Search Results (148)

This paper analyses a special case in evaluating the passive autoranging (AR) technique that dynamically extends the measurement range of a fiber Bragg grating/piezoelectric transducer (FBG/PZT) operating with a current transformer (CT) to realize a dual-purpose metering and protection photonic current transducer (PCT). The technique relies on shorting serially connected burden resistors operating with the CT, using MOSFET switches that react to a changing input current to extend measurement range. The rapid changes in the voltage at the FBG/PZT transducer that are associated with the MOSFET switching are then used on the FBG interrogator side to select the correct measurement range. However, when the MOSFET switching in the AR circuit occurs near the zero-crossing of the input current, the rapid changes in the voltage presented to the FBG/PZT no longer occur, rendering the correct range setting at the interrogator side problematic. The basic switching detection algorithm based on voltage derivative (dV/dt) thresholds proposed in the previous research is not sufficiently sensitive in these conditions, leading to incorrect range selection. To address this, a new detection algorithm based on temporal slope differencing around the zero-crossing is proposed as an additional detection mechanism for these special cases. Thus, the improved hybrid algorithm additionally computes the derivative dV/dt at the FBG/PZT voltage signal within a focused 6 ms temporal window centered around the zero-crossing point, a 3 ms window before and after each zero-crossing instance. It then compares the difference between these two values to a predefined threshold. If the difference exceeds the threshold, a switching event is identified. This method reliably detects even subtle switching events near zero crossings, enabling the accurate reconstruction of the burden current. The performance of the improved algorithm is validated through simulations and experimental results involving zero-crossing switching scenarios. Results indicate that the proposed algorithm improves MOSFET switching detection and facilitates reliable waveform reconstruction without requiring additional hardware. Full article

This submission is focused on the implementation of a system that acquires data from various types of sensors and securely stores them after encryption on a chip with a reconfigurable architecture. The system has the unique capability of encrypting the input data with a single secret cryptographic key, which is stored only inside the hardware of the system itself, so the key remains unrecognizable upon completion of the system synthesis for any unauthorized user. Being stored as a part of the whole system architecture, the cryptographic key cannot be attained. It is not stored separately on the system RAM or any other supported memory, making the collected data fully protected. The reported work shows a data acquisition system which measures temperature with a high level of precision, transforms it to degrees Celsius, stores the collected data, and transfers them via serial interface when requested. Before storage, the data are encrypted with a 256-bit key, applying the AES algorithm. The data which are stored in the system memory and sent as UART packets towards the main computer do not include the cryptographic key in the data stream, so it is impossible for it to be retrieved from them. We show the flexibility of such kinds of data acquisition systems for sensing different types of signals, emphasizing secure storage and transferring, including data from meteorological sensors or highly confidential or biometrical data. Full article

In contemporary industrial machinery, bearings are a vital component, so the ability to diagnose bearing faults is extremely important. Current methodologies face challenges in feature extraction and perform suboptimally in environments with high noise levels. This paper proposes an enhanced, multimodal, feature-fusion-bearing fault diagnosis model. Integrating a 1DCNN-dual MLP framework with an enhanced two-way cross-attention mechanism enables in-depth feature fusion. Firstly, the raw fault time-series data undergo fast Fourier transform (FFT). Then, the original time-series data are input into a multi-layer perceptron (MLP) and a one-dimensional convolutional neural network (1DCNN) model. The frequency-domain data are then entered into the other multi-layer perceptron (MLP) model to extract deep features in both the time and frequency domains. These features are then fed into a serial bidirectional cross-attention mechanism for feature fusion. At the same time, a GCOS learning rate scheduler has been developed to automatically adjust the learning rate. Following fifteen independent experiments on the Case Western Reserve University bearing dataset, the fusion model achieved an average accuracy rate of 99.83%. Even in a high-noise environment (0 dB), the model achieved an accuracy rate of 90.66%, indicating its ability to perform well under such conditions. Its accuracy remains at 86.73%, even under 0 dB noise and variable operating conditions, fully demonstrating its exceptional robustness. Full article

