bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research of flight test technology of response type on an FBW helicopter
Authors: Yang Wenfeng 
Published: December 2024

Abstract
This paper presents the response type requirements of ACAH (Attitude Command/Attitude Hold) and RCDH (Rate Command/Direction Hold) as specified in the Handling Qualities Requirements for Rotorcraft. It includes a simulation analysis of ACAH and RCDH response types, proposes validation flight test methods, and discusses their successful application in a specific fly-by-wire (FBW) helicopter. The test results demonstrate that these methods are suitable for the research of flight test technology of ACAH and RCDH response types.
Microplastic sampling path planning for unmanned surface vehicle (USV) based on RRT * and Dijkstra fusion algorithm
Authors: Shen Junyi , Fan Jianglong , Chan Tszho 
Published: December 2024

Abstract
Microplastics, an emerging environmental pollutant, have received widespread attention. This paper proposes an RRT* algorithm fused with Dijkstra’s algorithm to assist USV in achieving autonomous path planning for multi-objective points and B-spline smoothing of paths, allowing USV to be used to sample microplastics in the coastline and surface water. The fusion algorithm is also compared to the RRT* and artificial potential field algorithms using two metrics: path length and path smoothing, indicating its superiority in terms of both.
Real-time calibration of magnetometers based on the recursive least squares method
Authors: Ye Jing , Wu Zhiqiang 
Published: December 2024

Abstract
A real-time calibration method for magnetometers based on the recursive least squares (RLS) algorithm is proposed to address the issues of large data processing and lack of real-time performance in the calibration of magnetometers in complex magnetic environments using the traditional least squares (LS) algorithm. Firstly, an error model for the magnetometer is established. Then, using this error model as the measurement equation, the current measurement value is iterated from the previous measurement value through least squares iteration to update the state parameters. Finally, the effectiveness of the algorithm was verified by shaking the magnetometer in a “figure-eight” pattern. Experiments have shown that compared with the traditional least squares algorithm, the recursive least squares algorithm requires less data processing and offers faster calculation speed. Compared to LS calibration, the standard deviation of the magnetic vector modulus obtained from RLS calibration decreased by 24.4%, 17.4%, and 23.2% in three different environments, respectively. Additionally, by performing real-time detection and analysis of the state covariance matrix, it was determined that the calibration process is essentially complete after 3500 iterations.
Deep learning-based system for measuring weak electrical signals in plants
Authors: Wei Jiahao , Zheng Enrang 
Published: December 2024

Abstract
Due to the characteristics of plant electrical signals being weak, low-frequency, and susceptible to interference, this study proposes a hardware solution involving silver chloride medical adhesive electrodes and the design of conditioning circuits to amplify the plant electrical signals and reduce noise. On the software side, deep learning algorithms are proposed to extract the voltage values from a self-built plant electrical signal acquisition system. Experiments were conducted on two aloe vera plants grown in different environments. Voltage signals were synchronously collected by using a high-precision digital multimeter with anti-interference capabilities. The measured signals from the system were used as input signals for a 1D-CNN, and the synchronized high-precision digital multimeter measurements served as network labels. The 1D-CNN network was then trained by using deep learning algorithms to fit the voltage values from the acquisition system to those of the high-precision digital multimeter. This approach effectively reduces noise and extracts accurate voltage values in the self-built measurement system. By combining hardware and software, the precision of the measurements is improved, providing a new method for measuring plant electrical signals.
Discussion on the calibration method of gas chromatography-nitrogen chemiluminescence detector
Authors: Zhou Zhongmu , Xiang Mengdie , Zhang Yajun , Dong Guangxin , Ren Tingting 
Published: December 2024

