bluuebunny/crossref_metadata_2025_split huggingface dataset:
Data transparency and citation in the journal Gesture
Authors: Gawne Lauren , Krajcik Chelsea , Andreassen Helene N. , Berez-Kroeker Andrea L. , Kelly Barbara F. 
Published: May 2020

Abstract
Data is central to scholarly research, but the nature and location of data used is often under-reported in research
publications. Greater transparency and citation of data have positive effects for the culture of research. This article presents the results
of a survey of data citation in six years of articles published in the journal Gesture (12.1–17.2). Gesture researchers
draw on a broad range of data types, but the source and location of data are often not disclosed in publications. There is also still a
strong research focus on only a small range of the world’s languages and their linguistic diversity. Published papers rarely cite back to
the primary data, unless it is already published. We discuss both the implications of these findings and the ways that scholars in the field
of gesture studies can build a positive culture around open data.
On the reflexive-possessive markers in the Dongxiang language
Authors: Lefort Julie 
Published: May 2020

Abstract
Dongxiang is a language mainly spoken in the Autonomous District of southwest Gansu Province, People’s Republic of China. The Dongxiang nationality (東鄉族), as they are officially called, represents about 300,000 speakers. The Dongxiang language is one of the peripheral Mongolic languages spoken in the Gansu-Qinghai area, also known as the Shirongol group. These languages have been isolated from the other Mongolic languages and have been influenced by the surrounding Chinese dialects to a greater or lesser degree. They have common typological forms inherited from Middle Mongolian as well as features which have been induced by language contact. In this paper, I shall discuss the reflexive possessive markers in the Dongxiang language with a special focus on the suffix -nugvun. I shall show that the functions and use of Dongxiang reflexive possessive markers -ni and -ne are similar to those of the common Mongolic markers *-ni and *-xAn. The reflexive possessive marker -nugvun seems to be found in Dongxiang only and its origin remains unclear. In sources available from the 1980s to the 2000s, it is found associated with a restrictive number of pronouns, nouns, and idiomatic expressions and is highly grammaticalized. However, in more recent sources, it is found associated with a greater number of nouns and seems to have more semantic implications. Moreover, it is also found in a role which could be associated with that of a pronoun, and which can receive a plural and reflexive morphology. Nugvun can be used completely independently and is probably a calque of the Chinese dialect of Linxia 個家ge42 jia243
. This shows that it is most probably an innovation developed from the original suffix.
Zinc(II) tetraphenylporphyrin on Au(111) investigated by scanning tunnelling microscopy and photoemission spectroscopy measurements
Authors: De Luca Oreste , Caruso Tommaso , Grimaldi Ilenia , Policicchio Alfonso , Formoso Vincenzo , Fujii Jun , Vobornik Ivana , Pacilé Daniela , Papagno Marco , Agostino Raffaele Giuseppe 
Published: May 2020

Abstract
Porphyrins are a versatile class of molecules, which have attracted attention over the years due to their electronic, optical and biological properties. Self-assembled monolayers of porphyrins were widely studied on metal surfaces in order to understand the supramolecular organization of these molecules, which is a crucial step towards the development of devices starting from the bottom-up approach. This perspective could lead to tailor the interfacial properties of the surface, depending on the specific interaction between the molecular assembly and the metal surface. In this study, we revisit the investigation of the assembly of zinc-tetraphenylporphyrins on Au(111) in order to explore the adsorption of the molecular network on the noble metal substrate. The combined analysis of scanning tunneling microscopy (STM) imaging and core levels photoemission spectroscopy measurements support a peculiar arrangement of the ZnTPP molecular network, with Zn atoms occupying the bridge sites of the Au surface atoms. Furthermore, we prove that, at few-layers coverage, the interaction between the deposited layers allows a relevant molecular mobility of the adlayer, as observed by STM and supported by core levels photoemission analysis.
Skin-inspired electronics: emerging semiconductor devices and systems
Authors: Ma Zhong , Kong Desheng , Pan Lijia , Bao Zhenan 
Published: May 2020

