Remote Method Research Articles

Assessing electronic resource searching competency among postgraduate students

Purpose This study evaluated electronic resource searching competency among postgraduate students (PGS). Specifically, the study intended to identify online search strategies used by PGS in searching electronic resources, examine the mechanisms used by PGS to access electronic resources and identify the challenges faced by PGS when searching electronic resources. Design/methodology/approach An online survey was administered to 70 PGS who attended a training workshop on scholarly literature searching. A pre- and post-training assessment was carried out to establish their competence prior to and after the training. Findings The results show that during the preassessment, the majority of respondents indicated Google search and Google Scholar search engines were their primary sources of scholarly literature, and the majority used simple search strategies to locate scholarly literature. The results further show that, before the training, it was revealed that 50.5% of the PGS had never used subscribed databases such as EBSCOhost, Emeralds, Taylor and Francis, Wiley online library and Springer. After the post-training assessment, results indicated an increased level of using new techniques such as Boolean operation, phrase searches, truncations, search limit and subject directories. Access through local IP addresses was highly used compared to other mechanisms such as remote access authentication methods or discovery services. Students’ exposure to new strategies and search tools had significant improvement in searching scholarly literature. Originality/value This paper is the researcher’s original study and it has not been conducted before. The paper represents a true analysis of the search capability of postgraduates in areas of research.

A High-Resolution Remote Sensing Road Extraction Method Based on the Coupling of Global Spatial Features and Fourier Domain Features

Remote sensing road extraction based on deep learning is an important method for road extraction. However, in complex remote sensing images, different road information often exhibits varying frequency distributions and texture characteristics, and it is usually difficult to express the comprehensive characteristics of roads effectively from a single spatial domain perspective. To address the aforementioned issues, this article proposes a road extraction method that couples global spatial learning with Fourier frequency domain learning. This method first utilizes a transformer to capture global road features and then applies Fourier transform to separate and enhance high-frequency and low-frequency information. Finally, it integrates spatial and frequency domain features to express road characteristics comprehensively and overcome the effects of intra-class differences and occlusions. Experimental results on HF, MS, and DeepGlobe road datasets show that our method can more comprehensively express road features compared with other deep learning models (e.g., Unet, D-Linknet, DeepLab-v3, DCSwin, SGCN) and extract road boundaries more accurately and coherently. The IOU accuracy of the extracted results also achieved 72.54%, 55.35%, and 71.87%.

Advances in Remote Sensing and Machine Learning Methods for Invasive Plants Study: A Comprehensive Review

This paper provides a comprehensive review of advancements in the detection; evaluation; and management of invasive plant species (IPS) using diverse remote sensing (RS) techniques and machine learning (ML) methods. Analyzing the high-resolution datasets received from drones, satellites, and aerial photography enables the perfect cartography technique and analysis of the spread and various impacts of ecology on IPS. The majority of current research on hyperspectral imaging with unmanned aerial vehicle (UAV) enhanced by ML has significantly improved the accuracy and efficiency of identifying mapping IPS, and it also serves as a powerful instrument for ecological management. The integrative association is essential to manage the alien species better, as researchers from multiple other fields participate in modeling innovative methods and structures. Incorporating advanced technologies like light detection and ranging (LiDAR) and hyperspectral imaging shows potential for improving spatial and spectral analysis approaches and utilizing ML approaches such as a support vector machine (SVM), random forest (RF), artificial neural network (ANN), convolutional neural network (CNN), and deep convolutional neural network (DCNN) analysis for detecting complex IPS. The significant results indicate that ML methods, most importantly SVM and RF, are victorious in recognizing the alien species via analyzing RS data. This report emphasizes the importance of continuous research efforts to improve predictive models, fill gaps in our understanding of the connections between climate, urbanization and invasion dynamics, and expands conservation initiatives via utilizing RS techniques. This study also highlights the potential for RS data to refine management plans, enabling the implementation of more efficient strategies for controlling IPS and preserving ecosystems.

