bluuebunny/crossref_metadata_2025 huggingface dataset:
Classification of single-wave and bi-wave motion through fourth-order equations generated from the Ito model
Authors: Alquran Marwan
Published: June 2023

Recently, two fourth-order integrable equations were established by Wazwaz using the Boussinesq model. Tian and Zhang subsequently demonstrated that both equations are potential forms of the Ito model. This study investigates the dynamics of these equations using three effective schemes: the modified rational sine-cosine functions, Kudryashov-expansion, and the Hirota bilinear forms The study reports novel findings, including the observation that although these equations were derived from the same model, one propagates as a single-wave while the other propagates as a bi-wave. Additionally, some solutions of one equation can be obtained from the solutions of the other equation. These results are expected to be highly significant in the study of propagation solitary wave-solutions for nonlinear equations.
Semi-classical description of electrostatics and quantization of electric charge
Authors: Bhattacharya Kolahal
Published: June 2023

In this work, we present an explanation of the electric charge quantization based on a semi-classical model of electrostatic fields. We claim that in electrostatics, an electric charge must be equal to a rational multiple of the elementary charge of an electron. However, the charge is quantized if the system has certain boundary conditions that force the wavefunction representing an electric field to vanish at specific surfaces. Next, we develop the corresponding model for the electric displacement vector. It is demonstrated that a number of classical results, e.g. bending of field lines at the interface of two dielectric media, method of images, etc are all consistent with the predictions of this model. We also present the possible form of Gauss's law (or Poisson's equation), to find the wavefunctions of the field from a source charge distribution, in this model.
A molybdenum nanostructured-film target for tunable x-ray sources: surface-structure controllable preparing and radiation intensity selecting
Authors: Shi Jia , Shen Yan , Cheng Ao , Jiang Yingyi , Zhang Hu , Cui Tao , Chen Huanjun , Deng Shaozhi
Published: June 2023

Tunable x-ray sources have attracted interest due to providing selective focal spots and radiation intensities for different specific uses. Surface-structure of the anode target has a non-negligible impact on the radiation intensity of x-ray sources. The metal molybdenum (Mo) Lα characteristic x-ray exhibits great potential in solving key scientific problems of material analysis. However, there is still a lack of research on how to flexibly use Mo structure targets to meet the application requirements of different x-ray radiation devices. The reliable preparation of Mo targets with suitable surface-structure is also a significant challenge, particularly for those nanostructured-film targets that cannot be machined. In this study, we successfully prepared a series of self-assembled Mo nanostructured-films with controllable surface structures as a class of reflection-type x-ray sources’ anode target. The structure-activity relationship between the Mo surface nanostructures and the radiating Lα x-ray performance at different anode target angles was studied in a reflecting device layout. Mo nanostructures with smoother surface typically show better radiation performance at small inclination angles (0° to 30°), while the Mo films with a large number of nanoparticles and rough surface exhibit advantages at large inclination angles (60° to 80°). The results provide a feasible scheme for the future application of multi-functional tunable x-ray sources.
Unpacking the black box of deep learning for identifying El Niño-Southern oscillation
Authors: Sun Yu , Habibulla Yusupjan , Hu Gaoke , Meng Jun , Lu Zhenghui , Liu Maoxin , Chen Xiaosong
Published: June 2023

By training a convolutional neural network (CNN) model, we successfully recognize different phases of the El Niño-Southern oscillation. Our model achieves high recognition performance, with accuracy rates of 89.4% for the training dataset and 86.4% for the validation dataset. Through statistical analysis of the weight parameter distribution and activation output in the CNN, we find that most of the convolution kernels and hidden layer neurons remain inactive, while only two convolution kernels and two hidden layer neurons play active roles. By examining the weight parameters of connections between the active convolution kernels and the active hidden neurons, we can automatically differentiate various types of El Niño and La Niña, thereby identifying the specific functions of each part of the CNN. We anticipate that this progress will be helpful for future studies on both climate prediction and a deeper understanding of artificial neural networks.
Freeze-in dark matter in EDGES 21-cm signal*
Authors: Wu Shengyu , Xu Shuai , Zheng Sibo
Published: June 2023

The first measurement of the temperature of the hydrogen 21-cm signal reported by EDGES strongly favors the Coulomb-like interaction between freeze-in dark matter and baryon fluid. We investigate such dark matter in both the one- and two-component context with the light force carrier(s) essential for the Coulomb-like interaction being other than photons. Using a conversion of cross sections used by relevant experiments and Boltzmann equations to encode the effects of the dark matter-baryon interaction, we show that both cases are robustly excluded by the stringent stellar cooling bounds in the sub-GeV dark matter mass range. The exclusion of the one-component case applies to simplified freeze-in dark matter with the light force carrier as dark photons, gauged

,

,

, or axion-like particles, whereas the exclusion of the two-component case applies to simplified freeze-in dark matter with the two light force carriers as two axion-like particles coupled to standard model quarks and leptons.
The CIPM MRA—success and performance
Authors: Werhahn Olav , Olson Douglas A , Kuanbayev Chingis , Henson Andrew
Published: June 2023

