bluuebunny/crossref_metadata_2025_split huggingface dataset:
Experimental Study on the Combined Heating of Phase-Change Water Tank and Different Terminal Cooling Equipment
Authors: Zou Hang , Liu Zhanqiang , Long Enshen 
Published: November 2021

Abstract
In this paper, we set up a solar energy-phase change heat storage system and experimental study on the matching of the phase-change tank and three different terminal cooling equipment. Among them, phase-change water tank is used as heat source, meanwhile, radiator, heater and capillary as terminal cooling equipment. When radiator the terminal is radiator, the indoor temperature is difficult to meet the heating temperature requirements. When the terminal is heater, the indoor temperature can meet the requirements of heating temperature. However, the longitudinal distribution and lateral distribution of indoor air temperature are unevenly distributed and affect the thermal comfort of human body. When the terminal is capillary tube, the indoor temperature maintain at a high temperature and the temperature is satisfied with the thermal comfort of human body. Therefore, the capillary tube as the terminal cooling equipment is more advantageous of matching with the phase-change tank.
Study on Optimization Control of Hydrogen Sulfide Concentration in Coal-fired Boilers
Authors: Chen Kang , Fan Yu , Wang Xiao , Xu ZhaoRui 
Published: November 2021

Abstract
H2S is an important element to high-temperature corrosion for the water-cooled wall of coal-fired boilers, thus, it is an effective means to prevent high-temperature corrosion through reducing the concentration of H2S near the boiler wall. Since the concentration of H2S in the boiler is closely related to the concentration of O2 and CO, the research on the distribution of H2S atmosphere in the boiler furnace was conducted in this paper. With the air distribution regulation as the means, local O2 concentration is increased, to avoid the accumulation of H2S near the wall and reduce high-temperature corrosion.
Research on additional damping control of sub-synchronous oscillation in series-compensated DFIG system
Authors: Liang Weili , Wu Jiguang 
Published: November 2021

Abstract
Since series-compensated grid-connected system of doubly fed induction generator (DFIG) may cause sub-synchronous oscillation, with the purpose of improving the system stability, in this paper, the mechanism of sub-synchronous oscillation (SSO) is analyzed from the perspective of system damping, according to the mechanism, an additional damping controller is designed to suppress SSO. The controller uses rotor speed as the input signal and adds it into the d-axis current inner loop of the grid-side converter through filtering and proportional amplification, with the purpose of providing positive damping to the system. Finally, the model of DFIG series-compensated grid-connected system is established on PSCAD/EMTDC simulation platform to verify the suppression effect of the additional damping controller through time-domain simulation. The simulation results show that the device has good respond speed and suppression effect.
A DC-DC converter anti-interference system based on T-S fuzzy sliding mode control
Authors: Yu Siqi , Zhao Yan , Wang Yuri , You Fucai , Bai Jinyu 
Published: November 2021

Abstract
With the wide application of switching power supply, the research on its control method has become a hot spot at present, and DC-DC converter is one of the switching power supplies with the highest frequency. However, in daily use, the input voltage of the converter may fluctuate greatly, so it is very important to obtain a stable DC output voltage. Therefore, this paper proposes a nonlinear composite control strategy method based on T-S fuzzy sliding mode control for the system disturbance problem of DC-DC converter. After establishing the T-S fuzzy model, the variable structure control theory is added, and the sliding mode surface and sliding mode control law are designed and their stability is proved by Lyapunov function. The simulation results show that the proposed control method has a good control effect and can keep the system robust.
Design of an Intelligent Purification and Disinfection Apparatus for Air Conditioning Units
Authors: Duan Yitong , He Kun , Xie Xinyi , Zou Jingwen , Zhao Huiyu 
Published: November 2021

