bluuebunny/crossref_metadata_2025 huggingface dataset:
Vibro-Acoustic Signatures of Various Insects in Stored Products
Authors: Kadyrov Daniel , Sutin Alexander , Sedunov Nikolay , Sedunov Alexander , Salloum Hady
Published: October 2024

Stored products, such as grains and processed foods, are susceptible to infestation by various insects. The early detection of insects in the supply chain is crucial, as introducing invasive pests to new environments may cause disproportionate harm. The STAR Center at Stevens Institute of Technology developed the Acoustic Stored Product Insect Detection System (A-SPIDS) to detect pests in stored products. The system, which comprises a sound-insulated container for product samples with a built-in internal array of piezoelectric sensors and additional electret microphones to record outside noise, was used to conduct numerous measurements of the vibroacoustic signatures of various insects, including the Callosobruchus maculatus, Tribolium confusum, and Tenebrio molitor, in different materials. A normalization method was implemented using the ambient noise of the sensors as a reference, to accommodate for the proprietary, non-calibrated sensors and allowing to set relative detection thresholds for unknown sensitivities. The normalized envelope of the filtered signals was used to characterize and compare the insect signals by estimating the Normalized Signal Pulse Amplitude (NSPA) and the Normalized Spectral Energy Level (NSEL). These parameters characterize the insect detection Signal Noise Ratio (SNR) for pulse-based detection (NSPA) and averaged energy-based detection (NSEL). These metrics provided an initial step towards the design of a reliable detection algorithm. In the conducted tests NSPA was significantly larger than NSEL. The NSPA reached 70 dB for T. molitor in corn flakes. The insect signals were lower in flour where the averaged NSPA and NSEL values were around 40 dB and 11 dB to 16 dB, respectively.
Goji Disease and Pest Monitoring Model Based on Unmanned Aerial Vehicle Hyperspectral Images
Authors: Zhao Ruixin , Zhang Biyun , Zhang Chunmin , Chen Zeyu , Chang Ning , Zhou Baoyu , Ke Ke , Tang Feng
Published: October 2024

Combining near-earth remote sensing spectral imaging technology with unmanned aerial vehicle (UAV) remote sensing sensing technology, we measured the Ningqi No. 10 goji variety under conditions of health, infestation by psyllids, and infestation by gall mites in Shizuishan City, Ningxia Hui Autonomous Region. The results indicate that the red and near-infrared spectral bands are particularly sensitive for detecting pest and disease conditions in goji. Using UAV-measured data, a remote sensing monitoring model for goji pest and disease was developed and validated using near-earth remote sensing hyperspectral data. A fully connected neural network achieved an accuracy of over 96.82% in classifying gall mite infestations, thereby enhancing the precision of pest and disease monitoring in goji. This demonstrates the reliability of UAV remote sensing. The pest and disease remote sensing monitoring model was used to visually present predictive results on hyperspectral images of goji, achieving data visualization.
Deep Neural Network-Based Cigarette Filter Defect Detection System with FPGA Acceleration for Online Recognition
Authors: Huang Liang , Shen Qiongxia , Jiang Chao , Yang You
Published: October 2024

In the cigarette manufacturing industry, machine vision and artificial intelligence algorithms have been employed to improve production efficiency by detecting product defects. However, achieving both high accuracy and real-time defect detection for cigarettes with complex patterns remains a challenge. To address these issues, this study proposes a model based on RESNET18, combined with a feature enhancement algorithm, to improve detection accuracy. Additionally, a method is designed to deploy the model on a field-programmable gate array (FPGA) with high parallel processing capabilities to achieve high-speed detection. Experimental results demonstrate that the proposed detection model achieves a detection accuracy of 95.88% on a cigarette filter defect dataset with an end-to-end detection speed of only 9.38 ms.
Classification, Localization and Quantization of Eddy Current Detection Defects in CFRP Based on EDC-YOLO
Authors: Wen Rongyan , Tao Chongcong , Ji Hongli , Qiu Jinhao
Published: October 2024

The accurate detection and quantification of defects is vital for the effectiveness of the eddy current nondestructive testing (ECNDT) of carbon fiber-reinforced plastic (CFRP) materials. This study investigates the identification and measurement of three common CFRP defects—cracks, delamination, and low-velocity impact damage—by employing the You Only Look Once (YOLO) model and an improved Eddy Current YOLO (EDC-YOLO) model. YOLO’s limitations in detecting multi-scale features are addressed through the integration of Transformer-based self-attention mechanisms and deformable convolutional sub-modules, with additional global feature extraction via CBAM. By leveraging the Wise-IoU loss function, the model performance is further enhanced, leading to a 4.4% increase in the mAP50 for defect detection. EDC-YOLO proves to be effective for defect identification and quantification in industrial inspections, providing detailed insights, such as the correlation between the impact damage size and energy levels.
High-Resolution Phase-Based Ranging Using Inverse Fourier Transform in an Iterative Bayesian Approach
Authors: Mazur Jan
Published: October 2024

