Analytical Processing Systems Research Articles

Feedback system for reactor process analysis

The article discusses an approach to analyzing processes in industrial reactors using advanced systems with feedback. The authors describe the system preparation and image reconstruction algorithms of ultrasonic tomographs (USTs) that have applications in industry. The research presented in this paper focuses on developing effective strategies for controlling and monitoring chemical reaction processes in reactors. Using advanced data processing techniques, the authors propose systems with feedback that enable accurate analysis and optimization of reactor operating conditions. A key aspect is ultrasonic tomographic imaging, which provides precise data on the state of the process in the reactor. In summary, the paper presents a state-of-the-art approach to analyzing chemical reaction processes in industrial reactors using advanced feedback systems and ultrasonic imaging technologies. The proposed solutions are essential for improving efficiency and process control in the chemical industry.

Performance Analysis of an Aerial Remote Sensing Platform Based on Real-Time Satellite Communication and Its Application in Natural Disaster Emergency Response

The frequency of natural disasters has increased recently, posing a huge threat to human society. Rapid, accurate, authentic, and comprehensive acquisition and transmission of disaster information are crucial in emergency response. In this paper, we propose a design scheme for an aerial remote sensing platform based on real-time satellite communication. This platform mainly includes a civilian heavy-duty unmanned aerial vehicle, ground observation system with the self-developed orthographic image stabilization device, wireless communication system with an airborne mobile communication device using Ku band, ground satellite information receiving station, and data processing and application analysis system. The image stabilization capability of the ground observation system and the communication capability of the wireless communication system were verified through ground and flight tests respectively. The results showed that the stability accuracy of the platform was better than the theoretical threshold, the system transmission rate was not less than 2 M bandwidth, the data packet loss rate was low, and the time delay was not more than 2 s. The images captured in the experiment were clear, with a resolution of less than 1cm and an overlap rate of more than 70%. These all results meet the emergency observation requirement, which indicates that the aerial remote sensing platform based on real-time satellite communication has great potential for application in natural disaster emergency response.

Thermal network model of rotary eddy current braking system for transient thermal process analysis

Thermal network model of rotary eddy current braking system for transient thermal process analysis

Expanding the intellectual capabilities of OLAP technology using neural networks

The article highlights the main characteristics, features and structure of Online Analytical Processing systems based on the same technology that perform online analytical processing of data. This technology allows analysts to explore and navigate a multidimensional indicator structure called an online analytical processing cube (data cube). Indicators (measures) of data cube play an important role in the decision-making process. To solve certain problems, these measures often need to be classified or grouped. Moreover, empty measures are common in data cube. This fact negatively affects strategic decision making. Unfortunately, online analytical processing itself is not well suited for classifying, clustering, and predicting empty measures of data cube in the presence of large data. In this regard, today there is a need to use new technologies to solve such problems. Such technologies include neural networks. The article discusses the problem of integrating online analytical processing and a neural network, showing the possibilities and advantages of such integration. It mentions that in the case of big data, the integration of OLAP and neural networks is very effective in solving problems of classification, clustering and empty measure prediction of data cube. An architectural and technological model for the integration of online analytical processing and neural networks is presented.

Investigation of three-dimensional model reconstruction and fractal characteristics of crack propagation in jointed sandstone

The presence of random joints, cracks, and other defects significantly affects the meso-damage mechanism and macro-mechanical behavior of the rock. This study employed micro-CT scanning, digital image processing (DIP), and the rock failure process analysis system (RFPA3D) to reconstruct a genuine mesostructure, creating a three-dimensional (3D) numerical model of jointed sandstone. Under uniaxial stress, this model facilitated the meso-damage evolution process of prefabricated cracks in sandstone with varying dip angles. Additionally, the influence of jointed sandstone heterogeneity and prefabricated cracks with various dip angles on its failure mode and meso-damage mechanical properties were investigated. Utilizing the MATLAB platform, a 3D box dimension algorithm was developed to analyze the fractal characteristics of the mesodamage evolution in the sample. This algorithm enabled the quantitative characterization of the meso-damage evolution of sandstone. This study categorized three types of sandstone final failure modes: composite shear failure, shear failure along the joint surface, and tensile failure. Additionally, linear variations in the elastic modulus and compressive strength of the jointed sandstone were observed with increasing prefabricated fracture inclination, highlighting significant anisotropy. The presence of joints was found to induce and control the failure mode of sandstone. The meso-damage evolution process of sandstone was described in terms of the fractal dimension, indicating that more severe damage corresponded to a larger fractal dimension. This approach offers a novel statistical method for studying the progression of rock damage.

