Photoresponsive materials have attracted growing interest because of their potential applications in materials science, such as photoswitches, photopatterning, information storage, and so on. However, there are some challenges for photoresponsive materials for certain applications: 1) Only a few photoresponsive surfaces are transformed into multiple states after photoreactions to adapt to changing environmental conditions; 2) Photoresponsive materials may not function properly in cold environments, especially for gels. To address these problems, we have recently developed photoresponsive materials based on ruthenium (Ru) complexes. Such Ru complexes showed a photoinduced ligand substitution under visible light irradiation. Reconfigurable surfaces that can adapt to environmental changes and photoresponsive organohydrogels that function effectively at sub‐zero temperatures have been fabricated using photoresponsive Ru complexes. Herein, it is demonstrated that based on photocontrolled Ru–ligand coordination, reconfigurable surfaces can be modified for user‐defined functions via visible light irradiation and that photoresponsive gels can function even at –20 °C. As a perspective, Ru‐containing photoresponsive complexes could open up pathways for a variety of applications.
{"title":"Reconfigurable Materials Based on Photocontrolled Metal–Ligand Coordination","authors":"Jianxiong Han, Yun-shuai Huang, Ni Yang, Si Wu","doi":"10.1002/aisy.202000112","DOIUrl":"https://doi.org/10.1002/aisy.202000112","url":null,"abstract":"Photoresponsive materials have attracted growing interest because of their potential applications in materials science, such as photoswitches, photopatterning, information storage, and so on. However, there are some challenges for photoresponsive materials for certain applications: 1) Only a few photoresponsive surfaces are transformed into multiple states after photoreactions to adapt to changing environmental conditions; 2) Photoresponsive materials may not function properly in cold environments, especially for gels. To address these problems, we have recently developed photoresponsive materials based on ruthenium (Ru) complexes. Such Ru complexes showed a photoinduced ligand substitution under visible light irradiation. Reconfigurable surfaces that can adapt to environmental changes and photoresponsive organohydrogels that function effectively at sub‐zero temperatures have been fabricated using photoresponsive Ru complexes. Herein, it is demonstrated that based on photocontrolled Ru–ligand coordination, reconfigurable surfaces can be modified for user‐defined functions via visible light irradiation and that photoresponsive gels can function even at –20 °C. As a perspective, Ru‐containing photoresponsive complexes could open up pathways for a variety of applications.","PeriodicalId":7187,"journal":{"name":"Advanced Intelligent Systems","volume":"24 11 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82682905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The economical, agile, customizable manufacturing, and integration of multifunctional device modules into networked systems with mechanical compliance and robustness enable unprecedented human‐integrated smart wearables and usher in exciting opportunities in emerging technologies. The additive manufacturing (AM) processes have emerged as potential candidates for rapid prototyping printed devices with diversified functionalities, e.g., energy harvesting/storage, sensing, actuation, and computation. However, there are few review reports about the ink‐based additive nanomanufacturing of functional materials for human‐integrated smart wearables. To fill this gap, herein, the recent progress in ink‐based additive nanomanufacturing technologies, focusing on their capability and potential for producing wearable human‐integrated devices, is reviewed. The manufacturing process integration, functional materials, device implementation, and application performance issues in designing and implementing the ink‐based additively nanomanufactured wearable systems are thoroughly discussed. The recent printed devices focusing on the processing conditions and performance metrics are comprehensively reviewed. Finally, the vision and outlook for the challenges and opportunities associated with related topics are provided. The rapid progress achieved in related disciplines enables more capable smart human‐integrated wearable systems that can be fully printed with rapid, agile, reconfigurable, and smart AM platforms.
