Data Processing Concepts Research Articles

Gcxgclab: An R Package for Two-Dimensional Gas Chromatography Preprocessing and Analysis.

Comprehensive two-dimensional gas chromatography (GC×GC) is an established technique capable of chromatographically separating thousands of analytes in complex matrices. When coupled with highly sensitive detectors such as a high-resolution mass spectrometer, these instruments produce large multidimensional data sets. A prevailing challenge for GC×GC users is efficient data handling and analysis. Although commercial software packages exist for GC×GC data analysis, these platforms are typically optimized for low-throughput qualitative data interpretation utilizing desktop computer systems. Additionally, commercial GC×GC data processing packages offer little flexibility to explore custom or novel data processing concepts. In this work, an open-source R package, called "gcxgclab", was developed as an alternative data processing package for GC×GC users and offers data preprocessing and analysis functions including baseline correction, smoothing, phase shift, peak detection, peak alignment, extracted ion chromatogram, mass spectra extraction, mass defect analysis, and targeted and nontargeted analysis. This package was designed to be customizable and allows for batch data processing on desktops or high-performance computing systems to increase the throughput. gcxgclab is available for free on the Comprehensive R Archive Network (CRAN) at https://cran.r-project.org/web/packages/gcxgclab/index.html.

Improving Understanding of Data Processing Concepts through the TARL Approach (Teaching at the Right Level) in Class 5 Students of SD Muhammadiyah 23 Surakarta

This study aims to enhance the understanding of data processing concepts among fifth-grade students at SD Muhammadiyah 23 Surakarta through the Teaching at the Right Level (TaRL) approach. The research was conducted using a Classroom Action Research (CAR) methodology, which involved two cycles, each consisting of two meetings. The primary issue identified was the low level of students' comprehension of data processing concepts, such as data collection, classification, interpretation, and the use of diagrams and tables. To address this, an active and contextual learning approach was implemented, involving real-life data collection and analysis, the use of digital tools for data visualization, and Problem-Based Learning (PBL) strategies.In the first cycle, the intervention revealed limited improvement in student engagement and learning outcomes. Consequently, the second cycle introduced revised group formations and additional instructional strategies, including ice-breaking activities. The results showed a significant improvement in student participation and understanding, with an increase in average class scores from 65 in the first cycle to 81 in the second cycle. The percentage of students meeting the learning criteria rose from 14.28% to 82.14%. This study concludes that applying TaRL, along with improved group dynamics and interactive learning methods, effectively enhances students' data processing skills and overall learning outcomes.

Telemetry System to Monitor Elastic Torque on Rolling Stand Spindles

This article outlines the relevance of building online telemetry systems for online monitoring of the technical conditions of rolling mill equipment. Electromechanical systems of the horizontal stand of the plate Mill 5000 are described, when operating in harsh conditions caused by the shock loading when workpieces enter the stand. It is noted that dynamic torque overloads, exceeding the rated motor torque by many-fold, cause the fatigue failure of spindle joints and breakage of rolls. In this regard, the development and implementation of systems for monitoring the elastic torque on spindles are extremely urgent. This issue has long been studied, but the references provide no information on the building principles and hardware composition of such systems. The use of strain gauges connected according to a balanced bridge circuit to measure the elastic torque is justified. This paper’s contribution is the proposed modular principle for building a telemetry monitoring system based on the analysis of known techniques for measuring and transmitting diagnostic data. The developed system structure is provided and the concept of data transfer and processing are explained. This article suggests the inductive power supply of a measuring unit mounted on a shaft without the use of batteries. A hardware structure was developed to be applied in a system for measuring, transmitting, and visualizing signals proportional to the elastic torque, manufactured on the basis of data measuring instruments by leading companies. The specifics of placement and connection of strain gauges are considered. The hardware providing a wireless power supply to the signal encoder and digital data transfer between the transmitter and receiver is described. The results of implementing the system on Mill 5000 are provided. The installation of a telemetry ring and a receiving head for the inductive power supply and data reception is shown. An experimental assessment of the elastic torques occurring when workpieces enter the cage was obtained by implementing a drive control algorithm which provided biting in the drive acceleration mode. The reliability of measuring the elastic torque with an error not exceeding ±5% and the reduction of dynamic loads on the spindle by 1.3–1.5 times due to the elimination of impacts from closing angular gaps in spindle joints was confirmed. This increases the service life of mechanical equipment and reduces the cost of eliminating the accident aftermath. The prospect of modifying the developed system into a cyber-physical system for monitoring the rolling mill’s mechatronic equipment conditions is shown.