Forester: Approximate Processing of an Imperative Procedure for Query-Time Exploratory Data Analysis in a Relational Database

Query-time Exploratory Data Analysis (qEDA) is an increasingly demanding aspect of the data analysis process that entails visually and quantitatively summarizing, comprehending, and interpreting the primary characteristics of a dataset. Nowadays, an imperative procedure is popular in relational databases for EDA because it enables us to write multiple dependent declarative queries with imperative logic. As online analytical processing (OLAP) systems contain extremely large datasets, data scientists often need quick visualizations of data, using approximate processing of imperative procedures, before analyzing them in their entirety. We identify gaps in the existing techniques, in that they are unable to sample both declarative-dependent statements and control logic at the same time and perform multi-dependent sampling-based approximate processing within the permitted time in qEDA. Traditional approximate query processing (AQP) involves tuple sampling for a single query approximation and enables queries to be executed over arbitrary random samples of tables. However, available AQP methods cannot produce a further representative sample of the data distribution for the dependent statements to estimate accurately and quickly for multiple dependent statements. On the other hand, sampling control structures, like loops and conditional statements, are discussed separately, without regard to the imperative structure of statements in a procedure. In this study, we propose Forester, a novel agile approximate processing method for imperative procedures that performs imperative program-aware sampling, which includes both statements with control regions (i.e., branch and loop) and processes them approximately within the permitted time in qEDA. Our method produces more targeted samples for each relation, while maintaining the data and control flow of dependent queries and imperative logic and determining all the conditions for a relation across all the statements in the sample that guarantee the existence of relevant data for dependent data distribution. Utilizing a workload of multi-statement imperative procedures from the Transaction Processing Performance Council Decision Support (TPC-DS) database, our experiment demonstrates that Forester outperforms the existing system in sampling, producing minimum error, and improving response time.

Modernization of electronic document management and systems analysis processes using an automated platform

In modern organizations, the use of automated platforms play a key role in optimizing electronic document management and systems analysis. This paper discusses effective electronic document management and systems analysis using an automated platform. Implementation of the development is of great importance for the company, as it helps to speed up and simplify the process of document processing, reduces the time of orders and requests, and prevents errors. In addition, the implementation of such systems can reduce personnel costs and manual processes, ensuring more efficient execution of tasks and increasing the scale of the company. The development of the system is carried out to increase the speed of document flow, resulting in increased efficiency of the company and increased business volumes.

Model Desain Sistem Informasi Pengembangan Pemasaran Hewan Qurban Berbasis Web

In Pangkalpinang City and its surroundings, people who need sacrificial animals only look for them in their area. However, currently marketing sacrificial animals can also use a web-based system. CV. Ternak Sejahtera developed its marketing system with a web system to reach customers outside Pangkalpinang. The development of this marketing system was carried out using the Rapid Application Development method which is able to accommodate user needs well and repeat the system analysis and design process if there are changes to system requirements. This web-based system is designed so that customers can view sacrificial animals and make transactions online. The system also provides installment payment facilities for customers who purchased long ago. Customers also receive a service to deliver sacrificial animals with the guarantee that the animals are in good health and meet the requirements for sacrificial animals.

