bluuebunny/crossref_metadata_2025 huggingface dataset:
Assessing the Water Budget Closure Accuracy of Satellite/Reanalysis-Based Hydrological Data Products over Mainland China
Authors: Luo Zengliang , Yu Han , Liu Huan , Chen Jie
Published: November 2023

A good water budget involving four variables, including precipitation (P), evapotranspiration (ET), streamflow (R), and terrestrial water storage change (TWSC), is reflected in two aspects: a high accuracy against observations for each budget component and the low water budget closure residual error (ΔRes). Due to the lack of consideration of observations of budget components in existing water budget closure assessment methods (BCMs), when the ΔRes of budget components is low, their error against respective observations may still be high. In this study, we assess the water budget closure accuracy of satellite/reanalysis-based hydrological data products over mainland China based on six popular P products and multiple datasets of additional budget components (ET, R, and TWSC). The results indicated that the ΔRes changes between ±15 mm over mainland China. Satellite P products such as GPM IMERG showed better performance by comparing them with rain gauge-based observations. However, reanalysis P products such as GLDAS and FLDAS showed a better water budget closure since the selected datasets of additional budget components (ET and R) are also derived from reanalysis datasets. This indicates that these same data sources for budget components make it easier to close the water budget. The further development of satellite P products should consider the closure of the water budget with other water cycle variables.
A New Approach for Feeding Multispectral Imagery into Convolutional Neural Networks Improved Classification of Seedlings
Authors: Imangholiloo Mohammad , Luoma Ville , Holopainen Markus , Vastaranta Mikko , Mäkeläinen Antti , Koivumäki Niko , Honkavaara Eija , Khoramshahi Ehsan
Published: November 2023

Tree species information is important for forest management, especially in seedling stands. To mitigate the spectral admixture of understory reflectance with small and lesser foliaged seedling canopies, we proposed an image pre-processing step based on the canopy threshold (Cth) applied on drone-based multispectral images prior to feeding classifiers. This study focused on (1) improving the classification of seedlings by applying the introduced technique; (2) comparing the classification accuracies of the convolutional neural network (CNN) and random forest (RF) methods; and (3) improving classification accuracy by fusing vegetation indices to multispectral data. A classification of 5417 field-located seedlings from 75 sample plots showed that applying the Cth technique improved the overall accuracy (OA) of species classification from 75.7% to 78.5% on the Cth-affected subset of the test dataset in CNN method (1). The OA was more accurate in CNN (79.9%) compared to RF (68.3%) (2). Moreover, fusing vegetation indices with multispectral data improved the OA from 75.1% to 79.3% in CNN (3). Further analysis revealed that shorter seedlings and tensors with a higher proportion of Cth-affected pixels have negative impacts on the OA in seedling forests. Based on the obtained results, the proposed method could be used to improve species classification of single-tree detected seedlings in operational forest inventory.
Chaotic Properties of Gravity Waves during Typhoons Observed by HFSWR
Authors: Chen Xuekun , Yang Hongjuan , Lyu Zhe , Yu Changjun
Published: November 2023

The gravity wave produced by typhoons has been an essential subject of study that concerns numerous researchers. The damage to human beings and infrastructure in coastal regions caused by typhoon disasters annually is very severe, and analyzing gravity wave variation is a reliable approach to research typhoons. High-frequency surface wave radar (HFSWR) as an over-the-horizon radar can achieve real-time monitoring of an extensive sea area and space. This paper derived the gravity wave perturbation spectrum by handling high-frequency surface wave radar data during typhoons. The gravity wave spectrum data were examined by applying the chaos examination approaches of the Lyapunov exponent and phase-space reconstruction to the gravity wave spectrum data after processing and extraction. The reconstructed phase space had a specific shape in a certain direction, with the maximum Lyapunov exponent greater than zero. The gravity wave spectrum data are suggested to have chaotic properties through two chaos examination approaches. This paper demonstrated that the gravity waves observed by a radar have chaotic properties through the measurement data of HFSWR. While the chaotic properties suggest that observed gravity wave data are predictable in the short term, they are unpredictable in the long term. Predicting gravity wave data is important for understanding the chaotic properties of the atmosphere and for future gravity wave prediction.
Survey on Motion Planning for Multirotor Aerial Vehicles in Plan-Based Control Paradigm
Authors: Kulathunga Geesara , Klimchik Alexandr
Published: November 2023