Abstract
Current electronics are driven by advanced microfabrication for fast and efficient information processing. In spite of high performance, these wafer-based devices are rigid, non-degradable, and unable to autonomous repair. Skin-inspired electronics have emerged as a new class of devices and systems for next-generation flexible and wearable electronics. The technology gains inspiration from the structures, properties, and sensing mechanisms of the skin, which may find a broad range of applications in cutting-edge fields such as healthcare monitoring, human-machine interface, and soft robotics/prostheses. Practical demands have fueled the development of electronic materials with skin-like properties in terms of stretchability, self-healing capability, and biodegradability. These materials provide the basis for functional sensors with innovative and biomimetic designs. Further system-level integrations and optimizations enable new forms of electronics for real-world applications. This review summarizes recent advancements in this active area and speculates on future directions.
Flexible inorganic oxide thin-film electronics enabled by advanced strategies
Authors: Zhang Tianyao , Yao Guang , Pan Taisong , Lu Qingjian , Lin Yuan 
Published: May 2020

Abstract
With the advent of human-friendly intelligent life, as well as increasing demands for natural and seamless human-machine interactions, flexibility and wearability are among the inevitable development trends for electronic devices in the future. Due to the advantages of rich physicochemical properties, flexible and stretchable inorganic oxide thin-film electronics play an increasingly important role in the emerging and exciting flexible electronic field, and they will act as a critical player in next-generation electronics. However, a stable strategy to render flexibility while maintaining excellent performance of oxide thin films is the most demanding and challenging problem, both for academic and industrial communities. Thus, this review focuses on the latest advanced strategies to achieve flexible inorganic oxide thin-film electronics. This review emphasizes the physical transferring strategies that are based on mechanical peeling and the chemical transferring strategies that are based on sacrificial layer etching. Finally, this review evaluates and summarizes the merits and demerits of these strategies toward actual applications, concluding with a future perspective into the challenges and opportunities for the next-generation of flexible inorganic oxide thin-film electronics.
A review of flexible halide perovskite solar cells towards scalable manufacturing and environmental sustainability
Authors: Davis Melissa , Yu Zhibin 
Published: May 2020

Abstract
The perovskite material has many superb qualities which allow for its remarkable success as solar cells; flexibility is an emerging field for this technology. To encourage commercialization of flexible perovskite solar cells, two main areas are of focus: mitigation of stability issues and adaptation of production to flexible substrates. An in-depth report on stability concerns and solutions follows with a focus on Ruddlesden-Popper perovskites. Roll to roll processing of devices is desired to further reduce costs, so a review of flexible devices and their production methods follows as well. The final focus is on the sustainability of perovskite solar cell devices where recycling methods and holistic environmental impacts of devices are done.
Numerical and experimental analysis of the 3D printed multi-material ankle-foot orthosis
Authors: Otepbergenov Temirlan , Smagulov Zhalgas , Abilgaziyev Anuar , Kurokawa Syuhei , Ali Md. Hazrat 
Published: May 2020

Abstract
The application of 3D printing in medicine is the major area to concern in the nearest future. Namely, it is convenient to additively manufacture the Ankle-Foot Orthosis (AFO) by fused-deposition modeling 3D printer. AFO is the device, used in medicine, to help the patients rehabilitate from the foot drop disease. The shape of the AFO may vary depending on the leg and foot specifications of the patient. In this paper, three models of the AFO were designed to analyze both numerically and experimentally, those are fracture propagation, stress distribution, and deformation. The regions with the highest stress concentration were altered with the Nylon 12, and this contributed to stress reduction. Three different gait instances were considered for the numerical simulations FEA software. Then, the simplest model to prototype and its modified versions were tested by the compression machine, and the results were compared with the numerical ones. This work demonstrated the significance of the optimization of the multi-material 3D printed AFO’s performance and comfort for patients.
Research on Trajectory Prediction Algorithm for Low-altitude Emergency Rescue Aircraft
Authors: Bin Hu , Fang Pan , Xiaoxia Qian 
Published: May 2020

