The conventional computing architecture faces substantial chal-lenges,including high latency and energy consumption between memory and processing *** response,in-memory computing has emerged as a promising alternative...
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The conventional computing architecture faces substantial chal-lenges,including high latency and energy consumption between memory and processing *** response,in-memory computing has emerged as a promising alternative architecture,enabling computing operations within memory arrays to overcome these *** devices have gained significant attention as key components for in-memory computing due to their high-density arrays,rapid response times,and ability to emulate biological *** these devices,two-dimensional(2D)material-based memristor and memtransistor arrays have emerged as particularly promising candidates for next-generation in-memory computing,thanks to their exceptional performance driven by the unique properties of 2D materials,such as layered structures,mechanical flexibility,and the capability to form *** review delves into the state-of-the-art research on 2D material-based memristive arrays,encompassing critical aspects such as material selection,device perfor-mance metrics,array structures,and potential ***,it provides a comprehensive overview of the current challenges and limitations associated with these arrays,along with potential *** primary objective of this review is to serve as a significant milestone in realizing next-generation in-memory computing utilizing 2D materials and bridge the gap from single-device characterization to array-level and system-level implementations of neuromorphic computing,leveraging the potential of 2D material-based memristive devices.
Understanding charge transport mechanisms in thin-film transistors based on random networks of single-wall carbon nanotubes(SWCNT-TFTs)is essential for further advances to improve the potential for various nanoelectro...
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Understanding charge transport mechanisms in thin-film transistors based on random networks of single-wall carbon nanotubes(SWCNT-TFTs)is essential for further advances to improve the potential for various nanoelectronic ***,a comprehensive investigation of the two-dimensional(2D)charge transport mechanism in SWCNT-TFTs is reported by analyzing the temperature-dependent electrical characteristics determined from the direct-current and non-quasi-static transient measurements at 80-300 *** elucidate the time-domain charge transport characteristics of the random networks in the SWCNTs,an empirical equation was derived from a theoretical trapping model,and a carrier velocity distribution was determined from the differentiation of the transient ***,charge trapping and de-trapping in shallow-and deep-traps in SWCNT-TFTs were analyzed by investigating charge transport based on their trapping/de-trapping *** comprehensive analysis of this study provides fundamental insights into the 2D charge transport mechanism in TFTs based on random networks of nanomaterial channels.
A new three-phase hybrid-excited multi-tooth switched reluctance motor with embedded permanent magnets is proposed, capable of achieving higher torque density for transportation electrification applications. Operating...
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This paper investigates the optimized combination of rotor and stator teeth in a three-phase switched reluctance motor featuring a connected C-core topology to attain a larger winding area and, thus, a higher electric...
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High-temperature energy storage performance of dielectric capacitors is cru-cial for the next generation of power electronic ***,conduction losses rise sharply at elevated temperature,limiting the application of energ...
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High-temperature energy storage performance of dielectric capacitors is cru-cial for the next generation of power electronic ***,conduction losses rise sharply at elevated temperature,limiting the application of energy storage ***,the mica films magnetron sputtered by different insulating layers are specifically investigated,which exhibit the excellent high-temperature energy storage *** experimental results revealed that the PbZrO3/Al2O3/PbZrO3(PZO/AO/PZO)interface insulating layers can effec-tively reduce the high-temperature leakage current and conduction loss of the composite ***,the ultrahigh energy storage density(Wrec)and charge‒discharge efficiency(η)can be achieved simultaneously in the flexi-ble mica-based composite ***,PZO/AO/PZO/mica/PZO/AO/PZO(PAPMPAP)films possess excellent Wrec of 27.5 J/cm3 andηof 87.8%at 200◦C,which are significantly better than currently reported high-temperature capaci-tive energy storage dielectric *** with outstanding power density and electrical cycling stability,the flexible films in this work have great appli-cation potential in high-temperature energy storage ***,the magnetron sputtering technology can deposit large-area nanoscale insulating layers on the surface of capacitor films,which can provide technical support for the industrial production of capacitors.
Lung cancer requires accurate risk assessment and early detection due to its high prevalence and fatality rate. The simultaneous analysis of clinical symptoms and etiological factors using Machine Learning revolutioni...
