Hydrogels possess significant potential for the development of multifunctional soft materials in smart sensors and wearable devices,attributed to their distinctive properties of softness,conductivity,and biocompatibil...Hydrogels possess significant potential for the development of multifunctional soft materials in smart sensors and wearable devices,attributed to their distinctive properties of softness,conductivity,and biocompatibility.Nevertheless,their widespread application is frequently limited by inadequate mechanical strength and strain capacity.This study introduces a meticulously engineered hydrogel system,LM/SA/P(AAM-co-BMA),which integrates eutectic gallium-indium alloy(EGaIn)as both a polymerization initiator and a flexible filler.The resultant hydrogel demonstrates remarkable tensile strain capabilities of up to 2800% and a tensile strength of 2.3 MPa,achieved through a synergistic interplay of ionic coordination,hydrogen bonding,and physical polymer interactions.Furthermore,the hydrogel exhibits outstanding biocompatibility,recyclability,and stable long-term storage,rendering it an ideal candidate for the continuous monitoring of high-intensity physical activities.展开更多
The evolution process of magnetic domains in response to external fields is crucial for the modern understanding and application of spintronics.In this study,we investigated the domain rotation in stripe domain films ...The evolution process of magnetic domains in response to external fields is crucial for the modern understanding and application of spintronics.In this study,we investigated the domain rotation in stripe domain films of varying thicknesses by examining their response to microwave excitation in four different orientations.The resonance spectra indicate that the rotation field of stripe domain film under an applied magnetic field approaches the field where the resonance mode of sample changes.The saturation field of the stripe domain film corresponds to the field where the resonance mode disappears when measured in the stripe direction parallel to the microwave magnetic field.The results are reproducible and consistent with micromagnetic simulations,providing additional approaches and techniques for comprehending the microscopic mechanisms of magnetic domains and characterizing their rotation.展开更多
This paper examines GaSb short-wavelength infrared detectors employing planar PN junctions. The fabrication was based on the Zn diffusion process and the diffusion temperature was optimized. Characterization revealed ...This paper examines GaSb short-wavelength infrared detectors employing planar PN junctions. The fabrication was based on the Zn diffusion process and the diffusion temperature was optimized. Characterization revealed a 50% cut-off wavelength of 1.73 μm, a maximum detectivity of 8.73 × 10^(10) cm·Hz^(1/2)/W, and a minimum dark current density of 1.02 × 10^(-5) A/cm^(2).Additionally, a maximum quantum efficiency of 60.3% was achieved. Subsequent optimization of fabrication enabled the realization of a 320 × 256 focal plane array that exhibited satisfactory imaging results. Remarkably, the GaSb planar detectors demonstrated potential in low-cost short wavelength infrared imaging, without requiring material epitaxy or deposition.展开更多
At present, big data is very popular, because it has proved to be much successful in many fields such as social media, E-commerce transactions, etc. Big data describes the tools and technologies needed to capture, man...At present, big data is very popular, because it has proved to be much successful in many fields such as social media, E-commerce transactions, etc. Big data describes the tools and technologies needed to capture, manage, store, distribute, and analyze petabyte or larger-sized datasets having different structures with high speed. Big data can be structured, unstructured, or semi structured. Hadoop is an open source framework that is used to process large amounts of data in an inexpensive and efficient way, and job scheduling is a key factor for achieving high performance in big data processing. This paper gives an overview of big data and highlights the problems and challenges in big data. It then highlights Hadoop Distributed File System （HDFS）, Hadoop MapReduce, and various parameters that affect the performance of job scheduling algorithms in big data such as Job Tracker, Task Tracker, Name Node, Data Node, etc. The primary purpose of this paper is to present a comparative study of job scheduling algorithms along with their experimental results in Hadoop environment. In addition, this paper describes the advantages, disadvantages, features, and drawbacks of various Hadoop job schedulers such as FIFO, Fair, capacity, Deadline Constraints, Delay, LATE, Resource Aware, etc, and provides a comparative study among these schedulers.展开更多