Abstract
With the sudden outbreak and rapid spread of COVID-19, global economic development and social stability have been seriously affected. The virus mainly spreads infection among people on a large scale through the air. People are gradually focusing on how to use HVAC system, so that it can play a more efficient and positive role in epidemic prevention and control. Consequently, we designed an intelligent purification and disinfection apparatus for air-conditioning units. The apparatus integrates rapid virus detection and high-efficiency disinfection functions. It uses a modular design and different operating modes for different levels of epidemic periods. This apparatus is not only suitable for daily life, but also can meet the prevention and control requirements during the epidemic period, which takes the economy, energy saving, and environmental protection into account.
Multi-objective optimal planning of urban virtual power plant based on electrical distance
Authors: Zeng Rui , Yang Gaofeng , Xie Duyang , Zeng Yi , Zheng Tianwen , Zhang Chengyun , Pan Lei 
Published: November 2021

Abstract
Currently, virtual power plants (VPP) in urban areas face problems such as over-dispersion of distributed power sources, insufficient source-load coordination. Traditional VPP planning method increases the difficulty in the operation and the dispatch of VPP. Therefore, this paper proposes a planning method for urban VPP that fully considers the coupling characteristics between the buses. From the distribution network to district to bus, a multi-objective bilevel optimization planning model for urban VPP is established. The upper-level planning model aims at minimizing the annual comprehensive cost, and derive the overall capacity of wind power turbine (WT), photovoltaic(PV), and energy storage system (ESS) of VPP in each district. The lower-level planning model aims at minimizing the network loss, and realizes the site selection and capacity allocation in each selected site. The case study based on the IEEE-33 standard system was carried out to verify the advancement and effectiveness of the proposed method.
A Load Modeling Method Based on Machine Learning
Authors: Song Lei , Lu Chun-Guang , Huang Xiao-Qiong , Wang Qing-Juan , Zhou Chen-Hui , Chi-Jiang  , Wang Chao-Liang , Ding Yi , Diao Rui-Peng , Wei-Liu  , Li Yi-Long 
Published: November 2021

Abstract
More and more high-power impact loads in the power grid are put into use. When the power is impacted, these loads will cause the power grid bus voltage fluctuations and reduce the power quality. Therefore, in order to accurately analyze the changes in the power system, it is particularly important to establish a reasonable impact load model. This paper takes the impact load data generated by the CT machine during exposure as an example to analyze the characteristics of the impact load. Based on the active power characteristics of the impact load, machine learning methods (such as support vector machines and long and short-term memory networks) are introduced into the impact load modeling, and the power waveform change law of the impact load is accurately established by this method. Finally, the effectiveness of the method is verified by simulation.
Research on short-term wind power Prediction of GRU based on similar days
Authors: Lin Yong , Zhang Haiing , Liu JiYan , Ju WenJie , Wang JinYou , Chen XiaoDong 
Published: November 2021

Abstract
As the proportion of wind power generation continues to increase, accurate forecasting of wind power output is of great significance to the smooth operation of the entire power grid. However, due to the greater impact of environmental factors, wind power generation has strong randomness, and it becomes difficult to accurately predict the power generation. Thus, a new hybrid model for wind power generation prediction combining GRU neural networks and similar days’ characters analysis is proposed to address solve this problem. The prediction method employs grey relation analysis to screen similar days, which not only reduces the amount of data required to train the model, reduces the computational complexity, and improves the training speed, but also improves the prediction accuracy based on the selected datasets. In addition, this method also filters and processes the data through box-plot analysis and linear smoothing, which further improves the prediction accuracy of the model. The results show that compared with a single GRU network, the MAE of this method has dropped by 1.89, RMSE has dropped by 1.9, and MAPE has dropped by 11.07%. Obviously, the prediction model based on similar days extraction has obvious advantages.
Big Data Cleaning Model of Multi-Source Heterogeneous Power Grid Based On Machine Learning Classification Algorithm
Authors: Ying Zhangchi , Huang Yuteng , Chen Ke , Yu Tianqi 
Published: November 2021

