Software Aspects Research Articles

Requirements Engineering at a Turning Point: Key Research Trends Shaping the Future of Systems and Software Integration

Requirements Engineering (RE) is experiencing a significant transformation that requires urgent attention and creativity from industry experts to address the challenges of future systems and software development. At the core of this evolution is Requirements Engineering (RE), an essential process that defines, records, and maintains the fundamental aspects of software and systems design. With the rapid increase in complexity and interconnectedness across different industries, the issues linked to requirements engineering are becoming more pressing, significantly affecting costs, timelines, and overall performance. This article outlines current research trends in requirements engineering, focusing on emerging challenges and future pathways. We investigate advancements in RE techniques, methodologies, and tools, assessing their effects on building complex systems. Furthermore, we emphasize the growing significance of stakeholder engagement and agile practices in shaping requirements, highlighting their contributions to improving collaboration and adaptability. By evaluating the present state of practice and pinpointing critical areas of research concern, this article offers a guide for future requirements engineering studies, enabling researchers and practitioners to address the changing needs of software and systems engineering.

Image super-resolution reconstruction of vast-receptive-field pixel attention for precision measurement

Abstract Compared with traditional contact precision measurement, vision-based non-contact precision measurement has the features of low cost and flexible multi-point information extraction, but how to ensure the measurement accuracy of vision-based non-contact precision measurement is an urgent problem. Traditional thinking often focuses on hardware upgrades to improve image resolution, but this brings high costs and is limited by the physical characteristics of the hardware itself. In this paper, we start from the software aspect to improve the image resolution by using the super-resolution reconstruction algorithm and propose an image super-resolution reconstruction algorithm—Swin Transformer with a Vast-receptive-field Pixel Attention, which combines the vast-receptive-field pixel attention mechanism with the Swin Transformer self-attention mechanism, focuses on the learning of the high-frequency information features of the image. Experiments are conducted both in public datasets and real measurement images. Extensive experimental validation shows that the model can obtain more edge and high-frequency detail features in public datasets, and the objective evaluation index on Set5, Set14, B100, Urban100, and Manga109 datasets is improved by 0.06 dB on average compared with the existing algorithms. In actual measurements, the algorithm in this paper for USAF1951 resolution tablet, image super-resolution reconstruction image in the horizontal and vertical direction of the measurement accuracy increased by an average of 6.97%, the horizontal and vertical direction of the relative measurement accuracy of an average of 30.20% improvement. This study provides a potential development direction for vision-based non-contact precision measurement.

1D-CNN-Transformer for Radar Emitter Identification and Implemented on FPGA

Deep learning has brought great development to radar emitter identification technology. In addition, specific emitter identification (SEI), as a branch of radar emitter identification, has also benefited from it. However, the complexity of most deep learning algorithms makes it difficult to adapt to the requirements of the low power consumption and high-performance processing of SEI on embedded devices, so this article proposes solutions from the aspects of software and hardware. From the software side, we design a Transformer variant network, lightweight convolutional Transformer (LW-CT) that supports parameter sharing. Then, we cascade convolutional neural networks (CNNs) and the LW-CT to construct a one-dimensional-CNN-Transformer(1D-CNN-Transformer) lightweight neural network model that can capture the long-range dependencies of radar emitter signals and extract signal spatial domain features meanwhile. In terms of hardware, we design a low-power neural network accelerator based on an FPGA to complete the real-time recognition of radar emitter signals. The accelerator not only designs high-efficiency computing engines for the network, but also devises a reconfigurable buffer called “Ping-pong CBUF” and two-level pipeline architecture for the convolution layer for alleviating the bottleneck caused by the off-chip storage access bandwidth. Experimental results show that the algorithm can achieve a high recognition performance of SEI with a low calculation overhead. In addition, the hardware acceleration platform not only perfectly meets the requirements of the radar emitter recognition system for low power consumption and high-performance processing, but also outperforms the accelerators in other papers in terms of the energy efficiency ratio of Transformer layer processing.

Development Status of Integrated PET/MR Products

Integrated PET/MR is one of cutting-edge technologies in functional and molecular imaging. A review of the current development status of integrated PET/MR products can provide inspiration and promote the development of related fields. This study introduced the technical characteristics and research and development difficulties of integrated PET/MR products from both hardware and software aspects, summarized the publication of English and Chinese papers related to the clinical application of PET/MR products from 2008 to 2022, analysed the differences and current status of clinical application of integrated PET/MR products at home and abroad, and pointed out the development status and direction of integrated PET/MR products in China. Finally, the development of integrated PET/MR products was discussed in terms of technology, clinical application prospects, and market strategies.

