bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of micro steel fibre contents on compressive and self-sensing properties of polyethylene fibre-reinforced cement composite (PE-FRCC) in cyclic compression
Authors: Yun Hyun-Do , Choi Won-Chang , Park Wan-Shin , Jin Ai-Hua , Kim Yong-Chul , Seo Soo-Yeon 
Published: August 2023

Abstract
This study is conducted to develop a cement-based strain-detecting sensor with high cost-effectivity, large strain measuring range and good compatibility with concrete infrastructures. The paper describes experimental results on the compressive properties and piezoresistive behaviour of polyethylene(PE) fibre-reinforced cement composite(PE-FRCC) with different contents of micro steel fibres (SFs) under cyclic compression. The synthetic PE fibres were added into cement-based mortar to improve the strain capacity in compression and micro SFs at 0.25-1.5% by volume fraction of cement were incorporated to improve the compressive properties and electrical conductivity. Test results show that for the PE-FRCC with compressive strength of 32MPa, the increase in the micro SF content to 0.5% increased about 45% in the compressive strength compared to PE-FRCC without SFs. The addition of micro SFs into PE-FRCC improved the compressive properties, such as modulus of elasticity and lateral confinement. The incorporation of micro SFs is also effective to reduce the signal noise in the relationship between fractional change in resistance (FCR) and axial strain of PE-FRCC. PE-FRCC sensor with more 1.0% micro SF (PE0.75+SF1.00 composite) possess a strong linear relationship between FCR and axial strain during repeated compression at different stress amplitudes.
Internet of Things Horizontal Platform Development for Expanded Application Scenarios and Use Cases
Authors: Ganchev Ivan , Ji Zhanlin , O’Droma Máirtín 
Published: August 2023

Abstract
This paper presents the horizontal approach for the development of Internet of Things (IoT) platforms, based on a generic, multi-service, cloud-based IoT operational platform, called EMULSION, elaborated for the rapid development of mobile IoT systems and quick roll-out of corresponding IoT services. The platform is successfully used as a basis for the development of various IoT prototype systems for different IoT domains, such as smart environment control, smart health, smart electric appliances, smart water supply, etc. As an example of these, a ground surface displacement monitoring IoT system, operating in the area of smart environment control, is presented, along with aspects of the hardware design of the produced low-cost, small-size, global navigation satellite system (GNSS)-based sensor unit, utilized by it. The system architecture design is set out, supplemented by the presentation of initial test results.
The Broadband Emitting and Lattice Occupation Analysis of Eu2+, Eu3+ and Ce3+ co-doped K3YSi2O7 Phosphors
Authors: Chen Yuhui , Fan Pu , He Xiao , Liu Xiaoguang , Li Ling 
Published: August 2023

Abstract
Eu3+, Eu2+ and Ce3+
doped K3YSi2O7 phosphors are synthesized under reducing atmosphere. Photoluminescence properties show K3YSi2O7:1%Ce, 1%Eu at 330 nm excitation (FWHM = 211 nm, where FWHM stands for the full width at half maximum) can produce broadband emission. The preferential occupation sites of Ce and Eu ions in K3YSi2O7 are calculated using the bond energy theory. Eu2+, Eu3+, Ce3+ ions preferentially occupy K3, Y2, K1 sites, respectively. The broadband emission of the phosphor is caused by the dopant ions’ selective site occupancy.
Broadband absorption based on multi-layered ENZ film: from directional to omnidirectional absorption
Authors: Li Jiacheng , Liu Shuang , Wu Shenglan , Li Wei , Liu Yong , Zhong Zhiyong 
Published: August 2023

