bluuebunny/crossref_metadata_2025 huggingface dataset:
A Model for EEG-Based Emotion Recognition: CNN-Bi-LSTM with Attention Mechanism
Authors: Huang Zhentao , Ma Yahong , Wang Rongrong , Li Weisu , Dai Yongsheng
Published: July 2023

Emotion analysis is the key technology in human–computer emotional interaction and has gradually become a research hotspot in the field of artificial intelligence. The key problems of emotion analysis based on EEG are feature extraction and classifier design. The existing methods of emotion analysis mainly use machine learning and rely on manually extracted features. As an end-to-end method, deep learning can automatically extract EEG features and classify them. However, most of the deep learning models of emotion recognition based on EEG still need manual screening and data pre-processing, and the accuracy and convenience are not high enough. Therefore, this paper proposes a CNN-Bi-LSTM-Attention model to automatically extract the features and classify emotions based on EEG signals. The original EEG data are used as input, a CNN and a Bi-LSTM network are used for feature extraction and fusion, and then the electrode channel weights are balanced through the attention mechanism layer. Finally, the EEG signals are classified to different kinds of emotions. An emotion classification experiment based on EEG is conducted on the SEED dataset to evaluate the performance of the proposed model. The experimental results show that the method proposed in this paper can effectively classify EEG emotions. The method was assessed on two distinctive classification tasks, one with three and one with four target classes. The average ten-fold cross-validation classification accuracy of this method is 99.55% and 99.79%, respectively, corresponding to three and four classification tasks, which is significantly better than the other methods. It can be concluded that our method is superior to the existing methods in emotion recognition, which can be widely used in many fields, including modern neuroscience, psychology, neural engineering, and computer science as well.
Defense and Attack Game Strategies of Dual-Network Coupled CPPS with Communication Edge Failures
Authors: Zhu Guopeng , Yu Qiusheng , Xiao Shenyang , Qian Shaobo , Han Guangming , Zhang Yan , Ma Piming
Published: July 2023

With the development of power technology and communication technology, the power grid and power communication network have become interdependent and closely coupled. The load shedding operation of the power grid is an important means to reduce the occurrence of chain faults and ensure the safe and stable operation of the power grid. Based on the transmission of load control services in the communication network, this paper establishes a model for a dual-network coupled cyber physical power system (CPPS). Considering communication edge faults, the associated load capacity of the communication edge and the expected load loss of the power grid are defined. On this basis, the paper proposes a complete information zero-sum game mechanism called “defense attack defense” for communication edge failures, which takes the expected loss of load from the power grid as the benefit. The paper studies the optimal attack and defense game strategies and provides the algorithm implementation process for the three stages of the game. Considering the bandwidth capacity of the communication edge, this paper uses the Dijkstra algorithm or k shortest paths (KSP) algorithm with the cost factor of the communication edge as the weight to plan the main and backup communication channels for multiple load control services. The simulation results show that the game mechanism proposed in this paper can effectively reduce the expected load loss from the power grid and improve the stability of the CPPS.
A Comprehensive Investigation of Winding Eddy and Circulating Current Losses of Stator Iron Coreless PMBLDC Motors
Authors: Yang Liu , Zhao Jing , Fu Wenqi , Liu Xiangdong , Zhu Jianguo , Ai Chao
Published: July 2023

A method is proposed to comprehensively study the eddy and circulating current losses of stator winding wound by multiple parallel strands, to further improve the power density of stator iron coreless permanent magnet brushless DC (PMBLDC) motors. Analytical models of the eddy and circulating current losses in stator winding are deduced firstly to explicitly express the influencing factors of these two losses. As is shown, these factors are mutually contradicting. While the eddy current loss can be greatly reduced by using multiple parallel conductor strands, the circulating current loss will be extensively increased. The factors influencing these two winding losses, such as the strand diameter, magnetization types, and rotating speed, are investigated. A prototype of stator iron coreless PMBLDC motor without an inner rotor core is manufactured and tested to validate the theory. The experimental results of winding eddy and circulating current losses with different combinations of strand diameters and parallel numbers agree well with the theoretical results.
A Hybrid Switched-Inductor/Switched-Capacitor DC-DC Converter with High Voltage Gain Using a Single Switch for Photovoltaic Application
Authors: Shaabani Maryam , Mirzaei Amin , Rezvanyvardom Mahdi , Khosravi Farshad , Gorji Saman A.
Published: July 2023

This paper introduces a new high-step-up, non-isolated switched-inductor switched-capacitor DC-DC converter. The proposed converter remarkably integrates switched-capacitor and switched-inductor cells, leading to a significant increase in voltage gain. This unique composite structure not only ensures the continuity of input current, but also successfully minimizes the current ripple and voltage stress across the components, thereby optimizing efficiency. The standout feature of this converter is its singular switch controlled by pulse-width modulation (PWM), which simplifies its operation. A rigorous steady-state operation analysis is conducted, providing a comprehensive understanding of the converter’s performance. For validating the theoretical findings, the paper also details a real-world prototype of the converter. Comparative studies conducted with other similar structures substantiate the superiority of the proposed converter.
Numerical Heat Transfer and Fluid Flow: New Advances
Authors: Bartosik Artur S.
Published: July 2023