Abstract
A gas chromatography-nitrogen chemiluminescence detector (GC-NCD) is a special analytical instrument for analyzing nitrogen compounds in samples from petroleum, environment, pharmaceutical, and other fields. With the continuous deepening of the research on “nitrogen pollution”, it is necessary to explore the calibration method of GC-NCD in order to ensure the accurate and reliable detection results. On the basis of fully understanding the working principle and structure of GC-NCD, this paper analyzes its main metrological characteristics, analyzes the calibration feasibility with reference to the relevant metrological technical specifications, determines the specific calibration method, which is verified to be reasonable and feasible by experiments, and provides a technical basis for the effective traceability of GC-NCD.
Research on visual/INS integrated navigation technology based on FGO
Authors: Cheng Xun , Wang Yu 
Published: December 2024

Abstract
With the development of science and technology, there is an increasing demand for positioning accuracy in navigation. To make full use of the complementarity of existing navigation systems to improve navigation and positioning accuracy, this paper investigates the visual/INS combined navigation system based on the factor graph optimization (FGO) algorithm. In the traditional visual/INS combined navigation system, there is often the problem of image blurring due to the rapid change of light and shadow captured by the vision sensor and the attitude change of the carrier, which leads to a decrease in the positioning accuracy of the combined navigation system. Therefore, this paper first introduces the Retinex algorithm and BID algorithm to carry out the design of the image deblurring method; then the visual/INS combined navigation algorithm is implemented based on the factor graph optimization method; finally, the experimental scheme is designed, comparative experiments are carried out, and the researched method is verified by using the public dataset. The experimental results show that the combined navigation algorithm realized in this paper has high accuracy, and its positioning accuracy is improved by 40% compared with visual positioning.
Erosion of stainless steel electrodes in a high-repetition-rate gas spark switch
Authors: Feng Le , Liu Sheng , Bu Qinhao , Peng Jianchang , Zhang Qiaogen 
Published: December 2024

Abstract
High-repetition-rate gas spark switches are widely used in the field of nanosecond pulses. A discharge experimental platform has been established to investigate the erosion process of the electrodes in a high-repetition-rate gas spark switch. The surface morphology of the electrodes after different numbers of discharges at a repetition rate of 100 Hz is observed using a confocal laser scanning microscope. The results show that three different morphologies are presented on the electrode surface. Compared with the anode, the cathode surface has a higher roughness. There are irregular protrusions in the central area of the cathode, and small dot-like protrusions in the central area of the anode. The erosion process of the electrode at a high repetition rate can be divided into two stages. In the first stage, the roughness of the electrode increases with the discharge number. In the second stage, the arithmetic mean deviation of the central area of the cathode is maintained at around 4 μm, and on the central area of the anode, it is maintained at around 1 μm. The maximum profile peak height of the electrode continues to increase with the discharge number. This research has significant implications for the design of long-life gas spark switches.
Fault detection and treatment method of power converter station based on man-machine cooperative intelligence
Authors: Yan Nannan , Feng Jianfeng , Xue Xiangyang , Su Lei , Chen Yan 
Published: December 2024

Abstract
Aiming at the problems of low efficiency of human operation and maintenance and high cost of resources faced by converter station equipment in the current new power system, this work studies and proposes an intelligent converter station anomaly collaborative processing method. Based on the data set of the existing data structure of the converter station, the operation of the power equipment is monitored by the sensor equipment. According to the abnormal signal and the designed fault analysis technology and knowledge graph, the fault intelligent analysis and fault disposal strategy are realized. The experimental results show that the proposed method can effectively monitor the abnormal data in the intelligent converter station and realize efficient fault collaborative processing.
Distributed feedback design in heating process control
Authors: Liao Yilong 
Published: December 2024

Abstract
In our paper, we designed a distributed feedback control law for a fluid heating model, which is described by a one-dimensional first-order hyperbolic equation. This equation has a non-local boundary condition with time-delay terms. Further, according to geometric control theory, the distributed feedback control law ensures the exponential stability and the input-output stability in a closed-loop system. Finally, we evaluate the proposed controller performances by solving tracking and disturbance rejection problems through numerical simulation, and we compare the simulation results with the optimal control method.
BP neural network model in forecasting carbon peaking—taking the Yangtze River delta region as an example
Authors: Xing Jun , Huang Zirui , Wang Qiao , Zhang Chuanlin 
Published: December 2024