Sinan the Architect’s Process of Creating Spatial Typology

The article explores the process of central planning development and dome-bearing systems analysis in mosques belonging to Classical Ottoman Architecture, focusing on the typological plan variations found in Sinan the Architect’s octagonal-based central domes. It is aimed to determine the spatial typology of these octagonal based central domes, as they play a crucial role in creating a central space in mosques. The typology studies focused on the load-bearing systems in central dome designs of eighteen surviving mosques designed by Sinan the Architect. The study method involves scanning scientific publications, state archives, and photographing mosques. Mosques ground floor plans, including their dome projections and sectional drawings, have been examined. Gathering all the data from analysing the transfer of the dome load enabled a categorisation of eighteen mosques that can be classified into two primary groups and three sub-groups within each group.

Efficient Approximation Framework for Attribute Recommendation

Trend analysis is a fundamental type of analytical query in online analytical processing (OLAP) systems. In trend analysis, a key step is to identify k valuable attributes whose distributions in two subsets under different predicates significantly differ for further investigation, where the difference is measured by metric functions. However, the exact solution that involves scanning all records is prohibitively expensive, particularly when handling large datasets in the era of big data. To minimize unnecessary data access, the existing state-of-the-art solution TopKAttr adopts sampling to avoid the expensive data scan. However, their solution still has two main drawbacks. Firstly, their solution is tailored only for two limited metric functions: the Earth Mover distance and Euclidean distance, and cannot be generalized to more complicated metric functions. Besides, their solution still aims to return the exact top-k answers via the sampling method, which still causes high running costs as shown in our experiment. Motivated by these limitations, we propose a general approximation framework for attribute recommendation that efficiently returns the top-k attributes with theoretical guarantees while supporting an extensive range of metric functions, such as the Kolmogorov-Smirnov test (KS-test), Chebyshev distance, the Earth Mover distance, Euclidean distance, and with the potential to more metrics. The key to our framework is a new bound estimation strategy that can be applied to a wide spectrum of metrics, as we listed above. Based on our estimation framework, we further devise an efficient approximation algorithm with theoretical guarantees to answer the top-k queries, which is widely used in attribute recommendation. Extensive experiments on four real large datasets show that our framework gains up to an order of magnitude speed-up and consistently high accuracy compared to TopKAttr, providing a promising alternative for attribute recommendation in OLAP systems.

Data-Quality Assessment for Digital Twins Targeting Multi-Component Degradation in Industrial Internet of Things (IIoT)-Enabled Smart Infrastructure Systems

In the development of analytics for PHM applications, a lot of emphasis has been placed on data transformation for optimal model development without enough consideration for the repeatability of the measurement systems producing the data. This paper explores the relationship between data quality, defined as the measurement system analysis (MSA) process, and the performance of fault detection and isolation (FDI) algorithms within smart infrastructure systems. This research employs a comprehensive methodology, starting with an MSA process for data-quality evaluation and leading to the development and evaluation of fault detection and isolation (FDI) algorithms. During the MSA phase, the repeatability of a water distribution system’s measurement system is examined to characterise variations within the system. A data-quality process is defined to gauge data quality. Synthetic data are introduced with varying data-quality levels to investigate their impact on FDI algorithm development. Key findings reveal the complex relationship between data quality and FDI algorithm performance. Synthetic data, even with lower quality, can improve the performance of statistical process control (SPC) models, whereas data-driven approaches benefit from high-quality datasets. The study underscores the importance of customising FDI algorithms based on data quality. A framework for instantiating the MSA process for IIoT applications is also suggested. By bridging data-quality assessment with data-driven FDI, this research contributes to the design of digital twins for IIoT-enabled smart infrastructure systems. Further research on the practical implementation of the MSA process for edge analytics for PHM applications will be considered as part of our future research.

Exploring Data Acquisition and Real-Time Analysis Algorithms in Smart Manufacturing with a Focus on Automation and Inspection Technologies

The conducted research project is based on the process followed in the smart manufacturing method. It has been observed that there are different types of methods that have been used in the smart manufacturing process and among these methods most of the methods are directly associated with different modern technology and artificial intelligence as well. Along with the inclusion of automation systems in the smart manufacturing process, the incorporation of inspection technologies is also observed in the case of performing smart manufacturing systems. In association with these, the usage of an acquisition system and real-time analysis process is also observed as well. Independent steps are present inside the phases of production process of the smart manufacturing methods. The incorporation of automation processes significantly enhances the performance of individual phases within the smart manufacturing process, thereby raising the overall production standards. Automation minimizes the likelihood of human errors, data misplacement, and mishandling. Moreover, it proves highly advantageous in the data acquisition process, ensuring error-free data transfer through automated systems.

