bluuebunny/crossref_metadata_2025_split huggingface dataset:
Streaming with more diversity? A comparison of the representation of minorities in broadcasting versus streaming television content
Authors: Daalmans Serena , Haverkort Rhanna , Kleemans Mariska 
Published: July 2024

AbstractThis study focused on the representation of minority groups on television, following the idea(l) that television as a mirror of society should convey a well-balanced representation of society. The current study extends previous research in that it analyses the potential for differences between regular broadcasters and streaming platforms, due to the latter’s public commitments to diversity and inclusion. Our results reveal that on Dutch prime-time television and popular streaming platforms women and seniors are underrepresented, whilst sexual minorities are overrepresented on public broadcasters and ethnic minorities on all platforms. Furthermore, results revealed that public nor commercial broadcasters nor popular streaming platforms succeed in being a fully inclusive, diverse, equitable, and representative reflection of Dutch society.
Real-time processing system of a two-color CO2 laser interferometer for density feedback control in JT-60SA
Authors: Ohtani Y. , Sasao H. , Nakano T. , Fukumoto M. , Wakatsuki T. , Inoue S. , Kojima S. , Urano H. , Yoshida M. 
Published: July 2024

A real-time processing system for the two-color CO2 laser interferometer on the JT-60SA has been developed for density feedback control. The system has a novel feature that can detect fringe jumps due to off-normal events, such as loss detection due to displacement of the beam axis and changes in the laser wavelengths. Because a phase change due to the JT-60SA plasma is smaller than π/2, corresponding to the line-integral electron density NL of ∼6×1019 m−2 in a short interval of 500 ns, the threshold of the fringe jump detection is decided to be π/2. Hence, off-normal events can be detected from a fringe jump, leading to the abort of the real-time feedback control. In the density feedback control of the JT-60SA plasma, the system is employed as a density monitor, with NL being successfully controlled at 16.8% ± 6.6% lower than the reference.
Delay characteristics of quasi-nonvolatile memory devices operating in positive feedback mechanism
Authors: Oh Jeongyun , Jeon Juhee , Shin Yunwoo , Cho Kyoungah , Kim Sangsig 
Published: July 2024

Abstract
This study examines the memory and read delay characteristics of quasi-nonvolatile memory (QNVM) devices operating in a positive feedback mechanism through technology computer-aided design simulation. The QNVM devices exhibit a rapid operation speed of 5 ns, a significant sensing margin of approximately 8.0 μA, and a retention time of around 1 s without any external bias. These devices showcase an exceptionally brief read delay of 0.12 ns. The energy band diagrams during the memory operation are analyzed to clarify the factors influencing the read delay. The write and standby conditions modulate the potential barrier height during the standby operation, thereby affecting the read delay. Moreover, the shorter rising time causes the reduction of the read delay. This study demonstrates that the QNVM device has the potential to resolve energy consumption and speed issues in nonvolatile memory devices.
Deciphering baryonic feedback with galaxy clusters
Authors: To Chun-Hao , Pandey Shivam , Krause Elisabeth , Dalal Nihar , Anbajagane Dhayaa , Weinberg David H. 
Published: July 2024

Abstract
Upcoming cosmic shear analyses will precisely measure the cosmic matter distribution at low redshifts. At these redshifts, the matter distribution is affected by galaxy formation physics, primarily baryonic feedback from star formation and active galactic nuclei. Employing measurements from the Magneticum and IllustrisTNG simulations and a dark matter + baryon (DMB) halo model, this paper demonstrates that Sunyaev-Zel'dovich (SZ) effect observations of galaxy clusters, whose masses have been calibrated using weak gravitational lensing, can constrain the baryonic impact on cosmic shear with statistical and systematic errors subdominant to the measurement errors of DES-Y3 and LSST-Y1, with systematic errors on S8 and Ω
m
reaching 10% and 50% of the statistical errors, respectively. For LSST-Y6 and Roman surveys, these systematic errors increase to 150% and 100% of the statistical errors, indicating the necessity for further model developments for future surveys. We further dissect the contributions from different scales and halos with different masses to cosmic shear, highlighting the dominant role of SZ clusters at scales critical for cosmic shear analyses. These findings suggest a promising avenue for future joint analyses of Cosmic Microwave Background (CMB) and lensing surveys.
Bessel vortices in spin-1 Bose–Einstein condensates with Zeeman splitting and spin–orbit coupling
Authors: Luo 罗 Huan-Bo 焕波 , Zhang 张 Xin-Feng 鑫锋 , Li 李 Runhua 润华 , Li 黎 Yongyao 永耀 , Liu 刘 Bin 彬 
Published: July 2024