Abstract
Under the background of the rapid spread of new energy vehicles, we use the BP neural network model to study the relationship between the development of new energy vehicles and the realization of the goal of carbon peaking and carbon neutrality. We trained a BP neural network model by taking factors such as market ownership, sales volume, and charging facility construction of new energy vehicles as inputs and carbon emission as outputs. Through this model, we successfully forecast the time of carbon peaking in the Yangtze River Delta region to 2036, which provides a scientific basis for policymakers and business decision-makers. Finally, we provide suggestions to the authorities in the Yangtze River Delta region.
Several kinds of integral factors for first order nonlinear ODEs and some parts of their solutions
Authors: Luo Dongsheng , Zhang Lianying , Zhang Peiyong , Deng Hongyong , Liu Xianghu 
Published: December 2024

Abstract
For the first-ordered nonlinear ordinary differential equations, we explore several kinds of integral factors in this paper, where the concrete formulas of the integral factors are acquired, and some of them are applied to solve corresponding nonlinear ordinary differential equations. At first, the sufficient and necessary condition of linearity for ordinary differential equations is proved that the ordinary differential equations are linear if and only if their integral factors only have a unique independent variable. Secondly, for several types of nonlinear ordinary differential equations, their corresponding integral factors formulas are discussed with not the same methods according to their special characters and different structures. Finally, among some of the integral factors, they are applied to complete to solve their matching first-ordered nonlinear ordinary differential equations.
Research on satellite unidirectional random vibration test method based on vibration fatigue equivalence
Authors: Dong Sizhou , Bai Zhaoguang , Wang Shaobo , Liu Zhijia , Chang Jing 
Published: December 2024

Abstract
This article studies the unidirectional random vibration testing method based on vibration fatigue equivalence for batch production satellites, aiming to optimize the mechanical testing project of batch production satellites and reduce satellite development costs. This article first starts from the frequency domain vibration fatigue analysis method and constructs a relationship model between the number of acceleration cycles and the test duration. Then, based on the model of the relationship between the number of acceleration cycles and the duration of the experiment, the response of the satellite in various directions during the noise test was taken as a reference. The random vibration test and the noise test were analyzed for the number of acceleration cycles and the duration of the experiment. Finally, a unidirectional random vibration test method for batch production satellites was obtained.
Backstepping boundary control for the Rayleigh model with a class of boundary conditions
Authors: Chen Jiang 
Published: December 2024

Abstract
This paper presents that a boundary feedback controller is proposed to stabilize the Rayleigh model. Firstly, we transform the initial equation into a second-order hyperbolic equation. Secondly, by using a backstepping integral coordinate transformation, we transform the simplified second-order hyperbolic equation into a stable target system. Meanwhile, a gain kernel equation will be generated during the conversion process. By solving the gain kernel equation, our goal is to design the controller based on information from the gain kernel. Finally, simulation results demonstrate the effectiveness of our designed controller.
The inviscid limit of the incompressible micropolar system in ℝ3
Authors: Deng Zicong 
Published: December 2024

Abstract
In this paper, the inviscid limit of Cauchy’s problem of incompressible micropolar system in three dimensions is considered. As various viscosity coefficients go to zero (i.e., ρ → 0,v
→ 0,μ → 0 and η → 0), we prove that the solution converges to a solution that the original equations with zero coefficients of the viscosity.
Research on uncovering parallelism in perfect loop nests for GCC compiler
Authors: Li Haoran , Yan Pengyan , Liu Haohao , Han Lin , Nie Kai , Chen Mengyao 
Published: December 2024