Legal regulation of distance trading: problems and prospects

The article examines the problems of legal regulation of the remote method of selling goods in the context of the development of digital technologies and electronic commerce. Special attention is paid to the analysis of the legal features and peculiarities of remote trading, primarily using the Internet. The absence of significant administrative barriers involving strict state regulation of electronic commerce not only contributes to its development, but also, as judicial practice shows, generates negative consequences related to the protection of the rights of its participants. The author concludes that the balance of public and private interests in this case can been sured by creating a uniform terminological apparatus in the field of distance trading, more detailed regulation of the rights and obligations of its participants, and improving dispute resolution mechanisms.

A Remote-Sensing-Based Method Using Rockfall Inventories for Hazard Mapping at the Community Scale in the Arequipa Region of Peru

Small communities in the Arequipa region of Peru are susceptible to rockfall hazards, which impact their lives and livelihoods. To mitigate rockfall hazards, it is first necessary to understand their locations and characteristics, which can be compiled into an inventory used in the creation of rockfall hazard rating maps. However, the only rockfall inventory available for Arequipa contains limited data of large, discrete events, which is insufficient for characterizing rockfall hazards at the community scale. A more comprehensive inventory would result in a more accurate rockfall hazard rating map—a significant resource for hazard mitigation and development planning. This study addresses this need through a remote method for rockfall hazard characterization at a community scale. Three communities located in geographically diverse areas of Arequipa were chosen for hazard inventory and characterization, with a fourth being used for validation of the method. Rockfall inventories of source zones and rockfall locations were developed using high-resolution aerial imagery, followed by field confirmation, and then predictions of runout distances using empirical models. These models closely matched the actual runout distance distribution, with all three sites having an R2 value of 0.98 or above. A semi-automated method using a GIS-based model was developed that characterizes the generation and transport of rockfall. The generation component criteria consisted of source zone height, slope angle, and rockmass structural condition. Transport was characterized by rockfall runout distance, estimated rockfall trajectory paths, and hazard ratings of corresponding source zones. The representative runout distance inventory model of the validation site matched that of a nearby site with an R2 of 0.98, despite inventorying less than a third of the number of rockfalls. This methodology improves upon current approaches and could be tested in other regions with similar climatic and geomorphic settings. These maps and methodology could be used by local and regional government agencies to warn residents of rockfall hazards, inform zoning regulations, and prioritize mitigation efforts.

On the рossibility of multichannel optical backscattering sondes for joint balloon and lidar studies of the aerosol composition of the middle atmosphere

Aerosol backscattering sondes in the practice of aerological sounding, along with lidar observations, are used at night to study and monitor polar stratospheric clouds, tropospheric and stratospheric aerosol, cirrus clouds, pyroconvection, volcanic aerosol, as well as to verify remote methods and means of ground-based and satellite-based aerosol observations. For aerosol sondes, a simple two-wave measurement technique is used, which makes it possible to diagnose changes in aerosol composition by color index. The possibilities of the two-wave technique have limitations, which are discussed in this article. Aerological sounding combined with lidar observations expands the wavelength range for multi-wavelength studies, and direct measurements of atmospheric temperature increase the accuracy of aerosol sensing. The paper considers the application of 3 or more wavelenght techniques. Data from probe measurements using wavelengths of 470, 528, 850 and 940 nm and lidar sensing at wavelengths of 355 and 532 nm are presented.

Remote sensing to quantify potential aquifer recharge as a complementary tool for groundwater monitoring

Groundwater resources are vital for water security but face threats from overexploitation, contamination, and climate change. This study focuses on the Guarani (GAS) and Bauru (BAS) Aquifer Systems recharge in western São Paulo, Brazil. We enhanced the scalability of the Potential Recharge (PR) method and assessed recharge using Groundwater Storage (GWS) data from the Gravity Recovery and Climate Experiment (GRACE). Our findings indicate that while the remote sensing-based PR method aligns with existing literature, it tends to overestimate recharge. Conversely, the GWS method provides more conservative and reliable estimates. Integrating remote sensing-based methods is a crucial tool for improving recharge estimation and supporting groundwater resource management.

A comparative analysis of remote auditing in Albania: How it affects the quality of enterprise auditing

This paper conducts an extensive examination to explore the impact of remote auditing on audit quality. It aims to ascertain whether remote audit processes can match or exceed the standards set by traditional on-site audits. The study encompasses various remote audit methods, advantages, and challenges. The study employs a mixed methods approach, gathering and analyzing data through both quantitative measures and qualitative techniques. This includes surveys directed at audit professionals to glean insights into remote auditing and its effects on audit quality. Survey findings are analyzed according to a balance scorecard. The findings indicate that remote auditing has the potential to deliver high-quality audits but requires robust technological infrastructure, effective communication channels, and rigorous data protection protocols.