AbstractWe propose a flat multilayered structure fabricated from gradient epsilon-near-zero (ENZ) materials (SiO2/Si3N4/Al2O3/AlN/TiO2/α-Ta2O5) coated on aluminium (Al) that enables broadband directional control of infrared absorption and adopt the Particle Swarm Optimization (PSO) method to optimize its structural parameters. The results demonstrate that the absorbers can exhibit high absorption (> 0.6) at specific angles (60° to 80°) and near-unity omnidirectional (0° to 80°) absorption both in p-polarization with covering the entire long-wavelength infrared (LWIR) range (8 μm to 14 μm), respectively. The directional control of the absorption with high efficiency and wide bandwidth would be great potential in applications such as thermal imaging, infrared camouflaging, and radiative cooling.
Electrical Properties of Strain-Hardening Cement Composite (SHCC) with Multi-Walled Carbon Nanotubes Exposed to High temperature up to 900 °C
Authors: Jeong W J , Wang Q , Yun H D , Seo S Y 
Published: August 2023

Abstract
Cement-based sensors mixed with carbon nanotube (CNTs) for structural health monitoring were studied to detect changes in electrical resistance under the influence of temperature, pressure, and mass. Strain-hardening concrete composite mixed with CNT was heated to 900 °C to analyze the electrical resistance characteristics at high temperatures. The temperature and electrical resistance were measured using a thermocouple and an LCR meter during the heating and cooling processes. The resistance trend changed between 300 and 400 °C during the heating process, after which the resistance change rate with respect to temperature decreased. At 700 °C or higher, the resistance became larger as the initial resistance increases. In the cooling process, when the temperature dropped below 700 °C, a rapid change in resistance was observed, and the resistance began to drop sharply between 500 °C and 600 °C to become negative resistance. Following this, self-sensing ability decreased owing to changes in the resistance with respect to temperature. Multi-walled carbon nanotubes could not be distinguished by scanning electron microscope imaging after heating.
Application of Big Data and Artificial Intelligence in Substation Operation and Maintenance
Authors: Yang Lin , Li Wenwen , Zhang Su , Wan Jia , Zhao Hongbo 
Published: August 2023

Abstract
In order to solve the problem that a large amount of equipment data obtained in the operation and maintenance work of substations is not fully utilized, this paper mainly analyzes and processes the data obtained by operators from the site by combining data mining technology. The first is to use the trend extrapolation method for data fitting to guide equipment maintenance; The second is to use multiple linear regression method to analyze the influencing factors of equipment status and carry out defect prediction and fault diagnosis; Third, by analyzing the predictability of DGA data, the prediction method based on the maximum Lyapunov index is used to predict the dissolved gas in the oil, so as to judge the operation status of the transformer and the occurrence of the fault through the analysis of DGA prediction data, and realize the prediction of the transformer fault. Reasonable use of big data technology and artificial intelligence technology can greatly improve the intelligent level of substation operation and maintenance work, thus optimizing the allocation of human resources, and making the work more accurate and efficient.
Weighted Fuzzy Markov Chains for Regions Research on Rainfall Forecasting
Authors: Huang Xuan , Liu Xiaotong , Zhang Chunfu 
Published: August 2023

Abstract
The problem of rainfall prediction is of great importance for the study of the hydrological cycle of a watershed or region in China. Since rainfall series are not periodic as well as linear, rainfall series are measured based on Markov’s theorem, and the percentage of precipitation distance is used to classify the historical data. The traditional Markov chain was optimized and a weighted-fuzzy Markov rainfall prediction model was established. The results show that the average absolute error of the two prediction samples is 2.09%, except for 2019, when the rainfall in Guangzhou City is different from the past, and the model has high accuracy, which has good practical significance and extension value.
UAV Formation Adjustment Strategy Based on Greedy Criterion
Authors: Wang Yiru , Zhang Bo , Yang Huibing , Tang Zichun , Li Hanxu , Liu Xuanlin 
Published: August 2023

Abstract
In order to ensure that the UAV cluster remains electromagnetically silent during the attempted formation flight, so that the emission of electromagnetic wave signalsj is minimised, a purely azimuthal passive positioning method can be used to adjust the position of the UAVs. As it is difficult to keep the UAVs in formation flying on the same horizontal plane for a long time and the initial position information of the UAVs is not known. Therefore, this paper uses the sine and cosine theorems of in-plane triangles to connect slightly deviating UAVs to a determined UAV position, and in combination with the characteristics of the model, constructs a greedy criterion based on the minimum number of UAVs required to transmit the signal, and in this way gives an adjustment scheme for the UAV position.
Unsupervised Anomaly Detection of Subway Vibration Signal Based on Ultra-weak FBG Sensing Array Combined with RCMDE and Local Density
Authors: Yang Yan , Yin Qianru , Yue Lina 
Published: August 2023

