Hasil untuk "Applied optics. Photonics"

O. Kwon, J. Yu

This study presents the development of a virtual museum utilizing 3D Gaussian Splatting (3DGS), a novel real-time rendering technique, and evaluates its experiential quality and effectiveness in comparison with a conventional 360-degree panoramic image (360° image)–based system. While 360° images offer advantages such as high visual clarity and ease of implementation, they are inherently limited in terms of user mobility and interaction, which restrict their immersive potential. In contrast, 3DGS enables robust scene reconstruction even in complex exhibition environments, supporting free navigation and interaction, and is therefore considered a promising approach for immersive virtual experiences. Two systems are implemented based on identical exhibition content, and a comprehensive user evaluation is conducted incorporating both quantitative and qualitative methods. The results, measured through the Igroup Presence Questionnaire (IPQ) and additional user perception metrics, indicate that the 3DGS-based system achieves statistically significant higher scores across all IPQ items. Furthermore, participants report greater satisfaction, intention to reuse, preference for widespread use, and motivation to visit. Despite minor limitations in image sharpness and text readability, users generally perceive the visual quality of the 3DGS system to be acceptable—sometimes even impressive—and show a clear preference for its interactive and participatory features. These findings suggest that, with further advancements in rendering quality and optimization, 3DGS holds strong potential as a viable alternative for future virtual museum implementations.

Kavalambramalil George Paulson, Hanna Terletska, Herbert F Fotso

We investigate how an external driving field can control the amount of extractable work from a quantum emitter, a two-level quantum system (TLS) interacting with a photonic environment. In this scenario, the TLS functions as a quantum battery, interacting with the photonic bath that discharges it while the control field recharges it. Ergotropy serves as our measure of the extractable work from the quantum system. We systematically analyze how the ergotropy of the system evolves as it interacts with the photonic bath under the control of either a continuous driving field or a periodic pulse sequence. The coherent and incoherent contributions to the total ergotropy for various initial states are calculated. The role of detuning between the driving field and the emission frequency of the TLS, as well as the initial state of the system in work extraction, are investigated for continuous and periodic pulse-driving fields. We show that detuning has little impact on work extraction for a system driven by a periodic sequence of instantaneous pulses. However, for a continuously driven system, as the system approaches its steady state, ergotropy increases with detuning increases.

Yuzhe Liu, Qingqing Chen, Yifan Liu et al.

We investigate long-term-stable ultra-compact single-stage few-cycle pulse self-compression through soliton dynamics in a 12-cm homemade nodeless antiresonant argon-filled hollow-core fiber. The direct output of 6.5-fs self-compressed pulses and 5.2-fs post-compressed pulses is achieved from a 180-fs ytterbium laser with high repetition rates of up to 200 kHz. By mitigating optical resonances (Fabry–Pérot resonances of glass walls and Fano resonances at contact nodes) and mechanical resonances (flexural vibrations), we observe stable plasma-assisted blueshifted spectral evolution as the input pulse energy increased, which aligns well with numerical modeling.

Jing Liu, Xuanran Peng, Yaru Kang et al.

Surface plasmonic cavities consisting of dielectric nanoparticle chains directly placed on a metal substrate are designed and studied, including a periodic nanoparticle chain (PNC) cavity and several different surface plasmon trap (SPT) cavities. The SPT cavities are designed by adjusting the nanoparticle sizes and the spacing between nanoparticles. Among them, the nanoparticle sizes range from 10 nm to 140 nm, and the spacings between the nanoparticles range from 200 nm to 280 nm. Compared to the PNC cavity, the SPT cavities support a single mode operation with higher Q factors within a relatively wide bandwidth. In particular, when the particle size and the spacing between the particles of the chain are set to vary in a parabolic gradient profile, the Q factor of the SPT cavity can be improved up to 85% compared to the PNC cavity. Our designs can be applied in the development of high-Q-factor plasmonic nanolasers.