In general, optimal motion planning can be performed both locally and globally. In such a planning, the choice in favor of either local or global planning technique mainly depends on whether the environmental conditions are dynamic or static. Hence, the most adequate choice is to use local planning or local planning alongside global planning. When designing optimal motion planning, both local and global, the key metrics to bear in mind are execution time, asymptotic optimality, and quick reaction to dynamic obstacles. Such planning approaches can address the aforementioned target metrics more efficiently compared to other approaches, such as path planning followed by smoothing. Thus, the foremost objective of this study is to analyze related literature in order to understand how the motion planning problem, especially the trajectory planning problem, is formulated when being applied for generating optimal trajectories in real-time for multirotor aerial vehicles, as well as how it impacts the listed metrics. As a result of this research, the trajectory planning problem was broken down into a set of subproblems, and the lists of methods for addressing each of the problems were identified and described in detail. Subsequently, the most prominent results from 2010 to 2022 were summarized and presented in the form of a timeline.
Simultaneous Correlative Interferometer Technique for Direction Finding of Signal Sources
Authors: Oh Minkyu , Lee Young-Seok , Lee In-Ki , Jung Bang Chul
Published: November 2023

In this paper, we propose a novel simultaneous Correlative Interferometer (CI) technique that elaborately estimates the Direction of Arrival (DOA) of multiple source signals incident on an antenna array. The basic idea of the proposed technique is that the antenna-array-based receiver compares the phase of the received signal with one of the candidates at each time sample and jointly exploits these multiple time samples to estimate the DOAs of multiple signal sources. The proposed simultaneous CI-based DOA estimation technique collectively utilizes multiple time-domain samples and can be regarded as a generalized version of the conventional CI algorithm for the case of multiple time-domain samples. We first thoroughly review the conventional CI algorithm to comprehensively explain the procedure of the direction-finding algorithm that adopts the phase information of received signals. We also discuss several technical issues of conventional CI-based DOA estimation techniques that are originally proposed for the case of a single time-domain sample. Then, we propose a simultaneous CI-based DOA estimation technique with multi-sample diversity as a novel solution for the case of multiple time-domain samples. We clearly compare the proposed simultaneous CI technique with the conventional CI technique and we compare the existing Multiple Signal Classification (MUSIC)-based DOA estimation technique with the conventional CI-based technique by using the DOA spectrum as well. To the best of our knowledge, the simultaneous CI-based DOA estimation technique that effectively utilizes the characteristics of multiple signal sources over multiple time-domain samples has not been reported in the literature. Through extensive computer simulations, we show that the proposed simultaneous CI technique significantly outperforms both the conventional CI technique in terms of DOA estimation even in harsh environments and with various antenna array structures. It is worth noting that the proposed simultaneous CI technique results in much better performance than the classical MUSIC algorithm, which is one of the most representative subspace-based DOA estimation techniques.
A Condition-Monitoring Method for Rolling Bearings Based on Dynamic Asynchronous Peak-Factor Ratios
Authors: Zhu Guanhua , Huang Quansi , Zhang Zeyu
Published: November 2023

In response to issues such as the lack of capability for timely early warning and the difficulty in monitoring the status of rolling bearings, a condition-monitoring method for rolling bearings based on the Honey Badger Algorithm (HBA) for optimizing dynamic asynchronous periods is proposed. This method is founded on the peak factor and involves comparing peak factors at different periods to construct a dynamic asynchronous peak-factor-ratio-monitoring index, which is then optimized using the HBA. Simulated experiments were carried out using the XJTU-SY dataset. The results indicate that, compared to the early warning times defined by international standards, the warning times provided using this method are consistently over 33 min in advance within the test dataset. Additionally, an envelope spectrum analysis of the warning data confirms the existence of early faults. This demonstrates that the monitoring indicator developed in this paper is capable of delivering earlier and more accurate early fault warnings and condition monitoring for rolling bearings.
Strengthening Privacy and Data Security in Biomedical Microelectromechanical Systems by IoT Communication Security and Protection in Smart Healthcare
Authors: Jaime Francisco J. , Muñoz Antonio , Rodríguez-Gómez Francisco , Jerez-Calero Antonio
Published: November 2023