Aiming at the multifunctional requirements of the limited space in high-end vehicle side-door latches, a double single-loop RRUPRR mechanism driven by a single motor for both electric releasing and cinching is proposed based on the POC set. The kinematical equations of the RRURR mechanism possess 2 × 2 analytical solutions. In order to apply the current motion/force transmission performance index of the parallel mechanisms to the transmission performance analysis of the serial mechanisms, matching methods for chain-driving transference and the moving/fixed platform inversion are proposed. The solution of the performance index of a single-degree-of-freedom single-loop mechanism is equivalent to the solution of the input motion/force transmission performance index of a parallel mechanism. The overall motion/force transmission performance index of a single-loop mechanism is constructed, and the corresponding calculation procedure is defined. Chain-driving transference can be obtained through forward and inverse solutions of the RRURR mechanism. In response to the extremely high requirements for motion/force transmission performance of electric release mechanisms, the proposed overall motion/force transmission performance index is used to calculate for the input motion screw and corresponding transmission-force screw of the single-loop RRURR mechanism and obtain the overall motion/force transmission performance of the mechanism. The performance atlas of the mechanism shows that it has excellent motion/force transmission characteristics within the workspace. Using ADAMS simulation software, the driving torque required for electric releasing and cinching of a vehicle side-door latch mechanism with a single motor is analyzed. The overall motion/force transmission performance index of a single-loop mechanism can be applied to single-loop overconstrained mechanisms and non-overconstrained mechanisms. Full article

In this work, an innovative Schönflies motion generator manipulator is introduced, featuring a parallel architecture composed of serial chains with mixed degrees of freedom. Fundamental kinematic aspects essential to any manipulator such as displacement, velocity, acceleration, and singularity analyses are thoroughly addressed. Screw theory is employed to derive compact input–output expressions for velocity and acceleration, leveraging the properties of reciprocal screws and lines associated with the constrained degrees of freedom in the parallel manipulator. A key advantage of the proposed design is its near-complete avoidance of singular configurations, which significantly enhances its applicability in robotic manipulation. Numerical examples are provided to validate the theoretical results, with corroboration from specialized tools such as ADAMS™ software and data fitting algorithms. These results confirm the reliability and robustness of the developed kinematic analysis approach. Full article

Turbo Codes (TCs) are a family of convolutional codes that provide powerful Forward Error Correction (FEC) and operate near the Shannon limit for channel capacity. In the context of modern communication systems, such as those conforming to the DVB-RCS2 standard, Turbo Encoders (TEs) play a crucial role in ensuring robust data transmission over noisy satellite links. A key computational bottleneck in the Turbo Encoder is the non-uniform interleaving stage, where input bits are rearranged according to a dynamically generated permutation pattern. This stage often requires the intermediate storage of data, resulting in increased latency and reduced throughput, especially in embedded or real-time systems. This paper introduces a vector processing algorithm designed to accelerate the interleaving stage of the Turbo Encoder. The proposed algorithm is tailored for vector DSP architectures (e.g., CEVA-XC4500), and leverages the hardware’s SIMD capabilities to perform the permutation operation in a structured, phase-wise manner. Our method adopts a modular Load–Execute–Store design, facilitating efficient memory alignment, deterministic latency, and hardware portability. We present a detailed breakdown of the algorithm’s implementation, compare it with a conventional scalar (serial) model, and analyze its compatibility with the DVB-RCS2 specification. Experimental results demonstrate significant performance improvements, achieving a speed-up factor of up to 3.4× in total cycles, 4.8× in write operations, and 7.3× in read operations, relative to the baseline scalar implementation. The findings highlight the effectiveness of vectorized permutation in FEC pipelines and its relevance for high-throughput, low-power communication systems. Full article

The anatomical arrangement of the atrioventricular node has been likened to a riddle wrapped up in an enigma. There are several reasons for this alleged mystery, not least the marked variability in structure between different species. Lack of detailed knowledge of the location of the node relative to the atrial and ventricular septal structures has also contributed to previous misunderstandings. Recent studies comparing the findings of gross dissection with virtual dissection of living datasets, combined with access to a large number of serially sectioned human and animal hearts, have served to provide the evidence to solve the riddle. We summarise these findings in this review. We explain how the node is located within the atrial walls of the inferior pyramidal space. It becomes the non-branching component of the atrioventricular conduction axis as the axis extends through the plane of atrioventricular insulation to enter the infero-septal recess of the left ventricular outflow tract. The node itself is formed by contributions from the tricuspid and mitral vestibules, with extensive additional inputs from the base of the atrial septum. We show how knowledge of development enhances the appreciation of the arrangements and offers an explanation as to why, on occasion, there can be persisting nodoventricular connections. We discuss the findings relative to the circuits producing atrioventricular re-entry tachycardia. We conclude by emphasising the significance of the variation of the anatomical arrangements within different mammalian species. Full article