This article proposes an algorithm that determines the distance between two transceivers based on phase information collected in a specific frequency range. Even though we have focused on BLE technology, we do not necessarily adhere strictly to this standard regarding the procedures used to obtain phased samples. We assume that phase samples are given and propose an algorithm using a Bayesian approach to find delays in a multi-path environment. Analyzing these delays allows for determining the distance between both transceivers. We show several examples confirming the high accuracy and resolution of the proposed algorithm. Finally, we conclude with some pros and cons of the proposed solution, suggesting its use in such applications as, for example, virtual acoustics.
Mobile Application Development for Prepaid Water Meter Based on LC Sensor
Authors: Purboyo Ario Kusuma , Fakhrurroja Hanif , Pramesti Dita , Chaidir Achmad Rozan
Published: October 2024

This study presents a novel low-cost and low-power prepaid water meter system that combines tokenization and LC sensors to monitor water consumption accurately with mobile application via Bluetooth Low Energy (BLE) connectivity compared to conventional meters. Water meters play a vital role in monitoring water usage in Indonesia. Postpaid billing methods that rely on manual data recording are a source of concern due to potential inaccuracies caused by human error. This study presents the development of a prepaid water meter system that integrates LC sensors, BLE connectivity, a tokenization mechanism, and a mobile application to address this issue. The system offers a cost-effective solution by utilizing BLE + Global System for Mobile (GSM) from the user’s mobile phone. Using the design thinking methodology, the mobile application for the prepaid water meter achieved a usability testing score of 80. The load testing results for the back-end server, conducted with a sample size of 515 users, revealed a back-end latency of 1.973 milliseconds and an error rate of 8.74%. Furthermore, the LC sensors integrated into the PWM device showed an average error rate of 1.33%. The power consumption during each work cycle was measured at 129 mA and each battery is expected to last six years. Overall, with simple LC sensors, this system can precisely measure water usage.
Blind Recognition of Frame Synchronization Based on Deep Learning
Authors: Wei Jiazheng , Zhang Shitian , Jin Mingchao , He Xiandeng , Quan Dongxiao , Chen Chen
Published: October 2024

In this paper, a deep-learning-based frame synchronization blind recognition algorithm is proposed to improve the detection performance in non-cooperative communication systems. Current methods face challenges in accurately detecting frames under high bit error rates (BER). Our approach begins with flat-top interpolation of binary data and converting it into a series of grayscale images, enabling the application of image processing techniques. By incorporating a scaling factor, we generate RGB images. Based on the matching radius, frame length, and frame synchronization code, RGB images with distinct stripe features are classified as positive samples for each category, while the remaining images are classified as negative samples. Finally, the neural network is trained on these sets to classify test data effectively. Simulation results demonstrate that the proposed algorithm achieves a 100% probability in frame recognition when BER is below 0.2. Even with a BER of 0.25, the recognition probability remains above 90%, which exhibits a performance improvement of over 60% compared with traditional algorithms. This work addresses the shortcomings of existing methods under high error conditions, and the idea of converting sequences into RGB images also provides a reliable solution for frame synchronization in challenging communication environments.
Marine Oil Pollution Monitoring Based on a Morphological Attention U-Net Using SAR Images
Authors: Chang Lena , Chen Yi-Ting , Cheng Ching-Min , Chang Yang-Lang , Ma Shang-Chih
Published: October 2024

This study proposed an improved full-scale aggregated MobileUNet (FA-MobileUNet) model to achieve more complete detection results of oil spill areas using synthetic aperture radar (SAR) images. The convolutional block attention module (CBAM) in the FA-MobileUNet was modified based on morphological concepts. By introducing the morphological attention module (MAM), the improved FA-MobileUNet model can reduce the fragments and holes in the detection results, providing complete oil spill areas which were more suitable for describing the location and scope of oil pollution incidents. In addition, to overcome the inherent category imbalance of the dataset, label smoothing was applied in model training to reduce the model’s overconfidence in majority class samples while improving the model’s generalization ability. The detection performance of the improved FA-MobileUNet model reached an mIoU (mean intersection over union) of 84.55%, which was 17.15% higher than that of the original U-Net model. The effectiveness of the proposed model was then verified using the oil pollution incidents that significantly impacted Taiwan’s marine environment. Experimental results showed that the extent of the detected oil spill was consistent with the oil pollution area recorded in the incident reports.
The Shared Experience Actor–Critic (SEAC) Approach for Allocating Radio Resources and Mitigating Resource Collisions in 5G-NR-V2X Mode 2 Under Aperiodic Traffic Conditions
Authors: Aslam Sawera , Khan Daud , Chang KyungHi
Published: October 2024