Biomedical Microelectromechanical Systems (BioMEMS) serve as a crucial catalyst in enhancing IoT communication security and safeguarding smart healthcare systems. Situated at the nexus of advanced technology and healthcare, BioMEMS are instrumental in pioneering personalized diagnostics, monitoring, and therapeutic applications. Nonetheless, this integration brings forth a complex array of security and privacy challenges intrinsic to IoT communications within smart healthcare ecosystems, demanding comprehensive scrutiny. In this manuscript, we embark on an extensive analysis of the intricate security terrain associated with IoT communications in the realm of BioMEMS, addressing a spectrum of vulnerabilities that spans cyber threats, data manipulation, and interception of communications. The integration of real-world case studies serves to illuminate the direct repercussions of security breaches within smart healthcare systems, highlighting the imperative to safeguard both patient safety and the integrity of medical data. We delve into a suite of security solutions, encompassing rigorous authentication processes, data encryption, designs resistant to attacks, and continuous monitoring mechanisms, all tailored to fortify BioMEMS in the face of ever-evolving threats within smart healthcare environments. Furthermore, the paper underscores the vital role of ethical and regulatory considerations, emphasizing the need to uphold patient autonomy, ensure the confidentiality of data, and maintain equitable access to healthcare in the context of IoT communication security. Looking forward, we explore the impending landscape of BioMEMS security as it intertwines with emerging technologies such as AI-driven diagnostics, quantum computing, and genomic integration, anticipating potential challenges and strategizing for the future. In doing so, this paper highlights the paramount importance of adopting an integrated approach that seamlessly blends technological innovation, ethical foresight, and collaborative ingenuity, thereby steering BioMEMS towards a secure and resilient future within smart healthcare systems, in the ambit of IoT communication security and protection.
A Deep Learning Approach to Classify Surgical Skill in Microsurgery Using Force Data from a Novel Sensorised Surgical Glove
Authors: Xu Jialang , Anastasiou Dimitrios , Booker James , Burton Oliver E. , Layard Horsfall Hugo , Salvadores Fernandez Carmen , Xue Yang , Stoyanov Danail , Tiwari Manish K. , Marcus Hani J. , Mazomenos Evangelos B.
Published: November 2023

Microsurgery serves as the foundation for numerous operative procedures. Given its highly technical nature, the assessment of surgical skill becomes an essential component of clinical practice and microsurgery education. The interaction forces between surgical tools and tissues play a pivotal role in surgical success, making them a valuable indicator of surgical skill. In this study, we employ six distinct deep learning architectures (LSTM, GRU, Bi-LSTM, CLDNN, TCN, Transformer) specifically designed for the classification of surgical skill levels. We use force data obtained from a novel sensorized surgical glove utilized during a microsurgical task. To enhance the performance of our models, we propose six data augmentation techniques. The proposed frameworks are accompanied by a comprehensive analysis, both quantitative and qualitative, including experiments conducted with two cross-validation schemes and interpretable visualizations of the network’s decision-making process. Our experimental results show that CLDNN and TCN are the top-performing models, achieving impressive accuracy rates of 96.16% and 97.45%, respectively. This not only underscores the effectiveness of our proposed architectures, but also serves as compelling evidence that the force data obtained through the sensorized surgical glove contains valuable information regarding surgical skill.
The Role and Importance of Using Sensor-Based Devices in Medical Rehabilitation: A Literature Review on the New Therapeutic Approaches
Authors: Szabo Dan Alexandru , Neagu Nicolae , Teodorescu Silvia , Apostu Mihaela , Predescu Corina , Pârvu Carmen , Veres Cristina
Published: November 2023

Due to the growth of sensor technology, more affordable integrated circuits, and connectivity technologies, the usage of wearable equipment and sensing devices for monitoring physical activities, whether for wellness, sports monitoring, or medical rehabilitation, has exploded. The current literature review was performed between October 2022 and February 2023 using PubMed, Web of Science, and Scopus in accordance with P.R.I.S.M.A. criteria. The screening phase resulted in the exclusion of 69 articles that did not fit the themes developed in all subchapters of the study, 41 articles that dealt exclusively with rehabilitation and orthopaedics, 28 articles whose abstracts were not visible, and 10 articles that dealt exclusively with other sensor-based devices and not medical ones; the inclusion phase resulted in the inclusion of 111 articles. Patients who utilise sensor-based devices have several advantages due to rehabilitating a missing component, which marks the accomplishment of a fundamental goal within the rehabilitation program. As technology moves faster and faster forward, the field of medical rehabilitation has to adapt to the time we live in by using technology and intelligent devices. This means changing every part of rehabilitation and finding the most valuable and helpful gadgets that can be used to regain lost functions, keep people healthy, or prevent diseases.
A Portable Three-Layer Compton Camera for Wide-Energy-Range Gamma-ray Imaging: Design, Simulation and Preliminary Testing
Authors: Zhang Jipeng , Xiao Xiong , Chen Ye , Zhang Bin , Ma Xinhua , Ai Xianyun , Li Jinglun
Published: November 2023