This Special Issue, titled ‘Numerical Heat Transfer and Fluid Flow 2022’, presents articles addressed to Energies and is a continuation of the 2021 edition [...]
Evaluation of the Primary Energy and Carbon Dioxide Emissions of a Passive Ventilation System with a Solar Air Heater
Authors: Matsunaga Junichiro , Kikuta Koki , Hirakawa Hideki , Hayashi Motoya , Fukushima Akira
Published: July 2023

Improvements in envelope performance have reduced heat loss from insulation, and the ratio of heat loss through ventilation load has become relatively large. In recent years, the use of heat recovery ventilation systems (HRV) has particularly increased. However, ventilation generates not only ventilation load but also air conveying fan power, such that conserving energy for both is important. Therefore, this paper focuses on a passive ventilation system with a solar air heater (PVSAH), which is a passive ventilation system that does not use air conveying fan power and uses a solar air heater that uses solar energy. The total energy consumption of the PVSAH, the widely used mechanical exhaust ventilation system (EV), and the HRV, which has high energy efficiency, was compared with the ventilation load plus air conveying fan power. The primary energy evaluation and carbon dioxide (CO2) emissions were compared by region, and the optimal system was proposed according to regional characteristics. In warmer zones, the PVSAH saved the most energy, while the HRV increased energy consumption. The comparison of CO2 emissions by ventilation systems when using heat pumps for cooling and heating showed that PVSAH > MEV > HRV for Heating Degree-Day (HDD) 1500 and below, PVSAH > HRV > MEV for HDD 1500 to 2750, and HRV > PVSAH > MEV for HDD 2750 and above. MEV were favored in that order. As the CO2 emission factor decreases, the difference in CO2 emissions between systems decreases. If the difference in emissions becomes smaller, then considering the initial and running costs and the risk of failure of the system is crucial. A simple system configuration with low risks of failure and maintenance, such as PVSAH, may prove advantageous in the future.
Optimal Scheduling of Power Systems with High Proportions of Renewable Energy Accounting for Operational Flexibility
Authors: Lin Yi , Lin Wei , Wu Wei , Zhu Zhenshan
Published: July 2023

The volatility and uncertainty of high-penetration renewable energy pose significant challenges to the stability of the power system. Current research often fails to consider the insufficient system flexibility during real-time scheduling. To address this issue, this paper proposes a flexibility scheduling method for high-penetration renewable energy power systems that considers flexibility index constraints. Firstly, a quantification method for flexibility resources and demands is introduced. Then, considering the constraint of the flexibility margin index, optimization scheduling strategies for different time scales, including day-ahead scheduling and intra-day scheduling, are developed with the objective of minimizing total operational costs. The intra-day optimization is divided into 15 min and 1 min time scales, to meet the flexibility requirements of different time scales in the power system. Finally, through simulation studies, the proposed strategy is validated to enhance the system’s flexibility and economic performance. The daily operating costs are reduced by 3.1%, and the wind curtailment rate is reduced by 4.7%. The proposed strategy not only considers the economic efficiency of day-ahead scheduling but also ensures a sufficient margin to cope with the uncertainty of intra-day renewable energy fluctuations.
Analysis of Interharmonics Generation in Induction Motors Driven by Variable Frequency Drives and AC Choppers
Authors: Gudiño-Ochoa Alberto , Jalomo-Cuevas Jaime , Molinar-Solís Jesús Ezequiel , Ochoa-Ornelas Raquel
Published: July 2023

In modern power systems, interharmonics have emerged as noninteger frequency components that appear in current or voltage signals. Double-stage AC-DC-AC converters have been identified as a primary source of interharmonics. Previous studies have highlighted modulation techniques, filters, passive components, unbalanced conditions and DC link effects as relevant factors. However, the interaction between these factors and the inertial properties of induction motors has not been explored. This study assesses various types of AC drives, including variable frequency drives (VFDs) and soft starters (AC choppers), to investigate their interaction with machine inertial properties in interharmonic generation. The employed technique for time-frequency spectral analysis is the wavelet synchrosqueezed transform combined with a clustering method. This paper demonstrates that the interaction of the inertial properties of low-power induction motors with the variations of the switching frequencies of the VFDs, the filters used in the DC link and a soft start indirectly contribute to harmonic generation and potentially to interharmonics in the electrical grid and the outputs of the inverter.
Empowering Tomorrow’s Problem Solvers: Nexus Thinking and CLEWs Modelling as a Pedagogical Approach to Wicked Problems
Authors: Martindale Leigh , Cannone Carla , Niet Taco , Hodgkins Richard , Alexander Kane , Howells Mark
Published: July 2023

