bluuebunny/crossref_metadata_2025_split huggingface dataset:
Temporal Design of Art Painting Landscape Based on Ant Colony Optimization Algorithm
Authors: Jiang Qiuyue 
Published: February 2023

Abstract
In the long history of painting, art research in each period will also reflect on the current situation and future improvement. Inspired by the group behavior of natural insect communities, to find the shortest path between insect nests and food, a simulated evolutionary algorithm ant colony algorithm is proposed to simulate the foraging behavior of natural ant colonies. This paper studies the temporal design based on ant colony optimization algorithm. Time is an inseparable part of landscape design. With the continuous progress of time, various landscape characteristics have also been formed. The purpose of this paper is to provide theoretical and practical support for the improvement of art painting landscape design from the perspective of time. The ant colony optimization algorithm is used to analyze and analyze the values of the algorithm parameters.
A Quantitative Plant Type Recognition algorithm based on Gene Expression Programming
Authors: Deng Qingying , Deng Song 
Published: February 2023

Abstract
Efficient and accurate plant type identification is an important foundation for biological research. The existing traditional machine learning classification algorithms have the defects of low classification accuracy in solving plant type recognition and cannot quantitatively give the corresponding class recognition model. In this paper, we propose a Quantitative Plant Type Recognition algorithm based on Gene Expression Programming (QPTR-GEP). Firstly, the plant type data set to be processed is preprocessed; then, the GEP population corresponding to plant type identification is constructed, and the corresponding quantitative identification function expressions are obtained after genetic operations such as mutation, recombination and transposition; finally, the classification expression with the highest fitness is used as the classifier corresponding to a single plant type, and the classifier model integrating the data set containing all plant type is put into the data set for plant type identification. Experimental results on the open source Iris demonstrate that our proposed algorithm outperforms SVM and Decision Tree algorithms for plant type identification.
Analysis and Discussion on Emergency Rescue Inspection Case of Machine Roomless Elevator by Data
Authors: Wang Lei 
Published: February 2023

Abstract
This paper introduces the principle and method of emergency rescue for machine room-less elevator, analyzes an inspection case due to the failure of the electric release function, studies and proposes the importance of monitoring the door lock signal by the electric release device through the electrical working principle, and analyzes the failure reason and safety hidden danger of the emergency rescue device for machine room-less elevator.
Sentiment recognition model of EEG signals combined with one-dimensional convolution and BiBASRU-AT
Authors: Zhu Feiyu , Wang Jiehua , Ding Weiping , Xie Tian , Han Qiuyun 
Published: February 2023

Abstract
To address the problems of low accuracy of EEG emotion sentiment and insufficient feature extraction ability of recurrent model, an EEG sentiment recognition model combining one-dimensional convolution and BiBASRU-AT is proposed. The data set is preprocessed in segments to expand the number of samples, and 62 channel local emotional features are extracted from one-dimensional convolution; The built-in self-attention simple recurrent unit is constructed to capture the multi-channel fusion features and the dependence between channels. The soft attention mechanism identifies the key features that have a great impact on the identification of emotional tendencies, and the linear layer outputs the positive, neutral and negative emotion recognition results. The experimental results on the EEG data set(SEED) show that the model achieves an average classification accuracy of 90.24%, which is higher than the excellent deep learning model compared with the experiment. The built-in self-attention simple recurrent unit has stronger feature capture ability, which proves the effectiveness of the model.
Research on Location Routing Problem of Multi-type Precooling Facilities Based on Bi-level Programming Model
Authors: Wang Xuping , Zhang Chiyi , Yang Huimin , Li Ya 
Published: February 2023

Abstract
Compared with developed countries, the decay rate of fresh agricultural products in China is still high, which makes precooling problem in the first mile widely concerned by the government and enterprises. At the same time, new precooling facilities such as modular fixed precooling warehouses and mobile precooling vehicles have become effective tools to solve the precooling problem. Combined with the national conditions of scattered agricultural production and small farmers occupying the main body in China, it is necessary to unify the layout of fixed precooling facilities and mobile precooling facilities. In this paper, a bi-level programming based multi-type precooling facilities location-routing model is constructed from the perspective of precooling service providers. An extensive numerical experiment is carried on to show the efficiency of the model and algorithm in different problem sizes.
Investigation on Thermodynamic Stability of 10H and 14H Long Period Stacking Ordered Phase in Mg-Zn-Y Alloy
Authors: Yu Zhiqing , Li Xiaotao , Ma Zhenning , Wang Xun , Li Xing 
Published: February 2023