Electronic Load Device for Testing DC Power Supply

The project deals with a programmable electronic load device capable of dynamic variations of its load parameters to simulate a myriad of electrical conditions. Hence, one of the objectives of this paper is to implement, in a designed setup, variously heated loads, such as constant current, voltage, resistance, and power modes. That said, the designed system has hardware and software aspects that integrate advanced microcontroller capabilities so that high accuracy is assured through a series of test procedures on the system. The hardware design of the project encompasses choosing various resistors and relays modules (ESP32), selection of the proper power supplies, and microcontrollers. A program is being developed in the Arduino IDE that will program the microcontroller to do dynamic load control.It all began with the circuit design and resistor value choice, taking into consideration their power rating about effective heat dissipation. Dynamic loading control by the ESP32 microcontroller allows variable changes which are automatic in nature. On top of this, relay modules were used for effective switching of load and its adjustments, hence making the system flexible and responsive. The firmware developed in Arduino IDE automates control processes, which enables the smooth running of operations. In this regard, our experiments output results that show the device—a programmable electronic load mimicking load situations and providing performance information. Notably, the automated control system coupled with adjustable load capabilities increased the testing process efficiency and accuracy to a great deal. The overall effect of the programmable electronic load device is that it makes testing more professional by way of automation and provision of precise management for the test settings of the load. Its versatility also provides simulation of a wide scope of scenarios accommodating test conditions. It is designed to cater to heat regulation and power dispersion for the reliability of performance whiles in operation

Free open source communities sustainability: Does it make a difference in software quality?

ContextFree and Open Source Software (FOSS) communities’ ability to stay viable and productive over time is pivotal for society as they maintain the building blocks that digital infrastructure, products, and services depend on. Sustainability may, however, be characterized from multiple aspects, and less is known how these aspects interplay and impact community outputs, and software quality specifically.ObjectiveThis study, therefore, aims to empirically explore how the different aspects of FOSS sustainability impact software quality.Method16 sustainability metrics across four categories were sampled and applied to a set of 217 OSS projects sourced from the Apache Software Foundation Incubator program. The impact of a decline in the sustainability metrics was analyzed against eight software quality metrics using Bayesian data analysis, which incorporates probability distributions to represent the regression coefficients and intercepts.ResultsFindings suggest that selected sustainability metrics do not significantly affect defect density or code coverage. However, a positive impact of community age was observed on specific code quality metrics, such as risk complexity, number of very large files, and code duplication percentage. Interestingly, findings show that even when communities are experiencing sustainability, certain code quality metrics are negatively impacted.ConclusionFindings imply that code quality practices are not consistently linked to sustainability, and defect management and prevention may be prioritized over the former. Results suggest that growth, resulting in a more complex and large codebase, combined with a probable lack of understanding of code quality standards, may explain the degradation in certain aspects of code quality.

Modeling Enterprise Software with UAF

AbstractSystems and Software Engineers often have an uneasy relationship. The job of the systems engineer is to work with the stakeholders to define a set of requirements that meet their needs. These are then allocated to various solution spaces such as electronic hardware, mechanical, procedural, and software among others. For many systems, the functional requirements are almost exclusively software requirements. Correspondingly, as an increasing amount of project manpower, schedule time, and budget are allocated to software, it becomes increasingly important that systems and software engineers communicate effectively. The Systems Modeling Language (SysML) has helped in this regard in that it can provide executable behavioral models with precise semantics to express software requirements in a model. These models define “What is required” without overly constraining the implementation. In addition, SysML can be used to define performance constraints, required concurrency, hardware memory and processor budgets, interfaces, safety critical requirements, etc. These aspects are essential for software engineers to understand the constraints and limitations of their environment. At the System of Systems (SoS)/Enterprise level, defining software/systems employs a similar pattern, but at a higher level of abstraction. In the Unified Architecture Framework, capabilities are defined for the enterprise, with systems and software allocated to realize the capabilities. In the same way that capabilities depend on one another, the implementing systems and software interact to support each other. In the past, enterprise software would be modeled as residing in mainframes in a federated software pattern. Modern software can be modeled throughout the enterprise in a distributed network that can adapt to the changing needs of the enterprise to do load leveling, dynamic and late binding, reconfiguration, and reallocation of hardware resources as necessary. If the domain includes the Industrial Internet of Things (IIOT), then deployment could include edge devices, embedded software, Programmable Logic Controllers (PLC), PCs, servers, cloud computing, and of course mainframes. The Object management Group (OMG) Data Distribution Services (DDS) standard enables these capabilities across these devices in a universal format implemented by multiple vendors. However, before this complex system of systems can be implemented, it must first be architected and designed to ensure that it will be fit for purpose both now and as the complex system of systems expands and evolves. This paper will examine the aspects of modeling software in the UAF, and how it can help guide enterprise and system and software architecture.

