bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on Interdomain Routing Control in SDN Architecture
Authors: Chen Liangzhe , Zhu Yin , Sun Xinyu , Zhang Yinlin , Min Gang , Zou Yang , Shu Zhong 
Published: July 2022

AbstractAiming at the difficulty of network management due to the coexistence of traditional BGP network and new SDN network, this paper proposes a routing update algorithm with clear interdomain structure and network exception handling ability. By defining SDN, BGP-SDN fusion and BGP three network domains, a packet transmission path with route discovery and update capability were formed through the three network domains in sequence. On the premise of reducing the communication delay range, the route update delay is set, and the exception handling mechanism is introduced. Specify the master controller to make the Interzone routing control rules and make routing updates a key parameter in the data flow table of border switches. The algorithm firstly ensures the absolute unimpeded communication between network domains, provides a reliable time guarantee for network exception handling, enhances the connection between control servers between network domains and between control servers and boundary switches, and improves the synchronization of multiple links in network communication. By using Mininet to build a simulation experiment platform, the reliability and feasibility of the proposed algorithm are verified from the perspectives of data packet loss and Interzone route update delay, and it is suitable for application and implementation in the current Internet environment.
Multidimensional Data Analysis Based on LOGIT Model
Authors: Gan Jiahua , Zhang Meng , Xiao Yun 
Published: July 2022

AbstractLogit Model is an important method for empirical analysis of multi-source data. In order to explore the traffic safety mechanism, The Paper taked traffic behavior data as an example, researched personal characteristics of truck drivers, Analyzed the influence of the driver’s personal traits on traffic violations. Based on the binary logistics regression model, the analysis model of traffic violations was established. The results show that personality, driver’s license level, daily driving time, transportation route, vehicle ownership, and occupational disease are important factors that affect drivers’ violations. Further data analysis shows that truck drivers with bile personalities, driving for more than 12 h per day, no fixed transportation routes, and vehicles with loans have the highest probability of violations. The data analysis conclusion provides data basis for truck driver management and improving truck traffic safety.
Leveraging Modern Big Data Stack for Swift Development of Insights into Social Developments
Authors: Huang He , He Yixin , Zhang Longpeng , Zeng Zhicheng , Ouyang Tu , Zeng Zhimin 
Published: July 2022

AbstractInsights of social development, presented in various forms, such as metrics, figures, text summaries, whose purpose is to summarize, explain, and predict the situations and trends of society, is extremely useful to guide organizations and individuals to better realize their own objectives in accordance with the whole society. Deriving these insights accurately and swiftly has become an interest for a range of organizations, including agencies governing districts, city even the whole country, they use these insights to inform policy-makings. Business investors who peak into statistical numbers for estimating current economical situations and future trends. Even for individuals, they could look at some of these insights to better align themselves with macroscopical social trends. There are many challenges to develop these insights in a data-driven approach. First, required data come from a large number of heterogeneous sources in a variety of formats. One single source’s data could be in the size of hundreds of Gigabytes to several TeraBytes, ingesting and governing such huge amount of data is not a small challenge. Second, many complex insights are derived by domain human experts in a trail-and-error fashion, while interacting with data with the aid of computer algorithms. To quickly experiment various algorithms, it asks for software capabilities for infusing human experts and machine intelligence together, this is challenging but critical for success.By designing and implementing a flexible big data stack that could bring in a variety of data components. We address some of the challenges to infuse data, computer algorithm and human together in Zilian Tech company [20]. In this paper we present the architecture of our data stack and articulate some of the important technical choices when building such stack. The stack is designed to be equipped with scalable storage that could scale up to PetaBytes, as well as elastic distributed compute engine with parallel computing algorithms. With these features the data stack enables a) swift data analysis, by human analysts interacting with data and machine algorithms via software support, with on-demand question answering time reduced from days to minutes; b) agile building of data products for end users to interact with, in weeks if not days from months.
Technological Intervention of Sleep Apnea Based on Semantic Interoperability
Authors: Liang Ying , Gao Weidong , Chuai Gang , Hu Dikun 
Published: July 2022

AbstractSleep apnea is an important factor that could affect sleep quality. A great number of existing monitoring and intervention devices, such as the polysomnography, mature heart rate respiratory monitoring bracelets and ventilator headgear can improve breathing in sleep, but are all functioning separately, with their data being disconnected, which fails to achieve multi-parameter fusion or a greater variety of applications. With the development of the Internet of Things (IoT), information interaction between IoT devices to facilitate integration of IoT devices has become a hot research topic. This paper focuses on the interoperability information model and technology for establishing interoperability information model among sleep and health devices for sleep apnea syndrome. This paper analyzes the heterogeneity of the knowledge organization system in sleep health data information through the abstract representation of data information, establishes the mapping relationship between data, information, and devices, and realizes the semantic heterogeneity elimination. It also defines inference rules about sleep apnea scenarios, achieves semantic interoperability between monitoring devices and other health devices, and finally realizes an unmonitored closed-loop control system for sleep apnea intervention. According to the test results, the system can react quickly in sleep apnea scenarios.
Research on Visualization of Power Grid Big Data
Authors: Zhou Jun , Tang Lihe , Shi Songyuhao , Li Wei , Hu Pan , Wang Feng 
Published: July 2022

