Data Processing Software Research Articles

Analisis Perhitungan Pajak Bumi dan Bangunan Berbasis Data 3D Menggunakan UAV dan LiDAR di Kecamatan Baso, Kabupaten Agam

Land and Building Tax (PBB) calculations using conventional methods often face obstacles in terms of accuracy and efficiency. This research implements UAV (Unmanned Aerial Vehicle) technology integrated with LiDAR sensors to optimize PBB calculations in Baso District, Agam Regency in 2024. The research method used is applied research with a quantitative approach, using DJI Terra and TerraSolid software for data acquisition and processing. The results showed that UAV-LiDAR technology is able to produce 3D spatial data that presents detailed information about the dimensions of tax objects, including area, volume, and height of buildings. Compared to conventional 2D methods, this technology shows significant advantages in assessing multi-storey buildings and complex structures. The resulting point cloud data supports precise object classification and more accountable tax assessment. Although its implementation requires high initial investment, the technology proves effective in improving the validity of tax object data and strengthening the PBB calculation base. This research contributes to the modernization of local taxation system through the utilization of the latest geospatial technology.

Pengaruh Current Ratio (Cr) dan Debt To Equity Ratio (Der) Terhadap Laba Bersih Pada PT Tempo Scan Pasific Tbk Periode 2012-2022

This study aims to determine the effect of Current Ratio (CR) and Debt to Equity Ratio (DER) on Net Profit at PT Tempo Scan Pasific Tbk for the 2012-2022 period, both partially and simultaneously. This type of research is quantitative and the data sources used are secondary data in the form of financial reports (annual reports), namely balance sheets and income statements. The data analysis technique for this study uses SPSS (Statistical Program For Social Science) Version 24 data processing software. The samples used in this study are balance sheets and income statements published by PT Tempo Scan Pasific Tbk for the 11-year period 2012-2022. Based on the results of the hypothesis test, it shows that the Current Ratio (CR) variable on Net Profit is tcount 3.268> ttable 2.306, meaning that the Ho1 hypothesis is rejected and Ha1 is accepted, thus there is an influence between the Current Ratio (CR) on Net Profit at PT Tempo Scan Pasific Tbk for the 2012-2022 period. Meanwhile, for the variable Debt to Equity Ratio (DER) to Net Profit is tcount 3.378> ttable 2.306 meaning that the Ho2 hypothesis is rejected and Ha2 is accepted, thus there is an influence between Debt to Equity Ratio (DER) to Net Profit at PT Tempo Scan Pasific Tbk for the period 2012-2022. Simultaneously, that Current Ratio (CR) and Debt to Equity Ratio (DER) have a significant effect on Net Profit at PT Tempo Scan Pasific Tbk for the period 2012-2022 with an Fcount value of 6.209> Ftable 4.26. The results of the determination coefficient test show that Current Ratio (CR) and Debt to Equity Ratio (DER) contribute 60.80%. So the remaining 39.20% is influenced by other variables not examined in this study.

Parallelized Event Data Management System Based on MT-SNiPER Framework and PODIO

Software framework serves as a skeleton for the offline data processing software for many high energy physics (HEP) experiments. The event data management, including the event data model (EDM), transient event store and data input/output, implements the core functionalities of the framework, and has a great impact on the performance of the entire offline software. Future HEP experiments are generating increasingly large amounts of data, bringing challenges to offline data processing. To address this issue, a common event data management system that supports efficient parallelized data processing applications has been developed based on Software for Non-collider Physics ExpeRiments (SNiPER) common software framework as well as PODIO, a common EDM toolkit for future HEP experiments. In this paper, the implementation of a parallelized event data management (PEDM) system is introduced, including the integration with MT-SNiPER and PODIO, as well as the implementation of GlobalStore to support multi-threaded event processing. Finally, the application and performance evaluation of the data management system in OSCAR (offline software of Super Tau Charm Facility) is presented.

