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Journal articles on the topic 'Reconstruction intelligente'
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1
Epskamp-Dudink, Chantal, and Jan Martin Winter. "Benefits of scenario reconstruction in cold case investigations." Journal of Criminal Psychology 10, no. 2 (April 1, 2020): 65–78. http://dx.doi.org/10.1108/jcp-09-2019-0035.
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Purpose The purpose of this paper is to propose a methodological approach to increase the clearance rate of cold cases in The Netherlands and to contribute to the development of intelligence-driven criminal investigations in general police practice and within cold case investigations in particular. Design/methodology/approach This proposal is based on practical investigative experience and academic knowledge. Findings Reconstructing scenarios helps convert cold case information into intelligence, which is beneficial to law enforcement agencies in terms of time, resources and prioritising cold cases. Intelligence contributes to the formulation of more effective queries and to a more efficient adaptation of new and existing investigation methods, leading to a higher cold case clearance rate. Moreover, scenario reconstruction creates a link between intelligence and investigation, i.e. between science and practice, which adds to the further development of intelligence-driven investigations. Practical implications When carrying out scenario reconstructions, practical implications are expected, as intelligence products are currently not or barely used in practice and science is not yet embedded in the investigational practice. Originality/value To move from scenario reconstruction to intelligence-driven criminal investigation, the gap between science and the investigational practice needs to be bridged by persons familiar with both. This study hopes to provide the necessary and relevant impetus to this dialogue.
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Condorelli, Francesca, and Maurizio Perticarini. "Comparative Evaluation of NeRF Algorithms on Single Image Dataset for 3D Reconstruction." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-2-2024 (June 11, 2024): 73–79. http://dx.doi.org/10.5194/isprs-archives-xlviii-2-2024-73-2024.
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Abstract. The reconstruction of three-dimensional scenes from a single image represents a significant challenge in computer vision, particularly in the context of cultural heritage digitisation, where datasets may be limited or of poor quality. This paper addresses this challenge by conducting a study of the latest and most advanced algorithms for single-image 3D reconstruction, with a focus on applications in cultural heritage conservation. Exploiting different single-image datasets, the research evaluates the strengths and limitations of various artificial intelligence-based algorithms, in particular Neural Radiance Fields (NeRF), in reconstructing detailed 3D models from limited visual data. The study includes experiments on scenarios such as inaccessible or non-existent heritage sites, where traditional photogrammetric methods fail. The results demonstrate the effectiveness of NeRF-based approaches in producing accurate, high-resolution reconstructions suitable for visualisation and metric analysis. The results contribute to advancing the understanding of NeRF-based approaches in handling single-image inputs and offer insights for real-world applications such as object location and immersive content generation.
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Wu, Yi-Chang, Pei-Shan Chiang, Yao-Cheng Liu, and Ru-Yi Huang. "Use of artificial intelligence in banknote reconstruction." IAES International Journal of Robotics and Automation (IJRA) 13, no. 4 (December 1, 2024): 410. http://dx.doi.org/10.11591/ijra.v13i4.pp410-422.
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Banknotes may be damaged during various events, such as floods, fires, insect infestations, and mechanical or manual shredding. Disaster victims might need to perform banknote reconstruction when applying for currency exchange, or investigative agencies might need to conduct such reconstruction during evidence collection. When the number of banknote fragments is small, they can be manually assembled; however, when this number is large, manual assembly becomes increasingly difficult and time-consuming. Therefore, an automated and effective method is required for banknote reconstruction. The process of banknote reconstruction can be considered similar to solving a large-scale jigsaw puzzle. This study employed an artificial intelligence (AI) system to reconstruct damaged banknotes. A robotic arm was used to replace manual separation and automated digital image processing techniques, and AI image registration technology, deep learning, and logical operations were utilized. A deep convolutional neural network was used to estimate the relative homography between images, and fragmented banknotes were mapped to a reference banknote for image transformation, thereby reconstructing the damaged banknotes. Additionally, a repetitive matching method was established to optimize the matching results to achieve the best possible mapping and enhance validation efficiency.
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Báskay, János, Dorottya Pénzes, Endre Kontsek, Adrián Pesti, András Kiss, Bruna Katherine Guimarães Carvalho, Miklós Szócska, et al. "Are Artificial Intelligence-Assisted Three-Dimensional Histological Reconstructions Reliable for the Assessment of Trabecular Microarchitecture?" Journal of Clinical Medicine 13, no. 4 (February 15, 2024): 1106. http://dx.doi.org/10.3390/jcm13041106.
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This study aimed to create a three-dimensional histological reconstruction through the AI-assisted classification of tissues and the alignment of serial sections. The secondary aim was to evaluate if the novel technique for histological reconstruction accurately replicated the trabecular microarchitecture of bone. This was performed by conducting micromorphometric measurements on the reconstruction and comparing the results obtained with those of microCT reconstructions. A bone biopsy sample was harvested upon re-entry following sinus floor augmentation. Following microCT scanning and histological processing, a modified version of the U-Net architecture was trained to categorize tissues on the sections. Detector-free local feature matching with transformers was used to create the histological reconstruction. The micromorphometric parameters were calculated using Bruker’s CTAn software (version 1.18.8.0, Bruker, Kontich, Belgium) for both histological and microCT datasets. Correlation coefficients calculated between the micromorphometric parameters measured on the microCT and histological reconstruction suggest a strong linear relationship between the two with ⍴-values of 0.777, 0.717, 0.705, 0.666, and 0.687 for BV/TV, BS/TV, Tb.Pf Tb.Th, and Tb.Sp, respectively. Bland–Altman and mountain plots suggest good agreement between BV/TV measurements on the two reconstruction methods. This novel method for three-dimensional histological reconstruction provides researchers with a tool that enables the assessment of accurate trabecular microarchitecture and histological information simultaneously.
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Okano, Teruo. "Thermo-Intelligent Surfaces for Cell Culture." Advances in Science and Technology 53 (October 2006): 70–73. http://dx.doi.org/10.4028/www.scientific.net/ast.53.70.
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In order to avoid several complications resulted from biodegradable scaffolds or single cell injection, we have developed “cell sheet engineering”. Our concept is novel tissue reconstruction not from single cells but from cell sheets. In order to prepare cell sheets, temperature-responsive culture dishes are utilized. Since temperature-responsive polymers are covalently grafted on the dishes, various types of cells adhere and proliferate on them at 37°C, but are spontaneously detached only by reducing temperature below 32°C without any need for proteolytic enzyme. All the confluent cells are noninvasively harvested as a single contiguous cell sheets with intact cell-cell junctions and deposited extracellular matrix. We have utilized these harvested cell sheets for various tissue reconstructions including ocular surfaces, periodontal ligament, cardiac patches as well as bladder.
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LI, WEI, NINGCHUAN SHEN, and JU WANG. "R-CALCULUS: A LOGICAL APPROACH FOR KNOWLEDGE BASE MAINTENANCE." International Journal on Artificial Intelligence Tools 04, no. 01n02 (June 1995): 177–200. http://dx.doi.org/10.1142/s0218213095000103.
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The concepts of maintenance sequences of a knowledge base and their limits are introduced. Some concepts used in maintenance of knowledge bases, such as new laws, user’s rejections, and reconstructions of a base are defined; the related theorems are proved. A maintenance procedure scheme is defined. The maintenance sequences generated by the procedure are convergent, and their limits are the set of true sentences of the model. Some computational aspects of reconstructions are studied; an R-calculus is given to deduce a reconstruction when a knowledge base meets a rejection. Especially, an R-calculus for logic programming is provided and implemented in Prolog. Finally, our research is compared with AGM’s theory of belief revision and other relevant work.