Cinereous Vulture (Aegypius monachus) Welfare Monitoring in a Breeding Center during the Breeding Season

ABSTRACT One of the conservation measures of the globally near-threatened cinereous vulture is restoring populations via translocations, with some vultures originating from breeding centers. These centers need to have reproductive success, and securing good welfare levels should be a priority due to the negative implications a compromised welfare has on reproduction. Thus, assessing welfare in breeding centers is essential. Remote methods should be preferred, such as behavior analysis and use of space using camera systems. The study’s first objective was to develop an activity budget that could be used as a baseline for detecting behavior irregularities. The second was to determine if behavior analysis and use of space could detect potential welfare issues in a breeding center. The study developed an activity budget that could be used as a standard for behavior analysis for the captive population. Behavior irregularities were detected, and the potential need to improve the enclosure and its surroundings were noticed. Altogether, the proposed methodology and results will contribute to the detection of possible welfare issues in breeding centers and, consequently, improve reproductive success and species’ conservation.

Consideration of the Impact of COVID-19 Crises on Radiation Safety: Focus on Regulatory Systems and Related Activities

Background: The radiation safety regulation system, characterized by its critical and domestically tailored features, encountered unexpected challenges due to coronavirus disease 2019 (COVID-19). Accordingly, each country implemented diverse measures to ensure the continuous efficacy of its regulatory system. This study investigates the responses of five institutions concerning radiation safety, collecting data aiming to enhance preparedness through systematic procedure.Materials and Methods: The data were extracted from official documents or websites of respective regulatory bodies (RBs) that discussed their responses to the radiation safety regulation system from COVID-19. From this data, it was observed that each country responded uniquely based on its specific conditions.Results and Discussion: Due to the repercussions of COVID-19, the regulatory system faced challenges, particularly regarding on-site inspections. In response, many countries published COVID-19 annual reports, with a few set up dedicated websites addressing its impact on the radiation regulatory frameworks. This data observed the distinct and situation-specific approaches adopted by each country in response to the pandemic. Notably, several nations introduced digital technologies into their regulations, including remote systems and online methods, while also customizing their regulatory systems according to respective circumstances.Conclusion: A variety of responses from the national RB regarding the radiation safety regulation system after the outbreak of COVID-19 highlight the importance of crisis preparedness and indicate that the current regulatory system could be enhanced.

Implementation of a Secret and Verifiable Personal Remote Electronic Election of an Agrarian Organization per the Recommendation of the Council of Europe

Lockdowns and social progress have increased hours of work from home, often requiring remote methods of communication. Agricultural organizations from associations to cooperatives to joint stock companies must prepare to carry out more activities online. This article proposes a procedure for the possible implementation of a remote electronic election in personnel matters of the organization using the Belenios system, based on an evaluation of expectations from a questionnaire survey of agricultural college students and graduates. The proposed procedure is subsequently verified based on an evaluation of compliance with the Council of Europe recommendation on standards for electronic voting.

Hybrid, blended, and hyflex learning as future models for education

The education system continuously adapts to address abnormal social fluctuations such as pandemic lockdowns, climate change, disasters, and social distractions during war, migration, and more. Remote learning methods have advantages and disadvantages, a topic of discussion among many educators. Education is a critical part of society, ensuring the well-being of humanity. Future models for education refer to potential changes and advancements in the structure, delivery, and access to education. This includes innovations in teaching methods, learning environments, technology integration, and overall educational systems. Future models for education may involve the adoption of new teaching strategies and approaches that cater to diverse learning styles and preferences. This could include personalized learning, project-based learning, and flipped classrooms, aiming to enhance student engagement, critical thinking skills, and knowledge retention. The future of education may shift towards more dynamic and interactive learning environments, which can involve the use of virtual reality, augmented reality, gamification, and immersive simulations to create attractive educational experiences. Education in the future might incorporate innovative technology as a crucial component of the learning process, the use of artificial intelligence, adaptive learning platforms, online collaboration, and digital e-learning resources for content distribution. Technology integration targets to make education more accessible and flexible to individual student needs. Research plays a crucial role in shaping the future of education by notifying evidence-based practices and guiding decision-making processes. The article is a short review that discusses and analyses the differences and preferences between remote digital methods applying during COVID-19 restrictions.

