bluuebunny/crossref_metadata_2025_split huggingface dataset:
A two-layer planning model for source storage in distribution networks based on SSA-AVOA intelligent combination algorithm
Authors: Feng Nan , Jiang Leilei , Wang Zhen , Gao Ming , Song Dongming 
Published: December 2024

Abstract
As renewable energy sources become more integrated into the power grid, their output uncertainty presents several challenges, including increased planning costs for the distribution network, potentially reduced economic benefits, and decreased operational stability, which can elevate safety risks. To address these issues, a two-layer planning model for the distribution network has been proposed. The upper layer focuses on minimizing the total cost, while the lower layer targets reductions in total operating costs and voltage deviations. This model utilizes a hybrid search algorithm that combines the Sparrow Search Algorithm (SSA) with the African Vulture Optimization Algorithm (AVOA) to optimize site selection and capacity determination for distributed photovoltaic (PV) systems and energy storage systems (ESS). Experimental results show that this model effectively achieves a Pareto optimal front, balancing both economic and security considerations in the distribution network system.
State of charge estimation for lithium-ion batteries based on Gated Recurrent Unit neural network and an Adaptive Unscented Kalman Filter
Authors: Song Wei , Zhao Chengji , Yang Chao , Wu Mingda , Qiu Shaoxiang , An Rongbang 
Published: December 2024

Abstract
For battery management systems, the accurate estimation of the state of charge (SOC) of lithium-ion batteries is crucial, yet it still poses challenges. Traditional model-based filtering methods typically require accurate battery models, but parameter uncertainties arise from various factors such as battery aging and temperature variations, leading to parameter uncertainties. In contrast, data-driven approaches can effectively capture SOC variations under different operating conditions and temperatures, but often exhibit significant prediction fluctuations. To address these challenges, a combined SOC estimation approach known as GRU-AUKF is presented in this paper. This method utilizes Gated Recurrent Unit (GRU) networks based on temperature, current, and voltage to estimate SOC, followed by filtering the output using an Adaptive Unscented Kalman Filter (AUKF) to reduce estimating errors. Experimental results demonstrate that when estimating battery SOC across different temperatures ranging from 0°C to 50°C, the RMSE is less than 1.68%, and the MAE is less than 1.44%. Compared to methods solely employing GRU models, the proposed GRU-AUKF method exhibits superior performance in enhancing estimation accuracy, thus validating its effectiveness.
Reliability assessment of distribution networks with medium-voltage and low-voltage flexible interconnections considering graded transfer
Authors: Liu Wenjun , Li Shuaihu , Ma Rui , He Shuyun 
Published: December 2024

Abstract
For flexible interconnection, flexible interconnected devices (FID) are utilized to upgrade or build connection nodes, which can provide more ways for load recovery after faults, thereby improving the reliability level of the distribution network. Based on the characteristics of connection switch, medium-voltage (MV), and low-voltage (LV) flexible interconnection transfer methods, a reliability assessment method is proposed in this paper for medium-voltage and low-voltage flexible interconnection distribution networks (MLFIDN) considering graded transfer. First, a multi-state reliability model of the LV substation area and discrete probability distribution of DG output are established based on the system structure and composition. Then, the fault impact analysis based on graded transfer mode is proposed. A transfer recovery model that takes into account power balance, the node voltage, line current safety constraints, and flexible interconnection operation constraints is established. On this basis, a simulation method based on non-sequential Monte Carlo sampling is used for system reliability assessment. Finally, the effectiveness of the proposed method is verified by the IEEE-33 distribution network with MV and LV flexible interconnection reliability assessment. The reliability assessment results can quantify the improvement of flexible interconnection on the reliability of distribution networks.
Health status analysis of PEMFCs based on degradation mechanism model and data-driven method
Authors: Zhang Fan , Yin Yan , Qin Zhikun , Yao Junqi , Guo Ting 
Published: December 2024