(1) Background: The imaging energy range of a typical Compton camera is limited due to the fact that scattered gamma photons are seldom fully absorbed when the incident energies are above 3 MeV. Further improving the upper energy limit of gamma-ray imaging has important application significance in the active interrogation of special nuclear materials and chemical warfare agents, as well as range verification of proton therapy. (2) Methods: To realize gamma-ray imaging in a wide energy range of 0.3~7 MeV, a principle prototype, named a portable three-layer Compton camera, is developed using the scintillation detector that consists of an silicon photomultiplier array coupled with a Gd3Al2Ga3O12:Ce pixelated scintillator array. Implemented in a list-mode maximum likelihood expectation maximization algorithm, a far-field energy-domain imaging method based on the two interaction events is applied to estimate the initial energy and spatial distribution of gamma-ray sources. The simulation model of the detectors is established based on the Monte Carlo simulation toolkit Geant4. The reconstructed images of a 133Ba, a 137Cs and a 60Co point-like sources have been successfully obtained with our prototype in laboratory tests and compared with simulation studies. (3) Results: The proportion of effective imaging events accounts for about 2%, which allows our prototype to realize the reconstruction of the distribution of a 0.05 μSv/h 137Cs source in 10 s. The angular resolution for resolving two 137Cs point-like sources is 15°. Additional simulated imaging of the 6.13 MeV gamma-rays from 14.1 MeV neutron scattering with water preliminarily demonstrates the imaging capability for high incident energy. (4) Conclusions: We conclude that the prototype has a good imaging performance in a wide energy range (0.3~7 MeV), which shows potential in several MeV gamma-ray imaging applications.
Using Interoperability between Mobile Robot and KNX Technology for Occupancy Monitoring in Smart Home Care
Authors: Vanus Jan , Hercik Radim , Bilik Petr
Published: November 2023

It is important for older and disabled people who live alone to be able to cope with the daily challenges of living at home. In order to support independent living, the Smart Home Care (SHC) concept offers the possibility of providing comfortable control of operational and technical functions using a mobile robot for operating and assisting activities to support independent living for elderly and disabled people. This article presents a unique proposal for the implementation of interoperability between a mobile robot and KNX technology in a home environment within SHC automation to determine the presence of people and occupancy of occupied spaces in SHC using measured operational and technical variables (to determine the quality of the indoor environment), such as temperature, relative humidity, light intensity, and CO2 concentration, and to locate occupancy in SHC spaces using magnetic contacts monitoring the opening/closing of windows and doors by indirectly monitoring occupancy without the use of cameras. In this article, a novel method using nonlinear autoregressive Neural Networks (NN) with exogenous inputs and nonlinear autoregressive is used to predict the CO2 concentration waveform to transmit the information from KNX technology to mobile robots for monitoring and determining the occupancy of people in SHC with better than 98% accuracy.
AuCFSR: Authentication and Color Face Self-Recovery Using Novel 2D Hyperchaotic System and Deep Learning Models
Authors: Daoui Achraf , Yamni Mohamed , Altameem Torki , Ahmad Musheer , Hammad Mohamed , Pławiak Paweł , Tadeusiewicz Ryszard , A. Abd El-Latif Ahmed
Published: November 2023

Color face images are often transmitted over public channels, where they are vulnerable to tampering attacks. To address this problem, the present paper introduces a novel scheme called Authentication and Color Face Self-Recovery (AuCFSR) for ensuring the authenticity of color face images and recovering the tampered areas in these images. AuCFSR uses a new two-dimensional hyperchaotic system called two-dimensional modular sine-cosine map (2D MSCM) to embed authentication and recovery data into the least significant bits of color image pixels. This produces high-quality output images with high security level. When tampered color face image is detected, AuCFSR executes two deep learning models: the CodeFormer model to enhance the visual quality of the recovered color face image and the DeOldify model to improve the colorization of this image. Experimental results demonstrate that AuCFSR outperforms recent similar schemes in tamper detection accuracy, security level, and visual quality of the recovered images.
Advancing Network Security with AI: SVM-Based Deep Learning for Intrusion Detection
Authors: Abuali Khadija M. , Nissirat Liyth , Al-Samawi Aida
Published: November 2023

With the rapid growth of social media networks and internet accessibility, most businesses are becoming vulnerable to a wide range of threats and attacks. Thus, intrusion detection systems (IDSs) are considered one of the most essential components for securing organizational networks. They are the first line of defense against online threats and are responsible for quickly identifying potential network intrusions. Mainly, IDSs analyze the network traffic to detect any malicious activities in the network. Today, networks are expanding tremendously as the demand for network services is expanding. This expansion leads to diverse data types and complexities in the network, which may limit the applicability of the developed algorithms. Moreover, viruses and malicious attacks are changing in their quantity and quality. Therefore, recently, several security researchers have developed IDSs using several innovative techniques, including artificial intelligence methods. This work aims to propose a support vector machine (SVM)-based deep learning system that will classify the data extracted from servers to determine the intrusion incidents on social media. To implement deep learning-based IDSs for multiclass classification, the CSE-CIC-IDS 2018 dataset has been used for system evaluation. The CSE-CIC-IDS 2018 dataset was subjected to several preprocessing techniques to prepare it for the training phase. The proposed model has been implemented in 100,000 instances of a sample dataset. This study demonstrated that the accuracy, true-positive recall, precision, specificity, false-positive recall, and F-score of the proposed model were 100%, 100%, 100%, 100%, 0%, and 100%, respectively.
Anomaly Detection of Wind Turbine Driveline Based on Sequence Decomposition Interactive Network
Authors: Lyu Qiucheng , He Yuwei , Wu Shijing , Li Deng , Wang Xiaosun
Published: November 2023