F. Liu, F. Liu, Y. Ren et al.

The Dunhuang murals are a precious treasure of China's cultural heritage, yet they have long been affected by salt damage. Traditional methods for detecting salt content are costly, inefficient, and may cause physical harm to the murals. Among current techniques for measuring salt content in murals, hyperspectral remote sensing technology offers a non-invasive , circumventing issues of high costs, low efficiency. Building on this, our study developed a high-spectral feature inversion model for mural phosphate content using Fractional Order Differentiation (FOD), a novel three-band spectral index, and Partial Least Squares Regression (PLSR) algorithm. The specific research contents include: 1) Exploring the absorption mechanism of phosphates and their characteristic bands, combined with the optimal spectral index to construct a univariate linear regression model, providing a basis for rapid quantitative measurement of mural phosphate content. 2) By comparing the accuracy of the PSR and PNDI spectral indices based on the linear regression model, the first six orders of the highest accuracy spectral index were selected as the optimal three-band spectral index combination, used as explanatory variables, with mural plaster electrical conductivity as the response variable, employing the PLSR method to construct the mural phosphate content high-spectral feature inversion model. The study's findings include: 1) By comparing the outcomes of different orders of fractional differentiation, it was found that the model performance reached its optimum at a 0.3 order of differentiation for both PSR and PNDI data, with a determination coefficient (R²) of 0.728. 2) Utilizing PLSR, this study employed the previously determined optimal six-order three-band spectral index combination as explanatory variables, with salt content as the response variable, successfully constructing the high-spectral feature inversion model for mural phosphate content with a determination coefficient (R²) of 0.815. This provides an effective technical means for monitoring the salt damage conditions of precious cultural heritage such as murals.

MU Kuanlin, WU Yue, ZHOU Jian et al.

【Objective】Fiber Raman Amplifier (FRA) based on multi-pump technology has features of low noise, a wide gain bandwidth, and a controllable gain spectrum shape, which is regarded as an ideal optical relay amplifier for long-haul fiber optic transmission network systems. Intelligent optical amplifiers with adaptive controllable gain are required in dynamic fiber optic transmission network systems. This article introduces a gain control method for FRA based on neural network and numerical solutions of Raman power coupling equations.【Methods】First, the data set containing the signal gains, pump powers and wavelengths in the FRA is collected to train the neural network to establish an approximate mapping relationship between the signal gains and pump parameters. Subsequently, the trained neural network is utilized to determine the initial pump powers and wavelengths of the FRA based on the target gains of the signal. Finally, the pump powers are optimized by solving the numerical solutions of the Raman power coupling equations to improve the accuracy of the FRA output signal gains.【Results】The paper investigates the effect of the flatness of signal gains in each group in the training dataset on the accuracy of FRA output signal gains. When the gain fluctuation of each group signal in the training data is less than 2 dB, the mean and variance of the Root Mean Square Error (RMSE) of the 1 000 sets of test signal gains output by the FRA are 0.230 and 0.010 dB, respectively. Additionally, the mean and variance of the maximum error of the gains are 0.462 and 0.044 dB, respectively.【Conclusion】The results indicate that the proposed method can achieve high-precision FRA gain control, offering a new idea and method for investigating intelligent optical amplifier gain adaptive control in dynamic fiber optic transmission networks.

W. A. J. Van den Broeck, L. Terryn, W. Cherlet et al.

Terrestrial laser scanning (TLS) has emerged as a valuable technology for forest monitoring, providing detailed 3D measurements of vegetation structure. However, the semantic understanding of tropical tree point clouds, particularly the separation of woody and non-woody components, remains a challenge. Therefore, this paper addresses the gaps in both (1) data availability and (2) knowledge regarding the potential of 3D deep learning algorithms for leaf-wood segmentation of tropical tree point clouds. First, we contribute a new dataset consisting of 148 tropical tree point clouds with manual leaf-wood annotations. Second, we present initial results using the RandLA-Net 3D deep learning architecture to establish a benchmark on our dataset, achieving a mean intersection over union (mIoU) of 86.8% and overall accuracy of 94.8%. Visual inspection of predictions reveals areas of confusion and indicates applicability across different forest types. Our study demonstrates the potential of 3D deep learning for leaf-wood segmentation in tropical tree point clouds and highlights avenues for future research, including exploring different architectures and investigating the influence of prediction errors on volumetric tree reconstruction.

Kaoru Asaba, Tomoyuki Miyamoto

In the original publication [...]

D. Codato, C. Tha, S. E. Pappalardo et al.

<p>The last two decades have seen the development and diffusion of new technologies that can help in managing geographic information. This has led to a proliferation of grassroots processes for exploring, creating and sharing geographical data as a way for citizens to take part in decision making in different kinds of processes.</p><p>However, these ongoing processes are facing technological, cognitive and economic barriers. Universities with the use of open-source geospatial information and communication technologies (Geo-ICTs) should be the primary actors in supporting students and citizens in developing their own spatial thinking and abilities in a more effective and engaging way.</p><p>In this framework, the Jean Monnet Centre of Excellence on Climate Justice (University of Padova) is developing the massive open online course (MOOC) ‘GIScience for Climate Justice’, here with the use of open-source and freeware Geo-ICTs that will be freely available for all before the end of 2022.</p><p>By completing the MOOC, students will learn how to increase their knowledge of climate change and climate justice issues autonomously. Practical activities will improve their skills in obtaining and using geodata and information produced by European institutions, which can lead to them producing and sharing their own data and preparing and managing collaborative projects for sustainability and environmental monitoring.</p><p>In this contribution, the theoretical background and entire methodology for the preparation and dissemination of the MOOC are presented and discussed, with the aim of disseminating and sharing this experience to actors interested in developing similar activities of using Geo-ICTs for good.</p>