Abstract
The subway vibration signal can reflect the health status of the passing train and tunnel structure. Identifying the abnormal vibration signal is a prerequisite for safe subway operation. In view of the difficulties in collecting anomalous samples in actual engineering and extracting effective features of high-dimensional time series, an unsupervised anomaly detection approach on the ground of RCMDE and local density has been put forward to identify vibration signals captured by the ultra-weak FBG sensing array cable. Two experiments demonstrated that compared with other methods, RCMDE could better evaluate the signal and extract features more precisely and that the abnormal vibration signals of passing trains consistent with the facts were accurately detected by the proposed method while other methods had errors.
Multi-objective Logistics Distribution Path Optimization Based on Annealing Evolution Algorithm
Authors: Zeng Xinzhu , Wang Yiding 
Published: August 2023

Abstract
Logistics distribution is a collection of interrelated organizations and facilities. There is a waste of cost and time in many links. Therefore, it is particularly important to use information technology to improve distribution efficiency. Under the constraints of delivery vehicle cost and time, this paper proposes an improved genetic simulated annealing algorithm (SAGA), which combines the global search ability of the genetic algorithm (GA) and the simulated annealing algorithm (SA) with strong local search ability to solve the vehicle routing problem with time windows (VRPTW). The perturbation factor is introduced to improve the local search, and the crossover method is optimized to obtain more efficient genetic operators by using population information. In this paper, combined with the actual application case, the simulation experiment is carried out in MATLAB. The experimental results show that, compared with the traditional genetic algorithm and simulated annealing algorithm, the total cost of the improved genetic simulated annealing algorithm is reduced by about 15%, which provides a more suitable vehicle route planning scheme.
Betti Number for Point Sets
Authors: Wang Hao 
Published: August 2023

Abstract
Topology is the foundation for many industrial applications ranging from CAD to simulation analysis. Computational topology mostly focuses on structured data such as mesh. However, unstructured datasets such as point sets remain a virgin land for topology scientists. The significance of point-based topology can never be overemphasized, especially in the area of reverse engineering, geometric modeling, and algorithmic analysis. In this paper, we propose a novel approach to compute the Betti number for point set data and illustrate its usefulness in real-world examples. To the best of our knowledge, our work is pioneering and the first of its kind in the field of computational topology.
Application of k-sigma Algorithm Based on Monte Carlo in Outlier Detection
Authors: Chen Xingyan , Ding Zhengsheng 
Published: August 2023

Abstract
Under the background of intelligent times based on information technology, the analysis and replacement of outliers become particularly critical for databases in the face of massive sequential data streams. In order to improve the effectiveness and practicability of the detection method, this paper determines the abnormal scores of data points in a specific data set by using the K-Sigma algorithm of the Monte Carlo method, adaptively adjusts the k value according to the abnormal scores, and marks the abnormal points.
The advantages of the traditional k-sigma algorithm are fast operation speed and theoretical basis, while the disadvantages are that each index dimension is determined independently. However, in industrial production, due to the multi-index dimension of time series data, multiple size indicators of a data set are related to each other. Therefore, it is necessary to comprehensively consider whether an anomaly is abnormal by combining it with the data of other indicators. In addition, when there are no outliers in the data set, the traditional k-sigma algorithm is used to take the mean and variance of the data set as parameters. Due to the limitations of the data set itself, some data points will be mislabeled as outliers. Through the k-sigma algorithm based on the Monte Carlo method, we can effectively solve the above problems.
The k-sigma algorithm based on the Monte Carlo method can generate a normal distribution according to the distribution of original data points, and extract a large quantity of data from the distribution to generate Monte Carlo data set. The Mahalanobis distance li
from each sample point to the mean in the Monte Carlo data set is calculated and compared with the Mahalanobis distance lj
from the samples to be detected to the mean in the original data set. According to the number of sample points satisfying li
< lj
in the Monte Carlo data set, the value of the parameter kj
is determined adaptively, and thus the outliers are determined. We implemented the k-sigma algorithm based on the Monte Carlo method through python, evaluated the effectiveness of the algorithm by accuracy, recall rate, and F1 score, and compared it with some machine learning algorithms. The results verified the feasibility and effectiveness of the algorithm, which can be used for real-time anomaly detection in the energy management database.
Mathematical Model of Receiver Location with Unknown Transmitter Number
Authors: He Zhilong , Lv Shuangqing , Zhu Xunbo , Yang Zhengguo , Li Xuefang , Zhao Jianhong 
Published: August 2023

