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This paper introduced a novel approach to enhance the vertical scanning angle of a large aperture 2D electromagnetic micromirror through the utilization of a cascaded torsional beam design. The primary objective was to increase the vertical scanning angle without compromising the robustness, which was achieved by optimizing the trade-off between the rotation angle and the first mode of resonant frequency. The cascaded design provides flexibility to either increase the outer frame's rotation angle without sacrificing torsional stiffness or enhance the torsion beam's stiffness while maintaining the same rotation angle, thus elevating the first-mode resonant frequency and overall robustness. The effectiveness of the cascaded design was demonstrated through a comparative study with a non-cascaded 2D micromirror possessing the same aperture size, torque, and mass moment of inertia. Theoretical analysis and finite-element simulation are employed to determine critical parameters such as the stiffness ratio between the cascaded torsion beams, and to predict improvements in the scanning angle and primary resonant frequency brought by the cascaded design. Prototypes of both cascaded and non-cascaded designs are fabricated using a flexible printed circuit board combined with Computer numerical control (CNC) machining of a Ti-alloy thin film, confirming the superior performance of the cascaded 2D micromirror. The cascaded design achieved vertical scanning angles up to 26% higher than the traditional design when both were actuated at close resonance frequencies. Additionally, the micromirror was successfully integrated into a 3D LiDAR system. The light detection and ranging (LiDAR) system was modelled in Zemax OpticStudio to find the optimized design and assembly positions. [ABSTRACT FROM AUTHOR]

In this paper, we propose a method for calculating the DC source amplitude in an extended multilevel inverter (MLI) structure so that the maximum number of levels and the output voltage waveform are as close as possible to the sinusoidal wave with minimum total harmonic distortion (THD). For the developed structure, three algorithms are suggested to determine the amounts of DC voltage resources. The first important point about choosing the right amounts for the DC resources is that the number of levels should be as large as possible, and the second important point is that the intervals between the levels should be the same throughout the waveform. By observing these two points, the output voltage waveform can be as near as possible to the sinusoidal wave that we want. In this study, we used iteration-based methods to find suitable values for DC sources. Simulation results are offered to confirm the capability of the extended multilevel converter. After we solved the problem through calculation and analysis, a code was written in MATLAB with the aim that this time the code will tell us for what values of DC sources we will have the largest number of levels and as we expected, the output of the MATLAB code confirmed the correctness of the calculations. [ABSTRACT FROM AUTHOR]

Hybrid or resonant switched-capacitor (ReSC) based converters are enticing with their high performance in high- and fixed-ratio applications, due to their efficient utilization of both active semiconductors and passive components. In particular, the cascaded or two-stage topologies have shown promising device utilization with least components required for high conversion ratios. This paper presents a novel bi-lateral energy resonant conversion (BERC) technique, that further improves the passive utilization in two-stage topologies by merging voltage- and current-type hybrid SC converters, beneficial in achieving smaller form factor while maintaining high efficiency. The current-type hybrid SC topology, which relocates the output inductor to its input and enables energy process simplification between adjacent cascaded stages, is first introduced in this paper. A 48-to-12 V converter prototype employing the BERC technique is implemented, validated and demonstrated with a very compact size of 0.18 in$^{3}$, along with an excellent overall peak efficiency of 98.8% (including all gate driver losses) using a zero voltage switching scheme designed for BERC. The prototype is tested up to 60 A, thus achieving a power density of 3900 W/in$^{3}$ with a full-load efficiency more than 98%.

Cascaded multilevel inverters (MLIs) generate an output voltage using series-connected power modules that employ standard configurations of low-voltage components. Each module may employ one or more switched capacitors to double or quadruple its input voltage. The higher number of switched capacitors and semiconductor switches in MLIs compared to conventional two-level inverters has led to concerns about overall system reliability. A fault-tolerant design can mitigate this reliability issue. If one part of the system fails, the MLI can continue its planned operation at a reduced level rather than the entire system failing, which makes the fault tolerance of the MLI particularly important. In this paper, a novel fault location technique is presented that leads to a significant reduction in fault location detection time based on the reliability priority of the components of the proposed fault-tolerant switched capacitor cascaded MLI (CSCMLI). The main contribution of this paper is to reduce the number of MLI switches under fault conditions while operating at lower levels. The fault-tolerant inverter requires fewer switches at higher reliability, and the comparison with similar MLIs shows a faster dynamic response of fault detection and reduced fault location detection time. The experimental results confirm the effectiveness of the presented methods applied in the CSCMLI. Also, all experimental data including processor code, schematic, PCB, and video of CSCMLI operation are attached.