Aimed at identifying the health state of wind turbines (WTs) accurately by using the comprehensive spatio and temporal information from the supervisory control and data acquisition (SCADA) data, a novel anomaly-detection method called decomposed sequence interactive network (DSI-Net) is proposed in this paper. Firstly, a DSI-Net model is trained using preprocessed data from a healthy state. Subsequences of trend and seasonality are obtained by DSI-Net, which can dig out underlying features both in spatio and temporal dimensions through the interactive learning process. Subsequently, the trained model processes the online data and calculates the residual between true values and predicted values. To identify anomalies of the WTs, the residual and root mean square error (RMSE) are calculated and processed by exponential weighted moving average (EWMA). The proposed method is validated to be more effective than the existing models according to the control experiments.
Evaluation of CO2 Adsorption Parameters in Fluidised Zeolite 13X Beds Using Non-Linear Multivariate Optimisation
Authors: Caravella Alessio , Prenesti Giuseppe , De Luca Salvatore , Turano Maria , Testa Flaviano , Girimonte Rossella
Published: November 2023

This work is part of a research project aimed at studying potential sorbents for CO2 capture. The main parameters characterising the adsorption process of zeolite 13X were derived with the aim of overcoming the limits of experimental analysis and thus predicting the performances of the materials of interest. In particular, the main parameters that control the adsorption process of CO2 in zeolite 13X were evaluated through parametric optimisation. This systematic procedure allows for the prediction of the performances of the materials at different operating conditions, identifying the most suitable ones for the case under consideration. Another important application lies in the possibility of a preliminary study of a potential process scale-up for future industrial use. The captured carbon dioxide can be stored or used as a reagent in the production of products with higher economic values, such as methanol, DME and others.
Foreign Aid and Institutional Quality towards Reducing Gender-Based Violence
Authors: Asaleye Abiola John , Strydom Kariena
Published: November 2023

Studies have shown a possible link between women achieving some degree of economic independence through empowerment and a decline in gender-based violence (GBV). However, inadequate funding has been a major challenge in developing economies, while foreign aid has been seen as an alternative funding source. Foreign aid for promoting women’s rights and gender equality is improving in African countries. Yet, according to official statistics, the frequency of GBV in Africa is among the highest in the world. Given this, this paper examines the impact of women’s aid and institutional quality on factors that can reduce GBV using both cross-sectional autoregressive lags to investigate short- and long-run implications and the Panel Vector Correction Model to examine the shock effect of aid on other variables. Also, the mediating role of institutional quality and women’s aid are considered. The metrics used for the factors that reduce GBV are female children out of school, the secondary school gender parity index, the genital mutilation prevalence rate, and the metrics for institutional quality are the rules of law and government effectiveness. The implications from the findings show that enhancing the legal structure is very important in Africa, given the low coefficient values to reduce discrimination against the right to education; more should be done to increase the enrolment of female students through the maximisation of women’s aid in order to achieve the short- and long-term objectives of reducing gender violence. The findings also show that the rule of law significantly aids in the reduction of female genital mutilation in the short and long run; government effectiveness is insignificant. Also, they show that women’s aid also reduces female genital mutilation, albeit at a low rate. The results of this study call for strong enhanced government support and funding to end the practice of female genital mutilation and discrimination against female education in the short and long run.
Complexities of Intergovernmental Relations in Water Service Provision: A Developmental Local Government Perspective
Authors: Khangale Avhavhudzani , Madumo Onkgopotse Senatla , Tshiyoyo Michel Mudikolele
Published: November 2023

Water is a fundamental human right, and its provision is essential for the maintenance of the general quality of life. The South African government has a constitutional obligation to provide clean potable water to all citizens. This study explores the practice of cooperative government among the three spheres of government in the provision of water services to communities in South Africa. It also seeks to analyse the application of the principle of cooperative government as an effective tool for ensuring water service delivery in local government. Thus, to achieve these objectives, the study addresses two research questions: first, what are the complexities associated with intergovernmental relations in the efforts to provide water services to communities? And secondly, how could cooperative government be utilised as a mechanism for water service delivery in local government? This article begins by examining the literature on intergovernmental relations and cooperative government to provide a comprehensive understanding of the topic. A qualitative research method is applied, where interviews were conducted to determine the impact of cooperative governance on water governance. This study sheds light on the complexities associated with intergovernmental relations in the provision of water services to communities. The findings of this study recognise the need for municipalities to continuously monitor and improve their water service delivery strategies and water service delivery plans, to align with the conditions of the municipality and needs of the people. This is significant as it provides useful insights to policy makers, water service providers, and researchers in the field of intergovernmental relations and water service provision on how to address challenges associated with water service delivery within the intergovernmental relations context.
Transient Model for the Hydrodynamic Force in a Hydraulic Capsule Pipeline Transport System
Authors: Zhao Yiming , Li Yongye , Sun Xihuan
Published: November 2023

