Panoramic Data Research Articles

Fully automated deep learning approach to dental development assessment in panoramic radiographs

BackgroundDental development assessment is an important factor in dental age estimation and dental maturity evaluation. This study aimed to develop and evaluate the performance of an automated dental development staging system based on Demirjian’s method using deep learning.MethodsThe study included 5133 anonymous panoramic radiographs obtained from the Department of Pediatric Dentistry database at Seoul National University Dental Hospital between 2020 and 2021. The proposed methodology involves a three-step procedure for dental staging: detection, segmentation, and classification. The panoramic data were randomly divided into training and validating sets (8:2), and YOLOv5, U-Net, and EfficientNet were trained and employed for each stage. The models’ performance, along with the Grad-CAM analysis of EfficientNet, was evaluated.ResultsThe mean average precision (mAP) was 0.995 for detection, and the segmentation achieved an accuracy of 0.978. The classification performance showed F1 scores of 69.23, 80.67, 84.97, and 90.81 for the Incisor, Canine, Premolar, and Molar models, respectively. In the Grad-CAM analysis, the classification model focused on the apical portion of the developing tooth, a crucial feature for staging according to Demirjian’s method.ConclusionsThese results indicate that the proposed deep learning approach for automated dental staging can serve as a supportive tool for dentists, facilitating rapid and objective dental age estimation and dental maturity evaluation.

A 3D urban scene reconstruction enhancement approach based on adaptive viewpoint selection of panoramic videos

AbstractThe widely used unmanned aerial vehicle oblique photogrammetry often suffers from information loss in complex urban environments, leading to geometric and textural defects in the resulting models. In this study, a close‐range panoramic optimal viewpoint selection assisted 3D urban scene reconstruction enhancement method is proposed for areas prone to defects. We first introduce the ground panoramic data acquisition equipment and strategy, which are different from those of the single‐lens supplementary photography method. Data acquisition is accomplished through a single and continuous surround‐style collection approach. The full coverage of the panoramic video in the space–time dimension enables the acquisition of texture details without considering camera station planning. Then, a panoramic multiview image generation approach is proposed. Adaptive viewpoint selection is achieved using unbiased sampling points from the rough scene model, and viewpoint optimisation is adopted to ensure sufficient image overlap and intersection effects, thus improving the scene reconstructability. Finally, the 3D model is generated by photogrammetric processing of the panoramic multiview images, resulting in an enhanced modelling effect. To validate the proposed method, we conducted experiments using real data from Qingdao, China. Both the qualitative and quantitative results demonstrate a significant improvement in the quality of geometric and textural reconstruction. The tie‐point reprojection errors are less than 1 pixel, and the registration accuracy with the model from oblique photogrammetry is comparable to that of optimised‐view photography. By eliminating the need for on‐site camera station planning or manual flight operations and effectively minimising the redundancy of panoramic videos, our approach significantly reduces the photography and computation costs associated with reconstruction enhancement. Thus, it presents a feasible technical solution for the generation of urban 3D fine models.

Self-Supervised Place Recognition by Refining Temporal and Featural Pseudo Labels From Panoramic Data

Self-Supervised Place Recognition by Refining Temporal and Featural Pseudo Labels From Panoramic Data

Real time Sharing Method of Panoramic Data of Substation Equipment Based on RAFT Algorithm

Real time Sharing Method of Panoramic Data of Substation Equipment Based on RAFT Algorithm

Research and Application of Panoramic Data Visualization Platform for Stability Control Equipment Based on the Whole Life Cycle

In recent years, with the mass access of new energy such as UHV commissioning projects and photovoltaic wind, the problems in safely and stably operating regional power grid are becoming more and more prominent. Mass power grid stability control system and equipment play a significant role in this aspect. However, there are a great variety of manufacturers and models of the stability control systems and equipment, as well as configuration schemes for the operation strategy and fixed value of the primary equipment. Due to insufficient technological support, it is relatively inconvenient to manage the information and data of stability and control system on the whole process from feasibility research, initial test, factory debugging, site debugging, commissioning acceptance, protection verification, daily operation and maintenance management to the decommission of the system, thus failing to achieve the objective of classified management according to the relevant requirements, nor to modify and improve in time. Based on the management requirements and status quo of the stability and control equipment, a technical research on the panoramic data visualization platform for the stability control equipment with full life-cycle information covering the feasibility research, release, debugging, commissioning, verification, operation, decommission and so on of the equipment, which is available for the panoramic informationized and digital management of the stability control equipment, so as to realize the whole life cycle and systematic closed-loop management of the stability control system and the equipment.

