Hasil untuk "Electric apparatus and materials. Electric circuits. Electric networks"

Won Namgoong

While many techniques have been proposed to improve receiver linearity, feedforward cancellation is especially attractive because it operates at the system level and complements circuit-level linearization, enabling additional performance gains. This paper analyzes the effectiveness of feedforward cancellation in the presence of multiple and/or broadband blockers, as commonly encountered in wireless environments. A Volterra-series receiver model is used to capture both nonlinear behavior and wideband memory effects. The analysis shows that robust suppression of third-order intermodulation distortion requires maintaining an approximately constant ratio between the relevant Volterra kernels of the main and auxiliary paths across frequency. Guided by this result, we present a feedforward cancellation architecture that employs nominally identical main and auxiliary paths to promote consistent kernel ratios. Experimental results validate the analysis and demonstrate that reducing kernel-ratio variations leads to significant improvements in receiver linearity.

Karim M. Abozeid, Hassan Mostafa, A. H. Khalil et al.

This paper presents a novel design for a reconfigurable CDC as a multiplexed sensor fusion that converts three analog signals into digital output bits with different resolutions. The proposed reconfigurable CDC design uses the SAR technique that introduces a small chip area and low power consumption. The proposed novel CDC introduces reconfigurability by using a switching capacitive DAC that solves the problem of converting more than one analog signal with a single converter to a different number of output bits, giving better performance than previous designs. In this paper, three analog signals are used (as a case study) in a weather station to be converted. These signals are temperature, pressure, and humidity that are sensed using the BME-280 Bosch sensor. All CDC specifications are measured for each reconfigured number of output bits. The used supply voltage is 1.0 V, and the sampling frequency is 100 kHz. The 12-bit resolution consumes 2.54 µW, ENOB is 11.47 bits, and SNR equals 73.4 dB. The 8-bit resolution consumes 1.7 µW, ENOB is 7.39 bits, and SNR equals 46.24 dB. The 4-bit resolution consumes 0.68 µW, ENOB is 3.58 bits, and SNR equals 23.45 dB. The total chip area is 0.18 mm².

Sung-June Byun, Byeong-Gi Jang, Jong-Wan Jo et al.

This paper presents a bidirectional Four-Switch Buck-Boost (FSBB) converter with a high-voltage (HV) gate driver for use in power bank applications. The proposed FSBB is also integrated into this converter for increased efficiency. Thus, the proposed buck-boost converter can reduce conduction loss over a wide input voltage range by reducing the on-resistance of external MOSFETs using a gate source voltage (VGS) of 5V or 10V. The chip to be examined in this study is fabricated using a 130 nm 1P5M bipolar-CMOS-DMOS HV process with laterally diffused MOSFET (LDMOS) options to have a die size of 2.7 x 2.7 mm2. The proposed architecture is found to achieve a maximum output power level of 40W. The measurement results show that the maximum efficiencies at gate-source voltages (VGS) of 5V and 10V are 96.67% and 98.15%, respectively.

Peter H. Siegel

We are pleased to pick up this continuing series on individuals within our community who have made significant impacts in the field of microwaves, and to the world, over the course of their careers. This issue&#x0027;s <italic>Microwave Pioneer</italic> article is about Mau-Chung Frank Chang, who perhaps more than anyone else, is responsible for the widespread commercial use of the heterojunction bipolar transistor (HBT). Professor Chang is also an example of a researcher who very successfully crossed over from industry to academia and from research to management and back, having spent time in charge of a large team of commercial semiconductor fabrication engineers and as President of a major academic university. Throughout his very varied career, he always emphasized two things: the first he attributes to his mother&#x0027;s teaching - the great power of connecting individuals together to solve problems rather than trying to lead them to a solution, and the second &#x2013; which is all his own &#x2013; the fortitude to take on and stick with challenges that seemed daunting to others. We think you will benefit from hearing Frank&#x0027;s story and in getting to know him on a more personal level.

Vivien Enenkel, Veronika Yastrebova, Elena Voloshina et al.