Recent studies have indicated that foundation models, such as BERT and GPT, excel atadapting to various downstream tasks. This adaptability has made them a dominant force in buildingartificial intelligence (AI) system...Recent studies have indicated that foundation models, such as BERT and GPT, excel atadapting to various downstream tasks. This adaptability has made them a dominant force in buildingartificial intelligence (AI) systems. Moreover, a newresearch paradigm has emerged as visualizationtechniques are incorporated into these models. Thisstudy divides these intersections into two researchareas: visualization for foundation model (VIS4FM)and foundation model for visualization (FM4VIS).In terms of VIS4FM, we explore the primary roleof visualizations in understanding, refining, and evaluating these intricate foundation models. VIS4FMaddresses the pressing need for transparency, explainability, fairness, and robustness. Conversely, in termsof FM4VIS, we highlight how foundation models canbe used to advance the visualization field itself. Theintersection of foundation models with visualizations ispromising but also introduces a set of challenges. Byhighlighting these challenges and promising opportunities, this study aims to provide a starting point forthe continued exploration of this research avenue.展开更多
Visual analytics for machine learning has recently evolved as one of the most exciting areas in the field of visualization.To better identify which research topics are promising and to learn how to apply relevant tech...Visual analytics for machine learning has recently evolved as one of the most exciting areas in the field of visualization.To better identify which research topics are promising and to learn how to apply relevant techniques in visual analytics,we systematically review259 papers published in the last ten years together with representative works before 2010.We build a taxonomy,which includes three first-level categories:techniques before model building,techniques during modeling building,and techniques after model building.Each category is further characterized by representative analysis tasks,and each task is exemplified by a set of recent influential works.We also discuss and highlight research challenges and promising potential future research opportunities useful for visual analytics researchers.展开更多
Interactive model analysis,the process of understanding,diagnosing,and refining a machine learning model with the help of interactive visualization,is very important for users to efficiently solve real-world artificia...Interactive model analysis,the process of understanding,diagnosing,and refining a machine learning model with the help of interactive visualization,is very important for users to efficiently solve real-world artificial intelligence and data mining problems.Dramatic advances in big data analytics have led to a wide variety of interactive model analysis tasks.In this paper,we present a comprehensive analysis and interpretation of this rapidly developing area.Specifically,we classify the relevant work into three categories:understanding,diagnosis,and refinement.Each category is exemplified by recent influential work.Possible future research opportunities are also explored and discussed.展开更多
基金supported primarily by National Key Research and Development Program of China(2020YFA0710303)The authors thank the support from Natural Science Foundation of Fujian Province(2024J01258)Scientific Research Foundation of Fuzhou University(510936).
文摘Hydrogels possess significant potential for the development of multifunctional soft materials in smart sensors and wearable devices,attributed to their distinctive properties of softness,conductivity,and biocompatibility.Nevertheless,their widespread application is frequently limited by inadequate mechanical strength and strain capacity.This study introduces a meticulously engineered hydrogel system,LM/SA/P(AAM-co-BMA),which integrates eutectic gallium-indium alloy(EGaIn)as both a polymerization initiator and a flexible filler.The resultant hydrogel demonstrates remarkable tensile strain capabilities of up to 2800% and a tensile strength of 2.3 MPa,achieved through a synergistic interplay of ionic coordination,hydrogen bonding,and physical polymer interactions.Furthermore,the hydrogel exhibits outstanding biocompatibility,recyclability,and stable long-term storage,rendering it an ideal candidate for the continuous monitoring of high-intensity physical activities.
基金the Natural Science Foundation of Shandong Province(Grant No.ZR2022MA053),the National Natural Science Foundation of China(Grant Nos.11704211,11847233,52301255,12205157,and 12205093)the Funda-mental Research Funds for the Central Universities(Grant No.lzujbky-2022-kb01)+2 种基金China and Germany Postdoctoral Exchange Program(Helmholtz-OCPC)China Postdoctoral Science Foundation(Grant No.2018M632608)Applied Basic Research Project of Qingdao(Grant No.18-2-2-16-jcb).
文摘The evolution process of magnetic domains in response to external fields is crucial for the modern understanding and application of spintronics.In this study,we investigated the domain rotation in stripe domain films of varying thicknesses by examining their response to microwave excitation in four different orientations.The resonance spectra indicate that the rotation field of stripe domain film under an applied magnetic field approaches the field where the resonance mode of sample changes.The saturation field of the stripe domain film corresponds to the field where the resonance mode disappears when measured in the stripe direction parallel to the microwave magnetic field.The results are reproducible and consistent with micromagnetic simulations,providing additional approaches and techniques for comprehending the microscopic mechanisms of magnetic domains and characterizing their rotation.