РОЛЬ РЕГИОНАЛЬНЫХ ТЕКТОНИЧЕСКИХ НАПРЯЖЕНИЙ В ГРЯЗЕВОМ ВУЛКАНИЗМЕ ЮЖНОГО САХАЛИНА

The article is devoted to the study of the tectonic stress field of Southern Sakhalin on the basis of seismological, geological, tectonophysical, GPS and remote (satellite) methods. The most characteristic type of stress state for the South of Sakhalin is latitudinal — sublatitudinal horizontal compression. The field forming the morphology of the Pugachev and Yuzhno-Sakhalinsk mud volcanoes, as well as the shape of their lithoclastite fields, fully corresponds to the nature of this state, which is confirmed by the analysis of satellite images.The images were used to supplement the results of previous researchers on the study of the directions of the gryphon bands and to measure deformation of volcano lithoclastite fields. The Pugachev volcano lithoclastite fields bend strikes 25°, and that of the Yuzhno-Sakhalinsk mud volcano strikes 30°, which well corresponds to the regional tectonic stress field. The expediency of using remote (satellite) methods as an supplement to geological and geophysical methods, in particular borehole caliper, is shown.

Adaptation of the normative rating procedure for the International Affective Picture System to a remote format

BackgroundThe Self-Assessment Manikin (SAM), a pictorial scale for the measurement of pleasure and arousal dimensions of emotions, is one of the most applied tools in the emotion research field.ObjectiveWe present a detailed description of a remote method to collect affective ratings in response to pictures by using the SAM scale.MethodsTo empirically validate our remote method, we conducted a study using a digitized version of the SAM scale and delivered online didactic instructions that followed the normative rating procedure for the International Affective Picture System (IAPS) to the participants. We presented 70 pictures from the IAPS and an additional set of 22 food pictures to the participants.ResultsWe found strong correlations between the ratings of IAPS pictures obtained in our sample and those reported by North American and Brazilian participants in previous in-person studies that applied the same pictures and methodology. We were also able to obtain an additional standardized set of food pictures.ConclusionThe protocols described here may be useful for researchers interested in collecting remotely valid and reliable affecting ratings.

Field trial of a seismoacoustic method for ice cover parameters monitoring on the Franz Josef Land archipelago

Among the physical parameters of the freezing seas ice cover, ice thickness is of key importance, and its measurement is one of the most important tasks. The increased interest in the state of the sea ice cover as an indicator of global climatic changes, as well as the growth of comprehensive development of the Arctic shelf has caused intensive development of technical and methodological bases for ice observations. Despite the great variety of approaches to ice thickness estimation, all of them are not without weaknesses. Thus, most contact methods imply direct human presence, which significantly complicates the procedure, taking into account, among other factors, the rough weather conditions of the Arctic. Remote methods depend on weather conditions and cannot always provide high spatial resolution. In this connection, it is promising to use satellite observations coupled with the results of autonomous “ground” measurements, which can be seismoacoustic data containing information on the characteristics of elastic waves propagating in the ice-covered sea, is promising. The purpose of this work is to experimentally test a new passive method for monitoring ice cover parameters along long profiles based on the analysis of natural seismoacoustic fields. The article analyzes the data of a full-scale seismoacoustic experiment with a multichannel group of geophones placed on the floating ice of Alexandra Island in the Franz Josef Land archipelago within the framework of a complex expedition of the Russian Geographical Society. The demonstrates that it is in principle possible to use flexural-gravity waves propagating in the floating ice to estimate its characteristics, both in the active mode and by analyzing the ambient noise, is demonstrated. The results of ice parameter reconstruction obtained in a nondestructive manner using seismoacoustic waves and averaged over long profiles are compared with the data of direct contact measurements. This can be further used for monitoring seasonal and multiyear variability of sea ice thickness of freezing seas, including shelf zones.

