Search Results (127)

Against the backdrop of rapid urbanization and land development, the degradation of regional ecosystem services and the intensification of ecological risks have become prominent challenges. This study takes the Pinglu Canal Economic Belt—a region characterized by the triple pressures of “large-scale engineering disturbance, karst ecological vulnerability, and port economic agglomeration”—as a case study. Based on remote sensing image data from 2000 to 2020, a landscape ecological risk index was constructed, and regional landscape ecological risk levels were assessed using ArcGIS spatial analysis tools. On this basis, ecological sources were identified by combining the InVEST model with morphological spatial pattern analysis (MSPA),and an ecological resistance surface was constructed by integrating factors such as land use type, elevation, slope, distance to roads, distance to water bodies, and NDVI. Furthermore, the circuit theory method was applied to identify ecological corridors, ecological pinch points, and barrier points, ultimately constructing the ecological security pattern of the Pinglu Canal Economic Belt. The main findings are as follows: (1) Ecological risks were primarily at low to medium levels, with high-risk areas concentrated in the southern coastal region. Over the past two decades, an overall optimization trend was observed, shifting from high risk to lower risk levels. (2) A total of 15 ecological sources (total area 1313.71 km²), 31 ecological corridors (total length 1632.42 km), 39 ecological pinch points, and 15 ecological barrier points were identified, clarifying the key spatial components of the ecological network. (3) Based on spatial analysis results, a zoning governance plan encompassing “ecological protected areas, improvement areas, restoration areas, and critical areas” along with targeted strategies was proposed, providing a scientific basis for ecological risk management and pattern optimization in the Pinglu Canal Economic Belt. Full article

This study presents a unified symbolic–numerical framework for the automatic generation and conversion of two-port network parameters, including Z, Y, H, F, T (A, B, C, and D), and S matrices. The method integrates Modified Nodal Analysis (MNA) with exact symbolic computation to derive transfer functions, poles, zeros, and parameter sensitivities directly from the circuit topology, eliminating the need for manual algebraic manipulation. Unlike conventional tools such as PSpice 9.1 or RF simulation software* which operate primarily on numerical models, the proposed approach provides closed-form expressions suitable for analytical design, optimization, and parameter-tolerance evaluation. The implemented software routines generate all parameter sets within a single workflow and enable bidirectional conversion between low-frequency formulations and high-frequency scattering representations. Numerical case studies on band-pass filters confirm the correctness of the generated expressions, with deviations below 1% relative to reference simulation results. Full article

This article presents a comprehensive and intuitive analysis of the impact of packaging on diode performance and a two-step method for packaging parameter extraction. This is performed using a single forward bias point, one-port measurements and probe tips on a conventional printed circuit board (PCB). A PIN diode was used to validate the method, biased from reverse (−5 V) to forward (1.22 V) bias. Measurements were performed up to 27 gigahertz (GHz). The complete diode characterization process—from the design and the electrical modeling of the test fixture to the extraction of the unpackaged diode measurements—is detailed. The parameters of the package model were extracted, its effects were removed from the measurement, and the behavior of the unpackaged diode was determined. Three operating regions based on their radiofrequency and direct current (RF-DC) behavior were proposed, and an electrical model of the unpackaged diode was derived for each region. The results showed that the influence of the package caused the diode to remain in an unchanged behavior under different biases, indicating that it no longer rectified. The results presented herein are validated by the excellent correlation between the diode’s measured S-parameters, impedance, and admittance and their corresponding models. Full article

Emerging services such as artificial intelligence (AI), 5G, the Internet of Things (IoT), cloud data services and teleworking are growing exponentially, pushing bandwidth needs to the limit. Space Division Multiplexing (SDM) in the spatial domain, along with Ultra-Wide Band (UWB) transmission in the spectrum domain, represent two degrees of freedom that will play a crucial role in the evolution of backbone optical networks. SDM and UWB technologies necessitate the replacement of conventional Wavelength-Selective-Switch (WSS)-based architectures with innovative optical switching elements capable of handling both higher port counts and flexible switching across various granularities. In this work, we introduce a novel Photonic Integrated Circuit (PIC)-based switching element called flex-Waveband Selective Switch (WBSS), designed to provide flexible band switching across the UWB spectrum (~21 THz). The proposed flex-WBSS supports a hierarchical three-layered Multi-Granular Optical Node (MG-ON) architecture incorporating optical switching across various granularities ranging from entire fibers and flexibly defined bands down to individual wavelengths. To evaluate its performance, we develop a custom network simulator, enabling a thorough performance analysis on the critical performance metrics of the node. Simulations are conducted over an existing network topology evaluating three traffic-oriented switching policies: Full Fiber Switching (FFS), Waveband Switching (WBS) and Wavelength Switching (WS). Simulation results reveal high Optical-to-Signal Ratio (OSNR) and low Bit Error Rate (BER) values, particularly under the FFS policy. In contrast, the integration of the WBS policy bridges the gap between existing WSS- and future FFS-based architectures and manages to mitigate capacity bottlenecks, enabling rapid scalable network upgrades in existing infrastructures. Additionally, we propose a probabilistic framework to evaluate the node’s bandwidth utilization and scaling behavior, exploring trade-offs among scalability, component numbers and complexity. The proposed framework can be easily adapted for the design of future transport optical networks. Finally, we perform a SWaP-C (Size, Weight, Power and Cost) analysis. Results show that our novel MG-ON achieves strong performance, reaching a throughput exceeding 10 Pb/s with high OSNR values ≈14–20 dB and BER ≈10⁻⁹ especially under the FFS policy. Moreover, it delivers up to 7.5× cost reduction compared to alternative architectures, significantly reducing deployment/upgrade costs while maintaining low power consumption. Full article