Abstract
We investigate the ground states of spin–orbit coupled spin-1 Bose–Einstein condensates in the presence of Zeeman splitting. By introducing the generalized momentum operator, the linear version of the system is solved exactly, yielding a set of Bessel vortices. Additionally, based on linear solution and using variational approximation, the solutions for the full nonlinear system and their ground state phase diagrams are derived, including the vortex states with quantum numbers m = 0, 1, as well as mixed states. In this work, mixed states in spin-1 spin–orbit coupling (SOC) BEC are interpreted for the first time as weighted superpositions of three vortex states. Furthermore, the results also indicate that under strong Zeeman splitting, the system cannot form localized states. The variational solutions align well with numerical simulations, showing stable evolution and meeting the criteria for long-term observation in experiments.
Form factor for Dalitz decays from J/ψ to light pseudoscalars*
Authors: Shi 施 Chunjiang 春江 , Chen 陈 Ying 莹 , Jiang 蒋 Xiangyu 翔宇 , Gong 宫 Ming 明 , Liu 刘 Zhaofeng 朝峰 , Sun 孙 Wei 玮 
Published: July 2024

Abstract
We calculate the form factor

for the Dalitz decay

with

being the SU(

) flavor singlet pseudoscalar meson. The difference among the partial widths

at different

can be attributed in part to the

and quark mass dependences induced by the

anomaly dominance.

in both

is well described by the single pole model

. Combined with the known experimental results of the Dalitz decays

, the pseudoscalar mass

dependence of the pole parameter

is approximated by

with

and

. These results provide inputs for future theoretical and experimental studies on the Dalitz decays

.
Optimal Power Flow Calculation Based on SplitNN-DNN
Authors: He Xing , Wei Jie , Yi Zhihan , Li Xizhe , Song Rui , Chan Jian 
Published: July 2024

Abstract
Optimal power flow computation in power systems is an important aspect to ensure the smooth operation of power grids, but there are some challenges in terms of computing speed and data privacy protection in traditional methods. To address these issues, this study proposes a new method based on SplitNN-DNN. Firstly, we use a deep neural network to design a model that directly maps load data to voltage results, thereby improving computational efficiency. Second, we introduce a longitudinal federated learning technique to enable model training without data breaches. Finally, we conducted validation experiments on IEEE 118 and IEEE 300 node systems, and the results show that this approach not only protects data privacy, but also approaches the traditional centralized computation methods in performance, and has potential for practical applications.
Robust Assessment of Hosting Capacity of Renewable Generation in Distribution Systems Considering the Active Network Management
Authors: Gao Junyu , Yu Jianqiang , Zhang Gang , Zhang Xiaoyu , Liu Yanle 
Published: July 2024

Abstract
As the penetration rate of renewable distributed generation (RDG) increases, its random fluctuation characteristics have brought many problems to the safe operation of the active distribution network (ADN), such as voltage over-limit, reverse flow, and deterioration of power quality. Therefore, it has effectively affected the new energy hosting capacity of the ADN. Therefore, the effective assessment of the new energy hosting capacity of the ADN is a key part of the distribution network planning. In order to cope with the random fluctuation characteristics of new energy, this paper presents a two-stage robust assessment method of RDG hosting capacity of distribution networks by considering active network management (ANM) techniques such as network reconfiguration, reactive power compensation and on-load voltage regulation. Finally, the improved IEEE-33 distribution system is used to verify the results. The proposed method has been shown to be effective for evaluating the ADN’s RDG hosting capacity.
Combination of Matrix and Genetic Algorithms for Fault Location of Active Distribution Network
Authors: Li Juan , Lyu Pengpeng , Qian Zhonghao 
Published: July 2024