Abstract
With the rapid development of general aviation, this aviation solution is widely used in emergencies such as natural disasters, major accidents, and social security problems because of its fast start-up speed, high rescue efficiency, and less restrictions. In this paper, state-dependent mode transition hybrid estimation (SDTHE) is combined with the improved intent inference algorithm (IIIA) to obtain a more accurate trajectory prediction algorithm. The algorithm overcomes the shortcoming of the hypothesis that the likelihood function is zero in the interactive multiple model algorithm (IMM), and considers the real-time motion state and mode of the aircraft, so that the final prediction result is more accurate.
Current Status of Research on Space Emergency Launch
Authors: Zhao Long , Xin Chao-Jun , Shi Mei-Ling , Yang Chen , Wang Huai-Peng 
Published: May 2020

Abstract
The realization of space rapid emergency launch needs to be developed from rapid response spacecraft, rapid response vehicle and space rapid launch infrastructure, so as to constitute the organic whole of “trinity” and give full play to the effectiveness of the system. Rapid response vehicle and space rapid launch infrastructure are the mainly two aspects that closely related to the construction of space rapid emergency launch force. This article mainly focuses on the research and analysis of the development status of foreign space emergency launch force from the above two aspects.
Intelligent Fault Diagnosis of Satellite Communication Antenna via a Novel Meta-learning Network Combining with Attention Mechanism
Authors: Chang Y H , Chen J L , He S L 
Published: May 2020

Abstract
Shipborne satellite communication antenna which is used for remote control plays an irreplaceable role in ships, it is necessary to monitor its operation state. However, obtaining sufficient fault information in mass monitoring data is particularly difficult, which greatly degrades performance of existing intelligent algorithms. In this paper, a novel meta-learning network is proposed to realize state recognition of shipborne antenna under small samples prerequisite. The network is constructed to improve generalization even though inputs collected under different operating conditions. Meta-learning network consists of sampler, feature extractor, auxiliary classifier and discriminator. It trains an adaptive pseudo-distance to evaluate the degree of correlation between different data, then realize classification task. Feasibility and effectiveness of the network are verified by three bearing datasets. Results show that the proposed method uses few samples to successfully classify mechanical data of shipborne antenna even with different rotating speed and random noise.
Level Assessment Criterion and Method for C4ISR Systems Interoperability
Authors: Shuang-ling Wang 
Published: May 2020

Abstract
In this paper, the concept of C4ISR systems interoperability is analyzed and the difference compared with traditional system interoperability is presented. The influencing factors of C4ISR system interoperability is analyzed from the overall framework of the US military global information grid. Six attributes including structure, application, facility, security, operation and maintenance, and data are selected. The selection process of evaluation attributes is described. Based on the enhanced interoperability maturity mode, the C4ISR system level attribute model is given by combing with the development trend of C4ISR system technology system. The grade of maturity and an evaluation index system for C4ISR systems interoperability are built and the index level reference model is designed. Combining qualitative assessment with quantitative assessment, an index synthesis criterion based on the mapping model and the corresponding interoperability level evaluation method for C4ISR systems are proposed to provide a specific method model for measuring the interoperability level of the C4ISR system.
Research on Fault Diagnosis Training System Based on Virtual Space Launch Site
Authors: Liu Yuan , Song Zuowei , Gao Peng , Liu Jian 
Published: May 2020