{"title":"Ink‐Based Additive Nanomanufacturing of Functional Materials for Human‐Integrated Smart Wearables","authors":"Shujia Xu, Wenzhuo Wu","doi":"10.1002/aisy.202000117","DOIUrl":"https://doi.org/10.1002/aisy.202000117","url":null,"abstract":"The economical, agile, customizable manufacturing, and integration of multifunctional device modules into networked systems with mechanical compliance and robustness enable unprecedented human‐integrated smart wearables and usher in exciting opportunities in emerging technologies. The additive manufacturing (AM) processes have emerged as potential candidates for rapid prototyping printed devices with diversified functionalities, e.g., energy harvesting/storage, sensing, actuation, and computation. However, there are few review reports about the ink‐based additive nanomanufacturing of functional materials for human‐integrated smart wearables. To fill this gap, herein, the recent progress in ink‐based additive nanomanufacturing technologies, focusing on their capability and potential for producing wearable human‐integrated devices, is reviewed. The manufacturing process integration, functional materials, device implementation, and application performance issues in designing and implementing the ink‐based additively nanomanufactured wearable systems are thoroughly discussed. The recent printed devices focusing on the processing conditions and performance metrics are comprehensively reviewed. Finally, the vision and outlook for the challenges and opportunities associated with related topics are provided. The rapid progress achieved in related disciplines enables more capable smart human‐integrated wearable systems that can be fully printed with rapid, agile, reconfigurable, and smart AM platforms.","PeriodicalId":7187,"journal":{"name":"Advanced Intelligent Systems","volume":"91 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85659195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chihun Lee, Juwon Na, Kyongho Park, Hye-jeong Yu, Jongsun Kim, Kwon-Il Choi, D. Park, Seongjin Park, J. Rho, Seungchul Lee
This study combines an artificial neural network (ANN) and a random search to develop a system to recommend process conditions for injection molding. Both simulation and experimental results are collected using a mixed sampling method that combines Taguchi and random sampling. The dataset consists of 3600 simulations and 476 experiments from 36 different molds. Each datum has five process and 15 geometry features as input and one weight feature as output. Hyper‐parameter tuning is conducted to find the optimal ANN model. Then, transfer learning is introduced, which allows the use of simultaneous experimental and simulation data to reduce the error. The final prediction model has a root mean‐square error of 0.846. To develop a recommender system, random search is conducted using the trained ANN forward model. As a result, the weight‐prediction model based on simulated data has a relative error (RE) of 0.73%, and the weight prediction using the transfer model has an RE of 0.662%. A user interface system is also developed, which can be used directly with the injection‐molding machine. This method enables the setting of process conditions that yield parts having weights close to the target, by considering only the geometry and target weight.
{"title":"Development of Artificial Neural Network System to Recommend Process Conditions of Injection Molding for Various Geometries","authors":"Chihun Lee, Juwon Na, Kyongho Park, Hye-jeong Yu, Jongsun Kim, Kwon-Il Choi, D. Park, Seongjin Park, J. Rho, Seungchul Lee","doi":"10.1002/aisy.202000037","DOIUrl":"https://doi.org/10.1002/aisy.202000037","url":null,"abstract":"This study combines an artificial neural network (ANN) and a random search to develop a system to recommend process conditions for injection molding. Both simulation and experimental results are collected using a mixed sampling method that combines Taguchi and random sampling. The dataset consists of 3600 simulations and 476 experiments from 36 different molds. Each datum has five process and 15 geometry features as input and one weight feature as output. Hyper‐parameter tuning is conducted to find the optimal ANN model. Then, transfer learning is introduced, which allows the use of simultaneous experimental and simulation data to reduce the error. The final prediction model has a root mean‐square error of 0.846. To develop a recommender system, random search is conducted using the trained ANN forward model. As a result, the weight‐prediction model based on simulated data has a relative error (RE) of 0.73%, and the weight prediction using the transfer model has an RE of 0.662%. A user interface system is also developed, which can be used directly with the injection‐molding machine. This method enables the setting of process conditions that yield parts having weights close to the target, by considering only the geometry and target weight.","PeriodicalId":7187,"journal":{"name":"Advanced Intelligent Systems","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75161616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yegor Piskarev, J. Shintake, V. Ramachandran, Neil Baugh, M. Dickey, D. Floreano
The inherent compliance of soft robots often makes it difficult for them to exert forces on surrounding surfaces or withstand mechanical loading. Controlled stiffness is a solution to empower soft robots with the ability to apply large forces on their environments and sustain external loads without deformations. Herein, a compact, soft actuator composed of a shared electrode used for both electrostatic actuation and variable stiffness is described. The device operates as a dielectric elastomer actuator, while variable stiffness is provided by a shared electrode made of gallium. The fabricated actuator, namely variable stiffness dielectric elastomer actuator (VSDEA), has a compact and lightweight structure with a thickness of 930 μm and a mass of 0.7 g. It exhibits a stiffness change of 183×, a bending angle of 31°, and a blocked force of 0.65 mN. Thanks to the lightweight feature, the stiffness change per mass of the actuator (261× g−1) is 2.6 times higher than that of the other type of VSDEA that has no shared electrode.
