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Articles 5371 - 5400 of 11180

Full-Text Articles in Artificial Intelligence and Robotics

Design And Implementation Of A Hybrid Solver On Cpu And Gpu Multi-Target Machines, Lin Ma, Xuesong Zhang, Xinlin Lei, Tie Bao Apr 2022

Design And Implementation Of A Hybrid Solver On Cpu And Gpu Multi-Target Machines, Lin Ma, Xuesong Zhang, Xinlin Lei, Tie Bao

Journal of System Simulation

Abstract: The traditional parallel solving methods for the ordinary differential equations mainly include the task-oriented parallelism and the method-oriented parallelism. However, these two solving algorithms have serious shortcomings, which can only use CPU resource or just design for the homogeneous form of ODE(ordinary differential equations) clusters. By using RIDC(revisionist integral deferred correction) algorithm, a hybrid solver based on CPU and GPU multi-target machine is designed, which solves the differential equation system based on the pipeline form. Meanwhile, the parallel calculation within a single equation group and between the different equation groups is realized, which can give full play to the …

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Design And Development Of A Simulation System For Scheduling In Cloud Manufacturing Based On Microservice Architecture, Yongkui Liu, Ming Zeng, Lin Zhang, Jinwei Guo, Siyang Yuan, Yaoyao Ping Apr 2022

Design And Development Of A Simulation System For Scheduling In Cloud Manufacturing Based On Microservice Architecture, Yongkui Liu, Ming Zeng, Lin Zhang, Jinwei Guo, Siyang Yuan, Yaoyao Ping

Journal of System Simulation

Abstract: In view of the lack of the low coupling and highly extensible cloud manufacturing scheduling simulation system, that leads to inconvenience of the performance test on scheduling algorithms, a scalable cloud manufacturing scheduling model with the scheduling goal of the minimization of cost and completion time and the maximization of quality of service is proposed. A micro-service architecture based cloud manufacturing scheduling simulation system is designed and developed, which realizes the functions of system management, resource management, task management and simulation management, and has the characteristics of flexible autonomy, stability and scalability. The simulation system facilitates the …

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Image Reconstruction Of Electrical Capacitance Tomography Based On Convolutional Neural Network And Finite Element Simulation, Lifeng Zhang, Huiren Wang Apr 2022

Image Reconstruction Of Electrical Capacitance Tomography Based On Convolutional Neural Network And Finite Element Simulation, Lifeng Zhang, Huiren Wang

Journal of System Simulation

Abstract: To address the issues related to the mixed hybrid telemetry, track and command(TT&C) resource, including multiple attributes, large differences in preferences and scheduling conflicts when resources are limited in joint scheduling, on the basis of the description method in the single system TT&C network scheduling research, the characteristics of the hybrid TT&C task requirements are analyzed and the standardized description of the hybrid TT&C resource scheduling task requirements is provided. With the goal of maximizing the return value of TT&C scheduling, a hybrid resource joint scheduling model is established. A solution strategy based on an improved genetic …

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Indoor Positioning Algorithm Based On Xgboost Prediction And Elastic Net Error Compensation, Xiaofei Kang, Xuan Zeng, Wei Qiao Apr 2022

Indoor Positioning Algorithm Based On Xgboost Prediction And Elastic Net Error Compensation, Xiaofei Kang, Xuan Zeng, Wei Qiao

Journal of System Simulation

Abstract: Aiming at the multi-depot half-open vehicle routing problem and consideringthe soft time window constraints and vehicle speed changes, an optimization model with the goal of maximizing average customer satisfaction, shortest distribution distance and minimum distribution cost is established and a two-stage solution algorithm is designed. The self-adaptive grid density method and neighborhood crowding density method are used to maintain the external archives and to select the global optimal particles, and the convergence of the multi-objective particle swarm optimization (MOPSO) and the diversity of the later population can be improved to obtain the initial feasible solution. The initial feasible …

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Feature Matching Algorithm Based On Optimal Geometric Constraints And Ransac, Xiaojuan Ning, Jieru Li, Fan Gao, Yinghui Wang Apr 2022

Feature Matching Algorithm Based On Optimal Geometric Constraints And Ransac, Xiaojuan Ning, Jieru Li, Fan Gao, Yinghui Wang