Abstract
Aiming at the low cleaning rate of the traditional multi-source heterogeneous power grid big data cleaning model, a multi-source heterogeneous power grid big data cleaning model based on machine learning classification algorithm is designed. By capturing high-quality multi-source heterogeneous power grid big data, weight labeling of data source importance measurement, data attributes and tuples, and constructing Tan network based on the idea of machine learning classification algorithm, the data probability value is finally used to complete the classification and cleaning of inaccurate data. Experiments show that the model based on machine learning classification algorithm can effectively improve the imprecise data cleaning rate compared with the traditional model to solve multi-source heterogeneous imprecise data cleaning.
HV Cable Intelligent Sensing IoT Technology and Application
Authors: Yang Tianyu , Li Hai , Zhou Yunjie , Yuan Jialiang , Lou Tiecheng 
Published: November 2021

Abstract
In view of the challenges faced by the current HV cable O&M management, such as the growth of equipment scale, the severe security situation, the lack of comprehensive perception on equipment status, and the ability of intelligent analysis and decision-making to be improved, it was proposed to build a HV cable intelligent sensing IoT based on new sensors such as intelligent earthing box, PD intensive care unit, intelligent ground landmark and face recognition system for terminal stations, so as to comprehensively improve the quality and efficiency of HV cable O&M management. A pilot project was built in Hongqiao area in Shanghai, forming typical application scenarios such as IoT intelligent disposal, integration of monitoring and detection data in terminal stations, panoramic intelligent patrol inspection for ensuring power supply.
Emergent fields from hidden sectors
Authors: Anastasopoulos Pascal 
Published: November 2021

Abstract
The present research proceeding aims at investigating/exploring/sharpening the phenomenological consequences of string theory and holography in particle physics and cosmology. We rely on and elaborate on the recently proposed framework whereby four-dimensional quantum field theories describe all interactions in Nature, and gravity is an emergent and not a fundamental force. New gauge fields, axions, and fermions, which can play the role of right-handed neutrinos, can also emerge in this framework.
Preprint: UWThPh 2021-8
A Machine Learning approach to the EFT re-interpretation of the WZjj fully leptonic electroweak production
Authors: Bachas Konstantinos , Karkanias Ioannis , Kasimi Eirini , Leonidis Christos , Petridou Chara , Sampsonidou Despina , Zachariadou Katerina 
Published: November 2021

Abstract
In this paper we study the use of Machine Learning techniques to set constraints on indirect signatures of physics beyond the Standard Model in Vector Boson Scattering (VBS), in the electroweak (EWK) production of self-interacting W
±
Z bosons in association with two jets. The WZ fully leptonic channel has been extensively studied by the ATLAS Collaboration at the LHC and we are about to provide results using the full Run 2 data corresponding to an integrated luminosity of 139fb
−1. The EWK production of the WZ in association with two jets has been already observed at 36fb
−1 with an observed significance of 5.3 standard deviations. A factor of four increase in the integrated luminosity provides an opportunity to check for deviations from the Standard Model (SM) predictions, in particular for model independent, indirect searches for New Physics. Such searches can be realized in the context of an extension of the SM in terms of an Effective Field Theory (EFT) formalism, providing a way to quantify possible deviations from the Standard Model. The EFT Lagrangian besides the Standard Model terms comprises contributions from higher dimension operators, their effect being determined by the strength of their corresponding parameters (Wilson coefficients scaled to the appropriate power of Λ, indicating the scale of the appearance of New Physics). In this paper an attempt is made to search for New Physics effects in the WZjj production, using state-of-the-art machine learning models where diverse network architectures are effectively combined into ensembles trained on the outcomes of base learners maximizing performance. The base learners are trained to identify pure WZjj signal events originating from the effect of EFT operators, from WZjj background events originating from strong (QCD) or EWK WZjj processes. We investigate the utilization of the ensemble model response in estimating the sensitivity of WZjj events in some of the dimension-8 EFT operators and compare the results to sensitive kinematic variables traditionally used to constrain the EFT operator effects.
Status of the R2D2 project: A future neutrinoless double beta decay experiment
Authors: Katsioulas Ioannis 
Published: November 2021

