Remote Processing Research Articles

AUTOMATED SYSTEM FOR DETERMINING OF ELECTRICITY CONSUMPTION WITH ELEMENTS OF ARTIFICIAL INTELLIGENCE

Currently, Russia is moving towards automating the collection of information from metering devices for heat, gas, water, electricity, etc. Technologies are being developed that allow the transmission of resource consumption data via various communication channels, both wired and over-the-air. There are already devices and devices that allow transmitting readings of electricity metering devices over existing wired communication networks and this issue is being resolved at the legislative level, Federal Law No. 522-FZ of 07/01/2020 has been adopted. The basis for the research is to save time and effort in obtaining the necessary information to account for electricity readings from substations, increase the speed of decision-making, and be able to predict the situation with big data to identify abnormal values and eliminate them (for example, identified data from electricity meters will reduce the time labor of metering operators and economic losses of an energy supply company). The article proposes hardware and software methods for detecting data on electricity losses based on the use of artificial neural network algorithms and allowing to detect inconsistencies in commercial data readings of electric meters, which will reduce the commercial component of electricity losses. A verification calculation of an artificial neural network was performed for inconsistencies in the data on the transmitted electricity. The design of a receiving and transmitting digital module for remote data recording has been carried out, as well as the development of an automated system designed for remote collection, processing, storage and transmission of information on energy consumption and balance. The developed automated information and measurement system for remote data collection and transmission was tested at the manufacturer of smart electric energy meters with a radio channel.

Computational modeling of a surfatron mode microwave plasma in NH3/N2 for remote radical generation in a silicon native oxide cleaning process

Plasma-produced NxHy radicals facilitate the removal of native oxide layers in a semiconductor wafer surface. A remote microwave excited plasma with a NH3–N2 feed gas is used commonly to produce the active radicals. We perform a three-dimensional modeling of a microwave excited plasma operating in a surfatron mode. The device consists of a rectangular waveguide intersecting a quartz tube through which the feed gas flows. We discuss the propagation of a polarized 2.45 GHz microwave from the waveguide into the quartz tube where power is deposited into the plasma. The plasma–wave interaction is found to be highly three dimensional, with a propagating surface mode of the wave established along the dielectric tube plasma interface. Significant heating occurs on the side of the tube that directly faces the incident wave. As the flow carries the plasma-produced species down the tube, species radial profiles become increasingly diffusion controlled and axisymmetric. The dominant radicals that exit the tube are H2 and NH2, with nearly complete conversion of the feed gases to product species. The gas temperature rises above this inlet feed gas temperature and increases with increasing wave power. However, the gas temperature increase is not consequential to the overall radical yield from the plasma. The parametric study with changing pressure and input power illustrates the role of specific chemical reactions in the overall remote plasma process.

Remote Follow-up in a Heart Failure Pragmatic Trial: Insights From the CONNECT-HF

Randomized controlled trials typically require study-specific visits, which can burden participants and sites. Remote follow-up, such as centralized call centers for participant-reported or site-reported, holds promise for reducing costs and enhancing the pragmatism of trials. In this secondary analysis of the CONNECT-HF (Care Optimization Through Patient and Hospital Engagement For HF) trial, we aimed to evaluate the completeness and validity of the remote follow-up process. The CONNECT-HF trial evaluated the effect of a post-discharge quality-improvement intervention for heart failure compared to usual care for up to 1 year. Suspected events were reported either by participants or by health care proxies through a centralized call center or by sites through medical-record queries. When potential hospitalization events were suspected, additional medical records were collected and adjudicated. Among 5942 potential hospitalizations, 18% were only participant-reported, 28% were reported by both participants and sites, and 50% were only site-reported. Concordance rates between the participant/site reports and adjudication for hospitalization were high: 87% participant-reported, 86% both, and 86% site-reported. Rates of adjudicated heart failure hospitalization events among adjudicated all-cause hospitalization were lower but also consistent: 45% participant-reported, 50% both, and 50% site-reported. Participant-only and site-only reports missed a substantial number of hospitalization events. We observed similar concordance between participant/site reports and adjudication for hospitalizations. Combining participant-reported and site-reported outcomes data is important to capture and validate hospitalizations effectively in pragmatic heart failure trials.