Abstract
Proton exchange membrane fuel cells (PEMFCs), as an environmentally friendly energy conversion device, are considered an important solution to achieve the net-zero pathway. However, the widespread commercialization of PEMFC is still hindered by limitations in reliability and durability. This article combines the degradation mechanism model with data-driven optimization algorithms to achieve degradation mechanisms and internal health state analysis of PEMFCs. Firstly, a semi-empirical degradation model for PEMFCs is constructed and validated with experimental data from the polarization curve. Afterward, based on the 4750 h degradation test data, the aging factors are fitted based on genetic algorithms, including leakage current, electrochemical active surface area (ECSA), ion impedance, contact resistance, oxygen diffusion coefficient, and concentration loss coefficient. The health status of key components is reflected by these aging factors. This article provides an in-depth analysis of the aging mechanism observed in PEMFCs during long-term operation, thereby establishing a fundamental understanding of the health status pertaining to crucial components within PEMFCs.
Design and optimization of line CT energy harvesting device
Authors: Li Ke , Gao Kai , Zhang Jianfeng , Zhou Lei 
Published: December 2024

Abstract
The aim of this study is to design and optimize an energy harvesting device for line current transformers (CT). The main function of this device is to extract energy from CT on the line to supply power to related electronic devices such as sensors and monitoring equipment. Firstly, an in-depth analysis of the working principles and characteristics of CT was conducted to determine the design requirements and performance indicators of the energy harvesting device. Subsequently, an energy-harvesting device based on the principle of magnetic coupling was designed. Different circuit principles were developed to accommodate low-load and high-load scenarios on the line, and the structure and parameters were optimized to improve energy conversion efficiency and output stability. Through experimental validation, the performance and stability of the designed energy harvesting device under different working conditions were verified. Finally, the design scheme of the energy harvesting device was optimized, and further improvement and application suggestions were proposed. This study provides a theoretical and practical basis for improving the performance and reliability of line CT energy harvesting devices, which is of great significance for the safe operation of power systems and equipment monitoring.
Nonlinear modeling of ball screw-type inertial container suspension
Authors: Kou Farong , Li Jiaolian 
Published: December 2024

Abstract
In order to better reduce the influence of spring-loaded mass inertia on vehicle suspension performance and make it better adapt to road excitation, this paper proposes a ball screw inertial container suspension configuration with adjustable inertia coefficient. By adjusting the mass of the flywheel part of the passive ball screw inertial container in the radial direction, the rotating radius is changed under the action of centrifugal force, and then the rotating inertia is changed, so that the rotating inertia of the flywheel can be adjusted with the rotating speed of the flywheel itself to achieve the adjustable inertia coefficient. Considering the nonlinear influence of the ball screw inertial container suspension system, a two-freedom nonlinear dynamic model of 1/4 vehicle is established. The model is simulated and analyzed. The results show that, compared with the passive and fixed inertia coefficient ball screw inertial container suspension, the adjustable inertia coefficient is improved by 45%, 11%, and 37%, respectively, compared with the fixed inertia coefficient inertial container suspension. The ball screw inertial container active suspension can effectively suppress the vibration impact of vehicles under road excitation.
A hierarchical sorting method based on hierarchical clustering and its application in port evaluation
Authors: Gao Su , Cheng Cheng 
Published: December 2024

Abstract
A hierarchical sorting method with semantic description is developed to address sorting issues in management decisions. This approach achieves optimal hierarchical clustering results by incorporating indicators of intra-similarity, inter-similarity, and total similarity. Additionally, it integrates the axiomatic fuzzy sets theory to produce a semantic description of the hierarchical sorting results. The developed method can provide a good semantic expression for sorting results from a multi-level perspective and assist decision-makers in making reasonable decisions at different levels. This study takes the 40 main seaports as application examples for analyzing the applicability and practicability of the designed method.
A research of word difficulty clustering based on improved k-means++ algorithm
Authors: Wang Dongjie , Liu Lina 
Published: December 2024

