Precise Survey Research Articles

Improving Maternal and Neonatal Health Outcomes of Women Through Deep Antenatal Education Analysis With Health Belief Model

This ponder investigates the adequacy of antenatal instruction programs in making strides maternal and neonatal wellbeing results, pivotal measurements for surveying advance towards Economic Improvement Objective 3. Despite restorative progressions, maternal and neonatal horribleness and mortality rates stay concerning, particularly in moo- and middle-income nations. Antenatal instruction programs, planned to prepare hopeful moms with basic information and aptitudes, are proposed interventions. While a few ponders appear stamped enhancements in maternal self-efficacy and infant care hones, others uncover constrained effect on key wellbeing markers. Understanding the components contributing to these results is pivotal. Socially delicate programs custom fitted to populaces and the mode of conveyance impact viability. Integration into broader healthcare models and continuous back encourage upgrades impact. A precise survey and blend of existing investigate uncover solid relationships between the number of antenatal sessions gone to and viability scores. Relapse examination underscores the positive relationship between participation and program adequacy, maternal wellbeing results, and neonatal wellbeing results. Expanding the number of antenatal sessions essentially upgrades both maternal and neonatal wellbeing results, with factual examination demonstrating a coefficient of 0.3292 for program adequacy, 0.3433 for maternal wellbeing results, and 0.3283 for neonatal wellbeing results, all with p-values < 0.005. These discoveries offer profitable experiences for policymakers and healthcare suppliers pointing to make strides open wellbeing mediations.

Lake Environmental Data Harvester (LED) for Alpine Lake Monitoring with Autonomous Surface Vehicles (ASVs)

This article introduces the Lake Environmental Data Harvester (LED) System, a robotic platform designed for the development of an innovative solution for monitoring remote alpine lakes. LED is intended as the first step in creating portable robotic tools that are lightweight, cost-effective, and highly reliable for monitoring remote water bodies. The LED system is based on the Shallow-Water Autonomous Multipurpose Platform (SWAMP), a groundbreaking Autonomous Surface Vehicle (ASV) originally designed for monitoring wetlands. The objective of LED is to achieve the comprehensive monitoring of remote lakes by outfitting the SWAMP with a suite of sensors, integrating an IoT infrastructure, and adhering to FAIR principles for structured data management. SWAMP’s modular design and open architecture facilitate the easy integration of payloads, while its compact size and construction with a reduced weight ensure portability. Equipped with four azimuth thrusters and a flexible hull structure, SWAMP offers a high degree of maneuverability and position-keeping ability for precise surveys in the shallow waters that are typical of remote lakes. In this project, SWAMP was equipped with a suite of sensors, including a single-beam dual-frequency echosounder, water-quality sensors, a winch for sensor deployment, and AirQino, a low-cost air quality analysis system, along with an RTK-GNSS (Global Navigation Satellite System) receiver for precise positioning. Utilizing commercial off-the-shelf (COTS) components, a Multipurpose Data-Acquisition System forms the basis for an Internet of Things (IoT) infrastructure, enabling data acquisition, storage, and long-range communication. This data-centric system design ensures that acquired variables from both sensors and the robotic platform are structured and managed according to the FAIR principles.

An Application of 3D Cross-Well Elastic Reverse Time Migration Imaging Based on the Multi-Wave and Multi-Component Technique in Coastal Engineering Exploration