Differential Evolution (DE) -type algorithms perform efficiently on optimization problems, but for some problems, single DE-type algorithms still cannot achieve good results. Integrating multiple algorithms or strategies is an effective way to improve the performance of a single algorithm. This paper proposes a cascaded DE-type algorithm optimization framework with population adaptive allocation and reduction (cDE-APAR), which improves the performance of a single algorithm by cascading two DE-type algorithms and combining related strategies. The first stage of the algorithm runs a single algorithm. The second stage implements the other algorithm in parallel with a local search strategy and a global search strategy, and allocates resources reasonably among the single algorithm and related strategies through adaptive population allocation. Finally, individuals with the worst performance are eliminated through the population reduction strategy to improve the population's quality. In order to verify the performance of the algorithm, extensive simulations were performed using four test suites of CEC2005, CEC2013, CEC2014, and CEC2017. The results show that cDE-APAR significantly improves the performance of a single algorithm. Compared with nine state-of-the-art algorithms, cDE-APAR is significantly better than the comparison algorithms according to the Wilcoxon rank sum test and has significantly improved the accuracy and stability of the solution. [ABSTRACT FROM AUTHOR]

Due to their high efficiency and advanced battery management capability, cascaded multilevel inverters are an exciting option for battery electric powertrains. A promising, new and highly efficient cascaded multilevel inverter is the Parallel Enhanced Commutation Integrated Nested Multilevel Inverter. The inverter, with four semiconductor switches per submodule, can reconfigure individual battery cells in series and parallel and generate positive and negative phase voltages in regular four-quadrant operation. Therefore, emerging degrees of freedom in battery management and inverter operation must be managed and mapped into a specific Switching State for every switch. As controlling the high number of switches is safety-relevant, this publication profoundly explains the inverter's functionality. We introduce a Switching Function that accepts easy-to-understand functional states as input, simplifying research on higher-level control algorithms and advanced single-cell battery-management capabilities. As the Switching Function guarantees safe operation and the correct contribution of every cell to the overall functionality of the inverter, it enables researchers to confidently use and thereby accelerate research on the promising new topology. The method we describe is fast, simple, deterministic and designed to convert setpoint specifications into an executable Switching Pattern. We prove that our Switching Function is operable on an FPGA with a twenty-kilohertz setpoint update operating a 17-level inverter. [ABSTRACT FROM AUTHOR]

• The present three types of ECG signal quality can better accommodate follow-up analysis in practical applications. • A novel multi-task cascaded method is proposed for single-lead ECG in long-term monitoring. • Feature selection is performed to screen optimal task-specific combination. • The proposed method shows excellent generalization on various datasets. In long-term electrocardiogram (ECG) monitoring, the use of wearable devices for signal acquisition inevitably introduces noise, which could reduce the diagnostic capability. In order to improve the efficiency of signal analysis and the accuracy of clinical diagnosis, it is necessary to automatically evaluate the signal quality of ambulatory ECG. In this study, a novel multi-task cascaded method is proposed for signal quality assessment. Based on single-lead ECG, various signal quality indices were derived to assess three classes of signal qualities (clear ECG ideal for full wave analysis, mildly contaminated ECG available for ventricular activity-based analysis, severely contaminated ECG difficult to be analyzed) through a two-step classification corresponding to different tasks. The optimized subsets of quality indices were selected with a criterion of maximal-mean-minimal-variance. Different machine learning models were then trained and tested on public datasets. The results show that random forest using the optimal feature subsets had the best performance, with the overall classification accuracy of 93.76%, 95.13% and 99.61% on the three unknown test sets, respectively. Meanwhile, for the identification of acceptable and unacceptable signals in the first task, the AUC on the test sets reached 0.9967, 0.9959 and 1.0000, respectively. This paper presents a novel signal quality assessment framework, which could provide helpful feedback for ECG processing in specific application scenarios. It is expected to greatly promote accurate and efficient ECG-based diagnosis in long-term monitoring. [ABSTRACT FROM AUTHOR]