Abstract The implementation of graphene in spintronics requires the formation of high quality graphene–ferromagnet interfaces for efficient spin injection. By using low‐temperature scanning tunneling microscopy (STM), the atomic structure as well as the electronic properties of epitaxial graphene/ferromagnetic‐Mn5Ge3/semiconducting‐Ge heterostructures are investigated. The formation of the graphene/Mn5Ge3 interface is performed by Mn evaporation on the graphene/Ge(110) surface combined with annealing during and after deposition, yielding graphene on Mn5Ge3 crystallites of two distinct types, each displaying a principal facet – graphene/Mn5Ge3(0001) and graphene/Mn5Ge3(112¯0). STM imaging shows graphene/Mn5Ge3 interfaces with a high degree of structural order down to the atomic level. The local electronic structure of graphene/Mn5Ge3 probed by dI/dV spectroscopy and by quasiparticle interference mapping is found to be very close to that of free‐standing graphene, with only a very small electron doping. These findings provide important microscopic insights into a system with a potential for spintronics device fabrication compatible with modern semiconductor technology.

Amine MEZENNER, Mohamed Rayane LAKEHAL, Naouel ARAB et al.

Plant disease detection is a one of the most studied subjects in precision agriculture which aims to protect and improve agricultural crops. Commonly, intelligent systems based on CNN (Convolutional Neural Networks) are employed to identify multiple plant diseases by analyzing leaf images. In this work, we propose the use of the Compact Convolutional vision Transformer for tomato disease classification. Experiments conducted on a set of 10 tomato disease categories highlight the effectiveness of the proposed system which outperforms famous CNN models including DenseNet201, and MobileNetV2 by 1.73% in the overall classification accuracy.

Yunlin Lei, Xinyu Yang, Shouyu Wang et al.

Materials possessing long range ordering of magnetic spins or electric dipoles have been the focus of condensed matter research. Among them, ferri-systems with two sublattices of unequal/noncollinear spins or electric dipoles are expected to combine the properties of ferro- and antiferro-systems, but lack experimental observations in single phase materials. This is particularly true for the ferrielectric system, since the electric dipoles usually can be redefined to incorporate the two sublattices into one, making it indistinguishable from ferroelectric. This raises doubts about whether or not ferrielectricity can be considered as an independent ferroic order. Here we report the observation of true ferrielectric behaviors in a hybrid single crystal (MV)[SbBr5] (MV2+ = N,N'-dimethyl-4,4'-bipyridinium or methylviologen), where the two electric dipole sublattices switch asynchronously, thus cannot be reduced to ferroelectric by redefining the unit cell. Furthermore, the complex dipole configuration imparts circularly polarized light sensitivity to the system. An electric field can modulate the non-collinear dipole sublattices and even induce a transition from ferrielectric to ferroelectric state, thereby tuning the helicity-dependent photocurrent. This study opens a new paradigm for the study of true irreducible ferrielectricity (a new class of polar system) and provides an effective approach to the electric field control of spin-orbit coupling and circular photogalvanic effect.

Tetiana Bogodorova, Denis Osipov, Luigi Vanfretti

Wang Ye, Ma Li

In order to make full use of the potential of wireless sensor networks in higher education, this study aims to provide convenient intelligent learning and management functions by constructing an iot Android voice assistant based on wireless sensor networks. The system structure of Android voice assistant based on wireless sensor network is researched, designed and implemented. Through the integration of wireless sensor network and school network platform, the data collection, transmission and analysis functions are realized. The results show that the Android voice assistant based on wireless sensor network effectively provides intelligent learning and management functions in the network mode of higher education. Students and teachers can realize course inquiry, resource acquisition, teaching evaluation and other operations through voice commands to improve learning and teaching efficiency. By combining the data acquisition capabilities of sensors and wireless transmission capabilities, the system provides students, teachers and school administrators with intelligent learning and management functions, which is expected to promote the further development of higher education network environment.

Wen Zhao, Jie Zhong, Jiale Lv

Smart cities leverage technology, data, and digital infrastructure to enhance residents' quality of life, fostering sustainability and operational efficiency. To this end, the price data of rental housing in Hefei in 2022 were hereby collected to build a geographically weighted regression (GWR) model, and the mechanism of various factors on the price of rental housing in Hefei was discussed. Spatial correlation analysis revealed a notable autocorrelation of rental housing prices in Hefei, exhibiting a distribution pattern of decreasing values from the city center outward. Besides, the impact of 13 factors on house rent was examined. Overall, factors such as building area, proximity to wet markets, and distance from the top three hospitals were demonstrated to exert the most significant influence on rental housing prices in Hefei. The decision-making of smart cities needs to be scientifically analyzed to find out the factors affecting the price of rental housing in the region, and the research conclusions can provide certain references for urban decision-makers in the overall management of urban resources and targeted solutions to regional housing rental and other issues.