5G New Radio (NR)-V2X, standardized by 3GPP Release 16, includes a distributed resource allocation Mode, known as Mode 2, that allows vehicles to autonomously select transmission resources using either sensing-based semi-persistent scheduling (SB-SPS) or dynamic scheduling (DS). In unmanaged 5G-NR-V2X scenarios, SB-SPS loses effectiveness with aperiodic and variable data. DS, while better for aperiodic traffic, faces challenges due to random selection, particularly in high traffic density scenarios, leading to increased collisions. To address these limitations, this study models the Cellular V2X network as a decentralized multi-agent networked Markov decision process (MDP), where each vehicle agent uses the Shared Experience Actor–Critic (SEAC) technique to optimize performance. The superiority of SEAC over SB-SPS and DS is demonstrated through simulations, showing that the SEAC with an N-step approach achieves an average improvement of approximately 18–20% in enhancing reliability, reducing collisions, and improving resource utilization under high vehicular density scenarios with aperiodic traffic patterns.
How to Make the Skin Contact Area Controllable by Optical Calibration in Wearable Tactile Displays of Softness
Authors: Frediani Gabriele , Carpi Federico
Published: October 2024

Virtual reality systems may benefit from wearable (fingertip-mounted) haptic displays capable of rendering the softness of virtual objects. According to neurophysiological evidence, the easiest reliable way to render a virtual softness is to generate purely tactile (as opposed to kinaesthetic) feedback to be delivered via a finger-pulp-interfaced deformable surface. Moreover, it is necessary to control not only the skin indentation depth by applying quasi-static (non-vibratory) contact pressures, but also the skin contact area. This is typically impossible with available devices, even with those that can vary the contact area, because the latter cannot be controlled due to the complexity of sensing it at high resolutions. This causes indetermination on an important tactile cue to render softness. Here, we present a technology that allows the contact area to be open-loop controlled via personalised optical calibrations. We demonstrate the solution on a modified, pneumatic wearable tactile display of softness previously described by us, consisting of a small chamber containing a transparent membrane inflated against the finger pulp. A window on the device allowed for monitoring the skin contact area with a camera from an external unit to generate a calibration curve by processing photos of the skin membrane interface at different pressures. The solution was validated by comparisons with an ink-stain-based method. Moreover, to avoid manual calibrations, a preliminary automated procedure was developed. This calibration strategy may be applied also to other kinds of displays where finger pulps are in contact with transparent deformable structures.
ChatGPT in Pharmacy Practice: Disruptive or Destructive Innovation? A Scoping Review
Authors: Lima Tácio de Mendonça , Bonafé Michelle , Baby André Rolim , Visacri Marília Berlofa
Published: October 2024

ChatGPT has emerged as a promising tool for enhancing clinical practice. However, its implementation raises critical questions about its impact on this field. In this scoping review, we explored the utility of ChatGPT in pharmacy practice. A search was conducted in five databases up to 23 May 2024. Studies analyzing the use of ChatGPT with direct or potential applications in pharmacy practice were included. A total of 839 records were identified, of which 14 studies were included: six tested ChatGPT version 3.5, three tested version 4.0, three tested both versions, one used version 3.0, and one did not specify the version. Only half of the studies evaluated ChatGPT in real-world scenarios. A reasonable number of papers analyzed the use of ChatGPT in pharmacy practice, highlighting both benefits and limitations. The studies indicated that ChatGPT is not fully prepared for use in pharmacy practice due to significant limitations. However, there is great potential for its application in this context in the near future, following further improvements to the tool. Further exploration of its use in pharmacy practice is required, along with proposing its conscious and appropriate utilization.
Use of Edaphic Bioindicators to Mitigate Environmental Impact and Improve Agricultural Research and Training
Authors: Cano-Ortiz Ana , Piñar Fuentes José Carlos , Peña-Martínez Juan , Cano Eusebio
Published: October 2024

The world is currently experiencing unsustainable development, which poses significant risks to global society. In response, there is a growing advocacy for sustainable development across all sectors, driven by social resilience. This shift is fostering substantial socio-environmental tensions. However, the combined power of scientific research and social education has the potential to reverse this trend. Transitioning from an unsustainable territorial model to a sustainable one is both feasible and economically profitable. This transition can be achieved through knowledge of soil bioindicators, which provide valuable information about soil nutrient content. By understanding these indicators, nutrient inputs can be tailored, reducing or eliminating pollutants such as excessive fertilizers, herbicides, and pesticides. Training experts and raising social awareness through education on new research are essential steps in this process. For decades, it has been recognized that globalization, industrialization, and population growth have driven unsustainable development, leading to degraded agroecosystems. To address this issue, government institutions are promoting sustainability through ecological agriculture and CO2 reduction, both of which can be supported by the use of soil bioindicators.
Temporal-Spatial Analysis of Chinese Railway Efficiency Under CO2 Emissions: A Malmquist–Network Data Envelopment Analysis Model
Authors: Ji Wenxin , Qin Feifei
Published: October 2024