SUSTAINABLE UNINTERRUPTED LEARNING – AN APPROACH TO BLENDED LEARNING

Education is an all-encompassing lifetime process that is fundamental to every nation’s development. The world witnessed a major shift toward education and the different ways and modes of delivery of instruction to learners during the COVID-19 pandemic. Many approaches to the teaching-learning process came into existence during this time. Different ways of remote teaching-learning processes were explored. Post-pandemic it has become essential to be ready by adding and exploring some ways of teaching-learning processes which is uninterruptable and sustainable in the long run. Blended Learning can ace the race most effectively. The recent advances in technology and its user-friendliness are an added advantage. A Blended Learning approach incorporates technology with a normal face-to-face teaching pedagogy. The Blended Learning approach helps in overcoming the idea of learning once and from one place and by one instructor. It replaces this idea and helps the process of learning to be continuous, repeated, sustainable, and joyful. Blended learning allows the learner to customize his learning experience as it facilitates the advantages of control over time and space. The students of the upper primary level are at the cusp of enjoying autonomous learning. They start taking the onus of their work and success. This makes it an appropriate time to introduce Blended Learning. A flipped learning approach was employed in the present study. The subject of science being both experimental and theoretical also caters to multiple intelligence theory. The present study focuses on checking the efficacy of the intervention (with the help of e-books) by analyzing the achievement test scores of the control group and the experimental group. Blended learning was found to be an effective and sustainable option that can ensure uninterrupted study with a well-balanced approach in the long run.

The Influence Of Professional Skeptism, Independence, Audit Fee, And Remote Audit Process On Auditor Performance

This study aims to analyze how much influence professional skepticism, independence, audit fees and remote audit processes have on auditor performance. The population in this study is KAP in Surabaya and Malang, 60 responden. The sampling method used in this study are saturated samples. Collecting data in this study by distributing questionnaires to respondents. The samples used in this study were 60 auditors who worked in 11 Public Accounting Firms (KAP) in the cities of Surabaya and Malang. The analytical method used is multiple linear regression analysis and processed using SPSS version 25. The results of this study indicate that partially professional skepticism and audit fees have a significant effect on auditor performance. Meanwhile, independence and the remote audit process have no significant effect on auditor performance. Simultaneously, professional skepticism, independence, audit fees and remote audit processes have a significant effect on auditor performance. This research is in accordance with auditing theory and has implications for how auditors' performance in KAP is more skeptical and independent, so that it can help auditors to be more vigilant in detecting fraud.

Evaluation of the Emergency Remote Teaching from Different Perspectives: Student, Faculty Member and Educational Managers’ Opinions

In this study, it was aimed to examine the perception of emergency remote teaching in the emergency remote teaching process carried out in higher education institutions during the pandemic process in the context of the perception of emergency remote teaching, roles in the emergency remote teaching process, the advantages and disadvantages aspects in this process and the measurement and evaluation process according to the opinions of students, faculty members and educational managers. For this purpose, survey forms were conducted with five students, faculty members and educational managers. Phenomenology method, one of the qualitative research methods, was used in the study. The data obtained were analyzed using content analysis technique. As a result of the analysis, it was seen that students evaluated emergency remote teaching spatially by associating it with the concepts of difference, freedom and distance, while faculty members and managers mostly looked at emergency remote teaching under the dimension of access to information. All three stakeholders in the study group stated that the most positive aspect of emergency remote teaching is that it provides access to resources such as the ability to watch the courses afterwards and access to documents at all times.

The influence of technostress on anxiety disorder in higher education students during the Covid-19 pandemic

This article aimed to investigate the relationship between technostress and anxiety disorder in Brazilian public higher education students during the COVID-19 pandemic. The quantitative study was based on primary data (n = 1981) collected through the structured questionnaire of a population of Brazilian public higher education students. Partial least squares structural equation modelling method and multigroup analysis were used for data analyses and to compare the constructs. Of the five dimensions of technostress analysed, techno-uncertainty and techno-complexity did not influence generalized anxiety disorder. Nonetheless, the results demonstrated that technostress was present in the lives of the students studied, demonstrating significant relationships with generalized anxiety disorder. Therefore, this study presents relevant reflections regarding prolonged exposure and additional factors that technology influenced students’ quality of life, thus generating strategic alignments to improve the mental health of students who went through the remote teaching process imposed by the COVID-19 pandemic.