Precise surveys are indispensable in coastal engineering projects. The extensive presence of sand in the coastal area leads to significant attenuation of seismic waves within unsaturated loose sediments. As a result, it becomes challenging for seismic waves to penetrate the weathered zone and reach the desired depth with significant amount of energy. In this study, the application of three-dimensional (3D) cross-well elastic reverse time migration (RTM) imaging based on multi-wave and multi-component techniques in coastal engineering exploration is explored. Accurate decomposition of vector compressional (P) and shear (S) waves is achieved through two wavefield decoupling algorithms without any amplitude and phase distortion. Additionally, compressional wave pressure components are obtained, which facilitates subsequent independent imaging. This study discusses and analyzes the imaging results of four imaging strategies under cross-correlation imaging conditions in RTM imaging. The analysis leads to the conclusion that scalarizing vector wavefields imaging yields superior imaging of P- and S-waves. Furthermore, the imaging results obtained through this approach are of great physical significance. In order to validate the efficacy of this method in 3D geological structure imaging in coastal areas, RTM imaging experiments were performed on two representative models. The results indicate that the proposed 3D elastic wave imaging method effectively generates accurate 3D cross-well imaging of P- and S-waves. This method utilizes the multi-wave and multi-component elastic wave RTM imaging technique to effectively leverage the Earth’s elastic medium without increasing costs. It provides valuable information about the distribution of subsurface rock layers, interfaces, and other structures in coastal engineering projects. Importantly, this can be achieved without resorting to extensive excavation or drilling operations. This method addresses the limitations of current cross-well imaging techniques, thereby providing abundant and accurate geological and geophysical information for the analysis and interpretation of 3D geological structures in coastal engineering projects. It has important theoretical and practical significance in real-world production, as well as for the study of geological structures in coastal engineering.

Fine characterization of interbedding sand-mudstone based on waveform indication inversion

Abstract Owing to the increasing challenges associated with coal mine exploration and development, extremely precise surveys with high-resolution images are required to support production. Conventional inversion methods cannot provide sufficiently precise images of the complex lithologies in coal measure strata. Accordingly, this study performed research in Qiyuan mining area, Shanxi Province, China, and predicted the complex lithology on the basis of facies control using waveform indication inversion and waveform indication simulation. Horizontal changes in seismic waveforms were used to reflect lithologic assemblage characteristics for facies-controlled constraints, and the vertical mapping the connection between seismic waveform and logging curves was shown. Moreover, high-resolution inversions of wave impedance and natural gamma parameters were conducted. Combined with lithologic shielding and accurate time–depth conversion, the inversions enabled the precise characterization of the lithological assemblage distribution in the study area. Our results showed that waveform indication inversion could distinguish between coal seams and limestone, whereas waveform indication simulation based on natural gamma could effectively distinguish between sandstone and mudstone. Furthermore, the horizontal resolution was improved and the vertical resolution extended to a thickness of 2–3 m. In addition, the inversion results were highly consistent with drilling results, with an error <0.1 m. Therefore, waveform indication inversion and simulation could be applied to coal mines for safe and efficient production.

Capacity Enhancement in D2D 5G Emerging Networks: A Survey

Several efforts are being made to improve the capacity of 5G networks using emerging technologies of interest. One of the indispensable technologies to fulfill the need is device-to-device (D2D) communication with its untapped associated benefits. Interference is introduced at the base station due to massive traffic congestion. The purpose of this research is to expand the knowledge of interference mitigation in D2D using stochastic geometrical tools which will result in capacity enhancement. This study uses a literature review method based on 5G and other already existing literature on D2D communication. More than one hundred and twenty papers on D2D communications in cellular networks exist but no precise survey paper on interference management to enhance capacity using stochastic geometrical tools exists. The contribution of this survey to theory is that apart from already existing capacity enhancement methods, interference mitigation using stochastic geometrical tools is another technique that can also be used for capacity enhancement in D2D communications.

The impact of general medical health status, demographical, and patient-specific variables on need for dental treatment of children and adolescents under general anesthesia.