With the rapid development of China’s economy, railway transport has increasingly become the main mode of medium and long-distance transport in China. At the same time, we find that in the process of technical improvement, the greenhouse gases emitted from railway locomotives not only affect the environment but also have a big influence on operational effectiveness. In order to clearly understand whether the total undesired output—CO2 emissions—will have an impact on railway efficiency and the environment, we proposed a Malmquist–Network DEA model. Based on the data of 18 railway bureaus in China during the period of 2006–2020, we adopted the Malmquist–NDEA model to analyze the different efficiencies of each stage of the railway operation in China and analyze the environmental efficiency of China’s railway using temporal and spatial dimensions. We found that (1) including the CO2 emissions as an undesirable output in the model has an inverse effect on both the overall efficiency and the production consumption and profit stage efficiencies; (2) the average overall efficiency of these 18 rail bureaus has shown relative stability, and the negative effects of CO2 on the construction development and production stages are much lower than on the consumption and profit stages; and (3) the rail systems in the eastern areas have higher efficiencies in their construction development stage compared to the other two areas.
ESG Reporting of Commercial Banks in Poland in the Aspect of the New Requirements of the Directive on Corporate Reporting in the Field of Sustainable Development (CSRD)
Authors: Matuszak-Flejszman Alina , Łukaszewski Sebastian , Banach Joanna Katarzyna
Published: October 2024

For several years, commercial banks in Poland have been reporting activities related to the impact on the environment, society, and corporate governance (ESG). However, only new guidelines, mandatory for many entities, including banks, will allow for comparing these reports, which will be of great importance mainly for investors. The forms of these reports were and still are different, difficult to compare in individual years, and difficult to compare between banks. The article aims to present the banks’ preparation for the new reporting rules based on the latest ESG reports. The research was conducted in four groups of commercial banks operating in Poland. These are the largest companies listed in the WIG Banks sub-index of the Warsaw Stock Exchange. Gaps in the preparation of these banks for non-financial reporting were identified. The non-financial reports of the banks studied have significant information potential that can be used by various stakeholder groups, including investors, customers, employees, regulators, and local communities. However, the comparability of ESG reports is one of the key challenges faced by both reporting banks and users of these reports. The research results can be used both in scientific works and by bank representatives to improve non-financial reports.
Project Controls Model for Sustainable Construction Projects
Authors: Rajabi Sareh , El-Sayegh Sameh , Romdhane Lotfi
Published: October 2024

As sustainability rises in significance in the construction industry, there is a need to adopt new project management techniques to help achieve increases in sustainability objectives. There have been several research works that have investigated the integration of sustainability in construction. However, there is a gap in addressing performance measurement and evaluation during the construction phase. Traditional project performance evaluation methods use the Earned Value Management (EVM) technique to assess time, cost, and scope performance. However, EVM does not address the performance of sustainability goals. The main objective of this paper is to develop a new project controls method for sustainable construction projects. Sustainability performance indicators can play an essential role in advancing the practice of sustainable construction. Accordingly, a Sustainable Earned Value Management (SEVM) model incorporating sustainability indicators was developed to monitor the attainment of sustainability objectives in construction projects in addition to the traditional objectives. The proposed SEVM model uses the construction planning optimization model to prepare the baseline plan to monitor the project’s time, cost, and sustainability performance. The proposed model enhances the monitoring and control of sustainable construction projects in terms of time, cost, and sustainability using sustainability indicators.
Eco-Leadership in Action: Integrating Green HRM and the New Ecological Paradigm to Foster Organizational Commitment and Environmental Citizenship in the Hospitality Industry
Authors: Yoo Dong Yoon
Published: October 2024

The 21st century has spotlighted environmental sustainability in global discourse, urging businesses to act responsibly amidst climate change and resource depletion. This study explores the role of green human resource management (GHRM) in fostering the New Ecological Paradigm (NEP) among employees, enhancing organizational commitment (OC), and promoting organizational citizenship behavior towards the environment (OCBE) within the hospitality industry. Findings demonstrate that GHRM practices, including green recruitment, training, and performance management, significantly improve environmental performance and employee engagement in sustainability initiatives. Data were collected from 382 employees working in 5-star hotels in South Korea, utilizing a structured online survey to gather insights into GHRM’s influence on NEP, OC, and OCBE. The analysis was conducted using covariance-based structural equation modeling (CB-SEM) to rigorously test the hypothesized relationships among these constructs. However, integrating GHRM with NEP presents challenges, such as aligning organizational culture with eco-centric values and overcoming resistance to change. Motivated by the urgent need for sustainability, this research underscores the necessity for integrated HRM approaches to achieve sustainability. A key motivation behind this integration is to establish a workforce that not only understands but actively champions environmental stewardship, thereby strengthening the organization’s reputation and competitive advantage. Additionally, challenges such as balancing short-term operational costs with long-term environmental goals persist, requiring strategic commitment and effective resource allocation. Recommendations include embedding sustainability in HR policies, providing comprehensive environmental training, incentivizing green initiatives, establishing robust monitoring systems, and fostering cross-departmental collaboration to reduce the ecological footprint. This study contributes to the growing body of literature on sustainable business practices and highlights the strategic importance of eco-leadership.
To Sustainably Ride or Not to Ride: Examining the Green Consumption Intention of Ride-Hailing Services in the Sharing Economy by University Students
Authors: Khan Muhammad Ishfaq , Shah Syed Afzal Moshadi , Ali Mudassar , Naim Abdullah Faisal Al
Published: October 2024