Developing flexible, cost-effective, and durable sensors is a key challenge for integrating Cyber–Physical–Human Systems (CPHSs) into smart homes. This paper introduces a flexible pressure sensor array designed for CPHS applications, addressing the need for cost-effective and durable sensors in smart homes. Our approach combines flexible piezoelectric materials with Swept Frequency Capacitive Sensing (SFCS). Unlike previous pressure sensors made of flexible piezoelectric materials, which can only measure dynamic pressure due to charge leakage, by using SFCS, the piezoelectric material is not directly in the circuit, and our sensor can effectively measure static pressure. While traditional arrays require multiple I/O ports or a matrix configuration, our design measures four distinct locations using only a single I/O port. The sensor is also mechanically flexible and exhibits high durability, capable of functioning even after being cut or torn, provided the electrode contact area remains largely intact. To decode the complex, multiplexed signal from this single channel, we developed a two-stage deep learning pipeline. We utilized data from thin-film resistive pressure sensors as ground truth. A classification model determines which of the four sensors are being touched. Then a regression model uses this touch-state information to estimate the corresponding pressure values. This pipeline employs a hybrid architecture that integrates Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks. The results show that the system can estimate pressure values at each location. To demonstrate its application, the sensor system was integrated into a power recliner, thereby transforming the chair into an interactive tool for daily exercise designed to improve the well-being of older adults. This successful implementation establishes a viable pathway for the development of intelligent, interactive furniture for in-home exercise and rehabilitation within the CPHS paradigm. Full article

In this paper, a miniaturized balanced bandpass filter with flexible input/output (I/O) functionality is initially designed based on parallel-coupled microstrip lines. Unlike conventional balanced bandpass filters, the proposed filter features two distinct I/O configurations. In these two states, the I/O ports of the developed balanced filter are symmetrically arranged in either horizontal or vertical directions. Moreover, the developed balanced filter demonstrates excellent differential-mode and common-mode suppression in both states. To further enhance the common-mode suppression without compromising the differential-mode performance, an asymmetrical quarter-wavelength open-circuited stub is introduced in the middle of the filter when the I/O ports are vertically symmetric. The inclusion of this stub significantly broadens the common-mode suppression bandwidth. More importantly, the developed balanced filters achieve highly compact sizes, which is essential for integration into modern compact RF front-end modules. To verify the feasibility of the proposed design concept, two prototypes are designed and fabricated, whose simulated and measured results are in good agreement. Full article

The integration of renewable energy systems and electrified transportation requires advanced energy storage solutions capable of providing both high energy density and fast dynamic response. Hybrid energy storage systems offer a promising approach by combining complementary battery chemistries, exploiting their respective strengths while mitigating individual limitations. This study presents the design, modeling, and optimization of a hybrid energy storage system composed of two high-energy lithium nickel manganese cobalt batteries and one high-power lithium titanate oxide battery, interconnected through a triple dual-active multi-port converter. A nonlinear model predictive control strategy was employed to optimally distribute battery currents while respecting constraints such as state of charge limits, current bounds, and converter efficiency. Equivalent circuit models were used for real-time state of charge estimation, and converter losses were explicitly included in the optimization. The main contributions of this work are threefold: (i) verification of the model predictive control strategy in diverse applications, including residential renewable energy systems with photovoltaic generation and electric vehicles following the World Harmonized Light-duty Vehicle Test Procedure driving cycle; (ii) explicit inclusion of the power converter model in the system dynamics, enabling realistic coordination between batteries and power electronics; and (iii) incorporation of converter efficiency into the cost function, allowing for simultaneous optimization of energy losses, battery stress, and operational constraints. Simulation results demonstrate that the proposed model predictive control strategy effectively balances power demand, extends system lifetime by prioritizing lithium titanate oxide battery during transient peaks, and preserves lithium nickel manganese cobalt cell health through smoother operation. Overall, the results confirm that the proposed hybrid energy storage system architecture and control strategy enables flexible, reliable, and efficient operation across diverse real-world scenarios, providing a pathway toward more sustainable and durable energy storage solutions. Full article