The CIPM Mutual Recognition Arrangement (CIPM MRA) provides a technical framework to the measurement community for comparability of measurement results and international recognition of metrological capabilities declared by the national metrology institutes throughout the globe. Since its founding in 1999, the participating institutes have now published more than 25 700 peer-reviewed calibration and measurement capabilities (CMCs) in the CIPM MRA database (Key Comparison Database (KCDB)). It is these capabilities and the technical evidence behind them that underpin the international acceptance of measurements around the world. The success and wide adoption of the CIPM MRA indicate the maturity of the arrangement, however, the accompanying increased workload for the participants motivated a review of the practices with the aim to increase the efficiency while maintaining the technical rigor. This review identified a number of key factors that formed the basis of the revision of the modus operandi, including the procedures and the database. The review resulted in recommendations for the CIPM Consultative Committees (CCs), regional metrology organizations (RMOs), participating institutes, as well as the BIPM. The revamped KCDB incorporated the whole lifecycle of CMCs, familiarizing with the new system being supported by the Capacity Building and Knowledge Transfer Programme of the BIPM. The result was an improvement in not only efficiency of the CIPM MRA, but also its effectiveness. For example, the time required for the Joint Committee of the RMOs and the BIPM (JCRB) review of CMCs has dropped by more than 50% to 59 d (median) in 2022, and the number of uncompleted key comparisons (KCs) have been reduced by a factor of three to a total of 38 in March 2023, representing now less than 3% of the total KCs. In this paper we look at the key factors through the various metrological areas addressing practices by each CCs.
Unbalanced Class-incremental Learning for Text Classification Based on Experience Replay
Authors: Chen Lifeng , Zhang Huaping , Wushour Silamu , Li Yugang
Published: June 2023

While deep learning has achieved remarkable results for text classification, incremental learning for text classification is still a challenge. The main problem is that models suffer from catastrophic forgetting, which is they always forget knowledge learned before when labelled data comes sequentially and is trained in sequence. In this study, we propose methods of preventing catastrophic forgetting to handle unbalanced increased data. As an improvement over experience replay, our approaches improve the accuracy about 23.3% with 23% of all training data on Yahoo and 9.5% with 12% of all training data and on DBPedia.
CRAT-XML: Contrastive Representation Adversarial Training for Extremely Multi-Label Text Classification
Authors: Zhu Jie , Huang Heyan , Mao Xian-Ling
Published: June 2023

Extreme multi-label text classification is a very important and challenging problem in this age of widespread internet access, with a wide range of application scenarios, such as web tagging, legal document annotation, commodity classification, etc. Most of the existing state-of-the-art methods are based on deep learning, however, there are still two problems: 1) the vector representation generated by most pre-trained models suffers from anisotropy and uneven distribution, which has a significant impact on the XMC task. 2) existing models are large in size and use many models for integration. Some of them even took hundreds of hours to train. This seriously affects the efficiency of the experiments. Therefore, in this paper, we propose CRAT-XML, which uses contrast adversarial learning to optimize text representation and enhance the acquisition of dependency relations between text and labels, thus reducing the need for integration at the representation level and achieving relatively high accuracy under low-resource and low-time conditions. Experimental results demonstrate that our model achieves SOTA results on a single model, while achieving a large reduction in training time and model size.
Simulation and Analysis of Civil Aircraft Cabin Core Network Architecture based on Daisy Chain
Authors: Xiaoqiong Han , Xi Lu , Ruiqi Gong , Qing Zhu
Published: June 2023

With the rapid development of electronic technology, the application of civil aircraft cabin electronics is becoming more and more advanced. The traditional cabin core network architecture can no longer meet current cabin application requirements. Meanwhile, there are multiple of devices with duplicated functions in cabin of civil aircraft, and the number of each device with duplicated functions is very large. In order to solve the problem of repetitive deployment of a large number of devices with duplicated functions in the cabin system, the civil aircraft cabin core network architecture is proposed to adopt a two-level daisy chain network topology which has many advantages such as high robustness, high scalability and less cables. In the design phase of civil aircraft cabin core network architecture, modeling and simulation of the network architecture through simulation tools is an important means to study, predict, justify and judge the network performance. In this paper, a two-level daisy chain network architecture model with about 67 nodes for civil aircraft cabin core network is developed and the network performance of the model mentioned above is simulated through OPNET simulation tool in order to perform a trade-off analysis and evaluate the cabin core network architecture.
Research on Prediction Method of Objective Assessment of Building Acoustics Based on Machine Learning
Authors: Wan Yupeng , Zhou Yuanbo , Wen Jie , Chen Zheng , Zhao Jing
Published: June 2023

