Volume 20,Issue 6,2024 Table of Contents
Kawther M Musthafa
,
Azura Hamzah
,
Ooi Wei Ling
,
Ahmad Haziq Aiman Rosol
,
Norliza Mohamed
,
Sulaiman Wadi Harun
2024, 20(6):321-329.
DOI: https://doi.org/10.1007/s11801-024-3102-9
Abstract:
MXenes, drawn from MAX phases, are special two-dimensional substances with numerous advantages in nonlinear optics, specifically in giant and ultrashort pulsed-laser applications. Ti3C2Tx and Ti2CTx nanosheets however rapidly deteriorate under ambient conditions, limiting their applications. This paper demonstrates how excellent modulation depth of one of the MAX phase compounds vanadium zinc carbide (V2ZnC) makes it a brilliant saturable absorber (SA) in passively Q-switched all-fiber pulsed lasers, integrated such that a 16.73-µm V2ZnC-polyvinyl alcohol (PVA) thin film acts as SA in the laser. Saturable and non-saturable absorptions were found to be 13.2% and 10.47%, while saturation optical intensity and modulation depth were 6.25 kW/cm2 and 12.43%, respectively, illustrating the optical nonlinearity. The superiority of MAX-PVA, fabricated in four distinct ratios, was demonstrated by the fact that it self-starts a giant pulsed laser at pump power as low as 22.5 mW and firmly accomplished 120.6 kHz repetition rate with a pulse width of 2.08 µs. It is a fine SA for the use of pulsed-laser production using all-fiber laser due to fabrication simplicity and great optical, thermophysical, and mechanical qualities.
2024, 20(6):330-338.
DOI: https://doi.org/10.1007/s11801-024-3117-2
Abstract:
This paper presents a review of the position-sensitive detector (PSD) sensor, covering different types of PSD and recent works related to this field. Furthermore, it explains the theoretical concepts and provides information about its structure and principles of operation. Moreover, it includes the main information about the available commercial PSDs from different companies, along with a comparison between the common modules. The PSD features include high position resolution, fast response, and a wide dynamic range. These features make it suitable for various fields and applications, such as imaging, spectrometry, spectroscopy and others.
This paper presents a review of the position-sensitive detector (PSD) sensor, covering different types of PSD and recent works related to this field. Furthermore, it explains the theoretical concepts and provides information about its structure and principles of operation. Moreover, it includes the main information about the available commercial PSDs from different companies, along with a comparison between the common modules. The PSD features include high position resolution, fast response, and a wide dynamic range. These features make it suitable for various fields and applications, such as imaging, spectrometry, spectroscopy and others.
2024, 20(6):339-345.
DOI: https://doi.org/10.1007/s11801-024-3143-0
Abstract:
Thin-film lithium niobate electro-optical modulator will become the key device in the future optical communication, which has the advantages of high modulation rate, low half-wave voltage, large bandwidth, and easy integration compared with conventional bulk lithium niobate modulator. However, because the electrode gap of the lithium niobate film modulator is very narrow, when the microwave frequency gets higher, it leads to higher microwave loss, and the electro-optical performance of the modulator will be greatly reduced. Here, we propose a thin film lithium niobate electro-optic modulator with a bimetallic layer electrode structure to achieve microwave loss less than 8 dB/cm in the range of 200 GHz, exhibiting a voltage-length product of 1.1 V∙cm and a 3 dB electro-optic bandwidth greater than 160 GHz. High-speed data transmission test has been performed, showing good performance.
Thin-film lithium niobate electro-optical modulator will become the key device in the future optical communication, which has the advantages of high modulation rate, low half-wave voltage, large bandwidth, and easy integration compared with conventional bulk lithium niobate modulator. However, because the electrode gap of the lithium niobate film modulator is very narrow, when the microwave frequency gets higher, it leads to higher microwave loss, and the electro-optical performance of the modulator will be greatly reduced. Here, we propose a thin film lithium niobate electro-optic modulator with a bimetallic layer electrode structure to achieve microwave loss less than 8 dB/cm in the range of 200 GHz, exhibiting a voltage-length product of 1.1 V∙cm and a 3 dB electro-optic bandwidth greater than 160 GHz. High-speed data transmission test has been performed, showing good performance.
2024, 20(6):346-352.