Enhancing Data Collection Time Intervals and Modeling the Structural Behavior of Bridges in Response to Temperature Variations

The impact of temperature on bridges represents one of the main long-term challenges of structural health monitoring (SHM). Temperature is an environmental variable that changes both throughout the day and between different seasons, and its variations can induce thermal loads on bridges, potentially resulting in considerable displacements and deformations. Therefore, it is essential to obtain current data on the impact of daily and seasonal temperature variations on bridge displacements. Unfortunately, the maintenance costs associated with using precise estimates of thermal loads in a bridge design are quite high. The introduction of more accessible structural monitoring services is imperative to increase the number of observed structures. Viable solutions to make SHM more efficient include minimizing the costs of equipment, sensors, data loggers, data transmission systems, or monitoring data processing software. This research aims to improve the time intervals for collecting data on external temperature variations measured on a bridge structure through a sensor-based detection system and the integration of results into a regression analysis model. The paper aims to determine the appropriate interval for capturing and transmitting the structural response influenced by temperature variations over a year and to develop a behavioral mathematical model for the concrete structural components of a monitored bridge. The structural behavior was modeled using the statistical software TableCurve 2D, v.5.01. The results indicate that extending the data collection periods from 15 min to 4 h, in a static regime, maintains the accuracy of the regression model; instead, the effects of this integration are a significant reduction in the costs of data collection, transmission, and processing. The practical implications of this study consist of improving the monitoring of the structural behavior of bridges and the prediction under thermal stress, aiding in the design of more resilient structures, and enabling the implementation of efficient maintenance strategies.

Rapid structural analysis of bacterial ribosomes in situ

Rapid structural analysis of purified proteins and their complexes has become increasingly common thanks to key methodological advances in cryo-electron microscopy (cryo-EM) and associated data processing software packages. In contrast, analogous structural analysis in cells via cryo-electron tomography (cryo-ET) remains challenging due to critical technical bottlenecks, including low-throughput sample preparation and imaging, and laborious data processing methods. Here, we describe a rapid in situ cryo-ET sample preparation and data analysis workflow that results in the routine determination of sub-nm resolution ribosomal structures. We apply this workflow to E. coli, producing a 5.8 Å structure of the 70S ribosome from cells in less than 10 days and facilitating the discovery of a minor population of 100S-like disomes. We envision our approach to be widely applicable to related bacterial samples.

Core software for the super tau-charm facility

The Super Tau Charm Facility (STCF) is a new generation electron–positron collider, proposed to study various physics topics in the tau charm energy region. STCF will operate within a center-of-mass energy spanning 2 to 7[Formula: see text]GeV, with a peak luminosity of [Formula: see text] [Formula: see text]cm[Formula: see text]s[Formula: see text], which means STCF will produce two orders of magnitude more data compared to BESIII each year, posing great challenges for the data processing software. To support the intricate requirements from the offline data processing tasks, as well as to tackle this immense challenge caused by the huge data volume, the offline software for STCF (OSCAR) is designed and developed, based on the state-of-the-art technology and toolkits in the high energy physics community. This paper provides an overview of the design and implementation of OSCAR, highlighting its event data management system, parallel data processing capabilities leveraging SNiPER and TBB, and its geometry management framework powered by DD4hep. Presently, OSCAR is fully operational, effectively supporting the conceptual design of the STCF detector and exploring its vast physics potential.

Socio-demografske karakteristike zaposlenih i fleksibilni aranžmani rada - dokazi iz Srbije

The turbulent environment that influences the contemporary business has caused a reconfiguration of operations, where organizations have developed flexible work arrangements that involve the modification of traditional work. The goal of applying various forms of flexible work arrangements is to attract and retain talent, develop employee skills and capabilities, and become more innovative in terms of job organization. The aim of the research is to investigate differences in the use of flexible work arrangement according to socio-demographic characteristics of employees in the Republic of Serbia. The research was conducted on a sample of 582 employees, using the independent sample T-test and univariate analysis of variance (ANOVA) by using the IBM SPSS software for data processing. The research results indicated that there are statistically significant differences between employees who use flexible work arrangements according to gender, age, and level of education, and accordingly, the research hypothesis was confirmed. The scientific contribution is focused on a key segment related to the lack of scientific research on this topic in the Republic of Serbia and beyond. The results represent significant propositions for future research in this field and provide a basis for amending labor laws.

Analytical sensitivity factors from distributions of time of flight of photons for near-infrared spectroscopy studies in multilayered turbid media.