The purpose of this study is to predict the objective assessment of building acoustics more accurately and efficiently. In this paper, the neural network technology based on machine learning and computer acoustic simulation technology are combined to extract 10 typical characteristic parameters and 3 target parameters of 800 halls and rooms. Three matrix training sample databases are established by using Odeon platform. The reverberation time and speech transmission index are trained by BP neural network data fitting. The R results of the target parameters in this study are all more than 0.95. The MSE of the reverberation time parameter is in the range of 0.01-0.05 and the MSE of the STI parameter is less than 1 × 10−4. The results show that the neural network has good prediction accuracy, data generalization and application applicability. This prediction method can quickly evaluate the target parameters, reduce manpower and material resources, and improve work efficiency.
Design of a LDO with High PSRR
Authors: Sun Yichun , Li Jinghu , Chen Deyan , Luo Zhicong , Chen Riqing
Published: June 2023

One of the common ways to increase the PSRR(power supply rejection ratio) of LDO (low dropout linear regulator) is increasing the gain of error amplifier, but the stability of LDO system will also be reduced. A new high gain error amplifier is designed to push the poles inside the amplifier away from the origin, which ensures the stability of LDO system and improves the PSRR of low frequency band. At the TT process corner, the range of adjustable output voltage of LDO is 1.361~1.860 V under the simulation condition of 27 °C. When power supply ranges from 2.3 V to 3.3 V, the linear regulation rate is 238.3 µV/V; When the load changes from 0 to 20 mA, the load regulation rate is 9.6 µV/mA; At load current of 20 µA, the power supply rejection ratio of LDO is -97 dB@dc, and the phase margin of the whole circuit is greater than 66 degrees. The chip is verified in a 0.18 µm CMOS process. Setting the power supply voltage in the range of 2.3 to 3.3 V, the output voltage is stable at 1.8 V, and the error is only 1.9 mV, which is less than 0.2%.
Study on Parameters Optimization and Adaptation of Nitrogen Foam Flooding in Reservoirs with High Water Cut and High Permeability
Authors: Zhang Yu , Li Binfei , Wu Yizhi , Song Zhichao , Lu Teng , Zhang Mengyuan , Zeng Xianghui
Published: June 2023

Most oil reservoirs in China have entered the stage of high water cut. Affected by the heterogeneity of the reservoir, the water flow dominance channel is easily formed between injection-production wells in the plane direction of such reservoirs, and the phenomenon of water channelling is intensified. Therefore, a numerical simulation study of nitrogen foam flooding is carried out in this paper. According to the reservoir characteristics of the target block, the adaptability of nitrogen foam flooding to reservoirs in the ultra-high water cut stage is studied, the parameters of injection and production are optimized, and the applicable limits of nitrogen foam and the sensitivity of reservoir parameters are analysed. The optimization results of foam flooding indexes obtained through numerical simulation are as follows: the injection method of nitrogen foam is a mixed injection, the injection volume is 0.3 PV, the injection rate is 200 m3/d, the concentration of foaming agent is 0.5 wt%, and the gas–liquid ratio is 1: 1. The results show that for high-water-cut reservoirs, nitrogen foam flooding technology can effectively improve the water flooding effect of reservoirs and enhance oil recovery. It exhibits excellent adaptability to such reservoirs and has a very board application prospect. The results of numerical simulation optimization can provide theoretical guidance for field applications.
Overall Design and Power Generation Calculation of Photovoltaic System in Shanyin meteorological station
Authors: Li Jiangman , Wang Xiaoli , Shen Jianlin , Xu Junjie
Published: June 2023

Based on the data of Shanyin meteorological station and Solargis database, this paper evaluates the local solar energy resources, and carries out the overall scheme design and power generation estimation of the feasibility study stage of the 50MW photovoltaic power generation project in Shanyin county. After analysis, it is proposed to select crystalline silicon solar modules for the project. The specification of polycrystalline silicon solar modules is 305wp, and the specification of monocrystalline silicon solar modules is 315wp. It is recommended to adopt fixed installation for the photovoltaic module array. In addition, the component support of the project is fixed with an installation angle of 35°. 500mx inverter is selected for the project because of its high cost performance ratio. Based on the above work, the total power generation in 25 years is calculated.
Simulation Research on Control Strategy of Ocean Buoy Wind-Light-Diesel-Storage Integrated Power Supply System
Authors: Mao Qingyang , Dou Yinke , Yu Miaoyuan , Qin Jintao
Published: June 2023

Ocean buoys are important hydrometeorological collection equipment in marine scientific research activities, but because they are far away from land, there is a problem of insufficient energy supply. In view of the large amount of data transmitted by large buoys and the high energy consumption of equipment operation, this paper proposes a control strategy for a small-scale wind-solar-diesel-storage power supply system. In addition, the vibration of the buoy under the waves and the influence of the high temperature in the cabin on the diesel engine is analyzed so as to optimize the control strategy, and finally, use Matlab/Simulink to simulate the feasibility of the control strategy.
Research on Optimal Operation of Low Carbon Rural Microgrid Integrated with Optical Storage and Charging
Authors: Yang Chenjun , Meng Tao , Ma Haiyang , Qi Shiwei , Jia Zhonghua
Published: June 2023