Design of an electronic device in the STEAM context to relate results of physical measurements with sounds, and its analysis through science teachers' perception

This work presents the design and details of an electronic system that uses software and hardware aspects to generate sound frequencies associated with the measurement of physical phenomena, such as temperature or other. It has potential to create fun and motivation activities in the classroom, encouraging the students to think about the association between scientific and technological aspects. It is based on a STEAM (Science, Technology, Engineering, Arts, and Mathematics) approach where an Arduino processing board measures a physical phenomenon value with a sensor, computes a mathematical relationship to define an associated sound frequency, and next sends an output signal to excite a speaker. The proposed electronic system is simple, but this subject may not be very familiar to many science teachers and, therefore, this article explains it step by step to allow its effective understanding and later usage in the classroom. Furthermore, this article also presents a discussion with science teachers in order to analyze their perception when they are challenged to understand and analyze the proposed system under a teaching perspective, which emphasized concernments such as the lack of training and materials, but positively indicates the proposal is feasible and has a satisfactory teaching potential.

Development of fault location functions in a real digital fault recorder: Computational strategies and validation

This paper shares experiences acquired during the development of a fault location module (FLM) in a real Digital Fault Recorder and Phasor Measurement (DFRPM) device, which has been designed for the Itaipu utility, Brazil. Hardware and software aspects, as well as computational strategies and innovative solutions used to implement the FLM are addressed. The DFRPM fault location module (DFRPM-FLM) is validated by means of simulations in a Real-Time Digital Simulator, considering fault scenarios in high- and low-inertia systems. The case studies reveal that the adopted computational strategies resulted in a flexible and reliable DFRPM-FLM, which showed to be able to automatically estimate the fault location, without the need for human intervention.

Machine Design and Development of CoreXY FDM 3D Printer for Learning

This research aims to design and develop CoreXY FDM 3D Printer that can be optimized for learning purposes. By detailing aspects of design, hardware, and software, this research is expected to make a significant contribution in improving the quality of learning. Research using the Research and Development method, carried out based on the Machine Learning System Development model with stages in the form of Problem Understanding, Data Handling, Model Building, and Model Monitoring. The results showed that the lowest average depreciation value in the 3D printer developed was smaller than the 3D Printer machine from the previous study. The best print quality was produced in experiment number 3 where the print results were almost flat and smooth. So that the best print parameters are produced at a layer thickness of 0.1 mm and a print speed of 60 mm / minute. Blackbox Test results show that all components of the 3D printer machine have been able to function properly. The results of the user trial questionnaire showed that the average value of all aspects received a value of 3.55 from a range of values 1-4, indicating that this machine is very good to be used as a medium in the learning process. Comparison of FDM CoreXY 3D Print printing process time after development shows shorter print time than FDM CoreXY 3D Printer machine before development.

Towards improving aspect-oriented software reusability estimation

Nowadays, large numbers of organizations may opt for Aspect-Oriented Programming (AOP), which is an enhancement to Object-Oriented Programming (OOP). This is due to the addition of a number of concepts that have assisted in the production of more flexible and reusable components. One of the most important elements added by AOP is software reuse, which is based on reusability attributes. These attributes indicate the possibility of reusing one or more components in the development of a new system. It is one of the most essential attributes to evaluate the quality of a system’s components. Thus far, little attention has been paid to the process of measuring AOP reusability, and it has not yet been standardized. The objective of the current study is to come up with a reasonable measurement for AOP software reuse, which is simultaneously a significant topic for researchers while offering several advantages for organizations. Although numerous models have been built to estimate the reusability of software, most of them are not dedicated to Aspect-Oriented Software (AOS). In this study, a model has been designed for AOS reusability estimation and measurement based on a new equation depending on five attributes that have a range of positive and negative impacts on AOS reusability. Three of those attributes, namely coupling, cohesion, and design size, have been included in previous studies. This study proposes complexity and generality as two new attributes to be considered. Each of these attributes was measured based on the metrics also proposed in this study. A new equation to calculate AOS reusability was constructed based on the most important reusability attributes and metrics. Seven aspect projects were employed as a case study to apply the proposed equation. After the proposed equation was applied to the selected projects, we obtained new values of reusability to compare with the values that resulted from applying the previous equation. The fact that new values emerged indicates that the proposed reusability metrics and attributes had a significant effect.