Abstract
The nature of the neutrino is a central questions in physics. The search for neutrinoless double beta decay is the most sensitive experimental approach to demonstrate that the neutrino is a Majorana particle. Observation of such a rare process demands a detector with an excellent energy resolution, extremely low background, and a large mass of a double beta decaying isotope. R2D2 aims to develop a novel spherical high-pressure TPC that meets all the above requirements. As a first step, the energy resolution of the R2D2 prototype was measured. A 1.1% (FWHM) energy resolution was achieved for 5.3 MeV α-particles in Ar:CH4 at pressure up to 1.1 bar. This is a major milestone for R2D2 and paves the way for further studies with Xe gas and the possible use of this technology for neutrinoless double beta decay searches.
Extensive Air Shower Reconstruction using the timing information from the RF-system of the Astroneu array
Authors: Nonis S , Leisos A , Tsirigotis A , Bourlis G , Papageorgiou K , Gkialas I , Manthos I , Tzamarias S 
Published: November 2021

Abstract
The Astroneu cosmic ray telescope is a distributed hybrid array consisting of both scintillator counters and RF antenna detectors used for the detection of extensive air showers (EAS). The array is deployed at the Hellenic Open University campus, on the outskirts of the urban area of Patras in Greece. In the present development phase, the Astroneu telescope includes two stations consisting of 3 scintillation detectors modules (SDM) and one RF antenna while a third station includes 3 particle detectors and 4 RF antennas (3SDM-4RF). In each station, the RF-detectors are operating receiving a common trigger upon a 3-fold coincidence between the particle detectors of the station. In this study we present recent results from the 3SDM-4RF autonomous station related to the estimation of the direction of the incoming cosmic air shower using only the timing information from the 4 RF detectors. The directions of the reconstructed showers using the RF timing are in agreement with the corresponding results using the SDMs timing as well as with the simulation predictions. This verifies that the RF signal emitted from EAS originating form Ultra High Energy Cosmic Rays (UHECR), can be detected even in areas with strong electromagnetic background.
The μNet project: A status report
Authors: Petropoulos M , Tsirigotis A. , Leisos A 
Published: November 2021

Abstract

μNet aims at the deployment and long-term operation of an extensive school network of educational Cosmic Ray telescopes in the geographical area of Peloponnese. In the framework of μNet, an extended educational program will take place, encompassing educational activities for the construction, testing and operation of μCosmics (microCosmics) detectors, as well as for the remote operation of cosmic ray detection stations and astroparticle physics experimental devices deployed at the Hellenic Open University (HOU) campus. A pilot run of the μNet project started in 2020 aiming at the deployment and operation of a small school network in the prefecture of Achaea. In this work we present the progress of the program to date and the feedback we have received so far from the students and the teachers participating in it.
Conjunction of gallium doping and calcium silicate mediates osteoblastic and osteoclastic performances of tricalcium phosphate bioceramics
Authors: He Fupo , Qiu Chao , Lu Teliang , Shi Xuetao , Ye Jiandong 
Published: November 2021

Abstract
Gallium-containing biomaterials are considered promising for reconstructing osteoporotic bone defects, owing to the potent effect of gallium on restraining osteoclast activities. Nevertheless, the gallium-containing biomaterials were demonstrated to disturb the osteoblast activities. In this study, tricalcium phosphate (TCP) bioceramics were modified by gallium doping in conjunction with incorporation of calcium silicate (CS). The results indicated that the incorporation of CS promoted transition of β-TCP to α-TCP, and accelerated densification process, but did not improve the mechanical strength of bioceramics. The silicon released from the composite bioceramics diminished the inhibition effect of released gallium on osteoblast activities, and maintained its effect on restraining osteoclast activities. The TCP-based bioceramics doped with 2.5 mol% gallium and incorporated with 10 mol% CS are considered suitable for treating the bone defects in the osteoporotic environment.
Projecting armed conflict risk in Africa towards 2050 along the SSP-RCP scenarios: a machine learning approach
Authors: Hoch Jannis M , de Bruin Sophie P , Buhaug Halvard , Von Uexkull Nina , van Beek Rens , Wanders Niko 
Published: November 2021