AbstractWith the constant improvement of power grid planning and management requirements and the gradual advancement of the urbanization process, the problems that need to be taken into account in the planning process are increasing, especially the demand for big data visualization of the power grid has increased sharply. About 80% of the information that humans obtain from the external environment comes from the visual system. A picture is worth a thousand words. A good visualization platform can monitor the overall operation of the power grid, which is convenient for analyzing and monitoring the operation of power supply companies to provide customers with high-quality services. The platform can complete the interactive simulation of different services, and can display the monitoring and analysis of the power grid through a rich visual interface, which is convenient for people to understand the real-time status of the power grid. This paper uses various advanced visualization technologies and data module algorithms at home and abroad to cooperate with the monitoring network to realize the visualization platform of power grid big data, promote the further development of power grid big data applications, and form a big data standard system for power big data technology research, product research and development, and pilot construction.
Research on Positioning Technology of Facility Cultivation Grape Based on Transfer Learning of SSD MobileNet
Authors: Han Kaiyuan , Xu Minjie , Li Shuangwei , Xu Zhifu , Ye Hongbao , Hua Shan 
Published: July 2022

AbstractThere is an urgent need of developing grape picking robot with intelligent recognition function due to the decrease of grape picking workers’ population. Acquiring the 3D information of picking coordinate is the key process of constructing intelligent picking equipment. In this paper, based on SSD MobileNet neural network model, transfer learning and central deviation angle method were used to realize the positioning of picking coordinate points of facility cultivation grape by machine vision. After testing 720 fruit labels, 633 stem labels and 603 leaf labels labelled by pretreatment, the general precision was 79.5%, which was close to the inherent accuracy of the original model before transfer learning.
A Brief Comparison of K-means and Agglomerative Hierarchical Clustering Algorithms on Small Datasets
Authors: Abdalla Hassan I. 
Published: July 2022

AbstractIn this work, the agglomerative hierarchical clustering and K-means clustering algorithms are implemented on small datasets. Considering that the selection of the similarity measure is a vital factor in data clustering, two measures are used in this study - cosine similarity measure and Euclidean distance - along with two evaluation metrics - entropy and purity - to assess the clustering quality. The datasets used in this work are taken from UCI machine learning depository. The experimental results indicate that k-means clustering outperformed hierarchical clustering in terms of entropy and purity using cosine similarity measure. However, hierarchical clustering outperformed k-means clustering using Euclidean distance. It is noted that performance of clustering algorithm is highly dependent on the similarity measure. Moreover, as the number of clusters gets reasonably increased, the clustering algorithms’ performance gets higher.
Based on Internet of Things Platform Using NB-IoT Communication Low-Power Weather Station System
Authors: Wang Zhenxin , Deng Zhi , Xu Ke , Zhang Ping , Liu Tao 
Published: July 2022

AbstractIn recent years, meteorological environment has become a topic of concern to people. Various meteorological disasters threaten human life and production. Accurate and timely acquisition of meteorological data has become a prerequisite for dealing with various aspects of production and life, and also laid a foundation for weather prediction. For a long time, meteorological data acquisition system combined with modern information technology has gradually become a hot spot in the field of meteorological monitoring and computer research. The continuous development of NB-IoT technology has brought new elements to the research of meteorological monitoring system. This paper designs a weather station system based on NB-IoT, including data acquisition module, main controller module, NB-IoT wireless communication module, energy capture module, low power consumption scheme, etc.
Traffic Sign Detection Based on Improved YOLOv3 in Foggy Environment
Authors: Ma Luxi , Wu Qinmu , Zhan Yu , Liu Bohai , Wang Xianpeng 
Published: July 2022