A Low-Cost Test Platform for Performance Analysis of Phasor Measurement Units

In this paper, a customizable low-cost voltage waveform generator based on a real-time desktop PC and embedded data acquisition card synchronized with Coordinated Universal Time (UTC) is presented. A software approach to phase-locked loop synchronization with an external Global Positioning System (GPS) pulse signal is utilized to achieve a time uncertainty of ±1μs. This avoids expensive hardware modules for synchronization and timing purposes, which are commonly presented in literature. Besides the application for controlling the test platform, our own phasor data concentrator (PDC) application is running concurrently on the host PC. The latter is used for collecting and comparing the syncrophasor data from the test platform against the syncrophasor data measured by phasor measurement units (PMUs) under the test. The paper describes all procedures for generating reference test signals. Numerous case studies were performed, and experimental results for steady-state compliance as well as frequency ramp and phase modulation tests for dynamic compliance are presented in detail. All tests confirm that customizable test platform meets the requirements of IEEE/IEC standards. Compared to other calibrators, the cost as well as the specifications and point-by-point concept of data processing makes the described test platform suitable for performance analysis of PMU algorithms implemented on various development boards.

Automatic Generation of Assembly Instructions by Analyzing Process Recordings – A Concept Overview

The manual generation of instructions for complex assembly processes requires time and effort. Therefore, many companies refrain from documenting assembly processes and rely on the tacit expert knowledge of their employees. Due to demographic changes, the capturing of this implicit knowledge becomes increasingly relevant to prevent expertise loss. In this paper, we present a data acquisition and processing concept for the automated generation of assembly instructions. First, the assembly process is recorded using cameras. Then, the recordings are analysed combining multiple machine vision applications for object and activity recognition. Finally, the results are merged and displayed as digital assembly instructions.

Kemampuan Siswa Kelas V dalam Menyelesaikan Soal Materi Pengelolahan Data di SD Negeri Curug II

This study aims to describe the understanding of grade 5 students in learning data processing and to identify the types of errors that are often made by students. This study originates from the law of the Ministry of Learning of the Republic of Indonesia, No. 57 in 2014 on demonstrating essential skills of mathematics in specialization development, communication and life adjustment. This study used full-time and student checks of 34 students from SD. Data was collected through interviews, questionnaires and tests. Data processing includes making tables, line diagrams and bar diagrams. The results of the study show that students' understanding of data processing still needs to be improved. Common errors are conceptual errors, data usage errors, data interpretation errors, technical and input errors. Errors in the conclusions listed are common errors. Data processing education should be improved by providing a better understanding of basic data processing concepts and teaching students the proper way to use, interpret, and present data. It is also important to choose learning methods that are interactive, relevant and interesting to students. This research helps improve computer science education in grade 5 elementary schools and informs more effective learning efforts to improve students' understanding of mathematics.

Landscape Design for the South Labuhanbatu District Government Office Based on Eco-Design

The Labuhanbatu Selatan city (KLS) is a newly expanded city established in 2008. The city is currently still in the development stage and has overcome the clearing of land for settlements, plantations, and government offices. Besides the infrastructure, the city also needs a public green open space that can balance the ecosystem and human needs. The city government office is an area that can be optimized as a city park. This study aims to create a design concept and design the landscape of the KLS government office. This research was conducted using a descriptive method through a field survey and questionnaires distribution, which was done in four stages: preparation stage, data collection, data processing (concept, analysis, and synthesis), and design. The results show that KLS landscape can be improved by adding trees, shrubs, lawns, retention ponds, plazas, and benches to conserve ecology and human amenity.