Abstract
Timely and effective location of faults in distribution networks is important for restoring power supply and dealing with faults. In this paper, a method combining matrix algorithm and genetic algorithm (GA) is proposed to determine the fault section. Firstly, the matrix algorithm is applied to locate the fault section initially by combining the alarm information uploaded from the feeder terminal unit (FTU). Secondly, in order to deal with the problem of outputting wrong location results, the switching function of the active distribution network is constructed to check the location results calculated by the matrix, and the results that do not meet the checking will be treated as a suspicious fault set, and the relevant evaluation function is constructed and optimized using the genetic algorithm, so as to arrive at the correct fault zone location results. The results of the example simulation show that the method used in this paper can achieve fast and fault-tolerant fault location in active distribution networks.
Voltage Compensation Method for Multi-feeder Distribution Networks Based on a UPQC with PV Injection
Authors: Shen Xielin , Yuan Bo , Peng Weiwen , Ye Hua , Dong Tiantian 
Published: July 2024

Abstract
In response to the problem of prolonged low voltage at the end of distribution grids, a voltage compensation method for multi-feeder distribution networks based on a unified power quality controller (UPQC) with PV injection is proposed in this paper. In the proposed scheme, two series inverters, a single parallel rectifier and photovoltaic (PV) system are flexibly interconnected via DC bus. The voltage attenuation can be compensated by the two series inverter, and the parallel rectifier is capable of supplying energy to the DC side of the two series inverters on adjacent AC feeders. Meanwhile, active power can also be supplied by the PV panel through a DC/DC converter. The operation modes and control strategies of the proposed method are analyzed in-depth. Finally, a MATLAB/Simulink model is shown to verify the effectiveness of the method proposed in this paper.
End-to-End Delay Performance Analysis for Delay-Sensitive Services in Polymorphic Networks
Authors: Wu Peng , Wu Junmin , Wang Wei , Yao Jiming , Yu Yue 
Published: July 2024

Abstract
In the polymorphic network for smart grid, the end-to-end latency performance analysis of delay-sensitive power control services such as differential protection and distributed power regulation is a crucial component in the intelligent control and management of power network slicing. In this paper, based on a detailed analysis of end-to-end delay factors of power control service, the distributed power regulation pilot project is taken as a typical application scenario of power control service, and the end-to-end delay of such service is theoretically derived and analyzed in detail by using network calculus theory. Numerical verification shows that the end-to-end delay performance of the power control service is positively correlated with the number of concurrent data streams and the number of subsystems and negatively correlated with the system service rate. Compared with the burst degree of the current data streams, the burst degree of other data streams significantly impacts the end-to-end delay calculation results of the current data flow.
Application Research of Multi-Model Fusion Technology in Real-Time Prediction of Dispatch Order Operation Duration
Authors: Zhang ShouTian , Pang ZhengNing , Yan WeiLong , Qi JingXian , Yang Jian , Zhao FuQuan 
Published: July 2024

Abstract
Power grid dispatching is a challenging task that requires dispatchers to be forward-looking in multiple aspects, with the operation of dispatch orders being one of its core tasks. Currently, the prediction of dispatch order duration relies mainly on the manual maintenance of experienced dispatchers, which is not only labor-intensive but also demands a high level of expertise. As a result, the effectiveness of existing systems in this regard is difficult to guarantee. However, due to the complexity of business scenarios, there has been no deployment of systems based on artificial intelligence algorithms. To address this issue, this paper employs multi-model fusion technology to achieve real-time prediction of dispatch order operation duration and has deployed it in Zhejiang Electric Power Company. The main contribution of this paper lies in proposing a strategy to solve the problem of regression prediction after differentiating feature fusion. Additionally, the paper provides a detailed description of how the relevant algorithms were deployed in Zhejiang Electric Power Company and presents the results of practical applications, demonstrating the effectiveness and practicality of the proposed solution.
Deviation control strategy for electric vehicle virtual energy storage dispatching instruction execution
Authors: Wang Wen , Yang Ye , Qin Jian , Li Peijun , Li Bo , Qiao Chunyan , Chen Qifang , Xue Yinjuan 
Published: July 2024