In the last years, time-resolved near-infrared spectroscopy (TD-NIRS) has gained increasing interest as a tool for studying tissue spectroscopy with commercial devices. Although it provides much more information than its continuous wave counterpart, accurate models interpreting the measured raw data in real time are still lacking. We introduce an analytical model that can be integrated and used in TD-NIRS data processing software and toolkits in real time. This is based on the so-called sensitivity factors (SFs) of the distributions of time of flight (DTOFs) of photons measured in optically turbid and semi-infinite multilayered media, such as the human head. We derived analytical expressions for the SFs that link changes in the absorption coefficient of each layer to changes in the statistical moments of DTOFs acquired in a reflectance configuration. This was later validated with results from Monte Carlo (MC) simulations, which stand as the gold standard in terms of photon migration in biological tissue. Next, we designed a couple of simulated experiments depicting how the analytical SFs can be used to retrieve absorption changes in the particular case of a five-layered medium. Comparison between theory and simulations in 2-, 5-, and 10-layered media showed very good agreement (in most cases with weighted mean absolute percentage errors below 10%). Moreover, our derivations could be run in a few milliseconds (except for the extreme case of the variance SF in the 10-layered medium), which means a speedup of up to 10,000× with respect to MC simulations, with a much better spatial resolution and without their typically associated stochastic noise. In summary, our method achieves performances similar to those given by MC simulations, but orders of magnitude faster, which makes it very suitable for its implementation in real-time applications.

GDA: a GNSS data processing software for quality analysis

GDA: a GNSS data processing software for quality analysis

The design of IMB bus data processing software

The design of IMB bus data processing software

ANALYSIS OF THE INFLUENCE OF SUBJECTIVE NORMS AND CONSUMER ANIMOSITY ON THE DECISION TO BOYCOTT ISRAEL-AFFILIATED PRODUCTS WITH BRAND JUDGMENT AS A MODERATING VARIABLE: A STUDY ON WEST JAVA MUSLIM COMMUNITY

The crimes committed by Israel on an international scale have a global impact that directly influences how Muslim consumers view and evaluate products affiliated with Israel. The aim of the research is to analyze the influence of Subjective Norms and Consumer Animosity on the West Java Muslim community's decision to boycott Israel-affiliated products with Brand Judgment as a moderating variable. This research uses a quantitative approach and collects data through survey methods. The purpose of the selection method is to select 150 respondents based on the West Java Muslim community for research purposes. This research uses the Structural Equation Modeling method assisted by SmartPLS software for data processing. The results show that Subjective Norms have a positive and significant effect on Consumer Animosity, Subjective Norms and Consumer Animosity have a significant positive effect on the Boycott Decision, while Brand Judgment is able to moderate the relationship between Consumer Animosity negatively and significantly on the Boycott Decision.

The effect of liquidity, leverage, and profitability on tax avoidance

This study was conducted with the aim of testing and analyzing the effect of liquidity, leverage, and profitability on tax avoidance. This research is a type of quantitative research with the type of data used, namely secondary data obtained from the Company's annual financial statements through the official website of the Indonesia Stock Exchange (IDX). The population of this study is a food and beverage sector company listed on the Indonesia Stock Exchange (IDX) for the period 2018-2023. Sampling was carried out using purposive sampling technique so that a sample of 13 companies was obtained that fit the criteria. The data analysis method in this study is multiple linear regression analysis with the data processing software used, namely the Statiscal Package for Social Sciences 26 (SPSS 26) program. The results of this study indicate that Liquidity, Leverage, and Profitability have a significant negative effect on Tax Avoidance.

The Effect of Capital Structure, Profitability, Liquidity, and Solvency on Firm Value with Managerial Ownership as a Moderating Variable in Food and Beverage Sub-Sector Companies Listed on the Indonesia Stock Exchange 2020-2023

The purpose of this study was to analyze how the influence of capital structure, profitability, liquidity, and solvency, can affect firm value moderated by managerial ownership in food and beverage sub-sector companies listed on the Indonesia Stock Exchange (IDX) for the period 2020-2023. This research was conducted on food and beverage sub-sector companies listed on the IDX, data information was obtained through the official website of the Indonesia Stock Exchange www.idx.com, the sampling technique used purposive sampling with a population of 94 food and beverage companies listed on the Indonesia Stock Exchange for the period 2020-2023 and a sample of 16 companies. Tests were carried out with regression panel data analysis and Moderated Regression Analysis (MRA) using E-views statistical data processing software. The results of this study indicate that liquidity and solvency variables have no significant effect on firm value, capital structure variables and profitability have a significant effect on firm value. Managerial ownership is also unable to moderate the relationship between capital structure, profitability, liquidity, and solvency on firm value.