Development of a web-based patient decision aid for myopia laser correction method

BackgroundIn the context of healthcare centered on the patient, Patient Decision Aids (PtDAs) acts as an essential instrument, promoting shared decision-making (SDM). Considering the prevalent occurrence of myopia, the objective of this study is to furnish exhaustive and easily comprehensible information to assist patients in making well-informed decisions about their options for myopia laser correction.MethodThe research team developed a decision guide for myopia patients considering laser correction, aiming to facilitate informed decisions. The study followed the first four stages of the IPDAS process model: “scope/scoping,” “design,” “prototype development,” and “alpha testing.” Ten semi-structured interviews with patients (n = 6) and corneal specialist ophthalmologists (n = 4) were conducted to understand the challenges in selecting a laser correction method. Online meetings with 4 corneal specialists were held to discuss challenging cases. A comparison table of harms and benefits was created. The initial prototype was developed and uploaded on the internet portal. User feedback on software and text aspects was incorporated into the final web software, which was reviewed by a health education expert for user-friendliness and effectiveness.ResultEducational needs assessment revealed concerns such as pain, daily life activities, return to work, the potential need for glasses (‘number return’), eye prescription stability, and possible complications. These shaped the decision aid tool’s content. Expert consensus was achieved in several areas, with some items added or extended. In areas lacking consensus, comments were added for clarity. Five clients assessed the web app (PDAIN), rating it 46/50 in user-centricity, 47/50 in usability, and 45/50 in accuracy and reliability, totaling 138/150. Post-piloting, software errors were documented and rectified. During the trial phase, five myopic users interacted with the software, leading to modifications. User feedback indicated the tool effectively enhanced understanding and influenced decision-making.ConclusionPDAIN, serves as a facilitative tool in the process of selecting a corneal laser correction method for myopic patients. It enabling Nearsighted patients to make informed decisions.

АРХІТЕКТУРА СИСТЕМИ АВТОНОМНОГО КЕРУВАННЯ ДЛЯ FPV-ДРОНІВ

Drone technologies and robotic systems, that can be used to optimize or replace human labor in different areas, are continuing to develop and expand their area of application. Computational hardware, that can be used as an extension to basic drone hardware, is becoming more powerful for a smaller price and size. Autonomous drone control provides a practical solution for issues that are present when a drone is controlled manually by an operator. There are limitations that exclude the possibility of operator control and some solutions are much less effective if there is no autonomous algorithm. A large distance, radio interference or a huge amount of data to be analyzed are not as critical if a drone is capable to make decisions autonomously without an operator. Because of the features of a basic amateur FPV-drone its flight controller does not operate enough computing power to execute complex algorithms such as object detection, object tracking, calculation of a proper trajectory etc. In cases like this a companion computer should be used. Depending on an area of application, drone control algorithms may vary. Flight controllers’ firmware has some embedded functionality with relatively simple algorithms like pre-defined flight routes that use GCS-coordinates. In the case when more complex behavior is required (image processing, AI integration or autonomous decision making with manual controls), such firmware provides an ability to accept various drone commands that correspond to the MAVLink communication protocol. This work investigates important details of companion computers integration with flight controllers with examples and describes hardware and software aspects of implementation of autonomous drone controls. The research also provides solutions to problems that can be possible when implementing such a system.