The increasing prevalence of wicked problems, such as climate change, requires a transformation in education that equips students with the skills, competencies and knowledge to address these complex challenges. Wicked problems are characterised by their incomplete, contradictory, and ever-changing requirements, rendering them difficult to resolve due to intricate interdependencies. Nexus thinking offers a valuable approach to these problems, as it emphasises the interconnectedness of various systems, fostering a more comprehensive understanding of the challenges at hand. In this paper, we propose the use of Climate, Land, Energy, and Water (CLEWs) modelling as an innovative pedagogical strategy tool to cultivate nexus thinking among students. Building upon the pioneering CLEWs pedagogical work of Shivakumar et al., in their ‘Introduction to CLEWs’ Open Learn course, we demonstrate how this approach can be utilised in a Higher Education (HE) setting in the form of a Masters’ module for geography students.
Impact of a Redox Flow Battery on the Frequency Stability of a Five-Area System Integrated with Renewable Sources
Authors: Jena Narendra Kumar , Sahoo Subhadra , Sahu Binod Kumar , Naik Amiya Kumar , Bajaj Mohit , Misak Stanislav , Blazek Vojtech , Prokop Lukas
Published: July 2023

Energy storage devices are imperative to damp out the oscillations caused by sudden magnified disturbances occurring in a power system. The presence of a small rating of storage device in each area can alleviate the system oscillations effectively. Therefore, in this work, redox flow batteries (RFBs) have been integrated in each area of a five-area interconnected system for effective load frequency control (LFC). The RFB pumps up the active power into the system quickly to meet the short-time overload; in turn, the efficacy of the LFC in the system is boosted. Despite the presence of the RFB in the power system, a secondary controller is necessary to quench the deviation of frequency and tie-line power caused by the power mismatch between demand and generation. In this perspective, a cascade controller incorporated with a fractional operator (FO) has been endorsed and designed through a nascent selfish herd optimizer technique to evaluate the transient response of the system. Besides this, the unprecedented performance of fractional-order cascade controllers has been compared with one-stage classical controllers with and without a fractional operator. Further, the robustness of the proposed controller has been inspected through subjecting it to a random load in the presence/absence of an RFB and parametric variation. Finally, the proposed model has been simulated in the OPAL-RT-4510 platform to validate the performance of the proposed controller that has produced in the MATLAB environment.
Climate Impact Comparison of Biomass Combustion and Pyrolysis with Different Applications for Biochar Based on LCA
Authors: Safarian Sahar
Published: July 2023

Biochar can be useful to overcome several environmental challenges in different sectors of energy, industry, and agriculture. However, there are currently only a limited number of studies with the employment of biochar for various applications and their environmental impacts. This study develops an LCA framework to evaluate the climate impacts of biochar production and its applications in soil enhancement and as a substitute for coal-based fuels in steel industries and then compares it with conventional biomass usage for energy production for Sweden, Italy, and Poland. Various pyrolysis operating temperatures are also considered to determine the optimal conditions for each location. The results show that biomass pyrolysis with biochar usage in the agricultural sector has the least environmental impact with the most significant potential in Poland followed by Italy. lower temperatures (around 350 °C) are more favorable for Sweden in terms of CO2 emissions, due to the country’s renewable energy-based electrical system. Low to moderate temperatures (350–500 °C) are found to be optimal for pyrolysis temperature in Italy, while higher temperatures (around 650 °C) yield the highest GHG reduction for both biochar applications in Poland.
Paper Review of External Integrated Systems as Photovoltaic Shading Devices
Authors: Corti Paolo , Bonomo Pierluigi , Frontini Francesco
Published: July 2023

The building sector contributes to 40% of the total final energy consumption and 36% of CO2 emissions in Europe, and these are set to increase in the coming years. International directives are pushing towards a decarbonisation roadmap to improve the quality of cities and the health of citizens. Buildings have a potentially central role in terms of energy transition as a means to produce and save energy. Photovoltaic shading devices (PVSDs) protect buildings from direct solar radiation and overheating while producing renewable electricity onsite and increasing the users’ thermal comfort. Even though the potential of the PVSD is considerable, the sector is still unexplored, and few studies on the topic are available in the literature. This systematic review aims to present an exhaustive overview of the current literature on state-of-the-art PVSDs by analysing the scientific framework in terms of the status of the research. It presents a performance-based approach focusing on innovative products, PVSD design strategies, and energetic performance in distinct climate conditions and configurations. In particular, 75 articles and about 250 keywords were identified, selected, and analysed. The literature review serves as a basis for further R&D activities led by both the industrial and the academic sectors.
An Influence of Parameters of the Control Signal of Power LEDs on Their Junction Temperature and Emitted Light
Authors: Górecki Krzysztof , Ptak Przemysław , Gensikowski Michał
Published: July 2023