{"title":"Lighter and Stronger: Cofabricated Electrodes and Variable Stiffness Elements in Dielectric Actuators","authors":"Yegor Piskarev, J. Shintake, V. Ramachandran, Neil Baugh, M. Dickey, D. Floreano","doi":"10.1002/aisy.202000069","DOIUrl":"https://doi.org/10.1002/aisy.202000069","url":null,"abstract":"The inherent compliance of soft robots often makes it difficult for them to exert forces on surrounding surfaces or withstand mechanical loading. Controlled stiffness is a solution to empower soft robots with the ability to apply large forces on their environments and sustain external loads without deformations. Herein, a compact, soft actuator composed of a shared electrode used for both electrostatic actuation and variable stiffness is described. The device operates as a dielectric elastomer actuator, while variable stiffness is provided by a shared electrode made of gallium. The fabricated actuator, namely variable stiffness dielectric elastomer actuator (VSDEA), has a compact and lightweight structure with a thickness of 930 μm and a mass of 0.7 g. It exhibits a stiffness change of 183×, a bending angle of 31°, and a blocked force of 0.65 mN. Thanks to the lightweight feature, the stiffness change per mass of the actuator (261× g−1) is 2.6 times higher than that of the other type of VSDEA that has no shared electrode.","PeriodicalId":7187,"journal":{"name":"Advanced Intelligent Systems","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82472943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Guido T. van Moolenbroek, Tania Patiño, J. Llop, S. Sánchez
Medical imaging serves to obtain anatomical and physiological data, supporting medical diagnostics as well as providing therapeutic evaluation and guidance. A variety of contrast agents have been developed to enhance the recorded signals and to provide molecular imaging. However, fast clearance from the body or nonspecific biodistribution often limit their efficiency, constituting challenges that need to be overcome. Nanoparticle‐based systems are currently emerging as versatile and highly integrated platforms providing improved circulating times, tissue specificity, high loading capacity for signaling moieties, and multimodal imaging features. Furthermore, nanoengineered devices can be tuned for specific applications and the development of responsive behaviors. Responses include in situ modulation of nanoparticle size, increased intratissue mobility through active propulsion of motorized particles, and active modulation of the particle surroundings such as the extracellular matrix for an improved penetration and retention at the desired locations. Once accumulated in the targeted tissue, smart nanoparticle‐based contrast agents can provide molecular sensing of biomarkers or characteristics of the tissue microenvironment. In this case, the signal or contrast provided by the nanosystem is responsive to the presence or concentration of an analyte. Herein, recent developments of intelligent nanosystems to improve medical imaging are presented.
