Iftekharuddin Mar 2022

Two-Stage Transfer Learning For Facial Expression Classification In Children, Gregory Hubbard, Megan Witherow, Khan Iftekharuddin

Undergraduate Research Symposium

Studying facial expressions can provide insight into the development of social skills in children and provide support to individuals with developmental disorders. In afflicted individuals, such as children with Autism Spectrum Disorder (ASD), atypical interpretations of facial expressions are well-documented. In computer vision, many popular and state-of-the-art deep learning architectures (VGG16, EfficientNet, ResNet, etc.) are readily available with pre-trained weights for general object recognition. Transfer learning utilizes these pre-trained models to improve generalization on a new task. In this project, transfer learning is implemented to leverage the pretrained model (general object recognition) on facial expression classification. Though this method, the …

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Analyzing Decision-Making In Robot Soccer For Attacking Behaviors, Justin Rodney Mar 2022

Analyzing Decision-Making In Robot Soccer For Attacking Behaviors, Justin Rodney

USF Tampa Graduate Theses and Dissertations

In robotics soccer, decision-making is critical to the performance of a team’s SoftwareSystem. The University of South Florida’s (USF) RoboBulls team implements behavior for the robots by using traditional methods such as analytical geometry to path plan and determine whether an action should be taken. In recent works, Machine Learning (ML) and Reinforcement Learning (RL) techniques have been used to calculate the probability of success for a pass or goal, and even train models for performing low-level skills such as traveling towards a ball and shooting it towards the goal[1, 2]. Open-source frameworks have been created for training Reinforcement Learning …

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Backup Automation Using Power Automate For Malaysian Vaccination Centres, Raadhesh Kannan, Chin Ji Jian Mar 2022

Backup Automation Using Power Automate For Malaysian Vaccination Centres, Raadhesh Kannan, Chin Ji Jian

Journal of Informatics and Web Engineering

The Covid-19 pandemic has tested the world, especially the vaccine centres when it comes to logistics, maintenance of records, and issuing of vaccination certifications. The Malaysian vaccination centres (PPVs) known as Pusat Pemberian Vaksin in Malaysia have a secure, and reliable system to maintain records of who has been vaccinated and when. No system is fully secure and reliable, thus there needs to be a backup if anything happens to the records like data loss or tampering of records. Although the information flow is simplified using the MySejahtera app and scanning of QR codes, there is no contingency prepared should …

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Localization Techniques Overview Towards 6g Communication, Nawaid Hasan, Azlan Abd Aziz, Azwan Mahmud, Nur Asyiqin Binte Hamzah, Noor Ziela Abd Rahman Mar 2022

Localization Techniques Overview Towards 6g Communication, Nawaid Hasan, Azlan Abd Aziz, Azwan Mahmud, Nur Asyiqin Binte Hamzah, Noor Ziela Abd Rahman

Journal of Informatics and Web Engineering

Worldwide Researchers and scientist have started the investigation of the sixth generation (6G) while the fifth generation (5G) cellular system is being deployed. Under this main investigation the main aim of 6G is to provide intelligent and ubiquitous wireless connectivity with Terabits per second (Tbps) data rates. Accurate location information of the mobile devices is very much useful to accomplish these aims with the improvements of various parameters of wireless communication. The development in communication technology often creates new opportunities to improve the localization efficiency as demonstrated by the expected centimetre-level localization accuracy in 6G. While there are comprehensive literatures …

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Performance Of Sentiment Classification On Tweets Of Clothing Brands, Muhammad Shafiq Jalani, Hu Ng, Timothy Tzen Vun Yap, Vik Tor Goh Mar 2022

Performance Of Sentiment Classification On Tweets Of Clothing Brands, Muhammad Shafiq Jalani, Hu Ng, Timothy Tzen Vun Yap, Vik Tor Goh

Journal of Informatics and Web Engineering

Social media such as Facebook, Instagram, LinkedIn, and Twitter ease the sharing of ideas, thoughts, videos, and photos and information through the building of virtual networks and communities. This has allowed companies and products to reach a wider audience in terms of marketing and advertising, and to gauge feedback from the public. This research investigates clothing brand mentions on Twitter to perform sentiment analysis on users’ thoughts on three clothing brands, namely Asos, Uniqlo and Topshop. The data is collected by applying python libraries, Tweepy to access data from the Twitter streaming API. Following that, data pre-processing such as tokenization, …