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De Francesco, Francesco, Nicola Zingaretti, Pier Camillo Parodi, and Michele Riccio. "The Evolution of Current Concept of the Reconstructive Ladder in Plastic Surgery: The Emerging Role of Translational Medicine." Cells 12, no. 21 (November 3, 2023): 2567. http://dx.doi.org/10.3390/cells12212567.
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Plastic surgeons have used the reconstructive ladder for many decades as a standard directory for complex trauma reconstruction with the goal of repairing body structures and restoring functionality. This consists of different surgical maneuvers, such as secondary intention and direct tissue closure, as well as more complex methods such as local tissue transfer and free flap. The reconstructive ladder represents widely known options achievable for tissue reconstruction and wound closure that puts at the bottom rung the simplest methods of reconstruction and strengthens the complexity by moving upward. Regenerative medicine and surgery constitute a quickly spreading area of translational research that can be employed by minimally invasive surgical strategies, with the aim of regenerating cells and tissues in vivo in order to reestablish normal function through the intrinsic potential of cells, in combination with biomaterials and appropriate biochemical stimuli. These translational procedures have the aim of creating an appropriate microenvironment capable of supporting the physiological cellular function to generate the desired cells or tissues and to generate parenchymal, stromal, and vascular components on demand, and above all to produce intelligent materials capable of determining the fate of cells. Smart technologies have been grown that give extra “rungs” on the classic reconstructive ladder to integrate a more holistic, patient-based approach with improved outcomes. This commentary presents the evolution of the traditional concept of the reconstructive ladder in the field of plastic surgery into a new course with the aim of achieving excellent results for soft tissue reconstruction by applying innovative technologies and biologically active molecules for a wide range of surgical diseases.
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Salomon, Gavriel. "AI in Reverse: Computer Tools That Turn Cognitive." Journal of Educational Computing Research 4, no. 2 (May 1988): 123–39. http://dx.doi.org/10.2190/4lu7-vw23-egb1-aw5g.
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This article posits artificial intelligence (AI), as applied in instruction, is a more efficient means to old ends and that newer ends can be thought of. In particular, it is argued on the basis of some past research and on the basis of a Vygotskian view, that intelligent computer tools can not only simulate human cognition but, given specific conditions, humans can simulate computer's intelligence. That is, learners can internalize computers' intelligent tools and use them as cognitive ones. Internalization is discussed in terms of cognitive reconstruction of cultural artifacts of particular characteristics — tool-like nature, relative novelty of function, compatibility with learners' schemata, and most importantly — explicitness of operation. The article also discusses learning conditions that might facilitate the process of tool internalization, particularly “high road” learning whereby learners are intentionally mindful of a tool's mode of operation and logic. A preliminary study is briefly described showing that children are capable of internalizing the metacognitive guidance provided by a semi-intelligent Reading Aid and that they show evidence of internalizing the tool's “intelligence” thereby manifesting improved reading comprehension as well as improved essay writing. Four fundamental questions are raised for future research as well as questions of ethics.
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Pu, Jane J., Samer G. Hakim, James C. Melville, and Yu-Xiong Su. "Current Trends in the Reconstruction and Rehabilitation of Jaw following Ablative Surgery." Cancers 14, no. 14 (July 7, 2022): 3308. http://dx.doi.org/10.3390/cancers14143308.
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The reconstruction and rehabilitation of jaws following ablative surgery have been transformed in recent years by the development of computer-assisted surgery and virtual surgical planning. In this narrative literature review, we aim to discuss the current state-of-the-art jaw reconstruction, and to preview the potential future developments. The application of patient-specific implants and the “jaw-in-a-day technique” have made the fast restoration of jaws’ function and aesthetics possible. The improved efficiency of primary reconstructive surgery allows for the rehabilitation of neurosensory function following ablative surgery. Currently, a great deal of research has been conducted on augmented/mixed reality, artificial intelligence, virtual surgical planning for soft tissue reconstruction, and the rehabilitation of the stomatognathic system. This will lead to an even more exciting future for the functional reconstruction and rehabilitation of the jaw following ablative surgery.
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Sun, Bing, Xiao Jin Zhu, Xiao Ping Qiao, Lina Jiang, and Jin Cong Yi. "Analysis and Design of a FBG Intelligent Flexible Structure Based on Orthogonal Curvatures." Applied Mechanics and Materials 39 (November 2010): 67–72. http://dx.doi.org/10.4028/www.scientific.net/amm.39.67.
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With the research model of intelligent flexible structure by Fiber Bragg Grating (FBG) sensor, the dissertation deals with a design and manufacture methodology for FBG sensor array based on orthogonal curvatures, and offers the experiential analysis and validation. On basis of brief introduction to the principle of FBG sensor to detect curvatures and methodology of structural morphological reconstruction, detailed description of design solutions and manufacture processes have yielded based on orthogonal distributed FBG sensor array which includes some technological parts as the configuration of orthogonal distributed FBG sensor array, the technology of perception range-proportion and orthogonally contrapuntal-pasting, the method of casing and encapsulation, calibration for model structure and so on. Fitting and reconstructing of the model structure and validation of visualization is split up based on intelligent flexible model structure we make and experimental platform we develop. Thus, the result of the experiment adequately shows the FBG intelligent flexible structure designed and produced in the dissertation gives a splendid on fitting and reconstruction, in which the feasibility and validity of the design methodology and key technology has been proved deeply.
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Cai Xinyue, 蔡心悦, 周杨 Zhou Yang, 胡校飞 Hu Xiaofei, 吕亮 Liang Lü, 赵璐颖 Zhao Luying, and 彭杨钊 Peng Yangzhao. "基于超分辨率重建的小目标智能检测算法." Laser & Optoelectronics Progress 60, no. 12 (2023): 1210002. http://dx.doi.org/10.3788/lop220882.
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Wang, Zhenzhou, Xu Zhang, Pingping Yu, Wenjie Duan, Dongjie Zhu, and Ning Cao. "A New Face Recognition Method for Intelligent Security." Applied Sciences 10, no. 3 (January 25, 2020): 852. http://dx.doi.org/10.3390/app10030852.
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With the advent of the era of artificial intelligence and big data, intelligent security robots not only improve the efficiency of the traditional intelligent security industry but also propose higher requirements for intelligent security. Aiming to solve the problem of long recognition time and high equipment cost of intelligent security robots, we propose a new face recognition method for intelligent security in this paper. We use the Goldstein branching method for phase unwrapping, which can improve the three-dimensional (3D) face reconstruction effect. Subsequently, by using the three-dimensional face recognition method based on face radial curve elastic matching, different weights are assigned to different curve recognition similarity for weighted fusion as the total similarity for recognition. Experiments show that the method has a higher face recognition rate and is robust to attitude, illumination, and noise.
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Niu, Xiaomei. "Interactive 3D reconstruction method of fuzzy static images in social media." Journal of Intelligent Systems 31, no. 1 (January 1, 2022): 806–16. http://dx.doi.org/10.1515/jisys-2022-0049.