Abstract
In this paper, enthalpies of formation and electronic structures of long period stacking ordered phases in ternary Mg-Zn-Y alloys are calculated by first-principles. Through calculations of the enthalpies of formation, it was found that enthalpies of formation of 10H phase and 14H phase are negative, and the enthalpy of formation of 10H phase less than that of 14H phase. It shows that both phases can form stable structure. The energy of transformation calculations show that 14H phase is more stable than 10H phase. The analysis of electronic structure shows that the difference between the structural stability of 10H phase and 14H phase is due to the different number of bonding electrons at the lower energy level of Fermi level. More bonding electrons determine that 14H phase has better stability than 10H phase.
Construction Measures for Defect Reinforcement of Concrete Structures in Nanshan Water Purification Plant
Authors: Hu Cong , Yao Siqi , Ouyang Xuanri , Yu Mian , Xu Junpeng , Xie Shaoqi , Li Shumin 
Published: February 2023

Abstract
The concrete material due to conveniently, price is low wait for a reason, is currently the mainstream architecture materials, concrete is subject to corrosion in the process of serving, however, especially in wastewater treatment, water purification and other service of concrete structures under complicated environment, especially the strength degradation, the service life of the structure and the structure of security is extremely unfavorable. In this paper, the structural defects of the primary sedimentation tank of a set of system in Shenzhen Nanshan Water purification Plant are detected, the geological survey results and related construction experience are analyzed, and the anti-seepage reinforcement construction measures are put forward.
An Intelligent Compound Prediction Model Based on WOA and ELM
Authors: Wan Chunlu , Xu Kang , Wang Jie 
Published: February 2023

Abstract
In order to reduce the prediction error of Air Quality Index (AQI) by Extreme Learning Machine (ELM), an Intelligent Composite Prediction Model (ICPM) is proposed. ICPM uses an Improved Whale Optimization Algorithm (IWOA) to find the ELM parameters. IWOA introduces logarithmically varying nonlinear control factors and cosine varying adaptive weighting factors to balance local exploitation with global search capabilities. Prediction of AQI combined with daily historical data of air quality in Henan Province (2019), it is proved that ICPM has better prediction performance and generalization performance than ELM and other models.
Research on holographic display and technology application of art museum based on immersive design
Authors: Yu Deng , Yao Wang 
Published: February 2023

Abstract
With the rapid development of science and technology, artificial intelligence digital technology has gradually entered human life and combined with art. It has become a major trend of future exhibitions to create immersive exhibitions through the intervention of digital technology and artificial intelligence in art museums. The immersive art exhibition is to change the sensory conditions of the audience through the intervention of digital media, from the original visual experience to the fusion of various senses such as “sight, hearing and touch”, so that the audience can enter a new world of works experience. the immersive exhibition composed of the combination of technology and art has become an important exhibition method to attract audiences. The creation of immersive exhibitions relies on the application of technologies such as Front-projected Holographic Display and Augmented Reality. At present, immersive exhibitions around the world are emerging in an endless stream. Under the general trend of information exhibition, how to combine works of art with digital media and endow them with connotation, and how digital technology is involved in the exhibition to form the final immersive effect, are issues worth considering at present.
A Method for the Fusion of Results from RFID and VLPR
Authors: Wang Jia , Zhang Hong , Zou Huayi , Jiang Suiping 
Published: February 2023

Abstract
Radio Frequency Identification (RFID) and Vehicle License Plate Recognition (VLPR) are two main methods for vehicle identification. How to fusion the recognition results of the two methods is a problem that needs to be solved in practice. The existing fusion technology usually uses trigger acquisition for precise matching, or uses one recognition result as a reference to perform matching in another result set, while these technology does not provide a clearly algorithm or has certain limitations, and is not universal. A matching algorithm is presented in this paper, which takes advantage of the similarity metric between the results from RFID and VLPR, thus eliminating the drawbacks of existing match methods. The algorithm calculates the similarity metric of the results from RFID and VLPR by the vehicle license plate character graphics similarity, then find matching results from the two recognition results in a specific time window, finally work out precise matching result or similar matching result. The presented algorithm is simple but effective, with no need to triggering RFID and VLPR simultaneously. The algorithm can output both precise matches and similar matches. Through the verification results in the real road scene, the performance in the license plate similarity calculation and fusion matching process is consistent with expectations, which shows the effectiveness of the algorithm.
The Design of local placement detector for cable accessories based on ultrasonic technology
Authors: Zhao Tiemin , Liu Jianshu , Zheng Shiyang , Yang Le , Ding Zhen , Li Dongsheng , Li Kai , Li Wenpeng , Yang Xue , Chai Fangsen 
Published: February 2023