Abstract
Nowadays, Wordle, a daily puzzle game offered by the New York Times, is now becoming prevalent around the world by storm, and difficulty analysis of words has become a hot topic. However, the difficulty analysis of words is highly sensitive to the feature extraction of words, which undoubtedly creates great difficulties. Based on this, this paper proposes an improved K-means++ algorithm for clustering analysis of word difficulty, which is simulated and verified in the U.S. college students’ mathematical modeling C problem data. The results show that this paper clusters the 359 words in the data into 6 classes A, B, C, D, E, and F, and determines the class of word ERIE as B based on the distance between ERRIE and the word attributes of the six clustering centers. The DB index value of the model is as high as 0.815, and the results of the analysis of variance (ANOVA) of the clustering index are very significant, which proves the high accuracy of the model.
Numerical simulation study on critical initiation pressure of JO-11C booster explosive
Authors: Dang Shuaiying , Zou Debo , Yang Peiyuan , Cui Yongqiang , Lu Bingju , Cheng Dong 
Published: December 2024

Abstract
The booster pellet is the key component of a certain-shaped charge-cutting device. The booster pellet at the initiation point is excited by the electric detonator, and the booster pellet at the booster point is excited by the cutting cord. The initiation reliability of the booster pellet determines the reliability of the shaped charge-cutting device, so it is necessary to study the shock sensitivity of the booster pellet. In this paper, the critical initiation pressure of the JO-11C booster explosive is investigated by using numerical simulation. The results show that the critical gap thickness range for JO-11C booster explosive is 50-50.5 mm, and the critical initiation pressure range is 2.05-2.11 GPa.
All exact solutions to the generalized Maccari system with power law nonlinearity
Authors: Yang Yunfeng , Yang Yingquan , Hu Jinyan 
Published: December 2024

Abstract
In this study, we investigate the generalized Maccari system featuring power law nonlinearity. By employing envelope pattern transformations, the system is reformulated into an integral form. We provide exact solutions for the generalized Maccari system when n=1 and n=2 using the polynomial discrimination system method.
Observer design of discrete-time generalized quasi-one-sided Lipschitz nonlinear systems with multiple delays
Authors: Dong Wenqiang 
Published: December 2024

Abstract
In this article, the generalized quasi-one-sided Lipschitz condition is drawn into the topic of observer design for a kind of discrete-time nonlinear systems with multiple delays. The sufficient conditions for the asymptotic stability of full-order observer and reduced-order observer for systems are proposed, respectively. Under this condition, the two types of observers for systems can be designed, although the system parameter (A
0,C) is not detectable.
Stability analysis of a conventional SEIR epidemic model with relapse and general nonlinear incidence
Authors: Mu Xiaoqing 
Published: December 2024

Abstract
A conventional SEIR epidemic model is proposed, with the general nonlinear incidence rate. It is hypothesized that some recovered people may become infected again in this paper. Both the basic reproduction number and its critical effect on the system have been determined. We mainly used Jacobian matrices to discuss the local stability of the system and make use of geometric methods to research the system’s global stability. Eventually, we draw a brief conclusion.
A lightweight insulator string defect detection method based on improved YOLOv5
Authors: Gao Pengpei , Song Chunhe , Zhang Yue 
Published: December 2024

Abstract
In recent years, the use of drones to assess the safety status of insulators in power transmission systems has become a trend. To facilitate the application of intelligent algorithms on drone platforms, this paper proposes a lightweight insulator string defect detection method based on an improved YOLOv5. Firstly, to decrease the parameter count in the YOLOv5 backbone module, we opted for GhostNet. Considering the limitations of GhostNet in feature extraction, a lightweight attention mechanism is designed and integrated with GhostNet to enhance the accuracy of capturing defect features in insulator strings. Additionally, to further reduce parameters in the neck part of the YOLOv5 model, Ghost Convolution is introduced. Experimental results demonstrate that the proposed model performs excellently on the insulator string dataset and meets the requirements for real-time defect detection of insulators using drones.
Machine learning-based 2D model optimization design for fusion target pellets
Authors: Liu Pan , Wang Jian , Yuan Zilong 
Published: December 2024