Samir ZOUGHAB, Nouri BELHAOUCHET, Samir SAYAH

This paper presents a simple and efficient standalone photovoltaic (PV) water pumping system employing an induction motor drive. This system uses two power conversion stages linked by a DC-bus capacitor. The first is a DC-DC boost converter controlled by using a perturb-and-observe (P&O) maximum power point tracking (MPPT) technique; used to extract the available maximum power of the PV array. The second is a three-phase Pulse-Width Modulated Voltage Source Inverter (PWM-VSI) coupled to an induction motor for driving the centrifugal pump. This drive is controlled by the indirect field oriented control (FOC) which ensures high dynamic and static performances. The DC-bus voltage is regulated at a required level by using a proportional-integral (PI) controller. The reference speed is estimated from the affinity law and the DC-bus voltage control. The performances of the system are verified by digital simulation under Matlab/Simulink environment in steady-state and dynamic operating conditions.

Jin Shang, Xiaobo Xu

Image encryption is an important research field. In some application scenarios, only encrypting can actually attract the attention of attackers. Therefore, this article provides dual protection for images that require confidentiality. The image is first encrypted and then hidden in the normally transmitted image to avoid attacks from attackers. The encryption adopts a combination of DNA encoding and chaos theory, while the hiding adopts LSB algorithm. The experimental results show that the algorithm has achieved good security effects, and the correlation coefficient analysis has also achieved ideal results.

Petr S. Bednyakov, Petr V. Yudin, Alexander K. Tagantsev et al.

It is known that ferroelectric single crystals can be turned from a polydomain to a monodomain state by the application of an electric field. Here we report an unexpected opposite effect: the formation of through-the-crystal polydomain pattern in a monodomain BaTiO3 crystal in response to the applied electric field favoring the initial orientation of the polarization. The effect is achieved for special electric field direction which equally selects two domain states, which are present in the polydomain pattern. At the formation of the pattern, the new wedge domains propagate from the sides of the sample in the direction transverse to the electric field. The observations are rationalized in terms of a simple analytical model treating energies of competing domain configurations as functions of the electric field. The results of the analytical treatment are supported by phase field modeling.

Arka Bandyopadhyay, Nesta Benno Joseph, Awadhesh Narayan

This review presents recent breakthroughs in the realm of nonlinear Hall effects, emphasizing central theoretical foundations and recent experimental progress. We elucidate the quantum origin of the second-order Hall response, focusing on the Berry curvature dipole, which may arise in inversion symmetry broken systems. The theoretical framework also reveals the impact of disorder scattering effects on the nonlinear response. We further discuss the possibility of obtaining nonlinear Hall responses beyond the second order. We examine symmetry-based indicators essential for the manifestation of nonlinear Hall effects in time-reversal symmetric crystals, setting the stage for a detailed exploration of theoretical models and candidate materials predicted to exhibit sizable and tunable Berry curvature dipole. We summarize groundbreaking experimental reports on measuring both intrinsic and extrinsic nonlinear Hall effects across diverse material classes. Finally, we highlight some of the other intriguing nonlinear effects, including nonlinear planar Hall, nonlinear anomalous Hall, and nonlinear spin and valley Hall effects. We conclude with an outlook on pivotal open questions and challenges, marking the trajectory of this rapidly evolving field.

G.S. Prasanna Lakshmi, P.N. Asha, G. Sandhya et al.

Sustainable agricultural practices are required, especially for irrigation, to provide for a growing population. About 85% of the freshwater resources in the world are used for irrigation. ''Us,'' current irrigation procedures must be either updated or replaced with cutting-edge, intelligent systems that utilize the ML, IoT (Internet of Things), and sensor networks which are wireless. In the proposed paper, a brainy system for tracking and scheduling accuracy irrigation using IoT, a LoRa-based machine learning (ML) is being introduced. We developed an independent irrigation technique that would provide the tomato and eggplant with the precise amount of water they required was set up using the information obtained from the soil moisture sensors. In comparison to traditional watering, which required 7541 mL for the banana plant and 8755 mL for the rice plant, the irrigation system irrigated the plants with an overall quantity of 5010.745 mL &amp; 4421.09 mL in one month. Overall, this led to a 46% reduction in water usage, and the plants looked better than they would have with conventional watering. The simulation results clearly show that the suggested approach uses water more sensibly than cutting-edge models in the experiment farming region.