Journal of System Simulation

Abstract: In order to solve the problem that it's hard to reconcile the quality and computational efficiency of feature point matching. The initial matching for the extracted feature points is implemented through k-nearest neighbor (KNN) algorithm. According to the characteristics of equal length and same slope of the connecting line between matching points, the optimal geometric constraint is constructed based on the statistical sorting strategy to eliminate the obvious matching errors. Then random sample consensus (RANSAC) algorithm is utilized for further filtering to ensure the accuracy of the feature matching point pairs. Experimental results show that the method can obtain …

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Motion Simulation And Performance Analysis Of 2d Variable Stiffness Snake-Like Robot, Yanqin Long, Guifang Qiao, Guangming Song, Ying Zhang, Linlin Cheng Apr 2022

Motion Simulation And Performance Analysis Of 2d Variable Stiffness Snake-Like Robot, Yanqin Long, Guifang Qiao, Guangming Song, Ying Zhang, Linlin Cheng

Journal of System Simulation

Abstract: Mutual interference of vehicular laser radar causes serious performance reduction of target detection and tracking. From spatial, time and modulation frequency, various possible interference of lidars of pulse and frequency modulated continuous wave method in road environments are studied by simulation. The possibility of the interference is calculated, the features and performance reduction of the interference are analyzed. For the possible interference, using a method of pseudo random noise code to modulate the output amplitude of the continuous wave laser can effectively reduce the probability of interference and ensure the reliable operation of lidar in road environments.

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Optimization Of Dynamic Post-Disaster Emergency Distribution Network Under Perspective Of Rescue Efficiency, Xinyu Gao, Jing Ni Apr 2022

Optimization Of Dynamic Post-Disaster Emergency Distribution Network Under Perspective Of Rescue Efficiency, Xinyu Gao, Jing Ni

Journal of System Simulation

Abstract: Aiming at the emergency rescue, a dynamic directed rescue network is established with the dynamic changes of the location, demand, and affected population of disaster site, and a mathematical model is constructed with the maximum rescue efficiency. A data envelope analysis model is applied to evaluate the efficiency of each rescue route segment. An efficiency-based dynamic routing model is established to transform the dynamic routes into the multi-stage static routes through the time slice division. An improved hybrid greedy-ant colony optimization algorithm is designed to solve the model, and the proposed algorithm is compared with the genetic algorithm, particle …

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Idea Of Infinitesimal Method-Introduced Hybrid Tt&C Resources Joint Scheduling, Naiyang Xue, Dan Ding, Hongmin Wang, Yile Fan, Zhongqian Liu Apr 2022

Idea Of Infinitesimal Method-Introduced Hybrid Tt&C Resources Joint Scheduling, Naiyang Xue, Dan Ding, Hongmin Wang, Yile Fan, Zhongqian Liu

Journal of System Simulation

Abstract: Aiming at the study on the motion performance of a two-dimensional variable stiffness snake-robot, a Simulink/Adams co-simulation model is established, and the effects of the damping coefficient, the stiffness parameters and the angular frequency of the variable stiffness actuator on the motion energy consumption are analyzed. To realize the synchronous control of joint trajectory and stiffness, a motion controller based on two-layer CPG is proposed. The results show that the damping coefficient can effectively reduce the proportion of starting energy consumption of the variable stiffness snake-like robot, and the ratio of starting energy consumption increases with the stiffness parameter …

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Research On Multi-Depot Half-Open Vehicle Routing Problem With Time-Varying Speed, Kaiqing Zhang, Qichun Ji Apr 2022

Research On Multi-Depot Half-Open Vehicle Routing Problem With Time-Varying Speed, Kaiqing Zhang, Qichun Ji

Journal of System Simulation

Abstract: Based on the analysis of operation concept and its elements, this paper proposes a framework of operation effectiveness simulation evaluation under the guidance of operation concept. Based on this framework, the basic idea of operation effectiveness simulation evaluation index construction under the guidance of operation concept is put forward. The specific methods of operation task modeling based on description, operation activity modeling based on decomposition, and operation effectiveness index selection based on effect are studied. The operation effectiveness simulation evaluation index system is constructed by taking the ground assault unit mountain key point capture and attack operation task guided …

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Continuous Simulation Technology For Multi-State Evolution Of Urban Road Traffic, Qinglu Ma, Lin Zhang, Xinxin Yuan, Fengjie Liu Apr 2022

