The application of fuzzy theory in stealth laser dicing technology for wafers aims to enhance the precision and efficiency of cutting parameters. With technological advancements and the growth of the electric vehicle industry, the demand for semiconductor chips has rapidly increased, driving wafer cutting technology towards greater efficiency and precision. Compared to traditional blade cutting and laser cutting techniques, stealth laser dicing technology can avoid the chipping caused by blade cuts and the thermal damage caused by laser cuts, providing a stress-free and thermal damage-free solution. This study optimizes cutting parameters through a fuzzy control system using a layered setting method. The first layer determines the most suitable laser power based on the thickness of the workpiece and the metal layer; the second layer uses the final wafer thickness and the laser power determined in the first layer as inputs to calculate the optimal scribing height. These parameter settings aim to enhance cutting quality and efficiency while also verifying the practical application effects of the fuzzy control system. Experimental results show that the fuzzy control system significantly improves cutting precision and efficiency, achieving a $100 \%$ cutting success rate, a ${6 6 \%}$ reduction in material consumption, a 4% reduction in energy usage, and a $50 \%$ reduction in parameter adjustment labor time. The precision of the fuzzy control system in controlling laser power surpasses manual settings, and the optimization of scribing height is also significantly improved. The study demonstrates that fuzzy theory has extensive potential applications in stealth laser dicing of wafers. Future research may integrate artificial intelligence technology to further enhance the automation of cutting parameter settings, thereby improving production efficiency and product quality.
Advancements in network technology, such as 5G and 6G systems, have increased the need for large-scale data communication. This has led to a higher demand for efficient FFT processors capable of handling big data. In this paper, we propose a low-power variable-length FFT architecture with distributed memory to enhance data processing efficiency. The architecture employs an auto-correction rotator to efficiently and accurately generate the corresponding twiddle factors without excessive memory storage. To further reduce power consumption, distributed memory is used for storing computational data, with dynamic pointers facilitating data access. Simulations demonstrate improvements in processing speed and memory efficiency, addressing the demands for efficient data transmission. The proposed FFT chip design shows promise for application in next-generation network systems.
Designing a quantum circuit that prepares userspecific states is a fundamental task in quantum computation. This involves loading user-provided data into the initial superposition state of a quantum register, enabling further processing by quantum algorithms. To address this state preparation problem, a quantum circuit utilizing rotation Y gates and controlled rotation Y gates has been previously proposed. However, the method for determining the rotation angles of these Y gates has not been detailed. This paper introduces a closed-form method for computing these angle parameters based on user-provided data. Numerical examples demonstrate the ease of use of the proposed method, which is implemented using IBM’s quantum information software kit (Qiskit). Additionally, real-world feature data from iris flowers is used to show that the feature data can be accurately loaded into the quantum register, facilitating tasks such as machine learning, dimensionality reduction, or pattern recognition through quantum computation.
This study uses Yolov5 object detection technology to detect the deterioration and defects of the painted layer of oil paintings. Two non-destructive detection light source image data, ultraviolet light and normal light will be used to identify refills, insect removal, and missing painted layers to assist Restoration engineers in speeding up the efficiency of missing annotation work in the work review process.This study applied the data augmentation method to increase the sample size and class balance. The results of this study show that the data augmentation method and class balancing can effectively improve the performance of the model; the performance of the proposed oil painting layer defect detection model has reached more than 98% in the class of insect exclusion and 70% in the class of retouching and painting layer loss. The study’s results can initially assist the restorer in the inspection process, effectively detect and locate defects, and provide the defect type and location to the restorer for reference, shortening the inspection process time and improving operational efficiency.
Given an unlabeled time series dataset, it is often required to cluster similar time series data. Dynamic Time Warping (DTW) is one of the useful methods to evaluate the similarity between time series data. However, the algorithm of DTW has a high computational cost and requires substantial computation time. To solve the issue, a DTW distance calculator has been proposed to reduce the computation time of DTW distance calculations. Additionally, a conventional circuit using neuron CMOS Winner-Take-All (vCMOS WTA) circuit has also been proposed for the minimum value determination circuit used in the DTW calculator. However, the proposed minimum value determination circuit was still unstable. In this paper, we propose a new minimum value determination circuit for use in the DTW distance calculator. In addition, this paper describes the circuit design, the circuit operation, and the results of HSPICE simulations.
Anonymous property is a fundamental right for legitimate customers when he/she was shopping. But it could be misused by criminals. In this paper, we will propose an efficient and new blind signature (BS). The proposed scheme based on the ElGamal signature in that can prevent the misused of the BS scheme by criminals.