Aim of this retrospective study was to examine the influence of general medical, demographical, and other patient-specific factors on the need for dental treatment under general anesthesia in children and adolescents at Saarland University Hospital. For assessment of the clinical treatment need, a mixed dt/DT (decayed teeth) was introduced. A total of 340 patients under 18years of age who received restorative-surgical dental treatment between 2011 and 2022 were anonymously enrolled. Demographic and other patient-specific data, general medical health, oral health, and treatment related data were recorded. In addition to descriptive analysis, Spearman-Rho-test, Mann-Whitney-U-test, Kruskall-Wallis-test and Chi-square-test were used. More than half of the patients (52,6%) were in general health, but non-cooperative. The majority of the patients (66.8%) was between 1 and 5years of age (p < 0,001). Mean dmft was 10.95 ± 4.118, mean DMFT was 10.09 ± 7.885, and mean dt/DT was 10.79 ± 4.273. Analysis showed that communication difficulties significantly influenced dmft (p = 0.004), DMFT (p = 0.019), and dt/DT (p < 0.001). Type of insurance significantly affected dmft (p = 0.004) and dt/DT (p = 0.001). There was no significant effect of ASA on caries experience, however on prevalence of severe gingivitis (p < 0.001), number of extractions (p = 0.002), and need for repeated treatment (p < 0.001). Need for dental treatment in the present collective was high, independent of the considered variables. Non-Cooperativeness along with ECC was the main indication for dental general anesthesia. The mixed dt/DT was the most precise survey to evaluate clinical treatment needs. Given the enormous demand for these rehabilitations with strict selection, it is imperative to create more treatment capacities for patients mandatorily requiring general anesthesia by avoiding it in healthy patients.

Using poverty maps to improve the design of household surveys: the evidence from Tunisia.

In this paper we aim to propose a new method for improving the design effect of household surveys based on a two-stage design in which the first stage clusters, or Primary Selection Units (PSUs), are stratified along administrative boundaries. Improvement of the design effect can result in more precise survey estimates (smaller standard errors and confidence intervals) or in the reduction of the necessary sample size, i.e. a reduction in the budget needed for a survey. The proposed method is based on the availability of a previously conducted poverty maps, i.e. spatial descriptions of the distribution of per capita consumption expenditures, that are finely disaggregated in small geographic units, such as cities, municipalities, districts or other administrative partitions of a country that are directly linked to PSUs. Such information is then used to select PSUs with systematic sampling by introducing further implicit stratification in the survey design, so as to maximise the improvement of the design effect. Since per capita consumption expenditures estimated at PSU level from the poverty mapping are affected by (small) standard errors, in the paper we also perform a simulation study in order to take into account this addition variability.

Geomatic Data Fusion for 3D Tree Modeling: The Case Study of Monumental Chestnut Trees

In recent years, advancements in remote and proximal sensing technology have driven innovation in environmental and land surveys. The integration of various geomatics devices, such as reflex and UAVs equipped with RGB cameras and mobile laser scanners (MLS), allows detailed and precise surveys of monumental trees. With these data fusion method, we reconstructed three monumental 3D tree models, allowing the computation of tree metric variables such as diameter at breast height (DBH), total height (TH), crown basal area (CBA), crown volume (CV) and wood volume (WV), even providing information on the tree shape and its overall conditions. We processed the point clouds in software such as CloudCompare, 3D Forest, R and MATLAB, whereas the photogrammetric processing was conducted with Agisoft Metashape. Three-dimensional tree models enhance accessibility to the data and allow for a wide range of potential applications, including the development of a tree information model (TIM), providing detailed data for monitoring tree health, growth, biomass and carbon sequestration. The encouraging results provide a basis for extending the virtualization of these monumental trees to a larger scale for conservation and monitoring.

A Precise Survey on Multi-agent in Medical Domains

A Precise Survey on Multi-agent in Medical Domains

Acrylamide in Cooked Sprouts of Mung Bean (Vigna radiata).

We investigated the time-dependent acrylamide formation in mung bean sprouts during stir-frying under high and medium heat conditions. The acrylamide concentration range detected using the 3-mercaptobenzoic acid derivatization LC-MS/MS method was from below 29 ng/g [limit of detection (LOD)] to 6,900 ng/g. We also investigated the acrylamide levels in mung bean sprouts cooked using four methods while retaining their fresh firm texture using the thiosalicyclic acid derivatization LC-MS/MS method. The acrylamide concentration in microwave oven-cooked sprouts was below 16 ng/g (LOD). The samples cooked by stir-frying, parching, or boiling contained an acrylamide concentration above the LOD but below 42 ng/g [limit of quantification (LOQ)], except for one replicate of a stir-fried sample, whose acrylamide concentration was 42 ng/g. Bean sprouts are popular affordable vegetables, and when stir-fried, their acrylamide concentration is assumed to strongly affect the exposure of the Japanese population to acrylamide. Because the acrylamide concentration range of fried bean sprouts is as broad as mentioned above, the selection of a representative concentration value is difficult. A precise survey and data about acrylamide formation in relation to the bean sprout components before heating, their changes occurring during storage, and the cooking methods and conditions used are needed to estimate the exposure of the Japanese to acrylamide. Here, we showed that rinsing the sprouts before frying and frying them for a short time while mixing them well, while retaining the fresh firm texture to avoid burning and shriveling the sprouts is effective in decreasing the amount of acrylamide formed.