This article presents the method of implementation and the results of experimental investigations illustrating an influence of parameters of the signal controlling the current flowing through power LEDs on their junction temperature and on parameters characterizing the light emitted by them. The measurement system used and the tested power LEDs are described. The results of measurements of the junction temperature of the tested devices, the values of the average value of the power dissipated in the tested devices and the photometric and radiometric parameters of these devices obtained for different values of frequency and the duty cycle of the signal controlling the current flowing through the tested diodes are presented and discussed. It is shown that the operation of the considered semiconductor devices is more effective at low frequency values. The possibility of adjusting the optical parameters of the power LEDs in the considered range of frequency and the duty cycle adjustment is assessed. Additionally, the measured waveforms of the current supplying the tested LEDs is shown. The influence of the parasitic capacitances of the tested devices is discussed. On the basis of the obtained investigation results, some recommendations for the designers of lighting systems can be formulated. In order to obtain an almost linear dependence of the illuminance on the duty cycle, the values of frequency not exceeding 10 kHz should be used.
A New Digital Twins-Based Overcurrent Protection Scheme for Distributed Energy Resources Integrated Distribution Networks
Authors: Gómez-Luna Eduardo , Candelo-Becerra John E. , Vasquez Juan C.
Published: July 2023

This paper presents a novel overcurrent protection scheme based on digital twins for a distribution network with distributed energy resources. A coordination protection standard is employed to perform settings and coordinate intelligent electronic devices, evaluating the effects of distributed energy resources. In addition, some integration criteria for distributed energy resources are proposed to identify the impact on overcurrent protections. The power hardware-in-the-loop (PHIL) scheme is designed to develop digital twins (DT) that connect the real relays to the simulated network. Moreover, a standard for substation automation is employed to define the communication protocol for reading Generic Object-Oriented Substation Events (GOOSE) messages. Furthermore, the IEEE 13-node test feeder is employed to validate the method and model in the real-time simulation software. The results show a miscoordination of the overcurrent protection scheme installed in the distribution network with the action of different distributed energy resources.
A Study of the Decoupling of Economic Growth from CO2 and HFCs Emissions in the EU27 Countries
Authors: Cautisanu Cristina , Hatmanu Mariana
Published: July 2023

Economic activities are directly supported by the natural environment, and in this context, it has become crucial to analyse the phenomenon of decoupling economic growth from environmental degradation. The negative effects of economic activities on the environment are clearly visible, and understanding how to separate economic growth from environmental harm is of utmost importance. This paper aims to study the degree of the decoupling of economic growth, measured by GDP, from environmental degradation, quantified through CO2 and HFCs emissions, at the level of each EU27 country in the periods 2008–2012 and 2013–2020. In the analysis, graphical representations and statistical tests were utilised. In the first period, most of the EU27 countries registered negative levels for the variables considered, placing them into the negative coupling stage. In the second period, the evolution of the decoupling process was visible in all the countries, enabling them to make a significant transition to the relative or absolute stages. Overall, the Nordic countries could be observed as examples of best practices, managing to achieve the most desired stage of decoupling, i.e., the absolute one. These results are important for a wide range of stakeholders implicated in the preparation of programs, projects and policies dedicated to achieving economic growth in a sustainable manner.
Influence of Catalyst on the Yield and Quality of Bio-Oil for the Catalytic Pyrolysis of Biomass: A Comprehensive Review
Authors: Reza Md , Iskakova Zhanar , Afroze Shammya , Kuterbekov Kairat , Kabyshev Asset , Bekmyrza Kenzhebatyr , Kubenova Marzhan , Bakar Muhammad , Azad Abul , Roy Hridoy , Islam Md
Published: July 2023

In the modern world, as the population rises and fossil fuel supplies decline, energy demands continue to rise. Moreover, the use of fossil fuels harms the ecology, contributing to pollution and global warming. In order to overcome these difficulties, several approaches are revealed, such as the utilization of biomass as a renewable source of energy. Studies revealed that biomass can be converted into bioenergy via several thermal conversion processes, like pyrolysis, gasification, and torrefaction. Pyrolysis is the most convenient process to obtain three different types of biofuels (biochar as a solid, bio-oil as a liquid, and syngas as a gas). The biofuels produced in this process are normally lower in quality and cannot be used directly as fuel because they contain many undesirable components. Catalytic pyrolysis is one of the best processes to upgrade the quality of biofuels. Several varieties of catalysts are used in the catalytic pyrolysis process (ex situ and in situ). Due to stable operating conditions, both catalytic and non-catalytic pyrolysis procedures produce biochar that has a consistent output. Meanwhile, the effects of catalysts in the catalytic pyrolysis process considerably enhance the quality and quantity of bio-oils and syngas. By removing the unwanted oxygenated and nitrogenous components, the bio-oils produced through the catalytic pyrolysis method have a higher calorific value, reduced viscosity, and improved stability. Many researchers have looked at ways to increase the rate of pyrolysis, whereas a few have focused on maximizing the effects of the factors in order to improve the efficiency of catalytic pyrolysis. This review addresses the impact of catalysts on the catalytic pyrolysis of biomass to enhance the quality of the bio-oils in great detail. Machine learning and techno-economic analysis were investigated, as well as the future potential of the catalytic pyrolysis method for the generation of bio-oil.
Evaluation of Selected Dynamic Parameters of Rotating Turbocharger Units Based on Comparative Model and Bench Tests
Authors: Mazurkow Aleksander , Homik Wojciech , Lewicki Wojciech , Łosiewicz Zbigniew
Published: July 2023