DOI: https://doi.org/10.1007/s11801-024-3157-7
Abstract:
In this paper, we have designed and simulated all-optical tristate Pauli X, Y and Z gates using 2D photonic crystal. Simple line and point defects have been used to design the structure. The performance of the structure has been analyzed and investigated by plane wave expansion (PWE) and finite difference time domain (FDTD) methods. Different performance parameters, namely contrast ratio (CR), rise time, fall time, delay time, response time and bit rate, have been calculated. The main advantage of the proposed design is that all the Pauli gates have been realized from a single structure. Due to compact size, fast response time, good CR and high bit rate, the proposed structure can be highly useful for optical computing, data processing and optical integrated circuits.
In this paper, we have designed and simulated all-optical tristate Pauli X, Y and Z gates using 2D photonic crystal. Simple line and point defects have been used to design the structure. The performance of the structure has been analyzed and investigated by plane wave expansion (PWE) and finite difference time domain (FDTD) methods. Different performance parameters, namely contrast ratio (CR), rise time, fall time, delay time, response time and bit rate, have been calculated. The main advantage of the proposed design is that all the Pauli gates have been realized from a single structure. Due to compact size, fast response time, good CR and high bit rate, the proposed structure can be highly useful for optical computing, data processing and optical integrated circuits.
2024, 20(6):353-359.
DOI: https://doi.org/10.1007/s11801-024-3112-7
Abstract:
High-precision methane gas detection is of great importance in industrial safety, energy production and environmental protection, etc. However, in the existing measurement techniques, the methane gas concentration information is susceptible to noise, which leads to its useful signal being drowned by noise. A fusion algorithm of variational modal decomposition (VMD) and improved wavelet threshold filtering is proposed, which is used in combination with tunable diode laser absorption spectroscopy (TDLAS) to implement a non-contact, high-resolution methane gas concentration detection. The fusion algorithm can perform noise reduction and further segmentation of the methane gas detection signal. And the simulation and experiment verify the effectiveness of the fusion algorithm, and the experimental results show that for the detection of air containing 10 ppm, 30 ppm, 60 ppm, 80 ppm, and 99 ppm methane, the errors are 12.75%, 8.18%, 3.37%, 2.46%, and 1.78%, respectively.
High-precision methane gas detection is of great importance in industrial safety, energy production and environmental protection, etc. However, in the existing measurement techniques, the methane gas concentration information is susceptible to noise, which leads to its useful signal being drowned by noise. A fusion algorithm of variational modal decomposition (VMD) and improved wavelet threshold filtering is proposed, which is used in combination with tunable diode laser absorption spectroscopy (TDLAS) to implement a non-contact, high-resolution methane gas concentration detection. The fusion algorithm can perform noise reduction and further segmentation of the methane gas detection signal. And the simulation and experiment verify the effectiveness of the fusion algorithm, and the experimental results show that for the detection of air containing 10 ppm, 30 ppm, 60 ppm, 80 ppm, and 99 ppm methane, the errors are 12.75%, 8.18%, 3.37%, 2.46%, and 1.78%, respectively.
2024, 20(6):360-366.
DOI: https://doi.org/10.1007/s11801-024-3120-7
Abstract:
Laser display technology is the most promising display technology in the market and is widely used in many fields. However, laser speckle has been troubling the application and expansion of this technology in some fields. In order to better evaluate the speckle, speckle measurement methods must be studied. In this study, a dynamic measurement method for laser speckles is proposed according to the optical superposition characteristics of speckle, which can reduce the influence of non-coherent factors on the speckle measurement results. The feasibility of the dynamic speckle measurement method is verified by designing an experimental scheme.
Laser display technology is the most promising display technology in the market and is widely used in many fields. However, laser speckle has been troubling the application and expansion of this technology in some fields. In order to better evaluate the speckle, speckle measurement methods must be studied. In this study, a dynamic measurement method for laser speckles is proposed according to the optical superposition characteristics of speckle, which can reduce the influence of non-coherent factors on the speckle measurement results. The feasibility of the dynamic speckle measurement method is verified by designing an experimental scheme.
2024, 20(6):367-371.