Abstract
The paper uses the theory of elementary mathematics, uses the angle and side length relationship between multiple UAVs, and applies the sine theorem and cosine theorem to establish the bearings-only passive positioning model. The model can be solved by only two transmitters for accurate positioning, Through practice, the model has a high fitting degree, and finally realizes the positioning of the UAV.
Increased tropical cyclone intensification time in the western North Pacific over the past 56 years
Authors: Wu Liguang , Lu Jun , Feng Xiaofang 
Published: August 2023

Abstract
It has been projected that the influence of anthropogenic climate change on tropical cyclone (TC) intensity could be detected by the end of the century although significant increasing trends in TC intensity metrics have been found based on the currently available historic records. The human influences on TC intensity have been debated for about two decades because of a lack of quantitative assessment of the contributions of large-scale environmental factors and track shifting. As an extension of a previous study, we show that the observed rise in the percentage of intense TCs in the western North Pacific basin over the past 56 years resulted from the combined influence of the track shifting and temporary changes in environmental factors. The influence of environmental factors was primarily owing to the decrease of environmental vertical wind shear and the warming of sea surface temperature (SST). While a small part of the observed rise in the percentage of intense TCs resulted from SST warming, the track shifting increased the TC intensification time by 18.2% (11.3 h) over the past 56 years, accounting for more than one-third of the observed percentage increase in intense TCs. Since track shifting is also projected in the global warming experiments, this study suggests that anthropogenic climate change may intensify TCs by shifting TC prevailing tracks.
Estimation of Selection Indexes and some Genetic Parameters in the Genotypes of the Rice Crop Oryza sativa L.
Authors: Al-Wardi Mustafa Eskander Zaid , Abbas Saddam Hussein , Musa Abdul-Kadhim Jawad 
Published: August 2023

Abstract
The current slowdown in production is a cause for concern and must be reversed to meet the population increase. Therefore, it is necessary to exploit genetic resources in maximizing production to ensure food security, as genetic differences provide a continuous source of variation, which is the basis for selecting plants that are excelled in their productive traits. A field experiment was conducted at the rice research station in Al-Mishkhab which locoted in the south of centre of Najaf provainc/ Iraq, during the summer season 2021. The 22 genotypes were cultivated, using the RCBD randomized complete block design with three replicates, and the averages were tested by Duncan’s test at a probability level of 0.05. The results of the mean squares of the genotypes were significant for all studied traits at a probability level of 1% and the highest value of an indicator as a Selection Index was (1963.052) for the genotype of IPA1. The genotype IPA1 gave the highest averages in plant height, flag leaf area, number of days to physiological maturity, grain yield and biological yield, 134 cm, 38.59 cm, 151.33 days and 10.81 tons. ha−1 and 41.77 tons.ha−1 respectively. The genotype was significantly excelled by giving the highest values of chloropyll content 44.55 SPAD for Khazar and weight of 1000 grains 28.27 g for Al Baraka genotype. The genetic and phenotypic variations were significant for all traits with the close of genetic variances values to the values of the phenotypic variances. The results of the genetic analysis showed that the values of the phenotypic and genetic variation coefficients ranged between low and medium for most traits. The percentage of heritability in the broad sense was high for all traits, and the values of the expected genetic improvement ranged between low, medium and high for the traits and the highest value of the expected genetic advance as a percentage was 44.42 for the percentage of infertility.
Impact Foliar Spraying of NPK Nano Fertilizer on Yield Traits of Two Varieties of Bread Wheat (Triticum aestivum L.)
Authors: Alqasim Yahya Fawzi Yahya , Ghazal Salim Abdulla Younis Al- 
Published: August 2023