Anti-Fraud Analysis during the COVID-19 Pandemic: A Global Perspective

The ongoing coronavirus disease 2019 (COVID-19) pandemic has brought unexpected economic downturns and accelerated digital transformation, leading to stronger financial fraud motives and more complicated fraud schemes. Although scholars, practitioners, and regulators have begun to focus on the new characteristics of financial fraud, a systematic and effective anti-fraud strategy during the pandemic still needs to be explored. This paper comprehensively analyzes the lessons of anti-fraud that we should learn from the COVID-19 pandemic. By exploring the complex motives and schemes of fraud, we summarize the characteristics of financial fraud activities and further analyze the regulatory challenges posed by financial fraud during the outbreak. To better cope with the fraudulent activities during the pandemic, policy proposals on how to improve the supervision of financial fraud activities are put forward. In particular, the panoramic data and graph-based techniques are powerful tools for future fraud detection.

State assessment of 110–220 kV intelligent substation based on multisensor fusion algorithm control and image vision

With the development of modern information technology, intelligent substation technology has been widely used, which greatly promotes the development of power grid. The information integration platform of intelligent substations realizes panoramic data collection and data sharing of substations. With the continuous development of the economy and society, it is crucial to improve the power regulation ability of intelligent substations, make scientific use of intelligent technology, and optimize the patrol level of intelligent substation patrol robots to better meet the operation needs of substations. In the actual substation construction, the flexibility of equipment utilization in intelligent substations should be fully considered. In addition, the number of substations should be controlled to improve the utilization efficiency of patrol robots. This paper mainly summarizes the monitoring technology of intelligent substations, the positioning technology of inspection robots, and the multi-sensor control technology to lay a foundation for the follow-up inspection work of intelligent substations.

The application of an integrated monitoring system for power distribution and consumption

In view of the fact that the traditional integrated power distribution and consumption monitoring system and power information acquisition system are independent of each other, and the data between the two systems are not shared and reused, which brings great obstacles to the construction of new power systems, this paper proposes an integrated power distribution and consumption monitoring system. The system can simultaneously collect distribution monitoring data and power consumption information data, and accurately perceive the panoramic data of power systems such as high voltage power line, distribution transformer area, low voltage power line, metering tank and so on. Through big data statistical analysis and accurate prediction of fault events, realize the two-way interaction between distribution side and power consumption side, reduce power maintenance costs, improve power supply quality, it provides a strong guarantee for the safe operation of power distribution and electrical equipment.

Exploring the distribution of city street greenery from eye-level: an application of Baidu Map panoramic images data

ABSTRACT Increasing attention has been paid to the analysis of street greenery using the Green View Index (GVI). Current methods of vegetation extraction are not suitable for processing large amounts of data. This study introduces Visible Difference Vegetation Index (VDVI) to process Baidu Map panoramic static images which is relatively convenient for GVI calculation. The method is used to analyse the spatial distribution of street greenery in Guangzhou city in China. The results show that: (1) The spatial distribution of GVI values in Guangzhou show obvious agglomeration. (2) The average level and evenness of street greenery distribution is analysed. Tianhe and Yuexiu districts had high levels of evenly distributed street greenery; Liwan, Haizhu, Huangpu, and Panyu districts had good levels of street greenery but uneven distributions; Baiyun and Nansha had low levels of street greenery. (3)There is a significant correlation between road grade, house price, building age, land use and GVI values, which reveals the driving factors of GVI value distribution in Guangzhou. The GVI calculation method in this method is relatively convenient and accurate. GVI can be a new evaluation tool for street greenery in urban planning, additionally used as an index for urban environmental research.

Optimal sites for orthodontic anchor screw placement using panoramic images: risk of maxillary sinus perforation and contact with adjacent tooth roots during screw placement

ObjectivesThis study investigated the safety of orthodontic anchor screw (OAS) placement by examining the morphology and degree of depression of the maxillary sinus adjacent to the alveolar bone between the maxillary molars.MethodsWe reviewed panoramic and CT imaging data of 25 patients. First, the morphology of the maxillary sinus adjacent to the alveolar bone between the maxillary molars on panoramic images was classified into three types: non-depressed sinus, funnel-like sinus depression, and sawtooth-like sinus depression. Then, the distance from the maxillary buccal bone to the maxillary sinus or to the maxillary lingual bone and the distance between the roots of the maxillary second premolar and first molar at heights of 5, 6.5, and 8 mm from the alveolar crest were measured on CT images and compared between the three sinus morphology groups.ResultsThe sawtooth-like depression group had significantly smaller bone thickness than the other two groups, with mean thickness of < 4 mm at any height from the alveolar crest. The funnel-like depression and non-depression groups had mean bone thickness of > 8 mm at any height from the alveolar crest.ConclusionsSawtooth-like sinus depression had increased risk of maxillary sinus perforation, suggesting that OAS placement in this region should be avoided. In contrast, OAS placement between 6.5 and 8 mm from the alveolar crest is advisable in patients with funnel-like sinus depression and at a site > 8 mm from the alveolar crest in those with a non-depressed sinus.