An increase in ride-hailing services in the sharing economy can help to reduce the number of vehicles on the road, which will lead to a decrease in air pollution and noise pollution, an improvement in environmental conditions, a decrease in travel costs, and an increase in social benefits to travelers. Hence, there is a great need to examine the consumer’s intention toward usage of ride-hailing services in the sharing economy. The current study aims to examine the green consumption intention of eco-friendly services as an outcome of environmental responsibility and environmental knowledge. It also attempts to examine the serial mediation of green concern, value co-creation, and mediated moderation of social support as an explanatory mechanism of green consumption intention of eco-friendly services. The research design was cross-section and deductive. The respondents of the study were registered university students in Islamabad who were active consumers of major ride-hailing services in Pakistan, i.e., Uber, Careem, Uplift, InDriver, B4U Cabes, and SUVL. A total of 402 responses were gathered using purposive sampling. Partial Least Squares Structural Equation Modeling (PLS-SEM) in Smart PLS is used to evaluate the reliability of measurement instruments and the validity of the research model. The current study results showed that environmental responsibility and knowledge positively and significantly affect motivation to engage in green consumption. Furthermore, environmental concern and value co-creation partially mediate the proposed relationship. In addition, social support also moderates the association between green concern and value co-creation such that it strengthens the connection. The current research findings are an addition to the existing literature and have managerial applications with limitations preceded by future research directions.
Simulation-Based Design for Recycling of Car Electronic Modules as a Function of Disassembly Strategies
Authors: van Schaik Antoinette , Reuter Markus A.
Published: October 2024

Modules (or parts) of a car are a complex functional material combination used to deliver a specified task for a car. Recovering all materials, energy, etc., into high-grade materials at their end of life (EoL) is impossible. This is dictated by the second law of thermodynamics (2LT) and thence economics. Thus, recyclability cannot be conducted with simplistic mass-based approaches void of thermodynamic considerations. We apply, in this paper, a process simulation model to estimate the true recyclability of various SEAT (Volkswagen Group) car parts within the EU H2020 TREASURE project. This simulation model is developed with 190 reactors and over 310 feed components with over 1000 reaction species in the 880 streams of the flowsheet. The uniqueness of the work in this paper is to apply the full material declaration (FMD) and bill of materials (BOM) of all 310 materials in the parts as a feed to the process simulation model to show the parts’ true recyclability. We classified all parts into categories, i.e., copper-rich, steel-rich and plastic-rich, to maximally recover metals at the desired material quality, as well as energy. Recyclability is understood to create high-grade products that can be applied with the same functional quality in these parts. In addition, disassembly strategies and related possible redesign show how much recyclability can be improved. Process simulation permits the creation of alloys, phases, materials, etc., at a desired quality. The strength of the simulation permits any feed from any End-of-Life part to be analyzed, as long as the FMD and BOM are available. This is analogous to any mineral and metallurgical engineering process simulation for which the full mineralogy must be available to analyze and/or design flowsheets. This paper delivers a wealth of data for various parts as well as the ultimate recovery of materials, elements, and energy. The results show clearly that there is no one single recycling rate for elements, materials, and alloys. It is in fact a function of the complexity and material combinations within the parts. The fact that we use a thermochemical-based process simulator with full compositional detail for the considered parts means full energy balances as well as exergy dissipation can be evaluated. This means that we can also evaluate which parts, due complex mixtures of plastics, are best processed for energy recovery or are best for material and metal recovery, with thermochemistry, reactor technology and integrated flowsheets being the basis.
Defining Greenwashing: A Concept Analysis
Authors: Spaniol Matthew J. , Danilova-Jensen Evita , Nielsen Martin , Rosdahl Carl Gyldenkærne , Schmidt Clara Jasmin
Published: October 2024

The lack of a shared, operant definition for greenwashing has led to fragmented scholarly research, unclear guidelines for practice, inconsistent enforcement, and reactive policy frameworks; resulting in ineffective efforts to combat its growth. Using concept analysis, this research establishes a composite definition for greenwashing by identifying the constitutive attributes sourced across 79 scholarly definitions. The analysis finds six requirements necessary for identifying greenwashing: a claim on environmental performance by a private sector organization marketing a product or a service, which cannot be substantiated, made with deceptive intent, and done to establish a competitive advantage. Fulfilling these criteria warrants an accusation of greenwashing. With the aim to prevent its further spread and misuse, the article provides a diagnostic tool for separating similar but often conflated concepts from greenwashing to organize scholarly research, provide guidelines for practitioners, and support regulators’ case analysis.
The Influence of Information Security Management System Implementation on the Financial Performance of Indian Companies: Examining the Moderating Effect of National Culture
Authors: Duggal Kanika , Myeong Seunghwan
Published: October 2024