Performance analysis of a novel biomass gasification system coupled to a coal-fired power plant based on heat and water recovery

Biomass gasification co-firing is a technology that can be implemented instantly in almost all coal-fired power plants in a relatively short period to reduce the consumption of fossil fuel. Most studies have focused on improving the system according to variations in the gasification conditions, biomass types, co-firing ratio, and boiler loads. However, the whole system process analysis and structural improvement based on the matter and energy of the co-firing system require further investigation. In this study, a novel biomass air–steam circulating fluidized bed gasification co-firing system based on waste heat and flue gas water recovery with different co-firing ratios (approximately 10 %–40 %) was simulated and compared with the original air gasification co-firing system using Aspen Plus software. The impacts of recovered water participate in gasification process and the optimal steam to biomass ratio (S/B) when it varied from 0.5 to 2, on the syngas quality, thermal characteristics of flue gas, recovered water, coal consumption, exergy loss, and efficiency of the system were analyzed. Compared with the air gasification co-firing system, the results showed that the N2 content in syngas reduced from 41.14 % to 28.92 %, and the heat yield of syngas increased by 7.73 %, along with a 110 t/h recovered water surplus at a 40 % co-firing ratio when steam to biomass ratio was equal to 1. The maximum coal saving amount was 2.26–9.11 t/h and the volume of atmospheric pollutants emissions, such as carbon dioxide (CO2), sulfur oxides (SOx) and nitrogen oxides (NOx), reduced by 0.95 %–6.02 %, 0.91 %–0.95 %, and 11.38 %–36.47 % at a co-firing ratio of approximately 10 %–40 %. Furthermore, the exergy loss can be reduced by 4.35 %–10 % with a 1.72 %–3.96 % increase in exergy efficiency, indicating that the new system mode improves the comprehensive performance of the co-firing system.

Fracture Process and Failure Characteristics of Sandstone with Different Height-to-Diameter Ratios

The mechanical properties of rock materials significantly depend on their size due to their heterogeneity and the spatial randomness of joint development—a factor often neglected in pillar design and stability analyses within mining engineering. The rock samples examined herein were 100 mm in diameter and 100 mm, 200 mm, or 300 mm in height. This research analyzed the respective mechanical phenomena and failure patterns of rock specimens with varying height-to-diameter ratios under uniaxial compression. The experiment showed that the greater the height-to-diameter ratio, the smaller the elastic modulus and compressive strength. Remarkably, as the height-to-diameter ratio grew, the failure forms of the samples transitioned from splitting to shearing, while their peak strength gradually diminished. Specifically, a hike from 1:1 to 3:1 in the height-to-diameter ratio led to a roughly 20% decrease in peak strength. Utilizing the real rock fracture process analysis system (RFPA3D), the fracture processes and failure characteristics of rock specimens with dissimilar aspect ratios were comparatively explored from a microscopic viewpoint, with acoustic emissions revealing the entire process from crack initialization to penetration. The failure analysis affirmed that the simulation results corresponded closely with the experimental findings. The resultant research can offer theoretical support for the multiscale mechanical properties, fracture processes, and prediction of rock failure in mining engineering.