With the huge consumption of fossil fuels leading to increasingly serious environmental pollution, new energy has been vigorously promoted in China. And solar energy is the energy focused on development. Aiming at the impact of photovoltaic (PV) on rural microgrid consumption due to its volatility and randomness, and in response to the national policy of developing new energy EVs. Taking into account the constraints of various energy conversion, storage, transmission devices, and system balance constraints, the paper proposes an optimal operation control strategy for a low-carbon rural microgrid based on time-sharing price (TSP) and integration of optical storage and charging. Combined with the actual power consumption and time of use price, simulation analysis and verification are carried out.
Research on Heat Dissipation Performance of Eco-friendly Gas insulated Transformer with i-C4F7N/CO2 as the Insulation Medium
Authors: Wu Yuewei , Ding De , Bai Xiaochun , Lv Pinghai , Yu Xiaobing , Lei Yuhang
Published: June 2023

Generally, the thermal conductivity of gas insulation medium is generally worse than that of liquid insulation medium. The heat dissipation problem is the key to developing large-capacity gas-insulated transformers. The traditional SF6 gas-insulated transformers are facing the challenge of upgrading and updating due to the strong greenhouse effect of SF6. As an ideal substitute gas for SF6, i-C4F7N/CO2 gas mixture is used as a new insulation medium to develop eco-friendly gas-insulated transformers. In this work, we described the structure and parameters of 10 kV GIT and measured the temperature and pressure by mounting sensors in different parts of 10 kV GIT. Further, we analyzed the heat dissipation performance of the Transformer based on the pressure and temperature data. The results show that the GNAN cooling mode may not be applicable to eco-friendly GITs with large capacities and high loads.
Day-ahead multi-objective optimization of CHP unit with heat storage considering flexibility
Authors: Tang Ruoxin , Wang Peihong , Wang Qian , Wang Minli
Published: June 2023

Nowadays, with the growing number of renewable energy capacities, the flexibility of the energy system has become an indicator that must be considered under the impact of frequent peak regulation. However, more flexibility always means less economy. The purpose of this paper is to tackle the contradiction between flexibility and the economy in the energy system. Based on day-ahead load prediction, a multi-objective optimization method is proposed here considering the objectives of excess of power variation and operation cost. NSGA-II is used to deal with the optimization problem by forming a Pareto frontier containing all the optimized results. We take the microgrid system composed of two combined heat and power units and a molten salt heat storage tank as a case study. Two typical results that emphasize flexibility and economic indicator are analyzed respectively and compared with each other, which reduce general guidance of the operation mode’s selection.
Based on the Vasicek Model Error Analysis of the New Energy Power Generation and Energy Storage Allocation Decision Method
Authors: Chen Haiyan , Pang Weichao , Qi Fujun , Su Chao , Yu Hehe , Sun Xiaoxuan
Published: June 2023

New energy unit output prediction error probability characteristics analysis and decision alternatives to the system are of great significance. The conventional analytical model based on a specific analytical form is not flexible enough to describe the distribution law of the actual output of new energy, and there are errors. In order to suppress the impact of uncertainty, centralized new energy usually needs to be equipped with energy storage applications with sufficient capacity, thus affecting economic benefits. Therefore, from the point of view of stochastic process, according to a special stochastic differential equation Vasicek model, this paper gives the parameter estimation method of the new energy output model, avoids the specific analytical expression of the probability distribution, and proposes an improved energy storage allocation method based on this model. The example analysis shows that the proposed algorithm has better short-term prediction performance, which makes the decision of energy storage capacity allocation more accurate and economical.
A Simulation Study of Solar Thermal Steam Generation for Thermal Recovery of Thick Oil Based on Aspen Plus
Authors: Chen Pengfei , Chen Kang , Peng Huaiwu , Zhang Yanlong , Bawaa Baercheng , Zhao Qiuyang
Published: June 2023

High-temperature steam injection is a common means of thermal recovery of thick oil. Although the steam injection boiler currently used for thick oil injection can achieve fast start-stop control, the power consumption of the pump is large, and the boiler control is demanding. Besides, a large amount of fossil fuel is needed to supply the heat required for steam heating. Using solar thermal to realize the transformation of solar energy-molten salt heat energy-steam energy can effectively reduce the burning of fossil fuels and realize clean thermal recovery of thick oil. To ensure the actual demand of thermal recovery of thick oil, it is necessary to determine a reasonable steam evaporation volume and vapor phase fraction. This paper simulates a solar thermal heat exchange system for molten salt-steam based on Aspen Plus. The simulation results show that the heat load and required solar panel area of all heat exchangers rise when the evaporation volume increases. However, the superheater grows most slowly. When the vapor phase fraction at the evaporator outlet rises to 1, there is no phase change heat transfer in the superheater, and its heat load plummets to 230 kW.
Design and energy efficiency analysis of hydrogen - fueled SOFC-‘GT+ST’ combined cycle system
Authors: Cheng Yunrui , Zheng Puyan , Zhu Rui , Zhao Hang , Feng Kang , Luo Tian
Published: June 2023