Continuous Simulation Technology For Multi-State Evolution Of Urban Road Traffic, Qinglu Ma, Lin Zhang, Xinxin Yuan, Fengjie Liu

Journal of System Simulation

Abstract: Arming at the decreased positioning accuracy caused by the environment dynamic change of indoor positioning system, an error compensation algorithm based on XGBoost fusion elastic net is proposed. XGBoost positioning model is used to make a preliminary prediction on the target position. When the indoor environment changes, the elastic net algorithm is used to construct an error compensation model to correct the positioning error of XGBoost positioning model. The experimental results show that when only 15% of the fingerprint database samples need to be updated, the positioning accuracy of the proposed algorithm is controlled in 0.73m at the 80% …

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Simulation On Critical Conditions Of Delay Diffusion In Scale-Free Logistics Network, Hongguang Yao, Huihui Xiao, Hang Zhang Apr 2022

Simulation On Critical Conditions Of Delay Diffusion In Scale-Free Logistics Network, Hongguang Yao, Huihui Xiao, Hang Zhang

Journal of System Simulation

Abstract: Aiming at the critical condition of delay diffusion in scale-free logistics network, a susceptible-infected-susceptible(SIS) model based on the density of delay nodes is established by mean field theory, and the critical value is solved. By designing the delay diffusion simulation system in logistics network, a virtual network with scale-free attribute is generated, and the critical condition is verified by simulation. The results show that there are a few key nodes with high value in scale-free logistics network. Once these nodes have service obstades, compared with other nodes, it will lead to a larger range of delay and faster …

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Designing A Digital Interactive Emotion Measure (Diem) For Digital Media: Theoretical Foundations And Validation Protocols, Celeste Sangiorgio, Cassandra Berbary, Cory Crane, Caroline Easton Apr 2022

Designing A Digital Interactive Emotion Measure (Diem) For Digital Media: Theoretical Foundations And Validation Protocols, Celeste Sangiorgio, Cassandra Berbary, Cory Crane, Caroline Easton

Frameless

Awareness of emotions is often a treatment target in psychotherapy, but it is difficult to assess emotions due to ambiguity in measurement or scale design. Lack of clarity in scale design may increase risk that participant interpretations of scale items may not align with emotion constructs those scales were designed to capture. Furthermore, emphasis on verbal or written cues leads to low scientific representation of patients who cannot read emotion scales (e.g., low literacy). Touch-screen applications provide a unique opportunity to create a visual emotion measure which has low barriers but can be used to assess a high level of …

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Novel 360-Degree Camera, Ian Gauger, Andrew Kurtz, Zakariya Niazi Apr 2022

Novel 360-Degree Camera, Ian Gauger, Andrew Kurtz, Zakariya Niazi

Frameless

Circle Optics is developing novel technology for low-parallax, real time, panoramic image capture using an integrated array of multiple adjacent polygonal-edged cameras. This technology can be optimized and deployed for a variety of markets, including cinematic VR. Circle Optics’ existing prototype, Hydra Alpha, will be demonstrated.

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Warehouse And Logistics: Smart Picking With Vuzix Smart Glasses, Elise Hemink Apr 2022

Warehouse And Logistics: Smart Picking With Vuzix Smart Glasses, Elise Hemink

Frameless

Vuzix is an industry leader in augmented reality (AR) technology. We provide innovative products to an array of industries, a few being defense, security, enterprise, and consumers. Our AR technology provides a perfect balance of engagement in the digital and real worlds thanks to their innovative optics, AI apps and 5G capability.

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Creating A Virtual Reality Experience In Service To A Non-Profit Agency, Frank Deese, Susan Lakin, Isabelle Anderson Apr 2022

Creating A Virtual Reality Experience In Service To A Non-Profit Agency, Frank Deese, Susan Lakin, Isabelle Anderson

Frameless

In the summer of 2018, RIT Professors Susan Lakin and Frank Deese discussed with the principal officers of the Society for the Protection and Care of Children (SPCC) in Rochester how the new technology of Virtual Reality might be used to not only impart information to viewers, but generate empathy for those receiving services from the organization as well as those performing those services. Their ultimate goal was to create an experience that could be viewed with VR headsets at fundraising events and on a website using low-cost Google Cardboard.