B. Riedler, N. Stéphenne, E. Aguilar-Moreno et al.

Gender inequality is omnipresent in our society and in the field of education and training, the gender gap is especially evident in STEM (Science, Technology, Engineering and Mathematics) disciplines. While different studies have been conducted about potential reasons explaining this gap, little is known about gender inequality and underlying factors in the Earth Observation and Geoinformatics (EO*GI) domain. To close some parts of this knowledge gap, the initiative Women in Copernicus was established with the overall goal to make women working in the EO*GI field and especially in the Copernicus ecosystem more visible. This paper analyses the results of a survey of 462 women identifying reasons for not choosing STEM education and the barriers related to educational choices in their career path. The main obstacles that hinder choosing a STEM education for these women are stereotypes in society, missing female role models but also culture, television and society message transmitted by the media. The lack of self-confidence is an essential factor in this choice and is also experienced as a barrier during individual career paths. This analysis provides insights valuable for political decisions making targeting at a gender-balanced work environment and emphasizes the importance of attracting more girls and young women towards a STEM education and supporting them during their career to reach skills and occupational equality and strengthen the economic development of the EO*GI sector.

Peijun Tang, Ruikang K. Wang

An OCM system that employs a 1700 nm broadband laser source enables cellular level deep brain imaging, providing cytoarchitectural and myeloarchitectural information across cortical depth, without requiring tissue slicing. CC – corpus callosum.

Zoltán Balogh-Michels, Igor Stevanovic, Aurelio Borzi et al.

Abstract In this work, we present our results about the thermal crystallization of ion beam sputtered hafnia on 0001 SiO2 substrates and its effect on the laser-induced damage threshold (LIDT). The crystallization process was studied using in-situ X-ray diffractometry. We determined an activation energy for crystallization of 2.6 ± 0.5 eV. It was found that the growth of the crystallites follows a two-dimensional growth mode. This, in combination with the high activation energy, leads to an apparent layer thickness-dependent crystallization temperature. LIDT measurements @355 nm on thermally treated 3 quarter-wave thick hafnia layers show a decrement of the 0% LIDT for 1 h @773 K treatment. Thermal treatment for 5 h leads to a significant increment of the LIDT values.

Huangxuan Zhao, Ke Li, Ningbo Chen et al.

Optical-resolution photoacoustic microscopy (OR-PAM) is used for <italic>in vivo</italic> imaging of a variety of albino and pigmented eyes taking advantages of requiring no exogenous dye, performing high-resolution imaging, and achieving morphologic and functional imaging at the same time. However, to accurately diagnose the ophthalmic disease in the OR-PAM images, vascular enhancement algorithms are necessary for extracting vessels and quantifying them correctly. Vascular enhancement algorithms developed for other imaging technologies, are not suitable to be used for OR-PAM, because of the underlying differences in the physics of the formation of images. In this study, a new vascular enhancement algorithm called photoacoustic imaging vasculature enhancement filter (PAIVEF) is proposed, which not only enhances vasculature including micro-vessels signals, suppresses noise signals effectively, but also achieves highly sensitive and accurate enhancement of the vasculature within a large depth range in and out of the system&#x0027;s depth of focus (DOF). Using the PAIVEF, the morphologic and functional 3D images of the whole rat&#x0027;s ocular anterior vasculature segment was displayed simultaneously for a depth range of &#x223C;0.6 mm, which was &#x223C;7 times of the system&#x0027;s DOF. This study paves the way for the application of OR-PAM technology in ophthalmic disease research.

Z. Li, Y. Zhang, J. Hong

Atmospheric particulate pollutants not only reduce atmospheric visibility, change the energy balance of the troposphere, but also affect human and vegetation health. For monitoring the particulate pollutants, we establish and develop a series of inversion algorithms based on polarimetric remote sensing technology which has unique advantages in dealing with atmospheric particulates. A solution is pointed out to estimate the near surface PM_2.5 mass concentrations from full remote sensing measurements including polarimetric, active and infrared remote sensing technologies. It is found that the mean relative error of PM_2.5 retrieved by full remote sensing measurements is 35.5&thinsp;% in the case of October 5th 2013, improved to a certain degree compared to previous studies. A systematic comparison with the ground-based observations further indicates the effectiveness of the inversion algorithm and reliability of results. A new generation of polarized sensors (DPC and PCF), whose observation can support these algorithms, will be onboard GF series satellites and launched by China in the near future.