A wideband cascaded receiver and a stacked receiver using an improved clock strategy are proposed to support the software-defined radio (SDR). The improved clock strategy reduces the number of mixer switches and the number of LO clock paths required to drive the mixer switches. This reduces the dynamic power consumption. The cascaded receiver includes an inverter-based low-noise transconductance amplifier (LNTA) using a feed-forward technique to enhance the noise performance; a passive mixer; and an inverter-based transimpedance amplifier (TIA). The stacked receiver architecture is used to reduce the power consumption by sharing the current between the LNTA and the TIA from a single supply. It utilizes a wideband LNTA with a capacitor cross-coupled (CCC) common-gate (CG) topology, a passive mixer to convert the RF current to an IF current, an active inductor (AI) and a 1 / f noise-cancellation (NC) technique to improve the noise performance, and a TIA to convert the IF current to an IF voltage at the output. Both cascaded and stacked receivers are simulated in 22  n m CMOS technology. The cascaded receiver achieves a conversion-gain from 26  d B to 36 d B , a double-sideband noise-figure (NFDSB) from 1.4   d B to 3.9   d B , S 11 < − 10   d B and an IIP3 from − 7.5   d Bm to − 10.5   d Bm , over the RF operating band from 0.4   G Hz to 12  G Hz. The stacked receiver achieves a conversion-gain from 34.5   d B to 36  d B , a NFDSB from 4.6   d B to 6.2   d B , S 11 < − 10   d B , and an IIP3 from − 21   d Bm to − 17.5   d Bm , over the RF operating band from 2.2   G Hz to 3.2   G Hz. The cascaded receiver consumes 11 m from a 1  V supply voltage, while the stacked receiver consumes 2.4 m from a 1.2   V supply voltage. [ABSTRACT FROM AUTHOR]

This article presents a single-stage five-level boost inverter (5L-SBI) topology with reduced power components. The proposed topology falls under the self-balanced switch-capacitors (SCs) type and combines both a DC/DC boost converter and inverter with a switched-capacitor cell. The advantages of proposed topologies include the following: the number of switch counts is reduced, the maximum voltage gain is two times higher than the input voltage, and the capacitor's charging current is suppressed. Further, the proposed topology cascaded, and three-phase extensions are presented. To attest, the advantages of the proposed topology are thoroughly compared with other recent SCI topologies. The proposed topology is verified under dynamic loading conditions, and the results are presented, considering a 600 W laboratory prototype model. [ABSTRACT FROM AUTHOR]

Deep neural networks are now widely used in the medical image segmentation field for their performance superiority and no need of manual feature extraction. U-Net has been the baseline model since the very beginning due to a symmetricalU-structure for better feature extraction and fusing and suitable for small datasets. To enhance the segmentation performance of U-Net, cascaded U-Net proposes to put two U-Nets successively to segment targets from coarse to fine. However, the plain cascaded U-Net faces the problem of too less between connections so the contextual information learned by the former U-Net cannot be fully used by the latter one. In this article, we devise novel Inner Cascaded U-Net and Inner Cascaded U²-Net as improvements to plain cascaded U-Net for medical image segmentation. The proposed Inner Cascaded U-Net adds inner nested connections between two U-Nets to share more contextual information. To further boost segmentation performance, we propose Inner Cascaded U²-Net, which applies residual U-block to capture more global contextual information from different scales. The proposed models can be trained from scratch in an end-to-end fashion and have been evaluated on Multimodal Brain Tumor Segmentation Challenge (BraTS) 2013 and ISBI Liver Tumor Segmentation Challenge (LiTS) dataset in comparison to related U-Net, cascaded U-Net, U-Net++, U²-Net and state-of-the-art methods. Our experiments demonstrate that our proposed Inner Cascaded U-Net and Inner Cascaded U2-Net achieve better segmentation performance in terms of dice similarity coefficient and hausdorff distance as well as get finer outline segmentation. [ABSTRACT FROM AUTHOR]