Performance evaluation of single and double-frequency low-cost GNSS receivers in static relative mode

The advancement of low-cost GNSS receivers with modern built-up characteristics has opened a new window to investigate the performance of various low-cost receivers with an outlook on their performance and suitability for varied geodetic purposes. The main objective of this study is to evaluate the positioning performance of single and double-frequency GNSS receivers in combination with geodetic antennas in static relative mode regarding Mexican regulations. The recorded observations were processed by a static relative method including the CORS station from the National Institute of Statistics and Geography in Mexico (INEGI). The results of the survey conducted at a distance of 4 and 33 km from CORS station show similar accuracy for all low-cost receivers. For low-cost GNSS receivers NEO-M8T, NEO-6T, and ZED-F9P the solutions that were obtained reached mm in horizontal precision using a geodetic grade antenna. Similarly, the ZED-F9P model was proved at a long distance from the CORS station and presents high precision. Regarding the vertical component, in all cases where the GGM10 model was included, the vertical component is not allowed to use for topography or geodetic works, however, the horizontal component where mm precision was achieved is allowed for different highly precision survey works.

APPLICATION OF DIGITAL TWINS IN HIGH PRECISION GEOLOGICAL HAZARD SURVEY AND PREVENTION IN BEIJING

Abstract. Beijing is located in the northwest corner of the North China Plain, with a total area of 16410 km2, of which mountainous area accounts for about 61.3 % of the total area. Due to the complex geological and geomorphological conditions, the development of fault structures, the spatial-temporal uneven distribution of rainfall and the influence of human engineering activities, there are many sudden geological hazards in Beijing, such as collapse, landslide, debris flow and mining collapse. As is known, Beijing is one of the capital cities with most developed sudden geological hazard in the world. With the continuous development of economy and tourism in mountainous and shallow mountain valleys and the further enhancement of human activities, the threat of sudden geological hazard to Beijing's social and economic development will continue to exist. This paper explores the application of digital twin technology in the survey and prevention of geological hazard in Beijing, mainly using tilt aerial photogrammetry, 3D model production, remote sensing interpretation, ground analysis, database management and other methods to carry out high precision survey, mapping and investigation research. Furthermore, we analyze the relevant features of geological hazard hidden danger points, deeply study their dangers, and establish a two-dimensional and three-dimensional information management system for geological hazard in Beijing's mountainous areas. It is proved that the information management system can effectively improve the management and prevention of geological hazard.

A Critical Review on Sustainable Development of Green Smart Cities (GSCs) for Urbanization

This paper expects to dissect logical investigations zeroing in on both ecological maintainability and shrewd city ideas to discover the connection between these two. To do so, the review distinguishes data about scientists, models, structures, and devices zeroed in on the picked subjects. This examination utilizes a subjective strategy, through a precise survey of the writing, which looks at the terms, 'smart city and its sustainability', focused on maintainable improvement of smart urban communities. As per the 2030 Plan is a reasonable improvement achievement for humankind in its desire to focus on our people in the future really. Smart Urban areas assume a fundamental part in this turn of events, the turn of events heading is based, among different elements, on the satisfaction of the models set by the different Sustainable Development Objectives (SDOs). The motivation behind the ebb and flow research is to check the present status of science concerning the improvement of the SDOs in smart cities to lay out a hypothetical structure for the turn of events and mix of information well defined for a Smart City to partake in homogeneous observing of these pointers.