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Abstract Because the traditional social media fuzzy static image interactive three-dimensional (3D) reconstruction method has the problem of poor reconstruction completeness and long reconstruction time, the social media fuzzy static image interactive 3D reconstruction method is proposed. For preprocessing the fuzzy static image of social media, the Harris corner detection method is used to extract the feature points of the preprocessed fuzzy static image of social media. According to the extraction results, the parameter estimation algorithm of contrast divergence is used to learn the restricted Boltzmann machine (RBM) network model, and the RBM network model is divided into input, output, and hidden layers. By combining the RBM-based joint dictionary learning method and a sparse representation model, an interactive 3D reconstruction of fuzzy static images in social media is achieved. Experimental results based on the CAD software show that the proposed method has a reconstruction completeness of above 95% and the reconstruction time is less than 15 s, improving the completeness and efficiency of the reconstruction, effectively reconstructing the fuzzy static images in social media, and increasing the sense of reality of social media images.
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Wu, Jia, Jian Li, and Qi Ren. "Application of artificial intelligence image recognition technology based on Faster-R CNN in automatic inspection of power transmission and transformation." Journal of Physics: Conference Series 2306, no. 1 (November 1, 2022): 012006. http://dx.doi.org/10.1088/1742-6596/2306/1/012006.
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Abstract In order to effectively improve the work efficiency and real-time performance of an automatic inspection of power transmission and transformation, this paper studies the automatic inspection method of power transmission and transformation based on artificial intelligence image recognition technology. First, we use cameras and unmanned aerial vehicles (UAVs) to obtain image data for power transmission and transformation inspection. Second, through the artificial sample calibration and reconstruction technology, the power transmission, and transformation inspection sample database is constructed. Then, the model is trained using the Faster-R CNN algorithm based on regional relationship features. Finally, the model is further optimized through model release and evaluation to realize intelligent diagnosis in power transmission and transformation detection. This research raises the recognition accuracy of power transmission and transformation inspection, improves the intelligence and efficiency of inspection, and provides good technical support for the construction of intelligent operation inspection.
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Qin, Pinpin, Xing Li, Shenglin Bin, Fumao Wu, and Yanzhi Pang. "Research on transformer and long short-term memory neural network car-following model considering data loss." Mathematical Biosciences and Engineering 20, no. 11 (2023): 19617–35. http://dx.doi.org/10.3934/mbe.2023869.
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<abstract> <p>There is limited research on the loss and reconstruction of car-following features. To delve into car-following's characteristics, we propose a car-following model based on LSTM-Transformer. By fully leveraging the advantages of long short-term memory (LSTM) and transformer models, this study focuses on reconstructing the input car-following features. Training and testing were conducted using 700 car-following segments extracted from a natural driving dataset and the Next Generation Simulation (NGSIM) dataset, and the proposed model was compared with an LSTM model and an intelligent driver model. The results demonstrate that the model performs exceptionally well in feature reconstruction. Moreover, compared to the other two models, it effectively captures the car-following features and accurately predicts the position and speed of the following car when features are lost. Additionally, the LSTM-Transformer model accurately reproduces traffic phenomena, such as asymmetric driving behavior, traffic oscillations and lag, by reconstructing the lost features. Therefore, the LSTM-Transformer car-following model proposed in this study exhibits advantages in feature reconstruction and reproducing traffic phenomena compared to other models.</p> </abstract>
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Wu, Si. "Artificial Intelligence Application, Global Value Chain Reconstruction and Enterprise Knowledge Power Relationship: Grounded Theory Research Based on Intelligent Manufacturing Enterprises." SHS Web of Conferences 181 (2024): 04029. http://dx.doi.org/10.1051/shsconf/202418104029.
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In the process of application of artificial intelligence affecting the formation of enterprise knowledge power, there are many factors that can influence it. However, there is no mature theoretical framework for the specific important influencing factors. The TongKun Group in Zhejiang province is a “future intelligence factory” that uses artificial intelligence and other advanced technologies to realize the global value chain reconstruction and enterprise knowledge power. Based on the grounded theory. The research data are collected from Tongkun company. According to the research process of grounded theory, original interview data are tested for open coding, spindle coding, selective coding and theoretical saturation. Using coding, categories are summarized into five main categories: enterprise artificial intelligence technology foundation, enterprise artificial intelligence technology usage, enterprise artificial intelligence technology results (output), global value chain reconstruction, and enterprise knowledge power. Finally, according to the “storyline”, it is established that a relationship model about “artificial intelligence application, global value chain reconstruction and knowledge power” in enterprise.
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Hong, Sen-Yuan, and Bao-Long Qin. "Recent Advances in Robotic Surgery for Urologic Tumors." Medicina 60, no. 10 (September 25, 2024): 1573. http://dx.doi.org/10.3390/medicina60101573.
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This review discusses recent advances in robotic surgery for urologic tumors, focusing on three key areas: robotic systems, assistive technologies, and artificial intelligence. The Da Vinci SP system has enhanced the minimally invasive nature of robotic surgeries, while the Senhance system offers advantages such as tactile feedback and eye-tracking capabilities. Technologies like 3D reconstruction combined with augmented reality and fluorescence imaging aid surgeons in precisely identifying the anatomical relationships between tumors and surrounding structures, improving surgical efficiency and outcomes. Additionally, the development of artificial intelligence lays the groundwork for automated robotics. As these technologies continue to evolve, we are entering an era of minimally invasive, precise, and intelligent robotic surgery.
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Enßlin, Torsten. "Information Field Theory and Artificial Intelligence." Entropy 24, no. 3 (March 7, 2022): 374. http://dx.doi.org/10.3390/e24030374.
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Information field theory (IFT), the information theory for fields, is a mathematical framework for signal reconstruction and non-parametric inverse problems. Artificial intelligence (AI) and machine learning (ML) aim at generating intelligent systems, including such for perception, cognition, and learning. This overlaps with IFT, which is designed to address perception, reasoning, and inference tasks. Here, the relation between concepts and tools in IFT and those in AI and ML research are discussed. In the context of IFT, fields denote physical quantities that change continuously as a function of space (and time) and information theory refers to Bayesian probabilistic logic equipped with the associated entropic information measures. Reconstructing a signal with IFT is a computational problem similar to training a generative neural network (GNN) in ML. In this paper, the process of inference in IFT is reformulated in terms of GNN training. In contrast to classical neural networks, IFT based GNNs can operate without pre-training thanks to incorporating expert knowledge into their architecture. Furthermore, the cross-fertilization of variational inference methods used in IFT and ML are discussed. These discussions suggest that IFT is well suited to address many problems in AI and ML research and application.
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Xu, Xiangyang, and Hao Yang. "Robust model reconstruction for intelligent health monitoring of tunnel structures." International Journal of Advanced Robotic Systems 17, no. 2 (March 1, 2020): 172988142091083. http://dx.doi.org/10.1177/1729881420910836.
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Advanced robotic systems will encounter a rapid breakthrough opportunity and become increasingly important, especially with the aid of the accelerated development of artificial intelligence technology. Nowadays, advanced robotic systems are widely used in various fields. However, the development of artificial intelligence-based robot systems for structural health monitoring of tunnels needs to be further investigated, especially for data modeling and intelligent processing for noises. This research focuses on integrated B-spline approximation with a nonparametric rank method and reveals its advantages of high efficiency and noise resistance for the automatic health monitoring of tunnel structures. Furthermore, the root-mean-square error and time consumption of the rank-based and Huber’s M-estimator methods are compared based on various profiles. The results imply that the rank-based method to model point cloud data has a comparative advantage in the monitoring of tunnel, as well as the large-area structures, which requires high degrees of efficiency and robustness.