Fintech, Social Capital and Performance of Indonesian MSMEs

This research aims to determine the influence of financial technology, financial literacy and financial inclusion on the performance of micro, small and medium enterprises (MSMEs) in Indonesia mediated by social capital. This research uses quantitative methods, assisted by SmartPLS software for data processing in structural equation modelling analysis. The contribution of this research can be used as a financial strategy for MSMEs to survive, such as testing how financial technology, social capital and financial literacy interact. The results of this research show that the use of financial technology, financial inclusion and financial knowledge can significantly influence the performance of MSMEs. In addition, social capital significantly mediates the relationship between financial technology, financial inclusion, financial knowledge and MSME performance. The results of this research provide a solid basis for creating a broad and integrated policy strategy. The success of MSMEs depends on a wise combination of fintech, financial inclusivity, financial literacy and social wealth. Therefore, policy makers, financial institutions and business people can use this information to create an environment that supports the growth and sustainability of MSMEs and makes a greater contribution to the local and national economy.

A SIMPLIFIED FREQUENCY DOMAIN BEAMFORMING APPROACH FOR ACTIVE AND PASSIVE SURFACE WAVE SURVEYS

Frequency domain beamforming (FDBF) and cylindrical frequency domain beamforming (CFDBF) techniques are among the most robust methods for extracting experimental phase velocity dispersion data from wavefields recorded during either active- or passive-source surface wave testing. Both FDBF and CFDBF transformations rely on calculating the spatiospectral correlation matrix to compute the steered power response spectrum, which is essential for extracting surface wave dispersion data. The dimensions of the spatiospectral correlation matrix are directly influenced by the frequency sampling and the number of sensors employed in the survey setup. When the number of sensors is large, and/or the frequency range is broad, and/or the frequency sampling is dense, the spatiospectral correlation matrix size leads to a greater number of required computations to calculate the steered power response spectrum for both the FDBF and CFDBF techniques. Therefore, we propose a simplified and more computationally efficient frequency domain beamforming algorithm for both active and passive surface wave surveys. This method avoids the calculation of the spatiospectral correlation matrix and its multiplication with the Hermitian transpose of the steering vector, thereby reducing the computational complexity by an order. Furthermore, by leveraging vectorization techniques, the proposed algorithm employs matrix multiplications instead of loops, significantly heightening computational efficiency. We rigorously tested the algorithm using surface wave datasets collected across diverse subsurface conditions with varying sensor arrays and acquisition parameters (e.g., sampling frequencies and window lengths) to evaluate its efficacy. The results demonstrate that our proposed algorithm outperforms the conventional FDBF method in the processing time, highlighting its practical effectiveness. This method shows promise for integration into surface wave data processing software, offering substantial improvements in computational efficiency without compromising accuracy

Информационная система поддержки принятия решений при экоинвестиционном подходе к восстановлению природных экосистем, нарушенных в ходе освоения георесурсов

A conceptual approach to the restoration of natural ecosystems is to use the idea of adaptive systematic organization of ecosystems, since the driving force of evolution is the purposeful adaptation of ecosystems based on feedback, oriented towards increasing their viability and sustainability. The Mining Institute of the KSC of RAS has justified a methodology and developed a technology for restoring natural ecosystems disrupted during geo-resources development, in accordance with the principle of their self-organization, the creation of a biologically active environment. Formation of a biologically active environment as a result of establishing a seeded cereal phytocenosis without applying a fertile layer is the essence of an eco-investment approach, which consists in increasing the energy potential of the system-forming function of biota to increase the rate of restoration of natural ecosystems. A decision support information system has been developed for an eco-investment approach to restoring natural ecosystems disrupted during the development of geo-resources based on the principle of information unity of natural and technical systems, which allows us to consider natural ecosystems as information-driven, and environmental conditions as the controlling factors. The information system integrates a set of software data processing modules to monitor the dynamics of the natural ecosystems restoration at all the stages of the soil biological organization and implements the interaction of functional modules (databases, algorithms and data processing software, geoinformation components), linking them with unified information flows, which ensures the efficiency and quality of management decisions taken based on the ecoinvestment approach to restoration of the natural ecosystems disrupted during the development of geo-resources.