Obtaining the best operating parameters of the internal combustion engine has focused the attention of designers and researchers since the first years of its creation. Initial research focused on increasing engine power and overall efficiency. As time passed, these aspirations became more sophisticated and began to concern other operating parameters of the drive unit. The basic problem, however, remained the improvement of filling the cylinder with the working medium. Turbocharger charging consists in using the energy of the exhaust gases to drive a turbine placed on a common shaft with a compressor supplying air under increased pressure to the cylinders. Over time, the turbocharger became one of the key elements and its technical condition began to play a key role in the operation and performance of modern drive units. Like every element, the turbocharger itself is not without its faults. This procedure is known among manufacturers who, when designing power units and their assemblies, pay special attention to the essence of turbocharger construction. Since it is impossible to predict all the phenomena accompanying a working turbocharger at the design stage, the authors of this paper conducted bench tests of a selected batch of turbochargers, focusing mainly on the vibration measurements of the turbocharger rotating assembly. At the same time, we present a dynamic model of the mentioned system based on the analyses resulting from the solutions of the equations of a numerical model. In order to give the research a practical aspect, the results of the theoretical research were compared with the results of bench tests. It has been shown that the basic problem is to guarantee the correct operating parameters of the bearings in the position of static and dynamic equilibrium. Obtaining such operating parameters requires finding a compromise solution, e.g., between the maximum temperature in oil films and the amplitudes of vibration accelerations in bearing nodes. The research results presented in the article can be used as a field for further discussion in the field of research on the reliability of turbochargers and be helpful in the design process in order to avoid design errors and reduce production costs.
Characterization of Wind Resources of the East Coast of Maranhão, Brazil
Authors: Pimenta Felipe M. , Saavedra Osvaldo R. , Oliveira Denisson Q. , Assireu Arcilan T. , Torres Júnior Audálio R. , de Freitas Ramon M. , Neto Francisco L. Albuquerque , Lopes Denivaldo C. P. , Oliveira Clóvis B. M. , de Lima Shigeaki L. , Neto João C. de Oliveira , Veras Rafael B. S.
Published: July 2023

The objective of this work is to assess the wind resources of the east coast of Maranhão, Brazil. Wind profilers were combined with micrometeorological towers and atmospheric reanalysis to investigate micro- and mesoscale aspects of wind variability. Field campaigns recorded winds in the dry and wet seasons, under the influence of the Intertropical Convergence Zone. The dry season was characterized by strong winds (8 to 12 m s−1) from the northeast. Surface heat fluxes were generally positive (250 to 320 W m−2) at midday and negative (−10 to −20 W m−2) during the night. Convective profiles predominated near the beach, with strongly stable conditions rarely occurring before sunrise. Further inland, convective to strongly convective profiles occurred during the day, and neutral to strongly stable profiles at night. Wind speeds decreased during the rainy season (4 to 8 m s−1), with increasingly easterly and southeasterly components. Cloud cover and precipitation reduced midday heat fluxes (77 W m−2). Profiles were convective during midday and stable to strongly stable at night. Terrain roughness increased with distance from the ocean ranging from smooth surfaces (zo = 0.95 mm) and rough pastures (zo = 15.33 mm) to crops and bushes (zo = 52.68 mm), and trees and small buildings (zo = 246.46 mm) farther inland. Seasonal variations of the mean flow and sea and land breezes produced distinct diurnal patterns of wind speeds. The strongest (weakest) breeze amplitudes were observed in the dry (rainy) period. Daily changes in heat fluxes and fetch over land controlled the characteristics of wind profiles. During sea breezes, winds approached the coast at right angles, resulting in shorter fetches over land that maintained or enhanced oceanic convective conditions. During land breezes, winds blew from the mainland or with acute angles against the coastline, resulting in large fetches with nighttime surface cooling, generating strongly stable profiles. Coastal observations demonstrated that with increasing monopiles from 100 to 130 m it is possible to obtain similar capacity factors of beachfront turbines.
Impedance Acquisition of Proton Exchange Membrane Fuel Cell Using Deeper Learning Network
Authors: Xie Jiaping , Yuan Hao , Wu Yufeng , Wang Chao , Wei Xuezhe , Dai Haifeng
Published: July 2023