Research on Application of BIM+GIS Technology in Building Life Cycle

Based on a project, the application of BIM+GIS technology in the whole life cycle of the project building is studied. Selecting the image data based on the fusion of UAV tilt photography and panoramic data, a controllable data management platform is established. In the planning and design stage, the use of technology can reduce the frequency of exploration, check the project for design errors, reduce the number of rework of the project, improve work efficiency. In the construction phase, funding for large-scale projects through image data, using BIM Technology to simulate construction progress, collision check, etc. Reduce the waste of resources; in the operation and maintenance phase, through the management of the information data of the BIM model, so as to provide data support for the maintenance and other work in the later stage of the project.

Research on big data enabling governance decision based on consistency model

Big data has become a new factor of production in the era of digital governance. Big data has changed the thinking and mode of decision-making, enabled governance decision-making, and created a new paradigm of decision-making. However, in the actual application process, due to the limitations of data availability, time, cost, cognitive and psychological factors, it is often inconsistent with panoramic data. How to judge and solve the inconsistency between the data subset and the data set is the premise of making scientific decision. From the perspective of “consistency”, this paper constructs the basic assumptions of governance decision-making, combs and explains the solution path of consistency between the available data subset and the expected data set, expands the research perspective of measuring data similarity, and deepens the feasibility of data-driven enabling governance decision-making.

Raising awareness of the cultural, architectural, and perceptive values of historic gardens and related landscapes: panoramic cones and multi-temporal data

Historic gardens and their related landscapes are often experienced only for their social, aesthetic, and environmental resources, yet their cultural, architectural, and perceptive significance is often ignored. The paper demonstrates how historic and educational values of historic gardens and related landscapes can be revealed by combining historic maps, reading perspective cones, and also applying advanced digital and educational methods and techniques. Historical maps, especially military and cadastral maps, associated with historical iconography, can provide us with a lot of information to study historical gardens and also to define conservation and valorization plans that are related to the history of the site: geomatics tools to georeference and co-relate metric and non-metric historical maps provide growing useful outputs, that can be deployed through the use of Virtual Hubs, boosting the availability of content and the accessibility of open data for policy makers, experts, and non-expert members. Moreover, they can also support heritage education programs providing the opportunity to allow to understand the wealth of sites now simplified, in their system, with different functions and with a transformed context. The study of historic gardens involves the analysis of the landscape in its dynamism and complexity, defines tools that make users more aware of the richness of our heritage.

Hard and soft tissue lesion in oral cavity assessed by periapical and panoramic radiography

ObjectiveThis research was aimed to observe the hard and soft tissue lesion in the oral cavity assessed with the periapical and panoramic radiographic examination in Dental Hospital of Hasanuddin University. MethodsIt was an observational descriptive study with cross-sectional design through periapical and panoramic data from April–May 2017. The results were presented in the distribution table and graphic. ResultsTo diagnose almost various oral cavity lesions, the dentist need to receipt a radiographic examination both intraoral and extraoral radiography. The most common hard tissue lesions that detected through periapical radiographic were caries 37.1%, pulp lesion 34.6% and periodontal lesion 17.9%. In panoramic radiographic data, the highest prevalence of tissue lesion was periodontal lesion and periapical abnormality 33.7% with the number of women was higher than men in the 12–25 year age group. ConclusionThe prevalence of hard and soft tissue lesion in the oral cavity was high.

Visualizing Very Large Image Data Sets At Interactive Rates

This paper presents a system for real-time visualization of very large image data sets using ondemand loading and dynamic view prediction. We use a robust image representation scheme for efficient adaptive rendering and introduce a fast perspective view generation module to extend the applicability of the system to panoramic images. We demonstrate the effectiveness of the system by applying it both to imagery that does not require perspective correction and to very large panoramic data sets requiring perspective view generation. Furthermore, we extend and generalize the system to enable a wide range of applications. In a broad set of applications, the system permits smooth, real-time interactive navigation of very large panoramic and non-panoramic image data sets on average personal computers without the use of specialized hardware.

Condition monitoring of power transmission and transformation equipment based on industrial internet of things technology

Nowadays, Internet of Things (IoT) technology is an advanced and emerging information based technology and it possesses avast development potential. The application of IoT technology in power system is beneficial for the intelligent transformation of the power system. The power system provides a vast application space for the IoT technology. The purpose of this paper is to strongly promote the application and deployment process of the IoT in various industries and play a long-term important role in promoting the informatization transformation of China’s industry. This paper studies the state monitoring system of power transmission and transformation equipment based on panoramic data and introduces the information model into the IoT of power transmission and transformation equipment. According to the equipment panorama information required by the life cycle management of power transmission a comprehensive panorama information modeling scheme is proposed for smart substation equipment, and the network performance is monitored through simulation analysis. In particular, the end-to-end delay of the application layer changed greatly, with a decrease of 0.015 s. This study provides a reference for the development of state monitoring system of power transmission and transformation equipment in China.