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Incorporating Semi-Automated Approach For Effective Software Requirements Prioritization: A Framework Design, Fang-Fang Chua, Tek-Yong Lim, Bushra Tajuddin, Amarilis Putri Yanuarifiani Mar 2022

Incorporating Semi-Automated Approach For Effective Software Requirements Prioritization: A Framework Design, Fang-Fang Chua, Tek-Yong Lim, Bushra Tajuddin, Amarilis Putri Yanuarifiani

Journal of Informatics and Web Engineering

Software Requirements Prioritization (SRP) is one of the crucial processes in software requirements engineering. It presents a challenging task to decide among the pool of requirements and the variance of the stakeholder’s needs in prioritizing requirements. Semi-automated requirements prioritization is implemented in both manual and automatic processes. When prioritizing requirements, these aspects such as importance, time, cost and risk, should be taken into account. The emergence of machine learning is advancing to improve and automate the SRP process whereby decision making can be performed with minimal human intervention. Incorporating machine learning approaches in prioritization techniques can be implemented in the …

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The Impacts Of The Use Of Thematic & Chronologic Multi-Modal Information Representation On Sequential And Global Students’ Historical Understanding, Ling Weay Ang, Sellappan Palaniappan Mar 2022

The Impacts Of The Use Of Thematic & Chronologic Multi-Modal Information Representation On Sequential And Global Students’ Historical Understanding, Ling Weay Ang, Sellappan Palaniappan

Journal of Informatics and Web Engineering

This study examined the two different modes of multi-modes information presentations that affected sequential and global learners' history understanding: thematic and chronological. A total of 134 secondary schools’ students were enrolled (69 learning in chronological mode, 65 learning in thematic mode). Before the start of the treatment session, students were given a pre-test. The results showed that multimodal information presentation did not have a significantly great impact on historical learning or between pupils who learn in chronological and thematic ways. The chronological frame of reference technique, which reflected an interactive timeline, was reported to have supported students' sequential learning in …

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Robustness Analysis Of Classification Using Recurrent Neural Networks With Perturbed Sequential Input, Guangyi Liu, Arash Amini, Martin Takac, Nader Motee Mar 2022

Robustness Analysis Of Classification Using Recurrent Neural Networks With Perturbed Sequential Input, Guangyi Liu, Arash Amini, Martin Takac, Nader Motee

Machine Learning Faculty Publications

For a given stable recurrent neural network (RNN) that is trained to perform a classification task using sequential inputs, we quantify explicit robustness bounds as a function of trainable weight matrices. The sequential inputs can be perturbed in various ways, e.g., streaming images can be deformed due to robot motion or imperfect camera lens. Using the notion of the Voronoi diagram and Lipschitz properties of stable RNNs, we provide a thorough analysis and characterize the maximum allowable perturbations while guaranteeing the full accuracy of the classification task. We illustrate and validate our theoretical results using a map dataset with clouds …

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Deep Learning Techniques For Diabetic Retinopathy Classification: A Survey, Mohammad Z. Atwany, Abdulwahab H. Sahyoun, Mohammad Yaqub Mar 2022

Deep Learning Techniques For Diabetic Retinopathy Classification: A Survey, Mohammad Z. Atwany, Abdulwahab H. Sahyoun, Mohammad Yaqub

Computer Vision Faculty Publications

Diabetic Retinopathy (DR) is a degenerative disease that impacts the eyes and is a consequence of Diabetes mellitus, where high blood glucose levels induce lesions on the eye retina. Diabetic Retinopathy is regarded as the leading cause of blindness for diabetic patients, especially the working-age population in developing nations. Treatment involves sustaining the patient's current grade of vision since the disease is irreversible. Early detection of Diabetic Retinopathy is crucial in order to sustain the patient's vision effectively. The main issue involved with DR detection is that the manual diagnosis process is very time, money, and effort consuming and involves …