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Peng, Jiansheng, Kui Fu, Qingjin Wei, Yong Qin, and Qiwen He. "Improved Multiview Decomposition for Single-Image High-Resolution 3D Object Reconstruction." Wireless Communications and Mobile Computing 2020 (December 26, 2020): 1–14. http://dx.doi.org/10.1155/2020/8871082.
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As a representative technology of artificial intelligence, 3D reconstruction based on deep learning can be integrated into the edge computing framework to form an intelligent edge and then realize the intelligent processing of the edge. Recently, high-resolution representation of 3D objects using multiview decomposition (MVD) architecture is a fast reconstruction method for generating objects with realistic details from a single RGB image. The results of high-resolution 3D object reconstruction are related to two aspects. On the one hand, a low-resolution reconstruction network represents a good 3D object from a single RGB image. On the other hand, a high-resolution reconstruction network maximizes fine low-resolution 3D objects. To improve these two aspects and further enhance the high-resolution reconstruction capabilities of the 3D object generation network, we study and improve the low-resolution 3D generation network and the depth map superresolution network. Eventually, we get an improved multiview decomposition (IMVD) network. First, we use a 2D image encoder with multifeature fusion (MFF) to enhance the feature extraction capability of the model. Second, a 3D decoder using an effective subpixel convolutional neural network (3D ESPCN) improves the decoding speed in the decoding stage. Moreover, we design a multiresidual dense block (MRDB) to optimize the depth map superresolution network, which allows the model to capture more object details and reduce the model parameters by approximately 25% when the number of network layers is doubled. The experimental results show that the proposed IMVD is better than the original MVD in the 3D object superresolution experiment and the high-resolution 3D reconstruction experiment of a single image.
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Wang, Kaichao, Guojie Zhang, Tianqi Yi, and Xiaoxiong Zha. "Research on New Method for Safety Testing of Steel Structures—Combining 3D Laser Scanning Technology with FEA." Buildings 14, no. 8 (August 22, 2024): 2583. http://dx.doi.org/10.3390/buildings14082583.
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This paper introduces a novel approach to assessing structural safety, specifically aimed at evaluating the safety of existing structures. Firstly, a point cloud model of the existing commercial complex was captured utilizing three-dimensional (3D) laser scanning technology. Subsequently, an intelligent method for identifying holes within the point cloud model was proposed, built upon a YOLO v5-based framework, to ascertain the dimensions and locations of holes within the commercial complex. Secondly, Poisson surface reconstruction, coupled with partially self-developed algorithms, was employed to reconstruct the surface of the structure, facilitating the three-dimensional geometric reconstruction of the commercial complex. Lastly, a finite element model of the framed structure with holes was established using the reconstructed 3D model, and a safety analysis was conducted. The research findings reveal that the YOLO v5-based intelligent hole identification method significantly enhances the level of intelligence in point cloud data processing, reducing manual intervention time and boosting operational efficiency. Furthermore, through Poisson surface reconstruction and the self-developed algorithms, we have successfully achieved automated surface reconstruction, where the resulting geometric model accurately reflects the dimensional information of the commercial complex. Additionally, the maximum uniformly distributed surface load that the floor slabs within the framed structure with holes can withstand should not exceed 17.7 kN/m2, and its vertical deformation resistance stiffness is approximately 71.6% of that of a frame without holes.
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Ramírez Molina, Abel Andrés, Nejc Bezak, Glenn Tootle, Chen Wang, and Jiaqi Gong. "Machine-Learning-Based Precipitation Reconstructions: A Study on Slovenia’s Sava River Basin." Hydrology 10, no. 11 (November 8, 2023): 207. http://dx.doi.org/10.3390/hydrology10110207.
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The Sava River Basin (SRB) includes six countries (Slovenia, Croatia, Bosnia and Herzegovina, Serbia, Albania, and Montenegro), with the Sava River (SR) being a major tributary of the Danube River. The SR originates in the mountains (European Alps) of Slovenia and, because of a recent Slovenian government initiative to increase clean, sustainable energy, multiple hydropower facilities have been constructed within the past ~20 years. Given the importance of this river system for varying demands, including hydropower (energy production), information about past (paleo) dry (drought) and wet (pluvial) periods would provide important information to water managers and planners. Recent research applying traditional regression techniques and methods developed skillful reconstructions of seasonal (April–May–June–July–August–September or AMJJAS) streamflow using tree-ring-based proxies. The current research intends to expand upon these recent research efforts and investigate developing reconstructions of seasonal (AMJJAS) precipitation applying novel Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) techniques. When comparing the reconstructed AMJJAS precipitation datasets, the AI/ML/DL techniques statistically outperformed traditional regression techniques. When comparing the SRB AMJJAS precipitation reconstruction developed in this research to the SRB AMJJAS streamflow reconstruction developed in previous research, the temporal variability of the two reconstructions compared favorably. However, pluvial magnitudes of extreme periods differed, while drought magnitudes of extreme periods were similar, confirming drought is likely better captured in tree-ring-based proxy reconstructions of hydrologic variables.
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Hong, Chao, Jianmin Shi, Yan Xing, and Zejun Chang. "Research on the Coupling and Coordinated Development of Sports Tourism and Cultural Industry under the Background of Artificial Intelligence Era." Wireless Communications and Mobile Computing 2022 (April 11, 2022): 1–6. http://dx.doi.org/10.1155/2022/3191655.
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In the new era of rapid development of intelligent information, sports tourism and cultural industry have become a new goal to improve China’s urban competitiveness and realize the development of urban industry. Based on the integration of sports tourism industry and cultural industry, this paper establishes the relevant information data interface mode. This paper constructs the information coupling system model of sports tourism industry and cultural industry under the background of artificial intelligence era and obtains the corresponding data results by using the invisible statistical logic computer independent judgment (IDIJA) method of artificial intelligence system under the condition of incomplete data. The application of the coordinated development system of coupling industry can realize the rapid development of sports tourism and cultural reconstruction mode and achieve the new effect of intelligent sports tourism cultural comprehensive experience. It can not only improve the people’s quality of life but also provide feasible suggestions for improving the continuous development of the coupling and coordination of sports tourism and cultural industry.
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Dou, Shuyang, and Hiroshi Nagahashi. "An Intelligent Binocular Vision System with Zoom Lens for 3D Scene Reconstruction." International Journal of Computer and Electrical Engineering 8, no. 6 (2016): 304–18. http://dx.doi.org/10.17706/ijcee.2016.8.6.304-318.
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Zhu, Yueyun. "3D Reconstruction of Ancient Building Structure Scene Based on Computer Image Recognition." International Journal of Information Technologies and Systems Approach 16, no. 3 (March 31, 2023): 1–14. http://dx.doi.org/10.4018/ijitsa.320826.
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With the extensive application of computer image recognition (CIR), the high cost of three-dimensional (3D) models, long construction cycles, poor data visualization, and other problems have become the main bottlenecks in further development of CIR. Artificial intelligence (AI) is an important branch of computer science and has a wide range of application prospects and high practical value, especially in the field of medical and health applications of intelligent machines. This article introduces the background of 3D reconstruction of ancient architectural structure scenes, and then presents academic research and a summary on two key applications of CIR. It then summarizes 3D reconstruction and media technology in combination with AI used for medical diagnoses. In this article, the algorithm model is established, and various algorithms are proposed to provide a theoretical basis for the research of 3D reconstruction of ancient building structure scenes based on CIR.