Digital twin framework for smart greenhouse management using next-gen mobile networks and machine learning

Due to the increase in world population, arable land has been reduced. Consequently, the concept of urban greenhouses is on the rise. Smart greenhouses need to monitor physical parameters for the healthy growth of plants from remote locations. A digital twin is a representation of physical assets in the digital world, and this emerging technology has opened up opportunities for efficient system development for Industry 4.0. The digital twin receives real-time operational data to monitor the asset in the digital domain. It performs real-time processing, data analysis, and machine learning to predict optimized decisions. In the era of next-generation mobile networks, IoT devices can communicate and perform their remote operations in a timely manner. In smart greenhouse technology, the digital twin could be a revolutionary substitute for real-time remote monitoring and process management. However, there has been limited work on digital twin-driven smart greenhouse technology. In this paper, a process management framework is developed that can be interpreted as a machine learning and cloud-based data-driven digital twin for smart greenhouses. The proposed framework consists of three layers: the physical, fog, and cloud layers. The physical greenhouse measurements are monitored using a highly immersive cloud-based, real-time 3D environment. We present an example architecture using commercial cloud and open-source tools to verify the proof of concept. Additionally, different ML techniques are utilized to predict the operational requirements for smart greenhouses.

원격 음운변동중재가 읽기부진학생의 단어인지와 읽기유창성에 미치는 효과

Purpose: Communication technology and electronic devices are developing rapidly, and as many students have experienced remote education since COVID-19, the interest in the necessity and effects of telepractice has also grown in the field of speech-language pathology. Accordingly, this study aimed to investigate the effectiveness of telepractice for poor readers. Method: The subjects of the study were three 2nd-3rd grade students with poor reading. They were able to read words using the phonics principle but had difficulty reading words adapted to phonological processes. For these subjects, phonological processing intervention was conducted for 4 types of 7 coda rule, lenition, tensification, and aspiration. Both intervention and evaluation were conducted remotely using ZOOM. An intermittent multiple baseline design was applied to determine whether remote phonological processing intervention had a positive effect on the word identification of poor readers, and a pre-post design was applied to confirm improvements in reading fluency. Results: Results indicate that, following remote phonological processing intervention, all students demonstrated improvements in word identification scores compared to the baseline. Furthermore, their reading fluency scores exhibited enhancement in the post-test compared to the pre-test. Conclusion: In conclusion, the study demonstrates the effectiveness of remote phonological processing intervention for poor readers. We explored models and directions for future telepractice.

Where are the pandemic drones? On the ‘failure’ of automated aerial solutionism

In the early days of the COVID-19 pandemic, excitement broke out around the potential for drones to generate aerial solutions to devilish pandemic problems. But despite the hype, pandemic drones largely failed to take to the sky and far from the scale initially imagined. This article pursues the failure of the pandemic drone to materialise, showing how it nevertheless functioned as a locus of experimentation for remote logics and processes. As such, we shift focus away from what the pandemic drone is to if and where it – or its logics – can be found. To learn from the pandemic drone, we turn to three trajectories of failure: failure as experiment, failure as imaginary and failure as glitch. With particular attention to specific case studies, we show how failure enables drone logics and processes to migrate across various socio-technical forms, sites and applications of automated decision-making responses to the pandemic.

Multidecadal Variations in the Tropical Western Pacific Driven by Externally‐Forced AMV‐Like Changes

AbstractMultidecadal sea surface temperature (SST) variations in the tropical western Pacific (TWP) have been attributed to nonlinear external forcing and remote influences from the Atlantic Multidecadal Variability (AMV). However, the AMV resulted from both internal variability (IV) and external forcing. Thus, the origins of the TWP SST variations are not well understood. By analyzing observations and model simulations, we show that more than half of the decadal to multidecadal SST variations in TWP during 1920–2020 resulted from external forcing with the forced component correlated with AMV, while the internal component is unrelated to AMV. Furthermore, about 43%–49% of the forced AMV‐like SST variations in TWP result from remote influences of the forced AMV in the Atlantic via atmospheric teleconnection over the North Pacific, with the rest from other remote or local processes.