The extensive focus on information technology (IT) within organizations, along with the substantial significance of information security issues, has made information security a top priority for executives. The International Organization for Standardization 27001 (ISO-27001) policy outlines the requirements for an effective Information Security Management System (ISMS). Implementing an ISMS not only enhances the overall profitability of a firm, but it also has a significant impact in various scenarios. In this study, we examined how ISMS implementation can assist corporations financially, with a specific focus on the moderating effect of Indian national culture. We analyzed financial performance following ISMS and ISO-27001 implementation using sample data from 420 Indian small and medium-sized enterprises (SMEs). By analyzing 256 survey questionnaires from 420 SMEs, we found that national culture amplifies the strong interaction between ISMS implementation and SME performance in India. We found that ISMS implementation increased the profitability of recognized Indian firms, supporting study hypotheses. The findings provide valuable insights for SMEs seeking to enhance financial performance through ISMS implementation, emphasizing the moderating role of national culture in shaping these outcomes.
Green Order Sorting Problem in Cold Storage Solved by Genetic Algorithm
Authors: Yener Furkan , Yazgan Harun Resit
Published: October 2024

This study investigates the efficiency of cold storage warehouses and contributes to sustainable supply chain management by integrating eco-friendly practices into storage operations. In facilities for milk and its derivatives, unregulated order handling significantly increases energy consumption due to frequent door openings in the cooler. To address this challenge, we developed a novel mathematical model aimed at optimizing order sequences and minimizing energy costs, addressing a previously unexplored gap in the literature. A genetic algorithm (GA) was employed to solve this model, with careful consideration of carbon emissions generated during the algorithm’s execution. We utilized the Yates notation, an experimental design technique, to systematically optimize the GA’s parameters, ensuring robust and statistically valid results. This methodology enabled a thorough analysis of the factors influencing energy consumption. The findings enhance energy efficiency in cold storage warehouses, leading to reduced carbon dioxide emissions and fostering sustainable practices within supply chain management. Ultimately, this study successfully integrates green practices into cold storage operations, supporting broader sustainability objectives.
Impact of Servitization on Employee Satisfaction with Performance Evaluation Systems: A Case Study of China’s New Energy Sector Amid Power Market Reforms
Authors: Kong Qingmin , Lin Peng , Gu Tingting
Published: October 2024

This study investigates the mechanisms by which service-oriented transformation affects employee satisfaction with performance evaluation systems within the context of China’s electricity market reform. Using CGN New Energy’s Guangxi Branch as a case study and applying the grounded theory method, the research systematically analyzes employees’ perceptions of fairness, transparency, and career development during the transition from a product-oriented to a service-oriented model, based on in-depth interviews and surveys. The findings reveal that while servitization enhances employee skill development and career satisfaction, it also introduces challenges, such as increased work pressure and the demand for more transparent performance evaluation systems. This study provides valuable insights into optimizing management practices and performance evaluation systems in renewable energy companies, contributing both theoretically and practically to the literature on organizational transformation in the energy sector. These conclusions are not only significant for Chinese enterprises but also offer important reference points for global energy companies undergoing similar transitions.
Research on the Mechanism of the Green Innovation of Enterprises Empowered by Digital Technology from the Perspective of Value Co-Creation
Authors: Bo Qiushi , Liu Hui , Zheng Junwei
Published: October 2024

To help enterprises utilize digital technologies to increase their green innovation awareness and behavior and further clarify the “black box” of this process, this study first develops a theoretical framework to explain the mechanism of the functional attributes of digital technology, stakeholder value co-creation, and enterprise green innovation. Data are subsequently gathered from 342 manufacturing enterprises, and the meditation and moderation hypotheses are empirically analyzed using hierarchical regression and the bootstrapping method. A robustness test is conducted via data grouping. The findings indicate that digital technology openness and affordance have a positive effect on green product innovation and process innovation through value co-creation between businesses and stakeholders. Additionally, digital technology self-growth positively moderates the indirect effect of digital technology affordance on the green innovation of enterprises through value co-creation.
Synergistic Control of Active Filter and Grid Forming Inverter for Power Quality Improvement
Authors: Rahman Khaliqur , Hashimoto Jun , Koseki Kunio , Ustun Taha Selim , Orihara Dai , Kikusato Hiroshi
Published: October 2024