Stability analysis of jointed rock mass in large underground caverns based on multi-scale analysis method

Random defects at different scales are the crucial cause of damage evolution and cascade transfer in rocks. For a large-scale underground cavern, the rock mesoscopic heterogeneity and macroscopic random joints are inevitable factors of rock stability, which needs to be further studied. In this study, a multi-scale analysis method for the stability of jointed rock mass in large underground caverns is proposed. The statistical damage theory is used to describe the mesoscopic heterogeneous rock damage. Monte Carlo simulation and measured joint geometric information are combined to reconstruct the macroscopic random joint network of rock mass. The integrated analysis of mesoscopic heterogeneity of rock and the macroscopic response of random jointed rock mass is performed by Rock Failure Process Analysis (RFPA) system. The research shows that the existence of joint affects the failure mode of rock mass and strengthens the heterogeneity. The representative elementary volume (REV) of jointed rock mass and its equivalent mechanical parameters are determined and used in the stability analysis of a large-scale underground cavern project. Results show a good agreement with the in-situ monitoring deformation of surrounding rock mass, which verifies the effectiveness of the rock mass multi-scale analysis method.

Development of the structure and methodological support of the system for analysis of the details shaping using the technological inheritability of their quality parameters

Theoretical approaches, computer modell methods and experimental studies analyse the state and behaviour of machine parts to determine the changes in their properties and parameters from a single synergetic position. Development and implementation of integrated information systems for control of technological processes of manufacturing parts and machines assembly is an essential mover of the economic growth of industrialized countries. Complicating the operational conditions for the products increases the requirements for the parameters of their accuracy, surface layer quality, performance characteristics and reliability indicators. A mechanical engineering product is a technical system consisting of many subsystems and using the functionally-oriented design of technological processes planning for parts manufacturing. The structure and methodological providing of the PSPAS-system (Product Shaping / Processing Analysis System) investigates. PSPAS system includes the investigations of the technological inheritability of mechanical engineering product quality parameters combined with the analysis of traditional subsystems (cutting, surface plastic deformation, surface layer modification, assembly). Rheological simulation modelling, holding of experimental studies, the combination of mathematical modelling, theoretical and practical studies of technological processes ensure the implementation of the CAF system using the principle of functionally-oriented design during parts manufacturing and machines assembly.

INTEGRATED POPULATED SERVICES SYSTEM USING AGILE APPROACH

The significant and uneven population growth in Indonesia in each region triggers problems for implementing development. The government has tried to overcome various population problems, one of which is using electronic media to record and update population biodata in population administration in Indonesia, namely establishing a Population Administration Information System (SIAK). The goal is that all people can be recorded and recorded accurately in the SIAK database and have a Population Identification Number (NIK) which is helpful as a reference for the government in providing public services to the community, one of which is population services at the village level. Kelurahan is a government agency under the sub-district, led by the village head. Kelurahan consists of several RW, and each RW consists of several RT. For this reason, a government agency requires a system that can assist and facilitate agency devices, so a system is needed, namely a population information system in the Village. This study aims to make an Integrated Population Information System at the Kalurahan level. The Population Information System includes data services for new residents, birth data, death data, moving data, arrival date, and marriage data. The information system is accessed using mobile devices that have easy access for residents. The software development method used is a serial waterfall which starts from the system's planning, analysis, design, and implementation process. The output of this research is an applicative work for using research-based information technology to assist population services where the Integrated Population Service System can be accessed using a mobile application. Digitized data can be used as a basis for information retrieval, one of which is the opportunity to make efforts to facilitate population services through the information collected.