Learning from the present for the future: The Jülich LOFAR Long-term Archive

The Forschungszentrum Jülich has been hosting the German part of the LOFAR archive since 2013. It is Germany’s most extensive radio astronomy archive, currently storing nearly 22 petabytes (PB) of data. Future radio telescopes are expected to require a dramatic increase in long-term data storage. Here, we take stock of the current data management of the Jülich LOFAR Data Archive, describe the ingestion, the storage system, the export to the long-term archive, and the request chain. We analysed the data availability over the last 10 years and searched for the underlying data access pattern and the energy consumption of the process. We determine hardware-related limiting factors, such as network bandwidth and cache pool availability and performance, and software aspects, e.g. workflow adjustment and parameter tuning, as the main data storage bottlenecks. By contrast, the challenge in providing the data from the archive for the users lies in retrieving the data from the tape archive and staging them. Building on this analysis, we suggest how to avoid/mitigate these problems in the future and define the requirements for future even more extensive long-term data archives.

Reliability evaluation of spacecraft power generation performance with competitive failure processes under irradiation

AbstractThe performance of space power systems is crucial for space products as it determines the operational capabilities, endurance, and efficiency of satellites, spacecraft, and other extraterrestrial devices. Unlike reliability analysis in aerospace systems, studying spacecraft power generation performance requires consideration of both hardware and software aspects. Existing failure models do not fully capture the self‐recovery process of control programs. Therefore, this study presents an impact degradation model for space power systems that incorporates competitive failures under irradiation conditions. The model analyzes solar arrays and power controllers to derive a performance degradation model by considering the defect formation mechanism of amorphous semiconductor materials. Additionally, two shock types are defined based on redundancy backup in power controllers and scrubbing frequency in field‐programmable gate array (FPGA) units. Within the case analysis section, the research meticulously investigates and elucidates the correlation probabilities among varying proton irradiation doses, scrubbing frequencies, and the aforementioned shock types.

Evaluation of Orange data mining software and examples for lecturing machine learning tasks in geoinformatics

AbstractThe study presents the advantages of, and possible uses for, Orange software for data mining in combination with processing spatial data by ArcGIS Pro software in education. To present suitability of Orange software in education, the scientific method of Physics of Notation by D. Moody is used to evaluate the Orange software's visual vocabulary. All nine principles are applied in the presented evaluation. As a result, a high level of effective cognition of the Orange visual vocabulary is proven by this method. Namely, the semantic transparency of visual vocabulary, thanks the explicit inner icons, is semantically immediate. Also, principle of dual coding is used properly by automatic text labels of graphical symbols with the opportunity to rename labels. Renaming is also a way to ensure the partial overloading of symbols found by the first principle of semiotic clarity. The principle of cognitive interaction is partially fulfilled by automatically reorganizing connector lines between symbols to reduce the crossing of lines. A high level of effective cognition is beneficial for students. The evaluation of the visual notation of Orange software is presented to inform teachers and the geoinformatics community of the highly effective cognitive aspects of Orange software. The two practical lectures of processing in Orange and ArcGIS Pro software are shown to the teachers and students of geoinformatics community as examples of machine learning tasks. They are cluster analyses carried out with the density‐based spatial clustering of applications with noise method, first for the location of cafés in Olomouc town and the second example concerns finding similar European towns based on their land use arrangement, using the neural network and following hierarchical clustering. Both examples could provide inspiration for the geoinformatics community to adopt Orange data mining software.

Analysis of Metaverse and Cryptocurrency Crimes ın Forensic Accounting

The purpose of this study is to collect data on crimes that encompass the technological and software aspects referred to as the "new generation," and to analyze case studies and legal incidents related to crimes committed within the scope of the metaverse and cryptocurrency.
 The starting point of the study is the analysis of court decisions related to metaverse and cryptocurrency crimes. Within the scope of the study, thousands of court decisions have been scanned using text mining techniques. The keywords "metaverse," "bitcoin," "digital currency," "cryptocurrency," and "digital money" have been included in the search algorithm for the word corpus. Although no court decision containing the word "metaverse" was found, 37 decisions were identified in which the other terms from the word corpus were mentioned. The oldest decision dates back to July 12, 2019, while the most recent decision is dated March 23, 2023. In addition to the decisions of first-instance courts, the decisions of appellate and higher judicial authorities have also been examined within the framework of text mining studies.