Assessment of Land Subsidence Pattern in Pokhara Valley Using Sentinel-1 InSAR Processing

This research examines the use of Sentinel-1's enhanced remote method and Interferometric Synthetic Aperture Radar (InSAR) processing to monitor ground subsidence in Pokhara Valley City, Nepal. It aims to comprehend the reciprocal effects of land sinking on environmental sustainability, infrastructure stability, and urban growth. The methodology encompasses the acquisition and processing of Sentinel-1 SAR data, along with rigorous interferometric analysis to detect and quantify ground deformation. Spanning from 2019 to 2022 AD and, -analyzing annual displacement trends, initially, a subsiding trend was observed in 2019-20 AD with an average rate of 0.037 m/year followed by 0.072 m/year in 2020-21 AD, and then escalating to 0.165 m/year in 2021-22 AD. These fluctuations in rates illustrate the intricate interplay of urbanization and geological dynamics affecting land stability in the region. The implications of this study extend to urban planning and infrastructure management, emphasizing the necessity of integrating land subsidence monitoring into the developmental policies and strategies of Pokhara Valley. Additionally, the potential of Sentinel-1 InSAR as a valuable tool for geotechnical investigations offers a non-invasive, cost-effective means to assess and monitor ground deformation risks. By leveraging the capabilities of Sentinel-1 InSAR, the study contributes to the body of knowledge in geotechnical and civil engineering fields, particularly within the context of sustainable urban planning and disaster risk reduction.

Estimating Chlorophyll-a and Phycocyanin Concentrations in Inland Temperate Lakes across New York State Using Sentinel-2 Images: Application of Google Earth Engine for Efficient Satellite Image Processing

Harmful algae blooms (HABs) have been reported with greater frequency in lakes across New York State (NYS) in recent years. In situ sampling is used to assess water quality, but such observations are time intensive and therefore practically limited in their spatial extent. Previous research has used remote sensing imagery to estimate phytoplankton pigments (typically chlorophyll-a or phycocyanin) as HAB indicators. The primary goal of this study was to validate a remote sensing-based method to estimate cyanobacteria concentrations at high temporal (5 days) and spatial (10–20 m) resolution, to allow identification of lakes across NYS at a significant risk of algal blooms, thereby facilitating targeted field investigations. We used Google Earth Engine (GEE) as a cloud computing platform to develop an efficient methodology to process Sentinel-2 image collections at a large spatial and temporal scale. Our research used linear regression to model the correlation between in situ observations of chlorophyll-a (Chl-a) and phycocyanin and indices derived from Sentinel-2 data to evaluate the potential of remote sensing-derived inputs for estimating cyanobacteria concentrations. We tested the performance of empirical models based on seven remote-sensing-derived indices, two in situ measurements, two cloud mitigation approaches, and three temporal sampling windows across NYS lakes for 2019 and 2020. Our best base model (R2 of 0.63), using concurrent sampling data and the ESA cloud masking—i.e., the QA60 bitmask—approach, related the maximum peak height (MPH) index to phycocyanin concentrations. Expanding the temporal match using a one-day time window increased the available training dataset size and improved the fit of the linear regression model (R2 of 0.71), highlighting the positive impact of increasing the training dataset on model fit. Applying the Cloud Score+ method for filtering cloud and cloud shadows further improved the fit of the phycocyanin estimation model, with an R2 of 0.84, but did not result in substantial improvements in the model’s application. The fit of the Chl-a models was generally poorer, but these models still had good accuracy in detecting moderate and high Chl-a values. Future work will focus on exploring alternative algorithms that can incorporate diverse data sources and lake characteristics, contributing to a deeper understanding of the relationship between remote sensing data and water quality parameters. This research provides a valuable tool for cyanobacteria parameter estimation with confidence quantification to identify lakes at risk of algal blooms.

Changing smiles and minds-a community-based trial on parental knowledge impact on early childhood caries.