The Effectiveness of Distance Learning Assessment Practices: Case Study

Assessment is an essential component of the educational process as it tracks the progress of lessons, activities and facilitates learning through formative assessment or measures performance towards graduation or entry to higher levels of education or employment through summative assessment. However, increasing student enrollments in open-access educational institutions and the need for frequent assessments have led to a shift towards ICT (information and communication technologies) based remote assessment methods. The emergence of health emergencies and the strategy of Moroccan higher education has further accelerated this transition from traditional in-person assessments to remote assessments. This study uses a transversal research design to analyze the impact of distance assessment practices at Sultan Moulay Slimane University in Morocco. The research method includes the development of a benchmark for distance education evaluation methods and a statistical survey of randomly selected students (293) in eight university establishments, as well as other stakeholders involved in the remote assessment process. The objective is to determine the evaluation methodologies most appropriate to the specific context of Sultan Moulay Slimane University. Data is analyzed using descriptive statistics.

A fine digital soil mapping by integrating remote sensing-based process model and deep learning method in Northeast China

Accurate soil type maps provide an important basis for agricultural decision-making and land degradation control. In soil classification studies, the various environmental covariates are often selected based on the soil-forming framework. Since the mapping area and available observation data are limited, meteorological and vegetation cover factors have not been fully developed, and their role in soil classification needs to be evaluated. In addition, whether deep learning has out-performance in soil classification remains to be tested. The aim of this paper is to evaluate the accuracy of deep learning modelling techniques in classifying soil type using different combinations of input variables, and evaluate the importance of soil-forming variables in soil type classification. Therefore, we collected commonly used environmental covariates in Northeast China (NEC), including multiple meteorological factors and adopted a satellite-based biophysical model (Boreal Ecosystem Productivity Simulator, BEPS) to enrich vegetation cover factors. Next, four modeling strategies were developed: the soil-forming factors of soil and relief were considered as traditional environmental covariates (T), as well as combined with meteorologic variables (T + C), vegetation cover variables (T + V) and all available environmental covariates (T + C + V). Then, the effectiveness of different modeling strategies for soil classification was explored with convolutional neural network (CNN) model and multi-layer random forest (MRF) model based on soil separability. Finally, a 30 m resolution soil type map was established. The results demonstrated that both MRF and CNN can achieve high accuracy soil classification, while the CNN model performs better. The descending order of classification accuracy based on different modeling strategies of the CNN model is shown as T + C + V: 91.08%, T + V: 88.84%, T + C: 86.82%, and T: 83.96%. Meanwhile, the separability of different soil-forming factors for soil classification is soil properties, vegetation cover, temporal variation, meteorologic and relief in descending order. For Castanozems and Brown soils, MRF has higher classification accuracy, while CNN has better performance in Meadow soils and Fluvo-aquic soils. The methodology proposed in this paper aims to achieve high accuracy soil classification, provide an approach to understand the importance of soil-forming factors for the region, as well as for different soil types, and provide references for facilitating the interpretation of misclassified areas. Our results are accurate in the core areas, and therefore, this work facilitates researchers to be able to focus more on areas where different soil types intersect, thus significantly improves efficiency and saves resources, and promises to be a useful tool for future soil surveys.

AUDIOBOOKS

The area of education has so many themes that a study can branch out from different perspectives and still seem to lack an argument for so many sayings. For this reason, this article discusses a little of a pedagogical resource that is becoming a reality today, especially in a time of pandemic, in which the world was affected in the year 2020: reading in the lives of children in the remote school process. Audiobooks are new reading resources that are gaining space in schools. A different way from the usual is not about nonsense with reading, but about a new view on it; different but updated. As reading is a process in the student's life, and this does not happen immediately, the incentive of the teacher is an important part in the training of a student reader. Every child should be encouraged to know the literature so that he / she knows the importance of reading and interpreting, therefore, associating literacy and reading should be a pedagogical strategy for the teacher who seeks an adequate and continuous training process for his students. Due to the new format of Brazilian education in a pandemic era, audiobooks are used as a virtual technology tool.