This paper introduced a novel approach to enhance the vertical scanning angle of a large aperture 2D electromagnetic micromirror through the utilization of a cascaded torsional beam design. The primary objective was to increase the vertical scanning angle without compromising the robustness, which was achieved by optimizing the trade-off between the rotation angle and the first mode of resonant frequency. The cascaded design provides flexibility to either increase the outer frame’s rotation angle without sacrificing torsional stiffness or enhance the torsion beam’s stiffness while maintaining the same rotation angle, thus elevating the first-mode resonant frequency and overall robustness. The effectiveness of the cascaded design was demonstrated through a comparative study with a non-cascaded 2D micromirror possessing the same aperture size, torque, and mass moment of inertia. Theoretical analysis and finite-element simulation are employed to determine critical parameters such as the stiffness ratio between the cascaded torsion beams, and to predict improvements in the scanning angle and primary resonant frequency brought by the cascaded design. Prototypes of both cascaded and non-cascaded designs are fabricated using a flexible printed circuit board combined with Computer numerical control (CNC) machining of a Ti-alloy thin film, confirming the superior performance of the cascaded 2D micromirror. The cascaded design achieved vertical scanning angles up to 26% higher than the traditional design when both were actuated at close resonance frequencies. Additionally, the micromirror was successfully integrated into a 3D LiDAR system. The light detection and ranging (LiDAR) system was modelled in Zemax OpticStudio to find the optimized design and assembly positions.

There is currently a growing interest in efficient power generation and transformation without increasing the cost and complexity of a system. One type of transformation is the conversion of energy from a direct current to an alternating current, which is used in various applications, for example, in photovoltaic systems. One of the elementary components of these systems is the inverter. However, there are several drawbacks in the design of these systems, such as the energy balance between their semiconductor devices. Therefore, it is important to study alternatives to balance the energy and thus achieve a positive impact on both the economic and reliability aspects of the system. This article deals with the study, design, and implementation of the modification of a modulation technique with reconstructed modulating signals, which aims to ensure the energy balance in each cell of a multilevel inverter and, at the same time, present better results concerning the different parameters of comparison established, such as harmonic distortion, percentage of unbalance, percentage of use of digital resources, and power transferred to the load. [ABSTRACT FROM AUTHOR]

Purpose: Automatic muscle segmentation is critical for advancing our understanding of human physiology, biomechanics, and musculoskeletal pathologies, as it allows for timely exploration of large multi‐dimensional image sets. Segmentation models are rarely developed/validated for the pediatric model. As such, autosegmentation is not available to explore how muscle architectural changes during development and how disease/pathology affects the developing musculoskeletal system. Thus, we aimed to develop and validate an end‐to‐end, fully automated, deep learning model for accurate segmentation of the rectus femoris and vastus lateral, medialis, and intermedialis using a pediatric database. Methods: We developed a two‐stage cascaded deep learning model in a coarse‐to‐fine manner. In the first stage, the U2‐Net roughly detects the muscle subcompartment region. Then, in the second stage, the shape‐aware 3D semantic segmentation method SASSNet refines the cropped target regions to generate the more finer and accurate segmentation masks. We utilized multifeature image maps in both stages to stabilize performance and validated their use with an ablation study. The second‐stage SASSNet was independently run and evaluated with three different cropped region resolutions: the original image resolution, and images downsampled 2× and 4× (high, mid, and low). The relationship between image resolution and segmentation accuracy was explored. In addition, the patella was included as a comparator to past work. We evaluated segmentation accuracy using leave‐one‐out testing on a database of 3D MR images (0.43 × 0.43 × 2 mm) from 40 pediatric participants (age 15.3 ± 1.9 years, 55.8 ± 11.8 kg, 164.2 ± 7.9 cm, 38F/2 M). Results: The mid‐resolution second stage produced the best results for the vastus medialis, rectus femoris, and patella (Dice similarity coefficient = 95.0%, 95.1%, 93.7%), whereas the low‐resolution second stage produced the best results for the vastus lateralis and vastus intermedialis (DSC = 94.5% and 93.7%). In comparing the low‐ to mid‐resolution cases, the vasti intermedialis, vastus medialis, rectus femoris, and patella produced significant differences (p = 0.0015, p = 0.0101, p < 0.0001, p = 0.0003) and the vasti lateralis did not (p = 0.2177). The high‐resolution stage 2 had significantly lower accuracy (1.0 to 4.4 dice percentage points) compared to both the mid‐ and low‐resolution routines (p value ranged from < 0.001 to 0.04). The one exception was the rectus femoris, where there was no difference between the low‐ and high‐resolution cases. The ablation study demonstrated that the multifeature is more reliable than the single feature. Conclusions: Our successful implementation of this two‐stage segmentation pipeline provides a critical tool for expanding pediatric muscle physiology and clinical research. With a relatively small and variable dataset, our fully automatic segmentation technique produces accuracies that matched or exceeded the current state of the art. The two‐stage segmentation avoids memory issues and excessive run times by using a first stage focused on cropping out unnecessary data. The excellent Dice similarity coefficients improve upon previous template‐based automatic and semiautomatic methodologies targeting the leg musculature. More importantly, with a naturally variable dataset (size, shape, etc.), the proposed model demonstrates slightly improved accuracies, compared to previous neural networks methods. [ABSTRACT FROM AUTHOR]