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Condorelli, F., F. Rinaudo, F. Salvadore, and S. Tagliaventi. "A COMPARISON BETWEEN 3D RECONSTRUCTION USING NERF NEURAL NETWORKS AND MVS ALGORITHMS ON CULTURAL HERITAGE IMAGES." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B2-2021 (June 28, 2021): 565–70. http://dx.doi.org/10.5194/isprs-archives-xliii-b2-2021-565-2021.
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Abstract. In this research, an innovative comparison between 3D reconstructions obtained by means of Artificial Intelligence, in particular NeRF Neural Networks, and by Structure-from-Motion (SfM) and Multi-View-Stereo (MVS) open-source algorithms is proposed. The 3D reconstruction comparison is performed on two test cases, one of cultural interest, one useful only for technical discussion. It is known that the approaches are traditionally used with different objectives and in different contexts but they can however also be used with similar purpose, i.e., 3D reconstruction. In particular, we were interested in evaluating how NeRF reconstructions are accurate from a metric point of view and how the models obtained from the application of NeRF differ from the model obtained from the classical photogrammetry. By analyzing the results in the considered test cases, we show how NeRF networks, although computationally demanding, can be an interesting alternative or complementary methodology, especially in cases where classical photogrammetric techniques do not allow satisfactory results to be achieved. It is therefore suggested to expand efforts in this direction by exploiting, for example, the numerous improvement proposals of the original NeRF network.
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Yang, Chuan. "Thoughts on the Teaching of Art and Design in the Era of Artificial Intelligence." Education Reform and Development 4, no. 1 (June 30, 2022): 75–78. http://dx.doi.org/10.26689/erd.v4i1.4148.
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The advent of artificial intelligence has transformed the original mode of material and spiritual production. In view of autonomous machine intelligence, artificial intelligence has become a “production subject” and a new “subject” in the production of cultural intelligence, complete with legal social identity. The visual products produced by intelligent agents are not only the reproduction of the original vitality of some originals. More precisely, their works are the continuation of the concept and style of a designer. In a broad sense, they are the reconstruction of human civilization consciousness. The works produced by artificial intelligence mechanically create the material and conceptual parts of visual products, which directly leads to production mode transformation. The transition from “production tool” to “production subject” ensues a new thinking in the teaching of Art and Design courses. This paper analyzes the shift of production mode in the era of artificial intelligence and the trend changes epitomized by the characteristics of the Art and Design specialty, so as to put forward suggestions and thoughts on the development direction of existing curriculum teaching.
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Wan, Liyang, and Xi Chu. "Study on the impact of camera ISP algorithms on stripe structured light 3D reconstruction and the improvement of 3D reconstruction accuracy by photon input." Applied and Computational Engineering 88, no. 1 (August 27, 2024): 25–33. http://dx.doi.org/10.54254/2755-2721/88/20241461.
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This paper investigates the impact of camera image signal processing (ISP) algorithms on stripe structured light 3D reconstruction and explores the improvement of 3D reconstruction accuracy by photon input. Existing 3D reconstruction technologies have broad applications in fields such as intelligent manufacturing, healthcare, and consumer electronics, but their high precision requirements often cannot be met by current ISP algorithms. By using handheld devices to capture images and combining key techniques such as the multi-step phase shifting method, multi-frequency phase unwrapping method, and triangulation method, this paper conducts an in-depth study on the application of photon input in 3D reconstruction. The study demonstrates that using non-visual information (RAW images) as input can significantly improve reconstruction accuracy, producing more accurate results compared to images processed by ISP. The paper also quantifies the impact of ISP processing on 3D reconstruction results by comparing the depth information and point cloud data of two sets of images. Experimental results show that disabling certain ISP algorithms, such as bilateral noise filtering (BNF), edge enhancement (EEH), and non-local means denoising (NLM), can further improve reconstruction accuracy and reduce errors. In conclusion, this paper proposes a photon image-based 3D reconstruction method that, combined with artificial intelligence technology and differentiable point cloud rendering techniques, holds promise for achieving higher precision and faster 3D reconstruction. This technology is of great significance in practical applications, particularly in the field of industrial close-range 3D reconstruction.
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Hanna, Michael, David Granzow, Bjorn Bolte, and Andrew Alvarado. "NATO Intelligence and Information Sharing: Improving NATO Strategy for Stabilization and Reconstruction Operations." Connections: The Quarterly Journal 16, no. 4 (2017): 5–34. http://dx.doi.org/10.11610/connections.16.4.01.
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Ханна, Михаэль, Дэвид Гранзоу, Бьорн Болте, and Эндрю Алварадо. "Обмен разведывательными данными и информацией в рамках НАТО: усовершенствование стратегии НАТО для операций по стабилизации и восстановлению." Connections: The Quarterly Journal 16, no. 4 (2017): 5–38. http://dx.doi.org/10.11610/connections.rus.16.4.01.
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Peng, Qiaoxia. "Lifelong Learning System in the age of Artificial Intelligence: Change, Opportunity and Reconstruction." Journal of Electrical Systems 20, no. 2 (April 4, 2024): 1085–91. http://dx.doi.org/10.52783/jes.1294.
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Artificial Intelligence advances the offline and online education, digital education and virtual education, eventually all the way to lifelong education with online, digital and virtual Characteristics. In the era of “Artificial Intelligence” (AI), computer technology, Internet technology, big data technology, and cloud computing technology have been widely used in all life and work, making the information dissemination space broader and faster. Information Space provides a platform for new knowledge acquisition and learning for education. The lifelong learning system for the whole population has been updated to break through the modes and limitations of traditional education and meet the needs of all people. This paper first analyzes the connotation and characteristics of lifelong learning for all and points out the current policies and opportunities. Finally, it proposed to build a high-quality, efficient, and sustainable comprehensive lifelong learning system to form an excellent social learning situation in which "everyone can learn, everywhere can learn, and always can learn.” To enhance lifelong learning, efforts focus on expanding the main body responsible for learning, building intelligent learning environments, and providing precise guidance based on educational needs. It is also essential to improve feedback mechanisms, service places, and create an integrated online platform, alongside establishing knowledge-based organizations. This research focus on accountability and quality in lifelong learning since it is evolving with new technologies and opportunities. At the same time, it can expand learning, create an intelligent environment, improve feedback, and establish an online educational platform. This will provide inclusive and high-quality educational opportunities to all learners.
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Liao, Shu-Han, Chien-Ching Chiu, Po-Hsiang Chen, and Hao Jiang. "Microwave Imaging of Anisotropic Objects by Artificial Intelligence Technology." Sensors 23, no. 21 (October 27, 2023): 8781. http://dx.doi.org/10.3390/s23218781.
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In this paper, we present the microwave imaging of anisotropic objects by artificial intelligence technology. Since the biaxial anisotropic scatterers have different dielectric constant components in different transverse directions, the problems faced by transverse electronic (TE) polarization waves are more complex than those of transverse magnetic (TM) polarization waves. In other words, measured scattered field information can scarcely reconstruct microwave images due to the high nonlinearity characteristic of TE polarization. Therefore, we first use the dominant current scheme (DCS) and the back-propagation scheme (BPS) to compute the initial guess image. We then apply a trained convolution neural network (CNN) to regenerate the microwave image. Numerical results show that the CNN possesses a good generalization ability under limited training data, which could be favorable to deploy in image processing. Finally, we compare DCS and BPS reconstruction images for anisotropic objects by the CNN and prove that DCS is better than BPS. In brief, successfully reconstructing biaxial anisotropic objects with a CNN is the contribution of this proposal.