M.B. Jennyfer Susan, P. Subashini

Smart Colposcopy is a low-cost and highly effective screening device used to detect cervical cancer. However, the captured images can be significantly affected by specular reflection, resulting in reduced accuracy during the grading process. In this paper, proposed a novel approach to enhance the accuracy of cervical cancer grading by addressing the issue of specular reflection. Here the method employs binary masking to identify the glare region and fine-tuned U-Net model to perform segmentation. Partial convolutional inpainting is used to replace the segmented region with neighboring pixels, effectively removing the glare from the images. The resulting enhanced images are then fed into classification models, including DenseNet121, Vgg19, and Efficient Net, which are trained to accurately grade cervical cancer. Experimental results demonstrate that our proposed method significantly improves the accuracy of cervical cancer grading, achieving accuracy rates of 97.32%, 96.25%, and 96.75%, respectively.

Manbir Singh Punia, Kamal Malik, Vikash Kumar Garg

In the era of Internet of things and social media huge amount of data are generated day by day from numerous sources. The problem for each and every organization is to tackle with the volume, variety and velocity of data. This data is commonly referred to as “Big Data”. Most of the recent surveys provide the tools and techniques to deal with pace of data. In past decades traditional databases have shown tremendous growth in consistency, durability and isolation of data. But in current trends of data analytics, traditional database are fertile to deal with the volume, variety and velocity of database. In this paper, initially comparison is drawn to check the drawbacks of the existing system. To cope with the problems in existing system a partitioning-based technique is proposed and implemented using NoSQL Database. The final goal of this work is to identify the problems faced in traditional system and accordingly a partitioning based techniques are designed which will optimize the performance of query operation in terms of size and query time. To check the prediction accuracy around the regression line error estimation is used in the scenario. The measurement of speed difference between these proposed scenarios is depending on error estimation. Higher estimation is equal to higher performance. In this work the performance of MongoDB tuning technique is increased approximately by 65% as compare to the performance with default configuration of MongoDB. By using these techniques, the optimization of the system using MongoDB is increased compare to the Neo4j, Oracle 11g and traditional database. The final result shows that MongoDB performs best, followed by and Oracle 11g, Neo4j.

Sudip Paul, Shruti Jain

Ning Li, Charles Mackin, An Chen et al.

Abstract Phase change memory (PCM) is one of the most promising candidates for non‐von Neumann based analog in‐memory computing–particularly for inference of previously‐trained deep neural networks (DNN). It is shown that PCM electrical properties can be tuned systematically using a projection liner, which is designed for resistance drift mitigation, in the manufacturable mushroom PCM. A systematic study of the electrical properties‐including resistance values, memory window, resistance drift, read noise, and their impact on the accuracy of large neural networks of various types and with tens of millions of weights is performed. It is sown that the DNN accuracy can be improved by the PCM with liner for both the short term and long term after programming, due to reduced resistance drift and read noise, respectively, despite the trade‐off of reduced memory window. The liner conductance, PCM device characteristics, and network inference accuracy with PCM memory window and reset state conductance is correlated, which allows us to identify the device optimization space to achieve better short term and long term accuracy for large neural networks.

Bo He, Gang He, Shanshan Jiang et al.

Abstract Thin‐film transistors based on metal oxide semiconductors have become a mainstream technology for application in driving low‐cost backplanes of active matrix liquid crystal displays. Although significant progress has been made in traditional marketable devices based on physical vapor deposition derived metal oxides, it has still been hindered by low yield and poor compatibility. Fortunately, developing solution‐based 1D nanofiber networks to act as the fundamental building blocks for transistor has proven to be a simpler, higher‐throughput approach. However, oxide transistors based on such princesses suffer from degraded carrier mobility and operational instability, preventing the ability of such devices from replacing present polycrystalline Si technologies. Herein, it is shown that double channel heterojunction transistors with high electron mobility (>40 cm2 V−1 s−1) and operational stability can be achieved from electrospun double channels composed of In2O3 and ZnO layers. Adjusting the stacking order and the stacking density of In2O3 and ZnO layers can effectively optimize the interface electron trap, leading to the formation of 2D electron gas and the reduction of stress‐induced instability. These findings further elucidate the significant advance of electrospinning‐derived double channel heterojunction transistors toward practical applications for future low‐cost and high‐performance electronics.