Abstract
As flexible resources, electric vehicles (EVs) participate in the dispatching of power grid regulation. Due to the randomness of entering and exiting the station, each EV cluster cannot fully respond to the guiding power instructions issued by the operator, resulting in biased values. This paper establishes a deviation management and control model, and proposes a local deviation control strategy and a cross-cluster collaborative deviation control strategy based on the model, so as to fully utilize the deviation control capabilities of each EV’s virtual energy storage and minimize the power deviation. The effectiveness of the proposed deviation control strategy for scheduling instructions is verified by numerical examples.
An Impulse Equivalent VSC Model for Large Power Grids Containing Multiple Converters
Authors: Ma Jiaqi , Wang Qihang , Zhang Shuqing 
Published: July 2024

Abstract
This paper explores the impulse equivalent method for constructing voltage source converter (VSC) model in large power grids containing multiple converters. It addresses the challenge of simulation cycle mismatch with device switching moments and proposes a cross-cycle correction method. The method enhances the VSC electromagnetic transient (EMT) simulation model, making it suitable for large-scale power grid simulations. The approach is validated through case studies, confirming its accuracy and computational efficiency for complex power electronic networks.
A Security Domain Feature Pattern Recognition Method Based on Capsule Neural Network
Authors: Deng Qiuquan , Li Ling , Zhao Ligang , Liang Zhencheng , Zhen Hongyue , Zhou Tinghui 
Published: July 2024

Abstract
In this paper, a security domain feature pattern recognition method based on capsule neural network is proposed. Firstly, Halton sampling is performed on the active output of all generators except for the balancing machine to obtain a uniform sample in the coverage space. Then, the support vector machine based recursive feature elimination (SVM-RFE) method is used to select the critical pre fault feature quantities of the system. Finally, based on the selected active features, one-dimensional data is converted into two-dimensional data and input into the capsule neural network. Dynamic security domain boundaries are constructed in both two-dimensional and three-dimensional spaces, which can divide the feature space into stable and unstable subspaces.
GIS Partial Discharge Pattern Recognition Based on IWOA-SVM Algorithm
Authors: Wang Jiayi , Fang Yuan , Kou Jianqiang , Xia Yankun , Zhou Dianbo , Dong Hanbin 
Published: July 2024

Abstract
To effectively recognize partial discharge (PD) types in gas-insulated switchgear (GIS) equipment, a novel PD pattern recognition method is proposed. This method leverages an improved whale optimization algorithm (IWOA) to optimize the support vector machine (SVM). Firstly, typical PD defects were simulated in the GIS chamber. The PRPS results demonstrated significant differences among four PD defects. Secondly, multiple feature values of PD results were calculated for feature extraction. Finally, the IWOA-SVM algorithm was employed for the recognition of PD patterns in GIS. Experimental results indicate that the IWOA-SVM algorithm can effectively recognize different PD types and the predicted accuracy rate can reach 99.1667%, which is much higher than SVM and WOA-SVM algorithms, providing information to construction units for maintenance.
State of Power Estimation Method for Hybrid Capacitor Battery Based on PSO Algorithm
Authors: Guo Yilong , Chen Siwen , Xing Shiyou , Sun Jinlei , Pan Shiyan 
Published: July 2024

Abstract
Hybrid Capacitive Battery (HCB) is an emerging electrochemical energy storage device that holds immense potential in the application of future energy storage systems (ESSs). When the ESS composed of HCBs is controlled and scheduled, it is necessary to understand its ability to release or absorb power. Therefore, accurate power prediction of batteries is crucial. This paper introduces a method for estimating the state of power (SOP) in HCB using the particle swarm optimization (PSO) algorithm. The method mainly consists of three parts: first, an equivalent circuit model (ECM) is employed to accurately represent the HCB, then an H-∞ filter algorithm is used to estimate its state of energy (SOE). In the third step, an optimization objective function is established based on the HCB model to describe the terminal voltage changes during its charging and discharging process, and use PSO algorithm to solve and obtain the estimated SOP results. Finally, the reference values of the SOP were obtained through constant power pulse testing experiments, proving that this method can effectively predict SOP under constant power conditions.
A Method for Calculating the Environmental Protection Cost of Cement Plants Taking into Account the Diffusion Characteristics of Air Pollutants
Authors: Li Lingfang , Zhang Jie , Chen Yixuan , Pi Shanquan , Si Tianfang 
Published: July 2024