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Jian, Yingbin, Yunpeng Li, Lijie Wang, and Shenghuan Dong. "Intelligent Industrial Design System Based on Spatial Digital Technology." Advances in Multimedia 2022 (September 9, 2022): 1–10. http://dx.doi.org/10.1155/2022/6502153.
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In order to improve the effect of intelligent industrial design, this paper combines the spatial digital technology to construct the system structure of the intelligent industrial design community. Considering the existence of the identification diffusion angle, this paper analyzes the refraction of light when it enters the workpiece and lists the calculation methods of the refraction angle of different media. Moreover, considering that the various conditions of the workpiece detection surface will make the calculation of the refraction of the identification light more complicated; this paper analyzes the specific parameters of the identification light, which lays a theoretical foundation for the accurate calculation of the subsequent wavefront arc. In addition, this paper studies defect reconstruction methods based on circle, ellipse, and polygon models. Finally, through experimental research, this paper verifies that the intelligent industrial design system based on spatial digital technology has a good effect in industrial design and can effectively improve the intelligence of modern industrial design.
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Poza-Lujan, Jose-Luis, Juan-Luis Posadas-Yagüe, José-Enrique Simó-Ten, and Francisco Blanes. "Distributed Architecture to Integrate Sensor Information: Object Recognition for Smart Cities." Sensors 20, no. 1 (December 23, 2019): 112. http://dx.doi.org/10.3390/s20010112.
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Object recognition, which can be used in processes such as reconstruction of the environment map or the intelligent navigation of vehicles, is a necessary task in smart city environments. In this paper, we propose an architecture that integrates heterogeneously distributed information to recognize objects in intelligent environments. The architecture is based on the IoT/Industry 4.0 model to interconnect the devices, which are called smart resources. Smart resources can process local sensor data and offer information to other devices as a service. These other devices can be located in the same operating range (the edge), in the same intranet (the fog), or on the Internet (the cloud). Smart resources must have an intelligent layer in order to be able to process the information. A system with two smart resources equipped with different image sensors is implemented to validate the architecture. Our experiments show that the integration of information increases the certainty in the recognition of objects by 2–4%. Consequently, in intelligent environments, it seems appropriate to provide the devices with not only intelligence, but also capabilities to collaborate closely with other devices.
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Zhang, Liming, Lei Wang, Xu du, and Fanbo Meng. "CAD-Aided 3D Reconstruction of Intelligent Manufacturing Image Based on Time Series." Scientific Programming 2022 (March 11, 2022): 1–11. http://dx.doi.org/10.1155/2022/9022563.
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To improve the three-dimensional (3D) reconstruction effect of intelligent manufacturing image and reduce the reconstruction time, a new CAD-aided 3D reconstruction of intelligent manufacturing image based on time series was proposed. Kinect sensor is used to collect depth image data and convert it into 3D point cloud coordinates. The collected point cloud data are divided into regions, and different point cloud denoising algorithms are used to filter and denoise the divided regions. With the help of CAD, FLANN matching algorithm is used to extract feature points of time-series images and complete image matching. Three-dimensional reconstruction of sparse point cloud and dense point cloud is carried out to complete 3D reconstruction of intelligent manufacturing images. The experimental results show that the image PSNR of this method is always above 52 dB, and the maximum reconstruction time is 4.9 s. The 3D reconstruction effect of intelligent manufacturing image is better, and it has higher practical application value.
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Wang, Haoyu, Liu Hong, and Leonardo P. Chamorro. "Micro-Scale Particle Tracking: From Conventional to Data-Driven Methods." Micromachines 15, no. 5 (May 8, 2024): 629. http://dx.doi.org/10.3390/mi15050629.
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Micro-scale positioning techniques have become essential in numerous engineering systems. In the field of fluid mechanics, particle tracking velocimetry (PTV) stands out as a key method for tracking individual particles and reconstructing flow fields. Here, we present an overview of the micro-scale particle tracking methodologies that are predominantly employed for particle detection and flow field reconstruction. It covers various methods, including conventional and data-driven techniques. The advanced techniques, which combine developments in microscopy, photography, image processing, computer vision, and artificial intelligence, are making significant strides and will greatly benefit a wide range of scientific and engineering fields.
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Wang, He, Peng Lin, Zhansheng Hou, and Shijun Sun. "Research on Intelligent Monitoring and Maintenance Technology of Substation Based on Digital Twin." Journal of Physics: Conference Series 2136, no. 1 (December 1, 2021): 012029. http://dx.doi.org/10.1088/1742-6596/2136/1/012029.
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Abstract The design, research and development, test, operation and maintenance of power grid substation equipment are relatively independent. Related problems in each link cannot be comprehensively managed from the perspective of the full life cycle of equipment. Operation and maintenance personnel need to face data monitoring, network monitoring, equipment monitoring, business system monitoring, fault diagnosis and repair and other business scenarios. There are many types of information, complex association relationship, abstract and inefficient operation and maintenance information, “man-machine-object” can not be two-way cooperation and interaction, fault diagnosis and troubleshooting difficulties. Digital substation intelligent monitoring operational digital twin applications, digital intelligent substation operations provide operational monitoring service ability, realize the grid digital substation twin modeling and environment reconstruction, false or true merged superposition, two-way coordinated interaction, twin intelligence operations and panoramic visual monitoring, field devices for power grid operation maintenance, resource scheduling, and construction planning to provide guidance, Fully guarantee the safe and reliable operation of power grid equipment, realize the full life cycle management of power grid equipment, and improve the level of intelligence, visualization and digitalization of power grid.
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Cevik, Jevan, Ishith Seth, David J. Hunter-Smith, and Warren M. Rozen. "A History of Innovation: Tracing the Evolution of Imaging Modalities for the Preoperative Planning of Microsurgical Breast Reconstruction." Journal of Clinical Medicine 12, no. 16 (August 11, 2023): 5246. http://dx.doi.org/10.3390/jcm12165246.
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Breast reconstruction is an essential component in the multidisciplinary management of breast cancer patients. Over the years, preoperative planning has played a pivotal role in assisting surgeons in planning operative decisions prior to the day of surgery. The evolution of preoperative planning can be traced back to the introduction of modalities such as ultrasound and colour duplex ultrasonography, enabling surgeons to evaluate the donor site’s vasculature and thereby plan operations more accurately. However, the limitations of these techniques paved the way for the implementation of modern three-dimensional imaging technologies. With the advancements in 3D imaging, including computed tomography and magnetic resonance imaging, surgeons gained the ability to obtain detailed anatomical information. Moreover, numerous adjuncts have been developed to aid in the planning process. The integration of 3D-printing technologies has made significant contributions, enabling surgeons to create complex haptic models of the underlying anatomy. Direct infrared thermography provides a non-invasive, visual assessment of abdominal wall vascular physiology. Additionally, augmented reality technologies are poised to reshape surgical planning by providing an immersive and interactive environment for surgeons to visualize and manipulate 3D reconstructions. Still, the future of preoperative planning in breast reconstruction holds immense promise. Most recently, artificial intelligence algorithms, utilising machine learning and deep learning techniques, have the potential to automate and enhance preoperative planning processes. This review provides a comprehensive assessment of the history of innovation in preoperative planning for breast reconstruction, while also outlining key future directions, and the impact of artificial intelligence in this field.