Abstract
Aiming at the problem that the ground equipment system of space launch range is complex and it is difficult to implement real fault diagnosis training, this paper analyses the requirements of fault diagnosis training, puts forward a design scheme of fault diagnosis system based on virtual range, and expounds the basic workflow of virtual fault diagnosis training system. The fault tree and expert system are combined to complete the fault diagnosis training process design. The real-time scheduling method of virtual scene based on multi-threaded entrance is used to load and render the virtual scene in real time according to the movement trend of the virtual avatar, which ensures the fluency of interoperability in terms of function and performance, so as to achieve the purpose of improving the training effect.
Unsupervised Spatial-Temporal Model Based on Region Alignment for Person Re-identification
Authors: Li Wei , Qi Meibin , Yang Ning , Zhou Guowu , Yang Yubing 
Published: May 2020

Abstract
Person re-identification(re-ID) refers to find a specific pedestrian across disjoint camera views. Recently, person re-ID rely on supervised learning to train network by labeled information. Resulting poor generalization in real-world environment because of the lack of pedestrian labels. At the same time, person images are easily affected by background, illumination and pose variations. And these factors make it difficult to extract discriminative features to distinguish different pedestrians. In order to resolve this research problem, we proposing an unsupervised learning alignment method called Region Alignment of Spatial-Temporal Fusion(RASTF) which joints global features with local aligned features to get more discriminative features. Local features are aligned by calculating the shortest distances between regions. Our proposed framework integrates a novel region alignment method in unsupervised network and the experiment results indicate that can outperform the state-of-the-art unsupervised methods.
Deep-Shallow Occlusion Parallelism Network for Person Re-Identification
Authors: Wang Qian , Qi Meibin , Jin Kaiyuan , Jiang Jianguo 
Published: May 2020

Abstract
In recent years, the progress of person re-identification has advanced significantly, but person in real scenes are often obscured by various objects. This problem has been ignored or solved based on an incomplete assumption by the previous person re-ID methods. This paper proposes a new training mechanism, Deep-Shallow Occlusion Parallelism network, which responds to multi-scale occlusion in a more universal case and alleviate the negative impact of occlusion effectively. Specifically, the proposed consists of shallow occlusion and deep occlusion, to which are applied with shielding simulation to enhance the difficulty of training samples. What’s more, channel-spatial attention is applied to various positions in each branch to concentrate on discriminative features afteqr occlusion. In the end, the weighted fusion of the two branches not only informs the network of the information of changes before and after occlusion, but also complements the deep and shallow information effectively. It makes the network more robust. This method has excellent performance on the three basic re-ID datasets and the largest partial re-ID dataset, with the state-of-the-art reached to or even surpassed.
Innovative Research on the Improvement of Visual Quality of Data Journalism in China: Visual Language and Interaction Design
Authors: Chen Zhirui , Guo Wenchen 
Published: May 2020

Abstract
As the last node of data journalism creation, visual design plays a crucial role in the transmission of data information. Exploring the routes to improve the quality of data journalism at the visual language and interaction design, this paper analyzes the works won data journalism awards and produced by well-known media from 2012 to 2019, and discusses the misunderstandings and shortcomings in the current data journalism visualization practice. This paper presents the improvement routes of data mapping, symbolic expression, interaction level, and interactive narration.
An Improved Multi-Level Set C-V Model for Grading of Korean Pine Seeds
Authors: Qiu Xunchao , Yuan Jianqing , Li Lei 
Published: May 2020

Abstract
An improved multi-level set C-V model for non-destructive grading of Korean pine seeds is presented in this paper. On the basis of improved Ostu and rough segmentation results of expansion operation, the improved C-V model is used to extract the target contour of Korean pine seeds; the characteristic parameters of fruit length and maximum transverse diameter are extracted by mathematical morphology method, and polynomial fitting is carried out with the actual measured values to construct a mathematical model with better quality; according to the extracted characteristic parameters, a comprehensive evaluation and grading standard for Korean pine seeds is established. The experimental results show that this method can achieve simultaneous classification of multiple Korean pine seeds, and the average accuracy of classification can be up to 97.2%.
Object Detection in Optical Remote Sensing Images Based on Residual Network
Authors: Li Da , Gong Shaoxing , Liu Dong 
Published: May 2020