{"title":"Engineering Intelligent Nanosystems for Enhanced Medical Imaging","authors":"Guido T. van Moolenbroek, Tania Patiño, J. Llop, S. Sánchez","doi":"10.1002/aisy.202000087","DOIUrl":"https://doi.org/10.1002/aisy.202000087","url":null,"abstract":"Medical imaging serves to obtain anatomical and physiological data, supporting medical diagnostics as well as providing therapeutic evaluation and guidance. A variety of contrast agents have been developed to enhance the recorded signals and to provide molecular imaging. However, fast clearance from the body or nonspecific biodistribution often limit their efficiency, constituting challenges that need to be overcome. Nanoparticle‐based systems are currently emerging as versatile and highly integrated platforms providing improved circulating times, tissue specificity, high loading capacity for signaling moieties, and multimodal imaging features. Furthermore, nanoengineered devices can be tuned for specific applications and the development of responsive behaviors. Responses include in situ modulation of nanoparticle size, increased intratissue mobility through active propulsion of motorized particles, and active modulation of the particle surroundings such as the extracellular matrix for an improved penetration and retention at the desired locations. Once accumulated in the targeted tissue, smart nanoparticle‐based contrast agents can provide molecular sensing of biomarkers or characteristics of the tissue microenvironment. In this case, the signal or contrast provided by the nanosystem is responsive to the presence or concentration of an analyte. Herein, recent developments of intelligent nanosystems to improve medical imaging are presented.","PeriodicalId":7187,"journal":{"name":"Advanced Intelligent Systems","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80807782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mengya Xu, Seenivasan Lalithkumar, L. Yeo, Hongliang Ren
A lack of sensory feedback often hinders minimally invasive operations. Although endoscopy has addressed this limitation to an extent, endovascular procedures such as angioplasty or stenting still face significant challenges. Sensors that rely on a clear line of sight cannot be used because it is unable to gather feedback in blood environments. During the stent deployment procedure, feedback on the deployed stent's state is critical because a partially open stent can affect the blood flow. Despite this, no robust and noninvasive clinical solutions that allow real‐time monitoring of the stent deployment exists. In recent years, radio frequency (RF)‐based sensors can detect the shape and material of an object that is hidden from the direct line of sight. Herein, the use of a 3D RF‐based imaging sensor and a novel Convolutional Neural Network (CNN) called StentNet is proposed for detecting the stent's state without a need for a clear line of sight. The StentNet achieves an overall accuracy of 90% in detecting the state of an occluded stent in the test dataset. Compared with an existing CNN model, the StentNet significantly outperforms the 3D LeNet in the evaluation metrics such as accuracy, precision, recall, and F1‐score.
{"title":"Stent Deployment Detection Using Radio Frequency‐Based Sensor and Convolutional Neural Networks","authors":"Mengya Xu, Seenivasan Lalithkumar, L. Yeo, Hongliang Ren","doi":"10.1002/aisy.202000092","DOIUrl":"https://doi.org/10.1002/aisy.202000092","url":null,"abstract":"A lack of sensory feedback often hinders minimally invasive operations. Although endoscopy has addressed this limitation to an extent, endovascular procedures such as angioplasty or stenting still face significant challenges. Sensors that rely on a clear line of sight cannot be used because it is unable to gather feedback in blood environments. During the stent deployment procedure, feedback on the deployed stent's state is critical because a partially open stent can affect the blood flow. Despite this, no robust and noninvasive clinical solutions that allow real‐time monitoring of the stent deployment exists. In recent years, radio frequency (RF)‐based sensors can detect the shape and material of an object that is hidden from the direct line of sight. Herein, the use of a 3D RF‐based imaging sensor and a novel Convolutional Neural Network (CNN) called StentNet is proposed for detecting the stent's state without a need for a clear line of sight. The StentNet achieves an overall accuracy of 90% in detecting the state of an occluded stent in the test dataset. Compared with an existing CNN model, the StentNet significantly outperforms the 3D LeNet in the evaluation metrics such as accuracy, precision, recall, and F1‐score.","PeriodicalId":7187,"journal":{"name":"Advanced Intelligent Systems","volume":"178 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73656083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Integrated circuits designed to perform mathematical operations, such as Fourier transforms and matrix multiplications, in artificial visual perception and intelligent image processing are mainly constructed of conventional logic gates. However, Boolean logic is probably not the most optimal approach for brain‐inspired computing due to the fuzzy nature of biologic neural networks. This work demonstrates an application based on programmable fuzzy‐logic gates capable of combined photoelectric computations. Such an apparatus may be used to perform image compression immediately upon acquisition without having the need to rely on interaction between separate processor and sensor modules. It is based on resistive memory devices capable of state transitions in response to both electronic and light stimulations. Material nonimplication and logical true operations are first presented. A more complex functionality for material nonimplication of a logic conjunction is then demonstrated. These gates are then used as building blocks in the design and simulation of a configurable matrix multiplication unit that effectively implements in situ image compression. A membership function (FUZZIFY) that may be used to map strict logic levels to incremental fuzzy analog ones is also shown. Finally, an approach for integrating conventional logic with a fuzzy computation is discussed.