C. Zhang, X. Pan, S. Q. Zhang et al.

Recent advances in remote sensing have witnessed a great amount of very high resolution (VHR) images acquired at sub-metre spatial resolution. These VHR remotely sensed data has post enormous challenges in processing, analysing and classifying them effectively due to the high spatial complexity and heterogeneity. Although many computer-aid classification methods that based on machine learning approaches have been developed over the past decades, most of them are developed toward pixel level spectral differentiation, e.g. Multi-Layer Perceptron (MLP), which are unable to exploit abundant spatial details within VHR images. <br><br> This paper introduced a rough set model as a general framework to objectively characterize the uncertainty in CNN classification results, and further partition them into correctness and incorrectness on the map. The correct classification regions of CNN were trusted and maintained, whereas the misclassification areas were reclassified using a decision tree with both CNN and MLP. The effectiveness of the proposed rough set decision tree based MLP-CNN was tested using an urban area at Bournemouth, United Kingdom. The MLP-CNN, well capturing the complementarity between CNN and MLP through the rough set based decision tree, achieved the best classification performance both visually and numerically. Therefore, this research paves the way to achieve fully automatic and effective VHR image classification.

Abbas Khanmohammadi, Reinhard Enne, Michael Hofbauer et al.

In this paper, a nondeterministic random number generator based on detection of the single photons emitted by an Si-CMOS-LED light source integrated for the first time on the detector chip is presented and experimentally demonstrated. We use a ring-shaped single-photon avalanche diode (SPAD) around the Si-CMOS-LED fabricated in 0.35-&#x03BC;m HV-CMOS technology to generate random events. The time intervals between single-photon events are independent quantum random variables. A field-programmable gate array (FPGA) digitizes the time variables to the stream of random bits. Bias in the raw data due to the nonuniform distribution of the time intervals is removed by postprocessing in a special configuration of xor gates to improve the randomness of the generated random bits. The quantum random numbers in 1-Gb streams with bit generation rate of 1 Mb/s were directly delivered to a personal computer (PC) and passed all statistical tests from ENT, STS, and DIEHARD, as well as for more accuracy correlation and bias tests applied on these streams.

C. H. Wang

In recent years the cultural landscape has become an important issue for cultural heritages throughout the world. It represents the "combined works of nature and of man" designated in Article 1 of the World Heritage Convention. When a landscape has a cultural heritage value, important features should be marked and mapped through the delimitation of a conservation area, which may be essential for further conservation work. However, a cultural landscape’s spatial area is usually wider than the ordinary architectural type of cultural heritage, since various elements and impact factors, forming the cultural landscape’s character, lie within a wide geographic area. It is argued that the conservation of a cultural landscape may be influenced by the delimitation of the conservation area, the corresponding land management measures, the limits and encouragements. <br><br> The Jianan Irrigation System, an historical cultural landscape in southern Taiwan, was registered as a living cultural heritage site in 2009. However, the system’s conservation should not be limited to just only the reservoir or canals, but expanded to irrigated areas where farmland may be the most relevant. Through the analysis process, only approximately 42,000 hectares was defined as a conservation area, but closely related to agricultural plantations and irrigated by the system. This is only half of the 1977 irrigated area due to urban sprawl and continuous industrial expansion.

D. M. H. Leung, B. M. A. Rahman, K. T. V. Grattan

In this paper, an ultracompact design of a low-loss silicon (Si) polarization rotator based on a silicon-on-insulator platform, which contains an asymmetric strip Si nanowire waveguide core, is presented. A full-vectorial finite element method and the least squares boundary residual method are used to study the effects of the device parameters, the results of which indicate that a very high polarization conversion with a very low polarization crosstalk is possible.

杨国民, 王宝太

介绍了６２２．０８Ｍｂｉｔ／ｓＳＤＨ设备连续相同数字（ＣＩＤ：ｃｏｎｓｅｃｕｔｉｖｅｉｄｅｎｔｉｃａｌｄｉｇｉｔ）不敏感性测量仪的原理及研制情况，对高速伪随机码的产生方法、相位以及同步方法进行了探讨，给出了电路模拟和实验的结果

徐永明, 张晓频

对ＳＤＨ体系中的２．０４８Ｍｂｉｔ／ｓ支路信号异步映射进ＶＣ－１２的具体过程进行了分析。主要进行了正／零／负码速调整的参数设计，包括通过读写时差的变化来确定缓冲存储容量和上、下门限；并给出了码速调整，以及Ｃ－１２映射入ＶＣ－１２形成５００μｓＶＣ－１２复帧的电路原理框图