This paper presents a passive wireless temperature sensor based on an SS-compensated LC-thermistor topology. The system consists of two magnetically coupled LC tanks—each composed of a coil and a series capacitor—forming a series–series (SS) compensation network. The secondary side includes a negative temperature coefficient (NTC) thermistor connected in series with its coil and capacitor, acting as a temperature-dependent load. Magnetically coupled resonant systems exhibit different coupling regimes: weak, critical, and strong. When operating in the strongly coupled regime, the original resonance splits into two distinct frequencies—a phenomenon known as bifurcation. At these split resonance frequencies, the load impedance on the secondary side is reflected as pure resistance at the primary side. In the SS topology, this reflected resistance is equal to the thermistor resistance, enabling precise wireless sensing. The advantage of the SS-compensated configuration lies in its ability to map changes in the thermistor’s resistance directly to the input impedance seen by the reader circuit. As a result, the sensor can wirelessly monitor temperature variations by simply tracking the input impedance at split resonance points. We experimentally validate this property on a benchtop prototype using a one-port VNA measurement, demonstrating that the input resistance at both split frequencies closely matches the expected thermistor resistance, with the observed agreement influenced by the parasitic effects of RF components within the tested temperature range. We also demonstrate that using the average readout provides first-order immunity to small capacitor drift, yielding stable readings. Full article

This paper presents a microstrip active quasi-circulator designed for low-power wireless communication systems. The circuit consists of a second-order Wilkinson power divider and two power amplifiers with high gain and ultra-low noise characteristics. By leveraging the unidirectional transmission characteristics of the transistors and the isolation provided by resistors within the power divider, the interference between the transmitter (TX) and receiver (RX) is effectively suppressed. Additionally, thanks to the dual-amplifier architecture, no extra power amplification circuitry is required, thereby reducing the overall complexity and power consumption of the communication system. The detailed design procedure of the proposed quasi-circulator is presented. The measurement results show that, within the frequency range of 4.75 GHz to 6.11 GHz, the isolation between the TX and RX ports exceeds 20 dB, the return loss at each port is greater than 10 dB, and the transmission gains from the TX port to the antenna and from the antenna to the RX port are 3.1–8.7 dB and 2.7–4.0 dB, respectively, demonstrating a relative bandwidth of 25%. Full article

This paper presents the design and implementation of a wideband diode-based down-converter operating from 60 to 90 GHz with a variable flat conversion gain. The proposed down-converter is implemented utilizing the Miniature Hybrid-Microwave Integrated Circuit (MHMIC) technology. It is composed of a wideband double-balanced mixer, a Local Oscillator (LO) chain, and a differential TransImpedance Amplifier (TIA) with a variable gain. The designed mixer uses a novel topology exhibiting minimum reflection and high isolation between the RF and LO ports across a wide operating frequency of 30 GHz. In this topology, two balanced detectors generate the differential IF signal with minimum reflection. The characteristic impedance ($Z_0$) of the mixer is set to be $70.7$$\Omega$, to minimize trace widths to reduce the mutual coupling and increasing the bandwidth. The OPA 657 is the core of the designed differential TIA with a variable gain. In addition, the LO chain of the down-converter utilized a combination of an active (×2) and a passive (×3) multiplier to generate enough RF power in the desired frequency range. Also, a WR-12 waveguide to Substrate Integrated Waveguide (SIW) transition is designed for the RF and LO ports that operates through the E-band. The proposed down-converter demonstrates excellent performance, with a high isolation between RF and LO ports exceeding 22 dB and a maximum conversion gain of $-5$ dB, and a response with a variation of ±5 dB across the band. The proposed mixer exhibits a return loss of better than 10 dB at both RF and LO ports, and it consumes a power of 560 mW. Full article

In this paper, the accuracy of basic and advanced spiral inductor models for gallium nitride (GaN) integrated inductors is evaluated. Specifically, the experimental measurements of geometrically scaled circular spiral inductors, fabricated in a radio frequency (RF) GaN-on silicon technology, are exploited to estimate the errors of two lumped geometrically scalable models, i.e., a simple π-model with seven components and an advanced model with thirteen components. The comparison is performed by using either the standard performance parameters, such as inductance (L), quality factor (Q-factor), and self-resonance frequency (SRF), or the two-port scattering parameters (S-parameters). The comparison reveals that despite a higher complexity, the developed advanced model achieves a significant reduction in SRF percentage errors in a wide range of geometrical parameters, while enabling an accurate estimation of two-port S-parameters. Indeed, the correct evaluation of both SRF and two-port S-parameters is crucial to exploit the model in an actual circuit design environment by properly setting the inductor geometrical parameters to optimize RF performance. Full article