This paper addresses the challenges and opportunities associated with integrating grid-forming inverters (GFMs) into modern power systems, particularly in the presence of nonlinear loads. Nonlinear loads introduce significant harmonic distortions in the source voltage and current, leading to reduced power factor, increased losses, and an overall reduction in system performance. To mitigate these adverse effects, active filters are employed. The objective of this study is to investigate a synergistic approach to modeling and control in integrated power systems with GFMs, focusing on enhancing power quality and grid stability by reducing harmonic distortions through the use of voltage-source active filters. This research contributes to sustainability by supporting the reliable and efficient integration of renewable energy sources, thereby reducing dependency on fossil fuels and minimizing greenhouse gas emissions. Additionally, improving power quality and system efficiency helps reduce energy waste, which is crucial for achieving sustainable energy goals. Simulations are conducted on a 1000 kW GFM connected to a grid with a nonlinear variable load, demonstrating the system’s effectiveness in adapting to dynamic conditions, reducing harmonics, and promoting a stable, resilient, and sustainable power grid.
Experimental Study on the Protective Effect of High Alcoholysis Polyvinyl Alcohol (PVA) Solution Spraying on Loess Fill Slopes
Authors: Kong Xiangchao , He Faguo , Liu Qiang , Lv Xuemeng , Lu Tengfei , Zhang Lizhi , Yang Xin
Published: October 2024

Loess has high water sensitivity and exhibits poor characteristics such as weak cementation and high porosity. Under heavy rainfall, loess fill slopes are prone to erosion and landslides, posing serious threats to public safety and property. In light of these serious threats, this study employed the method of spraying polyvinyl alcohol (PVA) solution to improve loess fill slopes and systematically examine its protective effects. Through field investigations and combined laboratory and outdoor tests, this study comprehensively evaluated the mechanical properties, anti-aging and anti-erosion performance of loess after PVA solution spraying. Scanning electron microscopy was used to reveal the mechanism of PVA action at the microscopic level. The results showed that after treatment with PVA solutions of varying concentrations, the mechanical properties of loess samples were significantly enhanced, while also exhibiting excellent anti-aging and water resistance performance. Additionally, PVA-treated loess fill slopes exhibited excellent rain erosion resistance. A microscopic structural analysis showed that PVA fills the internal pores of loess, strengthens inter-particle bonding, and uses its hydrophobic groups’ water-repellent action to effectively enhance slope stability and erosion resistance. In conclusion, PVA treatment not only significantly enhances the protective effects of loess fill slopes but also holds important value in improving soil sustainability and environmental protection.
The Use of Waste Materials Red Mud and Bottom Ash as Road Embankment Fill
Authors: Soğancı Ali Sinan , Özkan Ilyas , Yenginar Yavuz , Güzel Yusuf , Özdemir Adnan
Published: October 2024

This study provides a comprehensive evaluation of red mud as a sustainable material for road base construction, particularly in combination with bottom ash. Red mud, a by-product of the Bayer process used in alumina extraction, is known for its high alkalinity and heavy metal content. For this reason, this waste material causes environmental challenges. Red mud sourced from the Eti Aluminum Factory in Seydişehir, Konya (Turkey), was stabilized with bottom ash. Then, these waste materials were tested through a number of experiments, such as in relation to their Atterberg limits, compaction characteristics, unconfined compressive strength (UCS), California bearing ratio (CBR), and microstructure through a scanning electron microscopy (SEM) analysis. The results highlight that the UCS of stabilized red mud samples significantly improved with the addition of bottom ash and longer curing periods. Specifically, the UCS values increased from 0.5 MPa to 2.5 MPa after 28 days of curing. Moreover, RM specimens stabilized with 25% bottom ash achieved a CBR value of 146.64% after 28 days, far exceeding Turkey’s road fill material requirement, which mandates a minimum unsoaked CBR value of 15%. These findings indicate that red mud stabilized with bottom ash not only meets but exceeds the structural requirements for road base materials. This approach provides a sustainable solution for the environmental management of red mud while contributing to infrastructure development. Through the recycling of these industrial by-products, this study presents a viable method to reduce waste and support economic and environmental sustainability in road construction projects.
An Evidential Reasoning Method of Comprehensive Evaluation of Water Quality Based on Gaussian Distribution
Authors: Zeng Yangyan , Zhang Xiangzhi , Cao Wenzhi , Deng Jilin , Zeng Hao
Published: October 2024