Electrochemical impedance is a powerful technique for elucidating the multi-scale polarization process of the proton exchange membrane (PEM) fuel cell from a frequency domain perspective. It is advantageous to acquire frequency impedance depicting dynamic losses from signals measured by the vehicular sensor without resorting to costly impedance measurement devices. Based on this, the impedance data can be leveraged to assess the fuel cell’s internal state and optimize system control. In this paper, a residual network (ResNet) with strong feature extraction capabilities is applied, for the first time, to estimate characteristic frequency impedance based on eight measurable signals of the vehicle fuel cell system. Specifically, the 2500 Hz high-frequency impedance (HFR) representing proton transfer loss and 10 Hz low-frequency impedance (LFR) representing charge transfer loss are selected. Based on the established dataset, the mean absolute percentage errors (MAPEs) of HFR and LFR of ResNet are 0.802% and 1.386%, respectively, representing a superior performance to other commonly used regression and deep learning models. Furthermore, the proposed framework is validated under different noise levels, and the findings demonstrate that ResNet can attain HFR and LFR estimation with MAPEs of 0.911% and 1.610%, respectively, even in 40 dB of noise interference. Finally, the impact of varying operating conditions on impedance estimation is examined.
Deep-Learning-Based Detection of Transmission Line Insulators
Authors: Zhang Jian , Xiao Tian , Li Minhang , Zhou Yucai
Published: July 2023

At this stage, the inspection of transmission lines is dominated by UAV inspection. Insulators, as essential equipment for transmission line equipment, are susceptible to various factors during UAV detection, and their detection results often lead to leakages and false detection. Combining deep learning detection algorithms with the UAV transmission line inspection system can effectively solve the current sensing problem. To improve the recognition accuracy of insulator detection, the MS-COCO pre-training strategy that combines the FPN module with a cascading R-CNN algorithm based on the ResNeXt-101 network is proposed. The purpose of this paper is to systematically and comprehensively analyze mainstream isolator detection algorithms at the current stage and to verify the effectiveness of the improved Cascade R-CNN X101 model by combining the mAP (mean Average Precision) value and other related evaluation indices. Compared with Faster R-CNN, Retina Net, and other detection algorithms, the model is highly accurate and can effectively deal with the false detection, leakage, and non-recognition of the environment in online special detection. The research in this paper provides a new idea for intelligent fault detection of transmission line insulators and has some reference value for engineering applications.
Decision Tree Models and Machine Learning Algorithms in the Fault Recognition on Power Lines with Branches
Authors: Kulikov Aleksandr , Loskutov Anton , Bezdushniy Dmitriy , Petrov Ilya
Published: July 2023

The complication of the structure, topology and composition of the future electrical networks is characterized by difficult-to-recognize circuit-mode situations and requires modern methods for analyzing information parameters. The growing trend of digitizing signals in substations and the use of the IEC 61850 standard results in a huge amount of new data available at the nodes of the electrical network. The development and analysis of new methods for detecting and recognizing the modes of electrical networks (normal and emergency) are topical research issues. The article explores a new approach to recognizing a faulted section of an electrical network with branches by concurrently analyzing several information features and applying machine learning methods: decision tree, random forest, and gradient boosting. The application of this approach for decision-making by relay protection has not been previously implemented. Simulation modeling and the Monte Carlo method are at the heart of obtaining training samples. The results of testing the studied methods under review showed the required flexibility, the ability to use a large number of information parameters, as well as the best results of fault recognition in comparison with the distance protection relay.
How Vegetation Colorization Design Affects Urban Forest Aesthetic Preference and Visual Attention: An Eye-Tracking Study
Authors: Chen Ziru , Huang Yaling , Shen Yuanping , Fu Weicong , Yao Xiong , Huang Jingkai , Lan Yuxiang , Zhu Zhipeng , Dong Jiaying
Published: July 2023

The enhancement of the urban forest landscape through vegetation colorization has emerged as a continuous concern for urban managers in southern Chinese cities. However, the understanding of how designers can effectively select the appropriate form and intensity of colorization design to align with users’ aesthetic preferences remains limited. The process of visual perception is closely intertwined with eye movements. Employing visualization techniques, this research aims to investigate the impact of colorization design on aesthetic benefits and eye movements in urban forests, considering four intensities (slight, low, medium, and high) and three forms (aggregate, homogeneous, and random). A total of 183 participants (with an average age of 23.5 ± 2.5 years) were randomly assigned to three groups to assess the aesthetics score, while eye-tracking devices were utilized to record eye movement behaviors. The outcomes indicate that a homogeneous design form and a moderate intensity of landscaping yield higher scenic benefits for urban forests. In the case of canopy landscape, both the form and intensity of landscaping have a significant influence on urban forest aesthetics. The HCI with aggregate form showed the best marginal effect (1.313). In contrast, MCI showed the best marginal effect when the design form was random and homogeneous (1.438, 1.308). Furthermore, although the form and intensity of the colorization design significantly affect eye exploration, the perception of landscape aesthetics does not correlate with eye movements. These findings provide valuable insights for design policies aimed at promoting the urban forest landscape, while also contributing to the enrichment of research in landscape perception studies employing eye-tracking technology.
Individual Tree AGB Estimation of Malania oleifera Based on UAV-RGB Imagery and Mask R-CNN
Authors: Gong Maojia , Kou Weili , Lu Ning , Chen Yue , Sun Yongke , Lai Hongyan , Chen Bangqian , Wang Juan , Li Chao
Published: July 2023