The liver is an irreplaceable organ in the human body, maintaining life activities and metabolism. Malignant tumors of the liver have a high mortality rate at present. Computer-aided segmentation of the liver and tumors has significant effects on clinical diagnosis and treatment. There are still many challenges in the segmentation of the liver and liver tumors simultaneously, such as, on the one hand, that convolutional kernels with fixed geometric structures do not match complex, irregularly shaped targets; on the other, pooling during convolution results in a loss of spatial contextual information of images. In this work, we designed a cascaded U-ADenseNet with coarse-to-fine processing for addressing the above issues of fully automatic segmentation. This work contributes multi-resolution input images and multi-layered channel attention combined with atrous spatial pyramid pooling densely connected in the fine segmentation. The proposed model was evaluated by a public dataset of the Liver Tumor Segmentation Challenge (LiTS). Our approach attained competitive liver and tumor segmentation scores that exceeded other methods across a wide range of metrics. [ABSTRACT FROM AUTHOR]

We review our recent experimental results on the cascaded Raman conversion of highly multimode laser diode (LD) pump radiation into the first- and higher-order Stokes radiation in multimode graded-index fibers. A linear cavity composed of fiber Bragg gratings (FBGs) inscribed in the fiber core is formed to provide feedback for the first Stokes order, whereas, for the second order, both a linear cavity consisting of two FBGs and a half-open cavity with one FBG and random distributed feedback (RDFB) via Rayleigh backscattering along the fiber are explored. LDs with different wavelengths (915 and 940 nm) are used for pumping enabling Raman lasing at different wavelengths of the first (950, 954 and 976 nm), second (976, 996 and 1019 nm) and third (1065 nm) Stokes orders. Output power and efficiency, spectral line shapes and widths, beam quality and shapes are compared for different configurations. It is shown that the RDFB cavity provides higher slope efficiency of the second Stokes generation (up to 70% as that for the first Stokes wave) with output power up to ~30 W, limited by the third Stokes generation. The best beam quality parameter of the second Stokes beam is close to the diffraction limit (M2~1.3) in both linear and half-open cavities, whereas the line is narrower (<0.2 nm) and more stable in the case of the linear cavity with two FBGs. However, an optimization of the FBG reflection spectrum used in the half-open cavity allows this linewidth value to be approached. The measured beam profiles show the dip formation in the output pump beam profile, whereas the first and second Stokes beams are Gaussian-shaped and almost unchanged with increasing power. A qualitative explanation of such behavior in connection with the power evolution for the transmitted pump and generated first, second and third Stokes beams is given. The potential for wavelength tuning of the cascaded Raman lasers based on LD-pumped multimode fibers is discussed. [ABSTRACT FROM AUTHOR]