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Can We Walk In Our Patients’ Shoes? Immersive Virtual Reality As An Empathy Training Tool For Medical Students, Riham Alieldin, Raffaella Borasi, Anne Nofziger, Karen Deangelis, Sarah Peyre Apr 2022

Can We Walk In Our Patients’ Shoes? Immersive Virtual Reality As An Empathy Training Tool For Medical Students, Riham Alieldin, Raffaella Borasi, Anne Nofziger, Karen Deangelis, Sarah Peyre

Frameless

Empathy is arguably the “backbone” of the patient-physician relationship. It has been shown to have numerous positive clinical outcomes especially in a patient-centered careservice. Nevertheless, studies have shown a disintegration of empathy and compassion in physicians during medical school and residency training due to the lack of standardization of empathy training in medical education.

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Visual Attention Methods In Deep Learning: An In-Depth Survey, Mohammed Hassanin, Anwar Saeed, Ibrahim Radwan, Fahad Shahbaz Khan, Ajmal Mian Apr 2022

Visual Attention Methods In Deep Learning: An In-Depth Survey, Mohammed Hassanin, Anwar Saeed, Ibrahim Radwan, Fahad Shahbaz Khan, Ajmal Mian

Computer Vision Faculty Publications

Inspired by the human cognitive system, attention is a mechanism that imitates the human cognitive awareness about specific information, amplifying critical details to focus more on the essential aspects of data. Deep learning has employed attention to boost performance for many applications. Interestingly, the same attention design can suit processing different data modalities and can easily be incorporated into large networks. Furthermore, multiple complementary attention mechanisms can be incorporated in one network. Hence, attention techniques have become extremely attractive. However, the literature lacks a comprehensive survey specific to attention techniques to guide researchers in employing attention in their deep models. …

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Iot Clusters Platform For Data Collection, Analysis, And Visualization Use Case, Soin Abdoul Kassif Baba M Traore Apr 2022

Iot Clusters Platform For Data Collection, Analysis, And Visualization Use Case, Soin Abdoul Kassif Baba M Traore

Symposium of Student Scholars

Climate change is happening, and many countries are already facing devastating consequences. Populations worldwide are adapting to the season's unpredictability they relay to lands for agriculture. Our first research was to develop an IoT Clusters Platform for Data Collection, analysis, and visualization. The platform comprises hardware parts with Raspberry Pi and Arduino's clusters connected to multiple sensors. The clusters transmit data collected in real-time to microservices-based servers where the data can be accessed and processed. Our objectives in developing this platform were to create an efficient data collection system, relatively cheap to implement and easy to deploy in any part …

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Machine Learning-Oriented Predictive Maintenance (Pdm) Framework For Autonomous Vehicles (Avs): Adopting Blockchain For Pdm Solution, Md Jobair Hossain Faruk, Hossain Shahriar, Maria Valero Apr 2022

Machine Learning-Oriented Predictive Maintenance (Pdm) Framework For Autonomous Vehicles (Avs): Adopting Blockchain For Pdm Solution, Md Jobair Hossain Faruk, Hossain Shahriar, Maria Valero

Symposium of Student Scholars

Autonomous Vehicles (AVs) refers to smart, connected and multimedia cars with technological megatrends of the fourth industrial revolution (Industry 4.0) and have gained huge strive in today's world. AVs adopt automated driving systems (ADS) technique that permits the vehicle to manage and control driving points without human drivers by utilizing advanced equipment including a combination of sensors, controllers, onboard computers, actuators, algorithms, and advanced software embedded in the different parts of the vehicle. These advanced sensors provide unique inputs to the ADS to generate a path from point A to point B. Ensuring the safety of sensors by limiting maintenance …

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Deep Learning: The Many Approaches Of Intrusion Detection System Can Be Implemented And Improved Upon, Trinity Taylor Apr 2022

Deep Learning: The Many Approaches Of Intrusion Detection System Can Be Implemented And Improved Upon, Trinity Taylor

Cybersecurity Undergraduate Research Showcase

For my research topic I decided to look at Deep learning. Deep learning can be used in many ways for example in web searching. Deep learning can also can improve new businesses and products. Deep learning could lead to amazing discoveries. Deep learning is making a neural network learn something. In my research I talk about Intrusion detection system, traditional approach for intrusion detection, existing intrusion detection, machine learning and deep learning based intrusion detection system, and future work.