Abstract
In the process of cable transmission, the existence of air gap, tip, burr and other conditions will cause partial discharge phenomenon and lead to cable insulation aging, which can affect the safety of power transmission. Partial discharge detection can detect early insulation defects accurately, timely and efficiently. It is an ideal method to detect the occurrence of PD by ultrasonic wave which is the by-product of PD because it is less affected by electromagnetic interference. At the same time, a clamping device is designed, which is compact in structure, easy to carry and high in accuracy. This discharge detector can reduce the degree of external interference in the detection process, improve the accuracy of ultrasonic waveform, accurately identify whether partial discharge occurs, and alarm.
Dynamic Detection Based on Planar Array Capacitance for Adhesive Defects of Thermal Protection Structure
Authors: Sun Yurong , Zhang Yuyan , Wen Yintang 
Published: February 2023

Abstract
The defect detection of thermal protective structures is of great significance in ensuring the safe flight of aircraft. In this paper, a dynamic measurement method based on the planar capacitance sensing principle is proposed to solve the problem of detecting defects in the adhesive layer of large-area thermal protection structures. This paper analyses the principle of capacitive sensing and establishes a planar array capacitive dynamic detection system. The dielectric distribution of the structural components to be measured is obtained at different locations by moving the array of electrode sensors regularly. To obtain the dielectric distribution information of the complete structure, the dielectric distribution at adjacent locations is spliced and fused. To achieve the precise location of the overlapping areas in the image to be fused, an image alignment method based on coordinates is adopted. The experimental results show that our proposed method can detect defects in the adhesive layer of large-area thermal protection structures and achieve complete visualization of the adhesive layer.
Research on Indoor AGV Fusion Localization Based on Adaptive Weight EKF Using Multi-sensor
Authors: Xu Haoran , Li Yi , Lu Yucheng 
Published: February 2023

Abstract
To solve the problem of large accumulative errors of wheel odometer and inertial measurement unit (IMU), which make pose calculation mistakes due to friction coefficient of the ground or bumps and collisions, furthermore, affect path planning and navigation of automated guided vehicle (AGV), an extensible fusion localization method based on multiple sensors is proposed. Based on the traditional extended Kalman filter (EKF), the internal positioning data is used for prediction, while the external positioning data is used for correction. According to the states of different sensors, the adaptive weight method is applied to eliminate the influence of system accumulative error and provide continuous and accurate positioning data. The experimental results show that compared to single-sensor, the fusion localization method has an increase in quantity, which can reach an accuracy within 5~8cm. It can deal with non-line-of-sight (NLOS) landmark occlusion situations, and can navigate in dim light or dark environments. The system ensures the accuracy of fusion data through visual positioning and ensures the stability of the system through the odometer and IMU. New positioning sensors are also possible to be added into the system for data fusion.
Research on Particle Swarm Fusion Sliding Mode Tracking Decoding Technology for Rotary Transformer
Authors: Du Yexin , Qing Li , He Jie 
Published: February 2023

Abstract
A sliding mode tracking fusion particle swarm optimization (PSO) was proposed to solve the soft decoding problem of the rotary transformer. Firstly, the principle of soft decoding of the rotary transformer was expounded and analyzed. Then the mathematical model of the sliding mode tracking and decoding system was established. Based on sliding mode tracking and decoding, the parameters in the model were selected iteratively by using a particle swarm optimization algorithm according to the fitness value function. Finally, the simulation environment was built by Simulink and S-function for simulation verification. The simulation results show that the decoding scheme based on particle swarm optimization and sliding mode tracking can track and decode the rotating transformers at different speeds, such as uniform speed, acceleration speed, and sines/cosines speed, without steady-state error and with certain anti-interference.
Intelligent Inspection Technology of Substation Secondary System Based on Machine Vision
Authors: Jin Sheng , Yin Jianjun , Zhou Jie , Cai Yihang , Hu Yanwei 
Published: February 2023