As one of the key processes of photosynthesis, carbon fixation and reduction is one of the most important biochemical reactions on planet Earth. Yet, reducing oxidized carbon elements through directly harnessing solar energy by using water-soluble, simple enzymes continues to be challenging. Here, CO₂ and bicarbonate were found to be transformed into methanol by fluorescent protein mRuby by using light as the single energy input. The binding of substrates to mRuby chromophore was supported by crystallography and light spectrometry. Gas chromatography showed the generation of methanol in mRuby-bicarbonate aqueous solution upon sunlight illumination. Atomic-resolution serial structures of mRuby showed snapshots of the step-by-step reduction of bicarbonate and CO₂. The amino, imino, or carboxylate group of residues near the chromophore was within hydrogen bonding distances of the substrates, respectively. A decrease in fluorescence was observed upon binding of bicarbonate, and the energy liberated from fluorescence was presumably utilized for methanol production. This research represents an exciting example of sunlight-driven photobiocatalysis by water-soluble small proteins. The new, green, and sustainable mechanisms uncovered here indicated great promises to harness solar energy straightforwardly, for, i.e., fuel production and green chemistry. Full article

All-optical matching systems that detect and localize designated target sequences in input all-optical data sequences have attracted significant attention in all-optical processing. They have various applications, including all-optical intrusion detection, optical frame alignment, and optical package identification. In real-world applications, noise is inevitable and can lead to incorrect matching results. In particular, noise accumulates in serial all-optical matching systems, rendering the systems useless after several cycles. In this study, we developed a scheme for suppressing noise in quadrature phase-shift-keying (QPSK)-oriented all-optical matching systems. First, we evaluated the impact of input and amplifier noise on a QPSK-oriented all-optical matching system at a transmission rate of 100 Gbaud. We then developed a second-order noise-suppression structure using a highly nonlinear fiber (HNLF). With an input optical signal-to-noise ratio (OSNR) of 6 dB and an amplifier noise figure (NF) of 4 dB, the QPSK-oriented all-optical matching system without the noise-suppression structure output incorrect results. However, when the system was optimized using the proposed noise-suppression structure, correct matching results were obtained. Furthermore, when the NF of the amplifiers was fixed at 4 dB, the optimized system could reduce the minimum input OSNR to 0 dB. With an input OSNR of 0 dB, the logarithm of the bit error rate (BER) of the output matching results of the optimized system tended to negative infinity. The extinction ratio (ER), contrast ratio (CR), and quality (Q) factor of the output of the optimized system were 154.9532, 166.94289, and 161.12 dB, respectively, indicating high noise resistance. These results demonstrate that the system optimized using the proposed noise-suppression scheme exhibits high stability and reliability in noisy environments. Full article

The integrated circuit (IC) industry has rapidly developed, with chip hardware security assuming a critical role in IC design. The physical unclonable function (PUF) exploits semiconductor process variation differences to generate unique responses randomly. Due to its non-replicability, PUF has emerged as one of the most commonly employed methods in hardware security. We propose PUF implementation employing an automatic scan selector to toggle between eight sets of multiplexers. With an 8-bit selector, 256 state inputs are automatically generated, and the PUF architecture enables a 256-bit unique identification code for the chip. Finally, the generated identification code is outputted either serially or in parallel and implemented on a field-programmable gate array platform. Full article

Maintenance of the exteriors of buildings with convex façades, such as skyscrapers, is in high demand in urban centers. However, manual maintenance is inherently dangerous due to the possibility of accidental falls. Therefore, research has been conducted on cleaning robots as a replacement for human workers, e.g., the dual ascension robot (DAR), which is an underactuated rope-driven robot, and the rope-riding mobile anchor (RMA), which is a rope-riding robot. These robots are equipped with a convex-façade-cleaning system. The DAR and RMA are connected to each other by a rope that enables vibration transmission between them. It also increases the instability of the residual vibration that occurs during the operation of the DAR. This study focused on reducing the residual vibrations of a DAR to improve the stability of the overall system. Because it is a rope-on-rope (ROR) system, we assumed it to be a simplified serial spring–damper system and analyzed its kinematics and dynamics. An input-shaping technique was applied to control the residual vibrations in the DAR. We also applied a disturbance observer to mitigate factors contributing to the system uncertainty, such as rope deformation, slip, and external forces. We experimentally validated the system and assessed the effectiveness of the control method, which consisted of the input shaper and disturbance observer. Consequently, the residual vibrations were reduced. Full article

With the growing demand for large-scale urban observation, multi-channel technology has become a cornerstone of high-resolution wide-swath SAR systems. The challenge of storing and transmitting the large data volumes generated by multi-channel systems has driven the development of advanced data compression techniques. However, in onboard implementations with non-power-of-two channel numbers and serial data formats, the existing multi-channel compression algorithms reveal significant conflicts involving channel counts, FFT cores, and the Krieger method. To address these issues, this paper introduces the Channel-Adaptive Range-Doppler domain filtering Serial Block Adaptive Quantization algorithm (CARDS-BAQ). By incorporating a point-frequency RD domain filtering approach and leveraging serial data matrix splicing and rollback combined with point-frequency ABAQ, CARDS-BAQ enables efficient data compression for arbitrary channel counts. The performance of CARDS-BAQ is validated using GF-3 measured data through comparative analysis with BAQ, ABAQ, MCBAQ, and 3MBAQ algorithms under power-of-two channel conditions. Additionally, its applicability and reliability for non-power-of-two channel numbers are demonstrated through payload flight experiments conducted in 2024 in Yingkou, Liaoning Province, China. CARDS-BAQ effectively supports data storage and transmission for large-scale urban observation, marking a significant advancement in remote sensing technology. Full article