This study provides an evidential reasoning method for water quality evaluation based on Gaussian distribution to handle the problem of comprehensive water quality evaluation for a region across a period (multiple sections and multiple time points). The method turns the collection of observed water quality indicator values into a probability distribution of water quality grades by using the Gaussian distribution to compute the confidence assessment of water quality grades over one period. It eliminates the subjectivity involved in determining confidence levels and the problem of information loss during data fusion that arises with conventional approaches. The probability distribution of each assessment grade is then determined by repeatedly synthesizing evidence of the same water quality grade using the improved evidential reasoning synthesis rule. To avoid the subjectivity included in experience-based weight settings, principal component analysis (PCA) is utilized to calculate the weights of water quality indicators based on contribution rates and load coefficients. In the end, utility theory is presented to modify the discrete probability distribution of precise numerical expressions, offering thorough results for the evaluation of water quality and facilitating the comparison of various water quality grades. Using the Xiangjiang River Basin as a case study, the proposed evaluation method is contrasted with popular techniques for assessing water quality, including the Single-Factor Evaluation Method, the Fuzzy Comprehensive Evaluation Method, and the Evidential Reasoning Comprehensive Evaluation Method. The findings suggest that the evidence reasoning approach for evaluating water quality that is based on Gaussian distribution is more rational, accurate, and scientific. Additionally, empirical studies on the annual water quality trends in various regions, the upstream, midstream, and downstream trends, and the water quality trends during wet and dry periods are conducted using this method to assess and analyze changes in water quality in the Xiangjiang River Basin during the “11th Five-Year Plan” and “12th Five-Year Plan” periods. The analysis findings demonstrate that, even if the rate of progress has slowed, the Xiangjiang River Basin’s overall water quality has been steadily improving since management and protection measures were put in place. This shows that the preventive and control efforts implemented in the “11th Five-Year Plan” and “12th Five-Year Plan” periods were successful; nevertheless, carrying out the current tactics might only have a limited impact. As a result, more advanced and creative approaches are required to encourage the ongoing enhancement of the water quality in the Xiangjiang River Basin.
Bridging the Knowledge–Practice Gap: Assessing Climate Change Literacy Among Science Teachers
Authors: Almazroa Hiya
Published: October 2024

This research aimed to investigate the knowledge levels and teaching practices of Saudi science teachers regarding climate change, focusing on exploring the correlation between these aspects. The cross-sectional descriptive survey included teachers at middle and high school levels in public schools. The questionnaire study comprised three sections: collecting demographic data, assessing teachers’ understanding of climate change through factual inquiries, and evaluating teaching practices related to climate change. The findings reveal a promising degree of awareness among teachers, with a majority correctly identifying crucial elements of climate change while also exposing misconceptions and knowledge gaps. While a notable portion of teachers reported teaching climate change-related aspects, some indicated minimal involvement in extracurricular activities linked to climate change. The correlation analysis between science teachers’ climate change knowledge and practices indicates a weak connection between the two variables, suggesting that teachers’ knowledge might not substantially impact their actual teaching practices regarding climate change concepts. Limitations included reliance on self-reported data and a sample size that could impact result generalizability. Future research recommendations include combining quantitative data with qualitative methods, comparing knowledge and practices across regions or demographics, and conducting longitudinal studies. This study’s implications stress the importance of targeted professional development, advocating for climate change education integration into formal curricula, and policy adjustments mandating climate change education.
Global Dynamics of Environmental Kuznets Curve: A Cross-Correlation Analysis of Income and CO2 Emissions
Authors: Almeida Dora , Carvalho Luísa , Ferreira Paulo , Dionísio Andreia , Haq Inzamam Ul
Published: October 2024

The environmental Kuznets curve (EKC) hypothesis posits an inverted U-shaped relationship between economic growth and environmental degradation. However, there is no consensus regarding the EKC hypothesis among countries and regions of different income groups. This study revisits the EKC hypothesis by employing cross-correlation analysis to explore the income–CO2 emissions relationship across 158 countries and 44 regions from 1990 to 2020. The empirical method utilizes a dynamic cross-correlation coefficient (CCC) approach, allowing for the assessment of lead-lag dynamics between income and CO2 emissions over time. By categorizing nations into the World Bank’s income classifications, we found a heterogeneous EKC pattern highlighting distinct environmental–economic dynamics across different income groups. The findings indicate that high-income countries show a decoupling of economic growth from CO2 emissions; whereas, low-income countries still exhibit a positive correlation between both variables. This underscores the necessity for tailored policy interventions that promote carbon neutrality, while considering each country’s unique development stage. Our research contributes to the ongoing issue of sustainable economic development by providing empirical evidence of the different pathways nations follow in balancing growth with environmental preservation.
Energy and Environmental Aspects of the Sustainability of Clothing Production
Authors: Rogale Dubravko , Firšt Rogale Snježana
Published: October 2024

The textile and clothing industries are very often lumped together when it comes to the environmental aspect such that the negative connotation of the textile industry from an environmental aspect is automatically transferred to the clothing industry. However, the two industries should be considered separately, particularly with regard to the machinery used and energy consumption in the production process. The energy consumption of electricity, compressed air, vacuum, steam, and other energy sources in the clothing industry is low compared to other related industries. Furthermore, no carcinogenic and allergenic waste is generated during the production of clothing, which has a low carbon footprint, i.e., it practically does not pollute the air, soil, and water. The waste produced during cutting is clean and unused and is immediately recycled. All of this contributes to the sustainability of the clothing industry from the energy and environmental aspects. This article describes the cutting and joining techniques used in the manufacture of clothing, from the energy and environmental aspects as well as aspects of the weaves, the necessary machine elements and mechanisms, and the energy used in all joining techniques, from which the above claims and facts can be seen.