Forest aboveground biomass (AGB) is an important research topic in the field of forestry, with implications for carbon cycles and carbon sinks. Malania oleifera Chun et S. K. Lee (M. oleifera) is a valuable plant species that is listed on the National Second-Class Protected Plant checklist and has received global attention for its conservation and resource utilization. To obtain accurate AGB of individual M. oleifera trees in a fast, low-finance-cost and low-labor-cost way, this study first attempted to estimate individual M. oleifera tree AGB by combining the centimeter-level resolution RGB imagery derived from unmanned aerial vehicles (UAVs) and the deep learning model of Mask R-CNN. Firstly, canopy area (CA) was obtained from the 3.5 cm high-resolution UAV-RGB imagery using the Mask R-CNN; secondly, to establish an allometric growth model between the diameter at breast height (DBH) and CA, the correlation analysis of both was conducted; thirdly, the AGB estimation method of individual M. oleifera trees was presented based on an empirical equation. The study showed that: (1) The deep learning model of Mask R-CNN achieved an average segmentation accuracy of 90% in the mixed forests to the extraction of the canopy of M. oleifera trees from UAV-RGB imagery. (2) The correlation between the extracted CA and field-measured DBH reached an R2 of 0.755 (n = 96). (3) The t-test method was used to verify the predicted and observed values of the CA-DBH model presented in this study, and the difference in deviation was not significant (p > 0.05). (4) AGB of individual M. oleifera was estimated for the first time. This study provides a reference method for the estimation of individual tree AGB of M. oleifera based on centimeter-level resolution UAV-RGB images and the Mask R-CNN deep learning.
Modeling Free Branch Growth with the Competition Index for a Larix principis-rupprechtii Plantation
Authors: Liu Yongkai , Wang Dongzhi , Zhang Zhidong , Liu Qiang , Zhang Dongyan , Xu Zhongqi
Published: July 2023

Competition among free branches in the tree canopy is an important factor influencing branch length growth. Therefore, there is a need to quantify this competition and to understand the impact of the regression technique on the predictive accuracy of the growth of free branch length (GFBL) model in a Larix principis-rupprechtii plantation. This study focused on an L. principis-rupprechtii plantation in Saihanba Mechanized Forest Farm. Five competition indices based on 2176-branch data points from 76 trees were used to quantify the branch competition, and three regression techniques (nonlinear least squares (NLS), nonlinear mixed-effects model (NLME), and nonlinear quantile regression (NQR)) were used to construct the GFBL model including the branch competition index. The results showed that the Chapman–Richards growth function, including the diameter at breast height (DBH) and depth of branch into crown (DINC), was the optimal equation for describing the GFBL in the studied L. principis-rupprechtii plantation. The branch competition index (CI) was found to be optimal for quantifying the branch competition when used with the maximum value parameter (a0) of the Chapman–Richards growth function. The three parameter estimation methods were compared, and the NLME, which included the CI, was found to have the highest predictive accuracy. The results of this study can act as a reference for improving the management, assessing the management effectiveness, and enhancing the quality of L. principis-rupprechtii plantations.
Afforestation Alters the Molecular Composition of Soil Organic Matter in the Central Loess Plateau of China
Authors: Song Xueshu , Guo Jingwen , Wang Xiao , Du Zhangliu , Ren Rongxiu , Lu Sen , He Chunxia
Published: July 2023

Many studies have been conducted on organic carbon changes under different land use patterns, but studies and data concerning changes in the molecular composition of soil organic matter (SOM) during land use conversion are scarce. In this work, we studied the chemical composition of SOM on two Robinia pseudoacacia L. plantations and their adjacent croplands in the Loess Plateau using biomarker and nuclear magnetic resonance (NMR) techniques. Experimental data on the molecular composition of SOM showed that the soil microbial biomass carbon content initially decreased and then returned to the original level gradually after afforestation, while the SOM content and stocks increased over time. At the initial stage of afforestation, the content of total solvent extracts did not change significantly but changed slowly over time in the plantations without artificial disturbance. With an increase in restoration time, the concentrations of both the microbial- and plant-derived solvent extracts increased. Moreover, the concentrations of plant-derived solvent extracts were consistently lower than those of microbial-derived solvent extracts. Afforestation also significantly increased the lignin-derived phenol content in the surface soil layer (0–10 cm). However, no obvious change was observed in the lignin-derived phenols of the two adjacent croplands. These results indicate that the accumulation of aboveground litter and underground roots has the strongest effects on the lignin-derived phenol content. In contrast to cropland, the two plantations exhibited a high degree of degradation of lignin-derived phenols in the surface soil, but this remained almost unchanged over time. Moreover, in contrast to 20 years after the establishment of the R. pseudoacacia plantation, the low alkyl/O-alkyl carbon ratio of the 8-year R. pseudoacacia plantation indicated that more easily degradable components accumulated during the initial stage of afforestation. Therefore, the proportion of the unstable carbon pool was relatively high and the SOM content may decline in the early stage of afforestation. These results provide evidence illustrating the detailed changes in the chemical composition of SOM during the ecological restoration process.
Recent Applications of Smart Technologies for Monitoring the Sustainability of Forest Operations
Authors: Venanzi Rachele , Latterini Francesco , Civitarese Vincenzo , Picchio Rodolfo
Published: July 2023