In order to enhance electricity generation efficiency of hydrogen-fueled fuel cell gas turbine combined cycle system abbreviated as SOFC-GT system, a new combined system of fuel cell with turbine abbreviated as SOFC-GT+ST system is based on the feature of high concentration of water vapor in the anode of hydrogen fuel cell and the introduction of steam turbine, and a system model based on ebsilon software is built to compare the system under the same parameter conditions. The system model is built based on ebsilon software, and the system power, power generating efficiency, and the loss of the electricity is comparatively studied under the same parameters, and improved SOFC-GT+ST is proposed. Research results show the following: the second system, which utilizes the spent gas of cathode and anode separately, effectively utilizes the thermal energy of water vapor in the anode spent gas and improves the power generation efficiency of the system; the improved SOFC-′GT+ST The improved SOFC-‘GT+ST’ system further improves the power generation efficiency of the system by recycling the hydrogen in the SOFC that does not participate in the electrochemical reaction, which reaches 65.88%. The research in this paper provides a reference for improving.
Reactive Power Control Characteristics and Parameter Identification of PV Inverter
Authors: Cai Dongyang , Chen Gang , Jiang Chuyang , Chen Yan
Published: June 2023

For getting the reactive power control model parameters of PV inverters, a method was proposed to test and identify parameters of the fault model of PV inverters based on symmetric and asymmetric fault sets. Firstly, the reactive power control structure of a grid-connected PV inverter is analyzed, and the parameters to be identified are defined. subsequently, according to various types and amplitudes of voltage that may occur in course of the operation of the test system, the overall data set is obtained, and the model given by the manufacturer is comprehensively tested. Finally, according to the test results, the manufacturer’s reactive power control model was obtained, and the parameters of the corresponding PSD-BPA model are identified by the Least Square method. The correctness of test results is verified by simulation.
Adaptability of Distribution Network Electrical Topology Identification Algorithm Based on Edge Computing
Authors: Yan Ping , Zhou Yifei , Li Yiyao , Xu Jie
Published: June 2023

With the rapid development of the national economy, the grid scale is continually expanding. The massive data in the operation of the distribution network brings great challenges to the distribution network electrical topology identification (DNETI). Edge computing can effectively solve the problem of computing and storage pressure of the master station in the face of massive data, as well as the delay and security problems in the transmission process. For edge computing scenarios, this paper studies the electrical topology identification algorithm of the distribution network and proposes an improved KNN algorithm. The simulation results show that the identification accuracy of the algorithm is as high as 97%. For the improved KNN algorithm, this paper also designs an algorithm adaptability test to identify the adaptability of the algorithm to software and hardware environment requirements. The results show that the algorithm has passed the software and hardware adaptability evaluation.
Research on Open Circuit Fault Location and Fault Tolerant Control of Inverter Power Transistor
Authors: Li Cheng , Gao Haibo , Gong Lei , Dong Xiaoyu , Dai Jian
Published: June 2023

As the key equipment of power conversion, the stability of the inverter directly affects the working state of the equipment. Aiming at the open circuit fault of the power tube, this paper designs a fault diagnosis and fault tolerance scheme of a three-phase bridge inverter based on the current signal. Firstly, the amplitude and phase characteristics of the current vector are used to judge the fault and fault location of the power tube. Then the output fault characteristic signal is converted into a fault-tolerant control signal. The fault leg is switched into a fault-tolerant leg under fault-tolerant control of the inverter bridge. The simulation results show that the diagnosis method proposed in this paper can judge the health and fault status of the inverter with high accuracy and achieve fault tolerant control, improving the stability of the inverter.
Intelligent Operation Maintenance Strategy for Modular Substation Based on Fault Tree Method
Authors: Yang Zheng , Liu Jun , Mu Hong , Jin Xingfu , Zhang Jinfeng , Lin Ying
Published: June 2023

Modular substations meet the development trends of the power transmission system. However, the operation maintenance strategy for the modular substation is still lacking. Herein, an intelligent operation maintenance strategy for the modular substation is proposed based on the fault tree method. After rating the state of components in the equipment, the state of the equipment is obtained. Subsequently, by analyzing the relationship between the equipment and modules in the substation, a fault tree model is established to calculate the risk value of each module. Eventually, based on the proposed operation maintenance time model, the optimal operation maintenance cycle of each module under different states is calculated and the intelligent operation maintenance strategy is put forward. This paper is helpful to improve the efficiency and quality of operation maintenance for modular substations.
Power Grid Fault Diagnosis Method Based on Inception Network
Authors: Zhang Ziqi , Du Mingxuan , Wang Zirui , Zhang Xu
Published: June 2023