AbstractAiming at the problem of poor detection accuracy and inaccurate positioning of traffic signs under foggy conditions, this paper proposes an improved YOLOv3 detection algorithm. Firstly, a data set of Chinese traffic signs in a foggy environment is constructed; The dark channel a priori algorithm based on guided filtering is used to process the image with fog, which overcomes the problem of image quality degradation caused by fog. Mosaic data enhancement is performed on the annotated data set image, which speeds up the convergence speed of the network. Increased the feature scale of YOLOv3 algorithm. The loss function of the network is optimized, CIOU is used as the positioning loss, and the positioning accuracy is improved. At the same time, the method of transfer learning is used to overcome the problem of insufficient samples. The enhanced yolov3 algorithm proposed in this paper has higher detection accuracy and shorter detection time than the standard yolov3 algorithm and SSD algorithm.
Sentiment Analysis-Based Method to Prevent Cyber Bullying
Authors: Ciaburro Giuseppe , Iannace Gino , Puyana-Romero Virginia 
Published: July 2022

AbstractCyberbullying is spreading in social networks frequented by young people. Its rapid spread is due to a series of specific preconditions due to the nature of the context within which the cyberbully finds himself operating. Anonymity, the absence of space-time limits, and the lack of responsibility of the individual are the strengths on which the actions of bullies are based. Automatically identifying acts of cyberbullying and social networks can help in setting up support policies for victims. In this study a method based on sentiment analysis is proposed with the use of recurrent neural networks for the prevention of cyberbullying acts in social networks.
Analysis and FP-Growth Algorithm Design on Discount Data of Department Store Members
Authors: Xu Jianghong , Jiang Cherry , Qu Yezun , Zhong Wenting , Gan Zhiwang 
Published: July 2022

AbstractThis paper mainly studies the discount data of department store members. The researsh shows that the total supply of discounted goods and the number of reward points issued have the most significant relationship with customer activation rate, the increase of discount rate and coverage scale would increase the activation rate of inactive members and invalid members. The increase of the score rate may have a stronger incentive effect on active members, but it has no obvious incentive effect on inactive and ineffective members. In addition, by integrating the commodity records of each purchase, and analyzing association rules, commodity combinations with associated consumption relationships are obtained, and the analysis model of commodity portfolio association rules is established. This paper is mainly based on the data of the member information, the sale water meter, the member consumption detailed list, the merchandise information table, through the data processing and analysis, rejects the abnormal data, prepares for the following processing. By analyzing the characteristics of member consumption and the difference between member and non-member consumption, we can provide marketing suggestions for the store manager FP-growth Algorithm is designed to evaluate the purchasing power of members based on their gender, length of membership, age and consumption frequency, and each parameter of the model is explained, so as to improve the management level of the shopping mall. On this basis, Suggestions for promotional activities in shopping malls are given.
New Principle of Fault Data Synchronization for Intelligent Protection Based on Wavelet Analysis
Authors: Wang Zuowei , Zhang Hong , Liu Dongchao , E. Shiping , Zhang Kanjun , Li Haitao , Li Hengxuan , Chen Zhigang 
Published: July 2022

AbstractIn order to eliminate the influence of the delay error of the sampled value in the data link on the longitudinal differential protection device, this paper proposes a protection data self-healing synchronization algorithm based on wavelet transform to calculate the moment of sudden change. First, calculate the mutation amount of the sampled data at each end in real time. When the mutation amount threshold is exceeded, it is determined that the multi-terminal system has a short-circuit fault. Then, according to the sudden change characteristics of the collected current waveform, the wavelet modulus maximum value is used to extract the fault sudden change time of each end data, based on the fault time at one terminal, the automatic compensation for the time differences between this terminal and others are realized, thus a new sampling sequence is formed. The resynchronized sampling sequences are used to calculate the differential current and braking current after fault to ensure the correct action of the protective device. Through theoretical analysis and simulations, the correctness and effectiveness of the proposed algorithm is verified; in addition, it is shown that this algorithm can improve the reliability of actions by the intelligent protection device, thus realizing protections such as multi-terminal differential, wide-area differential, etc.
Nakagami Parametric Imaging Based on the Multi-pyramid Coarse-to-Fine Bowman Iteration (MCB) Method
Authors: Li Sinan , Zhou Zhuhuang , Wu Shuicai 
Published: July 2022

AbstractNakagami-m parametric imaging has been used for imaging and detection of coagulation zone in microwave ablation. In order to improve the image smoothness and accuracy of coagulation zone detection, the multi-pyramid coarse-to-fine bowman iteration (MCB) method was proposed and compared with traditional moment-based estimator (MBE) method. Phantom simulations showed that the MCB method could obtain better image smoothness and higher accuracy in lateral target size detection than the MBE method. Experimental results of porcine liver ex vivo (n = 18) indicated that the m parameter obtained by the MCB method was more accurate than that obtained by the MBE method in detecting the coagulation zone. Nakagami-m parametric imaging based on MCB method can be used as a potential tool for microwave ablation monitoring.
The LVS parametric tadpole constraint
Authors: Gao Xin , Hebecker Arthur , Schreyer Simon , Venken Gerben 
Published: July 2022