Precision forestry is a useful technique to help forest stakeholders with proper sustainable forest management. Modern sensors and technologies, with special reference to the sustainability of forest operations, can be applied on a variety of levels, including the monitoring of forest activities regarding the three pillars (economy, environment, and society). In this review, we summarised the current level of knowledge regarding the use of precision forestry techniques for monitoring forest operations. We concentrated on recent data from the last five years (2019–2023). We demonstrated how an Industry 4.0 strategy for remote and proximal monitoring of working performance can be effective when using CAN-bus and StanForD data collected by modern forest machines. The same information can be effectively used to create maps of soil trafficability and to evaluate the patterns of skid tracks or strip roads built as a result of forest intervention. Similar information can be gathered in the case of small-scale forestry by using GNSS-RF (Global Navigation Satellite Systems—Radio Frequency) or even monitoring systems based on smartwatches or smartphones. LiDAR and Structure for Motion (SfM) photogrammetry are both useful tools for tracking soil rutting and disturbances caused by the passage of forest machinery. SfM offers denser point clouds and a more approachable method, whereas laser scanning can be considerably faster but needs a more experienced operator and better data-processing skills. Finally, in terms of the social component of sustainability, the use of location sharing technologies is strongly advised, based for instance on GNSS—RF to monitor the security of forest workers as they operate.
Study of Crack Generation and Expansion Behavior of Frame-Supported Float Glass after Heat Exposure
Authors: Zhang Yanni , Huang Luoxin , Deng Jun , Feng Zhichao , Yang Dan , Liu Xuemeng , Zhang Shuai
Published: July 2023

Float glass installed with frame supports is broadly exploited in building construction. In a fire environment, the breakage of float glass significantly influences the dynamic development of the fire within the building space. The thermal rupture behavior of the frame-supported float glass subjected to thermal loading is carefully examined using a self-built experimental system. The designed system is aimed at capturing crucial behavioral parameters. The experimental study reveals that the main reason for the breakage of the frame-supported float glass is the temperature difference on the glass surface, with a critical temperature difference of approximately 65 °C. The crack starts at the edge of the glass surface where the temperature difference is maximum and then rapidly expands. By intersecting the cracks, a crack island is configured, which is not dislodged under the stress of the supporting frame and the surrounding glass. A thermomechanical and micro-geometric model of the frame-supported float glass is developed based on the PFC2D program to show further the micro-crack expansion pattern of the frame-supported float glass under thermal loading. This scrutiny provides theoretical guidance for installing and using frame-supported float glass in construction projects and identifying fire evidence.
Technological and Sensory Quality of Gluten-Free Pasta Made from Flint Maize Cultivars
Authors: Bongianino Nicolás Francisco , Steffolani María Eugenia , Morales Claudio David , Biasutti Carlos Alberto , León Alberto Edel
Published: July 2023

The development of quality gluten-free products presents a major technological challenge in terms of structure, texture, and shelf life. However, there is insufficient information available to identify genotypes for obtaining gluten-free maize pasta of good acceptability and technological quality. The objective of this work was to evaluate the technological and sensory quality of gluten-free pasta made from different maize cultivars. The flint open-pollinated variety, flint inbred line, and three dent commercial hybrids were used. Grain and flour’s physical characteristics and chemical composition were determined. Gluten-free pasta was made via extrusion, and its quality traits were studied. A sensory evaluation test was carried out. Flint cultivars showed the lowest values on swelling index (both 1.77) and water absorption (124.30 and 134.58%). Pasta swelling index showed a negative association r = −0.77 to sodium carbonate retention capacity (p = 8.5 × 10−5) and water retention capacity (p = 6.6 × 10−5). Evaluators’ preference results showed a higher frequency of choices at the top level of preference (4) for the flint open-pollinated variety C6006. Thus, evaluators’ choices showed a positive association between sample preference and firmness. Pasta preference and technological quality have a direct relationship with fast tests over grain, such as test weight and float index.