With the continuous evolution of grid intelligence, the traditional grid fault diagnosis model can not satisfied the development needs of smart grid in terms of accuracy and diagnosis speed, and how to apply the fault information provided by the supervisory control and data acquisition (SCADA) system to achieve fast and accurate grid fault diagnosis is the main problem at present. In this paper, we propose an Inception network-based fault diagnosis method, in which the alarm information of different fault types is filtered and transformed into a grayscale map as model input to avoid the interference of redundant alarm information to the fault diagnosis, and the Inception network with excellent image feature extraction capability is employed to obtain the grayscale map of the alarm information to achieve fast fault diagnosis. This method has been proven to have excellent fault-type discriminatory capability and is effective in achieving fast and accurate fault diagnosis based on deep learning algorithms.
Research on electromagnetic scattering characteristics of high voltage transmission lines considering rough surface
Authors: Zhang Tianxun , Yu Pengcheng , Zhang Xiumin
Published: June 2023

With the continuous construction of the UHV power grid in China, the electromagnetic scattering of electromagnetic waves from random rough surfaces will have a certain impact on the passive interference of high-voltage transmission lines. To solve the problem of solving the propagation law of electromagnetic scattering in the electromagnetic interference of high-voltage transmission lines to radio stations, this paper is based on the approximation method and moment method of electromagnetic scattering, This paper explores the influence of lossless rough surface and lossy rough surface on the passive interference of high-voltage tower line, focusing on the influence of sea level and dielectric constant of seawater on the electromagnetic scattering characteristics of the target under the sea background, and obtains the general law.
Online Monitoring Method of Medium Voltage Energy Meter Based on Load Characteristic
Authors: Gao Chen , Lin Hua , Zhan Shi-an
Published: June 2023

There are some problems in the operation state of online electric energy meters, such as monitoring blank spots and loss caused by inaccurate measurement, which will reduce the economic benefits of power grid enterprises. This paper presents an online monitoring method suitable for the medium voltage side, which determines whether the voltage at the low voltage side of the transformer changes with the load and conforms to the external characteristic law of the transformer. The measured data collected by the metering device are used to calculate the voltage value of the first three-phase line at the operation of the transformer area. The three-phase balance rate and voltage fluctuation rate are used as multi-objective functions to solve the correction coefficient of current deviation.
Power Supply Enterprise Electricity Charge Centralized Accounting System Based on MVC Architecture
Authors: Zhang Siyu , Xu Jinglong , Yu Jinghe , Qian Yi , Yang Qixuan , Liu Haiyang
Published: June 2023

The continuous expansion of the scale of power users has brought tremendous pressure to the accounting of electricity charges. Faced with this situation, to ease the workload of electricity accounting, a centralized electricity accounting system for power supply enterprises based on Model View Controller (MVC) architecture is studied. With the help of the MVC architecture pattern, the three-tier framework of the electricity fee accounting system is designed. Sql server 2008 is applied to design the system database, including the establishment of E-R diagram and the design of the data table. There are two core functional units in the system: the power consumption statistics unit and the electricity accounting unit. The former unit obtains the power consumption data of users, and the latter unit completes the centralized accounting of electricity charges combined with the unit price. The results verify that under the designed system, the average absolute error of the user’s electricity charge reaches the relative minimum, which indicates that the accounting quality of the system is higher.
Study on Probabilistic Load Forecasting Model and Its Improvements
Authors: Chen Huican , Chao Zhu , Duan Qinwei , Tang Xuchen , Xie Xiangzhong , Lai Xiaowen , Wen Yakun
Published: June 2023

The current research on probabilistic load forecasting models mostly combines machine learning algorithms and quantile regression methods to construct quantile models. This paper first summarizes and combs the commonly used quantile regression forecast models. Combined with the actual data, we analyzed the main factors affecting the performance of probabilistic load forecasting and attempted to elaborate on the influencing mechanism. Then, a quantile regression probabilistic load forecasting strategy based on sample weight is designed. According to the analysis and experimental verification, we propose the future research direction for probabilistic load forecasting.
Ice-Covered Warning System and Terminal Application Based on Beidou Technology
Authors: Wu Jianrong , Fan Qiang , Wen Yi , Wu Yu , Hu Houpeng , Zhao Chao , Jiang Su
Published: June 2023

Disaster prevention and mitigation are one of the most prominent industrial applications of Beidou. Through the Beidou system’s short message and location reporting functions, it can realize disaster early warning, disaster rescue command and dispatch, and rapid emergency communication, which can greatly improve the speed of disaster emergency rescue response and decision-making ability. Based on the existing ice monitoring system of power grids and terminal in communication, positioning, and time synchronization problems such as the status quo analysis, based on the use of Beidou communication technology to modify ice monitoring system and terminals, and through system alignment, information coding and check, based on Beidou communication technology is verified in ice monitoring, especially the important role of disaster prevention and mitigation, it has important national strategic significance and multiple meanings such as industry 2025, new infrastructure and digital power grid.
METU-DBL: a cost effective proton irradiation facility
Authors: Karadöller E. , Uzun Duran S. , Kılıç U. , Hashmani R.K. , Demirköz M.B. , Efthymiopoulos I. , Can A.B. , Çakmakoğlu S. , Muçogllava B. , Kayaalp A. , Zorlu C.
Published: June 2023

The Middle East Technical University Defocusing Beamline
(METU-DBL) is designed to deliver protons with selectable kinetic
energies between 15–30 MeV, and proton flux
between 106–1010 protons/cm2/s, on a
maximum 21.55 to 15.40 cm target region with a beam uniformity
within ±6%, in accordance with the ESA ESCC No. 25100
specification for single event effects (SEEs) tests in the low
energy range. The achieved high proton fluences, allow users to test
space-grade materials; electronic circuits, ASICs, FPGAs, optical
lenses, structural elements, and coating layers for LEO, GEO, and
interplanetary missions.