Background/Objectives: The morphological characteristics of breast tumors play a crucial role in the preliminary diagnosis of breast cancer. However, malignant tumors often exhibit rough, irregular edges and unclear, boundaries in ultrasound images. Additionally, variations in tumor size, location, and shape further complicate the accurate segmentation of breast tumors from ultrasound images. Methods: For these difficulties, this paper introduces a breast ultrasound tumor segmentation network comprising a multi-scale feature acquisition (MFA) module and a multi-input edge supplement (MES) module. The MFA module effectively incorporates dilated convolutions of various sizes in a serial-parallel fashion to capture tumor features at diverse scales. Then, the MES module is employed to enhance the output of each decoder layer by supplementing edge information. This process aims to improve the overall integrity of tumor boundaries, contributing to more refined segmentation results. Results: The mean Dice (mDice), Pixel Accuracy (PA), Intersection over Union (IoU), Recall, and Hausdorff Distance (HD) of this method for the publicly available breast ultrasound image (BUSI) dataset were 79.43%, 96.84%, 83.00%, 87.17%, and 19.71 mm, respectively, and for the dataset of Fujian Cancer Hospital, 90.45%, 97.55%, 90.08%, 93.72%, and 11.02 mm, respectively. In the BUSI dataset, compared to the original UNet, the Dice for malignant tumors increased by 14.59%, and the HD decreased by 17.13 mm. Conclusions: Our method is capable of accurately segmenting breast tumor ultrasound images, which provides very valuable edge information for subsequent diagnosis of breast cancer. The experimental results show that our method has made substantial progress in improving accuracy. Full article

This study investigates the correlation between bluff body parameters and vortex flowmeter performance through big data modeling and machine learning techniques. Vortex flowmeters are widely used in industry due to their high accuracy and minimal pressure loss. Nonetheless, optimizing their design remains challenging due to the complex relationship between input and output parameters. Symmetry in bluff body design is crucial for vortex formation and stability. In this study, Latin Hypercube Sampling (LHS) was employed to generate 10,000 symmetry bluff bodies, and efficient serial simulations were conducted using Ansys Fluent, significantly reducing computational costs compared to traditional CFD methods. A regression model was developed using scikit-learn to map eight geometric parameters to eight performance indicators, achieving excellent fitting accuracy with residuals far smaller than the simulation accuracy of ANSYS Fluent. Through Grey Relational Analysis (GRA), objective function analysis, and in conjunction with CFD contour maps, this study has analyzed the relationships between input and output parameters and their impact on the Karman vortex street. This work has significantly improved the speed of big data collection and provided a solid theoretical foundation for data-driven optimization through big data analysis. In addition, the improvement of existing machine learning methods has achieved high-precision prediction and system parameter optimization, promoting the design of vortex flowmeters. Full article

The incorporation of Internet of Things (IoT) edge nodes into assistive technologies greatly improves the daily lives of individuals with disabilities by facilitating real-time data processing and seamless connectivity. However, the increasing adoption of IoT edge devices intended for individuals with disabilities presents significant security challenges, particularly concerning the safeguarding of sensitive data and the heightened risk of cyber vulnerabilities. To effectively mitigate these risks, advanced cryptographic protocols, including those based on elliptic curve cryptography, have been proposed to establish robust security measures. While these protocols are effective in reducing the risk of data exposure, they often demand considerable computational resources, which poses challenges for cost-effective IoT devices. Therefore, it is essential to prioritize the effective execution of cryptographic algorithms, as they rely on finite field operations such as multiplication, inversion, and division. Among these computations, field multiplication is particularly critical, serving as the backbone for the other operations. This study intends to create an innovative hybrid systolic array design for the Dickson basis multiplier, which integrates both serial and parallel inputs to enhance overall performance. The proposed design is anticipated to significantly reduce space and power consumption, thereby enabling the secure execution of complex cryptographic algorithms on resource-limited IoT devices designed for disabled people. By addressing these pressing security issues, the study aspires to fully leverage IoT technologies to enhance the living standards of individuals with disabilities, while ensuring that their privacy and security are meticulously maintained. Full article