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In recent years,the Internet of Things(IoT)has gradually developed applications such as collecting sensory data and building intelligent services,which has led to an explosion in mobile data ***,with the rapid develop...
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In recent years,the Internet of Things(IoT)has gradually developed applications such as collecting sensory data and building intelligent services,which has led to an explosion in mobile data ***,with the rapid development of artificial intelligence,semantic communication has attracted great attention as a new communication ***,for IoT devices,however,processing image information efficiently in real time is an essential task for the rapid transmission of semantic *** the increase of model parameters in deep learning methods,the model inference time in sensor devices continues to *** contrast,the Pulse Coupled Neural Network(PCNN)has fewer parameters,making it more suitable for processing real-time scene tasks such as image segmentation,which lays the foundation for real-time,effective,and accurate image ***,the parameters of PCNN are determined by trial and error,which limits its *** overcome this limitation,an Improved Pulse Coupled Neural Networks(IPCNN)model is proposed in this *** IPCNN constructs the connection between the static properties of the input image and the dynamic properties of the neurons,and all its parameters are set adaptively,which avoids the inconvenience of manual setting in traditional methods and improves the adaptability of parameters to different types of *** segmentation results demonstrate the validity and efficiency of the proposed self-adaptive parameter setting method of IPCNN on the gray images and natural images from the Matlab and Berkeley Segmentation *** IPCNN method achieves a better segmentation result without training,providing a new solution for the real-time transmission of image semantic information.
Because of their high torque, high power density, and appropriate speed range, brushless DC (BLDC) motors are the top choice for lightweight electric vehicles. The application's goal is to use a Hall position sens...
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Rapid discovery and synthesis of future materials requires intelligent data acquisition strategies to navigate large design spaces.A popular strategy is Bayesian optimization,which aims to find candidates that maximiz...
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Rapid discovery and synthesis of future materials requires intelligent data acquisition strategies to navigate large design spaces.A popular strategy is Bayesian optimization,which aims to find candidates that maximize material properties;however,materials design often requires finding specific subsets of the design space which meet more complex or specialized *** present a framework that captures experimental goals through straightforward user-defined filtering *** algorithms are automatically translated into one of three intelligent,parameter-free,sequential data collection strategies(SwitchBAX,InfoBAX,and MeanBAX),bypassing the time-consuming and difficult process of task-specific acquisition function *** framework is tailored for typical discrete search spaces involving multiple measured physical properties and short time-horizon decision *** demonstrate this approach on datasets for TiO2 nanoparticle synthesis and magnetic materials characterization,and show that our methods are significantly more efficient than state-of-the-art ***,our framework provides a practical solution for navigating the complexities of materials design,and helps lay groundwork for the accelerated development of advanced materials.
Prenatal depression,which can affect pregnant women’s physical and psychological health and cause postpartum depression,is increasing ***,it is essential to detect prenatal depression early and conduct an attribution...
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Prenatal depression,which can affect pregnant women’s physical and psychological health and cause postpartum depression,is increasing ***,it is essential to detect prenatal depression early and conduct an attribution *** studies have used questionnaires to screen for prenatal depression,but the existing methods lack *** diagnose the early signs of prenatal depression and identify the key factors that may lead to prenatal depression from questionnaires,we present the semantically enhanced option embedding(SEOE)model to represent questionnaire *** can quantitatively determine the relationship and patterns between options and *** first quantifies options and resorts them,gathering options with little difference,since Word2Vec is highly dependent on *** resort task is transformed into an optimization problem involving the traveling salesman ***,all questionnaire samples are used to train the options’vector using ***,an LSTM and GRU fused model incorporating the cycle learning rate is constructed to detect whether a pregnant woman is suffering from *** verify the model,we compare it with other deep learning and traditional machine learning *** experiment results show that our proposed model can accurately identify pregnant women with depression and reach an F1 score of *** most relevant factors of depression found by SEOE are also verified in the *** addition,our model is of low computational complexity and strong generalization,which can be widely applied to other questionnaire analyses of psychiatric disorders.
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