The total received dose on the Device-Under-Test (DUT) from
secondary particles created during proton-material interactions at
the first beam collimator and the beam dump never exceed 0.1% of
the dose from primary protons. The METU-DBL is equiped with several
measurement stations and services to the user teams. A secondary
measurement station in a rotating drum that can hold multiple
samples has been constructed next to the first collimator which
provides neutrons for transmission experiments. At the target
region, a robotic table is located, which provides mechanical and
electrical mounting points to the samples and allows multiple
samples to be tested in a row. A modular vacuum box can also be
attached on the robotic table for any test that may require a vacuum
environment. Power rails on the robotic table provide various
outputs for the DUT. For the data acquisition, high-speed networking
and a modular industrial PC are available at the target station. The
design of the METU-DBL control software enables test users to
integrate and optimize the data acquisition and controlling of the
DUT.

The beam properties at the target region are measured with the
diamond, Timepix3, and fiber scintillator detectors mounted on the
robotic table. With diamond and Timepix3 detectors, measurements are
taken from the five different points (center and the four corners)
of the test area to measure the proton flux and ensure that it is
uniform across the full test area. Fiber scintillators on both axes
(X and Y) scan the target area to cross-check the beam profile's
uniformity. Secondary doses during the irradiation are measured by a
Geiger-Müller tube sensitive to electrons and gammas above
0.1 MeV and by a neutron detector located at the entrance of the
R&D room. The room cools down relatively fast after any irradiation
(<1 hour).

Accurate linear energy deposition rates and absorbed doses on the
samples are calculated using MCNP6, FLUKA and Geant4 Monte Carlo
simulations. Alanine dosimetry measurements that are calibrated
against these simulations are also used to estimate the absorbed
dose on the sample.
Does higher education affect pro-environmental behavior? Evidence from household waste recycling in Greece
Authors: Kountouris Yiannis , Remoundou Kyriaki
Published: June 2023

We examine the effect of higher education attainment on pro-environmental behavior focusing on household waste recycling. To address the endogeneity of higher education attainment, we exploit a set of reforms that increased opportunities for university studies in Greece, affecting cohorts graduating from high school in year 2000. We leverage the exogenous variation introduced by the school enrollment age cutoff and estimate the local average treatment effect of higher education employing a fuzzy regression discontinuity design, comparing educational attainment and recycling behavior between households that were just, and just not exposed to the reforms. We find little evidence that higher education increases the probability of recycling, and no evidence that the share of household waste recycled responds to higher educational attainment. Our results suggest that human capital accumulation alone may not deliver green behavior returns.
Morphology of Rice (Oryza sativa L.) Under Drought Stress with The Application of Antioxidants in The Vegetative Phase
Authors: Sari H P , Hanum C , Hasanah Y
Published: June 2023

Rice production around the world is seriously at risk from drought stress. Rice under drought stress has lower productivity and has growth inhibition because to poor nutrient and water uptake. This study aimed to determine how upland rice under drought stress responded morphologically to antioxidant administration during the vegetative stage. A randomized block design with two components and three replications served as the basis for the experiment. The first factor is drought stress with a field capacity level of 80% field capacity (FC), 60% and 40% FC. The second factor is the foliar application of antioxidants consisting of spraying without antioxidants; ascorbic acid 1 mM; salicylic acid 1 mM; 0.5 mM ascorbic acid + 0.5 mM salicylic acid. Parameters observed were plant height at 4-8 WAP, dry root weight and root length. The results showed that drought stress reduced the number of leaves, root dry weight and root length. Antioxidant application increased plant height, dry root weight and root length.
Effectiveness of Bio Fungicide with Active Ingredients Consortium of Trichoderma virens to Control Ganoderma boninense in Palm Oil Nursery
Authors: Puspita F , Aqita D K , Yuda P A
Published: June 2023

Ganoderma boninensa is a main pathogen causes basal stem rot in palm oil plant. This study aimed to determine the effectiveness of bio fungicide plus with active ingredients from the consortium of Trichoderma virens and get the best formula of bio fungicide plus in controlling Ganoderma boninense on oil palm tree nurseries. This research was carried out at the UPT Experimental Garden and Laboratory of Plant Disease Faculty of Agriculture, Riau University also at the researcher’s home garden in Pekanbaru. This study was conducted from October 2020 to February 2021. This study was conducted experimentally using a completely randomized design consisted of five treatments and four replications. Each replication consisted of four oil palm trees seedling. The treatments were a different formula (the nutrition) of the bio fungicide plus from the T. virens consortium (root, stem, midrib) which are with no treatment (B1), palm fronds (B2), dry sago pulp (B3), sago starch (B4), and dry tofu pulp (B5). Data were analyzed by using analysis of variance and continued with Duncan’s New Multiple Range Test (DNMRT) at a 5% level to compare the mean of each treatment. The results showed bio fungicide plus from palm fronds as the formula is the most effective and the best formula for bio fungicide plus with 56,66% effectiveness.
Spatial Distribution of Flood Vulnerability in Langkat Regency, North Sumatera Province, Indonesia
Authors: Thoha A S , Slamet B , Harahap M M , Sari T Y , Hulu D L N
Published: June 2023