Abstract
In recent years, China’s installed capacity of new energy has been continuously improved, and the problem of new energy consumption has become increasingly prominent. The cement load has considerable demand response potential and can effectively help absorb new energy sources, but its high emission characteristics limit the development of the cement industry. In this context, the establishment of a systematic and refined cement load emission cost model will be of great significance to improve the wind power absorption capacity and promote the low-carbon and environmentally friendly operation of the power system. In this paper, the emission characteristics of SO2, NOx, particulate matter and CO2 from the cement load are analyzed. according to the cement production process. Then, the air pollutant emission cost of the cement plant is described from the aspects of environmental protection tax and environmental protection supplementary cost, and the carbon emission cost of the cement plant is calculated by using the laddered carbon transaction cost model, and finally the emission cost model of the cement plant is constructed.
Integrated Controller for Fuel Cell Systems: A Full-loop Architecture
Authors: Wang Jingyu , Guo Xiaoyu , Xu Luoyun , Wang Liuchao , Lu Zhongpei , Dong Zhen 
Published: July 2024

Abstract
In response to the global initiative towards hydrogen energy, increasing focus has been placed on enhancing the performance, reliability and endurance of fuel cells by utilizing advanced control and monitoring strategies. However, due to the multi-variable. multi-loop and multi-physics nature of hydrogen fuel cells, the current decentralized architecture, where fuel cell controllers are isolated and placed in separate enclosures is no longer sufficient to carry out intricate coordinated control strategies. To this end, in this paper, we introduce a novel full-loop architecture, which enables the integration of the fuel cell controller, the air compressor controller, and the power electronics controller within one enclosure, reducing system size and cost. Moreover, based on the integrated hardware architecture, coordinated control such as oxygen/hydrogen pressure coordination can be carried out efficiently. A case study on electrochemical impedance spectroscopy has been conducted, demonstrating the advanced control and monitoring capabilities of this controller architecture.
Optimization Method of Electricity Package Settlement for Complex Users Based on Flexible Computing Algorithm
Authors: Liang Bo , Xie Lei , Li Hanqi , Liu Xiaohui , Wang Zixu , Zhang Jiaqi 
Published: July 2024

Abstract
In order to improve the settlement speed and efficiency of electricity charges, an optimization method based on a flexible computing algorithm for complex customers’ electricity charges is proposed. The model first learns the label of user information and electricity consumption data, and uses convolutional neural network to generate multiple label sets of electricity consumption data information. By establishing the flexible computing correlation model and using the improved flexible neural tree method, the hierarchical flexible classification calculation based on the electricity package is realized, and the matching between the user and the package is automatically completed by training the correlation between the labels, so as to improve the efficiency of the algorithm.
Development of All Solid State Nanosecond Pulse Transformer Fault Detection Device Based on Marx Circuit
Authors: Cai Linglong , Tai Bin , Liu Jiangnan , Ma Zhiqin , Zhou Dan , Liao Zihao , Liu Yu 
Published: July 2024

Abstract
a nanosecond pulse generator with a fast leading edge for transformer fault diagnosis is developed. The device is composed of a full solid-state nanosecond pulse generator based on Marx circuit and with a tail cut switch and a field programmable logic gate array (FPGA) device. Among them, the nanosecond pulse source is mainly composed of DC power supply, control circuit and main circuit. The main circuit is a 9-level modular Marx circuit, using MOSFET as the main switch and tail cut switch; The control circuit generates a synchronous trigger pulse signal, which drives the MOSFET to work synchronously after being isolated through the optical fiber. The output nanosecond pulse voltage parameters are adjustable amplitude 0-8kv, pulse width 100˜1000ns, repetition frequency 1hz˜1000hz, rising edge 30ns and falling edge 40ns. The transformer fault diagnosis platform is built, and the transformer off-line and on-line fault diagnosis is carried out, which paves the way for further exploration of transformer fault diagnosis technology.