文摘This paper examines GaSb short-wavelength infrared detectors employing planar PN junctions. The fabrication was based on the Zn diffusion process and the diffusion temperature was optimized. Characterization revealed a 50% cut-off wavelength of 1.73 μm, a maximum detectivity of 8.73 × 10^(10) cm·Hz^(1/2)/W, and a minimum dark current density of 1.02 × 10^(-5) A/cm^(2).Additionally, a maximum quantum efficiency of 60.3% was achieved. Subsequent optimization of fabrication enabled the realization of a 320 × 256 focal plane array that exhibited satisfactory imaging results. Remarkably, the GaSb planar detectors demonstrated potential in low-cost short wavelength infrared imaging, without requiring material epitaxy or deposition.
文摘At present, big data is very popular, because it has proved to be much successful in many fields such as social media, E-commerce transactions, etc. Big data describes the tools and technologies needed to capture, manage, store, distribute, and analyze petabyte or larger-sized datasets having different structures with high speed. Big data can be structured, unstructured, or semi structured. Hadoop is an open source framework that is used to process large amounts of data in an inexpensive and efficient way, and job scheduling is a key factor for achieving high performance in big data processing. This paper gives an overview of big data and highlights the problems and challenges in big data. It then highlights Hadoop Distributed File System （HDFS）, Hadoop MapReduce, and various parameters that affect the performance of job scheduling algorithms in big data such as Job Tracker, Task Tracker, Name Node, Data Node, etc. The primary purpose of this paper is to present a comparative study of job scheduling algorithms along with their experimental results in Hadoop environment. In addition, this paper describes the advantages, disadvantages, features, and drawbacks of various Hadoop job schedulers such as FIFO, Fair, capacity, Deadline Constraints, Delay, LATE, Resource Aware, etc, and provides a comparative study among these schedulers.
基金supported by the National Natural Science Foundation of China(Grant Nos.U21A20469 and 61936002)the National Key R&D Program of China(Grant No.2020YFB2104100)grants from the Institute Guo Qiang,THUIBCS,and BLBCI.
文摘Recent studies have indicated that foundation models, such as BERT and GPT, excel atadapting to various downstream tasks. This adaptability has made them a dominant force in buildingartificial intelligence (AI) systems. Moreover, a newresearch paradigm has emerged as visualizationtechniques are incorporated into these models. Thisstudy divides these intersections into two researchareas: visualization for foundation model (VIS4FM)and foundation model for visualization (FM4VIS).In terms of VIS4FM, we explore the primary roleof visualizations in understanding, refining, and evaluating these intricate foundation models. VIS4FMaddresses the pressing need for transparency, explainability, fairness, and robustness. Conversely, in termsof FM4VIS, we highlight how foundation models canbe used to advance the visualization field itself. Theintersection of foundation models with visualizations ispromising but also introduces a set of challenges. Byhighlighting these challenges and promising opportunities, this study aims to provide a starting point forthe continued exploration of this research avenue.
基金supported by the National Key R&D Program of China(Nos.2018YFB1004300,2019YFB1405703)the National Natural Science Foundation of China(Nos.61761136020,61672307,61672308,61936002)TC190A4DA/3,the Institute Guo Qiang,Tsinghua University,in part by Tsinghua–Kuaishou Institute of Future Media Data。
文摘Visual analytics for machine learning has recently evolved as one of the most exciting areas in the field of visualization.To better identify which research topics are promising and to learn how to apply relevant techniques in visual analytics,we systematically review259 papers published in the last ten years together with representative works before 2010.We build a taxonomy,which includes three first-level categories:techniques before model building,techniques during modeling building,and techniques after model building.Each category is further characterized by representative analysis tasks,and each task is exemplified by a set of recent influential works.We also discuss and highlight research challenges and promising potential future research opportunities useful for visual analytics researchers.
文摘Interactive model analysis,the process of understanding,diagnosing,and refining a machine learning model with the help of interactive visualization,is very important for users to efficiently solve real-world artificial intelligence and data mining problems.Dramatic advances in big data analytics have led to a wide variety of interactive model analysis tasks.In this paper,we present a comprehensive analysis and interpretation of this rapidly developing area.Specifically,we classify the relevant work into three categories:understanding,diagnosis,and refinement.Each category is exemplified by recent influential work.Possible future research opportunities are also explored and discussed.