Abstract
To improve the ability to uncover parallelism in perfect loop nests for the GCC compiler, a method that utilizes the lambda transformation technique to uncover potential parallelism is proposed. Based on data references, dependence distance vectors and dependence direction vectors generated during the GIMPLE phase of the GCC compilation process, the GIMPLE form of perfect loop nests is converted into lambda representation in this paper, and the proposed method implements legal transformations on lambda representation for uncovering parallel loops in arbitrary loop nests. This method is integrated into the dependency analysis pass of the GCC compiler and has been experimentally validated on integer and floating-point benchmarks from the SPEC CPU2006 benchmarks. The results demonstrate that it can effectively enhance the existing loop analysis capabilities, loop transformation abilities, and loop parallelism uncovering capabilities of GCC. This method provides a reference for research on automatic parallelization techniques and holds practical application value within the GCC compiler.
Diversity of Fungi that Play a Role in Decomposing Rhizophora mucronata Leaf Litter in the Lower Deli River
Authors: Yunasfi  , Sitepu G A , Dalimunthe A , Sembiring S , Lubis S R , Sihotang V M S , Silalahi R A F , Purba JGM 
Published: December 2024

Abstract
Fungi are microorganisms that function as decomposers of R. mucronata leaf litter since they can produce enzymes that can break down cellulose and lignin, which are the main components of leaf and stem cell walls. The study’s goal was to evaluate the decomposition rate of R. mucronata leaves, carbohydrate and protein content, and the kind of fungi that were discovered in the leaf litter. The research procedures included site selection based on salinity levels, collection leaf litter of R. mucronata in the field, data gathering every 15 days, laboratory equipment sterilization used, making PDA media for culturing fungi, and isolation of fungi, identification of fungi. Levels of protein and carbohydrates in degraded R. mucronata litter were analyzed. This study was conducted between August 2023 and January 2024. The following categories of fungi are involved in the rate at which R. mucronata litter decomposes: Penicillium sp, Aspergillus sp, Aspergillus flavus, Aspergillus niger, Trichoderma sp. The diversity index value of fungi that play a role in the decomposition rate of R. mucronata litter is 1.32. R. mucronata litter decomposes at a rate of 9.09 grams/year. The average protein composition of R. mucronata litter is 6.046%, while the average carbohydrate content is 9.412%.
Evaluation of growth and yield of various stevia clones in Batu, Malang
Authors: Heliyanto B , Murianingrum M , Djumali  , Hartati R S S , Purwati R D , Suhara C , Hapsari B D , Parnidi  , Amin S , Sohri M , Mulyani S , Hariyanto D , Utari D , Slamet  
Published: December 2024

Abstract
Stevia (Stevia rebaudiana Bertoni) is a promising sweetener plant with leaves sweeter than sugar, possessing antibacterial, antifungal, antimicrobial, and antiviral properties. Despite this potential, the absence of high-productivity and high-quality stevia varieties in Indonesia remains a primary challenge. We have obtained several stevia potential clones from previous activities, which now require further evaluation to identify the most promising clone(s) for further assessment. In this study, 11 stevia potential clones were evaluated in a development area in Junggo, Tulungrejo Village, Batu City. The design used was a randomised block design repeated four times. The plot size was 4 m x 1 m, with plant spacing of 25 cm x 25 cm, resulting in 24 plants per plot. The observations included plant height, stem diameter, fresh and dry leaves weight, fresh and dry stalk weight and total fresh and dry biomass weight at the first harvest. The results showed that Majalengka, Karanganyar TIA-001B and Garut, are the four potential promising clones, with total dry biomass production in the first harvest ranging from 1575 to 2385 kg per hectare. These clones are thus selected for further evaluation and eventual release as new varieties.
The Survey of leaf blight disease (Exserohilum turcicum) on maize (Zea mays L.) in Pancur Batu District, Deli Serdang Regency to contribute the food security sustainability
Authors: Syakira F N , Safni I 
Published: December 2024

Abstract
Leaf blight caused by Exserohilum turcicum is a one of important diseases affecting maize. This leads to yield losses of up to 70% and therefore affect the sustainable food security. The study aim was to determine the distribution of Leaf blight disease caused by the fungus E. turcicum at Sei Glugur Village and Gunung Tinggi Village in Pancur Batu District, Deli Serdang Regency, North Sumatra Province. This research was exploratory research carried out using a survey method, by calculating the incidence and severity of leaf blight disease on maize plants on four fields in two villages, Sei Glugur Village and Gunung Tinggi Village. The highest disease incidence and disease severity were discovered in Sei Glugur Village, field 2, with an average disease incidence percentage of 83.64% and an average disease severity percentage of 33.15%.
Optimization of golden snail egg liquid organic fertilizer in sweet potato cultivation: towards sustainable agriculture and increased production
Authors: Rahmawati N , Wirayudha F 
Published: December 2024