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Internet Of Things Device Capabilities, Architectures, Protocols, And Smart Applications In Healthcare Domain: A Review, Md. Milon Islam, Sheikh Noorduddin, Fakhreddine (Fakhri) Karray, Ghulam Muhammad Apr 2022

Internet Of Things Device Capabilities, Architectures, Protocols, And Smart Applications In Healthcare Domain: A Review, Md. Milon Islam, Sheikh Noorduddin, Fakhreddine (Fakhri) Karray, Ghulam Muhammad

Machine Learning Faculty Publications

Nowadays, the Internet has spread to practically every country around the world and is having unprecedented effects on people's lives. The Internet of Things (IoT) is getting more popular and has a high level of interest in both practitioners and academicians in the age of wireless communication due to its diverse applications. The IoT is a technology that enables everyday things to become savvier, everyday computation towards becoming intellectual, and everyday communication to become a little more insightful. In this paper, the most common and popular IoT device capabilities, architectures, and protocols are demonstrated in brief to provide a clear …

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Mucot: Multilingual Contrastive Training For Question-Answering In Low-Resource Languages, Gokul Karthik Kumar, Abhishek Singh Gehlot, Sahal Shaji Mullappilly, Karthik Nandakumar Apr 2022

Mucot: Multilingual Contrastive Training For Question-Answering In Low-Resource Languages, Gokul Karthik Kumar, Abhishek Singh Gehlot, Sahal Shaji Mullappilly, Karthik Nandakumar

Computer Vision Faculty Publications

Accuracy of English-language Question Answering (QA) systems has improved significantly in recent years with the advent of Transformer-based models (e.g., BERT). These models are pre-trained in a self-supervised fashion with a large English text corpus and further fine-tuned with a massive English QA dataset (e.g., SQuAD). However, QA datasets on such a scale are not available for most of the other languages. Multi-lingual BERT-based models (mBERT) are often used to transfer knowledge from high-resource languages to low-resource languages. Since these models are pre-trained with huge text corpora containing multiple languages, they typically learn language-agnostic embeddings for tokens from different languages. …

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Practical Considerations And Applications For Autonomous Robot Swarms, Rory Alan Hector Apr 2022

Practical Considerations And Applications For Autonomous Robot Swarms, Rory Alan Hector

LSU Doctoral Dissertations

In recent years, the study of autonomous entities such as unmanned vehicles has begun to revolutionize both military and civilian devices. One important research focus of autonomous entities has been coordination problems for autonomous robot swarms. Traditionally, robot models are used for algorithms that account for the minimum specifications needed to operate the swarm. However, these theoretical models also gloss over important practical details. Some of these details, such as time, have been considered before (as epochs of execution). In this dissertation, we examine these details in the context of several problems and introduce new performance measures to capture practical …

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Multimodal Multi-Head Convolutional Attention With Various Kernel Sizes For Medical Image Super-Resolution, Mariana-Iuliana Georgescu, Radu Tudor Ionescu, Andreea-Iuliana Miron, Olivian Savencu, Nicolae Verga, Nicolae-Cătălin Ristea, Fahad Shabaz Khan Apr 2022

Multimodal Multi-Head Convolutional Attention With Various Kernel Sizes For Medical Image Super-Resolution, Mariana-Iuliana Georgescu, Radu Tudor Ionescu, Andreea-Iuliana Miron, Olivian Savencu, Nicolae Verga, Nicolae-Cătălin Ristea, Fahad Shabaz Khan

Computer Vision Faculty Publications

Super-resolving medical images can help physicians in providing more accurate diagnostics. In many situations, computed tomography (CT) or magnetic resonance imaging (MRI) techniques output several scans (modes) during a single investigation, which can jointly be used (in a multimodal fashion) to further boost the quality of super-resolution results. To this end, we propose a novel multimodal multi-head convolutional attention module to super-resolve CT and MRI scans. Our attention module uses the convolution operation to perform joint spatial-channel attention on multiple concatenated input tensors, where the kernel (receptive field) size controls the reduction rate of the spatial attention and the number …

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Improving Negation Detection With Negation-Focused Pre-Training, Hung Thinh Truong, Timothy Baldwin, Trevor Cohn, Karin Verspoor Apr 2022