The hydraulic capsule pipeline (HCP) is an eco-friendly and sustainable pipeline transport option. The freight-carrying capsule is driven by hydraulic pipe flow. Fluid drag is generated by the principal dynamic force effect on the capsule, which could influence the capsule’s motion speed. To make the HCP more efficient, a transient model for the hydrodynamic force in an HCP was developed in this study. From a numerical simulation, the coherent vortex structures of fluctuating modes were observed, and the velocity iso-surfaces of the coherent vortex of the wake flow exhibited an annular trend in circumferential connection. Then, the hydrodynamic force was analyzed: the steady component and transient component were resolved, and the general trend in forces in terms of the transient components was that the maximum amplitude of forces reduced with an increase in mode order. Through short-term Fourier transform, the frequency components and their variations in terms of the entire time range could be acquired. The transient model in this study provided a perspective to build the connection between the flow structures and the hydrodynamic force. By the transient model, the transient component of hydrodynamic force can be explained as the fluctuation of coherent vortex structures.
Smart Management of Energy Storage in Microgrid: Adapting the Control Algorithm to Specific Industrial Facility Conditions
Authors: Kaczorowska Dominika , Rezmer Jacek , Suresh Vishnu , Sikorski Tomasz
Published: November 2023

The article introduces a method for optimizing energy storage system scheduling in industrial microgrids. It employs a PSO-based heuristic algorithm using daily generation and load forecasts. The objective is economic optimization, minimizing energy costs, and maximizing profits. Market energy prices and distributor tariffs are the base of the objective function. An algorithm maintains the plan by controlling storage power based on real-time microgrid measurements, aligning with the intended power exchange curve. Due to PSO’s ability to perform multidimensional optimization, it is possible to find the global optimum of the objective function. To validate the practical applicability of this approach, it is exemplified through its implementation within a real-world industrial microgrid setting. The presented results indicate the method’s effectiveness but also show its weaknesses. For the two considered cases, a decrease in operating costs of 6.7% and 10.8% was achieved, respectively. On the other hand, the best results are obtained for shorter forecasts, which is why the algorithm, despite long planning periods, revises the ESS operation plan whenever there are significant deviations between the forecast and the actual power.
Enhancing Self-Explanation Learning through a Real-Time Feedback System: An Empirical Evaluation Study
Authors: Nakamoto Ryosuke , Flanagan Brendan , Dai Yiling , Yamauchi Taisei , Takami Kyosuke , Ogata Hiroaki
Published: November 2023

This research introduces the self-explanation-based automated feedback (SEAF) system, aimed at alleviating the teaching burden through real-time, automated feedback while aligning with SDG 4’s sustainability goals for quality education. The system specifically targets the enhancement of self-explanation, a proven but challenging cognitive strategy that bolsters both conceptual and procedural knowledge. Utilizing a triad of core feedback mechanisms—customized messages, quality assessments, and peer-generated exemplars—SEAF aims to fill the gap left by traditional and computer-aided self-explanation methods, which often require extensive preparation and may not provide effective scaffolding for all students. In a pilot study involving 50 junior high students, those with initially limited self-explanation skills showed significant improvement after using SEAF, achieving a moderate learning effect. A resounding 91.7% of participants acknowledged the system’s positive impact on their learning. SEAF’s automated capabilities serve dual purposes: they offer a more personalized and scalable approach to student learning while simultaneously reducing the educators’ workload related to feedback provision.
Study on the Stability and Seepage Characteristics of Underwater Shield Tunnels under High Water Pressure Seepage
Authors: Chen Luhai , Xi Baoping , Dong Yunsheng , He Shuixin , Shi Yongxiang , Gao Qibo , Liu Keliu , Zhao Na
Published: November 2023

The construction of underwater shield tunnels under high water pressure conditions and seepage action will seriously impact the stability of the surrounding rock. In this study, an analytical model for the strength of the two-lane shield tunneling construction under anisotropic seepage conditions was established, and a series of simulations were carried out in the engineering background of the underwater section of Line 2 of the Taiyuan Metro in China, which passes through Yingze Lake. The results show that: (1) the surface settlement has a superposition effect, and the late consolidation and settlement of the soil body under seepage will affect the segment deformation and the monitoring should be strengthened; (2) under the influence of the weak permeability of the lining and grouting layers, the pore pressure on both sides of the tunnel arch girdle is reduced by about 72% compared with the initial value, with a larger hydraulic gradient and a 30% reduction at the top of the arch; (3) within a specific range, the tunneling pressure can be increased, and the grouting pressure and the thickness of grouting layer can be reduced to control the segment deformation; (4) the more significant the overlying water level is, the larger the maximum consolidation settlement and the influence range of surface settlement. This study can provide a reliable reference for underwater double-lane shield tunnel design and safety control.
Online Learning and Experiences in Higher Education during COVID-19: A Systematic Review
Authors: Pedraja-Rejas Liliana , Rodríguez-Ponce Emilio , Muñoz-Fritis Camila , Laroze David
Published: November 2023