Deforestation has a real impact on increasing the level of disaster risk, especially flooding. The real impact of the flood disaster is experienced by Langkat Regency community, North Sumatera Province, Indonesia. The impact of flooding is physical, social, economic, and environmental losses that are perceived directly by the community close to the disaster site. The objective of this study is to analyze the distribution of flood vulnerability levels in Langkat Regency, North Sumatera Province. Determination of the distribution of the flood vulnerability level area used spatial modeling with a scoring method with several variables, including rainfall, land slope, soil texture, land use, landform, and riparian buffers. The distribution of flood vulnerability areas is mostly at very low level with the percentage of the area reaching 53% of the Langkat Regency area. The three districts that have the widest high - very high flood vulnerability levels are Wampu District covering an area of 63,805.92 ha or 14.56%, of the total area of Langkat Regency, Pematang Jaya District covers 78,882.02 ha or 18.01% and Hinai District covers an area of 70,311.41 ha with or 16.05%. This study offers suggestions that the spatial distribution data of flood vulnerability level areas can be developed into an early warning system, for making rapid disaster response procedures.
Optimization of Dry Land Through Intercropping of Coffee and Potatoes to Support Farmers’ Income
Authors: Parhusip D , Girsang S S
Published: June 2023

Coffee and potato intercropping is one of the ways to use land and increase farmers’ income. The objective is to increase land production and income of farmers on upland intercropping. The study was conducted at Gurgur Experimental station, Toba Samosir Regency from July to November 2019. The study used a randomized completed block design where the first factor was tuber size, where U1 = large tuber (size 91-120 g) and U2 = small tuber (size 61-90 g), and the second factor was fertilization, where P1 = control; P2 = control + Beauveria; P3 = control + solvent P; P4 = NPK; P5 = NPK + Beauveria; P6 = NPK + solvent P; P7 = NPK + Beauveria + solvent P with 4 replications. The recommendation for potatoes is a complete fertilizer application with the addition of Beauveria and P solvent, plant spacing of 80 x 30 cm, and manure to increase P availability. For coffee plants in the form of pruning, fertilization according to plant age, and application of dolomite and soil organic matter; profit increased by IDR. 102,459,124-, from coffee only IDR. 28,760,000, - to be IDR. 131,219,124, - on the intercropping of Coffee and Potatoes.
Parking Management in Kota Lama Area Medan Using Spatial Analysis
Authors: Panggabean I P T
Published: June 2023

Parking Management in the Kota Lama area Medan is very important to research, in addition to the planned development and socialization of changes in traffic flow in this area, the Kota Lama Area Medan is also a historical place that is preserved. Sustainability which is reviewed in this study is parking which has always been a problem in this area and is also the same problem in almost every city around the world. The spatial aspect is carried out to optimize the results of selecting the best location in this area. Aspects reviewed planning, evaluation, and strategies including the relationships and interactions between users-communities, and the environment, including the sustainability of parking management in the future. The summary of the study found that the characteristics of parking spaces in the Kota Lama Area were dominant in the form of on-street parking which greatly impacted traffic congestion. Potential parking locations are found in areas along the main road such as on Jalan Ahmad Yani, and around Lapangan Merdeka. The type of parking space at these potential locations is directed to the maximum extent possible by applying off-street types in the form of parking pockets and vertical buildings.
Roof Construction and Structural Transformation on Batak Toba Traditional House on Samosir Island
Authors: Novrial  , Eddy F , Affif A M
Published: June 2023

The Batak Toba Traditional House, one of the main attractions of Samosir Island, a volcanic island in the center of Lake Toba, is an example of a well-preserved cultural heritage. However, the Batak Toba Traditional House has undergone a transformation in recent decades, influenced by technological advances, material availability, and modernization. The authors aim to discover the roof transformation of structure and construction of Batak Toba Traditional Houses in Samosir Island’s four villages, namely Huta Siallagan, Lumban Sigiro, Lumban Parmonangan, and Sosor Batu. This study employs a descriptive qualitative approach, where the authors will produce descriptive information about the problems studied in written and oral form. The authors will observe and analyze the transformation of roof construction and structural components on Batak Toba Traditional Houses on Samosir Island. The result of this study is that there are slight transformations in the roof structure and construction system on Batak Toba Traditional House on Samosir Island. First, there is a transformation in the roof materials. Second, a transformation in the structural design. Third, the construction phases of the traditional houses. Last, a transformation in the roof structural joint systems.