Improving Negation Detection With Negation-Focused Pre-Training, Hung Thinh Truong, Timothy Baldwin, Trevor Cohn, Karin Verspoor

Natural Language Processing Faculty Publications

Negation is a common linguistic feature that is crucial in many language understanding tasks, yet it remains a hard problem due to diversity in its expression in different types of text. Recent work has shown that state-of-the-art NLP models underperform on samples containing negation in various tasks, and that negation detection models do not transfer well across domains. We propose a new negation-focused pre-training strategy, involving targeted data augmentation and negation masking, to better incorporate negation information into language models. Extensive experiments on common benchmarks show that our proposed approach improves negation detection performance and generalizability over the strong baseline …

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Wrapper And Hybrid Feature Selection Methods Using Metaheuristic Algorithms For English Text Classification: A Systematic Review, Osamah Mohammed Alyasiri, Yu N. Cheah, Ammar Kamal Abasi, Omar Mustafa Al-Janabi Apr 2022

Wrapper And Hybrid Feature Selection Methods Using Metaheuristic Algorithms For English Text Classification: A Systematic Review, Osamah Mohammed Alyasiri, Yu N. Cheah, Ammar Kamal Abasi, Omar Mustafa Al-Janabi

Machine Learning Faculty Publications

Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. …

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Intra-Hour Solar Forecasting Using Cloud Dynamics Features Extracted From Ground-Based Infrared Sky Images, Guillermo Terrén-Serrano Apr 2022

Intra-Hour Solar Forecasting Using Cloud Dynamics Features Extracted From Ground-Based Infrared Sky Images, Guillermo Terrén-Serrano

Electrical and Computer Engineering ETDs

Due to the increasing use of photovoltaic systems, power grids are vulnerable to the projection of shadows from moving clouds. An intra-hour solar forecast provides power grids with the capability of automatically controlling the dispatch of energy, reducing the additional cost for a guaranteed, reliable supply of energy (i.e., energy storage). This dissertation introduces a novel sky imager consisting of a long-wave radiometric infrared camera and a visible light camera with a fisheye lens. The imager is mounted on a solar tracker to maintain the Sun in the center of the images throughout the day, reducing the scattering effect produced …

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Human-Machine Communication: Complete Volume 4 Apr 2022

Human-Machine Communication: Complete Volume 4

Human-Machine Communication

This is the complete volume of HMC Volume 4.

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Embracing Ai-Based Education: Perceived Social Presence Of Human Teachers And Expectations About Machine Teachers In Online Education, Jihyun Kim, Kelly Merrill Jr., Kun Xu, Deanna D. Sellnow Apr 2022

Embracing Ai-Based Education: Perceived Social Presence Of Human Teachers And Expectations About Machine Teachers In Online Education, Jihyun Kim, Kelly Merrill Jr., Kun Xu, Deanna D. Sellnow

Human-Machine Communication

Technological advancements in education have turned the idea of machines as teachers into a reality. To better understand this phenomenon, the present study explores how college students develop expectations (or anticipations) about a machine teacher, particularly an AI teaching assistant. Specifically, the study examines whether students’ previous experiences with online courses taught by a human teacher would influence their expectations about AI teaching assistants in future online courses. An online survey was conducted to collect data from college students in the United States. Findings indicate that positively experienced social presence of a human teacher helps develop positive expectations about an …

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Sex With Robots And Human-Machine Sexualities: Encounters Between Human-Machine Communication And Sexuality Studies, Marco Dehnert Apr 2022

Sex With Robots And Human-Machine Sexualities: Encounters Between Human-Machine Communication And Sexuality Studies, Marco Dehnert

Human-Machine Communication

Sex robots are a controversial topic. Understood as artificial-intelligence enhanced humanoid robots designed for use in partnered and solo sex, sex robots offer ample opportunities for theorizing from a Human-Machine Communication (HMC) perspective. This comparative literature review conjoins the seemingly disconnected literatures of HMC and sexuality studies (SeS) to explore questions surrounding intimacy, love, desire, sex, and sexuality among humans and machines. In particular, I argue for understanding human-machine sexualities as communicative sexuotechnical-assemblages, extending previous efforts in both HMC and SeS for more-than-human, ecological, and more fluid approaches to humans and machines, as well as to sex and sexuality. This …

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