This paper aims to learn about Chilean teachers and students’ experiences and positions to understand how they coped with online learning during the COVID-19 pandemic. The article focuses on student engagement, virtual professional practices, and the difficulties teachers perceive. A review of articles published in Web of Science, Scopus, and SciELO is carried out to meet the objective. The results show different levels of behavioral, cognitive, and affective engagement of students. Different complications were also identified in the realization of professional practices in virtual modality. The profound impacts that this area had on teacher training were mainly highlighted. Finally, university professors raised difficulties in five aspects: acceptance and use, domestic, technological, organizational, and with students. These findings provide several recommendations for the post-COVID-19 era, which can serve as a guide for policymakers, university managers, and academics.
Sustainability of Informal Artisanal Mining in the Peruvian Andean Region
Authors: Valle Díaz Felipe Rafael , Apaza-Apaza Oscar , Rodriguez-Peceros Rosmel Iván , Huamán-Cuya Alfredo , Valle-Sherón Juan Felipe , Luque-Rivera Jesús Virgilio , Dávila-Ignacio Carlos Vidal , Chaccara-Huachaca Hermenegildo
Published: November 2023

The purpose of this article is to reflect on the sustainability of informal artisanal mining in the Peruvian Andean area until the year 2022. The research is basic and non-experimental in design and ex post facto in scope. The sample consisted of crime prevention statistics on socio-environmental conflict from guardianship institutions and a television program on mining. Our research procedure focused on gathering secondary information for a documentary review analysis based on past proven and disseminated facts. Informal artisanal mining is strengthened in the Peruvian Andean area due to the following influencing factors: support represented as the social license granted by communal assemblies; the flexibility of governmental management in relaxing compliance related to formalization and preventive laws regarding environmental protection; the resistance to formalization and the 50% increase in socio-environmental conflict; and the 25% increase in production costs related agricultural activities, which promotes the displacement towards mining activities. The environmental sustainability consequences are as follows: limited reconversion of agricultural land-use change in one-third of the communal territories at the headwaters of the basin, which generates the displacement of environmentally friendly economic activity, and a parallel positive action is the impossibility of modification or intervention affecting water surfaces and wetlands due to communal agreements that mining companies must respect during operation.
A Review of Optimization for Corrugated Boards
Authors: Fitas Ricardo , Schaffrath Heinz Joachim , Schabel Samuel
Published: November 2023

This paper presents a comprehensive review of optimization practices in the corrugated board industry, which has recently experienced significant interest in using optimization methodologies driven by sustainable demands and increasing computational capabilities. The authors cover different review perspectives, including historical context, manufacturing applications, design optimization, and numerical optimization algorithms used. The main findings of this study indicate that the corrugated board industry has experienced a shift from trial-and-error and expert-driven approaches to data-centric strategies, particularly since the beginning of the 21st century. Interestingly, the industry has also adopted Multi-Disciplinary Optimization techniques from other fields, which demonstrates the importance of knowledge convergence across sectors. However, due to the complex nature of corrugated boards—including materials, design, and manufacturing processes—there is still much research to be done in this area. This work provides guidance for future research directions and encourages innovation and improvement in corrugated board optimization practices. In particular, the strong developments of material models for paper in recent years will boost the use of optimization tools in this field.
Accumulation and Transport of Phthalic Acid Esters in the Soil-Plant System of Agricultural Fields with Different Years of Film Mulching
Authors: Zhang Haiying , Li Jia , Ma Taiyong , Ma Kun , Ni Xilu , Wu Shubao
Published: November 2023