Additive manufacturing-assisted sintering: Low pressure, low temperature spark plasma sintering of tungsten carbide complex shapes

Tungsten carbide (WC), renowned for its exceptional hardness and wear resistance, plays an essential role in various industrial applications (cutting tools, abrasives, and wear-resistant components). While traditional methods involve hot pressing, Spark Plasma Sintering (SPS) combined with Additive Manufacturing (AM) offers a cutting-edge approach, utilizing high-voltage electric current and mechanical pressure for rapid densification, particularly advantageous for fabrication of complex shape components made from challenging materials like nanosized binderless tungsten carbide. The study encompasses the entire spectrum of the powder's characterization, extending to the development of an intricate finite element simulation tailored for SPS sintering. Sintering cycles underscore the exceptional quality of the powder, demonstrating full density microstructures even under low-temperature (1550 °C) and low-pressure (50 MPa) conditions. The nanosized powder exhibits minimal microstructural coarsening, reflecting the high quality of the initial pure tungsten carbide nano powder. The core of this study revolves around the methodology employed for deriving constitutive parameters, following the Skorohod-Olevsky theory of continuum sintering. The derivation methods include variations in temperature, heating regimes, and stepwise pressure application during SPS. Additionally, a grain growth model is formulated based on microstructural analysis. Critical parameters, including the apparent sintering activation energy (800 kJ/mol) and the creep law stress exponent (n = 4.0), are discussed. The article concludes with the integration of the mechanical sintering model into finite element method (FEM) software, considering thermal and electrical aspects for a comprehensive SPS-AM modeling approach and its application to complex shape production. The research aims to enhance the understanding of SPS for tungsten carbide, providing insights for its application in manufacturing cutting-edge components in challenging environments.

Changes in core–mantle boundary heat flux patterns throughout the supercontinent cycle

SUMMARY The Earth’s magnetic field is generated by a dynamo in the outer core and is crucial for shielding our planet from harmful radiation. Despite the established importance of the core–mantle boundary (CMB) heat flux as driver for the dynamo, open questions remain about how heat flux heterogeneities affect the magnetic field. Here, we explore the distribution of the CMB heat flux on Earth and its changes over time using compressible global 3-D mantle convection models in the geodynamic modelling software ASPECT. We discuss the use of the consistent boundary flux method as a tool to more accurately compute boundary heat fluxes in finite element simulations and the workflow to provide the computed heat flux patterns as boundary conditions in geodynamo simulations. Our models use a plate reconstruction throughout the last 1 billion years—encompassing the complete supercontinent cycle—to determine the location and sinking speed of subducted plates. The results show how mantle upwellings and downwellings create localized heat flux anomalies at the CMB that can vary drastically over Earth’s history and depend on the properties and evolution of the lowermost mantle as well as the surface subduction zone configuration. The distribution of hot and cold structures at the CMB changes throughout the supercontinent cycle in terms of location, shape and number, indicating that these structures fluctuate and might have looked very differently in Earth’s past. We estimate the resulting amplitude of spatial heat flux variations, expressed by the ratio of peak-to-peak amplitude to average heat flux, q*, to be at least 2. However, depending on the material properties and the adiabatic heat flux out of the core, q* can easily reach values >30. For a given set of material properties, q* generally varies by 30–50 per cent over time. Our results have implications for understanding the Earth’s thermal evolution and the stability of its magnetic field over geological timescales. They provide insights into the potential effects of the mantle on the magnetic field and pave the way for further exploring questions about the nucleation of the inner core and the past state of the lowermost mantle.

탄소배출권 거래가 전남지역 산업 생산활동에 미치는 영향

When comparing South Korea's emission trading market on a global scale, such as in Europe, the United States, and China, South Korea possesses the hardware infrastructure required for the operation of an emission trading system. However, it appears to be lacking in the software aspect, including the implementation of various carbon reduction policies to complement the carbon emission trading system. The study empirically analyzes the impact of the carbon emission trading system on industries in Jeonnam. First, the carbon emission trading system does not seem to significantly constrain short-term production activities of businesses. Second, when examining the impact of carbon emission prices (KAU, EUA) on major industries in the Jeonnam region, carbon-related variables act as information intermediaries. It is evident that the chemical and steel industries in Jeonnam play the role of information recipients. Third, concerning the connectivity network with KAU as the central variable, it is apparent that the chemical and steel industries in Jeonnam receive more influence from KAU rather than influencing it. In the case of the connectivity network with EUA as the central variable, EUA plays the role of information recipients for the chemical and steel industries. This can be attributed to the participation of these industries in the European carbon emission trading market while exporting chemical and steel products to Europe, affecting EUA demand and prices. In the future, the impact of carbon emission reduction policies is likely to increase for domestic industries and companies in the Jeonnam region in the short term. To achieve regional and national carbon neutrality, policy measures tailored to the industrial structure characteristics of the Jeonnam region must be developed.