Abstract
Conventional object detection algorithm based on deep learning only make use of deep feature which would become indiscriminative for small target in optical remote sensing images when the network deepens. In this paper, a multi-layer feature fusion method based on residual learning is proposed, which combine the shallow feature with deep feature to classify object comprehensively. First, a ResNet50 backbone network is constructed to extract feature from multiple layers. Then, the scales of feature at different layers are unified through RoI Pooling layer to screen region proposals and be classified through the SVM classifier. Comparative experiments are conducted on UCAS_AOD dataset released by UCAS and the result shows that our model achieved relatively good performance with 0.8802 and 0.9120 f1 score in car and airplane categories respectively.
Long-Wave Signal Detection Method Based on Limit Threshold Chaotic Oscillator
Authors: Zhang Yang , Rui Guo-sheng , Liu Yun-fei , Liu Lin-fang 
Published: May 2020

Abstract
The transmission of long-wave signal in lightning is easily weakened to a very low amplitude, and affected by non-stationary time-varying strong noise, which makes the detection signal become extremely difficult, and it is difficult to achieve the extraction of useful information. As the main noise source of interference long wave signal, this paper studies the chaos detection method of lightning noise, proposes the detection method of long wave signal based on the limit threshold chaotic oscillator, combines the Euler equation, the main frequency ratio phase change discrimination algorithm and other technologies, based on the non-linear signal processing technology, completes the chaos detection of long wave weak signal by simulating the noise environment in the laboratory, its reliability is verified by theoretical experiments, which can provide an important basis for the development of long-wave reception technology.
Research on the Intelligent Recognition System of Printing Roller Surface Defects Based on Machine Vision
Authors: Liang Chen , Hanxv Sun , Qingxuan Jia , Yanheng Zhang , Shaozhong Cao , Wei’ Zhao , Tao Yu 
Published: May 2020

Abstract
The printing machine’s sleeves installation operation is a typical peg-in-hole assembly problem. The printing machine’s sleeves are usually heavy, and the precision requirement of fit is high. Therefore it is hard to fit them together, and the assembly efficiency is low. What’s more the assembly tasks may make great damage to the worker who assembles it. To solve these problems, a Gough-Stewart parallel peg-in-hole assembly robot with high precision is designed. The robot has a stereoscopic laser measurement system to obtain position and speed information to realize closed-loop workspace control of the robot. The stereoscopic laser measurement system can also ease the impact in the assembly process. The robot has a passive flexibility wrist to solve the jamming question. The assembly parallel robot is designed. The kinematics model of the stereoscopic laser measurement system and the dynamic model of the Gough-Stewart parallel robot are built. A sliding mode controller is designed for the control of this robot and the parameters of the controller are optimized. The validity of the system dynamic model and stability of the sliding mode controller is proved by Matlab simulation results. Gough-Stewart Parallel Robot’s application range could be widen by the presented work.
Research on Diagnosis of Dermatology Based on Deep Residual Neural Network
Authors: Wang Jiayuan , Wang Weiye , Tian Tian 
Published: May 2020

Abstract
The methods of dermatological clinical examination are mainly skin images, including dermoscopy. Residual neural network (ResNet) can predict diseases according to dermoscopy images and provide effective proposals for doctors. Based on the ResNet model, this article migrated the pre-trained model on ImageNet to simulation experiment, and used the Focal Loss function to solve the problem of experimental sample imbalance, including but not limited to operations such as flip, rotation, scaling, and loss function replacement, thereby improving network performance. The experimental results show that the model trained by our method can reach completely correct when it classified a small number of samples. Our model can reach accuracy rate of 90.08%, recall rate of 88.44%, and F1 score of 85.25%. Compared with the model with unmodified loss function at the same depth, our model has respectively improved by 1.3%, 4.62%, and 3.58% in the above three aspects, which indicates that our method is effective in predicting rare diseases, and in predicting common diseases the accuracy rate also achieves good results.