DOI: https://doi.org/10.1007/s11801-024-3170-x
Abstract:
Aiming at the problem of low surface defect detection accuracy of industrial products, an object detection method based on simplified spatial pyramid pooling fast (Sim SPPF) hybrid pooling improved you only look once version 5s (YOLOV5s) model is proposed. The algorithm introduces channel attention (CA) module, simplified SPPF feature vector pyramid and efficient intersection over union (EIOU) loss function. Feature vector pyramids fuse high-dimensional and low-dimensional features, which makes semantic information richer. The CA mechanism performs maximum pooling and average pooling operations on the feature map. Hybrid pooling comprehensively improves detection computing efficiency and accurate deployment ability. The results show that the improved YOLOV5s model is better than the original YOLOV5s model. The average test accuracy (mAP) can reach 91.8%, which can be increased by 17.4%, and the detection speed can reach 108 FPS, which can be increased by 18 FPS. The improved model is practicable, and the overall performance is better than other conventional models.
Aiming at the problem of low surface defect detection accuracy of industrial products, an object detection method based on simplified spatial pyramid pooling fast (Sim SPPF) hybrid pooling improved you only look once version 5s (YOLOV5s) model is proposed. The algorithm introduces channel attention (CA) module, simplified SPPF feature vector pyramid and efficient intersection over union (EIOU) loss function. Feature vector pyramids fuse high-dimensional and low-dimensional features, which makes semantic information richer. The CA mechanism performs maximum pooling and average pooling operations on the feature map. Hybrid pooling comprehensively improves detection computing efficiency and accurate deployment ability. The results show that the improved YOLOV5s model is better than the original YOLOV5s model. The average test accuracy (mAP) can reach 91.8%, which can be increased by 17.4%, and the detection speed can reach 108 FPS, which can be increased by 18 FPS. The improved model is practicable, and the overall performance is better than other conventional models.
2024, 20(6):372-378.
DOI: https://doi.org/10.1007/s11801-024-3177-3
Abstract:
Target detection is an important task in computer vision research, and such an anomaly detection and the topic of small target detection task is more concerned. However, there are still some problems in this kind of researches, such as small target detection in complex environments is susceptible to background interference and poor detection results. To solve these issues, this study proposes a method which introduces the attention mechanism into the you only look once (YOLO) network. In addition, the amateur-produced mask dataset was created and experiments were conducted. The results showed that the detection effect of the proposed mothed is much better.
Target detection is an important task in computer vision research, and such an anomaly detection and the topic of small target detection task is more concerned. However, there are still some problems in this kind of researches, such as small target detection in complex environments is susceptible to background interference and poor detection results. To solve these issues, this study proposes a method which introduces the attention mechanism into the you only look once (YOLO) network. In addition, the amateur-produced mask dataset was created and experiments were conducted. The results showed that the detection effect of the proposed mothed is much better.
2024, 20(6):379-384.
DOI: https://doi.org/10.1007/s11801-024-3207-1
Abstract:
Current mainstream unsupervised video object segmentation (UVOS) approaches typically incorporate optical flow as motion information to locate the primary objects in coherent video frames. However, they fuse appearance and motion information without evaluating the quality of the optical flow. When poor-quality optical flow is used for the interaction with the appearance information, it introduces significant noise and leads to a decline in overall performance. To alleviate this issue, we first employ a quality evaluation module (QEM) to evaluate the optical flow. Then, we select high-quality optical flow as motion cues to fuse with the appearance information, which can prevent poor-quality optical flow from diverting the network’s attention. Moreover, we design an appearance-guided fusion module (AGFM) to better integrate appearance and motion information. Extensive experiments on several widely utilized datasets, including DAVIS-16, FBMS-59, and YouTube-Objects, demonstrate that the proposed method outperforms existing methods.
Current mainstream unsupervised video object segmentation (UVOS) approaches typically incorporate optical flow as motion information to locate the primary objects in coherent video frames. However, they fuse appearance and motion information without evaluating the quality of the optical flow. When poor-quality optical flow is used for the interaction with the appearance information, it introduces significant noise and leads to a decline in overall performance. To alleviate this issue, we first employ a quality evaluation module (QEM) to evaluate the optical flow. Then, we select high-quality optical flow as motion cues to fuse with the appearance information, which can prevent poor-quality optical flow from diverting the network’s attention. Moreover, we design an appearance-guided fusion module (AGFM) to better integrate appearance and motion information. Extensive experiments on several widely utilized datasets, including DAVIS-16, FBMS-59, and YouTube-Objects, demonstrate that the proposed method outperforms existing methods.
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