Using one-dimensional convolutional neural networks and data augmentation to predict thermal production in geothermal fields

Numerical simulation is the most common method to predict reservoir production temperatures during geothermal energy extraction. Considering the principle of numerical modeling, the numerical simulation establishment process requires a large amount of good exploration data. In addition, it is heavily influenced by subsurface heterogeneity. Also, despite the superior performance of deep learning models, sparse data is a critical challenge in the training process. Therefore, we propose a one-dimensional-convolutional neural network (1D-CNN) model and use data augmentation techniques to build a large-scale multiscale production temperature data set. The network learns the nonlinear relationship between boundary conditions and production temperature from the data set and reaches the production temperature prediction for a three-well geothermal system. The maximum difference in production temperature is 1.8181 °C and the generalization performance is improved by 59.6%. It is worth noting that the excellent generalization capability indicates that the data-driven concept behind the model is an easily interpretable one. As a new data processing concept, the “data-guided approach” is a key step in establishing a universal approach for application in the geothermal field.

Real-Time Big Data Processing and Analytics: Concepts, Technologies, and Domains

In the digital era, data is one of the most important assets since it conceals valuable information. Developers of data-intensive systems have new challenges at each level of streaming, storing, and processing large quantities of data in a variety of forms and speeds. Obtaining useful information at the proper time and place is also crucial. Since the value of information is inversely proportional to time, real-time data processing and analytics are receiving more attention. Due to the importance of real-time data processing and analytics, this study focuses on real-time data processing concepts and terminology, popular technologies used in real-time data processing and analytics, popular NoSQL storage technologies used in real-time data processing, and real-time data processing application areas. The purpose of this paper is to provide researchers of real-time analysis and developers of data-intensive systems with a comparative perspective on real-time data processing by highlighting the key characteristics of real-time data processing technologies, NoSQL storage technologies, their application domains, and selected examples from previous studies.

Spin-State Modulation in FeII -Based Hofmann-Type Coordination Polymers: From Molecules to Materials.

Spin crossover complexes that reversibly interconvert between two stable states imitate a binary state of 0 and 1, delivering a promising possibility to address the data processing concept in smart materials. Thus, a comprehensive understanding of the modulation of magnetic transition between high spin and low spin and the factors responsible for stabilizing the spin states is an essential theme in modern materials design. In this context, the present review attempts to provide a concise outline of the design strategy employed at the molecular level for fine-tuning the spin-state switching in FeII -based Hofmann-type coordination polymers and their effects on the optical and magnetic response. In addition, development towards the nanoscale architectures of HCPs, i. e., in terms of nanoparticles and thin films, are emphasized to bridge the gap between the laboratory and reality.

Systematic and collaborative approach to problem solving using X-ray photoelectron spectroscopy

The methodology presented within this work is a result of years of interactions between many junior and senior X-ray Photoelectron Spectroscopy (XPS) users operating within the CasaXPS spectral processing and interpretation program framework. In particular, discussions arising from a series of workshops have been a significant source for developing the overall XPS data processing concept and are the motivation for creating this work. These workshops organized by the Institut des Matériaux Jean Rouxel (IMN), Nantes gather both experienced and novice users of XPS for a week of discourse in conceptual experiment design and the resulting data processing. However, the framework constructed and utilized within these workshops encouraged the dissemination of knowledge beyond XPS data analysis and emphasized the importance of a multi-disciplinary collaborative approach to surface analysis problem-solving. The material presented here embodies data treatment originating from data made available to the first CNRS Thematic Workshop presented at Roscoff 2013. The methodology described here has evolved over the subsequent workshops in 2016 and 2019 and currently represents the philosophy used in CasaXPS spectral data processing paradigm.

Simulation-based Evaluation of Hydrographic Data Analysis for Dune Tracking on the River Rhine

Knowledge of the static and morphodynamic components of the river bed is important for the maintenance of waterways. Under the action of a current, parts of the river bed sediments can move in the form of dunes. Recordings of the river bed by multibeam echosounding are used as input data within a morphological analysis in order to compute the bedload transport rate using detected dune shape and migration. Before the morphological analysis, a suitable processing of the measurement data is essential to minimize inherent uncertainties. This paper presents a simulation-based evaluation of suitable data processing concepts for vertical sections of bed forms based on a case study at the river Rhine. For the presented spatial approaches, suitable parameter sets are found, which allow the reproduction of nominal dune parameters in the range of a few centimetres. However, if parameter sets are chosen inadequately, the subsequently derived dune parameters can deviate by several decimetres from the simulated truth. A simulation-based workflow is presented, to find the optimal hydrographic data processing strategy for a given dune geometry.