This paper investigates the impact of Non-Line-of-Sight (NLOS) channels on the performance of UltraWideband (UWB) multi-anchor three-dimensional (3D) positioning systems. The study involves a series of experiments conducted in both Line-of-Sight (LOS) and NLOS conditions, using varying numbers of anchors to evaluate how these factors influence positioning errors. The results indicate that increasing the number of anchors in NLOS environments does not necessarily improve positioning accuracy. In fact, it can exacerbate positioning errors due to the intensification of multipath effects and signal attenuation. The findings emphasize the need for careful anchor placement and selection, particularly in environments prone to NLOS conditions, to ensure reliable performance of UWB-based indoor positioning systems.
This article proposed a broadband oval-ring slot CP (circularly polarized) antenna. This oval-ring slot antenna was fed by a 50-ohm CPW (coplanar waveguide). The antenna size is 72 mm $\times$ 68 mm. The antenna operates within a frequency range of 3.31 to 4.81 GHz and with a 3-dB AR (axial ratio) spanning from 3.55 to 4.45 GHz (22.5%).
Recently, Yan et al. proposed an identity-based matchmaking encryption with equality test (IB-ME-ET) scheme, which was constructed in the identity-based public key system (IB-PKS). IB-ME-ET features mutual pairing between senders and receivers and supports the property of equality test for ciphertexts. However, IB-PKS suffers from key escrow issues where the private key generator (PKG) holds users’ private keys, potentially compromising security and privacy. Fortunately, the certificateless public key system (CL-PKS) resolves the key escrow problem while maintaining the features of IB-PKS, namely, eliminating the need of establishing public key infrastructures. Therefore, our goal is to propose the first certificateless ME-ET (CL-ME-ET) scheme. The CL-ME-ET scheme not only retains the original features of IB-ME-ET but also addresses key escrow issues.
Measuring the respiratory rate of inpatients is important for detecting physical changes and signs of abnormality in medical field. Therefore, respiratory rate of inpatients is regularly measured. However, measuring respiratory rates places a heavy burden of healthcare workers. The reason is that respiratory rate is measured by visual observation. To reduce the burden of healthcare workers, we investigate a simple, non-invasive and automatic method of measuring respiratory rate. We focus on object detection algorithms. Object detection algorithms detect objects in the image. Then, bounding boxes are output at the locations of detected objects. We propose a method for measuring respiratory rate using the width of the bounding box.
Recently, the demand for video content has been increasing due to the growing number of diverse social networking users. On the other hand, it is necessary to be aware of copyrights when uploading videos. If copyrighted music is included in the video, the music must be removed from the video. There is a method using audio enhancement techniques to remove music from video, but this method removes the environmental sounds in the video, which reduces the sense of realism of the video. Therefore, a method has proposed to remove music only from multiple mixtures of sounds using machine learning. However, the music removal accuracy of the method is not sufficient. In contrast, augmenting the training data is expected to improve accuracy, however, there is no suitable augmentation methods for music data. Therefore, we propose applying pitch shifting as a data augmentation method for music data to improve the music removal accuracy. Then, we conduct a simulation using both the original data without augmentation and the data augmented with our proposed method, and compare the music removal accuracy. As a result, we confirm that music is removed with higher accuracy when learning with augmented data. Therefore, the data augmentation method proposed in this paper is effective.
Since the introduction of the ruby laser in 1960, solid-state laser technology has evolved significantly. While some early laser systems relied on LEDs for pumping, the emergence of high-brightness laser diodes (LDs) shifted towards Diode-pumped systems. However, LDs present challenges such as temperature sensitivity, requiring relatively precise cooling systems. Recent advancements in LED technology, driven by market demand, have improved LED performance and reduced costs, making them viable alternatives for laser pumping. This paper systematically compares diode-pumped and LEDpumped lasers, highlighting the advantages of LED in terms of price, stability, and volume. LiDAR technology for self-driving cars is a key application discussed, where LED-pumped lasers offer a safer, cost-effective solution!
While high-speed and large-capacity underwater acoustic communication has recently been improved, research and development of communication systems that can withstand low transmission rates and low signal-to-noise ratio environments has also been studied. We presented stretchable symbols with multiple sequences (SSMS) that is highly tolerant to harsh communication environments such as Doppler shift, terminal oscillation, and acoustic wave reflection. In this study, we present the performance evaluation of the SSMS system in terms of waveform data size and low probability of detection for various kinds of waveform patterns.
This paper presents a real-time Dynamic-Zone Active Noise Control (DZANC) system based on the modelmatching principle. Our goal is to suppress noise in multiple zones of a room. The proposed system is implemented using the Conv-TasNet to estimate the array filter coefficients for the desired zone. The residual noise power in the controlled zones is employed as the training loss function. In the training phase, the designated zone vector is concatenated with the primary noise signal as the network input. In addition, kernel ridge regression is used to interpolate the Acoustic Transfer Function (ATF) between adjacent measured control points to expand the effective control region with only a limited number of measurements. To validate the proposed multichannel DZANC system, simulations were performed using a six-loudspeaker linear array. The results demonstrated superior noise reduction in the controlled zone compared to several traditional digital signal processing (DSP)-based approaches. In addition, the proposed system effectively creates a quiet zone where the user is located by switching the filter coefficients learned by the Conv-TasNet.