Abstract
A field experiment was performed in two sites within Nineveh Governorate, the first site within the center of Mosul (Gleokhan) and the second site within the administrative boundaries of Namrod sub-district of Nineveh Governorate, which is (45) km away from the center of Mosul center. The treatments of the experiment was a three levels (1, 2 and 3 g.L−1) of NPK nano fertilizer and a fourth level of addition such as the control treatment (the traditional farmer method), and two varieties of bread wheat (Bhoth 22 and Abu Ghraib). was done Study the following qualities: number of spikes, spike length, number of spike grains, weight of 1000 grains, grain yield, biological yield, harvest index and straw yield. As for the results of the experiment, they were as follows: In the first study site (Gleokhan), no significant differences were observed between the levels of nano-fertilizer in most of the studied traits, and in the second site, the control treatment was significantly superior by recording the highest averages for most of the traits, and the spraying treatment 1 g.L−1 recorded a significant superiority for the weight of 1000 grains trait. Bhoth 22 outperformed Abu Ghraib with most of the studied traits and for both locations, while the Abu Ghraib cultivar was surpassed to Bhoth 22 in spike length and straw yield in the first location, spike length, number of grains per spike, and straw yield in the second location.
Impact of Humic Acid and some Pre and Post-Harvest Treatments in Improving Storage Behaviour of Hot Pepper Fruits (Capsicum annuum L.) Hybrid Barbarian F1
Authors: Fadala Laila Turki , Taain Dhia Ahmed , Hassan Fatima Ali 
Published: August 2023

Abstract
The experiment was carried out during the 2020-2022 growing seasons in one of the unheated greenhouses at Dhi Qar University, south of Iraq, in order to investigate the impact of adding humic acid, pre and post-harvest treatments and their interaction in the storage behavior of hot pepper fruits hybrid Barbarian F1. Factorial experiment consisted of three factors which were the possible combinations of three concentrations of humic acid 0, 1, 2 g. l−1 and five pre and post-harvest treatments which were aqueous extract of jujube leaves at a concentration of (75) g. l−1, aqueous extract of pomegranate peels at a concentration of 5 ml. l−1, calcium at a concentration of 1.5 ml. l−1, arginine acid at a concentration of 200 mg. l−1 in addition to control treatment (distilled water only). Fruits packed into polyethylene bags of 1 kg capacity containing 8 holes of 5 mm diameter and stored at a temperature of 10 ° C in a refrigerated incubator for two weeks. The experiment was designed out according to C.R.D design with three replicates. The results were analyzed by the analysis of variance and mean values were compared using the Revised Least Important Difference Test at 0.05 probability. Results showed that the fruits treated with humic acid at a concentration of 1 and 2 g.l−1 was superior to control in reducing the percentage of decay and retaining the highest content of vitamin C, total soluble solids, capsaicin and phenolic substances. As for the effect of the type of treatments, the fruits treated with calcium recorded the lowest percentage of decay compared to the rest of the treatments in both seasons. The soaking method outperformed compared to spraying one in retaining fruits content of vitamin C. the most interactions among studied factors were significant in their effect on the most parameters.
Effects of Trichoderma Harzianum and Trichoderma Asperellum Against Egg of Meloidogyne Incognita under Laboratory Condition
Authors: Abdulla Ghufran Ali , Saleh Hamood M. , Al-Hakeem Asmaa Mansour 
Published: August 2023

Abstract
In vitro experiment was conducted to evaluate the effects of two Iraqi isolates of Trichoderma harzianum and Trichoderma asperellum against Meloidogyne incognita. It was noted T. harzianum and T. asperellum had a clear effect on on egg hatching inhibition of root-knot nematode, Meloidogyne incognita. the percentage of egg hatching inhibition after the seventh day, reaching to 86.50% and 83.75% respectively, There were no significant differences between them compared to the control.