RETRACTED: Medical wireless IoT system and nursing intervention of chronic bronchitis based on clinical data

According to the WHO (World Health Organization), the chronic obstructive pulmonary disease has become the third leading cause of death in the group. The associated health sector related to 2030 based on the curve and the long-term cost of medical expenses. Age is the leading cause of a significant occurrence. The management of stable COPD patients to mitigate the attack, it is based on his system. Chronic obstructive pulmonary disease management system, portable spirometer and things mobile applications handheld, is a clinical information database. The Internet has established the configuration. The database, one of the MBOX format, through the Zhongshan hospital, collects data from the branch of the largest medical service provider in the region, located in the stable state of the 11 pieces of data from the main hospital of the patient follow-up. Lung function data is tested via a handheld portable spirometer and can be uploaded in real time. Other smartphone applications have been developed to establish direct communication between patients and physicians to improve disease management. It is worth noting that it classifies patient clinical data, sends it, stores it anonymously, and encrypts it for protection and privacy. What is useful in treating chronic diseases based on remote monitoring is that it significantly provides health information such as medical and biosensor data volume management and big data technology, this vast new medical technology. It can be increased. The application that needs to be processed. A potential solution for new services based on the Internet of Things is used to create the concept of big data processing.

Integrative data processing for cyber-physical off-site and on-site construction promoting co-design

The term co-design describes a collaborative design process, usually across the boundaries of individual areas. A major aspect, and often an obstacle in the implementation of the co-design approach, is the establishment of a centralized data management system. In the past, the data management concept has been approached from different perspectives. Current approaches usually are oriented along the process chain and thus reflect a unidirectional flow of information. Neither the information feedback nor the reaction to adjustments in upstream model steps is supported, which makes continuous collaboration more difficult and at best reduces the co-design approach for continuous data usage. This paper addresses these weaknesses while outlining an integrative data processing concept enabling co-design between the domains of construction and industrial prefabrication.Geometrical information generated during architectural design and construction planning is reused for the production of components, manufacturing-related design adjustments are transferred back into the domain of construction. Changes throughout the entire process are centrally recorded. To ensure independence from the software tools used and to consider their great diversity, data exchange is largely based on standards, namely industry foundation classes and the standard for the exchange of product model data. In order to counteract the sequential processing according to a waterfall model and to support the co-design approach, the industrial prefabrication toolchain, consisting of computer-aided manufacturing software and downstream postprocessors, is largely automated, so that reprocessing of a workpiece for minor geometric adjustments no longer requires any interaction of the production planner.

Projection of Banking Labor Absorption Related to Technology Development in Banten Province

The role of information technology in the banking sector is very important and even impossible to separate because almost all mechanisms in the implementation and processing of data are already in the form of information where only the information technology can be completed. As an example of ATM, is a technology that applies the concept of digital-based data processing, where the component of this tool is divided into two, namely hardware and software. The hardware is the PC and the ATM device interface itself and the software that runs and manages all transaction records. The purpose of this study was to determine the effect of technological progress on community welfare, employment and economic growth in Banten Province. The research data used in this study are secondary data, namely banking data and data taken from the Central Statistics Agency for the period of 2016-2018. The results show that technological advancements result in reduced employment but community welfare and economic growth are increasing.

Semantics and pragmatics of programming language ASAMPL

This paper presents semantics and practical implementation of the domain-specific programming language ASAMPL. This programming language has been developed to support the efficient processing of multimodal data processing, in particular, the processing of multimedia content which components are evidently defined in terms of time. The data processing concept employed in ASAMPL is based on the data structures, operations, and relations defined in the algebraic system of aggregates. The paper explains the compilation approach used for this programming language as well as it presents the test results and their discussion. Problems in programming 2020; 1: 74-83

Airborne Oblique Imaging: Towards the Hybrid Era

Abstract If the use of oblique aerial camera systems is steadily growing for 3D capture of urban areas, their combination with a LiDAR unit seems to have all the potential to lead the airborne mapping sector a step forward. To fully exploit the complementary sensor behaviour, a new perspective should be adopted that looks beyond the traditional data processing chains and extends them towards an hybrid data processing concept. Assisted tie point matching, integrated sensor orientation and augmented 3D reconstruction are the keystones of a rigorous hybrid workflow for hybrid sensors. They should all rely on a deep understanding of the different properties of active and passive 3D imaging, and of the uncertainty components in their measurements. The paper will focus on the most recent answers to these issues, that open new opportunities for boosting the quality of the geospatial products w.r.t completeness, geometric quality, object detection and processing efficiency