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Dong, Yuxing, Yan Li, and Zhen Li. "Research on Detection and Recognition Technology of a Visible and Infrared Dim and Small Target Based on Deep Learning." Electronics 12, no. 7 (April 5, 2023): 1732. http://dx.doi.org/10.3390/electronics12071732.
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With the increasing trend towards informatization and intelligence in modern warfare, high-intensity and continuous reconnaissance activities are becoming increasingly common in battlefield environments via airborne, vehicle, UAV, satellite and other platforms. Visible and infrared images are preferred due to their high resolution, strong contrast, rich texture details and color features, and strong information expression ability. However, the quality of imaging is easily affected by environmental factors, making it crucial to quickly and accurately filter useful information from massive image data. To this end, super-resolution image preprocessing can improve the detection performance of UAV, and reduce false detection and missed detection of targets. Additionally, super-resolution reconstruction results in high-quality images that can be used to expand UAV datasets and enhance the UAV characteristics, thereby enabling the enhancement of small targets. In response to the challenge of “low-slow small” UAV targets at long distances, we propose a multi-scale fusion super-resolution reconstruction (MFSRCNN) algorithm based on the fast super-resolution reconstruction (FSRCNN) algorithm and multi-scale fusion. Our experiments confirm the feasibility of the algorithm in reconstructing detailed information of the UAV target. On average, the MFSRCNN reconstruction time is 0.028 s, with the average confidence before and after reconstruction being 80.73% and 86.59%, respectively, resulting in an average increase of 6.72%.
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Kobrinskii, B. A., D. D. Dolotova, V. V. Donitova, and A. V. Gavrilov. "Radiological Images in the Construction of Hybrid Intelligent System." Vrach i informacionnye tehnologii, no. 4 (2020): 43–50. http://dx.doi.org/10.37690/1811-0193-2020-4-43-50.
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So far, the concept of image row or tuples in the development of intelligent systems has been discussed in relation to the role of phenotypic (external) manifestations of diseases in diagnostics. This study introduces the idea of neuroimaging tuples as a tool to make a prognosis of the course of chronic cerebral ischemia. The phenomenon of leukoaraiosis is analyzed as a radiological feature of chronic brain ischemia and a predictor of stroke. Image tuples are formed from the results of computed tomography, computed tomography angiography, magnetic resonance imaging, of 85 patients with chronic cerebral ischemia. Native computed tomography images were processed with adaptive filtering methods. Computed tomography angiography results were processed through a vesselness filter that allows development of 3D reconstructions of vasculature in leukoaraiosis areas. The problem of fuzzy images, the principles of comparative analysis of images and the possibility of using confidence factors in the image tuples are discussed in the article. A scheme of a hybrid intelligent system that combines traditional logic-linguistic rules and images based on primary information and reconstruction of the original DICOM images in the knowledge base was developed. The sphere of the application is stroke risk prediction using an intelligent system.
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Zhang, Linsen. "General Definitions of Information, Intelligence, and Consciousness from the Perspective of Generalized Natural Computing." Applied and Computational Mathematics 13, no. 5 (October 10, 2024): 186–92. http://dx.doi.org/10.11648/j.acm.20241305.17.
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Atoms themselves have no thoughts and cannot be thinking. Why does the human body, which is composed of atoms, have consciousness? The widely used concepts of information and intelligence in today’s science, which are related to this, do not yet have appropriate general definitions. Answering these interesting questions is a crucial issue for technological development in the historical context of human society entering the era of intelligence. The key lies in how to fully utilize the existing fundamental theories subtly related to information science. Here we attempt to give the definition of general information and general intelligence from the perspective of generalized natural computing, based on the least action principle, Hamilton-Jacobi equation, dynamic programming, reinforcement learning, and point out the relationship between the two. The least action principle for describing conservative systems can be seen as an intelligent manifestation of natural matter, and its equivalent form, the Hamilton-Jacobi equation, can be extended to describe quantum phenomena and is a special case of continuous dynamic programming equations. Dynamic programming is an efficient optimization method under deterministic models, while reinforcement learning, as a manifestation of biological intelligence, is its model-free version. The statement that reinforcement learning is the most promising machine learning method has a profound physical foundation. General information is defined as the degree to which a certain environmental element determines the behavior of the subject. General intelligence is defined as the automatic optimization ability of the action or value function of a system with a certain degree of conservatism. Intelligence is a basic property of material systems, rather than an emergent property that only complex systems possess. Consciousness is an advanced intelligent phenomenon, a reconstruction of quasi conservative systems based on complex systems.
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Xi, Mengying. "Reconstruction of New Media Art Ecology Based on Intelligent Technology Environment." Wireless Communications and Mobile Computing 2022 (July 23, 2022): 1–6. http://dx.doi.org/10.1155/2022/8084536.
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With the rapid development of modern multimedia technology and Internet technology, the traditional media in people’s daily life, including newspapers, magazines, radio, and television, are far less timely and extensive than the new media that use the Internet to spread, such as today’s headlines, microblog, TikTok, and NetEase News. In the process of its own development, Internet new media has gradually derived new media art, which is different from traditional art forms, with the mixture of sound, light, and electricity as the form of expression and the Internet as the media. The wide spread of new media art depends very much on the development of the Internet. In the early stage, the audience of new media is not wide, such as Tianya Forum and Sina blog. It is only for information exchange and communication with people who use the computer Internet. At the same time, the content shared is limited to words and pictures. When the computer Internet began to popularize and the mobile network terminal began to develop, new media art immediately sprouted. Starting from instant messaging, Tencent QQ integrates the strengths of all kinds of new media and promotes the further development of new media art. Standing at the juncture of 2022, after more than ten years of continuous innovation and development, the expression terminal has come from the computer to the mobile phone we use every day. The media has quickly entered the 5 g network from 2G and 3G networks, and the communication path and time have been quite flexible. In addition, AI (artificial intelligence) and other intelligent technologies have begun to enter people’s daily life. The combination of intelligent technology and new media art has brought new media art into another period of transformation and sublimation. This paper will discuss that in the current environment where intelligent technology has begun to be popularized in people’s daily life, new media art achieves the result of ecological reconstruction by innovating and deepening its own characteristics in combination with intelligent technology.
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Yang, Guo Qing, Shao Shan Lin, Hong Yu Li, Shi Ren Yang, and Shu Hui Cai. "Transformation Equipment Voice Reconstruction Based on Fourier Spectrum of Power-Frequency Multiple." Applied Mechanics and Materials 536-537 (April 2014): 168–71. http://dx.doi.org/10.4028/www.scientific.net/amm.536-537.168.
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The equipment voice de-noising and reconstruction algorithm is presented in this paper based on intelligent robot in transformer situation (transformer and high resistance). The method is an embodiment of information and intelligence which can be applied in voice recognition of inspection robot. Firstly, equipment voice was collected and formed a sample database. Secondly, the voice features were analyzed in sample database, and the power-frequency Fourier spectrum as the voice features was extracted in the frequency domain. Finally, Fourier spectrum of power-frequency multiple was used to construct the voice by taking advantage of the inverse Fourier transform. The experimental results show that the algorithm has stable performance, strong robustness, and can accurately reconstruct the voice, so it is benefit to the follow-up voice recognition.