Abstract
Increasing sweet potato production is often done by applying excessive amounts of chemical fertilizer which causes environmental degradation. The use of liquid organic fertilizer made from golden snail eggs, which are pests, is an alternative to increase sweet potato production while controlling golden snail pests using eco-friendly methods. This research aims to analyse the optimal concentration and time interval for applying golden snail eggs liquid organic fertilizer (GSE-LOF) to increase sweet potato production. Sei Mencirim Village in Deli Serdang Regency served as the research site in August – December 2023. The research design used was a Randomized Block Design, the first factor was concentration of GSE-LOF (0; 37.5; 75 and 112.5 mL/L) and second factor was the time interval of applying (5; 10 and 15 days). Data of the research showed that concentration of GSE-LOF had a noteworthy impact on length and weight of tuber and shoot fresh weight. The time interval for applying GSE-LOF had significant impact on shoot fresh weight. Interaction between concentration and time interval for application of GSE-LOF had a noteworthy impact on the shoot fresh weight. It is recommended to apply GSE-LOF with a concentration of 37.5 mL/L and an application interval of 15 days.
Effect of Lamtoro Leaf Liquid Organic Fertilizer and Chicken Manure on the Growth and Production of Shallots (Allium ascalonicum L.)
Authors: Vinolina N S , Sinaga T 
Published: December 2024

Abstract
Shallots, a high-value horticultural crop, are traditionally cultivated by farmers due to their significant economic importance. The provision of organic fertilizers presents a viable strategy to enhance shallot production while reducing reliance on synthetic fertilizers. This study investigated the influences of the provision of chicken manure and lamtoro leaf liquid organic fertilizer with various doses on shallot growth. A group randomized design was employed, incorporating two parameters and three repetitions. Parameter I involved chicken manure at doses of CM0 (control), CM1 (10 tons/ha), CM2 (20 tons/ha), and CM3 (30 tons/ha). Parameter II involved lamtoro leaf liquid organic fertilizer at concentrations of LL0 (control), LL1 (10%), LL2 (20%), and LL3 (30%). Data analysis was conducted using multiple statistical methods, and then the multiple range assessment of Duncan was continued at a significance level of 5%. The findings indicated that lamtoro leaf liquid organic fertilizer did not significantly affect all aspects tested. Furthermore, the combination of lamtoro leaf liquid organic fertilizer and chicken manure did not produce significant effects on the shallot growth. However, the giving of chicken manure significantly improved plant length, tuber fresh weight, and bulb dry weight.
Evaluation of the variability yield component characters and kinship relationships of several introduced local gogo rice cultivars
Authors: Wahyuni H , Siregar M N , Fatoni R B M I 
Published: December 2024

Abstract
Rice is a food crop that produces rice and acts as a source of energy for people in Indonesia. Increasing the genetic diversity of rice plants is important for further development in the field of rice plant breeding. The purpose of this study was to find out information about the diversity of yield component characters and kinship relationships of several local gogo rice cultivars introduced from Padang Lawas Regency. This study was conducted using an experimental method without a design. Then continued with the identification of quantitative characters of gogo rice plants. The genetic material used was 19 local upland rice cultivars introduced from Padang Lawas Regency. The study was conducted at the Screen House, Faculty of Agriculture, Universitas Sumatera Utara. The results of the study showed that all observed yield component characters had diversity because they had different results in each cultivar. The results of the UPGMA phylogenetics showed that the Sibahopotali cultivar had the furthest similarity coefficient value, namely 0.70. Close similarities were found in the Sibahopo Pinang cultivar with Siperak with a coefficient value of 0.90.