The Galactic underworld: the spatial distribution of compact remnants

ABSTRACT We chart the expected Galactic distribution of neutron stars and black holes. These compact remnants of dead stars – the Galactic underworld – are found to exhibit a fundamentally different distribution and structure to the visible Galaxy. Compared to the visible Galaxy, concentration into a thin flattened disc structure is much less evident with the scale height more than tripling to 1260 ± 30 pc. This difference arises from two primary causes. First, the distribution is in part inherited from the integration over the evolving structure of the Galaxy itself (and hence the changing distribution of the parent stars). Secondly, an even larger effect arises from the natal kick received by the remnant at the event of its supernova birth. Due to this kick we find 30 per cent of remnants have sufficient kinetic energy to entirely escape the Galactic potential (40 per cent of neutron stars and 2 per cent of black holes) leading to a Galactic mass-loss integrated to the present day of $\sim 0.4{{\ \rm per\ cent}}$ of the stellar mass of the Galaxy. The black hole – neutron star fraction increases near the Galactic centre: a consequence of smaller kick velocities in the former. Our simulated remnant distribution yields probable distances of 19 and 21 pc to the nearest neutron star and black hole, respectively, while our nearest probable magnetar lies at 4.2 kpc. Although the underworld only contains of order $\sim 1{{\ \rm per\ cent}}$ of the Galaxy’s mass, observational signatures and physical traces of its population, such as microlensing, will become increasingly present in data ranging from gravitational wave detectors to high precision surveys from space missions such as Gaia.

Geospatial assessment of rooftop solar photovoltaic potential using multi-source remote sensing data

Rooftop solar photovoltaics (PV) play increasing role in the global sustainable energy transition. This raises the challenge of accurate and high-resolution geospatial assessment of PV technical potential in policymaking and power system planning. To address the challenge, we propose a general framework that combines multi-resource satellite images and deep learning models to provide estimates of rooftop PV power generation. We apply deep learning based inversion model to estimate hourly solar radiation based on geostationary satellite images, and automatic segmentation model to extract building footprint from high-resolution satellite images. The framework enables precise survey of available rooftop resources and detailed simulation of power generation on an hourly basis with a spatial resolution of 100 m. The case study in Jiangsu Province demonstrates that the framework is applicable for large areas and scalable between precise locations and arbitrary regions across multiple temporal scales. Our estimates show that rooftop resources across the province have a potential installed capacity of 245.17 GW, corresponding to an annual power generation of 290.66 TWh. This highlights the huge space for carbon emissions reduction through developing rooftop PVs.

Astrometric gravitational-wave detection via stellar interferometry

We evaluate the potential for gravitational-wave (GW) detection in the frequency band from 10 nHz to $1\text{ }\text{ }\ensuremath{\mu}\mathrm{Hz}$ using extremely high-precision astrometry of a small number of stars. In particular, we argue that nonmagnetic, photometrically stable, hot white dwarfs (WD) located at $\ensuremath{\sim}\mathrm{kpc}$ distances may be optimal targets for this approach. Previous studies of astrometric GW detection have focused on the potential for less precise surveys of large numbers of stars; our work provides an alternative optimization approach to this problem. Interesting GW sources in this band are expected at characteristic strains around ${h}_{c}\ensuremath{\sim}{10}^{\ensuremath{-}17}\ifmmode\times\else\texttimes\fi{}(\ensuremath{\mu}\mathrm{Hz}/{f}_{\mathrm{GW}})$. The astrometric angular precision required to see these sources is $\mathrm{\ensuremath{\Delta}}\ensuremath{\theta}\ensuremath{\sim}{h}_{c}$ after integrating for a time $T\ensuremath{\sim}1/{f}_{\mathrm{GW}}$. We show that jitter in the photometric center of WD of this type due to starspots is bounded to be small enough to permit this high-precision, small-$N$ approach. We discuss possible noise arising from stellar reflex motion induced by orbiting objects and show how it can be mitigated. The only plausible technology able to achieve the requisite astrometric precision is a space-based stellar interferometer. Such a future mission with few-meter-scale collecting dishes and baselines of $\mathcal{O}(100\text{ }\text{ }\mathrm{km})$ is sufficient to achieve the target precision. This collector size is broadly in line with the collectors proposed for some formation-flown, space-based astrometer or optical synthetic-aperture imaging-array concepts proposed for other science reasons. The proposed baseline is however somewhat larger than the km-scale baselines discussed for those concepts, but we see no fundamental technical obstacle to utilizing such baselines. A mission of this type thus also holds the promise of being one of the few ways to access interesting GW sources in this band.