Data Processing, Storage, and Analysis: Applying Computational Procedures to the Case of a Falling Weight Deflectomer (FWD)

In the field of civil engineering, the adoption and use of Falling Weight Deflectometers (FWDs) is seen as a response to the ever changing and technology-driven world. Specifically, FWDs refer to devices that aid in evaluating the physical properties of a pavement. This paper has assessed the concepts of data processing, storage, and analysis via FWDs. The device has been found to play an important role in enabling the operators and field practitioners to understand vertical deflection responses upon subjecting pavements to impulse loads. In turn, the resultant data and its analysis outcomes lead to the backcalculation of the state of stiffness, with initial analyses of the deflection bowl occurring in conjunction with the measured or assumed layer thicknesses. In turn, outcomes from the backcalculation processes lead to the understanding of the nature of the strains, stresses, and moduli in the individual layers; besides layer thickness sensitivity, the determination of isotropic layer moduli, and establishing estimates in the subgrade CBR. Overall, impositions of elastic and low strain conditions foster the determination of resilient modulus and the analysis of unbound granular materials. Hence, FWD data processing, analysis, and storage gain significance in civil engineering because it informs the nature of designing new pavements and other rehabilitation design options.

A Study on Development of the Camera-Based Blind Spot Detection System Using the Deep Learning Methodology

One of the recent news headlines is that a pedestrian was killed by an autonomous vehicle because safety features in this vehicle did not detect an object on a road correctly. Due to this accident, some global automobile companies announced plans to postpone development of an autonomous vehicle. Furthermore, there is no doubt about the importance of safety features for autonomous vehicles. For this reason, our research goal is the development of a very safe and lightweight camera-based blind spot detection system, which can be applied to future autonomous vehicles. The blind spot detection system was implemented in open source software. Approximately 2000 vehicle images and 9000 non-vehicle images were adopted for training the Fully Connected Network (FCN) model. Other data processing concepts such as the Histogram of Oriented Gradients (HOG), heat map, and thresholding were also employed. We achieved 99.43% training accuracy and 98.99% testing accuracy of the FCN model, respectively. Source codes with respect to all the methodologies were then deployed to an off-the-shelf embedded board for actual testing on a road. Actual testing was conducted with consideration of various factors, and we confirmed 93.75% average detection accuracy with three false positives.

Epitaxial and contamination-free Co(0001) electrodes on insulating substrates for molecular spintronic devices

The growing field of molecular spintronics is an auspicious route to future concepts of data storage and processing. It has been reported that the hybridization of the electronic structures of non-magnetic organic molecules and ferromagnetic transition-metal (FM) surfaces can form new magnetic units, so-called hybrid molecular magnets, with distinct magnetic properties, which promise molecular spintronic devices with extremely high information density and low energy consumption. The investigation and profound understanding of these device concepts require the formation of clean and epitaxial interfaces between the surface of a FM bottom electrode and molecular thin films. This can only be realized under ultra-high vacuum conditions. In addition, the FM electrodes must be grown on an insulating substrate to electrically separate neighboring devices. Here, we report on procedures to realize an entirely in-situ preparation of mesoscopic test devices featuring structurally and chemically well-defined interfaces. Au(111)-buffered Co(0001) electrodes are deposited by molecular-beam epitaxy onto sapphire or mica substrates using a shadow-mask to define the geometry. The surface quality is subsequently characterized by scanning tunneling microscopy (STM) and other surface science analysis tools. 2,7-dibenzyl 1,4,5,8-naphthalenetetracarboxylic diimide (BNTCDI), which serves as an exemplary molecule, is sublimed through another shadow-mask, and the interface formation in the monolayer regime is also studied by STM. Finally, we deposit a Cu top electrode through yet another shadow-mask to complete a mesoscopic (200 × 200 μm2) test device, which reveals in ex-situ transport measurements for the Co/BNTCDI/Cu junction non-metallic behavior and a resistance-area product of 24 MΩ·μm2 at 10 K.