With the development and application of internet and information communication technology, countries around the world have invested heavily in the space industry in recent years, with particular emphasis on the deployment of satellite communication systems. However, the complexity of satellite communication and the uncertainty of environmental changes often affect communication quality. In order to enhance the fault diagnosis and maintenance capabilities of technicians for satellite communication systems, this study applies fuzzy theory to fault diagnosis in satellite communication ground station. The research work introduces the basic architecture and equipment functions of satellite communication systems and combines the years of maintenance experience of experienced personnel to analyze possible types of faults and their impact on system performance. It proposes a fault diagnosis method based on fuzzy theory and establishes a database of possible fault causes. After maintenance or operation personnel input the quality parameters of satellite modem $\mathbf{E b} / \mathbf{N o}$ (energy per bit to noise power spectral density ratio) and RSL (Received Signal Level) into the system, fuzzy logic inference and data analysis comparison are used to quickly and accurately determine possible fault causes and improvement methods in satellite communication ground station. Finally, through simulation experiments and actual maintenance, the accuracy and reliability of this system are verified. Both maintenance and operation personnel can use this diagnostic method to clarify possible fault causes in satellite communication systems. New staff can quickly enter the independent working stage, thereby effectively improving the work efficiency of the entire maintenance team, reducing time costs, and ensuring the reliability and stability of satellite communication systems.
Heat diffusion over a graph extends the classical heat diffusion problem into the realm of graph theory, where a graph consists of nodes connected by edges. This concept is widely used in various fields, such as network theory, computer science, and data analysis, to model and study the spread of heat through complex networks. Understanding heat diffusion over a graph provides powerful insights into the dynamic processes occurring within networks, offering a robust framework for analyzing and solving complex problems across various domains. In this paper, the heat diffusion process is treated as a graph signal governed by a discrete heat equation. When a noisy graph signal of heat diffusion is measured, the challenge is to estimate the diffusion time from the noisy measurement signal. To tackle this issue, a steepest descent method is proposed to estimate the diffusion time by minimizing the error function between the model signal and the measured signal. The matrix exponential used to compute model signal is calculated by using polynomial graph filter method for reducing the computation complexity. Experiments conducted on complex networks in the USA, with single-point, double-point, and triple-point heat sources, demonstrate the effectiveness of the proposed method.
This study proposes an adaptive decision feedback channel estimation (DFCE) scheme for single-carrier with frequency domain equalization (SC-FDE) multiple-input multiple-output (MIMO). The feature of the proposed approach is to control the forgetting factor sensitive to channel variation by using the terminal speed and to detect the actual channel condition based on the decision output of coded SC-FDE MIMO. Moreover, considering that SC signals generally have a significant envelope variation in the frequency spectrum, only the subchannel signals with large magnitudes are utilized for DFCE, which leads to noise enhancement suppression. The effectiveness of the proposed scheme is demonstrated in comparison with the traditional channel estimation scheme without DFCE through computer simulations.
This paper reveals that there is a greedy characteristic in the pathfinding algorithm that finds the optimal route based on individual vehicles, and because of that characteristic, unexpected congestion can occur when several vehicles search for a route in their optimal way, resulting in a loss in the overall travel time. To solve this problem, we will modify the $\mathrm{A}^{*}$ algorithm, a well-known algorithm in pathfinding. The heuristic function of $\mathrm{A}^{*}$ is a function that determines the performance of the algorithm, and if information about other vehicles is included in this function, the greedy characteristic decreases. The resulting path may not be optimal for each vehicle. But overall, the path can be determined to mitigate congestion. Finally, we argue for an arbiter who collects information about other vehicles and assigns heuristics to each vehicle’s pathfinding algorithm.
With the proliferation and widespread deployment of cameras, image captioning for automatically and concisely generating natural language descriptions of image contents has attracted a lot of attentions. In this work, we propose a method for image captioning based on segmentation attention. The segmentation masks of the objects are from Mask R-CNN. The proposed segmentation attention performs the attention in object mask level and further encodes the spatial information. The makes the generated caption more accurate. The experiment exhibits that the proposed method can achieve the high BLUE scores in Flickr 8K dataset.
In this paper, we consider channel estimation for wideband millimeter-wave (mmWave) systems with non-ideal pulse shaping filters. The use of non-ideal pulse shaping filters complicates the channel estimation problem. In the literature, such a problem has been addressed using oversampling or on-grid methods. We show that gridless estimation can be achieved for a orthogonal frequency-division multiplexing (OFDM) system with non-ideal pulse shaping filters. By using an appropriately chosen subset of subcarriers of the OFDM system, the estimation of a wideband mmWave channel is converted to a harmonic retrieval problem, which can be solved efficiently using gridless algorithms. Simulations are given to show that the proposed method enjoys high estimation accuracy with low complexity.