{"title":"Programmable Photoelectric Memristor Gates for In Situ Image Compression","authors":"D. Berco, D. Ang, P. S. Kalaga","doi":"10.1002/aisy.202000079","DOIUrl":"https://doi.org/10.1002/aisy.202000079","url":null,"abstract":"Integrated circuits designed to perform mathematical operations, such as Fourier transforms and matrix multiplications, in artificial visual perception and intelligent image processing are mainly constructed of conventional logic gates. However, Boolean logic is probably not the most optimal approach for brain‐inspired computing due to the fuzzy nature of biologic neural networks. This work demonstrates an application based on programmable fuzzy‐logic gates capable of combined photoelectric computations. Such an apparatus may be used to perform image compression immediately upon acquisition without having the need to rely on interaction between separate processor and sensor modules. It is based on resistive memory devices capable of state transitions in response to both electronic and light stimulations. Material nonimplication and logical true operations are first presented. A more complex functionality for material nonimplication of a logic conjunction is then demonstrated. These gates are then used as building blocks in the design and simulation of a configurable matrix multiplication unit that effectively implements in situ image compression. A membership function (FUZZIFY) that may be used to map strict logic levels to incremental fuzzy analog ones is also shown. Finally, an approach for integrating conventional logic with a fuzzy computation is discussed.","PeriodicalId":7187,"journal":{"name":"Advanced Intelligent Systems","volume":"70 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80576656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Herein, a new method for steering liquid metals (LMs) using only a magnetic field in open 3D space is proposed. The magnetic LM is composed of the alloy Galinstan and iron particles. The 3D horizontal and vertical manipulation of a magnetic LM can be realized via an external magnetic field. The magnetically actuated LM is not only manipulated on various complex pathways in the horizontal plane, but also vertically in 3D space without the use of electrolytes and electrodes. As a proof‐of‐principle, an intelligent delivery vehicle that can avoid obstacles and traps horizontally and overcome gravity vertically to offload a cargo is designed and implemented successfully. Furthermore, a biomimetic soft robotics that can realize both in‐plane and out‐of‐plane locomotion is demonstrated using only magnetic field. The novel 3D motion of the demonstrated system facilitates the development of practical LM‐based smart structures and devices.
{"title":"3D Manipulation of Magnetic Liquid Metals","authors":"Wenqing Zhou, Qingxuan Liang, Tianning Chen","doi":"10.1002/aisy.201900170","DOIUrl":"https://doi.org/10.1002/aisy.201900170","url":null,"abstract":"Herein, a new method for steering liquid metals (LMs) using only a magnetic field in open 3D space is proposed. The magnetic LM is composed of the alloy Galinstan and iron particles. The 3D horizontal and vertical manipulation of a magnetic LM can be realized via an external magnetic field. The magnetically actuated LM is not only manipulated on various complex pathways in the horizontal plane, but also vertically in 3D space without the use of electrolytes and electrodes. As a proof‐of‐principle, an intelligent delivery vehicle that can avoid obstacles and traps horizontally and overcome gravity vertically to offload a cargo is designed and implemented successfully. Furthermore, a biomimetic soft robotics that can realize both in‐plane and out‐of‐plane locomotion is demonstrated using only magnetic field. The novel 3D motion of the demonstrated system facilitates the development of practical LM‐based smart structures and devices.","PeriodicalId":7187,"journal":{"name":"Advanced Intelligent Systems","volume":"945 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77572240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Robot audition aims at developing robot's ears that work in the real world, that is, machine listening of multiple sound sources. Its critical problem is noise. Speech interfaces have become more familiar and more indispensable as smartphones and artificial intelligence (AI) speakers spread. Their critical problems are noise and multiple simultaneous speakers. Recently two technological advances have contributed to significantly improve the performance of speech interfaces and robot audition. Emerging deep learning technology has improved noise robustness of automatic speech recognition, whereas microphone array processing has improved the performance of preprocessing such as noise reduction. Herein, an overview and history of robot audition are provided together with introduction of an open‐source software for robot audition and its wide applications in the real world. Also, it is discussed how robot audition contributes to the development of computational auditory scene analysis, that is, understanding of real‐world auditory environments.