This study was carried out in New York City over a period of twelve months for each child. 1207 children from 977 families, with clinically diagnosed ECC, were recruited. Inclusion criteria included children that had at least one filled or decayed primary tooth surface and were aged between 2 years to 6 years. Exclusion criteria included children that may have conditions that would have prevented the provision of oral hygiene habits or moderation of diet, for example children with severe autism. Families were recruited from local specialist residency programmes within the city or by direct referral from local CHWs. Evaluation of the parental education was established through use of electronic surveys at baseline level and follow up following CHWs' intervention. The data was collected between 2015 and 2017 and required follow up appointments that were completed via telephone and other remote methods. Data collection separated caries risk factors into six domains with 26 factions across the pre- and post-intervention period. These addressed both parental knowledge of the aetiology of caries and factors that can contribute to this. Domains included titles such as saliva factors, hygiene, diet, severity/susceptibility, and outcome expectations. Parents were asked to note their agreement with the statements using a four-point scale (Strongly Agree, Agree, Disagree and Strongly Disagree). The survey was made up of statements including themes of caries risk factors, and behavioural science that can contribute to caries development. Examples include 'drinking juice can cause tooth decay' and 'all kids get tooth decay'. Correct answers would be given as part of the targeted advice and education given by the CHWs at subsequent visits. Data was collected from a total of 669 parents of 977 taking part in the study. Analysis focussed on the trend of changing knowledge of parents from baseline to follow up. The analysis also assessed features of the participants including the parents' first language, education level, country of birth, average age of the children and their insurance status - this was then assessed to see if this influenced the parents' beliefs and associations. Results found there was an improvement in the parental knowledge of salivary risks for caries, hygiene input and dietary effect post intervention. The only differing result was the statement that 'tooth decay is very common' - this showed a reduced change. The study concluded that the MySmileBuddy programme did improve parental education on Early Childhood Caries and factors influencing the risk of this, though acknowledges that there should be further exploration in the clinical impact that this education would have on the patients' caries status from the CHW input.

Remote liquid level monitoring based on coda wave interferometry

Abstract Accurate monitoring of liquid level is important for both liquid stocking and related industrial procedures, it is however difficult under extreme circumstances where the inner space of the container is inaccessible or out of reach. Therefore, this paper proposes a remote liquid level monitoring method based on the use of ultrasonic coda wave interferometry. Coda waves stem from multiply scattering of elastic waves under the interactions with the boundary of propagation medium or scatters during their propagation, they are commonly observed in complex propagation medium. For having propagation trajectories much longer than the coherent waves, coda waves are capable of sampling the propagation medium repeatedly and more comprehensively, which in turn provides coda waves with higher sensitivity to its propagation medium. Letting ultrasonic waves propagate within the liquid container, which is often elastic medium, they are capable of probing the solid-liquid interface globally and repeatedly. As the changing in liquid level alters such solid-liquid interfaces inevitably, the propagation of coda wave is thus affected even without any contact with the liquid level. In this manuscript, experimental study is represented, of which the results show that waveform distortion of coda waves, estimated by remnant decorrelation coefficients, is quantitatively related with the change of liquid level, demonstrates the feasibility of remote liquid level measurement and continuous monitoring of liquid level with ultrasonic techniques.

Energetics of a World-Tour Female Road Cyclist During a Multistage Race (Tour de France Femmes).

Despite the increased popularity of female elite road cycling, research to inform the fueling requirements of these endurance athletes is lacking. In this case study, we report for the first time the energetics of a female world-tour cyclist competing in the 2023 Tour de France Femmes, an 8-day race of the Union Cycliste Internationale. The 29-year-old athlete presented with oligomenorrhea and low T3 before the race. Total daily energy expenditure assessed with the doubly labeled water technique was 7,572kcal/day (∼4.3 physical activity levels), among the highest reported in the literature to date for a female. Crank-based mean maximal power was consistent with female world-tour cyclists (5min, mean 342W, 4.8W/kg; 20min 289W, 4.1W/kg). The average daily energy intake measured with the remote food photography method (Stage Days 1-7) was 5,246kcal and carbohydrate intake was 13.7g/kg (range 9.7-15.9g/kg), and 84g/hr during stages, and an average fat intake of 15% of daily energy intake. An estimated 2,326kcal/day energy deficit was evidenced in a 2.2kg decrease in body mass. Notwithstanding the high carbohydrate intake, the athlete was unable to match the energy requirements of the competition. Despite signs of energy deficiency preexisting (oligomenorrhea and low T3), and other further developing during the race (weight loss), performance was in line with that of other world-tour cyclists and a best personal performance was recorded for the last stage. This case study emphasizes the need for further research to inform energy requirements for female athletes' optimal performance and health.