Real-time performance evaluation and optimization of electrical substation equipment inspection algorithm based on distributed computing

Abstract Substation equipment inspection faces problems such as large amounts of data, various information types, complex analysis and calculations, and low resource integration. Distributed computing system uses networks to realize computer connectivity and collaboration, achieving in-depth sharing of computing resources, software resources, information resources, and communication resources. Therefore, firstly, this article introduces segmentation method for load balancing and recommendation calculation based on path search; secondly, an algorithm model for substation equipment inspection based on distributed computing is constructed; then, the article analyzes and discusses multi-core cluster task allocation, heterogeneous task scheduling framework, fragmented transmission mechanism, and vertical expansion mechanism; finally, case analysis and performance evaluation are carried out. Distributed computing has significant advantages in the inspection algorithm of power substation equipment. It can efficiently process large-scale data, improve computing power, ensure data redundancy and fault tolerance, provide good scalability, optimize resource utilization, and support remote data processing. By integrating multi-source data, distributed computing improves the accuracy and comprehensiveness of the algorithm, enhances security, supports complex algorithms such as machine learning and deep learning, and realizes real-time monitoring and early warning. The results show that the proposed algorithm can improve the efficiency of distributed parallel computing and analysis of substation equipment inspections and can simulate, evaluate, and screen substation equipment failure scenarios that may cause serious consequences within an effective time.

Application of an innovative approach to the organization of the educational process in higher education and training of applicants 073 and 281 specialties in the conditions of distance education

The study proved and substantiated the importance of innovative approaches and digitalization in the organization of the educational process of higher education. It has been found that the introduction of innovative approaches is a strategically key factor for achieving a high level of quality and efficiency of educational services. In particular, innovative technologies and digitalization allow universities to adapt to modern requirements and create flexible and accessible learning environments. 
 During the study, an analysis of differences in the interpretation of the concepts of «threat» and «risk» was conducted. In particular, it is determined that in education threats and risks can include not only financial difficulties, but also loss of reputation, low quality of education and insufficient competitiveness of graduates. It identifies the main range of problematic issues, sets of innovative approaches in higher education and highlights the principles and stages of diagnosis, which should take into account the specifics of the educational environment and the requirements of the modern labor market for its qualitative assessment. 
 In order to test the research, the article assesses and analyzes the introduction of innovative approaches in the Volodymyr Dahl East Ukrainian National University for the training of applicants 073 and 281 in the field of distance education. The strategic goals chosen to accelerate the digitalization process have been singled out and justified, considering the high standards of quality and the needs of the modern educational environment. The introduction of a digital student card, the creation of a digital educational environment and an increase in the level of digital literacy of students and teaching staff are key areas of the strategy of the Volodymyr Dahl East Ukrainian National University. In addition, innovative approaches have been developed, such as partnerships with technology companies, the creation of electronic libraries and archives aimed at supporting research activities and quality education in distance learning. 
 It provides a SWOT analysis of the Volodymyr Dahl East Ukrainian National University which highlights the main strengths and weaknesses of its functioning, as well as identifies the opportunities and threats faced by the university today in the most difficult conditions of existence. The conducted analysis allows us to draw conclusions and determine the prospects for further research in this direction. 
 In general, the study emphasizes the importance of innovation and digitalization in education as strategic factors contributing to improving the quality, efficiency, and competitiveness of educational institutions in the modern world. 
 The obtained results help to determine the optimal way to achieve the set goals, and their certification with certificates testifies to the importance and effectiveness of the chosen direction of innovative activity at Volodymyr Dahl East Ukrainian National University in the face of high requirements for remote educational process.