Abstract
This paper proposes a machine learning-based method for the optimal design of a two-dimensional model of a fusion target pellet. The optimized design of the 2D model of the fusion target pill based on machine learning includes: parameterization of the fusion target pill, mesh division, construction of a database, data dimensionality reduction, construction of a neural network, and genetic algorithm optimization. On the basis of the original 2D model grid of the fusion target, the H-type grid is kept unchanged, only the O-type grid is replaced, and the total number of grid points is kept unchanged, so that the 2D model of the modified fusion target with any modeling parameter can quickly extract the physical parameters at the specified position in the flow field, with better geometrical adaptability, and improve the efficiency of data processing effectively. By combining the principal component analysis method and artificial neural network method to achieve the reconstruction of the flow field of the two-dimensional model of the fusion target, under the premise of guaranteeing the accuracy requirements, reducing the dimension and compression of the computational volume, thus reducing the time-consumption and saving the computational resources, realizing the rapid evaluation of the radiation hydrodynamic performance of the two-dimensional model of the fusion target and the rapid search for the optimization of the two-dimensional model of the fusion target, and providing a new idea for the high-efficient design of the two-dimensional model of the high-performance fusion target.
Evaluation of robotic process automation tasks in large-scale environments: success rates for performance and Z scoring for non-conformity
Authors: Hartikainen Eija , Hotti Virpi 
Published: December 2024

Abstract
Automation software is utilized to enhance efficiency and precision in various industries. Nonetheless, the performance and consistency of these software programs require careful monitoring through measurements. At the Finnish Government Shared Services Centre for Finance and HR (Palkeet), robotic process automation logging systems and experiments have been conducted to evaluate these measures. Success rate calculations are based on the logging system’s information and the findings (100 107 robot runs and 69 657 084 log levels during 2021-2022 and 2023/1-6). Through control charts and Z scoring, the experiments assess the proportion of non-conformity purchase invoices (987253 invoices, and 263822 defectives during 2020-2022) that the software cannot handle due to certain reasons, and the findings support an implementation of the Z scoring to observe out-of-control robot runs and analyze the causes. These results can be used to adapt and control the automation software’s processing capabilities.
Torrefaction Pre-Treatment Process for Biomass Fuel Pellet Characterization as a Renewable Energy Source
Authors: Yustira A , Arif H 
Published: December 2024

Abstract
This article focuses on the utilization and processing of biomass waste into a product that has economic value, namely fuel pellets which will later be used as fuel. Fuel pellets are produced by the torrefaction method, this method is used to improve the quality of fuel pellets in terms of density and calorific value. The biomass that will be used in the torrefaction method is empty palm oil bunches, cocopeat, oil palm fronds, oil palm fronds and corn cobs. The resulting fuel pellets will be analyzed to see the quality of fuel pellets from which biomass is the best. Analysis of fuel pellets includes the value of water content, ash, volatile matter, fixed carbon, calorific value (HHV) and bulk density.
A rough calculation of the litter carbon in agarwood small scale forest in Asahan Regency, North Sumatra, Indonesia
Authors: Muhdi  , Htb K W , Hanafiah D S 
Published: December 2024

Abstract
One of the sources of forest carbon is the forest floor, such as dead organic material and litter. The aim of this research is to analyze estimates of litter and soil carbon stocks in small-scale forest agarwood in Asahan, North Sumatra. Laboratory analysis was carried out at the Agricultural Laboratory of the Universitas Sumatera Utara. The analysis of litter biomass is carried out in the laboratory. The average litter carbon on land in Hessa Perlompongan Village is 0.36 tons/ha, which is greater than the average litter carbon on land in Bunut Village, which is 0.19 tons/ha. There is a significant difference between the average carbon biomass of litter carbon in Hessa Perlompongan Village and Bunut Village.
Assessment of land suitability for palmarosa cultivation (Cymbopogon martinii) as an atsiri essential oil plant in Karangturi Sub-District, Karanganyar, Indonesia
Authors: Muhammad D M , Samanhudi  , Rahayu M , Setyawati A 
Published: December 2024