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Pseudo-Stereo For Monocular 3d Object Detection In Autonomous Driving, Yi-Nan Chen, Hang Dai, Yong Ding Mar 2022

Pseudo-Stereo For Monocular 3d Object Detection In Autonomous Driving, Yi-Nan Chen, Hang Dai, Yong Ding

Computer Vision Faculty Publications

Pseudo-LiDAR 3D detectors have made remarkable progress in monocular 3D detection by enhancing the capability of perceiving depth with depth estimation networks, and using LiDAR-based 3D detection architectures. The advanced stereo 3D detectors can also accurately localize 3D objects. The gap in image-to-image generation for stereo views is much smaller than that in image-to-LiDAR generation. Motivated by this, we propose a Pseudo-Stereo 3D detection framework with three novel virtual view generation methods, including image-level generation, feature-level generation, and feature-clone, for detecting 3D objects from a single image. Our analysis of depth-aware learning shows that the depth loss is effective in …

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Trust In Robotics: A Multi-Staged Decision-Making Approach To Robots In Community, Wenxi Zhang, Willow Wong, Mark Findlay Mar 2022

Trust In Robotics: A Multi-Staged Decision-Making Approach To Robots In Community, Wenxi Zhang, Willow Wong, Mark Findlay

Centre for AI & Data Governance (2019-2025)

Pivoting on the desired outcome of social good within the wider robotics ecosystem, trust is identified as the central adhesive of the HRI interface. However, building trust between humans and robots involves more than improving the machine’s technical reliability or trustworthiness in function. This paper presents a holistic, community-based approach to trust-building, where trust is understood as a multifaceted and multi-staged looped relation that depends heavily on context and human perceptions. Building on past literature that identifies dispositional and learned stages of trust, our proposed Decision to Trust model considers more extensively the human and situational factors influencing how trust …

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Autonomous, Long-Range, Sensor Emplacement Using Unmanned Aircraft Systems, Adam Plowcha, Justin Bradley, Jacob Hoberg, Thomas Ammon, Mark Nail, Brittany Duncan, Carrick Detweiler Mar 2022

Autonomous, Long-Range, Sensor Emplacement Using Unmanned Aircraft Systems, Adam Plowcha, Justin Bradley, Jacob Hoberg, Thomas Ammon, Mark Nail, Brittany Duncan, Carrick Detweiler

School of Computing: Faculty Publications

Automated, in-ground sensor emplacement can significantly improve remote, terrestrial, data collection capabilities. Utilizing a multicopter, unmanned aircraft system (UAS) for this purpose allows sensor insertion with minimal disturbance to the target site or surrounding area. However, developing an emplacement mechanism for a small multicopter, autonomy to manage the target selection and implantation process, as well as long-range deployment are challenging to address. We have developed an autonomous, multicopter UAS that can implant subsurface sensor devices. We enhanced the UAS autopilot with autonomy for target and landing zone selection, as well as ensuring the sensor is implanted properly in the ground. …

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Viral Pneumonia Screening On Chest X-Rays Using Confidence-Aware Anomaly Detection, Jianpeng Zhang, Yutong Xie, Guansong Pang, Zhibin Liao, Johan Verjans, Wenxing Li, Zongji Sun, Jian He, Yi Li, Chunhua Shen, Yong Xia Mar 2022

Viral Pneumonia Screening On Chest X-Rays Using Confidence-Aware Anomaly Detection, Jianpeng Zhang, Yutong Xie, Guansong Pang, Zhibin Liao, Johan Verjans, Wenxing Li, Zongji Sun, Jian He, Yi Li, Chunhua Shen, Yong Xia

Research Collection School Of Computing and Information Systems

Clusters of viral pneumonia occurrences over a short period may be a harbinger of an outbreak or pandemic. Rapid and accurate detection of viral pneumonia using chest X-rays can be of significant value for large-scale screening and epidemic prevention, particularly when other more sophisticated imaging modalities are not readily accessible. However, the emergence of novel mutated viruses causes a substantial dataset shift, which can greatly limit the performance of classification-based approaches. In this paper, we formulate the task of differentiating viral pneumonia from non-viral pneumonia and healthy controls into a one-class classification-based anomaly detection problem. We therefore propose the confidence-aware …

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