{"title":"Robot Audition and Computational Auditory Scene Analysis","authors":"K. Nakadai, Hiroshi G. Okuno","doi":"10.1002/aisy.202000050","DOIUrl":"https://doi.org/10.1002/aisy.202000050","url":null,"abstract":"Robot audition aims at developing robot's ears that work in the real world, that is, machine listening of multiple sound sources. Its critical problem is noise. Speech interfaces have become more familiar and more indispensable as smartphones and artificial intelligence (AI) speakers spread. Their critical problems are noise and multiple simultaneous speakers. Recently two technological advances have contributed to significantly improve the performance of speech interfaces and robot audition. Emerging deep learning technology has improved noise robustness of automatic speech recognition, whereas microphone array processing has improved the performance of preprocessing such as noise reduction. Herein, an overview and history of robot audition are provided together with introduction of an open‐source software for robot audition and its wide applications in the real world. Also, it is discussed how robot audition contributes to the development of computational auditory scene analysis, that is, understanding of real‐world auditory environments.","PeriodicalId":7187,"journal":{"name":"Advanced Intelligent Systems","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90437881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
G. Nasti, S. Coppola, V. Vespini, S. Grilli, A. Vettoliere, C. Granata, P. Ferraro
Liquids are the primary environments in which chemical, physical, and biological processes occur. Considering a liquid bridge as liquid unit volume (LUV) element, it is highly desirable to develop reliable tools for handling such volumes. Herein, a sort of intelligent microfluidic platform based on the pyroelectric‐electrohydrodynamics (EHD) is shown for manipulating liquid bridges and thus performing multiple functions in a flexible and simple way. Several basic operations with liquid bridges using an EHD‐pin matrix based on the pyroelectric effect engineered in ferroelectric crystals are demonstrated. By activating pyro‐EHD effect in predetermined positions (pins of the array), the locomotion and handling of single or multiple LUVs simultaneously are controlled. In particular, multiple operations such as lift, displacement, mixing, stretching, and carrying vector for microparticles, are shown. These tweezers based on a pyro‐EHD matrix can open the route for a multipurpose platform driven by physical intelligence and can be used for driving locomotion and operate manifolds functionalities in many areas of science and technology at microscale as well as nanoscale with advantages to be activated by the sole thermal stimulus, controlled remotely, and in noncontact mode.
{"title":"Pyroelectric Tweezers for Handling Liquid Unit Volumes","authors":"G. Nasti, S. Coppola, V. Vespini, S. Grilli, A. Vettoliere, C. Granata, P. Ferraro","doi":"10.1002/aisy.202000044","DOIUrl":"https://doi.org/10.1002/aisy.202000044","url":null,"abstract":"Liquids are the primary environments in which chemical, physical, and biological processes occur. Considering a liquid bridge as liquid unit volume (LUV) element, it is highly desirable to develop reliable tools for handling such volumes. Herein, a sort of intelligent microfluidic platform based on the pyroelectric‐electrohydrodynamics (EHD) is shown for manipulating liquid bridges and thus performing multiple functions in a flexible and simple way. Several basic operations with liquid bridges using an EHD‐pin matrix based on the pyroelectric effect engineered in ferroelectric crystals are demonstrated. By activating pyro‐EHD effect in predetermined positions (pins of the array), the locomotion and handling of single or multiple LUVs simultaneously are controlled. In particular, multiple operations such as lift, displacement, mixing, stretching, and carrying vector for microparticles, are shown. These tweezers based on a pyro‐EHD matrix can open the route for a multipurpose platform driven by physical intelligence and can be used for driving locomotion and operate manifolds functionalities in many areas of science and technology at microscale as well as nanoscale with advantages to be activated by the sole thermal stimulus, controlled remotely, and in noncontact mode.","PeriodicalId":7187,"journal":{"name":"Advanced Intelligent Systems","volume":"200 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80128380","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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