Abstract
In the past decade, several efforts have been made to project armed conflict risk into the future. This study broadens current approaches by presenting a first-of-its-kind application of machine learning (ML) methods to project sub-national armed conflict risk over the African continent along three Shared Socioeconomic Pathway (SSP) scenarios and three Representative Concentration Pathways towards 2050. Results of the open-source ML framework CoPro are consistent with the underlying socioeconomic storylines of the SSPs, and the resulting out-of-sample armed conflict projections obtained with Random Forest classifiers agree with the patterns observed in comparable studies. In SSP1-RCP2.6, conflict risk is low in most regions although the Horn of Africa and parts of East Africa continue to be conflict-prone. Conflict risk increases in the more adverse SSP3-RCP6.0 scenario, especially in Central Africa and large parts of Western Africa. We specifically assessed the role of hydro-climatic indicators as drivers of armed conflict. Overall, their importance is limited compared to main conflict predictors but results suggest that changing climatic conditions may both increase and decrease conflict risk, depending on the location: in Northern Africa and large parts of Eastern Africa climate change increases projected conflict risk whereas for areas in the West and northern part of the Sahel shifting climatic conditions may reduce conflict risk. With our study being at the forefront of ML applications for conflict risk projections, we identify various challenges for this arising scientific field. A major concern is the limited selection of relevant quantified indicators for the SSPs at present. Nevertheless, ML models such as the one presented here are a viable and scalable way forward in the field of armed conflict risk projections, and can help to inform the policy-making process with respect to climate security.
The cultural acculturation in architecture of Karawang Chinatown, West Java
Authors: Sudarwani M M , Purwanto E , Rukhayah R S 
Published: November 2021

Abstract
Chinese architecture which is part of Indonesia’s history is an interesting topic, because each of Chinese architecture in Indonesia carries its own characteristics which are quite unique with suitable materials based on existing local conditions. The character of Chinese architecture in various places in Indonesia is the result of a combination of Chinese architectural characters mixed with local architecture which is part of Indonesian architecture and also plays a very large role in Indonesian architectural styles. One of the interesting Chinatown areas used as a study location is Karawang Chinatown, Karawang Regency, West Java. The purpose of this study is: 1) To get a picture of Karawang Chinatown which has a concept of Chinatown architecture; and 2) To know the cultural acculturation in the architecture Karawang Chinatown. This study uses a qualitative approach that is based on the naturalistic paradigm with an inductive method. The cultural acculturation between Chinese culture and local/colonial culture creates a unique architecture and a symbolic meaning, the character is a blend of Chinese architecture with local architecture that needs to be preserved.
Distribution of residential room patterns while working from home online by anticipating the spread of virus Covid-19 virus (Universitas Budi Luhur Lecturer Houses)
Authors: Iskandaria H , Putri B I 
Published: November 2021

Abstract
The easy spread of the Covid-19 virus and its fatal effects have caused several Central and Local Governments to reduce activities outside the home including work and school which are replaced with online activities. Lecturers as academics carry out tasks that still have to teach and do Tri Dharma online from home so as to maintain health so as not to infect families but still be productive as a teacher. Based on the formulation of the problem, a descriptive research will be carried out in order to obtain an accurate picture of the field conditions regarding the facts and phenomena being studied. Observations, interviews and data from home owners will form the basis of research and several approaches include non-physical identification and physical identification. The results of this study are to determine the part of the residential room that was developed to anticipate the spread of the Covid 19 virus in the form of implementing health protocols in a residential environment by dividing the rooms of the house and parts of the house that can support work from home.