In precision cotton seeding, the toothed-disk precision seeder often experiences issues with missed seeding and multiple seeding. To promptly detect and address these abnormal seeding conditions, this study develops a modular photoelectric sensing monitoring system. Initially, the monitoring time window is divided using the capacitance sensing signal between two seed drop ports. Concurrently, a photoelectric monitoring circuit is designed to convert the time when seeds block the sensor into a level signal. Subsequently, threshold segmentation is performed on the time when seeds block the photoelectric path under different seeding states. The proposed spatiotemporal joint counting algorithm identifies, in real time, the threshold type of the photoelectric sensor’s output signal within the current monitoring time window, enabling the differentiation of seeding states and the recording of data. Additionally, an STM32 micro-controller serves as the core of the signal acquisition circuit, sending collected data to the PC terminal via serial port communication. The graphical display interface, designed with LVGL (Light and Versatile Graphics Library), updates the seeding monitoring information in real time. Compared to photoelectric monitoring algorithms that detect seed pickup at the seed metering disc, the monitoring node in this study is positioned posteriorly within the seed guide chamber. Consequently, the differentiation between single seeding and multiple seeding is achieved with greater accuracy by the spatiotemporal joint counting algorithm, thereby enhancing the monitoring precision of the system. Field test results indicate that the system’s average accuracy for single-seeding monitoring is 97.30%, for missed-seeding monitoring is 96.48%, and for multiple-seeding monitoring is 96.47%. The average probability of system misjudgment is 3.25%. These outcomes suggest that the proposed modular photoelectric sensing monitoring system can meet the monitoring requirements of precision cotton seeding at various seeding speeds. Full article

Memristive elements, known as memristors, memcapacitors and meminductors, have become an important topic of research in the electronics world in recent years. As there is still no efficient way to manufacture two-terminal memristive elements, many researchers have focused their efforts on designing emulator circuits that mimic these devices. In this study, a memcapacitor emulator circuit using Current Derivative Buffered Amplifier (CDBA) is proposed, which has significant advantages such as wide dynamic range, differential structure at the input port, high sloping rate and wide bandwidth. The main advantages of the emulator are that it is floating without grounding constraint, it is electronically adjustable, it has charge-controlled incremental and decremental modes and it has a simpler circuit structure since it does not contain a memristor. To ensure the integrity of the circuit theory, the results of the mathematical model and the simulation of the memcapacitor are given together. In addition, the characteristics of the experimentally investigated memcapacitor emulator are in good agreement with the simulation results. To provide an illustration of the performance of the proposed emulator, firstly the second-order active low-pass filter circuit and subsequently the amoeba learning circuit are selected as the working environment. The results show that the filtering performance of the proposed emulator at a value after the cut-off frequency in the filter circuit is $25\%$ more efficient than a standard capacitor and in terms of power consumption, it consumes $27.93\%$ less power than a standard capacitor. Moreover, the emulator successfully accomplishes the learning and data storage tasks in the amoeba learning circuit. Full article

Ultrasonic Power Transfer (UPT) offers several advantages over electromagnetic-based wireless power transfer (WPT), but its implementation in the air still faces significant challenges. The low transmission efficiency caused by substantial acoustic energy scattering and absorption and limited output power restricts its use in high-power scenarios. Electrical compensation has proven effective in improving circuit-level performance among various optimization methods, yet its application in air UPT remains underexplored due to the lack of an accurate mathematical model. Traditional modeling approaches, such as the Butterworth–Van Dyke (BVD) model, are unsuitable for air-based UPT systems due to weak coupling and high energy loss. To address these limitations, this paper presents a novel hybrid S-parameter model approach by integrating S-parameter theory with two-port network analysis to improve accuracy and reduce complexity. Based on this model, a novel double-side CL compensation scheme was designed, significantly enhancing the UPT system’s performance while simplifying the compensation circuit design using the Smith chart. Experimental results demonstrate that the proposed scheme enhances efficiency to 2.14% and increases output power to 13.5 mW, significantly improving the transmission performance of the UPT system in the air and offering an effective and practical solution. Full article

This paper presents a differential phase coupler design methodology in the IPD process. The coupler consists of a balun and two phase-shifter circuits. The compact balun was designed with lumped components and a common inductor. Each output of the balun circuit was connected to a phase shifter with an opposite phase to make a desired output phase. In the design example, a three-port 90-degree hybrid coupler was implemented on the IPD process to operate at the 6 GHz WIFI frequency. The post-simulation showed that all reflection coefficients were below −19 dB, with an insertion loss of 1.76 dB and isolation of 20 dB. The core chip size was only 0.02λ₀ × 0.018λ₀. Full article