Abstract
Palmarosa (Cymbopogon martinii) cultivation has gained significant interest because of the increasing demand for its essential oil (atsiri) in many industries. This research set out to thoroughly evaluate the land’s potential for palmarosa agriculture in the particular Karangturi Sub-District, located within the Gondangrejo District of Karanganyar Regency. This research employs a comprehensive approach to remote sensing, soil sampling, and geographic information system (GIS) analysis. It thoroughly examines and evaluates important factors including soil texture, pH levels, nutrient composition, topographical features, and climatic nuances, comparing scientific sources. According to the study’s findings, Karangturi Sub-District’s land area is at the marginal level (N; NW), which means it is not suitable enough for growing palmarosa due to the limiting factor for water availability. However, on other parameters, the status was suitable (S1-S3). Instead, some areas may require soil management to make them more suitable for cultivation. Through a framework based on scientific research, this study not only offers information on land suitability but also provides a basis for Palmarosa cultivation, which in turn can develop local agriculture and increase palmarosa essential oil production in the region.
Yield And Quality of Several Banyuwangi Sliced-Tobacco Lines for Sustainable Kretek Cigarette Production
Authors: Rochman F , Heliyanto B 
Published: December 2024

Abstract
Kretek cigarettes, which use sliced tobacco along with clove and sauces, are among the most popular tobacco products globally. Banyuwangi tobacco is one type of sliced tobacco used in these cigarettes. The primary challenge in developing Banyuwangi tobacco has been its low productivity. This study aimed to assess the yield and quality of ten promising tobacco lines from previous selections. The research was conducted over three years at two locations using a randomised block design with three replications. Parameters observed include dried sliced, quality index, crop index, nicotine, and stability. The results revealed that the Semarang Jahe 1 line produced the highest dried sliced tobacco, averaging 941.37 kg/ha, which is 31.44% above the average. Its crop index was 27.80% higher than the average, and it demonstrated high stability. The Jepril 1 line yielded 726.26 kg/ha of dry slices, 1.41% above the average, with a crop index 9.90% higher than the average, also showing stability. The Semarang Jahe 2 line produced 875.81 kg/ha of dry slices, 22.29% above the average, with a crop index 17.30% higher than the average, but it was location-specific. These three lines are promising for increasing farmers’ incomes. Special measures are recommended to promote sustainable organic cultivation.
Optimization of sterilization Ebony (Diospyros celebica Bakh.) leaf explants in suppressing phenolic compounds and contamination of in vitro culture
Authors: Tanjung S P , Siregar L A M , Hanafiah D S 
Published: December 2024

Abstract
This research aims to obtain the most optimal method of sterilization of ebony leaf explants and to know the types of contaminants that appear to improve the success of ebony regeneration initiation in vitro. This research was compiled using a non-factorial, completely randomized design (CRD) with five types of treatments using various sterilization methods by observing the percentage of sterile and non-browning explants, the percentage of explant browning, and the percentage of explant contamination. The research results showed that the D3 treatment (Fungicide + Tween 20, Bactericide + Tween 20, 10% NaOCl, 20% NaOCl, 30% NaOCl, and 70% Alcohol) gave the best results on the percentage of sterile and non-browning leaf explants at 100%.
Evaluation of agronomic performance of local rice from West Sumatra
Authors: Alfi R 
Published: December 2024

Abstract
Exploration and identification activities are the first steps in plant breeding activities in managing genetic resources. The use of new superior varieties will usually shift the use of local varieties. This study aims to identify the agronomic behavior of local rice cultivars from West Sumatra. The research was conducted in Padang City, West Sumatra, from September 2023 to January 2024. The genotypes used were five national superior varieties, 29 local cultivars, and adaptive varieties originating from five cities and districts in West Sumatra. The design was conducted using field experimental random block design with three replications for each genotype. The results showed that almost all observed results were significantly different except for the observation of flowering age. It is suspected that the environmental conditions are not a threat to the plants, so the cultivar can complete its life cycle until harvest.