Spatial Distribution Characteristics of Seagrass Habitat Based on Remote Sensing Data: Focusing on Wan Island

In May 2019, UAV photogrammetry using drones (unmanned aircraft) was conducted to investigate the spatial distribution characteristics of the seagrass habitat in Wan Island. Wan Is. sea was divided into 3 geographical areas (Site A, B, C) by referring to the seagrass distribution identified by the National Coastal seagrass forest precision survey (Ministry of Oceans and Fisheries, 2015), and contour lines were extracted from grid depth data. In addition, a 3-D benthic topographic map using DTM (Digital Terrain Model) was created to understand the characteristics and slope of the benthic topographic map. Through the analysis of the seagrass distribution results and the water depth results, it was confirmed that the boundary between the seagrass distribution in the outer and coastal areas converges to different water depth limits (within 10 m, and within 5 m), which is estimated to be based on the characteristics of the outer sea area. As a result of the analysis of the benthic topography, it was confirmed that the slope of the well-covered distribution was relatively gentle below 0.2~0.8 degrees, and the well-covered distribution was limited to the vicinity of the boundary where the slope changed rapidly. As a result of comparing the area of the seagrass distribution survey in 2015 and 2019, it was confirmed that the area was 238.4 ha and 1,070.9 ha, respectively, which was 4.5 times more widerly when performing Drone survey than diving survey. In order to understand the surrounding environment of the seagrass distribution site, satellite image data and license fishing ground information map at the time of drone shooting (May 2019) were checked. As a result, seaweed (Kelp, Sea mustard seaweed, Seaweed, Seaweed fulvescens, etc.) and shellfish (Abalone) were densely distributed, and most of the facilities except for Seaweed fulvescens farms were separated from their habitat. Drone survey confirmed &lt;i&gt;Zostera marina&lt;/i&gt;, &lt;i&gt;Zostera caulescens&lt;/i&gt;, and &lt;i&gt;Zostera japonica&lt;/i&gt; in Wan Is., but no &lt;i&gt;Phyllospadix iwatensis&lt;/i&gt; and &lt;i&gt;Halophila nipponica&lt;/i&gt; were identified in 2015. It was confirmed that there was a limit to classifying the types of vegetation due to the characteristics of &lt;i&gt;Phyllospadix iwatensis&lt;/i&gt; attached to the rock substrate, and in the case of &lt;i&gt;Halophila nipponica&lt;/i&gt; with short leaves of 2 to 3 cm, they were not exposed to the water even at low tide, so there was a limit to detection using drones. These research results are expected to be useful data for grasping the characteristics of a wide range of seagrass habitats in other seas in the future.

Application of horizontal gravity-gradient stack for estimation of surface layer density in mountainous areas