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Cao, Jinghao, Yang Li, and Sidan Du. "Robust Artificial Intelligence-Aided Multimodal Rail-Obstacle Detection Method by Rail Track Topology Reconstruction." Applied Sciences 14, no. 7 (March 27, 2024): 2795. http://dx.doi.org/10.3390/app14072795.
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Detecting obstacles in the rail track area is crucial for ensuring the safe operation of trains. However, this task presents numerous challenges, including the diverse nature of intrusions, and the complexity of the driving environment. This paper presents a multimodal fusion rail-obstacle detection approach by key points processing and rail track topology reconstruction. The core idea is to leverage the rich semantic information provided by images to design algorithms for reconstructing the topological structure of railway tracks. Additionally, it combines the effective geometric information provided by LiDAR to accurately locate the railway tracks in space and to filter out intrusions within the track area. Experimental results demonstrate that our method outperforms other approaches with a longer effective working distance and superior accuracy. Furthermore, our post-processing method exhibits robustness even under extreme weather conditions.
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Fan, Pochu, Junying Lee, and Xueying Liu. "Research on New Residential Digital Brokerage Services." Academic Journal of Management and Social Sciences 9, no. 1 (October 28, 2024): 21–24. http://dx.doi.org/10.54097/yvgjme46.
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In this paper, the digital economy era of residential service as the background, first explained the connotation of new residential service, and then analyzed the new residential service market status, and then elaborated the new residential service technology application landing, become the realization of wisdom to benefit the people, embrace the intelligent wave of real estate brokerage industry. Finally, the paper puts forward the path of digital transformation of residential service industry: in-depth industry, insight into business, refining key elements of business, building index system; Under the constraints of resources and technology, concentrate resources and make strategic choices; Standard productization, data accumulation, feedback business; Product intelligence, reconstruction process.
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HEMKER, ANDREAS, and KARL-HEINZ BECKS. "EVOLUTION ENGINES AND ARTIFICIAL INTELLIGENCE." International Journal of Modern Physics C 05, no. 01 (February 1994): 15–36. http://dx.doi.org/10.1142/s0129183194000039.
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In the last years artificial intelligence has achieved great successes, mainly in the field of expert systems and neural networks. Nevertheless the road to truly intelligent systems is still obscured. Artificial intelligence systems with a broad range of cognitive abilities are not within sight. The limited competence of such systems (brittleness) is identified as a consequence of the top-down design process. The evolution principle of nature on the other hand shows an alternative and elegant way to build intelligent systems. We propose to take an evolution engine as the driving force for the bottom-up development of knowledge bases and for the optimization of the problem-solving process. A novel data analysis system for the high energy physics experiment DELPHI at CERN shows the practical relevance of this idea. The system is able to reconstruct the physical processes after the collision of particles by making use of the underlying standard model of elementary particle physics. The evolution engine acts as a global controller of a population of inference engines working on the reconstruction task. By implementing the system on the Connection Machine (Model CM-2) we use the full advantage of the inherent parallelization potential of the evolutionary approach.
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Bansal, Bhavana, Aparajita Nanda, and Anita Sahoo. "Intelligent Framework With Controlled Behavior for Gene Regulatory Network Reconstruction." International Journal of Information Retrieval Research 12, no. 1 (January 2022): 1–17. http://dx.doi.org/10.4018/ijirr.2022010104.
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Gene Regulatory Networks (GRNs) are the pioneering methodology for finding new gene interactions getting insights of the biological processes using time series gene expression data. It remains a challenge to study the temporal nature of gene expression data that mimic complex non-linear dynamics of the network. In this paper, an intelligent framework of recurrent neural network (RNN) and swarm intelligence (SI) based Particle Swarm Optimization (PSO) with controlled behaviour has been proposed for the reconstruction of GRN from time-series gene expression data. A novel PSO algorithm enhanced by human cognition influenced by the ideology of Bhagavad Gita is employed for improved learning of RNN. RNN guided by the proposed algorithm simulates the nonlinear and dynamic gene interactions to a greater extent. The proposed method shows superior performance over traditional SI algorithms in searching biologically plausible candidate networks. The strength of the method is verified by analyzing the small artificial network and real data of Escherichia coli with improved accuracy.
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Carpenter, Chris. "Artificial Intelligence Improves Seismic-Image Reconstruction." Journal of Petroleum Technology 71, no. 10 (October 1, 2019): 65–66. http://dx.doi.org/10.2118/1019-0065-jpt.
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Zhang, Jianfeng. "Virtual Viewpoint Film and Television Synthesis Based on the Intelligent Algorithm of Wireless Network Communication for Image Repair." Wireless Communications and Mobile Computing 2021 (October 18, 2021): 1–15. http://dx.doi.org/10.1155/2021/9063410.
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With the development of the computer vision field, the acquisition of scene depth information is one of the important topics in the three-dimensional reconstruction of the computer vision field, and its significance is particularly important. The purpose of this paper is to study the virtual viewpoint video synthesis for image restoration based on the intelligent algorithm of wireless network communication. Aiming at the hole problem caused by the change of occlusion relationship, this paper proposes a hole-filling method based on background recognition. A threshold segmentation algorithm is used to reduce the filling priority of foreground pixels at the boundary of the hole and fully solve the hole problem. This paper also proposes a wireless sensor network node positioning model with swarm intelligence algorithm, which combines swarm intelligence algorithm with some key issues of wireless sensor network, speeds up the convergence, and improves the traditional intelligence algorithm. According to the experimental data in this paper, the algorithm in this paper is about 20% higher than the traditional algorithm in PSNR. On SSIM, the performance of the algorithm in this paper is 4.6% higher than the traditional algorithm at most, and the lowest is 2.2%.
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Lombardo, Giuseppe A. G., Rosario Ranno, Dario Melita, Isidoro Musmarra, Paolo Marchica, and Francesco Ciancio. "Evaluating AI's Efficacy in Enhancing Patient Education and Answering FAQs in Plastic Surgery: A Focused Case Study on Breast Reconstruction." Archives of Breast Cancer 11, no. 2 (May 1, 2024): 147–58. http://dx.doi.org/10.32768/abc.2024112147-158.
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Background: The rapid advent of artificial intelligence (AI) and machine learning (ML) in the healthcare sector offers new horizons for patient education and has the potential to redefine patient-provider interactions. Our research aimed to gauge the efficacy of ChatGPT-4 in delivering accurate, current, and safe medical guidance on breast reconstruction, and benchmark its responses against other established patient information channels. Methods: We presented ChatGPT-4 with six frequently posed questions about breast reconstruction. The model's replies were critically assessed by a committee of experienced plastic and reconstructive surgeons. To ensure the precision of the information, its responses were further cross-referenced against two major medical databases. Results: The results revealed that ChatGPT-4 produced well-articulated, factually sound, and holistic answers to the presented inquiries. However, the platform showed constraints in offering tailored guidance and occasionally cited outdated or irrelevant references. Notably, the system consistently advocated for professional consultation for nuanced information. Conclusion: ChatGPT-4 has emerged as a potential supplementary resource in patient education concerning breast reconstruction. Nevertheless, to harness its full potential and ensure its seamless integration into healthcare, further refinements and advancements in AI tools are paramount. The study underscores the importance of continuous evaluation and enhancement for AI solutions in the evolving landscape of patient education.