Abstract
The large volume scenario (LVS) for de Sitter compactifications of the type IIB string is, at least in principle, well protected from various unknown corrections. The reason is that, by construction, the Calabi-Yau volume is exponentially large. However, as has recently been emphasised, in practice the most explicit models are rather on the border of parametric control. We identify and quantify parametrically what we believe to be the main issue behind this difficulty. Namely, a large volume implies a shallow AdS minimum and hence a small uplift. The latter, if it relies on an anti-D3 in a throat, requires a large negative tadpole. As our main result, we provide a simple and explicit formula for what this tadpole has to be in order to control the most dangerous corrections. The fundamental ingredients are parameters specifying the desired quality of control. We comment on the interplay between our constraint and the tadpole conjecture. We also discuss directions for future work which could lead to LVS constructions satisfying the tadpole constraint with better control, as well as further challenges that may exist for the LVS. Our formula then represents a very concrete challenge for future searches for and the understanding of relevant geometries.
How to search for mirror stars with Gaia
Authors: Howe Aaron , Setford Jack , Curtin David , Matzner Christopher D. 
Published: July 2022

Abstract
We show for the first time how to conduct a direct search for dark matter using Gaia observations. Its public astrometric data may contain the signals of mirror stars, exotic compact objects made of atomic dark matter with a tiny kinetic mixing between the dark and SM photon. Mirror stars capture small amounts of interstellar material in their cores, leading to characteristic optical/IR and X-ray emissions. We develop the detailed pipeline for conducting a mirror star search using data from Gaia and other stellar catalogues, and demonstrate our methodology by conducting a search for toy mirror stars with a simplified calculation of their optical/IR emissions over a wide range of mirror star and hidden sector parameters. We also obtain projected exclusion bounds on the abundance and properties of mirror stars if no candidates are found, demonstrating that Gaia is a new and uniquely powerful probe of atomic dark matter. Our study provides the blueprint for a realistic mirror star search that includes a more complete treatment of the captured interstellar gas in the future.
Charge-swapping Q-balls in a logarithmic potential and Affleck-Dine condensate fragmentation
Authors: Hou Si-Yuan , Saffin Paul M. , Xie Qi-Xin , Zhou Shuang-Yong 
Published: July 2022

Abstract
We study charge-swapping Q-balls, a kind of composite Q-ball where positive and negative charges co-exist and swap with time, in models with a logarithmic potential that arises naturally in supersymmetric extensions of the Standard Model. We show that charge-swapping Q-balls can be copiously generated in the Affleck-Dine fragmentation process in the early universe. We find that the charge-swapping Q-balls with the logarithmic potential are extremely stable. By performing long time, parallelized lattice simulations with absorbing boundary conditions, we find that the lifetimes of such objects with low multipoles are at least 4.6 × 105/m in 3+1D and 2.5 × 107/m in 2+1D, where m is the mass scale of the scalar field. We also chart the attractor basin of the initial conditions to form these charge-swapping Q-balls.
Structural and functional comparison of magnesium transporters throughout evolution
Authors: Franken G. A. C. , Huynen M. A. , Martínez-Cruz L. A. , Bindels R. J. M. , de Baaij J. H. F. 
Published: July 2022

AbstractMagnesium (Mg2+) is the most prevalent divalent intracellular cation. As co-factor in many enzymatic reactions, Mg2+ is essential for protein synthesis, energy production, and DNA stability. Disturbances in intracellular Mg2+ concentrations, therefore, unequivocally result in delayed cell growth and metabolic defects. To maintain physiological Mg2+ levels, all organisms rely on balanced Mg2+ influx and efflux via Mg2+ channels and transporters. This review compares the structure and the function of prokaryotic Mg2+ transporters and their eukaryotic counterparts. In prokaryotes, cellular Mg2+ homeostasis is orchestrated via the CorA, MgtA/B, MgtE, and CorB/C Mg2+ transporters. For CorA, MgtE, and CorB/C, the motifs that form the selectivity pore are conserved during evolution. These findings suggest that CNNM proteins, the vertebrate orthologues of CorB/C, also have Mg2+ transport capacity. Whereas CorA and CorB/C proteins share the gross quaternary structure and functional properties with their respective orthologues, the MgtE channel only shares the selectivity pore with SLC41 Na+/Mg2+ transporters. In eukaryotes, TRPM6 and TRPM7 Mg2+ channels provide an additional Mg2+ transport mechanism, consisting of a fusion of channel with a kinase. The unique features these TRP channels allow the integration of hormonal, cellular, and transcriptional regulatory pathways that determine their Mg2+ transport capacity. Our review demonstrates that understanding the structure and function of prokaryotic magnesiotropic proteins aids in our basic understanding of Mg2+ transport.