Abstract
To solve the problems of low efficiency and poor precision in the current inspection of substation secondary systems, machine vision technology is introduced to conduct the design and research of inspection technology. It acquires equipment images and manufactures an image data set of that secondary system equipment of the transformer substation. It also processes and segments an inspection guideline image using machine vision technology and realizes itinerant inspection of the secondary system instrument equipment of the transformer substation based on the acquired inspection image. The comparative experiments show that the efficiency and accuracy of the new inspection technology have been significantly improved.
Multi-task Joint Learning to Enhance Named Entity Recognition
Authors: Shen Xiajiong , Hu Xiaojie , Liu Ning , Shen Yatian 
Published: February 2023

Abstract
Named Entity Recognition (NER) models have achieved good performance in recent years but also have some shortcomings. Existing models regard NER as a sequence labeling task for label prediction, without considering the impact of different stages in the entity recognition process on the final result. NER can be viewed as two separate subtasks: boundary detection task and type prediction task. The two subtasks can transmit information and cooperate in the process of entity recognition, so the synergy of the two subtasks is beneficial to NER. In this paper, we propose a method to split the NER task into multiple subtasks and use the information of each subtask to enhance the NER task. According to the characteristics of different subtasks, we use different feature extraction method models to extract structural information useful for this task effectively. Using the information extracted from each subtask or the final results of the subtasks, the performance of NER was enhanced through the gating network. We conducted extensive experiments on the CONLL2003 dataset, and the experimental results show that our proposed multi-task joint learning enhances the effectiveness of the named entity recognition model.
Identification for Red Automobile Based on Cifar-10 Using Machine Learning Models
Authors: Li Zongze 
Published: February 2023

Abstract
Algorithms were made and improved across time in different application fields to help them better fit and solve problems that human encounter. Specifically, this paper focuses on the identification mission, that is commonly needed and used by governmental facilities and police departments to track certain objects. However, it is not always that easy, and methods were made to help invent and test these algorithms, along with a vast dataset collected for use, so that they can be examined before putting into real-life use. An existing dataset called Cifar-10 was introduced and chosen, and different methods were introduced and used, to design and examine the accuracy of an identification method. This paper mainly focuses on a red automobile identification model. The experimental results demonstrated the effectiveness of the model. Further usages of similar models will also be applicable with corresponding adjustments, hoping to make it into other similar areas and fulfilling similar goals.
Polynomial tractability for integration in an unweighted function space with absolutely convergent Fourier series
Authors: Goda Takashi 
Published: February 2023

In this note, we prove that the following function space with absolutely convergent Fourier series
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RecurrentPRDM10Fusions in Superficial CD34-Positive Fibroblastic Tumors : A Clinicopathologic and Molecular Study of 10 Additional Cases of an Emerging Novel Entity
Authors: Zhao Ming , Yin Xiaona , He Huiying , Fan Yuqian , Ru Guoqing , Meng Xuli 
Published: February 2023

AbstractObjectivesSuperficial CD34-positive fibroblastic tumor (SCD34FT) is a rare mesenchymal neoplasm. The genetic alterations of SCD34FT have yet to be determined. Recent studies suggest it overlaps with PRDM10-rearranged soft tissue tumor (PRDM10-STT).MethodsThis study aimed to characterize a series of 10 cases of SCD34FT using fluorescence in situ hybridization (FISH) and targeted next-generation sequencing (NGS).ResultsThe study recruited 7 men and 3 women aged between 26 and 64 years. The tumors were located in the superficial soft tissues of the thigh (8 cases), foot, and back (1 case each), ranging in size from 1.5 to 7 cm. The tumors were composed of sheets and fascicles of plump spindled to polygonal cells, with glassy cytoplasm and pleomorphic nuclei. Mitotic activity was absent or low. Common and uncommon stromal findings included foamy histiocytic infiltrates, myxoid changes, peripheral lymphoid aggregates, large ectatic vessels, arborizing capillary vasculature, and hemosiderin deposition. All tumors expressed CD34, and 4 demonstrated focal cytokeratin immunoexpression. In 7 of 9 (77.8%) cases analyzed, FISH identified PRDM10 rearrangement. Targeted NGS revealed a MED12::PRDM10 fusion in 4 of 7 cases tested. Follow-up showed no recurrence or metastasis.ConclusionsWe demonstrate recurrent PRDM10 rearrangements in SCD34FT and provide additional evidence of a close relationship to PRDM10-STT.