The author proposes a new approach for analysing datasets of the differential curvature of a gravity-gradient tensor for density evaluation of the surface layer without a prior density assumption. The method, called the horizontal gravity-gradient stack–moving window correlation (HGGS-MWC) method, is based on a successive MWCs between the acquired data and the data of differential curvature responses of the surface layer calculated based on a digital elevation model. For improving the correlation, a HGGS processing method was devised and patented. It is applied to both datasets before the MWC processing. A point-source differential curvature response has the characteristic of forming a peculiar and symmetrical shape of a quadrant and distributing peaks and troughs over an underlying anomalous mass. These peaks and troughs are near or far away from their centre depending on the depth of the anomalous mass. This enables one to design a filter to enhance the responses of the surface layer. In addition, the HGGS processing affects both the contraction of the gravitational response and the attenuation of responses from deeper subsurface layers. The HGGS-MWC method leads to the production of values of the mass surface roughness ratio (MSR) in the wavenumber domain that are inherent to the measuring plane of surveys and determines the phase relation between the mass of the surface layer and the surface roughness. The MSR is a good indicator of whether a mass surplus or deficit relative to the regional average mass exists under a convex surface layer. Application to the observed datasets was performed in the area where serious landslides were triggered by the 2008 Iwate-Miyagi inland earthquake. Based on a flight height of 150 m, the mass variations of the surface layer, which is down to 300 m below the surface, are properly evaluated by analysing the wavelengths in the data mainly within the range of 270–650 m and perceivably up to 1,650 m. The specific areas can be delineated where low-density deposits, such as possible volcanic ashes and pumices associated with high water content, sit on high mountains with steep slopes. The information is useful for disaster prevention by playing a role in selecting potential areas for conducting further precise surveys. Regional density variations whose wavelengths are longer than 1,650 m remain unsolved and are an issue for future studies. With the issue solved, the results for the density distribution of the surface layer obtained by the HGGS-MWC method will serve for terrain corrections of the vertical gravity-gradient data and gravity data as well.

Current Artificial Intelligence (AI) Techniques, Challenges, and Approaches in Controlling and Fighting COVID-19: A Review.

SARS-CoV-2 (COVID-19) has been one of the worst global health crises in the 21st century. The currently available rollout vaccines are not 100% effective for COVID-19 due to the evolving nature of the virus. There is a real need for a concerted effort to fight the virus, and research from diverse fields must contribute. Artificial intelligence-based approaches have proven to be significantly effective in every branch of our daily lives, including healthcare and medical domains. During the early days of this pandemic, artificial intelligence (AI) was utilized in the fight against this virus outbreak and it has played a major role in containing the spread of the virus. It provided innovative opportunities to speed up the development of disease interventions. Several methods, models, AI-based devices, robotics, and technologies have been proposed and utilized for diverse tasks such as surveillance, spread prediction, peak time prediction, classification, hospitalization, healthcare management, heath system capacity, etc. This paper attempts to provide a quick, concise, and precise survey of the state-of-the-art AI-based techniques, technologies, and datasets used in fighting COVID-19. Several domains, including forecasting, surveillance, dynamic times series forecasting, spread prediction, genomics, compute vision, peak time prediction, the classification of medical imaging—including CT and X-ray and how they can be processed—and biological data (genome and protein sequences) have been investigated. An overview of the open-access computational resources and platforms is given and their useful tools are pointed out. The paper presents the potential research areas in AI and will thus encourage researchers to contribute to fighting against the virus and aid global health by slowing down the spread of the virus. This will be a significant contribution to help minimize the high death rate across the globe.

Photogrammetric Precise Surveying Based on the Adjusted 3D Control Linear Network Deployed on a Measured Object

In surveying engineering tasks, close-range photogrammetry belongs to leading technology by considering different aspects like the achievable accuracy, availability of hardware and software, accessibility to measured objects, or the economy. Hence, constant studies on photogrammetric data processing are desirable. Especially in industrial applications, the control points for close-range photogrammetry are usually measured using total stations. In the case of smaller items, more precise positions of control points can be obtained by deploying and adjusting a three-dimensional linear network located on the object. This article analyzes the accuracy of the proposed method based on the measurement of the linear network using a professional tape with a precision of ±1 mm. It is shown what accuracy of object feature dimensioning can be obtained based on the proposed innovative network method for photo-point measurement, using only the minimum required number of two stereo-images. The photogrammetric 3D model derived from them and captured with a non-metric camera is characterized by the highest possible precision, which qualifies the presented approach to accurate measurements used in the surveying engineering. The authors prove that the distance between two randomly optional points derived from the 3D model of a dimensioned object is equal to the actual distance measured directly on it with one-millimeter accuracy.