Tracking the long-term timing accuracy of the X-Ray Telescope on board the Neil Gehrels Swift Observatory

Context. The Neil Gehrels Swift Observatory has been operational since November 2004. Its X-ray Telescope (XRT), operating in the 0.3–10.0 keV range, is designed to provide detailed position, timing, and spectroscopic information. Aims. The calibration procedure for assessing the absolute timing accuracy of XRT was described in a previous paper. Here we update the past analysis using the complete data set of the Crab pulsar observations up to October 2022 and using a new version of the data-processing software package that includes corrections to several issues that could have affected the previous results. Methods. We evaluate the accuracy of the Crab pulse period determination using the folding technique and the pulse-phase analysis and compare our results with the values derived from radio observations. We also check the absolute time reconstruction, measuring the phase position of the main peak in the Crab profile and comparing it with the value reported in the literature, which is based on Rossi X-Ray Timing Explorer (RXTE) observations. Results. We find that the accuracy in period determination for the Crab pulsar is of the order of a few picoseconds for the observations with the largest data time span. The absolute time reconstruction, measured using the position of the main pulse peak, shows that the main peak precedes the phase of the position reported in the literature for RXTE by ~263 µs on average. This corresponds to 0.982 in phase, with an observed dispersion of ±0.02 in phase values. We also find that observations very close in time (down to ~1 day separation) show a significant variation in absolute phase.

RESEARCH ON THE IMPACT OF HUMAN RESOURCE MANAGEMENT INTENSITY ON EMPLOYEE SERVICE INNOVATION

In the business environment of the 21st century, employees play a core role in service innovation. Their creativity directly affects the quality of service and the market performance of enterprises. Stimulating and cultivating employees' service innovation ability is an important issue in modern enterprise management. This study designed and implemented a questionnaire survey, collected 584 valid sample data for formal investigation, and used SPSS software for data processing and empirical analysis. The results revealed that the intensity of human resource management positively impacts employee service innovation, thereby enhancing the relationship between human resource management and service innovation.

Research on infrared spectral characteristics and rapid detection technology of industrial hemp

Objective: The aim of this study was to research the infrared spectroscopic features of various industrial hemp samples, establish a rapid infrared detection method for industrial hemp based on cannabidiol (CBD) content, and utilize infrared spectroscopy to differentiate industrial hemp flowers and leaves from different varieties and origins. Methods: Appropriate preprocessing was conducted on the industrial hemp samples based on their inherent characteristics. The samples were then scanned using the FTIR spectrometer, with careful subtraction of the background spectrum. A semi-quantitative rapid detection method for flowers and leaves using infrared spectroscopy was developed through partial least squares discriminant analysis. Data processing software was used to conduct principal component analysis and cluster analysis on the transmittance values of infrared characteristic absorption peaks, aiding in the identification and differentiation of samples from different varieties, origins, and harvest dates. Results: A semi-quantitative rapid detection method for industrial hemp flowers and leaves based on CBD content was successfully developed. Principal component analysis was able to clearly distinguish industrial hemp of different varieties and origins, effectively clustering samples of the same variety. This underscores the significant impact of mid-infrared spectroscopy in the identification and analysis of industrial hemp, providing an innovative approach to quickly identifying different hemp varieties.

ERGONOMICS AS A FACTOR IN ENSURING SAFETY DURING THE OPERATION OF CONSTRUCTION MACHINES ON THE EXAMPLE OF EXCAVATORS

Problem statement. To improve the safe working conditions of excavator operators, it is important to effectively manage ergonomic quality indicators, increase the reliability of excavators, and improve the sanitary and hygienic conditions and comfort of operators. The set of ergonomic indicators of the operator–excavator system, including controllability, occupancy, serviceability, masterability and manufacturability, defines the concept of ergonomics (a criterion category of quality management that is also considered as an object of management). Changes in construction affect the efficiency of the operator-excavator system, taking into account specific production and technical, natural and climatic, and socio-economic conditions. The re-equipment of construction sites with new generation excavators equipped with modern control, computer information and diagnostic systems, hardware and software for data transmission, processing and analysis not only improves the efficiency of construction work but also changes the safe nature of human-machine interaction. The purpose of the article. Ensuring safety during the operation of construction machines (excavators), taking into account ergonomics criteria, which is an urgent scientific task, the solution of which will improve working conditions and increase the efficiency of excavators. Conclusion. The conducted research has shown that the ergonomic component “man – machine – environment” on the example of improving excavators allows to increase the safety of machines and improve the working conditions of construction machine operators. The use of the mathematical apparatus of fuzzy set theory to evaluate and manage the ergonomics of excavators is due to the nature and specificity of the functioning of the elements of the “operator–excavator” system. Information about the system elements can be represented by subjective opinions or judgements, inaccurate data or errors in measurements and parameter calculations. Therefore, it is necessary to use mathematical tools that take into account quantitative and qualitative information presented in linguistic form.