Compressed Sensing and its Applications in Risk Assessment for Internet Supply Chain Finance Under Big Data

Plenty of research focuses on supply chain finance and its risk, qualitatively or quantitatively. However, there are only a little literature studies on the Internet supply chain finance (ISCF), especially on its risk by quantitative analysis. After analyzing the information of partners’ panorama data and upstream and downstream data in the internet supply chain, this paper constructs a multiple dimensional intelligent risk assessment system for ISCF. By using the analytic hierarchy process gray assessment theory, a risk assessment model of ISCF is built. Based on the collected big data, tracking and monitoring partners’ panoramic data, and upstream and downstream data of the supply chain in real time, the risk of ISCF can be calculated through the assessment model, so the investor can decide whether to finance or not before lending and monitor the lender dynamically after loaning. Taking Zhong-ken Supply Chain Co., Ltd., a focal company in the supply chain, as an example, this paper evaluates the risk of lending to one financing enterprise and obtains a specific risk value, by which to describe the risk degree. Therefore, the model has certain practicability.

Citizen-centered big data analysis-driven governance intelligence framework for smart cities

Sensors and systems within rapidly expanding smart cities produce citizen-centered big data which have potential value to support citizen-centered urban governance decision-making. There exists a wealth of extant conceptual studies, however, further operational studies are needed to establish a specific path towards implementation of such data to governance decision-making with analytical algorithms that are appropriate for each step of the path. This paper proposes a framework for the use of citizen-centered big data analysis to drive governance intelligence in smart cities from two perspectives: urban governance issues and data-analysis algorithms. The framework consists of three layers: 1) A data-merging layer, which builds a citizen-centered panoramic data set for each citizen by merging citizen-related big data from multiple sources in collaborative urban governance via similarity calculation and conflict resolution; 2) a knowledge-discovery layer, which plots the citizen profile and citizen persona at both individual and group levels in terms of urban public service delivery and citizen participation via simple statistical analysis techniques, machine learning, and econometrics methods; and 3) a decision-making layer, which uses ontology models to standardize urban governance-related attributes, personas, and associations to support governance decision-making via data mining and Bayesian Net techniques. Finally, the proposed framework is validated in a case study on blood donation governance in China. This research highlights the value of citizen-centered big data, pushes data-to-decision research from conceptual to operational, synthesizes previously published frameworks for citizen-centered big data analysis in smart cities, and enhances the mutual supplement cross multiple disciplinaries.

A Hybrid Multilevel Storage Architecture for Electric Power Dispatching Big Data

Electric power dispatching is the center of the whole power system. In the long run time, the power dispatching center has accumulated a large amount of data. These data are now stored in different power professional systems and form lots of information isolated islands. Integrating these data and do comprehensive analysis can greatly improve the intelligent level of power dispatching. In this paper, a hybrid multilevel storage architecture for electrical power dispatching big data is proposed. It introduces relational database and NoSQL database to establish a power grid panoramic data center, effectively meet power dispatching big data storage needs, including the unified storage of structured and unstructured data fast access of massive real-time data, data version management and so on. It can be solid foundation for follow-up depth analysis of power dispatching big data.

PanoramicData: Data Analysis through Pen & Touch.

Interactively exploring multidimensional datasets requires frequent switching among a range of distinct but inter-related tasks (e.g., producing different visuals based on different column sets, calculating new variables, and observing the interactions between sets of data). Existing approaches either target specific different problem domains (e.g., data-transformation or data-presentation) or expose only limited aspects of the general exploratory process; in either case, users are forced to adopt coping strategies (e.g., arranging windows or using undo as a mechanism for comparison instead of using side-by-side displays) to compensate for the lack of an integrated suite of exploratory tools. PanoramicData (PD) addresses these problems by unifying a comprehensive set of tools for visual data exploration into a hybrid pen and touch system designed to exploit the visualization advantages of large interactive displays. PD goes beyond just familiar visualizations by including direct UI support for data transformation and aggregation, filtering and brushing. Leveraging an unbounded whiteboard metaphor, users can combine these tools like building blocks to create detailed interactive visual display networks in which each visualization can act as a filter for others. Further, by operating directly on relational-databases, PD provides an approachable visual language that exposes a broad set of the expressive power of SQL including functionally complete logic filtering, computation of aggregates and natural table joins. To understand the implications of this novel approach, we conducted a formative user study with both data and visualization experts. The results indicated that the system provided a fluid and natural user experience for probing multi-dimensional data and was able to cover the full range of queries that the users wanted to pose.