Rancang Bangun Aplikasi School & Campus Health Care Berbasis Mobile

The significant increase in the use of gadget devices and awareness of health, especially among college and university students, has encouraged the development of the School & Campus Health Care application. This application is an E-Health service specifically designed for the health needs of students and students, implemented via a mobile platform. In this context, the application aims to provide a solution for students who may experience health conditions that require consultation with a doctor, but cannot yet access direct services. This research focuses on developing a consultation application that allows users to get drug prescriptions from doctors virtually. Thus, it is hoped that this application can facilitate the remote health consultation process and provide easier access for students who need medical care. The result of this research is the implementation of an application that allows students to consult with doctors via a mobile platform, as well as obtain necessary drug prescriptions. Through this application, it is hoped that an efficient solution will be created in providing health services that are responsive to the needs of students and pupils in the school or campus environment.

Remote and local controls on dissolved oxygen in the Western Tropical Pacific thermocline during the last 700 kyr

The dissolved oxygen level of the low-latitude Pacific thermocline is a sensitive tracer of global ocean circulation, especially at high latitudes. However, its variability covering glacial–interglacial cycles has not been well documented. Based on the thermocline-dwelling foraminiferal population extracted from Calypso Core MD06–3047, we derived a record of the Western Tropical Pacific (WTP) thermocline oxygenation over the last 700 kyr. We found that the glacial thermocline oxygenation gradually enhanced to dome-like peaks during glacial periods, with significant relative abundance of thermocline-dwelling species minimum events. We suggest that the remote physical process of lateral O2 supply (dominated by Southern Ocean (SO) ventilation and Antarctic Intermediate Water advection, with a minor contribution of North Pacific Intermediate Water (NPIW)) and the local biological process of O2 consumption (by organic biological productivity, determined by iron supply and NPIW-driven nutrient supply) may together control the WTP thermocline oxygenation on glacial–interglacial cycles. The surprisingly synchronous co-variation indicates that SO ventilation and Antarctic Intermediate Water advection have the potential to be the primary controlling factors. Furthermore, the consistent and simultaneous dramatic increments in Marine Isotope Stages 13–11 transition and each deglacial period provide robust support for a close coupling between the global (mid-Brunhes) climatic shift scenario of SO ventilation and the WTP thermocline oxygenation.

APPLICATION OF AN ARTIFICIAL INTELLIGENCE SYSTEM TO INCREASE THE INFORMATION CONTENT OF REMOTE CONTROL OF THE OPERATION OF ON-BOARD SYSTEMS OF AIRCRAFT

This paper explores the application of artificial intelligence (AI) systems to augment the information content and efficacy of remote-control operations for on-board systems in aircraft. With the aviation industry rapidly advancing towards automation and digitalization, there is a growing need for intelligent solutions that optimize remote control processes. This study investigates various AI techniques such as machine learning, deep learning, and natural language processing to analyze vast amounts of data generated by on-board systems. By leveraging AI, this research aims to enhance the efficiency, reliability, and safety of remote-control operations in aircraft. Additionally, the paper discusses challenges, potential benefits, and ethical considerations associated with implementing AI in aviation. Through a comprehensive examination of AI applications, this research contributes to advancing the integration of intelligent technologies in aircraft operations, paving the way for more autonomous and adaptive air transportation systems.

JIRIAF: JLAB Integrated Research Infrastructure Across Facilities

The JIRIAF project aims to combine geographically diverse computing facilities into an integrated science infrastructure. This project starts by dynamically evaluating temporarily unallocated or idled compute resources from multiple providers. These resources are integrated to handle additional workloads without affecting local running jobs. This paper describes our approach to launch best-effort batch tasks that exploit these underutilized resources. Our system measures the real-time behavior of jobs running on a machine and learns to distinguish typical performance from outliers. Unsupervised ML techniques are used to analyze hardware-level performance measures, followed by a real-time crosscorrelation analysis to determine which applications cause performance degradation. We then facilitate bad behavior by throttling these processes. We demonstrate that problematic performance interference can be detected and acted on, which makes it possible to continue to share resources between applications and simultaneously maintain high utilization levels in a computing cluster. For a case study, we relocated the CLAS12 data processing workflow to a remote data processing facility, preventing file migration and temporal data persistency.