СТРУКТУРНА МОДЕЛЬ СИСТЕМИ УПРАВЛІННЯ ГАЗОВИДОБУВНИМ ПІДПРИЄМСТВОМ

The proposed decomposition model of the system analysis of the management of a gas production enterprise makes it possible to implement a universal approach to the modeling of any management system of an enterprise, in particular a gas production enterprise, and makes it possible to consider three key elements: organizational elements, which include the subject of management, the object of management and external the environment of the gas production enterprise; oriented interactions between organizational elements (it is necessary to note that the direction of interaction is significant and has a clear character), which can be information-management {IC} or material (raw) {M(C)} and the characteristics of interactions, namely: information interaction – these can be certain documents, acts and other (D), for material – finished products (GP) or raw materials (C). The decomposition model of the system analysis of the management of the gas production enterprise allows to increase the control over the process of system analysis and the adoption of management decisions made by the system manager. Also, it simplifies the process of feedback interaction between the object of management and the subject of management and makes it possible to quickly react to an ineffective result. Also, a classification of the interaction between the organizational elements of the gas production enterprise management system model is proposed: 1) positive interaction and negative interaction, this type of interaction reflects the existing (positive) or absent (negative) interaction between the organizational elements of the gas production enterprise management system model; 2) smoothed interaction and threshold interaction (single-level and multi-level), where the smoothed interaction reflects the uniformity of the organizational elements of the gas production enterprise management system model, and the threshold interaction reflects the hierarchy of interaction between the organizational elements of the gas production enterprise management system model; 3) one-way interaction and two-way interaction, where one-way interaction reflects a clear subordination of feedback, while the interaction can be either vertical or horizontal with direction detailing, and two-way interaction assumes that at least two organizational elements of the gas production enterprise management system model must interact; 4) rapid interaction, restraining interaction and preventive interaction.

SYNERGETIC APPROACH TO ANALYSIS AND IMPLEMENTATION OF SOCIO-PEDAGOGICAL PRACTICES

The article is devoted to the urgent problem of identifying potential possibilities of synergetic methodology for the study of socio-pedagogical activity as a special system that is transformed under the influence of unstable conditions of society. It is emphasized that the subject area of socio-pedagogical activity is currently being transformed, characterized by an increasing trend of spontaneous socialization of children, that its spatial and temporal characteristics are changing, as the space of children's problems is expanding, the time required for scientific understanding of problems and the search for solutions to them is decreasing. The appeal to the synergetic approach is due to the fact that it is focused on the analysis of system processes that are in a nonlinear, non-equilibrium state, in the "order – chaos - order" movement. The article uses the following concepts to describe the process of organization and self-organization of socio-pedagogical activity: "attractor" (an ordered process), "fluctuation" (the presence of potential opportunities in the process both to maintain the system and to destroy it), "bifurcation" (a chaotic state of the process). At the institutional level, the movement of socio-pedagogical activity through the stages of "order - chaos - order" is determined by the value orientations of its subjects. They are the center of attraction for specialists of helping professions and keep the system in a state of stable attractor. Violation of the value bases of socio-pedagogical activity disorganizes the system, leads it into a state of chaos (bifurcation). At the individual level of teacher–child interaction, a sense of stability (attractor) is formed if the practices used to solve the child's problems give a positive result. Otherwise, the teacher plunges into reflection, looking for ways of self-organization that contributes to solving problems.

ФОРМАЛІЗАЦІЯ АЛГОРИТМУ СИСТЕМНОГО АНАЛІЗУ УПРАВЛІННЯ ГАЗОВИДОБУВНИМ ПІДПРИЄМСТВОМ

Identified parameters of the system analysis of gas production enterprise management, namely: structural analysis, which is represented by the formation of a matrix of structuring of organizational elements and their interactions (MSOE), and dynamic analysis involves the construction of a model of dynamic organizational elements and their interactions (MDOE). It is important to note that structural analysis precedes dynamic analysis and dynamic analysis is based on structural analysis. A methodology for researching the level of uncertainty of the external environment of a gas production enterprise is proposed, which is formed on the basis of structural and dynamic analysis, which allows dividing the factors of the external environment into groups and tracking their change over time. This approach to the analysis of the external environment allows you to predict the change of the factor and accordingly design a highly effective management solution. The proposed classification of models of the process of system analysis of the management of a gas production enterprise and the types of models of the process of system analysis of the management of a gas production enterprise are detailed: descriptive and calculation models of general direction; descriptive models of general directions; descriptive-calculation models of general direction with partial detailing and framework models. A complex algorithm for the system analysis of the management of a gas production enterprise is proposed, which reflects the successive stages of its implementation, leading to the adoption of a highly effective management decision when carrying out structural analysis, dynamic analysis, modeling of a management decision, testing of a management decision and, as a result, the implementation of a management decision. A timely, highly effective management decision leads the enterprise to success and vice versa. We suggest using system analysis to make highly effective management decisions, and the logical algorithm of its application reduces the time for making a management decision and guarantees the maximum result.