In this study, we investigated the accumulation and transport patterns of phthalate ester (PAEs) compounds in the soil-plant system of maize and cabbage fields under different film mulching years. The total content of five PAEs in the maize fields soil ranged from 156.19 to 566.1 μg kg−1 with film mulching for 0–20 years. The total content of five PAEs in the cabbage field soils ranged from 252.48 to 559.07 μg kg−1 with film mulching for 0–30 years. The PAEs content in cabbage and maize field soils was lower than the environmental quality standards for soil (GB 15618-2008). With the increase in film mulching years, both maize and cabbage soil PAEs contents increased significantly (p < 0.05), while among the five PAEs, the contents of di-n-butyl phthalate (DnBP) and di(2-ethylhexyl) phthalate (DEHP) increased the most significantly, and the content of DEHP in the soils was the highest. The DEHP content in soils planted with maize ranges from 134.03 to 406.79 μg kg−1 with the film mulching for 20 years; while in soil planted with cabbage, it ranges from 229.35 to 405.2 μg kg−1 with the film mulching for 30 years. The DEHP content in all of the soils has not exceed the limit value established by the USEPA in U.S. Five PAEs were detected in maize seeds and cabbage leaves, among which the DEHP content exceeded the maximum residue limit set by the National Food Safety Standard (GB 9685-2016) for DEHP in food after more than 10 years of mulching. The bioaccumulation and translocation factors in cabbage showed a significant positive correlation with the film mulching years. However, the bioaccumulation factor and translocation factor in maize have weak correlations with the film mulching years, possibly due to the lower PAEs content in the deep soil layers where maize roots are distributed. Our research revealed a significant association between the presence and distribution of PAEs in crops and mulching years. These novel discoveries provide fundamental information for controlling PAEs pollution in agricultural environments.
Value Chain Digitalisation and Adoption Intention by Proactive Land Acquisition Strategy (PLAS) Farmers in the Eastern Cape Province, South Africa
Authors: Mazwane Sukoluhle , Makhura Moraka Nakedi , Senyolo Mmapatla Precious , Ginige Athula
Published: November 2023

Digital technologies disrupt agricultural value chains, thereby facilitating enhanced connectivity among various players. This contributes to the development of resilience and sustainability within farms. This study examined behavioural factors that influence farmers’ intentions to adopt value chain digital technologies available in South Africa. A simple random sample of 100 Eastern Cape PLAS farms was chosen. Data was collected using a semi-structured questionnaire. The data was analysed in R and STATA statistical packages using the unified theory of acceptance and use of technology (UTAUT) and structural equation modelling (SEM). The results indicated a significant relationship between performance and effort expectancy and the intention to adopt value technologies. Furthermore, male farmers had a higher expectation of performance and effort. Prioritising performance demonstrations and trainings on the utilisation of these technologies is crucial in efforts to enhance their adoption. This contributes to the existing body of literature on the deployment of value chain technologies.
Influence of Cotton Bleaching Methods on the Parameters of Generated Textile Industrial Wastewater
Authors: Uğur Şule Sultan , Karaboyacı Mustafa , Boguniewicz-Zablocka Joanna
Published: November 2023

The environmental impact of industrial wastewater after bleaching requires special attention to prevent the pollution of aquatic ecosystems. The aim of this study was to compare the effluent parameters obtained after using a traditional bleaching method and an alternative enzymatic bleaching method in order to assess their possible environmental impacts. In the classical bleaching method, NaOH and H2O2 were used, and in the alternative method, pectinase enzyme, H2O2, and sodium carbonate were used as the bleaching agents. The bleaching process was designed by determining the optimum amount of pectinase enzyme, the optimum temperature, and the optimum amount of peroxide. The whiteness of the treated cotton yarns was also evaluated. The different bleaching processes were analyzed and evaluated in terms of the wastewater discharged, the pH, chemical oxygen demand (COD), total dissolved solids (TDS), total suspended solids (TSS), and conductivity. These data show that the use of the pectinase enzyme allows us to obtain much lower COD and TSS values compared to those obtained using traditional bleaching. At the same time, the use of the proposed enzymatic bleaching method reduces the environmental impact since lower concentrations of pollutants are obtained in the effluent. Therefore, the pretreatment of wastewater may require the selection of a simpler and more environmentally friendly technology, such as enzymatic bleaching.
Enhanced Non-Communication-Based Protection Coordination and Advanced Verification Method Using Fault Impedance in Networked Distribution Systems
Authors: Noh Juan , Gham Seungjun , Yoon Myungseok , Chae Wookyu , Kim Woohyun , Choi Sungyun
Published: November 2023

In recent years, the networked distribution system (NDS), which is normally connected to the distribution line (DL), was actively studied as the topology of the future distribution system for reasons such as improving supply reliability, improving line utilization, and increasing the capacity of distribution generators (DGs). However, the NDS creates new issues in terms of protection coordination because of its bidirectional power flow and fault current flow. The issues associated with conventional protection schemes in the NDS include malfunction of protective devices due to bi-directional fault currents and failure of protection coordination due to communication failures between protective devices. When applying a conventional protection method in the NDS, the protection schemes become complicated, and there is a risk of protection coordination failure due to communication failure between protective devices. To solve this problem, this paper proposes an effective and innovative non-communication-based protection algorithm for protection coordination in the NDS. The proposed protection algorithm utilizes fault impedance characteristics, which allow not only determination of whether a fault occurred, but also the ability to identify the exact fault point. Therefore, the proposed method is expected to be sustainably utilized and contribute to developing protection schemes and devices in various system topologies and scenarios in the future. Additionally, this paper addresses the overall concept of hardware-in-the-loop simulation (HILS) and directly verifies the proposed protection algorithm using HILS. Therefore, this study establishes a sustainable foundation for future research on protection coordination using HILS.